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FACULTY OF NATURAL SCIENCES
DIVISION OF CELL AND MOLECULAR BIOLOGY
Influence of Human Gut Microbiota on the
Metabolic Fate of Glucosinolates
Vijitra Luang-In
SUBMITTED FOR THE DEGREE OF DOCTOR OF PHILOSOPHY
MARCH 2013
2
ABSTRACT Glucosinolates (GSLs) are secondary metabolites predominantly found in
cruciferous vegetables such as broccoli, brussel sprout, cabbage and cauliflower which
upon chopping and chewing will release the indigenous plant myrosinase enzyme that
catalyzes the hydrolysis of GSLs. This hydrolysis releases a range of breakdown products
including isothiocyanates (ITCs), which have been implicated in the cancer-protective
effects of cruciferous vegetables. Certain human gut bacteria are able to metabolize GSLs
and produce ITCs for human health benefits. In this work, six GSL-metabolizing bacterial
strains were isolated from human faecal sample and identified. Most bacteria were
capable of producing both nitriles (NITs) and ITCs from the metabolism of GSLs however
Enterococcus sp. C213 and Enterococcus faecium KT4S13 produced only NITs.
Enterococcus casseliflavus NCCP-53, Escherichia coli O83:H1 NRG 857C and Lactobacillus
agilis R16 were able to metabolize different types (allyl, aromatic, methylthioalkyl,
methylsulfinylalkyl and indolyl) of GSLs differently over 24 h of in vitro anaerobic
fermentations. For all GSLs, ITC production seemed to peak between 4 and 8 h of
incubation and then declined due to the inherent instability of ITCs in culture broths and
buffers. In contrast, NIT productions gradually increased over time and remained relatively
constant. The total percentage products from each GSL metabolism in all three bacteria
never reached 100%. Interestingly, E. coli O83:H1 NRG 857C produced methylthioalkyl
ITCs and NITs from methylsulfinylalkyl GSLs while E. casseliflavus NCCP-53 produced only
methylsulfinylalkyl ITCs from the same GSLs. This difference was due to reductase activity
in E. coli O83:H1 NRG 857C intact cells and cell-free extracts that biotransforms the
sulfoxide groups of methylsulfinylalkyl GSLs to the sulfide groups. The reductase enzyme is
yet to be identified at the gene and protein level, however it has been characterized using
cell-free extracts in this work. This reductase is inducible by GSLs, oxygen-independent
and requires Mg2+ ion and NADP(H) as co-factors for its activity with optimum pH and
temperature at pH 7.0 and 37˚C, respectively. Arylsulfatase activity was also detected in
this bacterium. The corresponding recombinant SUL2 enzyme (57 kDa) of E. coli O83:H1
NRG 857C expressed in BL21(DE3) exhibited arylsulfatase activity by desulfating synthetic
p-nitrocatachol sulfate substrate with optimum pH and temperature at pH 6.0 and 30˚C,
respectively. In addition, GSL-sulfatase activity was detected in crude extracts by being
3
able to desulfate different intact GSLs to produce desulfo-glucosinolates (DS-GSLs) with
less efficiency in comparison with the commercially available snail sulfatase from Helix
pomatia. The catalytic efficiency of recombinant SUL2 enzyme for GSLs in descending
order is as follows; sinigrin > glucoerucin > gluconasturtiin > glucoiberin. The DS-GSLs
(except DS-glucoraphanin) then act as substrates for the recombinant GH3 enzyme
defived from E. casseliflavus NCCP-53 to produce the corresponding NIT products in NB
broths and the buffer with the presence of 5 mM Fe2+ ions. This enzyme (79 kDa) showed
β-O-glucosidase activity for p-nitrophenyl β-D-glucopyranoside with optimum pH and
temperature at pH 7.0 and 37˚C, respectively. NIT productions only occurred from the
metabolism of intact GSLs in bacterial culture broths, but not in the buffers unless 5 mM
Fe2+ ions are present as co-factors. Putative bacterial GSL-degrading enzymes responsible
for ITC and NIT productions from GSL metabolisms are inducible by GSL in resting cells
experiments. By using two-dimensional gel electrophoresis (2-DE) and liquid
chromatography mass spectrometry (LC-MS/MS) for the comparative analysis between
proteins obtained from cultures of L. agilis R16 and E. coli O83:H1 NRG 857C with and
without GSL supplementation, upregulated/distinct proteins that may be involved in the
metabolism of GSLs by these bacteria were identified. These proteins belong to (sugar)
transport system, carbohydrate metabolism especially kinases and oxidoreduction process.
To date, bacterial GSL-degrading enzyme is yet to be identified.
4
ACKNOWLEDGEMENTS
Firstly, I would like to thank my primary supervisor Dr. John Rossiter for giving me
such an interesting PhD project. His kindness, guidance and consistent support have
always made me feel very fortunate to be under his supervision. Secondly, I would like to
thank my co-supervisor Prof. Martin Buck for his constructive criticism and
encouragement. Thirdly, I would like to thank my collaborators, Prof. Richard Mithen and
Dr. Arjan Narbad at the Institute of Food Research (IFR, Norwich) for their kind support,
advice and stimulating discussion for the progress of my work.
I also want to thank the late Dr. Judit Nagy for guiding me through proteomics
materials, Dr. Alex Jones (Sainsbury’s laboratory, Norwich) and Mr. Mark Bennette for
advice on LC-MS analysis, Dr. Ellen James for teaching me the dark art i.e. PCR and
molecular cloning, Dr. Nan Zhang for assisting me with protein purification techniques and
for some dirty-joke entertainment and Dr. Carmen Naneu-Palop for providing me with her
fecal sample as a source of human gut bacteria to study from and that gave rise to my new
nickname “Vinny the Poo’’. I want to give a massive thank you to all the past and present
members of the JR group who helped me on my experiments and lifted my spirit up during
some difficult times during my PhD study.
I am blessed to have all wonderful people entering my life during my 10-year stay
in the UK. This certainly has made my brief stay as a human being an incredible journey.
Friends have made me a better person. Moreover, I would not be where I am today
without my beloved parents who have been devoted their lives to get me the best
education, the best well-being and always support me on whatever I am determined to do.
I feel utmost grateful to them for all this lifetime. Above all, I’d pay my highest respect to
the timeless teachings of the Lord Buddha which keep me sane and shine the light on me
during the darkest hours in my life. I will continue to devote my life to follow the Buddha’s
disciplines till the end of time.
5
DECLARATION OF AUTHORSHIP
I certify that this thesis entitled “Influence of Human Gut Microbiota on the
Metabolic Fate of Glucosinolates” is written entirely by myself, and that the research to
which it refers to is my own. Any ideas or quotations from the studies by other people,
which were published or otherwise, are fully acknowledged in accordance with the
standard referencing practices of the discipline.
Vijitra Luang-In
6
TABLE OF CONTENTS
CONTENT PAGE
ABSTRACT 2
ACKNOWLEDGEMENTS 4
DECLARATION OF AUTHORSHIP 5
TABLE OF CONTENTS 6
LIST OF FIGURES 14
LIST OF TABLES 21
ABBREVIATIONS 25
ABBREVIATIONS FOR AMINO ACIDS 32
Chapter 1 Introduction
1.1 GSL structure, properties, occurrence and biological roles in plants 33
1.2 Biosynthesis of GSLs 39
1.3 Degradation of GSL and its degradation products 42
1.4 Biochemistry of myrosinases 44
1.5 Specifier proteins 46
1.6 Importance of ITCs to human health 47
1.6.1 Cancer Chemoprevention 47
1.6.2 Prevention of diseases 55
1.6.3 Genotoxicity of ITCs 56
1.7 Bioavailability of GSL degradation products in humans 57
1.8 Human gut microbiota 62
1.9 Cruciferous vegetables can alter human gut microbiota communities 65
1.10 Hypotheses 66
1.11 Objectives 66
Chapter 2 Metabolism of GSLs and DS-GSLs by human gut microbiota
2.1. Introduction 67
7
2.1.1 GSL degradation by human gut microbiota 67
2.1.2 Metabolic diversity of the intestinal microbiota 68
2.1.3 Characterization of human gut microbiota 70
2.1.3.1 Enrichment culture technique 72
2.1.3.2 16S rRNA gene analysis 73
2.1.3.3 Polymerase Chain Reaction (PCR) 74
2.1.4 Analytical methods for GSLs and their degradation products 74
2.1.5 Hypotheses 78
2.1.6 Objectives 79
2.2 Materials and Methods 80
2.2.1 Preparation of GSL substrates 80
2.2.2 Preparation of sulfatase 82
2.2.3 Desulfation of GSLs 82
2.2.4 HPLC analytic conditions for DS-GSLs detection 83
2.2.5 Preparation of DS-GSL substrates 84
2.2.6 Authentic ITC and NIT standards 85
2.2.7 Isolation of GSL-degrading bacteria 85
2.2.8 PCR amplification and identification of isolates 86
2.2.9 Culturing conditions and sample collection 87
for HPLC and GC-MS analyzes
2.2.10 Sample preparation for HPLC analysis and 88
quantification of GSL from HPLC results
2.2.11 Sample preparation for GC-MS analysis 88
2.2.12 GC-MS analytical conditions for the detection of GSL 89
degradation products
2.2.13 Determination of percentage product 94
2.2.14 Determination of stability and solubility of ITC/NIT standards 94
2.2.15 Resting cell experiments 94
2.2.16 Determination of metal ion dependency on 95
NIT production from GSL metabolism in bacterial resting cells
2.2.17 Cell-free extract experiments 96
8
2.2.18 Determination of co-factor dependancy for reductase 96
activity in cell-free extracts
2.2.19 Determination of reductase activity in cell-free 97
extracts in the conversion of sulforaphane to erucin
2.2.20 Protein quantification 98
2.2.21 Denaturing sodium dodecyl sulfate polyacrylamide 99
gel electrophoresis (SDS-PAGE)
2.2.22 Native gel electrophoresis 100
2.2.23 Statistical analysis 100
2.3 Results 101
2.3.1 Screening for GSL-metabolising human gut bacteria 101
2.3.2 Isolation and purification of GSL substrates 102
2.3.3 Time-course degradation product profiles of intact 104
GSLs in individual bacterial fermentations
2.3.4 Stability of ITC/NIT degradation products 122
2.3.5 Time-course degradation product profiles of DS-GSLs 128
by individual bacterial fermentation
2.3.6 Resting cell experiments 133
2.3.7 ITC and NIT production by bacterial resting cells 135
in the buffer and the media
2.3.8 Cell-free extract experiments from E. coli O83:H1 NRG 857C 140
2.3.9 Determination of GSL-degrading enzyme activity from bacterial 140
whole cell lystaes on the native gels
2.3.10 Sulfoxide reduction of glucoiberin and glucoraphanin 142
by reductase activity in E. coli O83:H1 NRG 857C
2.3.11 Mg2+ - and NAD(P)H- dependent reductase activity 150
and its optimal pH and temperature
2.4 Summary of key findings 154
2.5 Discussion 155
2.5.1 Bacterial GSL-degrading activity 155
2.5.2 Bacterial reductase activity 161
9
Chapter 3: Forward proteomics approach to identify bacterial proteins potentially
involved in the metabolism of GSLs
3.1 Introduction 164
3.1.1 Forward proteomics 164
3.1.2 Two-dimensional electrophoresis (2-DE) 167
3.1.3 Work-flow of gel-based strategy 168
3.1.3.1 Protein preparation 168
3.1.3.2 Protein separation 170
3.1.3.3 Gel analysis, spot detection and quantification 171
3.1.3.4 Spot excision and digestion 171
3.1.3.5 Protein identification by mass spectrometry 171
3.1.4 Applications of 2-DE in bacterial proteomics 172
3.1.5 Hypotheses 174
3.1.6 Objectives 175
3.2 Materials and Methods 176
3.2.1 Sinigrin supplementation in media and bacterial cell collection 176
3.2.2 Cell lysis and protein extraction 176
3.2.3 Protein quantification 177
3.2.4 Two-dimensional polyacrylamide gel electrophoresis (2D-PAGE) 178
3.2.5 Image acquisition and analysis 180
3.2.6 Estimation of pI and molecular weight (Mw) of the proteins 181
3.2.7 In-gel tryptic digestion 181
3.2.8 LC-MS/MS analysis 183
3.2.9 Database searching and protein identification 184
3.3 Results 185
3.3.1 Optimum GSL concentration to induce bacterial 185
myrosinase expression
3.3.2 Optimization of protein sample preparation for 2-DE 187
3.3.3 Comparative analysis of 2-DE maps of proteins isolated from 191
cells grown on media with and without sinigrin supplementation
3.3.4 LC-MS/MS analysis and protein identification 195
10
3.4 Discussion 200
Chapter 4: Reverse proteomics approach to identify bacterial proteins potentially involved in the metabolism of GSLs 4.1 Introduction 205
4.1.1 Reverse proteomics 207
4.1.1.1 Molecular cloning 208
4.1.1.2 Recombinant protein expression 211
4.1.1.3 Enzyme activity and assay 212
4.1.2 Hypotheses 213
4.1.3 Objectives 214
4.2 Materials and Methods 215
4.2.1 Sequence alignment and bioinformatic analysis 215
4.2.2 Genomic DNA extraction 215
4.2.3 Primers 216
4.2.4 Bacterial strains and plasmids 216
4.2.5 Polymerase chain reaction (PCR) 217
4.2.6 PCR product purification 218
4.2.7 Ligation 219
4.2.8 Preparation of competent cells with ligation mixture 220
4.2.9 Preparation of competent cells 220
4.2.10 Selection of transformants 220
4.2.11 Colony PCR experiment 221
4.2.12 Restriction enzyme digestion 222
4.2.13 Agarose gel electrophoresis 222
4.2.14 Plasmid extraction 223
4.2.15 DNA sequencing and sequence analysis 223
4.2.16 Recombinant protein expression and purification 223
4.2.17 SDS-PAGE analysis 224
4.2.18 Desalting recombinant enzymes 225
4.2.19 GOD-PERID assay 225
4.2.20 Substrates used in GOD-PERID assay 227
11
4.2.21 β-O-glucosidase activity assay 228
4.2.22 Arylsulfatase activity assay 230
4.3 Results 232
4.3.1 BLAST searches and sequence analysis of putative bacterial 232
myrosinases/sulfatase
4.3.2 Cloning of putative bacterial GSL-degrading enzyme/sulfatases 239
4.3.3 Recombinant protein expressions by IPTG induction 242
4.3.4 Enzyme activity assays 243
4.3.4.1 Myrosinase activity using GOD-PERID assay 243
4.3.4.2 β-O-glucosidase activity assay 246
4.3.4.3 Arylsulfatase activity assay 247
4.4. Discussion 248
Chapter 5: Characterization of the recombinant SUL2 enzyme from E. coli O83:H1 NRG
857C and the recombinant GH3 enzyme from E. casseliflavus NCCP-53
5.1 Introduction 250
5.1.1 Sulfatases in nature 251
5.1.2 Bacterial sulftases 253
5.1.3 The GH1 myrosinases 256
5.1.4 The GH3 β-glucosidases 261
5.1.5 Desulfation of intact GSLs and NIT production from DS-GSLs 263
5.1.6 Protein purification techniques 265
5.1.6.1 Desalting and buffer exchange 265
5.1.6.2 Ultrafiltration 265
5.1.6.3 Ion exchange chromatography 266
5.1.6.4 Ni2+-affinity Chromatography 269
5.1.7 Hypotheses 269
5.1.8 Objectives 270
5.2 Materials and Methods 271
5.2.1 Bioinformatics tools 271
5.2.2 Inducibility of a native SUL2 enzyme of E. coli O83:H1 NRG 857C 271
12
5.2.3 Reverse transcriptase polymerase chain reaction (RT-PCR) 271
5.2.4 Purification of recombinant enzymes 272
5.2.4.1 Affinity column chromatography 273
5.2.4.2 Ion-exchange column chromatography 274
5.2.5 Determination of pH and temperature optima 274
5.2.6 Enzyme activities measurements 275
5.2.6.1 Enzyme activities of the recombinant SUL2 enzyme 275
for intact GSLs determined by a discontinuous assay
using HPLC analysis
5.2.6.2 Enzyme activities of the recombinant SUL2 enzyme 276
for pNCS determined by a discontinuous assay
using a spectrophotometric method
5.2.7 Effects of various compounds on arylsulfatase activity of 276
the recombinant SUL enzyme
5.2.8 DS-GSLs as substrates for the recombinant GH3 enzyme 277
5.2.9 Intact GSL as substrates in a reaction containing both 277
the recombinant SUL2 enzyme and the recombinant GH3 enzyme
5.3 Results 278
5.3.1 Bioinformatics results of a native SUL2 enzyme of 278
E. coli O83:H1 NRG 857C
5.3.2 Inducibility of a native SUL2 enzyme of E. coli O83:H1 NRG 857C 281
5.3.3 Expression and purification of the recombinant SUL2 enzyme 283
5.3.4 Temperature and pH optima of the recombinant SUL2 enzyme 286
5.3.5 Desulfation of intact GSLs by the recombinant SUL2 enzyme 287
5.3.6 Enzyme activities of the recombinant SUL2 enzyme 291
5.3.7 Effects of compounds on arylsulfatase activity of the recombinant 295
SUL2 enzyme
5.3.8 Purification of the recombinant GH3 enzyme from 296
E. casseliflavus NCCP-53
5.3.9 Temperature and pH optima of the recombinant GH3 enzyme 297
5.3.10 Effects of metal ions on β-O-glucosidase activity of the 297
recombinant GH3 enzyme
13
5.3.11 NIT production from DS-GSLs by the recombinant GH3 enzyme 298
5.3.12 NIT production from intact GSLs by sequential action of 300
the recombinant SUL2 enzyme and the recombinant GH3 enzyme
5.4 Summary of key findings 303
5.5 Discussion 303
Chapter 6 General discussion
6.1 Summary of findings 309
6.2 Future work 315
6.2.1 Identification of other GSL degradation metabolites from 315
GSL metabolism
6.2.2 Further search for the putative bacterial GSL-degrading enzyme 315
from other bacteria
6.2.3 Determination of whether GSL-6-P is a substrate for bacterial 317
myrosinase in vitro
6.2.4 Purification of bacterial reductase 317
6.3 Conclusion 318
REFERENCES 319
APPENDIX 353
Appendix I 353
Appendix II 354
Appendix III 358
Appendix IV 358
14
LIST OF FIGURES
FIGURE PAGE
Figure 1.1 Structure of GSL 34
Figure 1.2 Typical HPLC chromatogram of GSL profile in 38
Sweetheart cabbage
Figure 1.3 Biosynthesis of GSLs 41
Figure 1.4 GSL degradation under different conditions 43
Figure 1.5 Mechanisms of action of ITCs in the modulation of 50
signalling pathways involved in cancer chemoprevention
Figure 1.6 ITCs modulate a large and diverse group of proteins 51
Figure 1.7 Expected metabolic fate of glucoraphanin and AITC following 59
ingestion of cooked broccoli (Brassica oleracea var. italica)
and mustard (Sinapis alba) respectively by human volunteers
Figure 1.8 The intestine's impact on health 63
Figure 2.1 ITC standard curves from GC-MS analysis 92
Figure 2.2 NIT standard curves from GC-MS analysis 93
Figure 2.3 Representative protein calibration curve 98
Figure 2.4 HPLC chromatograms of GSL substrates used in this work 104
Figure 2.5 Growth curves and pH values of bacterial cultures incubated 108
with individual GSLs anaerobically at 37˚C over a time course
Figure 2.6 Time-course degradation product profiles of bacterial cultures 111
anaerobically incubated with individual GSLs at 37˚C
Figure 2.7 GC-MS chromatograms of degradation products of different GSLs 114
Figure 2.8 Fingerprint fragment ions of GSL degradation products 115
generated by GC-MS analysis
Figure 2.9 GC-MS chromatograms of ITC degradation products from 116
glucoiberin and glucoraphanin metabolized by E. casseliflavus
NCCP-53 over a time course
Figure 2.10 GC-MS chromatograms of ITC/NIT degradation production 117
from glucoiberin and glucoraphanin metabolized by E. coli
15
O83:H1 NRG 857C over a time course
Figure 2.11 HPLC chromatograms of bacterial degradation 119
of glucobrassicin over a time course
Figure 2.12 Stability of 1 mM ITC/NIT standards in NB broths with/without 124
E. coli O83:H1 NRG 857C cells over a time course
Figure 2.13 Solubility of various concentrations of ITC standards 126
in distilled water
Figure 2.14 Stability of 1 mM ITC standards in various buffers without 127
E. coli O83:H1 NRG 857C cells over a time course
Figure 2.15 GC-MS chromatograms of degradation products of DS-GSLs 130
metabolized by individual three bacteria
Figure 2.16 NIT productions from DS-GSLs metabolized by individual 132
bacteria over a time course
Figure 2.17 GC-MS chromatograms of different degradation products 135
of gluconasturtiin or DS-gluconasturtiin metabolized by E. coli
O83:H1 NRG 857C induced resting cells in different incubation
conditions
Figure 2.18 Effect of the addition of metal ions on PITC/PNIT production 137
From the metabolism of gluconasturtiin in E. coli O83:H1
NRG 857C induced resting cells
Figure 2.19 GC-MS chromatograms of degradation products from 138
gluconasturtiin metabolism in E. coli O83:H1 NRG 857C
resting cells upon addition of metal ions in 0.1 M citrate
phosphate buffer pH 7.0
Figure 2.20 SDS-PAGE analysis of E. coli O83:H1 NRG 857C proteins 141
Figure 2.21 Native gel electrophoresis for GSL-degrading activity test 142
Figure 2.22 Hypothetic scheme of the putative bacterial reductase 143 in E. coli O83:H1 NRG 857C cells. A similar scheme is thought to occur in the metabolism of glucoiberin in these two bacteria. EC, E. casseliflavus NCCP-53; ECO, E. coli O83:H1 NRG 857C.
16
Figure 2.23 Reduction bioconversion of glucoiberin/glucoraphanin 144
to glucoiberverin/glucoerucin by E. coli O83:H1 NRG 857C
intact cells over a time course
Figure 2.24 HPLC chromatograms of methylsulfinylalkyl GSLs converted to 145
methylthioalkyl GSLs by E. coli O83:H1 NRG 857C cell-free extracts
(obtained from glucoraphanin- induced cells) over a time course
Figure 2.25 Reduction bioconversion of sulforaphane to erucin by 149
E. coli O83:H1 NRG 857C intact cells
Figure 2.26 GC-MS chromatograms showing the reduction bioconversion 150
of sulforaphane to erucin by E. coli O83:H1 NRG 857C induced
cell-free extracts over a time course
Figure 2.27 Different metabolic fates of glucoraphanin in E. coli O83:H1 151
NRG 857C (ECO8N) and E. casseliflavus NCCP-53 (ENTCA)
Figure 2.28 HPLC chromatograms showing the effects of co-factor(s) 153
on reductase activity in E. coli O83:H1 NRG 857C cell-free extracts
Figure 2.29 Effects of temperature, pH and aeration on reductase 154
activity in E. coli O83:H1 NRG 857C cell-free extracts
Figure 2.30 Summary of key findings in this chapter 155
Figure 3.1 Strategies for forward proteomics 166
Figure 3.2 Combined gel-LC-MS based strategy (GeLC-MS) 167
Figure 3.3 List of publications in proteomic field by means of 168
two-dimensional electrophoresis technology as of Dec 2011
Figure 3.4 Sub-cellular fractionation of Gram-negative bacterial cell culture 170
Figure 3.5 MALDI-TOF mass spectrometry 172
Figure 3.6 Tandem mass spectrometry (MS/MS) 173
Figure 3.7 BSA calibration curve 178
Figure 3.8 Protein ladders used in 2-DE work 180
Figure 3.9 Calibration curves for pI and Mw determination 181
Figure 3.10 Sinigrin degradation and AITC production from various 186
sinigrin concentrations at 8 h
Figure 3.11 Growth curves of bacteria with and without sinigrin 187
supplementation over 8 h
17
Figure 3.12 Comparison of protein patterns from two lysis methods 189
Figure 3.13 Reproducibility of 2-DE gels from L. agilis R16 190
Figure 3.14 Comparative analysis of representative 2-DE maps of 194
bacterial proteins
Figure 3.15 Representative comparison of 3D montage of expression 195
levels of protein spot
Figure 3.16 Representative MS and MS/MS spectra 196
Figure 3.17 Functional grouping of the 28 upregulated proteins identified 199
on 2-DE gels of both bacteria
Figure 4.1 Hypotheses of this chapter. See main texts for more details 205
Figure 4.2 Scheme of the reverse proteomics workflow 208
Figure 4.3 Recombinant expression mechanisms in pET expression system 211
Figure 4.4 Colour table referring to the labelling of amino acids 215
(single letter code) used in ClustalW alignments
Figure 4.5 Map of an expression vector, pET28b(+) 219
Figure 4.6 Quick-Load 1 kb DNA ladder molecular marker 222
Figure 4.7 Protein markers 223
Figure 4.8 GOD-PERID assay reaction principle 226
Figure 4.9 Calibration curve for GOD-PERID assay 227
Figure 4.10 Structures of substrates used in GOD-PERID assay 228
Figure 4.11 β-O-glucosidase activity assay reaction principle 228
Figure 4.12 Calibration curve for β-O-glucosidase activity assay 229
Figure 4.13 Sulfatase assay reaction principle 230
Figure 4.14 Calibration curve for arylsulfatase activity assay 231
Figure 4.15 Alignment of eight bacterial putative myrosinase peptide 234
sequences with the Brevicoryne brassicae myrosinase `Aphid'
Figure 4.16 Alignment of two bacterial putative sulfatase peptide 237
sequences with the H. pomatia sulfatase `Snail'
Figure 4.17 Phylogenetic tree for bacterial putative myrosinases 239
and sulfatases
Figure 4.18 Agarose gel electrophoresis of genomic PCR experiments 240
18
Figure 4.19 Agarose gel electrophoresis of colony PCR experiments 241
Figure 4.20 Agarose gel electrophoresis of restriction digestion experiments 242
Figure 4.21 Recombinant protein expressions on SDS-PAGE 243
Figure 4.22 Myrosinase activity using GOD-PERID assay 244
Figure 4.23 β-O-glucosidase activity using GOD-PERID assay 245
Figure 4.24 β-O-glucosidase activity assay 246
Figure 4.25 Arylsulfatase activity assay 247
Figure 5.1 Hypothese of this chapter. See main text for more details 250
Figure 5.2 Sulfatase reactions 251
Figure 5.3 Crystal structures of P. aeruginosa arylsulfatase (PARS) 254
Figure 5.4 Proposed mechanistic scheme for the hydrolysis of sulfate 255
ester by the active-site aldehyde FGly of PARS
Figure 5.5 The overall structure of plant myrosinase 257
Figure 5.6 The ascorbate activated catalysis of GSL hydrolysis by plant 258 myrosinase.
Figure 5.7 The structure of aphid myrosinase showing the dimer 258
Figure 5.8 The catalysis of glucosinolates by aphid myrosinase 259
Figure 5.9 Proposed scheme of NIT production by desulfation of GSL 264
via sulfatase and β-O-glucosidase
Figure 5.10 Ion-exchange chromatography 267
Figure 5.11 Format used for FPLC chromatography 268
Figure 5.12 Ni2+-affinity chromatography 269
Figure 5.13 Bioinformatics details on SUL2 enzyme 279
Figure 5.14 Inducibility test of a native SUL2 enzyme of E. coli 283
O83:H1 NRG 857C
Figure 5.15 Purification of the recombinant sulfatase SUL2 by 284
ion-exchange chromatography
Figure 5.16 Purification of the recombinant SUL2 enzyme expressed 285
in BL21(DE3)
Figure 5.17 Temperature and pH optima of the recombinant SUL2 enzyme 287
Figure 5.18 Kinetics of H. pomatia sulfatase activity (0.05 U/mL) in 288
desulfation of intact GSLs
19
Figure 5.19 HPLC chromatograms showing desulfation of intact GSLs 290
by crude extracts of the recombinant SUL2 enzyme and the
purified H. pomatia sulfatase on the DEAE-Sephadex column
Figure 5.20 Enzyme activities of the recombinant SUL2 enzyme 292
for pNCS substrate
Figure 5.21 Enzyme activities of the recombinant SUL2 enzyme 294
for GSL substrates
Figure 5.22 Effect of compounds on the activity of the recombinant 295
SUL2 enzyme
Figure 5.23 Purification of the recombinant GH3 enzyme expressed 296
in BL21(DE3)
Figure 5.24 Temperature and pH optima of the recombinant GH3 enzyme 297
Figure 5.25 GC-MS chromatograms showing NIT production from DS-GSLs 299
by the purified recombinant GH3 enzyme in NB broths
Figure 5.26 Reaction catalyzed by the recombinant enzymes SUL2 and GH3 303
Figure 6.1 Proposed scheme of myrosinase and reductase of E. coli 310
O83:H1 NRG 857C induction by GSL
Figure 6.2 Summarized scheme of GSL/DS-GSL metabolism by human gut 311
bacteria and by bacterial recombinant enzymes under various
conditions
Figure 6.3 Proposed schematic presentation of GSL-metabolizing 314
mechanism in human gut bacteria
Appendix IA Representative GC-MS chromatogram showing no degradation 353
products from the negative control containing only GSL
substrate without bacterial cells or only bacterial cells without
GSL incubated in the culture broths for 24 h at 37˚C under
anaerobic conditions
Appendix IB Representative GC-MS chromatogram showing no degradation 353
products from the negative control containing only DS-GSL
substrate without bacterial cells incubated in the culture broths
for 24 h at 37˚C under anaerobic conditions
Appendix II List of gene sequencing results from the recombinant plasmids 354
20
Appendix III Representative HPLC chromatograms showing no DS-GSL 358
production upon 8 h incubation of intact GSLs with crude extracts
from BL21(DE3) on the DEAE-Sephadex column at 30˚C under
aerobic conditions
Appendix IV Representative GC-MS chromatograms showing no NIT 358
production in the negative controls containing DS-GSL alone,
GSL alone, the GH3 enzyme alone, the SUL2 enzyme alone
or the two enzymes alone incubated in NB broth or in the buffer
for 24 h at 37˚C under anaerobic conditions
21
LIST OF TABLES TABLE PAGE Table 1.1 Most abundant GSLs found in nature 35
Table 1.2 Expected ITC or NIT product from GSL hydrolysis catalyzed 49
by plant myrosinase
Table 1.3 Chemopreventive actions of ITCs produced from GSL hydrolysis 52
Table 2.1 Some metabolic reactions of intestinal microbiota 69
Table 2.2 Advantages and disadvantages of current techniques used to 71
characterize human gut microbiota
Table 2.3 Listing of some commonly used methods for the analysis 78
of GSLs and their breakdown products
Table 2.4 Response factors for desulfated GSLs at 229 nm in relative to 81
that of desulfo-sinigrin
Table 2.5 GSLs involved in this work as detected by HPLC analysis 84
Table 2.6 Compositions of culture media 86
Table 2.7 Mass spectral (MS) data of GSL degradation products 90
Table 2.8 Compositions of SDS-PAGE, loading buffer, running buffer, 99
staining/destaining solutions
Table 2.9 Bacterial isolates exhibiting > 50% degradation of 1 mM 102
sinigrin in 24 h anaerobic incubation at 37˚C
Table 2.10 Detection of ITC and NIT products from GSL metabolism 106
in bacterial fermentations
Table 2.11 Bacterial growth and glucobrassicin degradation in E. coli 118
O83:H1 NRG 857C and E. casseliflavus NCCP-53 over a time course
Table 2.12 Time taken to obtain 50% degradation of each GSL 120
substrate by three bacteria
Table 2.13 Percentage products of each ITC/NIT product from all GSL 121
metabolisms by each bacterium
Table 2.14 Time taken to obtain 50% or 25% decline in each ITC or 125
NIT level, respectively in NB broth with or without the
presence of E. coli O83:H1 NRG 857C cells
22
Table 2.15 Time taken to obtain 50% decline in each ITC level in 128
various aqueous solutions without the presence of
E. coli O83:H1 NRG 857C cells
Table 2.16 Detection of NIT product from DS-GSL metabolism in 129
bacterial fermentations
Table 2.17 PITC production from gluconasturtiin metabolism in 133
E. casseliflavus NCCP-53 resting cells in different buffers
for 8 h at 37˚C under anaerobic conditions
Table 2.18 Degradation of gluconasturtiin by bacterial resting cells 134
in 0.1 M citrate phosphate buffer pH 7.0 anaerobically
incubated for 2 h at 37˚C
Table 2.19 Effect of EDTA on ITC/NIT production from gluconasturtiin 134
metabolism in E. coli O83:H1 NRG 857C in NB broth for 16 h
anaerobic incubation at 37˚C
Table 2.20 Effect of Fe2+ ions (5 mM) on ITC/NIT production from 136
the metabolisms of different GSLs (0.5 mM) by E. coli O83:H1
NRG 857C induced resting cells in 0.1 M citrate
phosphate buffer pH 7.0 for 16 h anaerobic incubation at 37˚C
Table 2.21 Reduction bioconversion of glucoraphanin by cell-free extracts 139
of E. coli O83:H1 NRG 857(obtained from glucoraphanin- induced
or gluconasturtiin-induced cells) over a time course in 0.1 M citrate
phosphate buffer pH 7.0 at 37˚C under anaerobic conditions
Table 2.20 Reduction bioconversion of sulforaphane to erucin by cell-free 146
extracts and resting cells of E. coli O83:H1 NRG 857C (induced
with 1 mM glucoraphanin overnight) over a time course in 0.1 M
citrate phosphate buffer pH 7.0 at 37˚C under anaerobic conditions
Table 2.22 Reduction bioconversion (%) of 0.25 mM glucoraphanin to 148
glucoerucin by the addition of 1 mM of co-factor(s) in desalted
cell-free extracts of E. coli O83:H1 NRG 857C (obtained from
glucoraphanin-induced cells) within 24 h at 37˚C under anaerobic
conditions
Table 3.1 Reagents used in in-gel tryptic digestion and their compositions 182
23
Table 3.2 Experimental results of each set of cultures (with or without 191
sinigrin supplementation) from each bacterium
Table 3.3 Protein identification of differentially abundance spots 197
(≥ 2 fold increase in spot volume ratio and ANOVA p ≤ 0.05 with
≥ 2 matched peptides) of L. agilis R16 and E. coli O83:H1 NRG
857C grown on media with 2 mM sinigrin supplementation
Table 4.1 Primers used in PCR experiments and their restriction sites are 216
underlined
Table 4.2 Bacterial strains and plasmids used in this study 217
Table 4.3 Components in one PCR reaction 217
Table 4.4 Thermal cycling conditions for Pfu DNA Polymerase- 218
mediated PCR amplification
Table 4.5 Components in one ligation reaction 219
Table 4.6 Components in one colony PCR reaction 221
Table 4.7 Thermal cycling conditions for Taq DNA Polymerase-mediated 222
colony PCR amplification
Table 4.8 Ingredients for restriction enzyme digestion 222
Table 4.9 Information on genome and proteome of bacteria under study 232
Table 4.10 List of putative bacterial GSL-degrading enzymes/sulfatases with 233
high similarity to aphid myrosinase and snail sulfatase
Table 5.1 Properties of snail and bacterial sulfatases 255
Table 5.2 Properties of plant and aphid myrosinases 260
Table 5.3 Properties of the GH1 and GH3 enzyme families in comparison 262
Table 5.4 List of primers used in RT-PCT experiments 272
Table 5.5 Steps involved in the elution of the recombinant SUL2 enzyme 274
using FPLC
Table 5.6 Six proteins from E. coli O83:H1 NRG 857C and E. coli BL21(DE3) 281
producing significant alignments with anaerobic sulfatase-
maturating enzyme homolog (AslB) from Escherichia coli strain K12
Table 5.7 Purification scheme of the recombinant SUL2 enzyme from 286
Ni2+-affinity column chromatography
Table 5.8 Specific activity and relative activity of crude extracts of the 291
24
recombinant SUL2 enzyme in desulfation of intact GSLs
Table 5.9 Enzyme activities of the recombinant SUL2 on different 293
substrates
Table 5.10 Purification scheme of the recombinant GH3 enzyme from 297
Ni2+-affinity column chromatography
Table 5.11 Effects of metal ions on β-O-glucosidase activity of the 298
recombinant GH3 enzyme
Table 5.12 NIT productions from DS-GSLs by the purified recombinant 300
GH3 enzyme
Table 5.13 NIT productions from intact GSLs by sequential action of the 301
recombinant SUL2 enzyme and the recombinant GH3 enzyme
25
ABBREVIATIONS
2-DE Two-dimensional gel electrophoresis
3MSP 3-Methylsulfinylpropyl
3MTP 3-Methylthiopropyl
4MSB 4-Methylsulfinylbutyl
4MTB 4-Methylthiobutyl
6pbg 6-phospho-β-galactosidase
ABTS 2,2'-azino-bis-3-ethylbenzthiazoline-6-sulphonic acid AITC Allyl isothiocyanate
ANIT Allyle nitrile
AP-1 Activator protein-1
APS Ammonium persulfate
ARE Antioxidant response element
ARS Arylsulfatase
ATP Adenosine triphosphate
Bcl-2 B-cell lymphoma 2)
BCRP Breast cancer resistance protein
bgl β-glucosidase BITC Benzyl isothiocyanate
BLAST Basic local alignment search tool BNIT Benzyl nitrile
bp Base pair
BSA Bovine serum albumin
C-terminus Carboxylic terminus
CCD Charge-coupled device CcpA Catabolite control protein A
CCR Carbon catabolite repression
cdc Cell division cycle
Cdk1 Cyclin-dependent kinase 1
26
cDNA Complementary deoxyribonucleic acid
CDPX Chondrodysplasia punctata
CFU Colony-forming unit
CM Carboxymethyl
COG Clusters of orthologous group
COSY Correlation spectroscopy
COX-2 Cyclooxygenase-2 Cre Catabolite responsive element
CREB cAMP response element-binding protein
CYP Cytochrome P450 enzyme
Da Dalton
DCM Dichloromethane
DEAE Diethylaminoethyl
DGGE Denaturing gradient gel electrophoresis DMSO Dimethyl sulfoxide
DNA Deoxyribonucleic acid
DS-GSL Desulfo-glucosinolate
DTT Dithiothreitol
E I Enzyme I
E II Enzyme II
EC Enterococcus casseliflavus NCCP-53
ECO Escherichia coli O83:H1 NRG 857C
EDTA Ethylenediaminetetraacetic acid
EI Electron ionization
ELISA Enzyme-linked immunosorbent assay
ER Endoplasmic reticulum
ER Enhanced resolution
ERN Erucin
ERN NIT Erucin nitrile
ESI Electrospray ionization
27
ESM Epithiospecifier modifier
ESP Epithiospecifier protein
EST Expressed sequenced tag
ETN Epithionitrile
FAB Fast atom bombardment mass spectrometry
FACS Fluorescence activated cell sorting
FADH2 Reduced flavin adenine dinucleotide
FGE Formylglycine-generating enzyme
Fgly Formylglycine
FISH Fluorescence in situ hybridization FPLC Fast protein liquid chromatography
G2/M Growth 2/Mitosis
GBS Glucobrassicin GC-MS Gas chromatography mass spectrometry
GeLC-MS Gel liquid chromatography mass spectrometry
GER Glucoerucin
GFP Green fluorescent protein
GH Glycosyl hydrolase family
GI Gastrointestinal
GIB Glucoiberin
GIV Glucoiberverin
GLC Gas liquid chromatography GlpK Glycerol kinase
GNT Gluconasturtiin
GRP Glucoraphanin
GSH Glutathione GSL Glucosinolate
GSL-6-P Glucosinolate-6-phosphate GST Glutathione S-transferase
GSTM1 Glutathione S-transferase Mu 1
28
GSTT1 Glutathione S-transferase Theta 1
GTP Glucotropaeolin
HAD Haloacid dehalogenase
HARSA Human lysosomal arylsulfatase A
HARSB Human arylsulfatase B
HDAC Histone deacetylase His Histidine
HL-60 Human promyelocytic leukemia cells HPLC High pressure liquid chromatography
HPr Histidine-containing Protein
I3C Indole-3-carbinol
I3M Indol-3-ylmethyl
IAA Iodoacetamide or Indole-3-acetic acid
IBR Iberin
IBR NIT Iberin nitrile
IBS Irritable bowel syndrome
IBV Iberverin
IBV NIT Iberverin nitrile
IEF Isoelectric focusing
IPG Immobilized pH gradient
IPTG Isopropylthio-β-galactoside ITC Isothiocyanate
ITC MA Isothiocyanate mercapturic acid
KEAP1 Kelch-like ECH-associated protein 1
Km Michaelis-Menten constant
KmR Kanamycin resistance
KO Knock out
LA Lactobacillus agilis R16
LAB Lactic acid bacterium LC-MS Liquid chromatography mass spectrometry
29
Ler Landsberg erecta
log P Octanol–water partition coefficient
LPS Lipopolysaccharide
m/z Mass to charge ratio
M+ Molecular ion
MA Mercapturic acid MALDI-TOF Matrix-assisted laser desorption/ionization time-of-flight
MAPK Mitogen-activated protein kinase
MEKK1 Mitogen-activated protein kinase kinase 1
MES 2-(N-morpholino)ethanesulfonic acid
MMP-9 Matrix metallopeptidase 9
mol mole
miRNA Micro RNA
mRNA Messenger ribonucleic acid
MRS de Man, Rogosa and Sharpe
MRP-1 Multidrug resistance protein 1
MS Mass spectrometry
MS/MS Tandem mass spectrometry
MSD Multiple sulfatase deficiency
Mw Molecular weight
N-terminus Amino acid terminus
NA Not available
NADH Nicotinamide adenine dinucleotide
NADPH Reduced nicotinamide adenine dinucleotide phosphate
NB Nutrient broth
ND Not detected
n.d. Not determined
NF-κB Nuclear factor kappa B
NIR Near infra-red reflectance
NIT Nitrile
30
NL Non-linear
NMR Nuclear magnetic resonance NQO1 NAD(P)H:quinone oxidoreductase 1
Nrf2 NF-E2-related factor-2
NSP Nitrile specifier protein
NTA Nitroloacetic acid P-His-HPr Histidyl-phosphorylated form of HPr
P-Ser-HPr Seryl-phosphorylated form of HPr
PAPS 3’ Phosphoadenosine 5’-phosphosulfate
PARS Pseudomonas aeruginosa arylsulfatase
pBgl Periplasmic β-glucosidase
PBS Phosphate buffered saline PCR Polymerase chain reaction
Pgp P-Glycoprotein
pI Isoelectric point
PITC Phenethyl isothiocyanate
pKa Ionisability constant
PMF Peptide mass fingerprinting
pNC p-Nitrocatechol
pNCS p-Nitrocatechol sulfate
PNIT Phenethyl nitrile
pNP p-Nitrophenol
pNPG p-Nitrophenyl-β-D-glucopyranoside PRD Phosphotransferase system-regulatory domain
psi Pound per square inch
PTM Post-translational modification PTS Phosphotransferase system
qPCR Quantitative polymerase chain reaction
QR Quinone reductase R The side chain group of an amino acid
31
RNA Ribonucleic acid
RNAi Ribonucleic acid interference
RNA-Seq RNA-sequencing
ROS Reactive oxygen species
rRNA Ribosomal RNA
RT-PCR Reverse transcriptase poly chain reaction
SCFA Short-chained fatty acid
SDS-PAGE Sodium dodecyl sulfate polyacrylamide gel electrophoresis SF Sulforaphane
SFN NIT Sulforaphane nitrile
SIGEX Substrate induced gene expression
SIM Selected ion monitoring
SIP Stable isotope probing
SNG Sinigrin
SRB Sulfate-reducing bacteria
STAT3 Signal transducer and activator of transcription factor 3
SUL Sulfatase
TBP Tributylphosphine
TEMED N,N,N',N'-Tetramethylethylenediamine
TFP Thiocyanate forming protein
TGGE Temperature gradient gel electrophoresis
TH Thiohydroximates
TLR4 Toll-like receptor 4
TNF-α Tumor necrosis factor alpha
TOCSY Total correlated spectroscopY
TPA Tissue plasminogen activator
TR Retention time
tRFLP Terminal restriction fragment length polymorphism
Tris-Cl Tris(hydroxymethyl)amino methane-hydrochloric acid
UGT UDP-glucuronosyl transferase
32
UV Ultraviolet
VEGF Vascular endothelial growth factor
Vmax Maximum velocity
WC Wilkins Chalgren
XRF X-ray fluorescence spectroscopy
ABBREVIATIONS FOR AMINO ACIDS
Amino acid Three-letter abbreviation One-letter symbol
Alanine Ala A
Arginine Arg R
Asparagine Asn N
Aspartate Asp D
Cysteine Cys C
Glutamine Gln Q
Glutamate Glu E
Glycine Gly G
Histidine His H
Isoleucine Ile I
Leucine Leu L
Lysine Lys K
Methionine Met M
Phenylalanine Phe F
Proline Pro P
Serine Ser S
Threonine Thr T
Tryptophan Trp W
Tyrosine Tyr Y
Valine Val V
33
Chapter 1: Introduction The regular consumption of broccoli along with other vegetables of the Brassica
family including cauliflowers, watercress, rocket salads and mustards have been
associated with a lower incidence of cancer. These vegetables are rich in glucosinolates
(GSLs), secondary metabolites that can be degraded by myrosinase (β-D-
thioglucohydrolase, E.C. 3.2.1.147) to biologically active molecules. Myrosinase is naturally
found in all Brassica plants and in the specialist aphids Brevicoryne brassicae and Lipaphis
erysimi. To date, one class of degradation products from GSLs, the isothiocyanates (ITCs)
have been the most-studied and implicated in the cancer chemopreventive properties of
Brassica vegetables. However, plant myrosinases are rapidly denatured by cooking, and
thus the health properties of these vegetables are entirely dependent upon the putative
bacterial GSL-degrading activity of human gut microbiota. Although plant and aphid
myrosinases are well-characterized, bacterial GSL-degrading enzyme still remains elusive.
Therefore, it is essential that the influence of human gut microbiota on the metabolic fate
of GSLs is researched, and this has become the focus of this PhD project.
1.1 GSL structure, properties, occurrence and biological importance in plants GSLs are naturally occurring secondary metabolites abundant throughout 15
botanical families of the order Capparales, such as the Brassicaceae, Capparaceae, and
Resedaceae (Rodman et al., 1996). Representatives of the Brassicaceae are of particular
importance as vegetables (e.g. cabbage, broccoli, cauliflower, Brussels sprouts), root
vegetables (e.g. radish, turnip, swede), leaf vegetables (e.g. rocket salad), and relishes (e.g.
wasabi, mustard) (Stoewsand et al., 1995, Fahey et al., 2001; Rosa et al., 1997) for human
diets. Interestingly, GSLs are also present in the genus Drypetes of the family
Euphorbiaceae, a genus completely unrelated to the other GSL-containing families (Halkier
& Gershenzon, 2006).
GSLs are substituted β-thioglucoside N-hydroxysulfates which consist of two
moieties, a glycone and a variable aglycone (Rosa et al., 1997). The glycone (β-D-glucose)
and aglycone (thiohydroximate-O-sulfonate) moieties are joined by a β-thioglucoside
linkage. The aglycone moiety is highly variable due to the side chain (R, Figure 1.1) derived
34
from any one of eight amino acids namely alanine (Ala), valine (Val), leucine (Leu),
isoleucine (Ile), phenylalanine (Phe), methionine (Met), tyrosine (Tyr) and tryptophan (Trp)
(Halkier & Gershenzon, 2006).
Figure 1.1 Structure of GSL. A GSL consists of a glycone and an aglycone joined by a β-thioglucosidic bond (red line). R is a side-chain of an amino acid.
Over 120 different GSLs have been identified to date (Fahey et al., 2001). Based on
the amino acid precursor of the side chain and the types of modification to the R group,
most GSLs can be assigned to one of three major structural groups (Hopkins et al., 2009).
Compounds derived from Ala, Leu, Ile, Met, or Val amino acids are known as aliphatic GSLs
constituting about 50% of the known structures, those derived from Phe or Tyr as
aromatic GSLs (10%), and those from Trp, indole GSLs (10%). The remaining 30% of known
structures are derived from various amino acids, or their biosynthetic origin is yet to be
known (Fahey et al., 2001; Mithen, 2001). The R groups of most GSLs are extensively
modified from these precursor amino acids, with methionine undergoing an especially
wide range of transformations (Fahey et al., 2001). Most of the R groups are elongated by
one or more methylene moieties. Both elongated and non-elongated R groups are subject
to a wide variety of transformations, including hydroxylation, O-methylation, desaturation,
glycosylation, and acylation. Known GSLs occur within structural series of variable side-
chain length, which are derived from corresponding chain-elongated amino acids. Thus, it
is likely that more than 170 additional GSLs exist in nature, but they have not yet been
discovered (Clarke, 2010). The structures of the most abundant GSLs and their classes are
shown in Table 1.1
35
Table 1.1 Most abundant GSLs found in nature
GSL class Semi-systematic name Trivial name R group
Aliphatic Allyl (2-propenyl) Sinigrin
3-Butenyl Gluconapin
2-Hydroxy-3-butenyl (R) Progoitrin
4-Pentenyl Glucobrassicanapin
Aromatic Benzyl Glucotropaeolin
2-Phenethyl Gluconasturtiin
36
GSL class Semi-systematic name Trivial name R group
Methylthioalkyl 3-(Methylthio)propyl Glucoiberverin
4-(Methylthio)butyl Glucoerucin
Methylsulfinylalkyl 3-(Methylsulfinyl)propyl Glucoiberin
4-(Methylsulfinyl)butyl Glucoraphanin
Indolic Indol-3-ylmethyl Glucobrassicin
1-Methoxyglucobrassicin Neoglucobrassicin
37
Aqueous solubility, ionisability (pKa), and lipophilicity (octanol–water partition
coefficient, log P) determine the dissolution of GSLs. Log P is a crucial factor indicating
passive membrane partitioning and therefore affects membrane permeability, but is
inversely related to solubility (i.e. increasing log P enhances permeability but reduces
solubility). The presence of the sulfate group (very low pK value of the sulfonic acid group)
confers strongly acidic properties on intact GSLs. Because of the sulfate group and
thioglucose moiety, intact GSLs are always water-soluble. Because of their negative log P
values, GSLs are unlikely to be able to cross cell membranes, and would have to be enabled
by active transport or through aqueous pores. The structure of the side chain influences log
P value of GSL degradation product (Holst & Williamson, 2004). Log P values were found
within a range of 0.23 to 4.37; thus most GSLs degradation products, such as ITC and indolyl
products, are relatively hydrophobic (Cooper et al., 1997). Several factors such as species,
cultivar, tissue type physiological age, plant health, environmental factors (agronomic
practice, climatic conditions), insect attack, and microorganism intrusion can influence GSL
occurrence and concentrations (Rosa et al., 1997; Mithen et al., 2000; Fenwick et al., 1989;
Ciska et al., 2000). GSLs are present in all organs of the plants, but their concentrations and
profiles vary. There are huge differences in GSL profiles in vegetative tissues and those in
flowers and seeds, where the total amount of the former can be 10 times higher than the
latter and can account for up to 10% of the dry matter. Also, there can be as many as fifteen
different GSLs in the same plant, but usually only three or four predominate. Phenethyl GSL
(a.k.a gluconasturtiin) is found at high levels in some minor crops such as radishes and
watercress, and hydroxybenzyl GSLs are the major component of white mustard, Sinapis
alba. The highest concentrations are predominant in the seeds, except for indol-3-ylmethyl
and N-methoxyindol-3-ylmethyl GSLs, which are rarely found in seeds (Brown et al., 2003). A
typical HPLC chromatogram with the peaks corresponding to different GSLs is shown in
Figure 1.2.
38
Figure 1.2 Typical HPLC chromatogram of GSL profile in Sweetheart cabbage. The peaks are glucoiberin, 1, sinigrin, 2, glucobrassicin, 3, 4-methyoxyglucobrassicin, 4 and neoglucobrassicin, 5. This figure was taken from Nurul Huda Abd Karim, PhD thesis. The potential roles of GSLs in plants are involved in several systems as follows:
Plant growth regulation by GSL metabolism. Indole GSLs have been proposed as
precursors for the plant hormone indole-3-acetic acid (IAA). The indole GSLs are typically
hydrolyzed to indole acetonitrile, which could be hydrolyzed further to IAA by nitrilase
(Searle et al., 1982; Bartel & Fink, 1994). Interestingly, mutation of the genes involved in the
late steps of biosynthesis of indole GSLs in Arabidopsis mutants leads to high levels of IAA
and a corresponding dwarf phenotype (including adventitious root). It was demonstrated
that disruption of the conversion of indole-3-acetaldoxime to indole GSLs causes increased
flux into IAA (Mikkelson et al., 2004). One of the more complex interactions of GSLs/ITCs is
their activity as allelochemicals, compounds that affect successive plant communities and/or
those growing simultaneously, in close proximity (Brown & Morra, 1995).
The role of the GSL-myrosinase system in plant-insect/herbivore interactions. GSLs
are well known as defensive compounds against generalist herbivores and are likely to play a
role in host plant recognition by specialist predators, therefore acting both as an insecticide
and as an insect feeding attractant (Louda & Rodman, 1983; Mithen et al., 1986; Louda et al.,
39
1987; Tsao et al., 1996; Rask et al., 2000). For example, GSLs serve as important feeding cues
to insects including Pieris sp. caterpillars and other specialist feeders e.g. Plutella sp., seed
weevils, flea beetles which are differentially stimulated to feed by various GSLs (Renwick et
al., 1992).
The role of the GSL-myrosinase system in plant/pathogen interactions. The role of
GSLs in defense against pathogens is less clear than that for herbivores. Plants recognize the
main signal molecules which are derivatives of jasmonic acid, salicylic acid and ethylene.
These molecules mediate the plant response resulting in the activation of distinct sets of
defensive genes (Reymond & Farmer, 1998; Turner et al., 2002). Another indication for a
putative defensive role of GSLs came from numerousl studies showing changes in GSL
pattern after treatment with signal molecules. The toxicity of GSL hydrolysis products to soil-
borne fungal and bacterial plant pathogens in vitro has been reported (Smolinska et al.,
2003; Mari et al., 2002). In addition, GSLs have been shown as nematicides (Lazzeri et al.,
1993; Mayton et al., 1996) and as a feeding deterrent to snails, caddisflies and amphipods
(Newman et al., 1992). To date, the mechanism of GSLs induction, the signaling pathways
involved and the plant’s potential benefit from GSLs abundance still remain to be
determined.
1.2 Biosynthesis of GSLs
Since the 1960s, the pathway of biosynthesis of GSLs has been elucidated, and many
intermediates, enzymes and genes involved have been identified. The biosynthesis of GSLs
was reviewed extensively (Botti et al., 1995; Halkier & Gershenzon, 2006; Sønderby et al.,
2010). Knowledge of biosynthetic pathways of GSLs has progressed as research advanced
from conventional in vivo feeding studies with radiolabelled precursors and biochemical
characterization of the enzymes, identification and characterization of the biosynthetic genes
encoding the involved enzymes. The publication of the Arabidopsis thaliana genome has
enabled the complete elucidation of the core biosynthetic pathway.
Biosynthesis of GSLs proceeds through three separate steps: (i) chain elongation of
selected precursor amino acids (only Met and Phe), (ii) formation of the core GSL structure,
and (iii) secondary modifications of the amino acid side chain (Figure 1.3). Both side-chain
elongation and secondary modifications are responsible for the >120 known glucosinolate
40
structures (Fahey et al., 2001), of which Arabidopsis has about 40, mainly derived from Met
and Trp (Kliebenstein et al., 2001). More details of the three biosynthetic steps are as
follows:
(i) Before entering the core structure pathway, Met undergoes chain elongation in a
similar process that the branched-chain amino acid Val is converted to its chain-elongated
homolog Leu. The first step involves a deamination by a branched-chain amino acid
aminotransferase (BCAT), which yields a 2-oxo acid. The 2-oxo acid then enters a cycle of
three successive transformations: condensation with acetyl-CoA by a methylthioalkylmalate
synthase (MAM), isomerization by an isopropylmalate isomerase (IPMI), and oxidative
decarboxylation by an isopropylmalate dehydrogenase (IPM-DH). The product of these three
reactions is a 2-oxo acid that has been elongated by a single methylene group (–CH2–
theNext, the molecule can either be transaminated by a BCAT to yield homoMet and enter
the core glucosinolate structure pathway or proceed through another round of chain
elongation. Accordingly, the overall process yields not only homoMet, but an array of chain-
elongated derivatives of Met.
(ii) The chain-elongated amino acids are then converted to aldoximes by cytochromes
P450 of the CYP79 family. CYP79B2 and CYP79B3 both metabolize Trp, CYP79A2 uses Phe as
a substrate (Wittstock & Halkier, 2000), CYP79F1 converts all chain-elongated Met
derivatives, and CYP79F2 only converts the long-chained Met derivatives. After that,
aldoximes are oxidized to activated compounds (either nitrile oxides or aci-nitro compounds)
by cytochromes P450 of the CYP83 family. CYP83B1 metabolizes both the Trp-derived and
Phe-derived acetaldoximes, and CYP83A1 converts aliphatic aldoximes. Following
conjugation of the activated aldoximes to a sulfur donor, glutathione (Dixon et al., 2010),
which can happen non-enzymatically, the produced S-alkyl-thiohydroximates are converted
to thiohydroximates by the C-S lyase SUR1 (Mikkelsen et al., 2004). Thiohydroximates are in
turn S-glucosylated by glucosyltransferases of the UGT74 family to form
desulfoglucosinolates. The glucosylation gives rise to desulfoglucosinolates, which are finally
sulfated by the sulfotransferases ST family to form a core GSL structure.
(iii) The core GSL structure can undergo side-chain modifications involving different
reactions, such as oxidation, desaturation, hydroxylation, removal of a methylsulfinyl group,
41
and addition of methoxy group. The flavin monooxygenase FMOGS-OX1 was identified as a
candidate for S-oxygenation (Hansen et al., 2007). AOP2 catalyzes the conversion of S-
oxygenated glucosinolates to alkenyl glucosinolates, whereas AOP3 catalyzes the conversion
to hydroxyalkyl glucosinolates (Kliebenstein et al., 2001). The overview of biosynthetic
pathways of GSLs is shown in Figure 1.3
Figure 1.3 Biosynthesis of aliphatic GSLs in Arabidopsis Col-0. (A) The chain-elongation machinery. Methionine enters the chain-elongation cycle via deamination by BCAT4 and is subsequently condensed with acetyl-CoA in a reaction catalyzed by MAM1 and MAM3. MAM1 can catalyze one to four condensation cycles, whereas MAM3 catalyzes one to six cycles. Subsequently, an isomerization and oxidation-decarboxylation step occurs and the molecule can re-enter the cycle or enter the core pathway following a transamination step. (B) Synthesis of the core methylthio GSL structure. The first enzymatic step has side chain specificity with CYP79F1 that converts both short- and long- chained methionine derivatives (n = 1–6) to the corresponding aldoxime whereas CYP79F2 only takes the long-chained methionine derivatives (n = 5–6). See main texts for more details. (C) Secondary modifications. Short- and long-chained methylthio glucosinolates can be secondarily modified to methylsulfinyl glucosinolates in Col-0 leaves. In the seeds, the short-chained methylsulfinyl glucosinolates can be further modified to hydroxy form by AOP3 and benzoyloxy form by BZO1. Characterized enzymes in the pathway are noted next to the reaction arrows. This figure was adapted from Sønderby et al., (2007). Most genes in the pathway have been identified and characterized in the model plant
Arabidopsis thaliana (Sønderby et al., 2010). Modification of the levels of specific GSLs in
crop plants has been a strong interest as certain GSLs have desirable properties in flavour,
insect protection, biofumigation, and cancer prevention, whereas others have undesirable
properties. To date, metabolic engineering of GSL profiles has included altering the
expression of one or more CYP79 enzymes. Identification of the CYP79s as the enzymes
catalyzing the conversion of amino acids to aldoximes has provided important molecular
42
tools for modulating the profile of GSLs (Mikkelsen et al., 2002). Recently, the introduction
of the seven-step pathway of indolyl GSL from Arabidopsis thaliana to Saccharomyces
cerevisiae resulted in the first successful production of GSLs in a microbial host (Mikkelsen et
al., 2012). This production of indolyl GSL serves as a proof-of-concept for the expression
platform, and establishes a basis for large-scale microbial production of GSLs of interest.
Recently, stable genetic transfer of the six-step benzyl GSL pathway from A. thaliana to
Nicotiana tabacum (tobacco) leads to the production of benzyl GSL without causing
morphological alterations (Moldrup et al., 2012). Crucifer-specialist insect herbivores, like
the economically important pest Plutella xylostella (diamondback moth), frequently use GSLs
as oviposition stimuli. The transfer of a GSL biosynthetic pathway to a non-crucifer is likely to
stimulate oviposition on an otherwise non-attractive plant (Moldrup et al., 2012). In addition,
broccoli with a greater content of the glucoraphanin precursor of anti-carcinogenic ITC called
sulforaphane has been bred successfully using plant breeding methods (Mithen et al., 2003).
Three segments of the genome of a wild relative of broccoli Brassica villosa containing
greater concentrations of aliphatic GLS than commercial broccoli cultivars were introgressed
into commercial broccoli cultivar Marathon. More recently, a commercial-quality broccoli
(Beneforté®; Seminis Vegetable Seeds, Inc.) was bred to include Brassica villosa genetics
with two- to three-fold higher glucoraphanin content compared with commercial standard
hybrids (Vissavajjhala et al., 2011). A benefit of this high-glucoraphanin variety is that it
enables nutritional intervention studies that concentrate on a specific phytonutrient from a
whole food (James et al., 2012).
1.3 Degradation of GSL and its degradation products Most GSLs are chemically and thermally stable and thus degradation is mainly
enzymatically driven. Myrosinase co-occurs with GSLs and is involved in the enzymatic
degradation of these compounds. In A. thaliana, myrosinase is found in specialised cellular
compartments called myrosin cells separated from GSLs that are stored primarily in sulfur
rich cells (S-cells) located in close vicinity to the phloem (Koroleva et al., 2000; Koroleva et al.,
2010). It still remains unknown whether this type of compartmentation is common in other
cruciferous plants. The location of myrosinase in the cytoplasm of specialised myrosin cells
scattered throughout the plant tissue was proven by histochemical and immunological
studies (Kelly et al., 1998). Upon tissue disruption, myrosinase and GSL come into contact,
43
causing degradation of the β-thioglucosidic bond, and subsequently releasing glucose and an
unstable aglycone intermediate, the thiohydroxamate-O-sulfonate (Figure 1.4). The default
products are the isothiocyanates (ITCs) unless specifier proteins are present in which case
nitriles (NITs) and elemental sulfur, thiocyanate (TC), epithionitrile (ETN) can be formed
(Kissen et al., 2009; Bones et al., 2006). The scheme of GSL degradation under various
conditions is shown in Figure 1.4.
Figure 1.4 GSL hydrolysis under different conditions. In the first step, myrosinase-catalyzed degradation yields glucose and an unstable aglycone. In the absence of specifier proteins, the aglycone rapidly rearranges to an ITC. By contrast, the formation of epithionitriles, nitriles and thiocyanates depends on the chemical nature of the GSL side chain, and involves the action of an additional protein under physiological conditions. ESP, epithiospecifier protein; NSP, nitrile specifier protein; R, variable side chain; TFP, thiocyanate forming protein. This figure was modified from Tripathi & Mishra (2007).
The GSL degradation product formed by the reaction depends largely on the
chemical structure of the side chain. For example, indole GSLs produce only NITs and
unstable ITCs that rapidly form non-volatile indolylcarbinols (Bones & Rossiter, 1996; Burow
et al., 2006; Mithen, 2001; De Vos et al., 2005). On the other hand, aliphatic GSL degradation
yields volatile and pungent ITCs. The pH, the concentration of ferrous ions, and the presence
of epithiospecifier protein (ESP) or epithiospecifier modifier protein (ESM) are also
important factors contributing to the outcome of the myrosinase-GSL reaction (Burow et al.,
2006; Lambrix et al., 2001).
At pH 6-7, ITC production is favoured and is derived from the aglycone intermediate
by a Lossen rearrangement involving the migration of the side chain from the oxime carbon
44
to the adjacent nitrogen. The formation of NITs in vitro is favoured at a pH 3-4 in the
presence of Fe2+ ions (Uda et al., 1986). However, protein factors may be involved in NIT
formation in vivo, such as epithiospecifier modifier protein (ESM) and/or nitrile specifier
protein (NSP) (Foo et al., 2000; Bernardi et al., 2000; Kissen & Bones, 2009). When the GSL
side chain has a terminal double bond, epithiospecifier protein (ESP) promotes the reaction
of the sulfur atom of the β-thioglucosidic bond with the double bond to form a thirane ring,
giving an ETN (Figure 1.4). The formation of thiocyanate (TC) can only be derived from three
GSLs namely sinigrin, glucotropaeolin and glucoraphanin and is thought to be facilitated by
thiocyanate forming protein (TFP) (Wittstock & Burow, 2007).
Many endogenous factors can affect plant myrosinase activity and product formation
or the activity of ESP. Myrosinase activity was increased in some plant species with low
concentrations of ascorbic acid, but it was inhibited at higher concentrations (Botti et al.,
1995). During storage and processing of Brassica vegetables, cell damage occurs,
accompanied by competing processes of degradation and de novo biosynthesis of specific
GSLs. This multiple set of parameters affecting the outcome of the degradation gives rise to
a complex profile of degradation products in these plants. In addition, the chemical structure
of the GSL products is important for their biological activity. Small changes to side-chain
structures can have significant effects. For example, while methylthioalkyl GSLs produce
volatile and pungent ITCs (the major flavour compound in salad rocket is erucin),
methylsulfinylalkyl GSLs (the next products in the biochemical pathway) produce non-
volatile ITCs with relatively mild flavours, such as those found in broccoli. Removal of the
methylsulfinyl group and addition of a double bond results in a volatile ITC. Finally, addition
of a hydroxyl group to 3-butenyl and 4-pentenyl GSLs results in the spontaneous cyclisation
of the unstable ITC and the production of a non-volatile product (Holst & Williamson, 2004).
1.4 Biochemistry of myrosinases Myrosinases, as the only group of β-thioglucosidases known in nature, use GSLs as
substrates. Most myrosinases including myrosinase MYR1 from Brassica napus hydrolyze
multiple GSL substrates (Chen & Halkier, 1999) however some myrosinases from Brassica
napus and Crambe abyssinica are highly specific (Bernardi et al., 2003; MacLeod & Rossiter,
1986). All plant myrosinases are encoded by a multigene family. Six genes encoding classical
myrosinases have been identified in A. thaliana genome of which only four are functional
45
(TGG1-2 and TGG 4-5), and two (TGG3 and TGG6) are encoded by pseudogenes (Xu et al.,
2004; Wang et al., 2009). Twenty myrosinase genes or more were found in Brassica napus
and Sinapis alba and were grouped into families A and B (Rask et al., 2000). Some of which
have non-overlapping expression patterns (James & Rossiter, 1991; Lenman et al., 1993; Xue
et al., 1993). Biochemical characterisation of two myrosinases (previously known as
myrosinase I and II) identified from Brassica napus revealed the different features between
them in terms of their molecular weight and glycosylation level (myrosinase II had a smaller
number of glycosylated residues as compared with myrosinase I) (James & Rossiter, 1991).
Myrosinase is an abundant constitutively expressed protein in some cruciferous seeds, and is
easily obtainable by simple ammonium sulfate fractionation followed by ion-exchange
chromatography.
Classical myrosinases belong to a phylogenetically distinct group within glycosyl
hydrolase family 1 (GH1) and are thought to have evolved from -O-glucosidase ancestors
(Xu et al., 2004). This enzyme is a homodimer that contains three disulfide bridges, two of
which are important for stabilizing the N-terminus of myrosinase (Rask et al., 2000). In
addition, salt bridges, hydrogen bond and high carbohydrate content up to 20% are also
believed to provide stability to the myrosinases enabling the enzyme to carry out GSL
degradation in an extracellular environment without being inactivated by its reactive
products. A unique feature of plant myrosinase is its activation by ascorbic acid. Early work
had shown that ascorbic acid created an allosteric effect on the activity of the enzyme
(Ohtsuru & Hata, 1973; Ohtsuru & Hata, 1979). However, more recent studies have shown
that ascorbic acid is rather a catalytic base, and GSL degradation can be effectively promoted
in the absence of ascorbic acid, but at a much slower rate (Burmeister et al., 1997; Bones &
Rossiter, 2006).
The elucidation of the mechanism of plant myrosinase has been aided by x-ray
structural analysis of white mustard myrosinase (Burmeister et al., 1997). The use of a 2-F-2-
deoxybenzyl GSL inhibitor to irreversibly inhibit myrosinase by forming a covalent link
between the C-1 of the glycosyl unit and Glu 409 has enabled the identification of a catalytic
Glu 409 and a Gln 187 in the active site (Cottaz et al., 1996). This myrosinase is a dimer
linked by a zinc atom and has a characteristic (β/α)8-barrel structure which act through a
mechanism that gives retention of the anomeric configuration (Cottaz et al., 1996).
46
The myrosinase-GSL system has been extensively studied in plants (Wallsgrove &
Bennett, 1995; Halkier & Du, 1997). It was not until 2001 when the non-plant myrosinase
was first fully characterized (Jones et al., 2001). The cabbage aphid B. brassicae was shown
to produce a myrosinase capable of hydrolysing several common plant GSLs e.g. sinigrin and
glucotropaeolin (Francis et al., 2002; Jones et al., 2002). This myrosinase was purified, and
an x-ray structural determination was carried out (Huseby et al., 2005; Jones et al., 2002;
Jones et al., 2001). Sequencing has shown that this myrosinase has significant sequence
similarity (35%) to plant myrosinases and other members of GH1 (Jones et al., 2002). In
common with plant myrosinase, aphid myrosinase has the characteristic (β/α)8-barrel
structre. The residues acting as a proton donor and a nucleophile in GSL degradation by
aphid myrosinase are identified as Glu 167 and Glu 374, respectively. Gln 187 and Glu 409
are the equivalent residues in plant myrosinase, and Glu 183 and Glu 397 for the cyanogenic
β-glucosidase. Assumingly, a proton donor is necessary for GSL degradation in the case of
aphid myrosinase, but not for plant myrosinases. Unlike plant myrosinase, aphid myrosinase
does not require ascorbic acid for its activity and it appears to be more similar to animal β-O-
glucosidases than to plant myrosinase. This assessment was determined by sequence
similarity and phylogenetic techniques (Jones et al., 2002).
1.5 Specifier proteins
Except for ITCs, the biological roles of the other GSL degradation products are not
well understood. However, previous studies indicate that they may act in direct and indirect
defense (Wittstock et al., 2003; Wittstock & Burow, 2010). Other than ITCs, other products
namely NITs, ETNs and organic TCs can be formed by the rearrangement of the aglycone
promoted by supplementary proteins called ‘specifier proteins’ (Tookey, 1973).
Thus far, nine plant specifier proteins have been identified and characterized
biochemically with different substrate and product specificities at the molecular level
(Kuchernig et al., 2012). Specifier proteins were first discovered in Crambe abyssinica
(Brassicaceae) and found to have effect on the degradation products without having
hydrolytic activity on GSLs themselves (Tookey, 1973). A vast stride of progress has been
made within the past decade in identifying the role of specifier protein. The gene that
encodes for epithiospecifier protein (ESP) was first identified in A. thaliana ecotype
Landsberg erecta (Ler) (Lambrix et al., 2001). This stable ESP was found to redirect the
47
conversion of aglycones from ITCs by myrosinases towards the formation of simple NITs and
ETNs (Burow et al., 2006) rather than being an allosteric co-factor of myrosinase as proposed
earlier (Petroski & Kwolek, 1985). Thiocyanate forming protein (TFP), which has been
identified from Lepidium sativum, shares 63-68% amino acid sequence identity with known
ESPs and up to 55% identity with myrosinase-binding proteins from A. thaliana (Burow et al.,
2006). Despite the similarities in sequence identity between ESP and TFP, it is not known
whether both of these specifier proteins are derived from a common ancestor (Burow &
Wittstock, 2009). Recently, a recombinant TFP enzyme from Thlaspiarvense arvense
(Brassicaceae) was purified in active form in E. coli (Kuchernig et al., 2011). Interestingly, this
protein promotes the formation of allyl thiocyanate as well as the corresponding ETN upon
myrosinase-catalyzed degradation of allyl GSL, the major GSL of Thlaspiarvense arvense. All
other GSLs tested were converted to their simple NITs when hydrolyzed in the presence of
this protein. In contrast with A. thaliana ESP, TFP in vitro activity is not strictly dependent on
Fe²⁺ addition to the assay mixtures (Kuchernig et al., 2011).
Another supplementary protein namely nitrile specifier protein (NSP), capable of
redirecting degradation of GSLs to NITs, has also been identified. It was first found in the
larvae of the butterfly Pieris rapae and was also identified in A. thaliana (Burow et al., 2006;
Kissen & Bones, 2009). NSP promote simple NIT formation at physiological pH values, but do
not catalyse ETN or TC formation (Burow & Wittstock, 2009; Kissen & Bones, 2009). In A.
thaliana, six specifier proteins have been identified so far including one ESP (Lambrix et al.,
2001) and five NSPs (Burow & Wittstock, 2009; Kissen & Bones, 2009).
1.6 Importance of GSLs and ITCs to human health
1.6.1 Chemopreventive effects of GSLs
It has been shown that cancer is 30–40% preventable over time by appropriate food
and nutrition (American Institute for Cancer Research 2007). Accumulating evidence on
plant foods and cancer prevention suggests the potentially beneficial effect of GSLs which
are abundant in cruciferous vegetables (Lynn et al., 2007; Ambrosone & Tang, 2009; Mithen
et al., 2010; Traka & Mithen, 2009; Bosetti et al., 2012). Epidemiologic studies published
prior to 1996 revealed that the majority (67%) of 87 case-control studies showed an inverse
48
correlation between some type of cruciferous vegetable intake and cancer risk (Verhoeven
et al., 1996). In the past decade, results of large prospective cohort studies and studies
taking into account individual genetic variation suggest that the relationship between
cruciferous vegetable intake and the risk of several types of cancer is more complex than
previously thought (Higdon et al., 2007). To date, the inverse association appeared to be
most consistent for cancers of the lung and digestive tract. Evidence of chemopreventive
effects of cruciferous vegetables for lung, colorectal and prostate cancer are summarized
below:
Lung Cancer: Several case-control studies demonstrated that people diagnosed with
lung cancer had significantly lower intakes of cruciferous vegetables than people in cancer-
free control groups (Verhoeven et al., 1996). Prospective studies of Finnish men (Miller et al.,
2004) and Dutch men and women (Feskanich et al., 2000) indicated that higher intakes of
cruciferous vegetables (more than three weekly servings) were associated with significant
reductions in lung cancer risk.
Colorectal Cancer: A small clinical trial found that the consumption of 250 g/d (9
oz/d) of broccoli and 250 g/d of Brussels sprouts significantly increased the urinary excretion
of a potential carcinogen found in well-done meat, namely 2-amino-1-methyl-6-
phenylimidazo[4,5-b]pyridine (PhIP) (Walters et al., 2004). A prospective study of Dutch
adults found that men and women with the highest intakes of cruciferous vegetables
(averaging 58 g/d) were significantly less likely to develop colon cancer than those with the
lowest intakes (averaging 11 g/d) (Voorrips et al., 2000).
Prostate Cancer: To date, epidemiological studies provide only modest support for
the speculation that high intakes of cruciferous vegetables reduce prostate cancer risk
(Kristal & Lampe, 2002). Four out of eight case-control studies published since 1990 found
that some measure of cruciferous vegetable intake was significantly lower in men diagnosed
with prostate cancer than men in a cancer-free control group (Cohen et al., 2000; Jain et al.,
1999; Joseph et al., 2004; Kolonel et al., 2000).
At present, the putative role on cancer chemoprevention of cruciferous vegetables is
attributed to the bioactivity of GSL degradation products, mainly ITCs. ITCs have been shown
to protect against the most common cancer types, such as breast, lung, colon and prostate
49
cancers in both in vivo and in vitro studies (Bianchini & Vainio, 2004; Hayes et al., 2008;
Keum et al., 2005; Wu et al., 2011; Nakamura, 2009; Yang et al., 2010; Lai et al., 2010;
Cheung & Kong, 2009; Kim et al., 2011; Sehrawat & Singh, 2011; Cheung et al., 2008;
Powolny et al., 2011; Wang et al., 2010; Yin et al., 2009). Following metabolism of GSLs into
ITCs in vivo, the structural difference of GSLs is conferred to that of the cognate ITCs. For
example, glucoraphanin is hydrolyzed by plant myrosinase to sulforaphane (SFN), sinigrin to
allyl ITC (AITC), gluconasturtiin to phenethyl ITC (PITC), glucotropaeolin to benzyl ITC (BITC),
glucoerucin to erucin (ERN), glucoiberin to iberin (IBR) and glucoiberverin to iberverin (IBV).
The summary table of the expected ITC or NIT degradation products from GSL hydrolysis
catalyzed by plant myrosinase is shown in Table 1.2.
Table 1.2 Expected ITC or NIT product from GSL hydrolysis catalyzed by plant myrosinase
GSL substrate ITC product NIT product
Sinigrin (SNG) Allyl isothiocyanate (AITC) Allyl nitrile (ANIT)
Glucotropaeolin (GTP) Benzyl isothiocyanate (BITC) Benzyl nitrile (BNIT)
Gluconasturtiin (GNT) Phenethyl isothiocyanate (PITC) Phenethyl nitrile (PNIT)
Glucoerucin (GER) Erucin (ERN) Erucin nitrile (ERN NIT)
Glucoiberin (GIB) Iberin (IBR) Iberin nitrile (IBR NIT)
Glucoraphanin (GRP) Sulforaphane (SFN) Sulforaphane nitrile (SFN NIT)
Several mechanisms for the activities of ITCs in different stages in cancer
chemoprevention have been proposed (Figure 1.5).
50
Figure 1.5 Mechanisms of action of ITCs in the modulation of signalling pathways involved in cancer chemoprevention. CYP = Cytochrome; GST = Glutathione-S-transferase; UGT = UDP-glucuronosyl transferase; NF-κB = Nuclear factor kappa B; HDAC = Histone deacetylase; miRNA = micro RNA. This figure was modified from Navarro et al., (2011).
This includes inhibition of phase I carcinogen activating enzymes such as CYP
enzymes (Yoxall et al., 2005; Conaway et al., 1996), induction of phase II carcinogen
detoxification enzymes such as glutathione-S-transferase (Talalay, 2000; Nakamura et al.,
2000), induction of cell cycle arrest (Gamet-Payrastre et al., 2000; Singh et al., 2004) and
apoptosis (Xiao et al., 2003). ITCs are known to modulate a large number of important
cancer-related proteins (Figure 1.6) through various mechanisms.
51
Figure 1.6 ITCs modulate a large and diverse group of proteins. The modulation of many proteins by ITCs involves direct reaction of the –N=C=S groups of ITCs with cysteine thiols of the proteins. Macrophage migration inhibitory factor is modulated via its amino group. The mechanisms for modulation of many other proteins are not yet known. See main texts for details. This figure was modified from Zhang (2011).
For examples, inhibition of cytochrome P450 (CYP) enzymes (von Weymarn et al.,
2007), induction of phase II enzymes via activation of NF-E2-related factor-2 (Nrf2) (Zhang &
Hannink, 2003; Thimmulappa et al., 2002), inhibition of histone deacetylases (HDACs) (Wang
et al., 2008; Myzak et al., 2006), inhibition of membrane drug transporters (Callaway et al.,
2004, Ji & Morris, 2005), modulation of cell cycle regulators and Bcl-2 family proteins (Geng
et al., 2011; Xiao et al., 2006; Zhang & Tang, 2007) activation of caspases (Park et al., 2007;
Wu et al., 2005), downregulation of α-/β-tubulins and/or inhibition of tubulin polymerization
(Mi et al., 2009; Mi & Chung, 2010), downregulation of vascular endothelial growth factor
(VEGF) (Boreddy et al., 2011) and its receptor and inhibition of nuclear factor kappa B (NF-
κB) (Xu et al., 2005), activator protein-1 (AP-1) (Li & Zhang, 2005; Gopalakrishnan & Tony
Kong, 2008), mitogen-activated protein kinase kinase 1 (MEKK1) (Cross et al., 2007), signal
52
transducer and activator of transcription factor 3 (STAT3) (Gong et al., 2009) and Toll-like
receptor 4 (TLR4) (Youn et al., 2010).
Most of the activities mentioned above are shared by different ITCs (Munday &
Munday, 2004). The reactivity of ITC lies in its electrophilic nature and its tendency to
undergo facile addition reactions with N-, O-, or S-based nucleophiles. At least some of their
chemopreventive mechanisms are all activated through direct reaction of the carbon atom
of the –N=C=S group of ITCs with the cysteine sulfhydryl groups of glutathione (GSH) and
proteins (Drobnica et al., 1975; Zhang, 2000). The side chains of ITCs may play secondary
roles, by influencing the electrophilicity of the –N=C=S group, altering the access to the
reactive carbon through steric effects and controlling the lipophilicity of the whole molecule
(Zhang, 2011). This explains the intriguing capability of ITCs to target a diverse group of
proteins, and the phenomenon that different ITCs often share similar biological activities and
metabolic profiles. The summary of the expected ITC products from the hydrolysis of GSLs by
plant myrosinase and corresponding chemopreventive properties of ITCs is shown in Table
1.3.
Table 1.3 Chemopreventive actions of ITCs produced from GSL hydrolysis
ITC Chemopreventive mechanisms of ITC
AITC from sinigrin
Source: brussels sprouts,
cabbage, cauliflower,
kale, mustard,
horseradish and wasabi
Proliferation inhibition of various types of human cancer cells
through cell cycle arrest and/or induction of apoptosis (Zhang &
Hannink, 2003; Xiao et al., 2003; Musk & Johnson, 1993; Tang &
Zhang, 2004), inhibition of cell adhesion, migration and invasion
(Hwang & Lee, 2006) and stimulation of histone acetylation (Lea
et al., 2001), activation of Nrf2, phase II genes (Munday et al.,
2006; Zhang et al., 1998), and also inhibition of Helicobacter
pylori (Shin et al., 2004) and Escherichia coli O157:H7 (Luciano et
al., 2009).
BITC from
glucotropaeolin
Anti-cancer effects in both in vivo and in vitro experimental
models (Hwang et al., 2008; Nakamura, 2009; Hecht, 1999),
activation of DNA damage, causes growth 2/mitosis (G2/M) cell
53
Source: Papaya (Carica
papaya) and garden
cress
cycle arrest and apoptosis (Zhang et al., 2006), inhibition of tissue
plasminogen activator (TPA)-induced oxidative stress through
inhibition of reduced nicotinamide adenine dinucleotide
phosphate (NADPH) oxidase and leukocyte infiltration (Nakamura
et al., 2004), inhibition of tumor necrosis factor alpha (TNF-α)-
induced matrix metallopeptidase 9 (MMP-9) secretion by
downregulation of NF-κB and AP-1 (Lee et al., 2009).
PITC from
gluconasturtiin
Source: Watercress and
garden cress
Activation or inhibition of various cellular signaling pathways such
as phase I/II detoxification modification enzymes (Munday &
Munday, 2004), Nrf2 and Kelch-like ECH-associated protein 1
(Keap1) (Itoh et al., 2003) and NF-κB (Jeong et al., 2004),
induction of cell cycle arrest by reduction of cyclin-dependent
kinase 1 (cdk1) and cell division cycle 25c (cdc25c) (Xiao et al.,
2004).
SFN from glucoraphanin
Source: Broccoli,
Broccoli sprouts,
cabbage, Brussel sprouts
Strong antitumor activities in vitro and in vivo (Conaway et al.,
2005; Fimognari & Hrelia, 2007; Chiao et al., 2002; Singh et al.,
2004; Jakubikova et al., 2005). Induction of phase II detoxification
gene expression through the Nrf2 or the antioxidant response
element (ARE) pathway (Sibhatu et al., 2008), reduction of the
number of polyps through suppressing mitogen-activated protein
kinase (MAPK) signalling (Bertl et al., 2006), suppression of
lipopolysaccharide (LPS)-induced cyclooxygenase-2 (COX-2)
expression, downregulating NF-κB, CCAAT/enhancer binding
protein (C/EBP), cAMP response element-binding protein (CREB)
and AP-1 (Woo & Kwon, 2007). Treatments for gastritis and
stomach cancer caused by Helicobacter pylori (Fahey et al., 2002).
ERN from glucoerucin
Source: Rocket slads
ERN may also exert its potential protective effects against human
cancer through multiple mechanisms similar to those triggered by
SFN (Melchini & Traka, 2010) e.g. induction of phase II enzymes
e.g. QR and GST in rat and human tissues (Hanlon et al., 2009;
Munday & Munday, 2004; Zhang et al., 1992), upregulation of
54
phase III detoxification system e.g. multidrug resistance-
associated protein 1/2 (MRP-1/2) in human colonic cancer CACO-
2 cells (Munday & Munday, 2004; Harris et al., 2008), induction of
tumour suppressor proteins (p53, p21), cell cycle arrest, pro-
apoptotic signals (Melchini et al., 2009; Fimognari et al., 2004;
Jakubikova et al., 2005).
IBR from glucoiberin
Source: Horseradish,
mustard
There are fewer studies on both IBR and IBV in comparison to
SFN. IBR increased glutathione S-transferase (GST) and quinone
reductase (QR) activities in the urinary bladder of the rats
demonstrating protective effects against chemical carcinogenesis
(Staack et al., 1998). IBR also led to induction of phase II enzymes
e.g. thioredoxin reductase (Barrera et al., 2012; Wang et al.,
2005), induction of apoptosis and cell cycle arrest (Jadhav et al.,
2007; Jakubikova et al., 2006).
IBV from glucoiberverin
Source: Horseradish,
mustard
Induction of phase II enzymes e.g. QR and GST in a variety of rat
tissues (Munday & Munday, 2004; Kim & Singh, 2009). However,
the anticancer effects of IBR and IBV on the tumor cells have not
been investigated in detail.
The biological effect of the above ITCs varies due to the side-chain structure. For
example, in vitro studies have shown that SFN is taken into cells faster, kept intracellularly
longer, and at higher accumulations than several other ITCs (Zhang & Talalay, 1998; Ye &
Zhan, 2001). SFN also has the highest potency of inducing the expression of two phase II
enzymes, QR and GST (Zhang & Talalay, 1998; Vermeulen, 2009). In contrast, AITC was
shown to be most effective in causing HL60 (human promyelocytic leukemia cells) cell cycle
arrest (Jakubikova et al., 2005) while PITC and BITC were the most effective in inducing
apoptosis, among six different ITCs (Munday et al., 2008). Based on the study of the effect of
ten synthetic ITC analogues on pro-inflammatory NF-κB activity in vitro, it was reported that
subtle changes in ITC structure had a profound impact on inhibition potential (Prawan et al.,
2009). Therefore, in addition to the amount consumed, the variety of cruciferous vegetables
ingested may also influence biological response. However, differential effects of cruciferous
55
vegetables with diverse GSL profiles have not been directly compared in vivo in humans
(Navarro et al., 2011).
To date, a major impediment to our understanding of the chemopreventative
mechanisms stimulated by GSLs is that relatively little is known about the biological effects
of GSL breakdown products other than ITCs and the indole-containing derivatives.
Specifically, there are little data about chemopreventative activities of TCs, NITs, cyano-
epithioalkanes and oxazolidine-2-thiones. Our group showed that 3-butenyl-ETN showed
some toxicity at high dose (0.1 mM) on MCL-5 cells and cHo1 cells. Other products including
2-propenyl-ETN, 2-propenyl NIT and 3-butenyl NIT were, at most, marginally toxic (Nurul
Huda Binti Abd Kadir, PhD thesis). ANIT has also been shown to induce antioxidant and
detoxification enzymes (Tanii et al., 2008). The question of whether ETN and NIT products of
GSL degradation also have chemopreventative properties still remains unanswered. Also, it
is unclear whether the formation of TCs, NITs, cyano-epithioalkanes and oxazolidine-2-
thiones from GSLs, at the expense of forming ITCs, is undesirable from a cancer
chemoprevention perspective (Hayes et al., 2008). These are areas that warrant further
examination.
1.6.2 Preventive effects against diseases
Unlike most small molecule pharmacological agents that affect single targets, the
intracellular targets of ITCs are multiple. For example, activation of transcription factor Nrf2
alone caused by ITC exposure leads to an orchestrated upregulation of an extremely large
network of genes with cytoprotective, antioxidant, and anti-inflammatory functions. It is this
ability to induce versatile and long-lasting responses, which ultimately protects against
oxidative stress, electrophilic stress, and chronic inflammation (the three main underlying
causes of most chronic diseases) that makes ITCs exceedingly efficient protective agents
(DinkovaKostova et al., 2012). Not only chemopreventive ability, but ITCs especially SFN also
has the potential to reduce the risk of diabetes (Cui et al., 2012; Miao et al., 2012; Xue et al.,
2008), atherosclerosis (Kwon et al., 2012; Kivela et al., 2010), respiratory diseases (Ritz et al.,
2007; Riedl et al., 2009), neurodegenerative disorders (Ping et al., 2010; Dash et al., 2009),
ocular disorders (Kong et al., 2007; Gao et al., 2004), and cardiovascular diseases (Zakkar et
al., 2009; Angeloni et al., 2009).
56
It is known that oxidative stress is a link between cardiovascular risk factors and
vascular disease, and thus a target for cardiovascular prevention. SFN exhibits cytoprotective
effects i.e. increase in cell viability and decline in DNA fragmentation in neonatal cardiac
myocytes. This is mediated by the increase in the expression of multiple antioxidant proteins
and reduction of reactive oxygen species (ROS) production (Angeloni et al., 2009). In
addition, SFN was shown to induce the activity of antioxidants and phase II enzymes such as
catalase, superoxide dismutase, glutathione peroxidase, glutathione reductase, glutathione
S-transferase, NAD(P)H:quinone oxidoreductase-1 and glutathione in rat aortic smooth
muscle cells and isolated mitochondria of aortic smooth muscle cells (Zhu et al., 2008). Other
ITCs have exhibited neuroprotective activity in either in vitro or in vivo models of neuronal
cell death or neurodegeneration, respectively (Kelsey et al., 2010). They are directly able to
scavenge free radicals or indirectly increase endogenous cellular antioxidant defenses via
activation of the Nrf2 transcription factor pathway. Interestingly, SFN was shown to prevent
metabolic dysfunction in an in vitro model of hyperglycemia by preventing the increasing
cellular accumulation of the glycating agent methylglyoxal (Xue et al., 2008).
1.6.3 Genotoxicity of ITCs
Genotoxicity refers to the ability of chemicals to damage DNA and/or cellular
components regulating the genome fidelity such as the topoisomerases, spindle apparatus,
DNA polymerases and DNA repair systems (Wobus & Löser, 2011). All adverse effects on
genetic information are also included (Fimognari et al., 2011).
While normal consumption of cruciferous vegetables seems to be beneficial to
human health, any large increase in intake could conceivably lead to undesirable effects. A
partial overlapping between the chemopreventive doses of ITCs and those exhibiting
genotoxic potential can be seen for most ITCs (Fimognari et al., 2011). For example, BITC
exerts in vitro protective effects against cancer development in the range 0.01–50 μM and
genotoxicity even at the dose 0.1 μM (Kassie et al., 1999). PITC exhibits cancer protective
effects in the interval 0.1–100 μM and the genotoxic effects in the interval 2–613 μM (Musk
et al., 1995). The same is true for SFN with the in vitro cancer protective effects appear in
the interval 0.1–2,000 μM, the neuroprotection in the range 0.01–10,000 μM and the
genotoxic effects in the interval 10–140 μM (Musk et al., 1995). As far as the in vivo studies
57
go, only AITC exhibits protective effects at levels of doses lower than those that resulted in
genotoxicity (Kassie et al., 2000). Particular attention should be paid to BITC and PITC as they
show a clear genotoxic potential at doses endowed with a chemopreventive potential. The
mechanisms of genotoxicity are complex and some of them very specific and linked to the
presence of the ITC group. SFN analogues with oxidized sulfur (e.g. erysolin) are potent
inducers of ROS. However, ERN, at the same dose levels, had no such effect (Kim et al., 2010).
It was concluded that some ITCs possess a genotoxic activity, but not all. The
potential threats associated with the intake of different ITCs are characterized by a different
toxicological profile. These findings need to be verified and extended by further studies. The
genotoxic effects of ITCs in vivo are needed to be studied as thus far in vivo data are only
available for AITC, BITC, PITC and methyl ITC. However, it is highly unlikely that such
toxicities would occur in humans, because dietary consumption levels of those ITCs and ITC
exposure in humans appear to be several orders of magnitude lower than the doses found in
the animal studies (µmol vs mmol, repectively) (Fimognari et al., 2011).
1.7 Bioavailability of GSL degradation products in humans
When brassica vegetables are cooked, a partial or total inactivation of myrosinase
can occur. Various factors also lead to variations in bioavailability of GSLs and GSL
degradation products (Dekker et al., 2000). These changes are primarily resulted from the
type of vegetable matrix, the extent of its cellular disruption, the duration and method of
cooking and the chemical structure of the GSL precursors (Rungapamestry et al., 2007).
Interestingly, it was shown that the overall average bioavailability of ITCs is 61% and 10% for
raw and cooked cruciferous vegetables, respectively (Vermeulen et al., 2006; Melchini &
Traka, 2010). After consumption of cooked brassica with heat inactivated plant myrosinase,
GSLs are hydrolyzed in the colon action by the gut microbiota. Feeding trials with human
subjects have shown that degradation of GSLs and absorption of ITCs are greater following
consumption of raw brassica with active plant myrosinase than after ingestion of the cooked
plant with inactive myrosinase (Rungapamestry et al., 2007). The digestive fate of GSLs may
be further influenced by the extent of cell rupture during ingestion, gastrointestinal (GI)
transit time, meal composition, individual genotype and differences in colonic microbiota.
The differences in epidemiological evidence relating preventive effects of brassica
58
consumption against cancer in man, especially in cohort studies (International Agency for
Research on Cancer, 2004) may be partly explained by these causes of variation, coupled
with differences between individuals in the metabolism of isothiocyanates (Seow et al.,
2005). A better knowledge of the digestive and absorptive fate of dietary GSLs and their ITC
metabolites has emerged mostly from mechanistic studies in animal models such as rats and
hamsters (Brusewitz et al., 1977; Mennicke et al., 1983; Michaelsen et al., 1994; Duncan et
al., 1997; Elfoul et al., 2001). The low recoveries of intact GSLs and their metabolites in
faeces of animals fed GSLs or ITCs suggest that a substantial proportion of ingested GSLs and
ITCs are metabolized in vivo (Slominski et al., 1988; Bollard et al., 1997; Rouzaud et al.,
2003). However, there is little information on the degradation of GSLs during and after
consumption of brassica vegetables by human subjects. The complexity of the GSL–
myrosinase system and the host of factors are likely to influence the degradation of GSLs in
vivo, this information is important in understanding the physiological consequences of
brassica consumption. Studies with human subjects have used urinary biomarkers to assess
the absorption of ITCs after the intake of GSLs from brassica vegetables (Getahun et al.,
1999; Conaway et al., 2000; Shapiro et al., 2001; Rouzaud et al., 2004). Following their
absorption into the intestinal epithelium, ITCs are released into the systemic circulation and
metabolized by the mercapturic acid pathway in the liver (Rungapamestry et al., 2007). ITCs
initially form conjugates with glutathione, then undergo enzymic modification and are
excreted in urine as their corresponding N-acetylcysteine (NAC) conjugates i.e. mercapturic
acid (MA) (Brusewitz et al., 1977; Mennicke et al., 1983). Urinary isothiocyanate mercapuric
acid (ITC MA) excretion therefore partially reflects ITC absorption in vivo, although variation
in pre- and post-absorptive recovery may also be important. The metabolic fate of GSLs and
ITCs following consumption of brassica within experimental meals by volunteers is shown in
Figure 1.7. Thus far, only the ITC MAs have been studied as urinary biomarkers of GSL
degradation in vivo. This approach has provided a reasonable understanding of the overall
uptake of ITCs after consumption of brassica by human subjects (Chung et al., 1998;
Mennicke et al., 1988).
59
Figure 1.7 Expected metabolic fate of glucoraphanin and AITC following ingestion of cooked broccoli (Brassica oleracea var. italica) and mustard (Sinapis alba) respectively by human volunteers. Following absorption, the ITC are metabolized by the mercapturic acid pathway. Initially, they are conjugated with glutathione in a glutathione transferase (GST)-catalyzed reaction and finally N-acetylcysteine conjugates (mercapturic acids) are formed. This figure was modified from Rungapamestry et al., (2007).
The metabolism of GSL degradation products and their bioavailability may be
influenced by inter-individual variations. This hypothesis is generally poorly understood and
controversial. The absorption of ITCs has been shown to vary, although not markedly,
between individuals. Low inter-individual variation has been observed after the ingestion of
AITC in the form of mustard, with recovery of 60–90% of the administered doses of AITC
(Rouzaud et al., 2004). Inter-individual variation is 1.5-fold greater after the ingestion of
cooked watercress than after raw watercress (Getahun et al., 1999), indicating that there
may be inter-individual differences in the colonic degradation of GSLs, as well as other
factors such as gastrointestinal transit time, extent of chewing and genotype.
Polymorphisms in genes coding for the activity of GST isoforms have been described (Seow
et al., 2005), and they may explain inter-individual variation in the metabolism and excretion
of ITCs. The role of GSTs involves detoxification of a wide range of electrophiles by
conjugation with glutathione. Particularly, glutathione S-transferase Mu 1 (GSTM1) was
shown to use ITCs as substrates (Kolm et al., 1995). Null genotypes for GSTM1 and
60
glutathione S-transferase Theta 1 (GSTT1) lead to the absence of their respective enzymes.
Therefore, ITC may be metabolized more slowly among GSTM1-null and GSTT1-null
individuals and consequently increase the tendency of upregulation of other GST isoenzymes
(Ketterer et al., 1998; Lin et al., 1998). Individuals with GSTM1- and/or GSTT1-null genotypes
have been shown to be at reduced risk of developing colorectal and lung cancers after the
intake of ITCs (Keum et al., 2004). The low GST activity and a slower rate of excretion of ITCs
in these individuals may help retain more ITCs at target tissues (e.g. colon) and provide a
pro-apoptotic effect in situ (Johnson, 2004).
When myrosinase is deactivated by cooking, the ionised nature of GSLs may be
expected to enable them to reach the distal gut where they could be transformed by
bacterial enzymes. This speculation was first examined and confirmed by studies in which
antibiotic treatments were used to reduce the large bowel microbiota (Slominski et al.,
1987; Shapiro et al., 1998). Reducing the microbial digestion by a combination of mechanical
cleansing and antibiotics caused a dramatic reduction (8.7-fold) of ITCs as dithiocarbamate
excretion from 11.3 ± 3.1% of the initial dose to 1.3 ± 1.3% (Shapiro et al., 1998). As these
are human data, there seems to be no doubt about the importance of the gut microbiota in
digestive ITC formation.
More direct evidence was eventually obtained from gnotobiotic experiments. A
whole faecal microflora from rats or humans was introduced into initially germfree rats, and
resulted in the disappearance of intact GSLs in the cecal and colonic contents, coupled with
the emergence of systemic effects reflecting GSL degradation (Nugon-Baudon et al., 1988;
Rabot et al., 1993; Campbell et al., 1995). It appears that the ability to degrade GSLs is widely
distributed among intestinal bacteria (Oginsky et al., 1965). Representatives of various
genera (e.g. Bacteroides, Peptostreptococcus, Enterococcus, Escherichia, Proteus) have been
isolated from human faeces. These bacteria were able to degrade progoitrin and sinigrin in
vitro (Rabot et al., 1995). Bifidobacterium sp., B. pseudocatenulatum, B. adolescentis, and B.
longum showed the ability to digest GSLs, sinigrin and glucotropaeolin in vitro (Cheng et al.,
2004).
The formation of AITC from sinigrin in the digestive tract of rats mono-associated
with a human gut strain of Bacteroides thetaiotaomicron has been reported with the
possible involvement of bacterial myrosinases (Elfoul et al., 2001; Rouzoud et al., 2004). The
61
degradation of GSLs by the human colonic microbiota has been studied in some detail in a
dynamic in vitro large-intestinal model (Krul et al., 2002). The study was carried out with
sinigrin which was shown to be degraded to AITC. The degree of conversion depended on
the concentration of sinigrin used and the nature of the inoculum. Since not all the ITC was
accounted for, possibly further metabolism was indicated to unidentified metabolites.
As yet, little is known of the structure of microbial GSL derivatives. A detailed analysis
of GSL degradation by human digestive microbiota has been carried out using 1H NMR on
both sinigrin and glucotropaeolin. By using this technique, it was shown that allylamine and
benzylamine were exclusively produced from these GSLs, respectively (Combourieu et al.,
2001). However, this appears to conflict with the later report where only ITCs were detected
(Krul et al., 2002). Upon anaerobic incubation of cooked watercress juice with human faeces,
18% of GSLs are hydrolyzed to ITCs in 2 h (Getahun et al., 1999). The contribution of the
digestive microbiota to ITC production, in vivo and in the distal gut, has been ascertained.
Following gavage with 50 µmol sinigrin, substantial amounts of AITC (up to 100 nmol at 12 h
after dosing) were measured in the cecal and colonic contents of gnotobiotic rats harbouring
a human digestive strain of Bacteroides, while no allyl nitrile (ANIT) could be detected (Elfoul
et al., 2001). It may be speculated that NITs were formed, but were not detectable because
they were readily transformed into other metabolites. This hypothesis is supported by
observations on ANIT degradation in sheep rumen fluid (Duncan & Milne, 1992) and by
reports on the ability of various microorganisms to convert NITs to organic acids and
ammonia (Kobayashi & Shimizu, 1994).
The formation of other derivatives, e.g. desulfo-glucosinolates (DS-GSLs) and TCs, has
scarcely been investigated, and studies are often not conclusive, chiefly because of analytical
impediments (Slominski et al., 1988; Rowan et al., 1991). Nevertheless, the versatility of
microbial enzymatic activities would be expected to lead to a wider array of metabolites
than those so far identified. The post-absorptive fate of GSL derivatives other than ITCs has
received comparatively little attention. TCs may be converted to cyanide and thiol
derivatives by GSTs (Ohkawa et al., 1972) and ETNs may be excreted in the form of MAs
(Brocker et al., 1984).
To date, GSL degradation by the colonic microbiota, have been much less
investigated than GSL degradation by plant myrosinase in plant material or food products.
Therefore, microbial digestions of GSLs need to be fully addressed to improve an
62
understanding of bacterial GSL-degrading enzyme occurrence/activity and the bioavailability
of GSL degradation products in the human gut.
1.8 Human gut microbiota The human gut microbiota is a complex ecosystem (Tap et al., 2009) that is estimated
to be composed of approximately 1014 bacterial cells—which is ten times more than the
total number of human cells in the body (Savage et al., 1977). There are more than 800
species of bacteria in the human gut with 30–40 species dominating this community,
comprising up to 99% of the total population (Rouzaud et al., 2004). The gut microbiome, a
term for the collective community of bacteria and their total genome capacity in the human
gut, is approximately 150 times larger than the human gene complement. With an estimated
3.3 million microbial genes, it has been referred to as the 'forgotten organ' and a
'superorganism' (Qin et al., 2010; Gill et al., 2006; O’Hara et al., 2006). Seven phyla
constitute the bulk of the gut microbiota, namely Firmicutes, Bacteroidetes, Proteobacteria,
Fusobacteria, Verrucomicrobia, Cyanobacteria and Actinobacteria. The Firmicutes and
Bacteroidetes phyla accommodate the most abundant species and constitute over 90% of
the human gut microbiota (Eckburg et al., 2005; Backhed et al., 2005; Tap et al., 2009). As
early as 1907, it was hypothesized that replacing or diminishing 'putrefactive' bacteria in the
gut with lactic acid bacteria could improve bowel health and prolong life (Metschnikoff et al.,
1907). Since the 1990s, interest has grown in the role that the human gut microbiota has in
disease. To date, metagenomics and human microbiome research have arrived at the
forefront of biology mainly due to major technical and conceptual developments (Devaraj et
al., 2013). One of the most important objectives in human microbiome research is to
understand the symbiotic relationship between gut microbes and their host and to find any
correlation between microbes and diseases. Large-scale projects such as the US Human
Microbiome Project (HMP) (The Human Microbiome Project Consortium, 2012) and the
European Metagenomics of the Human Intestinal Tract (MetaHIT) (Qin, J. et al., 2010) have
made a vast stride towards this goal.
Accumulating evidence since the burst of human gut microbiome research and
metagemomics suggest that the gut microbiota play a role in the regulation of several host
metabolic pathways. That results in interactive host-microbiota metabolic, signaling, and
63
immune-inflammatory axes that physiologically connect the gut, muscle, liver and brain
(Nicholson et al., 2012; Holmes et al., 2012). The gut microbiota fights against
enteropathogens (Fukuda et al., 2011), extracts nutrients and energy from our food
(Yatsunenko et al., 2012), and boosts normal immune function (Olszak et al., 2012).
Disruptions to the normal balance between the gut microbiota and the host have been
correlated with obesity (Kallus & Brandt, 2011), malnutrition (Smith et al., 2013; Trehan et
al., 2013), inflammatory bowel disease (IBD) (De Cruz et al., 2012; Mann & Saeed, 2012)
neurological disorders (Bercik et al., 2012; Dinan & Cryan, 2012) and cancer (Kostic et al.,
2012; Tjalsma et al., 2012; Chen et al., 2012). Moreover, a growing body of evidence
indicates that the gut microbiota can communicate with the central nervous system possibly
through endocrine, neura and immune pathways and therefore affects brain function and
behavior (see Review by Cryan et al., 2012). The impact of intestine on human health is
summarised in Figure 1.8.
Figure 1.8 The intestine's impact on health. The gastrointestinal (GI) tract contributes to health by ensuring digestion and absorption of nutrients, minerals and fluids; by induction of mucosal and systemic tolerance; by defence of the host against infectious and other pathogens; and by signalling from the periphery to the brain. This figure was taken from Bischoff (2011).
64
Importantly, the diet is considered a primary factor that influences gut bacterial
diversity, and thus may alter its functional relationships with the host (Ley et al., 2008). A
variety of enzymatic activities from human gut microbiota with crucial influence on human
health through biotransformation of secondary plant products and xenobiotic compounds
have been reported (McBain et al., 1998; Heavey & Rowland, 2004; Blaut & Clavel, 2007).
Among a plethora of genes that have been identified in the human gut microbiome,
those that encode carbohydrate-active enzymes (CAZymes) are of particular importance, as
these enzymes are required to digest most of dietary polysaccharides to fermentable
monosaccharides. Most enzymes that cleave glycosidic bonds between carbohydrates or
between a carbohydrate and a non-carbohydrate moiety by hydrolysis (addition of water)
are categorized into enzyme family glycoside hydrolase (GH)(Henrissat 1991; Koropatkin et
al., 2012). At present, GHs are classified into 130 families with the conservation of amino
acid sequences, catalytic residues, molecular mechanism and stereochemical outcome
among members of a given family. GH classification uses the IUB Enzyme Nomenclature
(1984) based on the type of reaction that GH enzymes catalyse and on their substrate-
specificity. For GHs (EC 3.2.1.x), the first three digits indicate enzymes hydrolyzing O-glycosyl
linkages whereas the last number indicates the substrate and sometimes reflects the
molecular mechanism. However, such a classification does not always reflect the structural
features of GH enzymes (Henrissat 1991).
The CAZy database is a knowledge-based resource specialized in the enzymes that
build and breakdown complex carbohydrates and glycoconjugates (Cantarel et al., 2009).
The substrates hydrolyzed by members of a CAZy family are structurally diverse however
they display conserved characters such as the orientation of the glycosidic bond (axial or
equatorial) and often have a functional commonality such as being present in animal or
plant cell wall carbohydrates (Kaoutari et al., 2013). Therefore, assigning several GH families
to broad substrate categories that can facilitate the annotation of the encoding genes is
possible (Cantarel et al., 2012). If a primary degrader was designated as a bacterium that is
able to digest a complex carbohydrate due to enzymatic capacity that is missing in other
species, each complex carbohydrate may well have many different primary degraders. In
healthy adults, it was reported Bacteroidetes members in the faecal microbiota can vary
from ~15% to ~90% in the proportional representation, and that of Firmicutes members
65
varies from ~70% to ~5% of the microbiota (The Human Microbiome Project, 2012). Such
compositional variations would give rise to substantial differences in the capacity of the
microbiota to degrade complex polysaccharides provided that there is a strong difference in
CAZyme content and diversity between these two phyla. Thus, CAZymes can serve as a
useful biomarker of the functional diversity of the human gut microbiota.
1.9 Cruciferous vegetables can alter human gut microbiota communities
In spite of minor fluctuation over a short period of time, the gut bacterial community
of healthy adults is considered relatively stable (Delgado et al., 2004). However, this
community was altered by short-term dietary shifts, commonly found in controlled dietary
interventions (Gibson et al., 1995; Langlands et al., 2004; Smith et al., 2006; Costabile et al.,
2008). Several dietary components, e.g. dietary fibers such as cellulose, hemicelluloses, and
pectin (Bourquin et al., 1993), and other compounds such as lignans (Milder et al., 2007) and
GSLs (Fahey et al., 2001) present in cruciferous vegetables can be used as metabolic
substrates for certain human gut bacteria. For example, cellulose can be transformed to
short-chained fatty acid (SCFA) by Bacteroidetes (Robert et al., 2007). Lignans such as
secoisolariciresinol can be degraded in vitro by certain Eggerthella and Peptostreptococcus
isolated from human feces (Clavel et al., 2005). GSLs can also be metabolized in vitro by E.
coli, E. faecalis, B. thetaiotaomicron, E. faecium, certain Bifidobacterium spp. and
Peptostreptococcus spp. (Brabban et al., 1994; Rabot et al., 1995; Elfoul et al., 2001; Cheng
et al., 2004).
It was thought that constituents of high-cruciferous vegetable diets are likely to
influence the growth of certain bacteria in the human gut bacterial community and
ultimately modify the community composition (Li et al., 2009). Terminal restriction fragment
length polymorphism (tRFLP) fragments technique revealed that Alistipes putredinis,
Eubacterium hallii, Phascolarctobacterium faecium and Eggerthella spp. were associated
with cruciferous vegetable intake, and Burkholderiales was associated with the cruciferous
vegetable-free diet (Li et al., 2009). This substantial difference in the bacterial community
structure among individuals was also reported that is in agreement with other previous
studies (Ley et al., 2006; Eckburg et al., 2005). Bacterial species with the same metabolic
functions associated with cruciferous vegetable intake may not be closely related
66
phylogenetically. For example, incubations with GSLs in vitro showed that bacteria able to
hydrolyze GSLs come from several different phylogenetic families, including Actinobacteria,
Firmicutes, and Bacteroidetes (Brabban et al., 1994; Rabot et al., 1995; Elfoul et al., 2001;
Cheng et al., 2004). Phylogenetic analysis of the glycosidase gene family shows that the
activity of hydrolyzing GSLs is not conserved within one discrete phylogenetic group of
bacteria (Mian, 1998). Since different individuals may have different types of distantly
related bacteria having GSL-degrading activity, it is likely that GSL consumption can either
trigger or suppress different species in the gut bacterial community (Li et al., 2009).
1.10 Hypotheses
The hypotheses of this PhD project are as follows:
Certain human gut bacteria can metabolise GSLs to ITCs and/or NITs like plant and
aphid myrosinases and cetain human gut bacteria can modify the GSL side chain and the
nature of GSL degradation products.
Different GSL-degrading bacteria may degrade identical or different GSLs at different
rates
Several enzymes may be involved in GSL metabolism in GSL-degrading bacteria.
1.11 Objectives To test the above hypotheses, the objectives are set as follows:
To isolating and identifying GSL-degrading bacteria from human faecal sample.
To identify the degradation products of different types of GSLs and certain DS-GSLs
metabolized by individual bacteria. Cell-free extract and resting cells experiments
were performed to detect bacterial GSL-degrading activity in vitro and to test its
inducibility (Chapter 2).
To identify bacterial enzymes potentially involved in the metabolism of GSLs via
forwards proteomics approach by using two-dimension electrophoresis (2-DE) gels
(Chapter 3).
To identify and characterize bacterial enzymes potentially involved in the metabolism
of GSLs via reverse proteomics approach by using Basic Local Alignment Search Tool
(BLAST) searches, molecular cloning, protein purification techniques and enzyme
activity assays (Chapter 4 and 5).
67
Chapter 2: Metabolism of different GSLs and DS-GSLs by human gut bacteria 2.1. Introduction:
2.1.1 GSL degradation by human gut microbiota
To date, a number of microorganisms including bacteria and fungi have been
reported for their GSL-degradation properties. The better understanding of myrosinase
occurrence is important for both biological and biotechnological aspects of food and feed
industries. Most work has concentrated on the characterization of GSL degradation by intact
microbial cells (Maheshwari et al., 1981; Palop et al., 1995; Rakariyatham & Sakorn, 2002)
and several reports have shown myrosinase production from Aspergillus sp. (Ohtsuru & Hata,
1973; Sakorn et al., 1999). Previous in vitro studies have observed that bacteria able to
hydrolyze GSLs belong to several different phylogenetic families including Actinobacteria,
Firmicutes and Bacteroidetes (Brabban & Edwards, 1994; Cheng et al., 2004; Elfoul et al.,
2001; Palop et al., 1995; Rabot et al., 1995). Phylogenetic analysis of various β-glucosidase
genes also showed that they are not solely attached to one bacterial phylogeny (Mian, 1998).
Bacteria from different phylogenetic groups may have relevant genes to code enzymes
involved in releasing glucose from complex molecules in the gut environment for energy
utilisation. Degradation of GSLs in the colon or caecum has been known for some time
(Rabot et al., 1995). The gastrointestinal microflora of rats and poultry has the ability to
hydrolyze GSLs (Krul et al., 2002; Nugon-Baudon et al., 1990; Nugon-Baudon et al., 1988;
Slominski et al., 1988). Once cruciferous vegetables are consumed, humans rely on gut
bacteria in GSL conversion to ITCs since vigoruous cooking tends to deactivate degradative
enzymes. The significance of human gut bacteria in producing ITCs was demonstrated in a
previous feeding study showing a dramatic decline in urinary ITC excretion after cruciferous
vegetable consumption when volunteers were pre-treated with antibiotics and bowel
cleansing (Shapiro et al., 1998).
Out of above 800 bacterial species in the human gut community, up to 99% of the
total population come from dominant 30–40 species (Bäckhed et al., 2005). A distinct
68
combination of bacteria species from each person may ultimately contribute to inter-
individual differences in metabolism of dietary constituents and hence health status of the
host. To date, in vitro experiments incubating mixed or pure cultures of bacteria with GSLs
have confirmed that several bacterial species residing in the human gut, such as E. coli, B.
thetaiotaomicron, E. faecalis, E. faecium, L. agilis, certain Peptostreptococcus spp. and
Bifidobacterium spp., have the ability to metabolize GSLs in culture (Brabban & Edwards,
1994; Cheng et al., 2004; Elfoul et al., 2001; Palop et al., 1995; Rabot et al., 1995). In addition
to the amount of consumed cruciferous vegetables, the composition of gut bacterial
community may influence exposure to bioactive ITCs and ultimately determine cancer risk of
the hosts.
2.1.2 Metabolic diversity of the intestinal microbiota
The GI tract is a habitat for a large number of bacteria with a contribution to normal
digestive function. Most intestinal microbiota residing in the large intestine has the primary
function to anaerobically degrade and ferment organic matter i.e. protein and carbohydrate
into absorbable energy. The main production of this process is SCFA including butyrate,
propionate and acetate and also gases e.g. H2, CO2 and CH4 (in some cases). Especially,
butyrates are known to have a crucial role in gut environment and health (Pryde et al.,
2002). The contribution of different functional groups of microbiota linked in a trophic chain
is required to operate this complex microbial fermentative process. These bacteria can
produce a variety of hydrolytic enzymes that transform complex substrates into smaller
fragments. Further fermentation of these fragments is carried out by these hydrolytic
bacteria and also by other bacterial communities able to utilize the released breakdown
products. In comparison with other bacterial communities, human gut bacteria have more
diverse enzymes that enable them to metabolize drugs and other xenobiotics to a much
further extent (Scheline, 1973; Abu Shamat, 1993; Mikov, 1994). It has been suggested that
the gut microbiota can function as an organ with a metabolic capacity at least equivalent to
the liver (Scheline, 1973). However, the important differences between hepatic and bacterial
metabolism are that the liver is primarily responsible for oxidative and conjugative
metabolisms that produce polar high molecular weight metabolites while reductive and
hydrolytic reactions are prevalent in the gut microbiota generating non-polar low molecular
weight byproducts. Thus far, at least thirty commercially available drugs were substrates for
69
bacterial enzymes (Sousa et al., 2008) and presumably there are many more from the new
and existing drugs (with the potential for contact with the distal gut) to be discovered. Some
metabolic reactions of intestinal microbiota from either humans or rats are presented in
Table 2.1.
Table 2.1 Some metabolic reactions of intestinal microbiota
Reactions Example References
Reductions
Nitro compounds Clonazepam, nitrazepam Elmer & Remmel 1984; Takeno et al., 1990; Rafii et al., 1997
Sulfoxides Sunlindac, sulfinylpyrazone Strong et al., 1987; Strong et al., 1984b 21-Hydroxycorticoids Aldosterone Miyamori et al., 1988 Double bonds Digoxin, daidzein Reuning et al., 1985; Rafii et al., 2007 Azo compounds Prontosil Gingell et al., 1971 Amides Zonisamide Kitamura et al., 1997
Degradation
Nitrate esters
Glyceryl trinitrate, isosorbide dinitrate
Abu Shamat & Beckett 1983; Abu Shamat, 1993
Sulfate esters Sodium picosulfate Jauch et al., 1975 Succinate esters Carbenoxolone Iveson et al., 1971 Amides Methotrexate, chloramphenicol Valerino et al., 1972; Holt, 1967 Glucuronides Morphine glucuronide Walsh & Levine, 1975; Schneider et al., 1999
Glucosides sennosides, quercetin-3-glucoside Hersperidin Lee et al., 2004
Arabinofuranocyl Sorivudine Okuda et al., 1998
Proteolysis Hormones Insulin, calcitonin Tozaki et al., 1997
Removal of functional groups
N-Dealkylation Methamphetamine Caldwell & Hawksworth, 1973 Deamination Flucytosine Vermes et al., 2003 N-oxide bond cleavage Ranitidine Basit & Lacey, 2001
Other reactions Heterocyclic ring
fission Levamisole Shu et al., 1991 Side-chain cleavage Steroids Cerone-McLernon et al., 1981 Acetylation 5-Aminosalicylic acid van Hogezand et al., 1992 Isoxazole scission Risperidone Meuldermans et al., 1994
70
2.1.3 Characterization of human gut microbiota
Our understanding of the gut microbiota, how it interacts with the host and causes
human disease, has been enhanced by advances in culture-independent techniques for
phylogenetic investigation and quantification. Comprehensive knowledge of the entire gut
microbiota is neccessary to understand relationships between the gut microbiota and
disease. Culture and biochemical typing were the gold standards for the identification of
bacterial species for many years. Since the 1990s, however, culture-independent techniques
have transformed our knowledge of the gut microbiota as they are able to give a more
representative 'snapshot' of this niche (Rajilić et al., 2007; Zoetendal et al., 2006). These
techniques are based on sequence divergences of the small subunit ribosomal RNA (16S
rRNA), and are able to demonstrate the following: first, the microbial diversity of the gut
microbiota; second, qualitative and quantitative information on bacterial species; and third,
changes in the gut microbiota in relation to disease. Examples of these techniques include
terminal restriction fragment length polymorphism (tRFLP), denaturing gradient gel
electrophoresis (DGGE), fluorescence in situ hybridization (FISH), DNA microarrays, and next-
generation sequencing of the 16S rRNA gene or its amplicons. The techniques currently used
to characterize the gut microbiota with their advantages and limitations are presented in
Table 2.2.
71
Table 2.2 Advantages and disadvantages of current techniques used to characterize human
gut microbiota
Technique Description Advantages Disadvantages
Culture Isolation of bacteria on selective media Cheap, semi-quantitative
Labour intensive, <30% of gut microbiota have been cultured to date
qPCR
Amplification and quantification of 16S rRNA. Reaction mixture contains a compound that fluoresces when it binds to double-stranded DNA
Phylogenetic identification, quantitative, fast
PCR bias, unable to identify unknown species
DGGE/TGGE Gel separation of 16S rRNA amplicons using denaturant/temperature
Fast, semi-quantitative, bands can be excised for further analysis
No phylogenetic identification, PCR bias
tRFLP
Fluorescently labelled primers are amplified and then restriction enzymes are used to digest the 16S rRNA amplicon. Digested fragments separated by gel electrophoresis
Fast, semi-quantitative, cheap
No phylogenetic identification, PCR bias, low resolution
FISH
Fluorescently labelled oligonucleotide probes hybridize complementary target 16S rRNA sequences. When hybridization occurs, fluorescence can be enumerated using flow cytometry
Phylogenetic identification, semi-quantitative, no PCR bias
Dependent on probe sequences—unable to identify unknown species
DNA microarrays
Fluorescently labelled oligonucleotide probes hybridize with complementary nucleotide sequences. Fluorescence detected with a laser
Phylogenetic identification, semi-quantitative, fast
Cross hybridization, PCR bias, species present in low levels can be difficult to detect
Cloned 16S rRNA gene sequencing
Cloning of full-length 16S rRNA amplicon, Sanger sequencing and capillary electrophoresis
Phylogenetic identification, quantitative
PCR bias, laborious, expensive, cloning bias
Direct sequencing of 16S rRNA amplicons
Massive parallel sequencing of partial 16S rRNA amplicons for example, 454 Pyrosequencing® (Roche Diagnostics GMBH Ltd, Mannheim, Germany) (amplicon immobilized on beads, amplified by emulsion PCR, addition of luciferase results in a chemoluminescent signal)
Phylogenetic identification, quantitative, fast, identification of unknown bacteria
PCR bias, expensive, laborious
Microbiome shotgun sequencing
Massive parallel sequencing of the whole genome (e.g. 454 pyrosequencing® or Illumina®, San Diego, CA, USA)
Phylogenetic identification, quantitative
Expensive, analysis of data is computationally intense
Abbreviations: DGGE, denaturing gradient gel electrophoresis; FISH, fluorescence in situ hybridization; qPCR, quantitative PCR; TGGE, temperature gradient gel electrophoresis; tRFLP, terminal restriction fragment length polymorphism. The table was taken from Fraher et al. (2012).
72
In this work, enrichment culture technique, 16S rRNA gene sequencing and PCR were
employed to characterize human gut bacteria, therefore only these techniques are reviewed
as follows.
2.1.3.1 Enrichment culture technique
Metabolic and genetic characteristics need to be effectively studied in order to
determine the role an organism plays in its environment. Culturing bacteria in a laboratory is
the best way to do this however certain organisms may be found in low abundance in its
environment and cannot be isolated easily using general all-purpose media (Schlegel &
Jannasch, 1967). Since these bacteria are likely to be outgrown by more numerous species, it
is nearly impossible to obtain a pure bacterial culture. Therefore, the knowledge of
nutritional and environmental conditions (including specific energy sources and dependency
on oxygen source) which favor bacterial growth is essential to isolate bacteria (Schlegel &
Zaborosch, 1993).
As pioneered by Winogradsky and Beijerinck (Winogradsky, 1890), enrichment
culture technique was designed to enable a particular type of microorganism to outgrow all
others. For example, a GSL-metabolizing microorganism can be isolated from a soil solution
by using a GSL substrate as the only energy source in liquid media incubated under
anaerobic conditions. This approach has been used to isolate GSL-metabolizing soil
bacterium Citrobacter in our laboratory (Abdulhadi Albaser, PhD thesis). Selective media can
also be used to suppress the growth of unwanted microorganisms so that only the desired
one can grow. In contrast, enrichment media are used to favor the growth of the desired
ones without deliberately inhibiting the others. The effects of these two medium types are
occasionally the same while other organisms might not grow due to the specific makeup of
the enrichment medium (Jennings & Isaac, 1995). Three general strategies used in an
enrichment culture are as follows;
(i) Chemical strategies: include using a specific energy source such as a GSL substrate
that enriches for microorganisms with specific capacity to metabolize it as an energy source.
Acidophilic organisms can also be selected for by controlling the pH to between 4.0 and 5.4.
(ii) Physical strategies: include incubating at high or low temperature which would
select for thermophilic (heat loving) or psychrophilic (cold loving) microorganisms. Anaerobic
organisms can be selected for by incubating the cultures without oxygen.
73
(iii) Biological strategies: include using a live host to enrich for a particular type of
bacterial virus.
Enrichment cultures can be used to enumerate microbial populations in a sample. By
using a dilution endpoint series, the inoculum is serially diluted in a sterile medium, and
numerous tubes of medium are inoculated with aliquots of each successive dilution. The
purpose of this is to minimize the probability of introducing even one individual into a given
tube in a series of tubes with a dilute microbial suspension. Thus, only the organism of
interest will grow in the last dilution at the endpoint (Claus, 1995). This technique is
relatively easy to be used in the search for new microbial types by selecting for organisms
with specific capabilities. However, contamination is likely to occur and the numbers of
microorganisms isolated from the enrichment cultures never represent the true numbers
found in their environment.
Knowledge of the gut microbiota was limited to culture-based techniques, an
approach that has been used since the early 20th century. Since then, advances have been
made in the phenotyping of isolates on the basis of their fermentation profiles and in vitro
growth requirements. Although bacterial identification by culture is fairly cheap, it is labour
intensive, and culture alone gives a limited view of the diversity of the gut microbiota
because < 30% of gut microbiota members have been cultured to date (Eckburg et al., 2005;
Guarner & Malagelada, 2003). It is important to remember that uncultured organisms in the
gut microbiota are not necessarily unculturable. They might, in fact, be culturable but
permissive growth conditions for these organisms have not yet been developed or
discovered.
2.1.3.2 16S rRNA gene analysis
Ribosomes (70S) are dispersed throughout the cytoplasm of a bacterial cell and made
up of two subunits: 30S and 50S. The 50S subunit contains two RNA molecules: 5S and 23S.
The 30S subunit (or small subunit) contains one RNA molecule: 16S ribosomal RNA (16S
rRNA). One of the functions of 16S rRNA is the initiation and extension of protein synthesis.
As rRNA (5S, 16S and 23S) is highly conserved between bacterial species, yet contains
variable regions that yield a phylogenetic signal, it is a useful target for phylogenetic
identification i.e. bacterial identification. Of the three bacterial rRNA genes, the 16S rRNA
74
gene provides the most tractable combination of conserved sites for PCR primers. Its
variable regions as evolutionary chronometers are usually used in preference to 5S or 23S
rRNA genes for phylogenetic identification (Clarridge, 2004; Olsen et al., 1986; Rajendran et
al., 2011). Most (but not all) contemporary culture-independent techniques for the analysis
of the gut microbiota are thus based on analysis of the 16S rRNA gene.
2.1.3.3 Polymerase chain reaction (PCR)
Although PCR has been a huge technical advance across the medical field, it has
limitations; each physical, chemical, and biological step—from retrieving a sample to the
resulting 16S rRNA amplicons—represents a potential source of bias (Wintzingerode et al.,
1997). For example, differential lysis of microbial cells can affect the final apparent
microbiota composition. Gram-positive organisms typically require rigorous conditions to
lyse the bacterial cell wall (which is thicker than in Gram-negative bacteria), while these
same conditions may cause excessive fragmentation of Gram-negative chromosomal DNA
(Olsen et al., 1986). Another major limitation of PCR is that primers must be designed to
target all phyla.
2.1.4 Analytical methods for GSLs and their degradation products
The abundance and structural variety of the GSLs and the fact that each can produce
different breakdown products makes their analysis very complicated (McGregor et al., 1983;
Verkerk et al, 1998). Because GSLs coexist with myrosinase in the plant, cutting or grinding
of fresh tissue in the presence of water will lead to rapid degradation of the parent
compounds, and this adds greatly to the complexity of the problem. In general, the analytical
approach can be divided into methods for total GSLs, individual GSLs and the degradation
products.
For analysis of intact GSLs, inhibition of myrosinase-like activity is essential. Before
disruption of the material, samples should be freeze-dried or frozen in liquid nitrogen to
complete dryness. The use of aqueous methanol for extraction, in combination with high
temperatures, also inhibits myrosinase (Heaney & Fenwick, 1993). Total GSLs yield
equimolar amounts of glucose upon degradation with myrosinase, and methods based on
the measurement of released glucose proved to be relatively rapid and simple to apply
(Heaney et al., 1988). The total GSL content of a food sample can be measured by
75
determining the quantity of glucose released after treatment with the enzyme, but account
must be taken of any endogenous glucose. To achieve this, extraction of GSLs can be
performed followed by a selective clean-up to eliminate free glucose and other interfering
compounds, after which controlled enzymatic release of bound glucose is possible (Mithen
et al., 2000). Several titrimetric and gravimetric methods have been described for the
quantification of the bisulfate ion (unstable aglycone, which after a Lossen rearrangement
produces and equimolar quantity of bisulfate) generated after degradation of GSLs by
myrosinase. There is also a method in which the bisulfate liberated after sulfation is
precipitated with barium chloride, and residual barium is measured by X-ray emission
spectroscopy (Schnug et al., 1987).
The traditional method for the identification and quantification of the individual
derivatised GSLs is gas liquid chromatography (GLC)(Underhill & Kirkland, 1971). Originally,
the GSLs were extracted with boiling water, derivatised and separated by isothermal
chromatography, but substantial improvements have subsequently been made (Thies,
1976). In particular, ion exchange purification of GSL extracts to remove carbohydrates and
other impurities before derivatisation has increased the sensitivity of this method.
Several common liquid chromatography ultraviolet (LC/UV) and liquid
chromatography mass spectrometry (LC/MS) techniques employing ion-pair reagents to
neutralize the charge on the sulfate group of the GSL molecule are used for determining
intact GSLs. Thus, the separation is a property of the functionality of the variable R groups.
Common ion-pair reagents used include tetra-alkyl ammonium bromide in combination with
phosphate buffers, triethylamine in combination with formic acid, and ammonium acetate
buffers (Arguello et al., 1999; Hrnčiřík et al., 1998; Prestera et al., 1996; Zrybko et al., 1997).
The separation and peak shape obtained from intact GSLs are often very poor as tetra-alkyl
ammonium bromide reagents are difficult to dissolve. Other ion-pair reagents produce
marginally better peak profiles, but the separation is still imperfect (Mellon et al., 2002).
More robust and universally applicable LC/MS (and LC/UV) methods are required.
A major breakthrough in GSL analysis has been achieved with the introduction of
enzymatic on-column desulfation using sulfatase (Thies, 1976; Thies, 1978). The introduction
of a desulfation step before derivatisation was performed to eliminate sulfate that
76
interfered with GC analysis. Desulfation was elegantly carried out on the ion exchange
column, using a commercially available sulfatase isolated from an edible snail, H. pomatia.
Free sulfate in the GSL extract, which could inhibit the sulfatase, was precipitated by an
addition of barium acetate and removed by centrifugation before addition of the extract to
the ion exchange column (Vallejo et al., 2004; Mithen et al., 2000).
Since some GSLs, particularly the indoles, are thermally unstable, high performance
liquid chromatography (HPLC) has become the preferred method with the advantage of
direct determination of GSLs. One of the most commonly used method, reversed-phase
HPLC was developed for quantitative analysis of DS-GSLs (Fenwick et al., 1983). In this
method, an on-column enzymatic desulfation treatment of plant extracts is followed by
HPLC detection of the resultant DS-GSLs. Adaptation of the sulfohydrolase (sulfatase)
desulfation method as an HPLC method, although the most widely used method for GSL
separation, is still subject to difficulties in interpretation because of the effects of pH, time
and enzyme activity of the desulfation products (Fahey et al., 2001). Typically, this method
uses response factors determined with purified DS-sinigrin and uses DS-glucotropaeolin as
an internal standard (Brown et al., 2003). Corresponding DS-GSL times, and comparison to
standardized rapeseed extracts, are typically used to validate chromatographic profiles.
Unfortunately, the biological activity of these molecules is compromised by the removal of
the sulfate. After desulfation, they can no longer serve as substrates for myrosinase, and
thus their cognate ITCs are not available for bioassay or direct measurement by
cyclocondensation—key tools in the study of the pharmacokinetics, pharmacodynamics and
bioactivity of these compounds.
HPLC systems using an ultraviolet (UV) detector are very sensitive; levels of DS-GSLs
in the nano-molar range can be detected. Whilst spectral data of individual DS-GSLs will
allow initial confirmation of structural class, the addition of MS detection further improves
the discriminatory power of the technique. DS-GSLs are commonly separated using end-
capped C18 reverse phase columns eluted with water:acetonitrile gradients, whilst isocratic
elution with water:methanol phases has also been reported for the separation of both DS-
GSLs and intact GSLs. Reverse-phase C18 HPLC methods are preferable and more accurate for
determining GSL content. These methods are especially robust, powerful, and selective
77
when they form a component of an optimised negative ion mass spectrometry LC–MS
method (Bennett et al., 2004). One of the major issues in the analysis of GSLs has been the
lack of suitable standards. The only commercially available GSLs are glucotropaeolin and
sinigrin. Sinigrin is not a suitable internal standard due to its presence in most brassicacious
plants, but glucotropaeolin is not normally present in Brassica and has been used as internal
standard. Several mass spectrometric techniques have been investigated for structure
elucidation of the various DS-GSLs e.g. direct probing electron impact, chemical ionisation,
and fast atom bombardment (FAB). Considerable structural information can be obtained
with these techniques. Many years ago, a novel enzyme-linked immunosorbent assay (ELISA)
procedure for the determination of sinigrin and progoitrin in Brussels sprouts extracted with
phosphoric acid, using antisera raised against hemisuccinate-linked GSL conjugates has been
described (van Doorn et al., 1999). The method tended to overestimate GSL content in
comparison to HPLC methods but seems to offer great potential advantages at lower cost
and shorter time for routine analysis in breeding programmes (Mithen et al., 2000).
The volatility of many compounds presents a drawback in the investigation of GSL
breakdown products using HPLC method. Moreover, TCs and NITs are not detectable
spectrometrically, and ITCs/NITs can be analyzed by GLC. Oxazolidinethiones and indoles
may be also analyzed using HPLC with UV detection. A method for analysing
oxazolidinethiones in biological fluids with a high degree of selectivity was developed
(Quinsac et al., 1992). However, HPLC finds most use in the analysis of intact GSLs or DS-
GSLs. For identification and confirmation of structures, both HPLC and GLC can be coupled to
mass spectrometry (MS). Mass spectroscopy has proved to be invaluable in the identification
and structural elucidation of GSLs and their breakdown products. Positive ion FAB mass
spectrometry has yielded mass spectra characterised by abundant protonated and
cationised molecular ions with relatively little fragmentation (Fenwick et al., 1982). In the
negative ion mode, FAB produces an abundant molecular ion (of the GSL anion). This proved
especially advantageous in the analysis of crude plant extracts and mixtures of purified GSLs.
Many years ago, a spectroscopic quantitation of organic ITCs was developed (Zhang et al.,
1992). Almost all organic ITCs react quantitatively with excessive vicinal dithiols under mild
conditions to form five-membered cyclic condensation products with a release of the
corresponding free amines (R-NH2) The method can be used to measure 1 nmol or less of
78
ITCs in crude mixtures and pure ITCs. Some of the methods used for analysis of GSLs and
their degradation products are summarized in Table 2.3
Table 2.3 Listing of some commonly used methods for the analysis of GSLs and their
breakdown products
Compound Method
Total GSL Palladium chloride and thymol assays
Glucose- and sulfate-release enzyme assays
Enzyme-linked immunosorbent assay (ELISA)
Near infra-red reflectance (NIR) spectroscopy; alkaline degradation and thioglucose detection
High resolution nuclear magnetic resonance (NMR) spectroscopy
Individual intact GSL Reverse phase HPLC
Thermospray LC with tandem MS; high performance capillary electrophoresis; capillary GC–MS, GC–MS, GC–MS/MS
DS-GSL Reverse phase HPLC
Degradation products X-ray fluorescence spectroscopy (XRF); GC or GC–MS; HPLC
2.1.5 Hypotheses
The hypotheses on which this chapter is based are as follows:
GSL metabolism in certain human gut bacteria is mediated by bacterial GSL-
degrading activity to produce ITCs and/or NITs like plant and aphid myrosinases.
Certain human gut bacteria can modify the GSL side chain and the nature of the
degradation products.
Different GSLs are metabolized with different efficiencies by the same bacteria and
different bacteria.
The diversity of gut bacteria myrosinases may partly explain the inter-individual
variation in GSL metabolism.
79
2.1.6 Objectives
Based on the above hypotheses, the objectives of this study are as follows:
To isolate and identify GSL-degrading bacteria from a human faecal sample using
enrichment culture technique and 16S rDNA gene analysis, respectively.
To identify and quantify GSL degradation products from the metabolism of different
types of GSLs in individual bacterial fermentations in vitro over a time course using HPLC and
GC-MS analyses.
To identify and characterize bacterial GSL-degrading activity in cell-free extract
experiments and to test its activity on the native gel.
To examine the inducibility of bacterial GSL-degrading activity in resting cells
experiments.
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2.2 Materials and Methods
2.2.1 Preparation of GSL substrates
Pure sinigrin (SNG) was purchased from Apin Chemicals (UK) or purified from
Brassica nigra. Gluconasturtiin (GNT)(ca. 97% purity) from land cress seeds (Barbarea verna),
glucotropaeolin (GTP)(ca. 95% purity) from watercress seeds (Lepidium sativum), glucoerucin
(GER) (ca. 96% purity) from rocket seeds (Eruca sativa), and glucoiberin (GIB) (ca. 95% purity)
from candytuft seeds (Iberis umbellata) were extracted by previously reported method
(Thies, 1988). Glucoraphanin (GRP) (ca. 97% purity) was prepared by further oxidation of
GER following the previous report (Lori et al., 1999). Glucobrassicin (GBS) (ca. 90% purity)
was prepared from wild cabbage seeds (Brassica oleracea).
For each GSL extraction, the previous method (Thies, 1988) was used. The seed
source (100 g) was ground using a coffee grinder (Wahl James Martin ZX595 coffee grinder)
to a fine powder. The seed powder was defatted with petroleum ether (60-80 fractions) by
repeated extraction (7 Xs) after which the residual seed was allowed to dry completely in a
fume hood. The defatted seed was added to boiling methanol (250 mL; 80%) for 20 min to
extract the GSLs, and this step was repeated. The combined methanol extracts were filtered
using filter aid and concentrated using a Rotavapor-210 (Büchi, UK) to dryness at less than
40C under vacuum. The dried extract was re-dissolved in distilled water (120 mL) and
subjected to protein precipitation by adding 9 mL of a Pb(OAc)2:Ba(OAc)2 (1:1; each 0.5 M).
The mixture was cooled at -20C for 15 min and centrifuged at 16,000g for 15 min. The
supernatant was loaded onto a pre-packed diethylaminoethyl (DEAE) - Sephadex A25 in
Econo-Pac column (Bio-Rad, UK). To prepare the column, 1.43 g DEAE-Sephadex A25 (Sigma-
Aldrich, UK) was swollen with 6 M imidazole/0.3% (v/v) overnight, and the excess buffer
decanted and mixed with water (repeated several times). The slurry was poured onto an
Econo-Pac column and washed with water (3 Xs 20 mL). A solution of formic acid/i-
propanol/water (3:2:5) was poured into the column (2 Xs 5 mL) followed by water (4 Xs 5
mL). The 0.5 M K2SO4 solution (25 mL) was poured into the column, and the eluate was
allowed to drop in 25 mL ethanol contained in a 100 mL beaker. The cloudy mixture was
then agitated and cooled for 10 min at 4C. The mixture was then centrifuged at 16,000g for
15 min to remove precipitated potassium sulfate, and the supernatant was then evaporated
81
nearly to complete dryness in a 250 mL round bottomed flask. The dried residues were
dissolved in absolute methanol (8 mL), transferred to a 15 mL Falcon tube and cooled at -20
C for 15 min after which it was centrifuged for 15 min at 4C. Only the supernatant was
evaporated in a 100 mL round bottomed flask nearly to dryness. The dried residues in a 100
mL flask were dissolved in 6 mL water and frozen at -80C for 2 h before being freeze-dried
overnight. Appropriate amount of the freeze-dried powder of GSL was weighed out in a 1.5
mL Eppendorf tube. This was then dissolved in 1 mL Milli-Q water to make a 10 mM stock
solution. A pure sinigrin stock solution (10 mM) was prepared in the same manner. A
solution of sinigrin (100 µL of 1 mM final concentration), as an internal standard, was added
into a solution of GSL (100 µL of 1 mM final concentration). The mixture was then desulfated
(Section 2.2.3) and analyzed by HPLC (Section 2.2.4). The purity (%) of the isolated GSL can
be compared with the pure sinigrin standard of the same amount using the formula below:
Purity (%) = Area of GSL x Response factor* x 100% Area of sinigrin standard *The response factor (RF), determined empirically as Area for standard: Area for equimolar
amount of GSL (Brown et al., 2003), is shown for each GSL in Table 2.4.
Table 2.4 Response factors for desulfated GSLs at 229 nm relative to that of desulfo-
sinigrin
GSL Relative response factor
Sinigrin 1.0
Glucoiberin 1.2
Glucoraphanin 0.9
Glucoiberverin 0.8
Glucoerucin 0.9
Glucotropaeolin 0.8
Gluconasturtiin 1.0
Glucobrassicin 0.3* *Determined by Buchner (1987). This table was taken from Brown et al., (2003).
82
For the preparation of GRP substrate, GER (50 mg) previously obtained from the
above extraction method was reconstituted in 1 mL Milli-Q water and oxidised to GRP
following the procedure of Lori et al. (1999). Hydrogen peroxide (50 µL) was added and the
solution was incubated at 60C for 30 min. The mixture was loaded onto DEAE Sephadex A25
column, eluted and dried using a Rotavapor. The dried extract was re-dissolved in Milli-Q
water and separated on a pre-packed (pre-swollen with water overnight) G10 Sephadex
(Sigma-Aldrich, UK) column (26 mm x 800 mm), and fractions were eluted with Milli-Q water
at 0.5 mL/min for 10 mL/fraction. Fractions containing GSLs were collected and freeze-dried
overnight in a freeze dryer (HETO Dry Winner). The freeze-dried material was desulfated and
analyzed by HPLC to confirm the purity. All GSLs involved in this work are shown in Table 2.5.
2.2.2 Preparation of sulfatase
Sulfatase type H-1 from H. pomatia (10,000 units/g) (Sigma-Aldrich, UK) (0.7 g) was
dissolved in 30 mL of Milli-Q water, followed with the addition of 30 mL of cold absolute
ethanol. After centrifugation at 10,000g in Avanti J-26 XP centrifuge (Beckman Coulter) for
15 min, the supernatant was collected, and 1.5 volume of cold ethanol was added to the
supernatant. The precipitate acquired following centrifugation of the mixture at 10,000g for
15 min was re-dissolved in 20 mL of Milli-Q water. The crude extract was passed through a
pre-packed DEAE Sephadex A25 (0.2 g dry weight pre-swollen with 0.5 M sodium acetate pH
5.0 overnight, and washed with water). The eluted extract was then passed through a pre-
packed CM Sephadex C25 (Sigma-Aldrich, UK) (0.2 g dry weight pre-swollen with distilled
water overnight). The resulting solution containing sulfatase at 0.3 U/mL was stored at −20°C
in aliquots until required.
2.2.3 Desulfation of GSLs
A mini column (Bio-Rad, UK) was pre-packed with 1 mL of a pre-equilibrated DEAE
Sephadex A25 suspension (bed volume 50% of total volume) in 20% ethanol and washed
with 1 mL of Milli-Q water (2 Xs) and allowed to drain. Sample containing GSL was well-
mixed with 10 µL of Pb(OAc)2:Ba(OAc)2 (1:1; each 0.5 M) solution in a 100 µL sample volume
to precipitate any impurities in the sample that may interfere with HPLC analysis. The
mixture was centrifuged at 16,200g for 2 min, and the clear supernatant was loaded onto
83
the column and washed with 1 mL of water (2 Xs) followed by 0.5 mL of 20 mM sodium
acetate buffer pH 5.0 (2 Xs). Sulfatase (75 μL) was added to the column and was left
overnight. DS-GSLs were eluted from the column with 0.5 mL Milli-Q water (3 Xs). Depending
on the amount of material applied to the column, the eluate was either freeze-dried in a
freeze dryer and reconstituted in 200 µL of Milli-Q water or analyzed directly in a 1.5 mL
eluted solution by HPLC analysis.
2.2.4 HPLC analytic conditions for DS-GSLs detection
DS-GSLs (Section 2.2.3) were analyzed by HPLC. Injections (10 μL) were made onto a
pre-equilibrated C18 reversed-phase column, Synergy 4u Hydro-RP (150mm x 2mm, 4μm
particles) (Phenomenex, UK). The column was designed for high water loads with high
efficiency of elution of a sample prepared in high water content. This column was further
fitted with a SecurityGuard ™ Universal HPLC guard column (Phenomenex, UK) to filter solid
parts stemming from pump seals or injection rotors that otherwise shorten the lifetime of a
column dramatically. The entire column was connected to Agilent Technology 1200 binary
pump series (Agilent, UK) and auto sampler Agilent 1100 series (Agilent, UK). Individual HPLC
run was carried out for 36 min using a water (solvent A), acetonitrile (solvent B) gradient,
and the following program was used: 2% (v/v) acetonitrile for 15 min, a gradient of 2% - 25%
(v/v) acetonitrile for 2 min, a gradient of 25% - 70% (v/v) acetonitrile for 2 min, 70% (v/v)
acetonitrile for 2 min, a gradient of 70% - 2% (v/v) acetonitrile for 2 min and a final 15 min
wash in 2% (v/v) acetonitrile. All runs were carried out at 35C at a flow rate of 0.2 mL/min.
The DS-GSLs were detected at 229 nm using a UV detector (Waters, UK). GSLs present in the
samples were identified based on their retention times with known standards (Table 2.5).
84
Table 2.5 GSLs involved in this work as detected by HPLC analysis
Type of GSL Trivial name Semisystematic name Molecular
Weight TR (min)*
Alkyl Sinigrin (SNG) 2-Propenyl (PRO)
358.37 6.00
Aromatic Gluconasturtiin (GNT) 2-Phenethyl (PHE)
409.43 16.23
Aromatic Glucotropaeolin (GTP) Benzyl (BEN)
423.46 13.37
Methylthioalkyl Glucoiberverin (GIV) ** 3-Methylthiopropyl (3MTP)
406.47 11.34
Methylthioalkyl Glucoerucin (GER) 4-Methylthiobutyl (4MTB)
421.51 13.23
Methylsulfinylalkyl Glucoiberin (GIB) 3-Methylsulfinylpropyl (3MSP)
453.00 3.63
Methylsulfinylalkyl Glucoraphanin (GRP) 4-Methylsulfinylbutyl (4MSB)
436.50 5.56
Indolyl
Glucobrassicin (GBS)
Indol-3-ylmethyl (I3M) 447.46 15.21
*Retention time at which GSL was eluted from the C18 reversed-phase column and detected by a UV detector. **Glucoiberverin (GIV) was not used as a substrate in bacterial fermentation, however it was identified on HPLC chromatograms as compared with GSL chromatographic profiles obtained from Arabidopsis thailiana (Nurul Huda Binti Abd Kadir, PhD thesis). Quantification of each GSL from the area of HPLC peak was achieved by using a
response factor (Table 2.4) for each GSL relative to the external standard, sinigrin (SNG) that
included in every HPLC run along with the samples. The concentration of each GSL, given
that its response factor (RF) was known, was calculated from the following formular:
Amount of GSL (mol) = (Area of GSL/Area of SNG) x RF x Amount of SNG (mol)
2.2.5 Preparation of DS-GSL substrates
DS-GSLs as substrates from the corresponding intact GSLs were prepared as follows.
Each GSL (30 mg) was dissolved in 10 mL of 0.02 M sodium acetate buffer pH 5.0 containing
10 mL of sulfatase type H-1 from H. pomatia (Sigma-Aldrich, UK) (0.3 U/mL) at 37°C for 16 h.
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The reaction mixture was combined with 37.5 mL of absolute ethanol, and the precipitate
was removed by centrifugation at 16,100g for 10 min. Residual ethanol was removed from
the supernatant under vacuum and the residue dissolved in 2 mL Milli-Q water and then
passed through a mini-column (10mm × 80mm) filled with 2 mL bed volume of
diethylaminoethyl (DEAE) - Sephadex A25 (Sigma-Aldrich, UK) (which had been swollen with
0.5 M sodium acetate pH 5.0 overnight and equilibrated with 2 X 1 mL Milli-Q water). The 2
mL flow-through was collected and the column was rinsed with 2 mL of water, and the
eluate (4 mL in total) was freeze-dried yielding approximately 16 mg of DS-GSL as white
powder. Identification and purity of DS-GSL of over 90% were determined using a response
factor method (Brown et al., 2003) as described in Section 2.2.1.
2.2.6 Authentic ITC and NIT standards
Phenethyl isothiocyanate (PITC), phenethyl nitrile (PNIT), benzyl isothiocyanate (BITC),
benzyl nitrile (BNIT), allyl isothiocyanate (AITC), allyl nitrile (ANIT), 3-methylthiopropyl
isothiocyanate (3MTP-ITC) or iberverin (IBV) and 4-methylsulfinylbutyl isothiocyanate
(4MSB-ITC) or sulforaphane (SFN) were purchased from Sigma-Aldrich (UK). Other standards
of ≥ 97% purity including 4-methylthiobutyl isothiocyanate (4MTB-ITC) or erucin (ERN), 5-
methylthiopentyl nitrile (5MTP-NIT) or erucin nitrile (ERN NIT), 4-methylthiobutyl nitrile
(4MTB-NIT) or iberverin nitrile (IBV NIT) were synthesised in our laboratory. The remaining
standard, 5-methylsulfinylpentyl nitrile (5MSP-NIT) or sulforaphane nitrile (SFN NIT) of ≥ 97%
purity was a kind gift from the Institute of Food Research (IFR, Norwich). Note that iberin
(IBR), iberin nitrile (IBR NIT), iberverin nitrile (IBV NIT) were not purchased or available in this
work.
2.2.7 Isolation of GSL-degrading bacteria
A faecal sample from a healthy volunteer was homogenized in phosphate buffered
saline (PBS) solution, pH 7.0 using a Stomacher 400 (Seward, UK) operating at 180g for 45 s.
Faecal homogenate (100 µL) was inoculated into the culture medium (900 µL) containing 1
mg of sinigrin. Three different media without glucose addition were used; Wilkins Chalgren
(WC), Nutrient broth (NB) and de Man, Rogosa and Sharpe (MRS). The composition of each
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medium is shown in Table 2.6. Note that L. agilis R16 used in this work was obtained from
Palop et al (1995), not from enrichment culture experiment.
Table 2.6 Compositions of culture media
Media Compositions in 1 L pH
MRS (no glucose)
10 g Peptone, 10 g Meat extract, 5 g Yeast extract, 1 g Tween-80, 2 g K2HPO4, 5 g Na-acetate, 2 g (NH4)2 citrate, 0.2 g MgSO4-7H2O, 0.05 g MnSO4-H2O
7.1 ± 0.2
WC (no glucose)
10 g Tryptone, 10 g Gelatin peptone, 5 g Yeast extract, 5 g NaCl, 1 g L-Arginine, 1 g Sodium pyruvate, 0.005 g Hemin, 0.0005 g Vitamin K
6.5 ± 0.2
NB 5 g Peptone, 1.5 g Beef extract, 1.5 g Yeast extract, 5 g NaCl 6.5 ± 0.2
Aliquots were serially diluted (10-fold) in those media every two days until the
sixteenth day in an anaerobic cabinet (MACS-MG-1000-anaerobic workstation, DW
Scientific) under an atmosphere of 5% CO2, 10% H2 and 85% N2. At day sixteen, each culture
medium (100 L) was plated onto selective corresponding media agar (1.5% agar added to
liquid broth) containing 1 mM sinigrin and incubated in the anaerobic cabinet at 37°C till
colonies were visible. From each selective media, colonies with different morphologies were
sub-cultured in 1 mL of corresponding broths containing 1 mM sinigrin overnight. Overnight
cultures were centrifuged at 16,000g for 5 min at room temperature and the clear
supernatant was screened for the presence of degradation product by GC-MS analysis
(Sections 2.2.11 and 2.2.12). The GSL-metabolizing bacterial colonies were sub-cultured in
their corresponding media till OD600nm reached ~ 0.6 and then stored at – 80°C in glycerol
(40% v/v).
2.2.8 PCR amplification and identification of isolates
DNA was extracted directly from bacterial pellet using QIAamp DNA Mini Kit (Qiagen,
UK). Universal 16S primers designed by Wang et al. (1996) were used, and their sequences
were: AmpF 5’- GAGAGTTTGATYCTGGCTCAG- 3’ and AmpR 5’-AAGGAGGTGATCCARCCGCA -
3’. All amplification reactions were carried out in a Thermocycler PCR sprint Hybaid (Thermo
Electron). The thermocycle programme used for the amplifications in each PCR reaction (50
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μL total volume) consisted of one cycle of 96°C for 4 min followed by 25 cycles of 96°C for 30
s, 50°C for 30 s and 72°C for 60 s, and then one cycle of 72°C for 4 min as previously
described (Nueno-Palop & Narbad, 2011). The PCR products were resolved by
electrophoresis in a 1.2% (w/v) agarose (Sigma-Aldrich-Aldrich, UK) gel. Visualization of the
gene products on the gel was enabled by an addition of SYBRE Safe (Invitrogen, UK) staining
(1 μL/100 mL gel volume). PCR amplified products were cleaned-up using Wizard PCR Preps
DNA Purification System (Promega, UK) according to the manufacturer’s instructions and
used as a template in the DNA sequencing reactions using an ABI Prism BigDye v3.1
Terminator Cycle Sequencing Ready Reaction kit (Nueno-Palop & Narbad, 2011). Sequences
obtained were examined by BLAST search (Altschul et al., 1990) using the NCBI database.
The identities of the isolates were determined on the basis of the highest matching score.
2.2.9 Culturing conditions and sample collection for HPLC and GC-MS analyzes
Bacterium from glycerol stock was sub-cultured in a corresponding 5 mL liquid
medium overnight. The next day, 100 µL of overnight culture was sub-cultured in 900 µL
fresh medium containing 1 mM GSL substrate. Note that 1 mM glucose was added to MRS
media to promote growth of L. agilis R16 at 37°C while its optimum growth temperature is
at 30°C. Biological triplicates were incubated for each time interval; 0, 2, 4, 6, 8, 10, 16, and
24 h at 37°C in an anaerobic generation system using a 2.5 L Anaerogen jar supplied with an
AnaeroGen sachet (Oxoid, UK) to simulate the human gut conditions. At each time interval,
the pH and the OD600nm values of the culture broths were recorded using Corning pH meter
model 240 and LKB Novaspec II spectrophotometer, respectively before being centrifuged at
16,000g for 5 min at room temperature. Clear supernatant of 100 µL was transferred to a 1.5
mL Eppendorf tube for HPLC analysis (Section 2.2.3, desulfation of GSLs), and the other 900
µL of the supernatant was transferred to a 2 mL Eppendorf tube for GC-MS analysis (Section
2.2.11, extraction of degradation products). AnaeroGen sachets (Oxoid, UK) were
replenished at each time interval to maintain an effective anaerobic environment.
Appropriate controls include (i) incubations of each GSL without bacterial cells, (ii) bacterial
incubations without GSLs, (iii) incubations of liquid broths without GSLs and bacterial cells.
All experiments involving bacterial cells and cell-free-extracts were anaerobically incubated
in triplicayes unless otherwise stated.
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2.2.10 Sample preparation for HPLC analysis and quantification of GSL from HPLC results
Sample preparation for HPLC analysis was carried out as previously described
(Section 2.2.3) and analyzed under current HPLC conditions (Section 2.2.4).
Concentration of GSL present in a 100 μL of sample supernatant was determined
using a response factor method (Brown et al., 2003). Since 100 μL was taken from the total
sample volume of 1000 μL, the corrected concentration of GSL present in the total volume of
1 mL was calculated as follows:
The volume of the supernatant used in extraction = 100 μL
From Brown et al., (2003) method, the amount of GSL (μmol) in 100 μL = X
Amount of GSL (μmol) in 1000 μL bacterial culture = X × (1000/100)
Absolute concentration (μmol/mL) of GSL in 1000 μL bacterial culture = X × 10
2.2.11 Sample preparation for GC-MS analysis
The degradation products were extracted from 900 µL supernatant in a 2 mL
Eppendorf tube. The same volume of dichloromethane (DCM) was added in the same tube
and the mixture was vortexed briefly and centrifuged at 16,000g for 2 min. This step resulted
in the separation of the mixture into two layers; the upper layer containing media broth and
the lower layer containing DCM with any ITC or NIT degradation products dissolved in it.
Only the lower layer was then transferred to a new 1.5 mL Eppendorf tube using a
hypodermic syringe. The extracts were dried over 0.5 g magnesium sulfate (BDH, UK) to
remove any remaining water residues that may interfere with downstream GC-MS analysis.
After that, the solutions were centrifuged at 16,000g for 10 min, and only the clear
supernatants were transferred to a 1.5 mL Agilent sample vial to be processed by GC-MS
directly. Sample concentration was avoided as this causes the massive losses of sample
through volatilization. For quantification, equal recovery was assumed, and an internal
standard was not considered necessary.
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2.2.12 GC-MS analytical conditions for the detection of GSL degradation products
A Hewlett Packard 6890 series system, with the Hewlett Packard 5973 mass selective
detector (HP, UK) was used for GC-MS analysis. Two capillary columns; (i) Restek 200MS
crossbond trifluoro propyl methyl polysiloxane (30m × 0.25mm i.d.; film thickness, 0.25 μm)
for ANIT (polar column necessary for analysing volatile ANIT) and (ii) Agilent SMS 5% phenyl
methyl siloxane capillary (30m × 0.25mm i.d.; film thickness, 0.25 μm) for the remaining
degradation products, were used with helium as the carrier gas (splitter inlet pressure, 40
kPa). For the Restek 200MS, the temperature was held constant at 50°C for the total 4 min
run. For Agilent SMS column, the temperature was kept at 50°C for 5 min and ramped to
150°C at 5°C min−1 for 25 min, and then ramped to 250°C at 5°C min−1 for 15 min. The total
45 min run was carried out with a flow rate of 1 mL/min, average velocity of 36 cm/s,
pressure of 7.56 psi and injection volume of 1 μL. Mass spectra were obtained by electron
ionization (EI) over a range of 50−550 atomic mass units. Ion source temperature was 230°C,
and the electron multiplier voltage was 70.1 eV. Peaks were identified by comparing
retention times, mass spectra and fragment ion fingerprints with those obtained from the
authentic standards. Mass spectral data and retention times of GSL degradation products
obtained from current GC-MS conditions are shown in Table 2.7.
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Table 2.7 Mass spectral (MS) data of GSL degradation products
GSL substrate Expected degradation
productsa MS spectra data m/z
TR
(min)*
Sinigrin (SNG) Allyl-ITC (AITC) 99 (M+), 72, 65 6.9
Allyl-NIT (ANIT) 67 (M+), 52 2.8
Gluconasturtiin
(GNT) Phenethyl-ITC (PITC) 163 (M+), 105, 91, 77, 72 24.7
Phenethyl-NIT (PNIT) 131 (M+), 91, 62 18.6
Glucotropaeolin
(GTP) Benzyl-ITC (BITC) 149 (M+), 91, 65 22.0
Benzyl-NIT (BNIT) 117 (M+), 91, 62 15.5
Glucoiberverin (GIV) Iberverin (IBV) 147 (M+), 126, 101, 72, 61 20.6
Iberverin nitrile (IBV NIT)** 115 (M+), 75, 68, 61 13.8
Glucoerucin (GER) Erucin (ERN) 161 (M+), 115, 72, 61 23.8
Erucin nitrile (ERN NIT) 129 (M+), 87, 61, 55 17.4
Glucoiberin (GIB) Iberin (IBR)** 163 (M+), 130, 116, 100, 72 29.2
Iberin nitrile (IBR NIT) 131 (M+), 115, 69, 61 NA
Glucoraphanin (GRP) Sulforaphane (SFN) 177 (M+), 160, 115, 72 33.4
Sulforaphane nitrile (SFN NIT) 145(M+), 128, 82, 55 26.2
Glucobrassicin (GBS) Indole-3-carbinol (I3C) n.d. n.d.
*Retention time at which degradation product was eluted as detected by GC-MS analysis. **These compounds were not available as authentic standards however they were detected in the reactions during bacterial fermentations. Their identifications were made according to previously reported retention time and fingerprint profiles (Vaughn et al., 2005). n.d., not determined.
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The external standard method was used for quantitative analysis of GSL degradation
products. Appropriate amount of authentic ITC/NIT standard was weighed out in a pre-
weighed 1.5 mL Agilent vial and appropriate volume of absolute ethanol was added to make
up a 100 mM stock solution. Various concentrations of each ITC/NIT standard in a range of
0.01- 2 mM diluted in DCM solutions were chromatographed by GC-MS separately from the
samples. Each concentration of each ITC/NIT standard was made in triplicates. The
calibration curves of various concentrations of each ITC/NIT standard versus peak areas were
generated (Figure 2.1 and 2.2), respectively. Note that both iberin (IBR) and iberverin nitrile
(IBV NIT) were detected as degradation products by GC-MS analysis, but corresponding
authentic standards were not purchased or synthesized. Quantification of their presence in
the samples was determined by using calibration curves of iberverin (IBV) and erucin nitrile
(ERN NIT), respectively which have similar structures, and assumingly have similar responses
under the same GC-MS conditions. Therefore, the approximate concentrations, rather than
absolute concentrations, were obtained for these two products.
Concentration of ITC/NIT degradation product present in a 900 μL of sample
supernatant was determined using a calibration curve of each ITC/NIT standard (Figure 2.1
and Figure 2.2). Since 900 μL was taken from the total sample volume of 1000 μL, the
corrected concentration of ITC/NIT present in the total volume of 1 mL was calculated as
follows:
The volume of the supernatant used in extraction = 900 μL
From the standard curve, the amount of ITC/NIT (nmol) in 900 μL = Y
The amount of ITC/NIT (nmol) in 1000 μL = Y × (1000/900)
Absolute concentration (nmol/mL) of ITC/NIT in 1000 μL = Y × 1.11
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Figure 2.1 ITC standard curves from GC-MS analysis. (A) Allyl isothiocyanate (AITC). (B) Benzyl isothiocyanate (BITC). (C) Phenethyl isothiocyanate (PITC). (D) Erucin (ERN). (E) Iberverin (IBV). (F) Sulforaphane (SFN). Values are means of triplicates.
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Figure 2.2 NIT standard curves from GC-MS analysis. (A) Allyl nitrile (ANIT). (B) Benzyl nitrile (BNIT). (C) Phenethyl nitrile (PNIT). (D) Erucin nitrile (ERN NIT). Values are means of triplicates.
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2.2.13 Determination of the percentage product
Using X and Y values from sections 2.2.10 and 2.2.12, respectively, the percentage
product from GSL degradation can be calculated as follows:
Concentration of GSL at time 0 h = X0
Concentration of GSL at time of interest = Xt
Percentage product (%) = Y/(X0-Xt) x 100%
Note that the units of X and Y must be the same for the calculation. 2.2.14 Determination of stability and solubility of ITC/NIT standards
Since the decline of ITC degradation products over a time course was observed in all
GSL metabolisms in all bacterial fermentations, it was speculated that ITC products may be
unstable in aqueous solutions. Therefore, the control experiments were conducted. The NB
medium, Milli-Q water and different buffers containing each authentic ITC/NIT standards
without bacterial culture were anaerobically incubated at 37˚C over a time course. The
supernatants were extracted for GC-MS analysis as previously described (Section 2.2.11) to
determine the stability of ITC/NIT in the corresponding medium/buffer over a time course at
the experimental conditions. Three types of buffers; (i) 0.1 M citrate phosphate buffer pH
7.0, (ii) 0.1 M PBS buffer pH 7.0 and (iii) 0.1 M Tris-Cl buffer pH 7.0 were tested in this
experiment.
Authentic AITC and PITC standards in a range of 0.05 – 1 mM were also tested for
their solubility in 0.1 M citrate buffer pH 7.0. If the linear regression was obtained at all
concentrations, this means these ITCs are easily dissolved in aqueous solution.
2.2.15 Resting cell experiments
(i) Myrosinase induction: Each of three bacteria was anaerobically cultured overnight
in 1 mL corresponding medium supplemented with 1 mM sinigrin (induced cells) and
without it (control cells) at 37˚C. Both samples were centrifuged at 16,000g for 15 min at 4˚C.
The supernatants were discarded, and the cells were washed twice in 1 mL 0.1 M citrate
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phosphate buffer pH 7.0 to remove any GSL/ITC/NIT traces. After centrifugation, the washed
cells were re-suspended in 1 mL of the same buffer containing 1 mM gluconasturtiin and
incubated at 37˚C for 2 h. Afterwards, the cells were removed by centrifugation for 5 min at
16,000g, and 100 µL of the supernatant was prepared for HPLC analysis (Section 2.2.10) for
GSL detection, and 900 µL was prepared for GC-MS analysis (Section 2.2.11) for ITC/NIT
detection.
(ii) Reductase induction: E. coli O83:H1 NRG 857C cells were anaerobically cultured
overnight in 1 mL NB medium supplemented with either 1 mM glucoraphanin or
gluconastutiin (induced cells) and without any GSL supplementation (control cells) at 37˚C.
The remaining steps were performed as for myrosinase induction, but 1 mM sulforaphane
was added to the buffer containing resting cells in place of 1 mM gluconasturtiin. The
reductase activity was monitored over a time course by HPLC analysis.
2.2.16 Determination of metal ion dependency on NIT production from GSL metabolism in
bacterial resting cells
Since NIT production was not detected from GSL metabolism in bacterial resting cells
in 0.1 M citrate phosphate buffer, it was thought that metal ions may be required in the
buffer for NIT production. To test this hypothesis, chelating agent
ethylenediaminetetraacetic acid (EDTA) of 1, 5, 10 mM concentrations were individually
added to E. coli O83:H1 NRG 857C bacterial cultures containing 1 mM gluconasturtiin in NB
media that were incubated at 37˚C anaerobically for 16 h. The pH values of sample with and
without the addition of EDTA at T0h and T16h were recorded. The sample supernatants were
analyzed by GC-MS as previously described (Section 2.2.11) to determine whether NIT
production by bacterial fermentation in culture broth was inhibited by EDTA addition.
Additional experiment was conducted in which either 5 mM of CoCl2, CaCl2, MgCl2,
FeSO4, NiCl2, or MnCl2 (Sigma-Aldrich, UK) was individually added to bacterial resting cells
(induced by 1 mM gluconasturtiin overnight) in 0.1 M citrate phosphate buffer pH 7.0
containing 0.5 mM of a GSL substrate (as per section 2.2.15 (i) Myrosinase induction). The
reactions were anaerobically incubated at 37˚C for 16 h. Appropriate control samples (i) GSL-
containing buffer without bacterial cells or metal ions, (i) GSL-containing buffer plus each
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metal ion without bacterial cells, (iii) GSL-containing buffer plus bacterial cells without any
metal ions were also included. The sample supernatants were analyzed by GC-MS as
previously described (Section 2.2.11) to determine whether NIT production by bacterial
resting cells in the buffer was promoted by metal ion addition.
2.2.17 Cell-free extract experiments
(i) Myrosinase induction: Each of three bacteria was anaerobically grown overnight at
37˚C in 100 mL corresponding medium supplemented with 1 mM sinigrin (induced cells) and
without it (controlled cells). The bacterial culture was centrifuged at 4,000g for 15 min at 4˚C,
and the pellets were washed twice with 0.1 M citrate phosphate buffer pH 7.0 to remove
traces of GSL/ITC/NIT products if any. The bacterial suspensions in the same buffer (with 20
µL protease inhibitor cocktails (Melford, UK) added) were then disrupted using a cell
disruption machine (Constant Systems, UK) with two shots at 30k psi. Whole cell lysates
were centrifuged at 16,000g for 30 min at 4˚C, and the clear supernatant referred to as cell-
free extracts were obtained and filtered sterile. The quantity of protein was determined
using Bradford’s reagent (Bio-Rad, UK) (Section 2.2.20). Cell-free extracts (300 µL) were
anaerobically incubated with 1 mM gluconasturtiin (100 µL of 10 mM stock solution) in 600
µL of 0.1 M citrate phosphate buffer pH 7.0 at 37˚C for 16 h. After that, sample supernatant
(100 µL) was prepared for HPLC analysis (Section 2.2.10) for GSL detection, and other
supernatant (900 µL) was prepared for GC-MS analysis (Section 2.2.10) for ITC/NIT product
detection.
(ii) Reductase induction: E. casselfiflavus NCCP-53 and E. coli O83:H1 NRG 857C cells
were anaerobically grown overnight in 100 mL NB medium supplemented with 1 mM
glucoraphanin (induced cells) and without it (controlled cells). The remaining steps were
performed as the above (i), but 1 mM glucoraphanin or glucoiberin was added to the buffer
containing cell-free extracts in place of 1 mM gluconasturttin. The reductase activity of the
cell-free extracts was monitored over a time course.
2.2.18 Determination of co-factor dependancy for reductase activity in cell-free extracts
To determine whether co-factors required for reductase activity, cell-free extracts of
E. coli O83:H1 NRG 857C were desalted using Econo-Pac 10DG desalting columns (Bio-Rad,
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UK). The appropriate buffer used in the preparation of cell-free extracts (20 mL) was added
to the column to equilibrate it. The cell-free extract supernatant (3 mL) was then added to
the column, and the effluent was discarded. The elution buffer of choice (4 mL) was added
to the column to elute the higher molecular weight component(s) and the eluate (4 mL)
containing proteins was collected. The column was then washed with elution buffer (20 mL)
to elute remaining salt ions from the column. This fraction (20 mL) collected as ‘salt ions’ was
freeze-dried overnight in a freeze dryer (HETO Dry Winner). The obtained powder was re-
dissolved in 1 mL Milli-Q water and then was used as ‘freeze-dried factors’.
The reaction mixture (0.2 mL) contained desalted cell-free extract (100 µL), 0.25 mM
glucoraphanin (5 µL of 10 mM stock solution) and either 1 mM of CoCl2, CaCl2, MgCl2, FeSO4,
NiCl2, or MnCl2 (Sigma-Aldrich, UK) solution, 1 mM FAD, 1 mM NADH, 1 mM NADPH (20 µL of
10 mM stock solution) or a combination of two factors or all factors together or ‘freeze-dried
factors’ (100 µL) in 0.1 M citrate phosphate buffer pH 7.0. This mixture was anaerobically
incubated at 37˚C for 16 h. The supernatant (100 µL) was then subjected to HPLC analysis
(Section 2.2.10) for the detection of reduction conversion of glucoraphanin. All chemicals
used in this experiment were purchased from Sigma-Aldrich, UK.
2.2.19 Determination of reductase activity in cell-free extracts in the bioconversion of
sulforaphane to erucin
The non-desalted cell-free extracts (300 µL) of E. coli O83:H1 NRG 857C (induced by 1
mM glucoraphanin overnight) were filtered sterile and then were anaerobically incubated
with 1 mM sulforaphane (Sigma-Aldrich, UK) (50 µL of 20 mM stock solution in absolute
ethanol) in 650 µL of 0.1 M citrate phosphate buffer pH 7.0 at 37˚C for 5 and 22 h. After that,
sample supernatant (1 mL) was prepared for GC-MS analysis (Section 2.2.11) for the
detection of sulforaphane bioconversion to erucin.
2.2.20 Determination of pH and temperature optima for reductase activity in cell-free
extracts in the bioconversion of glucoraphanin to glucoerucin
To determine temperature and pH optima, temperature and pH conditions were
varied under the same experimental conditions using the non-desalted cell-free extracts.
The reaction mixture (0.2 mL) contained non-desalted cell-free extract (100 µL), 0.25 mM
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glucoraphanin (5 µL of 10 mM stock solution) in 0.1 M citrate phosphate buffer. This mixture
was anaerobically incubated at 37˚C for 16 h. The supernatant (100 µL) was then subjected
to HPLC analysis for the detection of reduction bioconversion of glucoraphanin.
2.2.21 Protein quantification
Protein quantification was performed according to Bradford (1976) using Bradford’s
reagent (Sigma-Aldrich, UK). The total assay volume (1.55 mL) contained 0.05 mL of the
protein sample (0.1–1.4 mg/mL protein sample) and 1.5 mL of the Bradford Reagent
(B6916)(Sigma-Aldrich, UK) per Eppendorf tube which was gently mixed and incubated at
room temperature for 15 min. To create the calibration curve, 2 mg/mL BSA protein
standards (Sigma-Aldrich, UK) were serially diluted to produce a range from 0.1–1.4 mg/mL
of BSA. The samples (in triplicates) were transferred into cuvettes and the absorbance at 595
nm was recorded within 1 h. The protein sample concentration was determined by
comparison of the unknown samples to the standard curve prepared using the protein
standards (Figure 2.3). ‘Blank’ controls containing no protein but an equivalent amount of
Bradford’s reagent were used to zero the LKB Novaspec II spectrophotometer (Pharmacia,
UK).
Figure 2.3 Representative protein calibration curve. Various amount of BSA were plotted against absorbance at 595nm. Values are means of triplicates.
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2.2.22 Denaturing sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE)
Proteins were analyzed by sodium dodecyl sulfate polyacrylamide gel electrophoresis
(SDS-PAGE) (Laemmelli, 1970). Compositions to make 12.5% SDS-PAGE, loading buffer,
running buffer, staining/destaining solutions are shown in Table 2.8. Protein samples (20 µg)
were mixed with 2x SDS PAGE loading buffer. The mixture was boiled at 100°C for 2 min
prior to be resolved on a 12.5% SDS-PAGE gel in 1X SDS running buffer using Mini-PROTEAN
Tetra Cell apparatus (Bio-Rad, UK). The gel was electrophoresed at 180 V for 50 min.
Afterwards, it was stained with Coomassie Brilliant Blue R-250 staining solution for 15 min,
and washed once with Milli-Q water before being destained with destaining solution till the
gel background was clear, and the protein bands became visible.
Table 2.8 Compositions of SDS-PAGE, loading buffer, running buffer, staining/destaining
solutions
12.5% SDS-PAGE (for 2 gels) 12.5% separating gel (10 mL): 3.3 mL of Milli-Q
water, 4.0 mL of 30% (w/v) acrylamide, 0.8%
(w/v) bis-acrylamide stock solution (37.5:1) (Bio-
Rad, UK), 2.5 mL of Tris-Cl (1.5 M, pH 8.8), 100 µL
of 10% SDS (Sigma-Aldrich), 100 µL of 10%
ammonium persulfate (APS) (Sigma-Aldrich), 4 µL
of N,N,N',N'-Tetramethylethylenediamine
(TEMED) (Sigma-Aldrich)
4% stacking gel (3 mL): 2.1 mL of Milli-Q water,
0.5 mL of 30% (w/v) acrylamide, 0.8% (w/v) bis-
acrylamide stock solution (37.5:1) (Bio-Rad, UK),
0.38 mL of Tris-Cl (1.0 M, pH 6.8), 30 µL of 10%
SDS, 30 µL of 10% ammonium persulfate (APS)
(Sigma-Aldrich), 3 µL of N,N,N',N
Tetramethylethylenediamine (TEMED) (Sigma-
Aldrich)
SDS PAGE loading buffer 2x: 0.5 M Tris-HCl (pH 6.8), 4.4% (w/v) SDS, 20% (v/v) glycerol (GE
Healthcare), 2% (v/v) 2-mercaptoethanol (Sigma-Aldrich), and 0.05% bromophenol blue (Sigma-
Aldrich) in Milli-Q water
10X SDS Running Buffer (1 L): 30 g Tris-base (Sigma-Aldrich), 144 g glycine (Sigma-Aldrich), 10 g SDS
dissolved in Milli-Q water
Coomassie staining solution (1 L): 2.5 g Coomassie blue R-250 (Rio-Rad), 450 mL methanol, 450 mL
Milli-Q water, 100 mL acetic acid
Destaining solution (1 L): 300 mL methanol, 100 mL acetic acid and 600 mL Milli-Q water
100
2.2.23 Native gel electrophoresis
The native gels were made in a similar procedure as denatured SDS-PAGE gels
(section 2.2.21), except SDS was not added in any solutions shown in Table 2.8. Protein
samples (20 µg) were well-mixed with 2x native gel loading buffer. The Mini-PROTEAN Tetra
Cell gel apparatus was placed in the ice-filled box to prevent any protein denaturation
caused by heat during the run. The native gel was electrophoresed at 100 V for 2 h. After
that, one portion of the gel was stained with Coomassie Brilliant Blue R-250 solution, and the
other was incubated for 1 h at 37°C with substrate solution (sufficient to cover the gel).
Substrate solution contained 50 mM sodium acetate buffer (pH 7.0), 10 mM sinigrin, 0.5 mM
ascorbic acid, and 50 mM barium chloride (Sigma-Aldrich). GSL-degrading activity was
indicated as a white precipitate of barium sulfate on the gel. The positive control, the
purified myrosinase from S. alba (5 µg) was also loaded on the native gel to assess the
validity of native gels for GSL-degrading activity detection.
2.2.24 Statistical analysis
Data analysis including calculation of average values, percentage products, linear
regression and standard deviations were performed using Microsoft Excel 2010 or GraphPad
Prism 6. The data were analyzed by one-way analysis of variance (ANOVA). Differences were
considered significant if p < 0.05.
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2.3 Results 2.3.1 Screening for GSL-metabolising human gut bacteria It is well-known that plant myrosinase can metabolize GSL to ITC or NIT product
depending upon the conditions of the hydrolysis. Accumulating evidence suggests that
certain bacteria may exhibit GSL-degrading activity (or myrosinase-like activity) as ITC and/or
NIT products were detected upon GSL incubation with bacterial culture in vitro. Thus, the
hypothesis of this experiment is that certain human gut bacteria may be able to metabolize
GSL to ITC or/and NIT product like plant myrosinase.
In order to develop the predominant GSL-degrading component of the microbial
community from a human fresh faecal sample, the use of enrichment culture for 16 days
with sinigrin as a selective carbon source in different growth media was implemented. Note
that M9 minimal media were used initially to grow bacteria with sinigrin supplementation,
but bacteria did not grow well (data not shown) and thus rich media were used instead. A
mixture of bacteria capable of metabolizing 1 mM sinigrin had a degradation capacity of 80%,
80% and 50% in MRS, WC and NB broths, respectively within 24 h anaerobic incubation at
37˚C. The negative control containing 1mM sinigrin without any faecal sample showed no
degradation suggesting that sinigrin is stable. Its degradation must be due to human gut
microbiota in faecal sample. Twenty bacterial colonies from the three agar plates were
individually sub-cultured in their corresponding liquid broths containing 1 mM sinigrin for 24
h anaerobic incubation at 37˚C. Sinigrin degradation by each culture was assessed by HPLC
analysis. Six colonies with a degradation capacity higher than 50% were subjected to 16S
rDNA gene analysis for strain identification. L. agilis R16 previously reported to have a high
capacity to degrade sinigrin (Palop et al., 1995) was not isolated from the enrichment culture
experiment, but was also included in this study. The strain identification, degradation rates
and degradation products obtained are shown in Table 2.9.
It was found that six GSL-degrading bacteria include three Gram-positive
Enterococcus, two Gram-negative Escherichia coli, and one clone SEW-E-011. Most of them
produced both AITC and ANIT from sinigrin degradation except Enterococcus sp. C213 and
Enterococcus faecium KT4S13 that only produced ANIT without AITC at all (Table 2.9).
Although clone SEW-E-011 yielded the highest degradation of sinigrin (Table 2.9), it was not
chosen for further study due to unavailability of its genome/proteome database.
102
L. agilis R16 (obtained from Palop et al., 1995), Enterococcus casseliflavus NCCP-53,
and Escherichia coli O83:H1 NRG 857C were chosen for further experiments as they all
produced both AITC and ANIT as degradation products with high degradation rates.
Importantly, accessibility to the genome/proteome database of relative E. casseliflavus
strains and E. coli O83:H1 NRG 857C would facilitate molecular cloning work.
Table 2.9 Bacterial isolates exhibiting > 50% degradation of 1 mM sinigrin in 24 h anaerobic
incubation at 37˚C
Broth Bacterial strain Type* OD600nm Degradation (%)
Degradation products
WC Clone SEW-E-011 Gram + 0.557 82.3 ± 1.05 AITC and ANIT
WC Enterococcus casseliflavus NCCP-53 Gram + 0.382 78.7 ± 2.13 AITC and ANIT
WC Enterococcus sp. C213 Gram + 0.487 75.1 ± 1.12 ANIT
MRS Lactobacillus agilis R16** Gram + 0.771 71.7 ± 0.98 AITC and ANIT
NB Escherichia coli O83:H1 NRG 857C Gram - 0.511 57.8 ± 3.11 AITC and ANIT
NB Escherichia coli UMNF18 Gram - 0.474 57.4 ± 2.45 AITC and ANIT
MRS Enterococcus faecium KT4S13 Gram + 0.524 50.1 ± 1.89 ANIT
Values are mean ± SD, n = 3, but only means are shown for OD600nm values. *Type of bacteria; Gram +, Gram-positive; Gram -, Gram-negative. **L. agilis R16 was obtained from Palop et al. (1995), not from the enrichment culture.
2.3.2 Isolation and purification of GSL substrates
Since GSLs are not generally commercially available except for sinigrin, most GSL
used in later bacterial fermentation experiments were purified from seed sources as
mentioned in section 2.2.1. For each GSL extraction, the previous method (Thies, 1988) was
used. The seed source from specific Cruciferous plant was ground and defatted and dried.
The defatted seed was boiled in methanol to extract the GSLs. The methanol extracts were
filtered and concentrated to dryness. The dried extract was re-dissolved in distilled water
and subjected to protein precipitation. The supernatant was loaded onto a pre-packed
diethylaminoethyl (DEAE)-Sephadex A25 column for GSL purification. The solution of K2SO4
was used to elute GSL from the column into ethanol and the potassium sulphate precipitate
103
was removed. The clear supernatant was then evaporated nearly to complete dryness. The
dried residues of GSL were dissolved in absolute methanol and were evaporated to dryness.
The dried residues were dissolved water and freeze-dried overnight. Appropriate amount of
the freeze-dried powder of GSL was weighed out and dissolved in water. The GSL solution
was then desulfated (Section 2.2.3) and analyzed by HPLC (Section 2.2.4). The purity (%) of
the isolated GSL was determined by comparing with pure sinigrin standard of the same
amount that was ran along side with the GSL sample. All isolated GSL substrates were obtained with above 90% purity. The HPLC
chromatograms of all purified GSLs used in this work are shown in Figure 2.4.
104
Figure 2.4 HPLC chromatograms of GSL substrates used in this work. (A) Glucoiberin with the retention time at 3.7 min. (B) Glucoraphanin with the retention time at 5.4 min. (C) Sinigrin with the retention time at 6.2 min. (D) Glucoerucin with the retention time at 13.4 min. (E) Glucotropaeolin with the retention time at 13.7 min. (F) Gluconasturtiin with the retention time at 16.4 min. (G) Glucobrassicin with the retention time at 15.4 min. Residual peaks within 5 min are dirts eluted from the column. Small peaks detected at early retention time represent unknown residues eluted from C18 reverse-phase column. 2.3.3 Time-course degradation product profiles of intact GSLs in individual bacterial
fermentations
From section 2.3.1, certain bacteria isolated from human faecal sample were capable
of metabolizing sinigrin to AITC and/or ANIT. Three bacteria; L. agilis R16, E. casseliflavus
105
NCCP-53, and E. coli O83:H1 NRG 857C that have never been reported for GSL-degrading
capacity (except Lactobacillus agilis R16 with sinigrin) were studied to determine whether
they were able to metabolize different GSLs (with different side chains) differently in terms
of types of products generated and degradation rates. To do so, each bacterial culture was
grown on a GSL substrate in their corresponding broths anaerobically at 37˚C over a time
course. Six different intact GSL substrates including sinigrin, glucotropaeolin, gluconasturtiin,
glucoerucin, glucoiberin, and glucoraphanin (1 mM) were used in this experiment (Figure
2.4) while glucobrassicin (0.1 mM) was used as a substrate in the later experiment. The
amount of degraded GSL over time was determined by HPLC analysis using authentic sinigrin
as external standard (section 2.2.10) and the amount of ITC and/or NIT product generated
upon GSL degradation was determined by GC-MS analysis using external authentic standard
calibration curve (section 2.2.12).
It was found that all three bacteria were capable of metabolizing most GSLs to
corresponding ITCs and/or NITs (Table 2.10) in the same way that plant myrosinase
hydrolyzed these GSLs. This suggests that human gut bacteria exhibited GSL-degrading
activity like plant myrosinase during GSL metabolism.
106
Table 2.10 Detection of ITC and NIT products from GSL metabolism in bacterial
fermentations
GSL Corresponding ITC and
NIT* LA EC ECO
Sinigrin
AITC √ √ √ ANIT √ √ √
Glucotropaeolin
BITC √ √ √ BNIT √ √ √
Gluconasturtiin
PITC √ √ √ PNIT X √ √
Glucoerucin
ERN √ √ √ ERN NIT √ √ √
Glucoiberin
IBR X √ X (IBV) IBR NIT X X X (IBV NIT)
Glucoraphanin
SFN X √ X (ERN) SFN NIT X X X (ERN NIT)
*Corresponding GSL degradation products typically produced by plant myrosinase and detected in bacterial fermentations. See abbreviations in Table 2.7. Brackets indicate the detection of the unexpected products instead. LA; L. agilis R16; EC, E. casseliflavus NCCP-53; ECO, E. coli O83:H1 NRG 857C.
Growth curves and pH values of bacterial cultures incubated with individual GSLs
were recorded (Figure 2.5). L. agilis R16 grown on any GSL substrates in modified MRS broth
containing 1 mM glucose reached stationary phase at 16 h of incubation (Figure 2.5A). Note
that 1 mM glucose was added to support the growth of this bacterium before it began to
metabolize GSL. Without glucose addition, this bacterium would grow slowly and not reach
its optimal growth (Palop et al., 1995). Highest OD600nm values of approximately 1.0 were
observed in L. agilis R16 when glucoiberin and glucoraphanin were substrates while lower
OD600nm values of 0.8-0.9 were observed among other GSL substrates (Figure 2.5A). E.
casseliflavus NCCP-53 grown in WC broth reached stationary phase at 5 h with the highest
OD600nm values of approximately 0.48-0.60 when glucotropaeolin, glucoiberin and
glucoraphanin were substrates while lower OD600nm values of 0.37-0.51 were observed
among other GSL substrates (Figure 2.5B). Similarly, E. coli O83:H1 NRG 857C reached
stationary phase at 8 h of incubation, but with the highest OD600nm values of approximately
0.50 found among all GSL substrates (Figure 2.5C).
107
Since L. agilis R16 is a lactic acid-producing bacterium (LAB) generating lactic acid
upon metabolism of glucose under anaerobic conditions, the pH decline over a time course
was expected. The pH values declined from 7.0 to 4.0 over a time course was observed in all
GSL substrates (Figure 2.5D). In contrast, E. casseliflavus NCCP-53 showed an increasing
trend in pH values initially from pH 6.5 to pH 7.0 or 7.5 after 6 h in all GSL substrates (Figure
2.5E). On the other hand, E. coli O83:H1 NRG 857C showed a decreasing trend in pH values
initially from pH 6.5 to below pH 6.0 for all GSLs (Figure 2.5F). Since GSLs alone did not
degrade spontaneously when incubated at 37°C for 24 h and bacteria did not accumulate
any GSL degradation products unless they were cultivated in medium containing GSLs
(Appendix I), the presence of any GSL degradation products can be ascribed only to bacterial
metabolism.
108
Figure 2.5 Growth curves and pH values of bacterial cultures incubated with individual GSLs anaerobically at 37˚C over a time course. (A) Growth kinetics (in log scale) of L. agilis R16 (LA) in modified MRS broth containing 1 mM glucose, (B) Growth curves of E. casseliflavus NCCP-53 (EC) in WC broth, (C) Growth curves of E. coli O83:H1 NRG 857C (ECO) in NB broth, (D) pH values of LA, (E) pH values of EC and (F) pH values of ECO. Values are means of triplicates. SNG, Sinigrin; GTP, Glucotropaeolin; GNT, Gluconasturtiin; GER, Glucoerucin; GIB, glucoiberin and GRP, glucoraphanin.
109
The graphs of time-course GSL degradation of each GSL substrate and GSL
degradation product formation by each bacterium are generated (Figure 2.6).
For sinigrin, complete degradation was detected within 8 h in E. casseliflavus NCCP-
53 while gradual degradation was observed over a time course in both L. agilis R16 and E.
coli O83:H1 NRG 857C with absolute degradation predicted to occur beyond 24 h incubation
(Figure 2.6A). This means sinigrin was more favoured by E. casseliflavus NCCP-53 than the
other two bacteria. Higher concentrations of both allyl isothiocyanate (AITC) and allyl nitrile
(ANIT) products were detected by GC-MS analyses in E. casseliflavus NCCP-53. The
decreasing trend in AITC production was observed in all bacteria after it peaked at 4 or 8 h
while NIT production seemed to increase till it peaked at 6 or 8 h and afterwards it remained
fairly constant (Figure 2.6A).
When glucotropaeolin was used as a substrate, complete degradation occurred in
only E. coli O83:H1 NRG 857C within 24 h while the other two bacteria yielded 96%
degradation at 24 h. The trends in production of both benzyl isothiocyanate (BITC) and
benzyl nitrile (BNIT) in all three bacteria were similar to those found in sinigrin degradation
(Figure 2.6B).
For gluconasturtiin, complete degradation at 6 h was found in both E. casseliflavus
NCCP-53 and L. agilis R16 and at 16 h in E. coli O83:H1 NRG 857C. The trends in production
of both phenethyl isothiocyanate (PITC) and phenethyl nitrile (PNIT) in all three bacteria
were similar to the previous two GSLs. Higher concentrations of total products were found in
E. casseliflavus NCCP-53 > E. coli O83:H1 NRG 857C > L. agilis R16 (Figure 2.6C). Surprisingly,
no PNIT product was detected in L. agilis R16 despite several attempts were repeated. The
reason for this is unknown.
For glucoerucin, complete degradation was found at 24 h in all three bacteria (Figure
2.6D). The trends in production of erucin (ERN) and erucin nitrile (ERN NIT) were also similar
in all bacteria and similar to those of other ITC/NIT production from the previous GSLs.
For glucoiberin and glucoraphanin, the results are rather different from other GSL
substrates. Glucoiberin was 40% degraded at 24 h in E. casseliflavus NCCP-53 and 50% at 8 h
in E. coli O83:H1 NRG 857C while 10% degradation was found in L. agilis R16 at 24 h (Figure
2.6E). The ITC product found in a very low concentration in E. casseliflavus NCCP-53 was
iberin (IBR) while iberverin (IBV) was found in a much higher concentration in E. coli O83:H1
110
NRG 857C. Interestingly, no corresponding NIT product was found in E. casseliflavus NCCP-53
while iberverin nitrile (IBV NIT) was found in in E. coli O83:H1 NRG 857C. No ITC/NIT
production was detected in L. agilis R16 (Figure 2.6E).
Similarly, glucoraphanin was 50% degraded at 24 h in E. casseliflavus NCCP-53 and at
4 h in E. coli O83:H1 NRG 857C while 11% degradation at 24 h was found in L. agilis R16
(Figure 2.6F). The ITC product found in a very low concentration in E. casseliflavus NCCP-53
was sulforaphane (SFN) while ERN was found in a much higher concentration in E. coli
O83:H1 NRG 857C. Interestingly, no NIT product was found in E. casseliflavus NCCP-53 while
ERN NIT was found in E. coli O83:H1 NRG 857C. No ITC/NIT production was detected in L.
agilis R16 (Figure 2.6F)
For glucoiberin and glucoraphanin substrates, they were degraded in descending
rates by E. coli O83:H1 NRG 857C > E. casseliflavus NCCP-53 > L. agilis R16. E. casseliflavus
NCCP-53 metabolized these GSLs to the expected ITC products without any NIT products. In
contrast, E. coli O83:H1 NRG 857C metabolized these GSLs to ITC/NIT degradation products
that are reduced analogues of the expected degradation products. The reason for this was
further investigated in section 2.3.10.
111
Figure 2.6 Time-course degradation product profiles of bacterial cultures anaerobically incubated with individual GSLs at 37˚C. The left, middle and right panels show GSL degradation, ITC production and NIT production, respectively. (A) Sinigrin. (B) Glucotropaeolin. (C) Gluconasturtiin. (D) Glucoerucin. (E) Glucoiberin. (F) Glucoraphanin. LA, L. agilis R16; EC, E. casseliflavus NCCP-53; ECO, E. coli O83:H1 NRG 857; AITC, allyl isothiocyanate; ANIT, allyl nitrile; BITC, benzyl isothiocyanate; BNIT, benzyl nitrile; PITC, phenethyl isothiocyanate; PNIT, phenethyl nitrile. Values are means ± SD, n = 3.
112
Figure 2.6 Time-course degradation product profiles of bacterial cultures anaerobically incubated with individual GSLs at 37˚C. The left, middle and right panels show GSL degradation, ITC production and NIT production, respectively. (A) Sinigrin. (B) Glucotropaeolin. (C) Gluconasturtiin. (D) Glucoerucin. (E) Glucoiberin. (F) Glucoraphanin. LA, L. agilis R16; EC, E. casseliflavus NCCP-53; ECO, E. coli O83:H1 NRG 857C; IBR, Iberin; IBV, Iberverin; IBV NIT, Iberverin nitrile; SFN, Sulforaphane; ERN, Erucin; ERN NIT, Erucin nitrile. Values are means ± SD, n = 3.
113
The GC-MS chromatograms of ITC/NIT degradation products from the metabolisms
of GSLs are shown in Figure 2.7. Fingerprint fragment ions of GSL degradation products are
shown in Figure 2.8.
114
Figure 2.7 GC-MS chromatograms of degradation products of different GSLs. (A) SNG was metabolized to ANIT 1, at 2.83 min and AITC 2, at 6.98 min. (B) GTP was metabolized to BNIT 3, at 15.5 min and BITC 4, at 22.0 min BNIT. (C) GNT was metabolized to PNIT 5, at 18.6 min and PITC 6, at 24.7min. (D) GIV was metabolized to IBV NIT 7, at 13.8 min and IBV 8, at 20.6 min. (E) GER was metabolized to ERN NIT 9, at 17.4 min and ERN 10, at 23.8 min. (F) GIB was metabolized to IBR 11, at 29.2 min. (G) GRP was metabolized to SFN 12, at 33.4 min. Referred to Table 2.7.
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Figure 2.8 Fingerprint fragment ions of GSL degradation products generated by GC-MS analysis. (1) ANIT, (2) AITC, (3) BNIT, (4) BITC, (5) PNIT, (6) PITC, (7) IBV NIT, (8) IBV, (9) ERN NIT, (10) ERN, (11) IBR and (12) SFN. Referred to Table 2.7.
116
Since ITC productions from glucoiberin and glucoraphanin metabolized by E.
casseliflavus NCCP-53 over a time course were rather low (Figure 2.6E and 2.6F, respectively),
the corresponding GC-MS chromatograms showed high noise signals (data not shown).
Therefore, selected ion monitoring (SIM) mode was used to generate representative
chromatograms of ITC products of these GSLs in this bacterium (Figure 2.9A and 2.9B,
respectively).
Figure 2.9 GC-MS chromatograms of ITC degradation products from glucoiberin and glucoraphanin metabolized by E. casseliflavus NCCP-53 over a time course. (A) Glucoiberin was metabolized to iberin, 1 at 29.23 min. (B) Glucoraphanin was metabolized to sulforaphane, 2 at 33.40 min. Selected ion monitoring (SIM) mode was used to generate these chromatograms in order to minimize noise signals.
117
The GC-MS chromatograms of ITC/NIT productions from glucoiberin and
glucoraphanin metabolized by E. coli O83:H1 NRG 857C over a time course are shown in
Figure 2.10A and 2.10B, respectively.
Figure 2.10 GC-MS chromatograms of ITC/NIT degradation productions from glucoiberin and glucoraphanin metabolized by E. coli O83:H1 NRG 857C over a time course. (A) Glucoiberin was metabolized to iberverin nitrile, 1 at 13.8 min and iberverin, 2 at 20.6 min. (B) Glucoraphanin was metabolized to erucin nitrile, 3 at 17.4 min and erucin, 4 at 23.8 min.
118
These results show that ITC productions from glucoiberin and glucoraphanin
metabolized by both bacteria declined after 8 h. However, NIT productions from E. coli
O83:H1 NRG 857C increased over time and remained fairly constant at 8 and 16 h as
previously seen in the trends of NIT productions from other GSL substrates in all bacteria.
Glucobrassicin, as another GSL substrate, was used at a much lower concentration
(0.1 mM) due to low materials of purified glucobrassicin. Only two bacteria, E. coli O83:H1
NRG 857C and E. casseliflavus NCCP-53, were tested on this GSL. Bacterial growth and
glucobrassicin degradation in the two bacteria were monitored over a time course (Table
2.11).
Table 2.11 Bacterial growth and glucobrassicin degradation in E. coli O83:H1 NRG 857C and
E. casseliflavus NCCP-53 over a time course
Time (h)
ECO EC
OD600nm GBS (µM)a Degradation (%)b OD600nm GBS (µM)a Degradation
(%)
0 0.12 ± 0.01 100 ± 2 0 0.10 ± 0.02 100 ± 4 0
2 0.21 ± 0.02 76 ± 3 24 ± 5 0.18 ± 0.02 65 ± 5 35 ± 7
4 0.32 ± 0.02 61 ± 5 39 ± 6 0.35 ± 0.03 62 ± 4 38 ± 6
6 0.44 ± 0.03 58 ± 2 42 ± 3 0.42 ± 0.02 58 ± 3 42 ± 5
8 0.48 ± 0.02 55 ± 5 45 ± 6 0.51 ± 0.01 35 ± 2 65 ± 3
16 0.51 ± 0.01 53 ± 4 47 ± 5 0.56 ± 0.02 27 ± 4 73 ± 5 aRemaining glucobrassicin (GBS) in the reaction solution, 100 µM was an initial concentration. bDegradation (%) of GBS = the amount of GSL degraded in (%) relative to the initial amount. Values are mean ± SD, n = 3. ECO, E. coli O83:H1 NRG 857C; EC, E. casseliflavus NCCP-53
Both bacteria were able to degrade glucobrassicin with 47% degradation at 16 h by E.
coli O83:H1 NRG 857C and 73% degradation by E. casseliflavus NCCP. The degradation
products of glucobrassicin by these bacteria were not detected under current GC-MS
conditions. The products may be extremely volatile, and thus LC-MS analysis instead of GC-
MS analysis may be required for further analysis. The HPLC chromatograms of glucobrassicin
metabolism in E. coli O83:H1 NRG 857C and E. casseliflavus NCCP-53 over a time course are
shown in Figure 2.11.
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Figure 2.11 HPLC chromatograms of bacterial degradation of glucobrassicin over a time course. (A) Sinigrin external standard at 6 min. (B) E. coli O83:H1 NRG 857C gradually degraded glucobrassicin (14.6 min) over time with 47% degradation at 16 h. (C) E. casseliflavus NCCP-53 gradually degraded glucobrassicin (14.6 min) with 73% degradation at 16 h. The arrows indicate the insets showing enlarged peaks of glucobrassicin. Peaks no. 1 to 3 found in all figures are unknown residues, no. 4 and 5 are probably polar GSLs emerged during the metabolism. These figures are representatives of triplicates with similar results.
120
The time taken to obtain 50% decline of each GSL substrate by three bacteria is
shown in Table 2.11. Among all GSL substrates tested so far, the degradation rates are in
descending order: gluconasturtiin > sinigrin > glucoerucin > glucotropaeolin > glucoiberin or
glucoraphanin in L. agilis R16 (Table 2.12). E. casseliflavus NCCP-53 degraded these
substrates in a slightly different descending order: gluconasturtiin > glucoerucin > sinigrin >
glucotropaeolin > glucobrassicin > glucoraphanin > glucoiberin. In contrast, E. coli O83:H1
NRG 857C showed rather different descending order: glucoerucin > glucoraphanin >
gluconasturtiin > sinigrin > glucoiberin > glucotropaeolin > glucobrassicin.
Table 2.12 Time taken to obtain 50% decline of each GSL substrate by three bacteria
GSL Time (h) of 50% decline*
LA EC ECO
Sinigrin 4 3.4 6
Glucotropaeolin 7 6 12
Gluconasturtiin 1.8 1.8 5
Glucoerucin 6 3 3.5
Glucoiberin > 24 > 24 8
Glucoraphanin > 24 24 4
Glucobrassicin NA 15 > 16 *Time taken to observe 50% decline from each GSL. Values are means of triplicates. LA, L. agilis R16; EC, E. casseliflavus NCCP-53; ECO, E. coli O83:H1 NRG 857C.
From these results, it was speculated that the polarity and the size of GSL side chain
may influence degradation rate in which GSL with the less polar side chain was more easily
degraded by L. agilis R16 and E. casseliflavus NCCP-53 as the polarity of GSL substrates in
descending order is: glucoiberin > glucoraphanin > sinigrin > glucotropaeolin > glucoerucin >
gluconasturtiin > glucobrassicin. However, this speculation does not hold true for E. coli
O83:H1 NRG 857C. The percentage product of each product from each bacterial GSL
metabolism is shown in Table 2.13.
121
Table 2.13 Percentage products of each ITC/NIT product from all GSL metabolisms by each
bacterium
GSL Bacteria Product Percentage product (%)*
2 h 4 h 6 h 8 h 10 h 16 h 24 h
SNG ECO AITC 27 ± 4 28 ± 5 20 ± 4 19 ± 3 13 ± 2 7 ± 1 6 ± 0.2
ANIT 18 ± 5 25 ± 4 30 ± 6 14 ± 3 12 ± 5 11 ± 2 14 ± 3
EC AITC 32 ± 3 6 ± 0.5 15 ± 2 12 ± 1 9 ± 3 10 ± 2 7 ± 1
ANIT 21 ± 7 11 ± 1 22 ± 3 28 ± 6 28 ± 4 22 ± 3 16 ± 4
LA AITC 13 ± 4 10 ± 2 11 ± 3 23 ± 1 5 ± 2 2 ± 0.3 1 ± 0.1
ANIT ND ND ND ND 4 ± 2 3 ± 0.6 4 ± 1
GTP ECO BITC 9 ± 2 18 ± 3 17 ± 2 20 ± 4 11 ± 3 3 ± 0.2 1 ± 0.2
BNIT 5 ± 1 14 ± 4 13 ± 2 18 ± 2 22 ± 9 15 ± 6 7 ± 1
EC BITC 3 ± 0.3 18 ± 2 30 ± 4 23 ± 3 21 ± 2 10 ± 1 6 ± 0.4
BNIT 11 ± 3 18 ± 5 22 ± 2 19 ± 3 20 ± 4 15 ± 2 11 ± 3
LA BITC ND 6 ± 2 11 ± 3 14 ± 5 7 ± 1 4 ± 2 2 ± 0.9
BNIT 16± 2 15 ± 5 12 ± 4 14 ± 4 13 ± 3 15 ± 4 14 ± 3
GNT ECO PITC ND 12 ± 3 13 ± 2 22 ± 6 10 ± 1 4 ± 0.3 2 ± 0.1
PNIT 5 ± 1 10 ± 3 19 ± 3 8 ± 3 6 ± 2 8 ± 2 5 ± 1
EC PITC ND 6 ± 0.4 11 ± 4 13 ± 3 7 ± 3 2 ± 1 0.6 ± 0.2
PNIT ND 20 ± 6 27 ± 4 24 ± 9 21 ± 6 13 ± 5 16 ± 3
LA PITC 9 ± 2 13 ± 5 16 ± 3 11 ± 3 7 ± 1 5 ± 2 3 ± 1
PNIT ND ND ND ND ND ND ND
GER ECO ERN ND 4 ± 2 27 ± 8 34 ± 9 35 ± 17 20 ± 5 5 ± 1
ERN NIT ND 10 ± 3 6 ± 2 23 ± 6 22 ± 4 16 ± 1 10 ± 0.5
EC ERN 27 ± 6 40 ± 14 33 ± 6 24 ± 10 25 ± 6 9 ± 4 7 ± 2
ERN NIT 11 ± 3 24 ± 8 24 ± 7 23 ± 2 18 ± 4 12 ± 1 12 ± 1
LA ERN ND ND 16 ±4 15 ± 3 9 ± 1 6 ± 0.2 4 ± 0.2
ERN NIT ND 7 ± 2 5 ± 0.6 6 ± 1 6 ± 0.2 3 ± 1 2 ± 0.6
GIB ECO IBV 14 ± 8 12 ± 2 8 ± 2 8 ± 1 5 ± 1 4 ± 1 1 ± 0.2
IBV NIT 16 ± 6 9 ± 2 7 ± 2 5 ± 1 4 ± 0.4 5 ± 0.4 3 ± 0.7
EC IBR ND 2 ± 1 3 ± 0.5 3 ± 1 1 ± 0.1 1 ± 0.3 0.4 ± 0.1
GRP ECO ERN 4 ± 2 5 ± 1 6 ± 1 10 ± 1 6 ± 2 3 ± 0.5 1 ± 0.2
ERN NIT 8 ± 2 4 ± 1 5 ± 0.6 6 ± 3 9 ± 2 8 ± 1 6 ± 1
EC SFN 6 ± 1 2 ± 0.8 3 ± 1 3 ± 0.6 2 ± 0.3 1 ± 0.2 0.3 ± 0.1
*The amount of product (mol) in (%) relative to the digested amount of GSL (mol). SNG, sinigrin; GTP, glucotropaeolin; GNT, gluconasturtiin; GER glucoerucin; AITC, allyl isothiocyanate; ANIT, allyl nitrile; BITC, benzyl isothiocyante; BNIT, benzyl nitrile; PITC, phenethyl isothiocyanate; PNIT, phenethyl nitrile; ERN, erucin; ERN NIT, erucin nitrile; GIB, glucoiberin; IBV, iberverin; IBR, iberin; IBV NIT, iberverin nitrile; GRP, glucoraphanin; SFN, sulforaphane; ND, Not detected. Values are means ± SD, n = 3. LA, L. agilis R16; EC, E. casseliflavus NCCP-53; ECO, E. coli O83:H1 NRG 857C.
These results showed that the total percentage products of both ITC and NIT
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products from each GSL metabolism in all three bacteria never reached 100% (Table 2.13).
The highest total percentage products from each GSL in all bacteria were found between 4
and 8 h where ITC productions peaked. E. coli O83:H1 NRG 857C showed the highest total
percentage products of sinigrin (53%) at 4 h, glucotropaeolin (38%) at 8 h, glucoerucin (57%)
at 8-10 h, gluconasturtiin (32%) at 6 h, glucoiberin (34%) at 2 h and glucoraphanin (16%) at 8
h. E. casseliflavus NCCP-53 showed the highest total percentage products of sinigrin (40%) at
8 h, glucotropaeolin (42%) at 8 h, glucoerucin (64%) at 4 h, gluconasturtiin (38%) at 6 h,
glucoiberin (3%) at 6-8 h and glucoraphanin (3%) at 6-8 h. L. agilis R16 showed the highest
total percentage products of sinigrin (23%) at 8 h, glucotropaeolin (28%) at 8 h, glucoerucin
(21%) at 8 h, gluconasturtiin (16%) at 6 h. The total percentage products from the
metabolisms of glucoiberin and glucoraphanin in all bacteria were much lower than those
obtained from other GSLs.
2.3.4 Stability of ITC/NIT degradation products
It was noticeable that ITC productions from metabolisms of all GSL substrates
declined over a time course following their peaks and the total percentage product of both
ITC and NIT formation from each GSL metabolism never reached 100% (Table 2.13).
Therefore, the study of the stability of ITC/NIT in culture broths was carried out to determine
whether these ITC/NIT products were stable under current fermentation conditions. To
achieve this, each authentic ITC/NIT standard was added to NB media with and without E.
coli O83:H1 NRG 857C cells incubated over a time course at 37˚C under anaerobic conditions.
The levels of all ITC standards tested including AITC, BITC, PITC, IBV and ERN declined sharply
from 1 mM (at time 0 h) to 0.2 – 0.4 mM within 8 h in NB broths without bacterial cells
(Figure 2.12A). These results suggest that ITCs had short lives in NB broths. Assumingly, the
same occurrence may be applied to MRS and WC broths even without bacterial cells. When
bacterial cells were added to those ITC standards in NB broths, the decline of ITCs levels
seemed to be faster (from 1 mM to 0.1 – 0.3 mM within 8 h) (Figure 2.12B). That explains
why the decreasing trends in ITC production from all GSL metabolisms in all bacterial cells
were observed (Figure 2.6). However, it is not clear whether these authentic ITC standards
were degraded to other metabolites. ITCs may be conjugated to the medium components
and/or cellular components. This indeed needs further investigation. The same test was
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performed to determine the stability of NIT standards including ANIT, BNIT, PNIT, IBV NIT
and ERN NIT in NB broths. The levels of these NIT standards in NB media without bacterial
cells were rather stable over time, except for ANIT with a decline from 1 to 0.7 mM after 2 h
(Figure 2.12C). With cells, slight declines of NITs from 1 to 0.8-0.9 mM were observed while
ANIT declined sharply from 1 to 0.68 mM within 2 h (Figure 2.12D).
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Figure 2.12 Stability of 1 mM ITC/NIT standards in NB broths with/without E. coli O83:H1 NRG 857C cells over a time course. (A) ITC standards without cells. (B) ITC standards with cells. (C) NIT standards without cells. (D) NIT standards with cells. Values are means of triplicates.
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The time taken to obtain 50% or 25% decline in each ITC or NIT level, respectively in
NB broths with or without the presence of bacterial cells is shown in Table 2.14.
Table 2.14 Time taken to obtain 50% or 25% decline in each ITC or NIT level, respectively in
NB broths with or without the presence of E. coli O83:H1 NRG 857C cells
ITC Time (h) of 50% decline
NIT Time of 25% decline
No cells Cells No cells Cells
AITC 6.2 2.3 ANIT 4 1.8
BITC 5.9 3.6 BNIT > 24 > 24
PITC 6.2 2.4 PNIT > 24 > 24
IBV 7.5 3.2 IBV NIT > 24 > 24
ERN 5.2 3.7 ERN NIT > 24 > 24
SFN 5.1 1.8 Values are means of triplicates. This experiment was carried out at 37˚C under anaerobic conditions over a time course.
The time taken to obtain 50% or 25% decline in each ITC or NIT level was shortened
by the presence of bacterial cells in NB broths. This suggests the possibility of interactions of
ITCs or NITs with bacterial cellular components, but with less pronounced effect on NIT
levels.
To test the solubility of ITCs in aqueous solution, various concentrations of AITC and
PITC were extracted in distilled water. The linear regressions were obtained from both ITCs
(Figure 2.13) indicating that ITCs of physiological concentrations were easily dissolved in
distilled water. Therefore, the decline of ITC productions over a time course is not due to
insolubility of ITCs in aqueous solutions.
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Figure 2.13 Solubility of various concentrations of authentic ITC standards in distilled water. Values are means of triplicates.
The stability of ITCs was further investigated in aqueous solutions over a time course;
distilled water, 0.1 M citrate phosphate buffer pH 7.0, 0.1 M PBS buffer pH 7.0 and 0.1 M
Tris-Cl buffer pH 7.0. It was shown that all ITCs tested in aqueous solutions declined over
time with different rates indicating the instability of ITCs in aqueous solutions (Figure 2.14).
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Figure 2.14 Stability of 1 mM authentic ITC standards in various buffers without E. coli O83:H1 NRG 857C cells over a time course. Several aqueous buffer solutions of 0.1 M and pH 7.0 were used. (A) Tris-Cl. (B) PBS. (C) Citrate phosphate. (D) Distilled water. Values are means of triplicates.
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The time taken to obtain 50% decline of each ITC in different aqueous solutions is
shown in Table 2.15.
Table 2.15 Time taken to obtain 50% decline in each ITC level in various aqueous solutions
without the presence of E. coli O83:H1 NRG 857C cells
ITC Time (h) of 50% decline
Water Citrate Phosphate PBS Tris Cl
AITC 7.1 1.7 4.8 4.6
BITC 11 5 7.2 7.5
PITC 18 5.6 7.3 7.2
IBV 15 3.8 12.5 7.3
ERN 15 3.7 5.2 7.1
SFN 6 n.d. n.d. n.d.
Values are means of triplicates. n.d., not determined.
These results showed that the levels of ITCs declined fastest in citrate phosphate
buffer and slowest in distilled water. PBS and Tris-Cl buffers had less pronounced effects
than citrate phosphate buffer. It was assumed that the presence of citrate, phosphates and
chlorides in these buffers may be attributed to faster decline of ITC levels in comparion with
water molecules alone.
2.3.5 Time-course degradation product profiles of DS-GSLs in individual bacterial
fermentation
Previously, it was reported that rat intestinal microbiota digest DS-sinigrin to form
allyl nitrile (ANIT) and 1-cyano-2,3-epithiopropane (Lu et al., 2011). To determine whether
the three bacteria can metabolize any DS-GSLs to NIT products or other metabolites,
different DS-GSLs of 1 mM including DS-sinigrin, DS-glucotropaeolin, DS-gluconasturtiin, DS-
glucoerucin, and DS-glucoraphanin were used as substrates in the same fermentation
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conditions as in the previous experiments. The negative controls containing only DS-GSLs
without bacterial cells showed no degradation products at 24 h suggesting DS-GSLs were
stable under experimental conditions (Appendix II).
The generation of NIT products from the metabolisms of DS-GSLs in all three bacteria
is summarized in Table 2.16. These results indicate that DS-GSLs are precursors to pure NIT
production whereas intact GSLs are precursors to both ITC and NIT production during the
same bacterial fermentation in culture broths.
Table 2.16 Detection of NIT product from DS-GSL metabolism in bacterial fermentations
DS-GSL Corresponding NIT product LA EC ECO
DS-Sinigrin ANIT √ √ √
DS-Glucotropaeolin BNIT √ √ √
DS-Gluconasturtiin PNIT √ √ √
DS-Glucoerucin ERN NIT √ √ √
DS-Glucoraphanin SFN NIT X X X (ERN NIT)
*Corresponding NIT products expected to be produced from DS-GSL metabolism. See abbreviations in Table 2.7. Brackets indicate detection of the unexpected products instead. LA; L. agilis R16; EC, E. casseliflavus NCCP-53; ECO, E. coli O83:H1 NRG 857C. A tick (√) means the product was detected and a cross (X) means not detected.
The results showed that E. coli O83:H1 NRG 857C was able to metabolize all DS-GSLs
to the corresponding NIT products without any ITC products (Figure 2.15).
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Figure 2.15 GC-MS chromatograms of degradation products of DS-GSLs metabolized by individual three bacteria. (A) DS-sinigrin was metabolized to allyl nitrile (ANIT), 1 (2.83 min). (B) DS-glucotropaeolin was metabolized to benzyl nitrile (BNIT), 2 (15.5 min). (C) DS-gluconasturtiin was metabolized to phenethyl nitrile (PNIT), 3 (18.6 min) by E. casseliflavus NCCP-53 and E. coli O33:H1 NRG 857C. (D) DS-glucoerucin was metabolized to erucin nitrile (ERN NIT), 4 (17.4 min). (E) DS-glucoraphanin was metabolized to pure erucin nitrile, 5 (17.47 min) by E. coli O33:H1 NRG 857C only. These figures are representatives of triplicates with similar results.
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However, E. casseliflavus NCCP-53 was able to metabolize all DS-GSLs except for DS-
glucoraphanin while L. agilis R16 was not able to metabolize DS-gluconasturtiin to PNIT or
DS-glucoraphanin to ERN NIT. These results are in accordance with the previous results
showing absence of ERN NIT product from glucoraphanin metabolism in E. casseliflavus
NCCP-53 (Figure 2.6F) and the absence of PNIT product from gluconasturtiin metabolism in L.
agilis R16 (Figure 2.6C). It is clear that L. agilis R16 was unable to produce PNIT from either
gluconasturtiin or DS-gluconasturtiin. The reason for this is unknown.
NIT production profiles from DS-GSLs metabolisms in individual bacteria over a time
course are shown in Figure 2.16. Concentrations of NIT products among all three bacteria
increased over a time course with slight higher NIT productions in comparison with those
obtained from the metabolisms of intact GSLs. At 24 h, E. coli O83:H1 NRG 857C and L. agilis
R16 showed 56% ANIT production in (%) relative to the initial dose of DS-sinigrin and 52%
from E. casseliflavus NCCP-53. All three bacteria showed approximately 30% BNIT
production from DS-glucotropaeolin at 24 h. Similarly, 25-30% PNIT productions from DS-
gluconasturtiin were detected in all bacteria except L. agilis R16 (no PNIT production from
the metabolism of gluconasturtiin either). For ERN NIT productions from DS-glucoerucin, 38,
34 and 30% productions were observed in E. coli O83:H1 NRG 857C, E. casseliflavus NCCP-53
and L. agilis R16, respectively at 24 h. However, the concentrations of ERN NIT from DS-
glucoraphanin metabolism in E. coli O83:H1 NRG 857C (i.e. 13% production) were much
lower than other NIT products from the metabolisms of other DS-GSL substrates. The other
two bacteria were unable to produce ERN NIT from this substrate. This indicates that DS-
glucoraphanin substrate was not favoured by these bacteria.
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Figure 2.16 NIT productions from DS-GSLs metabolisms in individual bacteria over a time course. (A) DS-sinigrin was metabolized to allyl nitrile (ANIT). (B) DS-glucotropaeolin was metabolized to benzyl nitrile (BNIT). (C) DS-gluconasturtiin was metabolized to phenethyl nitrile (PNIT) by ECO and EC. (D) DS-glucoerucin was metabolized to erucin nitrile (ERN NIT). (E) DS-glucoraphanin was metabolized to erucin nitrile (ERN NIT) by ECO only. LA, L. agilis R16; EC, E. casseliflavus NCCP-53; ECO, E. coli O83:H1 NRG 857C. Values are means ± SD, n = 3.
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2.3.6 Resting cell experiments
From the previous results (section 2.3.3), the three bacteria were capable of
metabolizing GSLs to ITCs and/or NITs like plant myrosinase suggesting that these bacteria
may exhibit GSL-degrading activity. To determine whether putative GSL-degrading enzyme
activity in three bacteria are inducible or constitutively expressed (like plant myrosianse),
resting cell experiments were carried out. Firstly, E. casseliflavus NCCP-53 was used in a trial
using different buffers to find the optimal buffer for ITC production from GSL metabolism.
Washed suspensions of non-induced cells (grown without 1 mM GSL in WC media overnight)
and induced cells (grown on 1 mM sinigrin) were anaerobically incubated with 1 mM
gluconasturtiin in various types of buffers for 8 h at 37˚C. As a result, both induced and non-
induced cells of E. casseliflavus NCCP-53 in all buffers produced PITC products without PNIT
products (Table 2.17) even in the buffers containing no ascorbic acid (i.e. an activator for
plant myrosinases). However, higher PITC products were observed in induced cells suggesting
the inducibility of bacterial GSL-degrading enzymes. Several buffer conditions supported PITC
production in the resting cell experiments, but citrate phosphate buffer pH 7.0 was chosen to
be used in further experiments as it gave the highest PITC production from the metabolism of
gluconasturtiin.
Table 2.17 PITC production from gluconasturtiin metabolism in E. casseliflavus NCCP-53 resting cells in different buffers for 8 h at 37˚C under anaerobic conditions
No. Buffer Sample PITC products (μM)
1 0.03 M MES + 6 mM MgCl2 + 2 mM ascorbic acid + 1 mM GNT N 73 ± 12 I 116 ± 14
2 0.1 M Citrate phosphate buffer pH 7.0 + 1 mM GNT N 123 ± 8
I 276 ± 15
3 0.1 M Citrate phosphate buffer pH 6.0 + 1 mM GNT N 118 ± 11
I 197 ± 21
4 0.05 M PBS buffer pH 7.0 + 1 mM GNT N 113 ± 18
I 203 ± 10
5 0.1 M Tris Cl buffer pH 7.0 + 1 mM GNT
N 83 ± 14 I 176 ± 20
GNT, gluconasturtiin; I, Induced cells; N, Non-induced cells. Values are means ± SD, n = 3
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A further resting cell experiment was carried out in which either non-induced or
induced resting cells of individual three bacteria was anaerobically incubated with 1 mM
gluconasturtiin in 0.1 M citrate phosphate buffer pH 7.0 for only 2 h at 37˚C. The putative
bacterial GSL-degrading activity from L. agilis R16 is most likely to be inducible as the induced
cells degraded gluconasturttin to completion while the non-induced cells showed 71%
degradation. Higher degradation of gluconasturtiin was also detected in E. casseliflavus NCCP-
53 in spite of no major difference in bacterial growth. In contrast, E. coli O83:H1 NRG 857C
showed complete degradation in both induced and non-induced cells (Table 2.18). The reason
for this is still not known. However, PITC products were only detected in induced cells and not
in non-induced cells (Table 2.18). There was no detection of NIT products in any bacteria. It
seems likely that putative bacterial GSL-degrading activity from E. casseliflavus NCCP-53 and E.
coli O83:H1 NRG 857C is inducible since their induced cells produced PITC products in buffers,
but the non-induced cells did not.
Table 2.18 Degradation of gluconasturtiin by bacterial resting cells in 0.1 M citrate
phosphate buffer pH 7.0 anaerobically incubated for 2 h at 37˚C
Properties LA EC ECO
I N I N I N
OD600nm 0.723 ± 0.004
0.738 ± 0.014
0.513 ± 0.008
0.498 ± 0.012
0.425 ± 0.002
0.448 ± 0.007
GNT degradation
(%)* 100 71 ± 12 80 ± 8 71 ± 5 100 100
PITC (µM) 75 ± 11 ND 41 ± 15 ND 44 ± 13 ND
*The amount of GNT disappearance in (%) relative to the initial dose (1 µmol/mL) of GNT. GNT, Gluconasturtiin; LA, L. agilis R16; EC, E. casseliflavus NCCP-53; ECO, E. coli O83:H1 NRG 857C; I, Induced; N, Non-induced; ND, Not detected; PITC, Phenethyl isothiocyanate. Values are means ± SD, n = 3
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2.3.7 Determination of metal ion dependency on NIT production from GSL metabolism in
the buffer and culture broths
To determine the conditions required for PITC/PNIT production from gluconasturtiin
and DS-gluconasturtiin metabolism in resting cells of E. coli O83:H1 NRG 857C induced by 1
mM sinigrin overnight, both buffer and NB broth were used in this experiment. It was found
that gluconasturtiin and DS-gluconasturtiin were stable in the buffer as no degradation
products were found without bacterial induced resting cells (Figure 2.17A). Both PNIT and
PITC were produced when induced resting cells were incubated in NB broths (Figure 2.17B)
while only PITC was produced when induced resting cells were incubated in 0.1 M citrate
phosphate buffer pH 7.0 (Figure 2.17C). Only PNIT was produced from DS-gluconasturtiin in
NB broths with induced resting cells (Figure 2.17D). This suggests that there may be
something present in NB broths and absent in the buffer that are responsible for PNIT
production.
Figure 2.17 GC-MS chromatograms of different degradation products of gluconasturtiin or DS-gluconasturtiin metabolized by E. coli O83:H1 NRG 857C induced resting cells in different incubation conditions. (A) No product was found in 0.1 M citrate phosphate buffer pH 7.0 containing either gluconasturtiin or DS-gluconasturtiin without resting cells. (B) Phenethyl nitrile (PNIT), 1 (18.60 min) and phenethyl isothiocyanate (PITC), 2 (24.69 min) were produced from gluconasturtiin in NB broth with induced resting cells. (C) Only PITC, 2 was produced from gluconasturtiin in 0.1 M citrate phosphate buffer pH 7.0 with induced resting cells. (D) Only PNIT, 1 was produced from DS-gluconasturtiin in NB broth with induced resting cells. These figures are representatives of triplicates.
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To determine whether metal ions are required for NIT production in NB broth, three
concentrations (1, 5, 10 mM) of ethylenediaminetetraacetic acid (EDTA) as a metal ion-
chelating agent were added into E. coli O83:H1 NRG 857C bacterial cultures in NB broth
containing 1 mM gluconasturtiin anaerobically incubated at 37˚C for 16 h. The results showed
that EDTA had a significant inhibitory effect on both PITC and PNIT production from
gluconasturtiin metabolism in E. coli O83:H1 NRG 857C in NB broth (Table 2.19). The pH
values dropped from 6.5 to 5.3-5.6 upon EDTA addition, but it was not the cause of NIT
product inhibition since NIT production was still detected in this pH range during bacterial
fermentation experiments.
Table 2.19 Effect of EDTA on ITC/NIT production from gluconasturtiin metabolism in E. coli
O83:H1 NRG 857C in NB broth for 16 h anaerobic incubation at 37˚C
EDTA (mM) PNIT (mM) PITC (mM) pH
0 0.185 ± 0.031 0.083 ± 0.015 6.5 ± 0.1
5 0.004 ± 0.001 ND 5.6 ± 0.2
10 ND ND 5.4 ± 0.1
20 ND ND 5.3 ± 0.1 ND, Not detected; PITC, Phenethyl isothiocyanate; PNIT, Phenethyl nitrile. Values are means ± SD, n = 3 An additional experiment was conducted in which either metal ions, CoCl2, CaCl2,
MgCl2, FeSO4, NiCl2, MnCl2 of the same concentration (5 mM) was individually added to E. coli
O83:H1 NRG 857C resting cells (induced by 1 mM sinigrin in NB broth overnight). The reaction
mixture was anaerobically incubated in 0.1 M citrate phosphate buffer pH 7.0 containing 0.5
mM gluconasturtiin at 37˚C for 16 h. Appropriate control samples (i) GSL-containing buffer
without bacterial cells or metal ions, (i) GSL-containing buffer plus each metal ion without
bacterial cells, (iii) GSL-containing buffer plus bacterial cells without any metal ions were also
included.
The results showed that the control, GSL-containing buffer plus Fe2+ without bacterial
cells gave NIT products (4.5 µM) while the other controls with the addition of other metal ions
showed no NIT products indicating the existence of non-enzymatic NIT production promoted
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by Fe2+ addition (Figure 2.18). The addition of Co2+, Ca2+, Ni2+, Mn2+ had an inhibitory effect on
PITC production and no PNIT production was detected. However, the addition of Fe2+ ions
resulted in PNIT production, but with reduced PITC production. This indicates that NIT
production in bacterial resting cells in the buffer was promoted by 5 mM Fe2+ ions (Figure
2.18). Interestingly, the addition of Mg2+ had stimulatory effect on PITC production without
PNIT production.
Figure 2.18 Effects of metal ions on PITC/PNIT production in E. coli O83:H1 NRG 857C induced resting cells. Each metal ion solution (5 mM) was incubated in 0.1 M citrate phosphate buffer pH 7.0 containing 0.5 mM gluconasturtiin with induced resting cells of E. coli O83:H1 NRG 857C at 37˚C for 16 h. Control 1, cells and 5 mM Fe2+ without GSL; Control 2, GSL and 5 mM Fe2+ without cells; Control 3, cells and GSL without any metal ions. Values are means of triplicates.
The GC-MS chromatograms of degradation products from gluconasturtiin metabolism
in E. coli O83:H1 NRG 857C resting cells upon addition of metal ions in 0.1 M citrate
phosphate buffer pH 7.0 are shown in Figure 2.19.
0 50 100 150 200 250Control 1Control 2Control 3
2+Co2+Ca2+Ni2+Mn2+Mg2+Fe3+Fe
PNITPITC
Concentration (M)
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Figure 2.19 GC-MS chromatograms of degradation products from gluconasturtiin metabolism in E. coli O83:H1 NRG 857C resting cells upon addition of metal ions. (A) PITC, 1 (24.69 min) production was promoted by Mg2+ ions and inhibited by Mn2+ ions. There was no PNIT production. (B) PNIT, 2 (18.60 min) production was promoted by Fe2+ ions with reduced PITC production. Each metal ion solution (5 mM) was incubated in 0.1 M citrate phosphate buffer pH 7.0 containing 0.5 mM gluconasturtiin with induced resting cells of E. coli O83:H1 NRG 857C at 37˚C for 16 h. These figures are representatives of triplicates.
The same experiments were carried out with other four GSLs, glucotropaeolin,
glucoerucin, glucoiberin and glucoraphanin to determine whether Fe2+ ions would promote
NIT production from the metabolism of GSLs in the buffer. Similarly, Fe2+ ions promoted NIT
139
production from all GSLs tested, but with reduced ITC production compared to the contols (no
addition of Fe2+ ions) (Table 2.20). The non-enzymatic NIT productions in trace amounts were
also observed in the control samples containing only GSLs and 5 mM Fe2+ without bacterial
resting cells (Table 2.20).
Table 2.20 Effect of Fe2+ ions (5 mM) on ITC/NIT production from the metabolisms of GSLs
(0.5 mM) by E. coli O83:H1 NRG 857C induced resting cells anaerobically incubated in 0.1 M
citrate phosphate buffer pH 7.0 for 16 h at 37˚C
GSL GTP GER GIB GRP
Products (μM) BITC BNIT ERN ERN NIT IBV IBV
NIT ERN ERN NIT
No cells + Fe2+ ND 6 ± 2 ND 4 ± 1 ND 5 ± 2 ND 6 ± 1
Cells + no ions 52 ± 12 ND 55 ± 10 ND 42 ± 8 ND 48 ± 6 ND
Cells + Fe2+ 36 ± 5 69 ± 9 34 ± 8 57 ± 7 16 ± 4 46 ± 9 19 ± 5 49 ± 8 GTP, Glucotropaeolin; GER, glucoerucin: GIB, glucoiberin; GRP, glucoraphanin; BITC, Benztl isothiocyanate; BNIT, Benzyl nitrile; ERN, Erucin; ERN NIT, Erucin nitrile; IBV, Iberverin; IBV NIT, Iberverin nitrile; ND, Not detected. Values are means ± SD, n = 3.
Since NIT production was not detected in the negative control sample containing only
GSLs without bacterial cells in the culture broths MRS, WC and NB used during bacterial
fermentations at 24 h. It was postulated that the concentration of Fe2+ ions present in the
culture broths may be so low (possibly lower than 5 mM used in the current experiment) that
it was not sufficient to promote the non-enzymatic NIT production from GSL in the culture
broths. Therfore, NIT production in the culture broths with the presence of bacterial cells was
thought to be mainly enzymatically-driven with the aid of low concentration of Fe2+ ions.
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2.3.8 Cell-free extract experiments from all bacteria
Since putative bacterial GSL-degrading enzyme activity from all three bacteria is likely
to be inducible (Section 2.3.6), these bacterial cells were induced with 1 mM sinigrin in
corresponding broths overnight to allow the induction of GSL-degrading enzyme activity to be
studied in cell-free extract experiments. To determine whether the GSL-degrading enzyme
activity is in the soluble fraction, cell-free extracts of all three bacteria after cell disruption
were incubated with 1 mM gluconasturtiin in 0.1 M citrate phosphate buffer pH 7.0 for 16 h
and the detection of ITC/NIT formation was carried out by GC-MS analysis. No ITC/NIT
products were observed from any cell-free extracts. This result indicates that no myrosinase-
like activity could be detected under the conditions tested. It is thought that bacterial GSL-
degrading enzyme activity may be inactive in this in vitro activity assay. Since bacterial GSL-
degrading activity was only detected in bacterial anaerobic fermentation experiments, it was
postulated that bacterial GSL-degrading activity may be sensitive to air exposure in cell-free
extract experiments. Another possibility is that bacterial GSL-degrading activity may be part of
the protein complex or multiple component protein system that once disrupted (upon cell
breaking up during cell-free extraction in this case) renders GSL-degrading enzyme activity
inactive.
2.3.9 Determination of GSL-degrading enzyme activity from bacterial whole cell lystaes on
the native gels
Since no bacterial GSL-degrading enzyme activity were detected from cell-free extracts
of all bacteria, it was hypothesized that bacterial GSL-degrading enzyme might be
extracellular (i.e. secreted into the culture broths). Interestingly, several groups report
extracellular β-glucosidase secreted by fungi such as A. fumigatus Z5 (Liu et al., 2012),
Daldinia eschscholzi (Aphichart et al., 2007) and from the algal lytic bacterium Sinorhizobium
kostiense AFK-13 (Kim & Lee, 2007). To test this hypothesis, the overnight culture broths from
both sinigrin-induced and non-induced E. coli O83:H1 NRG 857C cultures were centrifuged,
and the clear broths were analyzed on SDS-PAGE to see whether there were any proteins
secreted into the culture broths. No protein bands were found (Figure 2.20). This indicates
that bacterial GSL-degrading enzyme was still in the whole cell lysate.
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Figure 2.20 SDS-PAGE analysis of E. coli O83:H1 NRG 857C proteins. Whole cell lysates, supernatants and culture broths (after removal of cell pellets) collected from both induced (I) and non-induced (N) cultures of E. coli O83:H1 NRG 857C were analyzed on 4-12% SDS-PAGE. Lane M is PageRuler prestained protein marker (ThermoScientific, UK).
Native PAGE gels have been a successful assay for GSL-degrading enzyme activity
(Shikita et al., 1999; Thangstad et al., 2004; Ahuja et al., 2011). Myrosinase can be located
after native polyacrylamide gel electrophoresis by incubating the gel with sinigrin. The sulfate
released from sinigrin by myrosinase action reacts with barium ion in the incubation solution
to produce white precipitate of barium sulfate. This activity gel assay was used to determine
whether there is bacterial GSL-degrading enzyme activity in the whole cell lysates. The
positive control, purified plant myrosinase from white mustard (Sinapis alba), was also
included to test the validity of the assay. Only the positive control displays GSL-degrading
enzyme activity as indicated by white precipitate. However, no GSL-degrading enzyme activity
was detected from bacterial whole cell lysates or supernatants (Figure 2.21).
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Figure 2.21 Native gel electrophoresis for GSL-degrading enzyme activity test. The whole cell lysates and supernantants of non-induced (N) and induced (I) samples of E. coli O83:H1 NRG 857C were analyzed on the native gel. (A) Coomassie-stained native gel showing the band of purified plant myrosinase (boxed) (B) Activity native gel showed white precipitate of barium sulfate (boxed) from the activity of plant myrosinase indictaing the presence of GSL-degrading enzyme activity towards sinigrin. Other white precipitates between the lanes are false positive. Other white precipitates between the lanes are false positive because once the bands
excised and incubated with a solution of gluconasturtiin (i.e. aromatic GSL), phenethyl
isothiocyanate (PITC) product was not detected while the plant myrosinase gave this product.
This result confirms that putative bacterial GSL-degrading enzyme activity was not detected in
cell-free extracts.
2.3.10 Sulfoxide reduction of glucoiberin and glucoraphanin by reductase activity in E. coli
O83:H1 NRG 857C
From the previous time-course study during bacterial fermentation experiments
(Section 2.3.3), E. coli O83:H1 NRG 857C and E. casseliflavus NCCP-53 were able to metabolize
glucoiberin and glucoraphanin to different products (referred to Table 2.10). E. casseliflavus
NCCP-53 produced only iberin (IBR) from glucoiberin and produced only sulforaphane (SFN)
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from glucoraphanin without any NIT products. In contrast, E. coli O83:H1 NRG 857C produced
iberverin (IBV) and iberverin nitrile (IBV NIT) from glucoiberin, erucin (ERN) and erucin nitrile
(ERN NIT) from glucoraphanin. Since no corresponding products i.e. iberin (IBR) and
sulforaphane (SFN) were detected from metabolisms of glucoiberin and glucoraphanin in E.
coli O83:H1 NRG 857C, instead the reduced sulfide ITC and NIT analogues were produced. It
was suspected that this bacterium exhibits reductase activity that can reduce the sulfoxide
groups on methylsulfinylalkyl GSLs i.e. glucoiberin and glucoraphanin to produce
methylthioalkyl GSLs i.e glucoiberverin and glucoerucin with the sulfide groups and thus
produced IBV, IBV NIT and ERN, ERN NIT as products. The hypothetic scheme of the putative
bacterial reductase in E. coli O83:H1 NRG 857C is shown in Figure 2.22. Thus, the aim of this
section was to identify the bacterial reductase from E. coli O83:H1 NRG 857C intact cells and
cell-free extract.
Figure 2.22 Hypothetic scheme of the putative bacterial reductase in E. coli O83:H1 NRG 857C cells. A similar scheme is thought to occur in the metabolism of glucoiberin in these two bacteria. EC, E. casseliflavus NCCP-53; ECO, E. coli O83:H1 NRG 857C.
It was found that glucoiberin and glucoraphanin disappeared over time during E. coli
O83:H1 NRG 857C fermentation. Concomitantly, their reduced analogues, glucoiberverin and
glucoerucin increased until 4 or 8 h and then declined (Figure 2.23) due to subsequent
metabolism catalyzed by possibly bacterial GSL-degrading enzyme to IBV, IBV NIT and ERN,
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ERN NIT. The differences in degradation products from the metabolism of glucoiberin and
glucoraphanin in E. coli O83:H1 NRG 857C and E. casseliflavus NCCP-53 could be explained by
the reduction of methylsulfinylalkyl GSLs i.e. glucoiberin and glucoraphanin to (reduced)
methylthioalkyl GSLs i.e. glucoiberverin and glucoerucin (Figure 2.23), respectively over time
by a putative reductase enzyme present in E. coli O83:H1 NRG 857C intact cells.
Figure 2.23 Reduction bioconversion of glucoiberin/glucoraphanin to glucoiberverin/glucoerucin during E. coli O83:H1 NRG 857C fermentation over a time course. The cultures were anaerobically fermented at 37˚C and the presence of GSLs was detected by HPLC analysis. Values are means of triplicates.
To determine whether reductase enzyme of E. coli O83:H1 NRG 857C was inducible by
GSLs, E. coli O83:H1 NRG 857C was grown overnight without glucoraphanin supplementation
in NB broth and the following day the cell-free extracts were obtained. The cell-free extracts
were anaerobically incubated with either 1 mM glucoiberin or glucoraphanin in 0.1 M citrate
phosphate buffer pH 7.0 at 37˚C over a time course. There was no reduction of these GSLs.
However, when a bacterial culture of E. coli O83:H1 NRG 857C was induced with 1 mM
glucoraphanin in NB medium overnight before isolating the cell-free extracts, the reduction of
the sulfoxide groups of glucoiberin and glucoraphanin was observed. The HPLC
chromatograms displaying the reduction bioconversion of glucoiberin and glucoraphanin to
glucoiberverin and glucoerucin by E. coli O83:H1 NRG 857C cell-free extracts (obtained from
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glucoraphanin-induced cells) are shown in Figure 2.24. The reduction bioconversion (%) from
glucoiberin/glucoraphanin to glucoiberverin/glucoerucin was found to be 67 and 56%,
respectively at 16 h (Table 2.19A). These results strongly suggest the existence of active,
inducible, soluble, cytosolic reductase enzyme in E. coli O83:H1 NRG 857C.
Figure 2.24 HPLC chromatograms of methylsulfinylalkyl GSLs converted to methylthioalkyl GSLs by E. coli O83:H1 NRG 857C cell-free extracts (obtained from glucoraphanin-induced cells) over a time course. This experiment was carried out in 0.1 M citrate phosphate buffer pH 7.0 at 37˚C under anaerobic conditions and samples were taken at 4 and 16 h. (A) Glucoiberin, 1 (3.62 min) was converted to glucoiberverin, 2 (11.12 min). (B) Glucoraphanin, 3 (5.33 min) was converted to glucoerucin, 4 (13.8 min). These figures are representatives of triplicates.
To determine whether the reductase enzyme of E. coli O83:H1 NRG 857C is inducible
by other GSL substrates other than glucoraphanin, 1 mM gluconasturtiin was added to E. coli
O83:H1 NRG 857C culture overnight and the following day its cell-free extracts were
incubated with 1 mM glucoraphanin over a time course. It was found that gluconasturtiin-
induced cell-free extracts showed similar trends in the bioconversion of 0.25 mM
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glucoiberin/glucoraphanin to glucoiberverin/glucoerucin (Table 2.21B) when compared with
those from glucoraphanin-induced cell-free extracts (Table 2.21A). This indicates that
bacterial reductase of E. coli O83:H1 NRG 857C is likely to be induced by both methylsulfinyl
GSL i.e. glucoraphanin and also aromatic GSL i.e. gluconasturtiin.
Table 2.21 Reduction bioconversion of glucoraphanin by cell-free extracts of E. coli O83:H1
NRG 857C (obtained from gluconasturtiin/glucoraphanin-induced cells) over a time course
GSL conversion Bioconversion (%)
4 h 16 h A) Glucoraphanin-induced From glucoiberin to glucoiberverin
18 ± 5 67 ± 9
From glucoraphanin to glucoerucin
23 ± 4 56 ± 8
B) Gluconasturtiin-induced From glucoiberin to glucoiberverin
15 ± 6 60 ± 15
From glucoraphanin to glucoerucin
21 ± 8 61 ± 9
Values are means SD, n = 3. This experiment was carried out in 0.1 M citrate phosphate buffer pH 7.0 at 37˚C under anaerobic conditions with 100 µL cell-free extracts using 0.25 mM GSL substrate.
E. casseliflavus NCCP-53 cell-free extracts were also tested for reduction bioconversion
of methylsulfinylalkyl GSLs as previously described with the cell-free extracts of E. coli O83:H1
NRG 857C. It was found that there was no reduction bioconversion of glucoraphanin from any
cell-free extracts of E. casseliflavus NCCP-53, indicating a lack of reductase activity in this
bacterium (data not shown) under the conditions tested.
Not only E. coli O83:H1 NRG 857C cells were able to convert methylsulfinylalkyl GSLs
to methylthioalkyl GSLs, they were also able to convert methylsulfinylalkyl ITC i.e.
sulforaphane to a reduced methylthioalkyl ITC i.e. erucin within 5 h during anaerobic
fermentations at 37˚C in NB broths (Figure 2.25).
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Figure 2.25 GC-MS chromatograms showing reduction bioconversion of sulforaphane to erucin by E. coli O83:H1 NRG 857C intact cells. (A) Sulforaphane, 1 (33.40 min) at 0 h. (B) A decline of sulforaphane, 1 led to an increase of erucin, 2 (23.86 min) after 5 h anaerobic incubation at 37˚C in NB broths. These figures are representatives of triplicates. Similar experiments were carried out using cell-free extracts and resting cells of E. coli
O83:H1 NRG 857C (induced with 1 mM glucoraphanin overnight) incubated with 1 mM
sulforaphane over a time course in 0.1 M citrate phosphate buffer pH 7.0 at 37˚C under
anaerobic conditions. It was found that 28.4 and 11.3% of initial sulforaphane was converted
to erucin at 5 and 22 h in cell-free extracts (Table 2.22). Similarly 21.6 and 8.6% bioconversion
of initial sulforaphane to erucin was detected in induced resting cells of E. coli O83:H1 NRG
857C at 5 and 22 h, respectively (Table 2.22). The control sample containing only 1 mM
sulforaphane without cell-free extracts or resting cells in the buffer showed the decline of 49
and 80% in sulforaphane level at 5 and 22 h (Table 2.22). The levels of both sulforaphane and
erucin observed in cell-free extracts and resting cells also declined between 5 and 22 h (Table
2.22). This was possibly due to the instability of sulforaphane and erucin that may be
conjugated to the buffer components (referred to section 2.3.4) or sulforaphane/erucin
degradation or further metabolism to unknown and/or undetected metabolites.
5 10 15 20 25 30 350
100000
200000
300000 5 10 15 20 25 30 350
200000
400000
600000To
tal I
on C
urre
nt
Retention Time (min)
B
A
2
Tota
l Ion
Cur
rent
1
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Table 2.22 Reduction bioconversion of sulforaphane to erucin by cell-free extracts and
resting cells of E. coli O83:H1 NRG 857C (induced with 1 mM glucoraphanin overnight) over
a time course
Time (h)
Cell-free extracta Resting cells in bufferb Controlc
SFN (μM) ERN (μM) SFN (μM) ERN (μM) SFN (μM)
0 1000 (100) ND 1000 (100) ND 1000
5 245 ± 13 (24.5) 284 ± 9 (28.4) 23 ± 5 (2.3) 216 ± 10 (21.6) 512 ± 13 (51.2)
22 83 ± 10 (8.3) 113 ± 11 (11.3) 4 ± 0.6 (0.4) 86 ± 7 (8.6) 203 ± 9 (20.3)
aCell-free extracts (300 µL) was added to a 1 mL reaction containing 1000 μM sulforaphane at 0 h. bResting cells of OD600nm = 0.5 was added to a 1 mL reaction mixture. cThe control sample containing only 1 mM sulforaphane without cell-free extracts or resting cells in the buffer. Values representing the ITC concentrations remained in the solution are means ± SD, n = 3. This experiment was carried out in 0.1 M citrate phosphate buffer pH 7.0 at 37˚C under anaerobic conditions. ND, Not detected; SFN, Sulforaphane; ERN, Erucin. The GC-MS chromatograms showing the reduction bioconversion of sulforaphane to
erucin by E. coli O83:H1 NRG 857C induced cell-free extracts over a time course in 0.1 M
citrate phosphate buffer pH 7.0 at 37˚C under anaerobic conditions are shown in Figure 2.26.
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Figure 2.26 GC-MS chromatograms showing the reduction bioconversion of sulforaphane to erucin by E. coli O83:H1 NRG 857C induced cell-free extracts over a time course. (A) Sulforaphane, 1 (33.40 min) at 0 h and the control sample containing only sulforaphane without cell-free extract incubated for 22 h. (B) A decline of sulforaphane, 1 led to an increase of erucin, 2 (23.86 min) after 5 h. (C) The levels of both sulforaphane, 1 and erucin, 2 declined at 22 h. Reactions were performed in 0.1 M citrate phosphate buffer pH 7.0 at 37˚C under anaerobic conditions. These figures are representatives of triplicates. From these results, the scheme of glucoraphanin metabolism in E. casseliflavus NCCP-
53 and E. coli O83:H1 NRG 857C has been proposed in Figure 2.27. This is thought to be the
same for the metabolism of glucoiberin.
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Figure 2.27 Different metabolic fates of glucoraphanin in E. coli O83:H1 NRG 857C (ECO) and E. casseliflavus NCCP-53 (EC). Erucin is a reduced analogue of sulforaphane. A similar scheme is thought to occur in the metabolism of glucoiberin in these two bacteria.
2.3.11 Mg2+- and NAD(P)H- dependent reductase activity and its optimal pH and
temperature
The aim of this section was to characterize E. coli O83:H1 NRG 857C reductase in cell-
free extracts. In general, reductase enzymes require reducing co-factors such as NADH or
NADPH for activity (De Jongh et al., 1987; Lamed & Zeikus, 1980; Panagiotou &
Christakopoulos, 2004; Stenbaek et al., 2008). Dehydrogenase enzymes require both a
divalent metal ion and a reducing co-factor for oxidoreductase activity (Goulian & Beck, 1966;
Hektor et al., 2002; Hori et al., 1967). Some reductase enzymes can use either NADH or
NADPH for activity (Corvest et al., 2012; Verduyn et al., 1985; Vermeulen et al., 2006).
To determine whether E. coli O83:H1 NRG 857C reductase require such factors, the
cell-free extracts were desalted to remove any factors present in the cell-free extracts. The
resulting desalted cell-free extracts were added with 1 mM of either Mg2+, FAD, NADH or
NADPH or a combination of two factors. Other metal ions e.g. Mn2+, Fe2+, Fe3+, Ca2+, Co2+, Ni2+,
used in section 2.3.7 were also tested in this experiment in addition to Mg2+. The reaction
mixture was incubated with 0.25 mM glucoraphanin for 24 h and was analyzed by HPLC for
the detection of the bioconversion to glucoerucin. As a result, both Mg2+ and either of NADH
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or NADPH were required as co-factors for reductase activity (Table 2.23). Other metal ions
with/without combination of reducing reagents gave negative results.
Table 2.23 Reduction bioconversion (%) of 0.25 mM glucoraphanin to glucoerucin by the
addition of 1 mM of co-factor(s) in desalted cell-free extracts of E. coli O83:H1 NRG 857C
(obtained from glucoraphanin-induced cells) within 24 h at 37˚C under anaerobic conditions
Treatmentsa % Conversion of glucoraphanin to glucoerucinb
Cell-free extract* 71 ± 5
Freeze-dried factors fraction** 85 ± 8
FAD or NADH or NADPH ND
Mg2+, Mn2+, Fe2+, Fe3+, Ca2+, Co2+, or Ni2+ ND
FAD + Mg2+ ND
NADH + Mg2+ 52 ± 4
NADPH + Mg2+ 58 ± 9
NAD(P)H + other metal ion ND
aDesalted cell-free extracts were mixed with co-factor(s) indicated. bConversion (%) to glucoerucin (mol) as (%) relative to the initial dose of glucoraphanin (mol) as analyzed from HPLC chromatograms. Values are means ± SD, n = 3. *Cell-free extracts (non-desalted) alone without any addition of co-factors. **Salt fraction (from non-desalted cell-free ectracts) collected during desalting step and freeze-dried and then added to desalted protein extracts. ND, Not detected.
The HPLC chromatograms showing the effects of co-factor(s) on reductase activity in
the desalted E. coli O83:H1 NRG 857C cell-free extracts at 24 h at 37˚C under anaerobic
incubations are shown in Figure 2.28.
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Figure 2.28 HPLC chromatograms showing the effects of co-factor(s) on reductase activity in E. coli O83:H1 NRG 857C cell-free extracts. (A) Desalted cell-free extracts with 0.25 mM glucoraphanin, 1 (5.33 min) without any factors. (B) Desalted cell-free extracts added with a solution of freeze-dried factors showed bioconversion from 1 to glucoerucin, 2 (13.8 min). (C) Desalted cell-free extracts added with 1 mM of each FAD, NADPH, and, NADH factors. The peak, 3 at 15.3 min indicates the presence of FAD without bioconversion. (D) Desalted cell-free extracts added with 1 mM MgCl2. (E) Desalted cell-free extracts added with 1 mM of both FAD and MgCl2. (F) Desalted cell-free extracts added with 1 mM of both NADPH and MgCl2. (G) Desalted cell-free extracts added with 1 mM of both NADH and MgCl2. The reactions were performed in 0.1 M citrate phosphate buffer pH 7.0 at 37˚C under anaerobic conditions for 24 h. The figures are representatives of triplicates.
The optimal temperature and pH of reductase activity in cell-free extracts in the
bioconversion of glucoraphanin to glucoerucin as detected by HPLC analysis were found at
37˚C and pH 7.0, respectively (Figure 2.29A and 2.29B). It is interesting to note that previous
study on reduction of an uricosuric drug called sulphinpyrazone by human or rabbit faeces
153
gave greater reduction under anaerobic than under aerobic conditions (Strong et al., 1987). In
this work, however, both aerobic and anaerobic conditions resulted in similar rates with no
significant difference in the bioconversion of glucoraphanin to glucoerucin by reductase in E.
coli O83:H1 NRG 857C cell-free extracts over a time course (Figure 2.29C). Similarly, the
recent study showed that the presence of oxygen did not influence the bioconversion of
methylsulfinylalkyl GSLs in Escherichia coli Nissle 1917 and Enterobacter cloacae ATCC13047
(Mullaney et al., 2013).
Figure 2.29 Effects of temperature, pH and aeration on reductase activity in E. coli O83:H1 NRG 857C cell-free extracts (obtained from glucoraphanin-induced cells in the bioconversion (%) of glucoraphanin to glucoerucin. (A) Optimal temperature was found at 37˚C. (B) Optimal pH was found at pH 7.0. The reactions were performed in 0.1 M citrate phosphate buffer for 24 h under anaerobic conditions. (C) The effect of aerobic and anaerobic conditions upon reductase activity. Values are means of triplicates.
From these results, it was found that reductase enzyme in E. coli O83:H1 NRG 857C
cell-free extracts is inducible by GSLs, oxygen-independent, Mg2+- and NAD(P)H-dependent
for its sulfoxide reductivity towards methylsulfinylalkyl GSLs.
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2.4 Summary of findings
The summary of key findings in this chapter is shown in Figure 2.30.
Figure 2.30 Summary of key findings in this chapter. (A) Bacterial fermentations in culture broths. (B) Bacterial resting cells in 0.1 M citrate phosphate buffer pH 7.0. (C) Bacterial reductase from cell-free extract in 0.1 M citrate phosphate buffer pH 7.0. LA, L. agilis R16; ECO, E. coli O83:H1 NRG 857C; EC, E. casseliflavus NCCP-53.
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2.5 Discussion:
2.5.1 Bacterial GSL-degrading activity
This report showed GSL-degrading capacity from six strains of human gut bacteria that
have never been published before. Enterococcus sp. C213 and E. faecium KT4S13 are NIT
producers. However, clone SEW-E-011, E. casseliflavus NCCP-53, L. agilis R16 (obtained from
Palop et al. (1995), E. coli UMNF18 and E. coli O83:H1 NRG 857C are both ITC and NIT
producers. This suggests the presence of GSL-degrading activity or bacterial myrosinase-like
activity, similar to plant myrosinase, in these human gut bacteria. This is the first report to
show the time-course degradation product profiles from the metabolisms of different GSLs
including sinigrin, glucotropaeolin, gluconasturtiin, glucoerucin, glucoiberin, glucoraphanin,
glucobrassicin and certain corresponding DS-GSLs by the two chosen bacteria Enterococcus
casseliflavus NCCP-53, E. coli O83:H1 NRG 857C and a bacterium L. agilis R16. A general trend
of ITC and NIT production over a time course was shown for the first time upon different GSL
metabolism in the three bacteria. For most GSLs, once ITC production peaked during bacterial
fermentations, it gradually declined while NIT production gradually increased and remained
fairly constant or slightly declined for certain GSLs in certain bacteria. The stability test of
several authentic ITC/NIT standards in culture broths with and without the presence of
bacterial cells and in different aqueous solutions have been carried out for the first time. The
results showed that all ITC levels decline over a time course in all solutions whereas NIT levels
stayed fairly constant except ANIT.
This is the first finding of ITC products detected upon the metabolism of glucoraphanin
and glucoiberin in bacterial fermentations. E. coli O83:H1 NRG 857C produced erucin and
erucin NIT products from glucoraphanin, and iberverin and iberverin NIT from glucoiberin. It is
likely that this bacterium cannot metabolize these GSLs directly. However, E. casseliflavus
NCCP-53 produced sulforaphane and iberin from glucoraphanin and glucoiberin, respectively
without NIT production. Interestingly, both bacteria were found to metabolize glucoerucin
more readily and produced the corresponding erucin and erucin NIT products at higher levels
than when glucoraphanin and glucoiberin were used as substrates. This result is different
from the previous study showing only NIT products were produced from the metabolisms of
glucoraphanin and glucoiberin in Lactobacillus plantarum KW30, Lactococcus lactis subsp.
lactis KF147, Escherichia coli Nissle 1917 and Enterobacter cloacae (Mullaney et al., 2013). The
different hydrolysis products obtained from the same GSLs in different bacterial strains
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underscore the diversity of gut bacterial GSL-degrading enzymes that may partly explain the
inter-individual variation in GSL metabolism and bioavailability observed in epidemiological
studies (Ambrosone et al., 2004; Higdon et al., 2007; Seow et al., 2005; Steck et al., 2007).
Since there is very few evidence in the metabolism of DS-GSLs in bacterial
fermentation, the time-course degradation product profiles from the metabolisms of
different DS-GSLs by the three bacteria were performed for the first time. The results showed
that pure NITs were produced from the metabolisms of most DS-GSLs during bacterial
fermentations. This supports the speculation that DS-GSL is a pre-cursor to NIT production
(Wathelet et al., 2001). This finding is in accordance with previous work where DS-GSL, the
intermediate, hypothesized by Smits et al. (1993) explains why ANIT formation continues
after total disappearance of GSL in their experiments. Thus, it is probable that these bacteria
may exhibit sulfatase activity that desulfates intact GSLs to produce DS-GSLs and hence NIT
production, in addition to ITC production, from the metabolism of intact GSLs. Interestingly,
this is the first finding to show that bacterial resting cells produced only ITCs (without any
NITs) from the metabolism of GSLs in citrate phosphate buffer pH 7.0. Also, NIT production
only occurred in the culture media during bacterial fermentations. It was found that Fe2+ ions
(present in the culture broths used) are required for NIT productions from bacterial
metabolisms of GSLs in citrate phosphate buffer pH 7.0.
Our results confirm that human gut microbiota is diverse in its capacity to metabolize
GSLs to different products. As previously reported, certain human gut bacteria such as B.
pseudocatenulatum, B. adolescentis and B. longum produced NITs predominantly from
sinigrin and glucotropaeolin metabolism (Cheng et al., 2004) while some bacteria such as L.
agilis R16 and B. thetaiotaomicron produced ITCs predominantly from sinigrin metabolism
(Elfoul et al., 2001). There may be different enzymes/mechanisms involved in the metabolism
of the same or different GSLs by different bacteria. In addition, the structure of GSL substrate
e.g. the size and the high polarity of sulfoxide group of glucoraphanin and glucoiberin may
render β-thioglucosidic bonds of these GSLs inaccessible to bacterial GSL-degrading enzymes,
and thus influencing the metabolic capacity of each bacterium. That may be the reason why L.
agilis R16 cannot metabolize glucoraphanin or and glucoiberin to ITC/NIT products. Our result
supports the previous reports suggesting that individual GSLs are differently affected by
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digestive enzymes in vitro (Maskell & Smithard, 1994). Clearly GSL metabolism in the human
gut is a much more complex process than previously thought.
It was found in this work that ITCs are unstable in aqueous solutions. This effect was
more pronounced when bacterial cells were present in the medium. In contrast, the levels of
most NITs except for ANIT in broths remained fairly constant without bacterial cells with a
slight decline in the presence of bacterial cells. The fact that NITs are less labile than ITCs may
be a rationale for rather constant NIT production from all GSL metabolisms during bacterial
fermentations. Also, both ITC and NIT production occurred in the pH range of 3.7-7.6. This
contradicts with the previous thought that NIT production in culture broths was due to low pH
conditions (Cheng et al., 2004; Mullaney et al., 2013).
Thus far, our results are in agreement with the previous findings from previous studies
reporting that ITCs are unstable in aqueous solutions. The electrophilic character of the
functional isothiocyanic group has enabled ITCs to react with some nucleophilic agents
including amino, hydroxyl, thiol, carboxylic acids from small peptides, amino acids and water
(Zhang et al., 1996; Cejpek et al., 1998) and probably flavonols to potentially generate new
compounds (Cejpek et al., 2000; Kawakishi & Kaneko, 1987; Luciano et al., 2008). The
reactions of AITC with alanine, glycine, and several peptides in model systems have been
described (Cejpek et al., 2000). In the previous report, most sulforaphane was lost at 24 h
incubation with bacteria, and almost 50% loss was also found without bacteria (Basten et al.,
2002; Lai et al., 2010). This was also the case with AITC (Combourieu et al., 2001; Ye et al.,
2002; Zhang, 2004). It has been proposed that the composition of the media or the buffer
may react with sulforaphane (or any ITCs), and thus depleted ITCs in the culture broths
(during bacterial fermentations) and the buffer used in this work. Our results indicate that the
ITC instability in the media/buffer is currently underestimated. Thus, the total percentage
products obtained from GSL metabolism represented in this work and previous works may be
underestimated. However, it still remains unclear whether ITC/NIT products generated during
bacterial fermentations behave in the same way as those purchased ITC/NIT standards did in
the stability test. AITC has been reported to be unstable and is gradually decomposed to other
compounds having a garliclike odor in the presence of water at both room temperature and
37°C (Kawakishi & Namiki, 1969). AITC is also sensitive to temperature and pH. The high
temperature of 37°C and alkaline conditions accelerate the decomposition of AITC (Ina et al.,
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1981). The decomposition rate of AITC in a low concentration range (below 1.6 mM) obeys
the first-order rate equation, and its degradation kinetics can be explained by the nucleophilic
attack of hydroxide ions and water molecules on the AITC molecule (Ohta et al., 1995). In
aqueous solution, pH and especially temperature have an influence on the decomposition of
AITC (Ohta et al., 1995). In addition, Combourieu et al., (2001) also tested the stability of AITC
and BITC incubated in the buffer in the absence of cells for 48 h at 37°C under the same
conditions as those employed with bacterial incubations. Both allylamine and benzylamine
were detected by 1D 1H NMR spectroscopy indicating the high sensitivity of these ITCs to
hydrolysis (Combourieu et al., 2001). In the previous report, after 17 h incubation of sinigrin
with L. agilis R16, a 45% decline in AITC concentration was observed as well as the control
incubation of AITC in broth without bacteria (Palop et al., 1995). This indicates a spontaneous
chemical transformation of AITC, and the chemical nature of any ITC conversion product
therefore remains to be investigated. Other ITCs have also been reported for their instability
in aqueous solutions. For examples, PITC is unstable in aqueous media and rapidly degraded
to phenethylamine at low pH (Negrusz et al., 1998). In our study, the total percentage
products from the metabolisms of all GSLs by all three bacteria never reached 100% in spite of
high degradation rates up to 100% of most GSLs over 24 h. This suggests that there might be
other metabolite products that were not detected by current methods or ITCs may be further
degraded by bacteria (Kliebenstein et al., 2001; Palop et al., 1995; Tang et al., 1972).
Therefore, in theory, higher GSL degradation rate by bacteria does not necessarily always
translate into a higher ITC yield and higher ITC exposure for the host.
Although, conversion of GSLs to ITCs by plant myrosinase (S. alba) was shown to have
a yield of up to 90% (Kawakishi & Muramatsu, 1966; Piotrowski, 2004). Other previous studies
showed that the percentage products of most bacterial GSL metabolisms were far from 100%
(Cheng et al., 2004; Combourieu et al., 2001; Giamoustaris & Mithen, 1996; Hall et al., 2001;
Krul et al., 2002; Mithen et al., 1995; Palop et al., 1995; Parkin et al., 1994). This suggests that
the efficiency of bacterial GSL-degrading enzyme is lower compared to the action of plant
myrosinase (Krul et al., 2002) or metabolites other than ITCs may be formed during the
metabolism. By using 1D and 2D 1H NMR spectroscopy, Combourieu et al. (2001) have clearly
shown that sinigrin and glucotropaeolin are converted by the human fecal microbiota into
allylamine and benzylamine, respectively. This finding is in contradiction with most studies
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showing that human gut bacteria produced ITCs from GSLs (Shapiro et al., 1998; Getahun and
Chung, 1999; Elfoul et al., 2001), and low amounts of ITCs were recovered accounting for 10
to 20% of the initial amounts of GSLs. From our results, amines or alcohols as derivatives of
ITC/NIT products were not detected on GC-MS chromatograms suggesting no such
degradation of ITC/NIT products occurred in the three bacteria tested. However, the
unaccounted for metabolite products, if any, should be further investigated.
This work demonstrated that Fe2+ ions are required for NIT productions from GSL
metabolisms by bacterial resting cells in the buffer. Similarly, plant myrosinases also requires
Fe2+ ions as co-factors for NIT production from GSL metabolism in vitro (Sørensen, 1990;
Burow et al., 2006; de Torres Zabala et al., 2005). However, GSL degradation to NIT products
can also occur via a non-enzymatic mechanism catalyzed by Fe2+ (Bellostas et al., 2007;
Bellostas et al., 2009). From our results, NITs were produced only in trace amounts from
intact GSLs in the buffer containing 5 mM Fe2+ ions without bacterial cells suggesting a non-
enzymatic NIT production caused by Fe2+ ions. It is likely that myrosinase-catalyzed NIT
production by gut bacteria was also promoted by Fe2+ ions present in culture broths. An
increased NIT production in the presence of Fe2+ has been previously reported both in the
presence (Agerbirk et al., 1998; de Torres Zabala et al., 2005) and the absence of myrosinase
(Bellostas et al., 2008; Austin et al., 1968). Similar to our results, inhibition of ITC production
in the presence of myrosinase and Fe2+ has been observed as an outcome of enhanced NIT
production (Agerbirk et al., 1998; de Torres Zabala et al., 2005; Bellostas et al., 2009). It has
been hypothesized that NIT production by Fe2+ in the absence of myrosinase involves the
formation of a GSL–Fe2+ complex, which leads to the formation of the NIT (Bellostas et al.,
2008). NIT formation from GSLs through myrosinase-mediated degradation has been known
to be influenced by the low pH of the media (Gil & MacLeod, 1980; VanEtten et al., 1966)
and/or the presence of Fe2+ ion (Austin et al., 1968; Tookey & Wolff, 1970; Uda et al., 1986).
The previous study showed that ANIT production from sinigrin occurred above pH 6.30 at 80
μM of Fe2+ ion in the incubation mixtures (Lu et al., 2011). In comparison with the reported
data (Austin et al., 1968; Bellostas et al., 2007; Uda et al., 1986), this concentration was
significantly lower to promote ANIT formation from sinigrin the digestive incubation mixture.
This suggests that the human gut bacteria may utilize another mechanism for NIT formation
instead of the promotive effect of Fe2+ ion and/or a lower medium pH (Lu et al., 2011).
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Whether human gut bacteria utilizes the ESP-involving route for the formation of NIT
production from DS-GSL remains to be determined by further investigations (Lu et al., 2011).
The bacterial GSL-degrading activity (a.k.a. myrosinase-like activity) of the three
bacteria responsible for producing ITCs and NITs were found to be inducible by GSL substrate
in resting cells experiments. This finding supports the speculation that bacterial GSL-
degrading activity is inducible by GSLs. For examples, bacterial myrosinases of Enterobacter
cloacae and L. agilis R16 were produced only in the presence of the inducer such as sinigrin
and mustard extract, respectively (Tani et al. 1974, Palop et al., 1995). From the cell-free
extracts experiment, glucoiberin/glucoraphanin was directly converted to
glucoiberverin/glucoerucin by E. coli O83:H1 NRG 857C cells without being further
metabolized suggesting that there was no GSL-degrading activity in cell-free extracts. It is
speculated that GSL-degrading activity may be in the membrane/debris fraction or is an
insoluble enzyme or part of a protein complex. Thus far, GSL-degrading activity, as indicated
by ITC/NIT production from GSL metabolism, was only detected in bacterial intact cells during
fermentation experiments, not in cell-free extracts. This is in accordance with the previous
report that sinigrin-degrading activity of L. agilis R16 was always associated with the presence
of intact cells (Palop et al., 1995; Prescott & John, 1996) indicating that intracellular or cell-
associated activity is always involved. Also, fungal myrosinase of Aspergilus niger was
reported to be remarkably unstable and could not be protected by stabilizing agents
(Kliebenstein et al., 2001; Ohtsuru & Hata, 1973). The instability of bacterial GSL-degrading
enzyme may be the issue with the bacteria studied in this work. To date, the only bacteria
that showed myrosinase activity in cell-free extracts include Gram-positive Bifidobacterium
(Cheng et al., 2004), Gram-negative Enterobacter cloacae (Tani et al. 1974) and Gram-
negative Citrobacter (Abdulhadi Albaser, PhD thesis). Interestingly, for the case of Citrobacter,
ITC production from the metabolism of GSLs in broths and citrate phosphate buffers was
barely detected by GC-MS analysis, but a glucose release from GSL degradation to glucose
was detected by GOD-PERID assays (personal communications). A similar result was also
obtained from Bifidobacterium (Cheng et al., 2004) where ITCs were not detected from the
metabolism of GSLs. These findings are different from our results obtained from bacterial
fermentations showing both ITC and NIT productions from most GSL metabolisms. This
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suggests the diversity in enzymes/mechanisms involved in the metabolism of the same or
different GSLs by different bacteria.
2.5.2 Bacterial reductase activity
The bacterial reductase involved in the GSL metabolism was partially characterized for
the first time in this work. The reductase from E. coli O83:H1 NRG 857C cell-free extract is
inducible by GSLs, oxygen-independent and requires Mg2+ ion and NADP(H) as co-factors for
its activity with optimum pH and temperature at pH 7.0 and 37˚C, respectively. This reductase
was shown to be able to biotransform methylsulfinylalkyl GSLs (sulfoxide) to methylthioalkyl
GSLs (sulfide) and also biotransform methylsulfinylalkyl ITC to methylthioalkyl ITC. This result
supports the previous finding of the bioconversion of methylsulfinylalkyl GSLs i.e. glucoiberin
and glucoraphanin by a reduction reaction in human gut bacteria (Lai et al., 2010; Mullaney et
al., 2013; Saha et al., 2012).
It was speculated that the sulfoxide groups on glucoiberin and glucoraphanin may
present steric effects that prevent bacterial GSL-degrading enzyme to gain access to the β-
thioglucosidic bonds of these GSLs or prevent the transportation of GSLs into bacterial
cytoplasm in Gram-positive bacteria or periplasm in Gram-negative bacteria. The transport of
GSL and GSL-degrading enzyme activity may be tightly linked. E. coli O83:H1 NRG 857C seems
to overcome this problem by expressing a reductase enzyme to bioconvert the sulfoxide
groups of methylsulfinylalkyl GSLs i.e. glucoiberin/glucoraphanin to the sulfide groups of
methylthioalkyl GSLs i.e. glucoiberverin/glucoerucin before the latter being metabolized by
bacterial GSL-degrading enzyme to corresponding ITC and NIT products. It was thought that E.
coli O83:H1 NRG 857C cannot metabolize methylsulfinylalkyl GSLs directly as no
corresponding oxidized product series were detected. Due to the bacterial reductase, higher
levels of products were obtained from glucoiberin/glucoraphanin metabolism in E. coli
O83:H1 NRG 857C than those obtained in E. casseliflavus NCCP-53. From our results, the
interconversion of iberverin and iberin products are expected to be in a manner analogous to
that of sulforaphane and erucin as previously reported (Bheemreddy & Jeffery, 2007;
Kassahun et al., 1997; Lai et al., 2010; Saha et al., 2012). Since bioconversion of GSL can be
achieved by human gut bacteria, one could assume that the consumption of Brassica
vegetables rich in glucoerucin (e.g. rocket salad) or glucoiberverin may give rise to the same
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active components in vivo as glucoraphanin-containing broccoli species. Although this
reduction bioconversion may be part of bacterial oxidoreduction process that can be
reversible, there was no proof of a reversible oxidation reaction as there was no conversion to
sulforaphane from erucin production during the metabolism of glucoerucin in E. coli O83:H1
NRG 857C fermentation. Also, the amounts of the reduced methylthioalkyl GSL always
increased over a time course and above the oxidized methylsulfinylalkyl species in E. coli
O83:H1 NRG 857C cell-free extracts.
It has been long known that under the anaerobic conditions in the human gut, the
principal reaction of sulfoxides is a reduction to the corresponding sulfides. Sulfoxides that
have been tested extensively both in vivo and in vitro are the xenobiotics sulphinpyrazone and
sulindac. Sulphinpyrazone is a uricosuric drug that is metabolized to a sulfide analogue with a
platelet anti-aggregatory activity, ten times more active than its sulfoxide counterpart (Del
Maschio et al., 1984). Studies in the rat (Renwick et al., 1982; Kashiyama et al., 1994), rabbit
(Strong et al., 1984b) and in humans (Strong et al., 1984a) have shown that intestinal
microflora are exclusively responsible for reduction bioconversion of sulphinpyrazone to the
active sulfide metabolites. Sulindac is a sulfoxide prodrug that requires reduction to the active
anti-inflammatory sulfide analogue. The human gut bacteria were shown to reduce sulindac in
vitro (Galletti et al., 2001; Strong et al., 1987). Studies with over 200 isolated strains of human
bacteria showed significant sulfoxide reduction by several facultatively anaerobic bacteria,
such as E. coli, Klebsiella oxytoca and KIebsiella pneumoniue under anaerobic conditions
(Strong et al., 1987). Interestingly, it was reported that the sulfoxide R(+)-flosequinan was
reduced by these bacteria to the sulfide. This stereoselectively demonstrates that chiral
inversion at the sulfoxide position of flosequinan enantiomers via stereoselective reduction of
sulfoxide was enabled by human gut bacteria (Eiji et al., 1994; Kashiyama et al., 1994).
Sulfoxides were also found to be reduced via aldehyde dehydrogenase or a hepatic
thioredoxin-dependent system in the presence of an electron donor (Lee & Renwick, 1995). At
least three different soluble enzymes in E. coli capable of reducing sulindac are present. One
of which appeared to be a NADPH-linked thioredoxin system; only one of the enzymes was
capable of reducing the more hindered sulfoxide groups in sulphinpyrazone or flosequinan
(Botti et al., 1995; Lee & Renwick, 1995). From the same study, NADH, NADPH and
dithiothreitol (DTT) were shown to act as co-factors for sulfoxide reductase activity in E. coli
cytosolic fraction that had reduction activity with sulindac, diphenyl sulfoxide and
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sulphinpyrazone. There is a possibility that multiple sulfoxide reductase systems are present
in E. coli cytosol (Chen & Halkier, 1999; Lee & Renwick, 1995). Similar to the above report, our
results showed that cytosolic E. coli O83:H1 NRG 857C reductase is oxygen-independent and
NAD(P)H- and Mg2+ -dependent for its sulfoxide reduction towards methylsulfinylalkyl GSLs.
The search for the corresponding gene or protein responsible for sulfoxide reduction in E. coli
O83:H1 NRG 857C is underway in our group.
Interestingly, 6-phospho-β-glucosidase (NCBI Ref: YP_006120095.1) of E. coli O83:H1
NRG 857C is the only β-glucosidase (out of six) with the predicted gene ontology in
oxidoreduction activity (Consortium, 2012) and contains sugar binding site, NAD binding site,
and divalent metal binding site. This protein is a member of glycoside hydrolase family 4
(GH4) with the unique requirement for NAD(H) and a divalent metal for oxidoreduction
activity (Henrissat et al., 1995; Thompson et al., 1998; Thompson et al., 1999). It remains to
be determined whether this 6-phospho-β-glucosidase is capable of reducing the sulfoxide on
methylsulfinylalkyl GSL or ITC/NIT series. However, the recent report proposed that the
enzyme methionine sulfoxide reductase A (MsrA) EC 1.8.4.11 (ExPASy) may be responsible for
the reduction bioconversion (Mullaney et al., 2013). Previously, the membrane-associated
and soluble peptide methionine sulfoxide reductases in E. coli were found to require NADPH
for its reduction activity (Lori et al., 1999; Spector et al., 2003). Also, sulfoxide reductase
catalytic subunit YedY of E. coli O127:H6 strain E2348/69 was able to catalyze the reduction of
a variety of substrates e.g. trimethylamine N-oxide, dimethyl sulfoxide, L-methionine
sulfoxide and phenylmethyl sulfoxide with the requirement of molybdenum as a cofactor
(Iguchi et al., 2008). In E. coli O83:H1 NRG 857C, ten sulfoxide reductases remain to be tested
for reduction activity upon methylsulfinylalkyl GSLs.
Thus far, our findings from this work underline the significant influence of human gut
bacteria on the metabolic fate of GSLs. ITC products generated from these metabolisms may
promote chemoprevention in human health. In addition, bacterial reductase showing the
reduction bioconversion of methylsulfinylalkyl GSLs to methylthioalkyl GSLs provides a link to
the sulfoxide reduction of xenobiotics in humans. It remains to be determined whether this
reductase can also act upon xenobiotics.
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Chapter 3: Forward proteomics approach to identify bacterial proteins potentially involved in the metabolism of GSLs 3.1 Introduction
In Chapter 2 (section 2.3.6), resting cells experiment demonstrated that the putative
bacterial GSL-degrading enzyme activity from all three bacteria tested is likely to be inducible
by GSL supplementation as the resting cells from GSL-induced overnight cultures yielded
higher GSL degradation and corresponding ITC products in the buffer as opposed to those
cells from overnight cultures without GSL supplementation that produced no ITC product with
less GSL degradation. It is therefore hypothesized that GSL supplementation is likely to induce
GSL-degrading enzyme and possibly other enzymes involved in bacterial GSL metabolism.
Thus, forward proteomics approach using 2-DE technique was performed to compare the
protein patterns on 2-DE gels obtained from protein extracts isolated from the cells with and
without GSL supplementation. The distinctively expressed or upregulated proteins found in
bacterial cultures grown on media upon GSL supplementation are expected to be involved in
bacterial GSL metabolism.
3.1.1 Forward proteomics
The term ‘proteome’ coined by Marc Wilkins in 1994 describes the entire set of
proteins encoded by the genome of an organism, cell or tissue at a given time (Wilkins et al.,
1996). Therefore, the term ‘proteomics’ is the study of proteomes which may entail several
different aspects related to the study of proteins at a global or cellular level. This includes the
analysis of protein expression patterns, biological function, macromolecular protein structure,
spatiotemporal intracellular distribution, stability and turnover rates, posttranslational
modification (PTM) as well as protein–protein interactions. Thus far, proteomics has been
mainly considered as an approach allowing for either protein identification from complex
mixtures of proteins or the characterization of changes at the level of their expression/PTM
levels. This has been termed ‘forward proteomics’ which primarily depends on the power of
sample preparation technologies, mass spectrometry (MS) analysis and bioinformatics to
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achieve satisfactory goals (Cristoni & Bernardi, 2004).
Classical forward proteomics work involves two dominant strategies; a gel-based
approach and a gel-free based approach (Figure 3.1). The gel-based approach involves a
separation step, usually by a means of two-dimensional gel electrophoresis (2-DE) followed by
imaging analysis, spot excision, protein digestion and protein identification using mass
spectrometry (MS) (Figure 3.1) (Andersen & Mann, 2000). Proteins resolved by 2-DE can be
identified by in-gel trypsin digestion via peptide mass fingerprinting (PMF) using MS or
tandem mass spectrometry (MS/MS) (Link et al., 1999). The gel-free based approach is based
on the use of stable isotope tagging and liquid chromatography (LC-MS) (Aebersold & Mann,
2003). The perturbed and non-perturbed protein extracts are differentially labeled with
different stable isotopes (12C/13C, 14N/15N and 1H/2H). This enables the same peptide from
two different samples to exhibit the same chemical behavior, with a difference in mass
detectable by MS techniques. Peptide peak intensities can be used for relative quantification
of these peptides. The steps of this approach are as follows: (1) differential isotopic labelling;
(2) digestion of combined protein samples to obtain peptide mixtures; (3) chromatographic
fractionation of mixed peptide samples; (4) analysis of the separated peptides by MS/MS; and
(5) processing of the MS results to obtain relative protein abundance as well as protein
identification by database searching (Figure 3.1). This strategy is also known as shotgun
proteomics.
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Figure 3.1 Strategies for forward proteomics. Gel-based proteomics (on the left) mainly involves the use of 2-DE, protein digestion and MS. LC-MS driven proteomics or gel-free based proteomics (on the right) involves the use of stable isotope tagging and liquid chromatography (LC-MS). This figure was taken from Roepstorff (2012).
In this work, a preferred strategy called ‘GeLC-MS’ was used to separate the proteins
by 2-DE technique, the gel spots were sliced and digested followed by LC-MS/MS analysis
(Figure 3.2).
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Figure 3.2 Combined gel-LC-MS based strategy (GeLC-MS). This figure was taken from adapted from Roepstorff (2012).
3.1.2 Two-dimensional electrophoresis (2-DE)
Two-dimensional electrophoresis (2-DE) was developed almost 40 years ago (Klose,
1975; O' Farrell, 1975). Two different separation methods are combined in 2-DE: isoelectric
focusing (IEF) and ‘conventional’ sodium-dodecyl sulfate polyacrylamide gel electrophoresis
(SDS-PAGE) in order to separate proteins on the basis of pI and molecular weight, respectively.
Therefore, individual protein components can be spatially resolved and subsequently be
visualized as ‘spots’ on the gels.
Any single-dimension method cannot resolve more than 80–100 different protein
components. However, it was shown that 1,100 different proteins from lysed E. coli cells were
resolved on a single 2-DE map (O' Farrell, 1975). Theoretically, 2-DE is capable of resolving up
to 10,000 proteins simultaneously (Klose, 1975), with approximately 2,000 proteins being
routine, and detecting and quantifying protein amounts of less than 1 ng per spot (Lopez,
2007).
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The limitations of the 2-DE approach are well known, i.e. poor solubility of membrane
proteins, limited dynamic range and difficulties in displaying and identifying low-abundance
proteins. However, 2-DE still remains as one of the major separation techniques for the next
years because its resolution and the advantage of storing the isolated proteins in the gel
matrix until further analysis is unrivalled by any other alternative technique. To date, there
are more than 5,000 publications reported using the 2-DE technique for analyzing protein
patterns in a plethora of biological systems (Figure 3.3). The increasing trend was observed
from 1996 to 2011.
Figure 3.3 List of publications in proteomic field by means of two-dimensional electrophoresis technology as of Dec 2011. The list is generated using PubMed search with keywords ‘two-dimensional electrophoresis,’ ‘2-DE,’ ‘2-D electrophoresis,’ ‘2-D gel electrophoresis,’ ‘2D-PAGE,’ ‘2D-DIGE’ or ‘DIGE’ and each of ‘proteome,’ ‘proteomic’ or ‘proteomics.’ A growing trend is observed in the late 1990s to early 2000s. The number of publications is levelled in recent years, suggesting an importance of gel-based approaches in proteomics is still evident at present.
3.1.3 Work-flow of gel-based strategy
3.1.3.1 Protein preparation
When cultured cells are used, highly consistent conditions are required. As for any
experimental approach, sample preparation is the most critical part of proteomics
experiments. This step involves tissue/cell homogenization and/or lysis.
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In general, proteins can be found in cytoplasm, inner membrane, outer membrane,
periplasm (in the case of Gram-negative bacteria) or extracellularly (secreted). Various
procedures can be used to obtain specific cell fractions, enabling their protein content to be
determined (Figure 3.4). For Gram-negative bacteria, the periplasmic extract can be isolated
by cell spheroblasting, followed by differential centrifugation, or by a cold osmotic shock
method. After separation of periplasmic proteins, cell lysis can be used to isolate the
cytoplasmic proteins, with the membrane fraction separated by centrifugation. The inner and
outer membranes of Gram-negative bacteria can be isolated by selective cell lysis using
lysozyme or ethylenediaminetetraacetic acid (EDTA) treatment, by mechanical methods such
as the use of a French Press, or by using commercially available chemical lysis reagents
(mostly detergents) (Thein et al., 2010). After lysis, distinct inner and outer membrane
vesicles are formed, which can be separated from each other by density centrifugation (with
the inner membrane vesicles having a higher density). Selective detergent treatment, such as
with Triton X-100, which preferentially dissolves cytoplasmic membranes, can also be used to
separate inner and outer membrane protein fractions. In Gram-positive bacteria, cell surface
proteins have been successfully isolated for analysis. The methodology that is known as
surface shaving liberates surface exposed protein domains by digesting the cell surface with
enzymes such as trypsin or proteinase K. Choosing the appropriate fractionation method is
essential to the success of subcellular proteomics as cross-contamination of the various
fractions will seriously affect the results.
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Figure 3.4 Sub-cellular fractionation of Gram-negative bacterial cell culture. Centrifugation was utilized to separate intact bacterial cells from culture medium and extracellular proteins. Protein samples in the supernatant constitute the extracellular fraction. Periplasm can be isolated by cell spheroblasting or cold osmotic shock treatment followed by ultracentrifugation. The cytosolic frac- tion and membrane fraction can be isolated separately via various cell lysis procedures, detergent treatment and ultracentrifugation. This figure was taken from Curreem et al., (2012).
3.1.3.2 Protein separation
The 2-DE technique combines two dimensions of physical protein separation by their
chemical properties (Klose, 1975; O' Farrell, 1975). Firstly, the proteins are arranged according
to their content of basic or acidic amino acids on a linear gel with an immobilized pH-gradient
(Bjellqvist et al., 1982; Klose, 1975), and are separated by their isoelectric point (pI). Secondly,
pI-separated proteins are separated by their molecular size similar to a conventional SDS-
PAGE (Klose, 1975; Laemmli, 1970). These two combined techniques gives rise to a high-
resolution separation of single protein types on a two-dimensional arrangement of proteins.
The separated proteins can be visualized on the gel by different staining methods, for
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example, Coomassie brilliant blue (Meyer & Lamberts, 1965), silver (Rabilloud et al., 1988), or
fluorescent staining (Berggren et al., 1999). Each spot on a 2-DE gel represents one protein
species, and a specific pattern of the spots on the gel corresponds to each cell or a cellular
condition. Thus, changes of the cellular proteome such as its gene activity and metabolism
under healthy or diseased conditions can be determined by changes in this spot pattern
(Klose, 1975).
3.1.3.3 Gel analysis, spot detection and quantification
Following the previous step, the gel images were captured by using laser imaging
devices, scanners, or charge-coupled device (CCD) camera-based (Berth et al., 2007). The
obtained digitized computer images of the gel can be displayed with common image analysis
software. The quantitative information of the gel is transformed into computer-readable data
via image capture step. Next, most 2-DE programs follow these steps for the evaluation of 2-
DE gel images: spot detection, spot filtering, spot editing, background correction, gel
matching, normalisation, comparison, quantification and reporting and exporting of data. One
of the crucial steps is normalisation. Before the gels are compared for differences in the spot
pattern, the spot volumes of the different gels have to be adjusted by normalisation. This step
corrects for different protein loads and staining effectiveness. Gels are normalised according
to the total spot volume or the volume of a single prominent reference protein (Berth et al.,
2007).
3.1.3.4 Spot excision and digestion
After gel analysis, the next procedure involves several steps: (1) excision of the spot of
interest; (2) treatment with an appropriate protease (e.g. trypsin); (3) extraction (purification)
of the peptide fragments produced; followed by (4) mass spectrometric analysis.
3.1.3.5 Protein identification by mass spectrometry
There are two main approaches for the identification of proteins using MS-based
techniques: (i) peptide mass fingerprinting and (ii) peptide sequencing.
(i) Peptide mass fingerprinting (PMF) is typically performed using matrix assisted laser
desorption/ionization (MALDI) for ionization of the peptides and a time-of-flight (TOF) mass
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analyzer to characterize peptides (Figure 3.5). Identification of proteins using PMF takes
advantage of the high mass accuracy of the method (Yates et al., 2009). Spots excised from
the 2-DE gel are digested with trypsin, generating a ‘fingerprint’ of tryptic peptides that can
serve as a signature for a protein. Protein identification is made by comparing the
experimentally obtained molecular weights of the peptides with theoretically calculated ones
from proteins in a database (or of those derived from theoretical translation of DNA sequence
in the database).
Figure 3.5 MALDI-TOF mass spectrometry. Sample is co-deposited with matrix on a stainless steel plate and advanced to the mass spectrometer by ionization with a laser. The TOF analyzer separates ions based on the time it takes them to travel the length of the flight tube. This figure was taken from Delahunty & Yates (2006).
(ii) Peptide sequencing is achieved by tandem mass spectrometry (MS/MS) using
electrospray ionization (ESI) and either a quadrupole or ion trap mass spectrometer (Figure
3.6). Like PMF, proteins separated on a 2-DE gel are excised and digested with trypsin prior to
analysis. Unlike MALDI, ESI is performed at atmospheric pressure and can be linked with liquid
chromatographic (LC) methods for the introduction of the sample into the mass spectrometer
(LC-MS/MS). The additional chromatographic separation helps to resolve co-eluting proteins
and increase the number of identifications that can be made for a protein mixture. The
peptide fragmentation data collected from MS/MS are specific for each peptide because they
yield the actual amino acid sequence of the peptide as well as its molecular weight. The
increased specificity makes MS/MS capable of identifying multiple proteins from a gel spot of
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protein mixtures. Amino acid sequences of the peptides are obtained by de novo
interpretation of the spectra. These sequences are then BLAST searched against the protein
database to identify the protein of origin.
Figure 3.6 Tandem mass spectrometry (MS/MS). (A) Electrospray ionization (ESI) ionizes the analytes out of a solution and is therefore readily coupled to liquid-based. This figure was taken from Lane (2005). (B) Tandem mass spectrometry with two mass analyzers separated by an ion activation device. A mixture of peptides is ionized by ESI process and then separated in the first segment by their mass to charge (m/z) ratios. Selected ions are then advanced to the ion activation device where they are fragmented. This figure was taken from Delahunty & Yates (2006).
3.1.4 Applications of 2-DE in bacterial proteomics
The use of proteomics, especially 2-DE, is of central importance to study a ‘proteome
map’ of a large proportion of the entire protein complements of the cell. In combination with
MS, and the plethora of bacterial whole-genome sequence data currently available, it is often
possible to identify almost every single protein spot on the 2-DE gel.
A better understanding of bacterial cellular physiology can be achieved by profiling the
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proteome of bacterial grown under certain conditions. Since protein expression is an
energetically costly process, only the specific proteins directly required for growth, survival or
pathogenicity are expressed under a particular physiological condition. Consequently,
cataloging all the proteins expressed under a specific set of conditions (including the
identification of postranslational modifications) can lead to identification of the components
responsible for maintaining certain cellular activities. A bacterium, such as E. coli, which has
approximately 4,300 genes, typically expresses 1,000–1,500 proteins under standard
laboratory growth conditions. This is ideally suited to 2-DE, in which it is possible to
simultaneously visualize and quantify a comparable number of protein spots on a single gel
(Kalia & Gupta, 2005). Using 2-DE expression profiling under various culture conditions, it is
often possible to identify sets of proteins involved in basic cellular metabolism versus those
expressed in response to various cellular stresses or external stimuli. The majority of ‘house-
keeping’ proteins functioning in central metabolic pathways are expressed at relatively
constant levels during the active growth stage however many proteins involved in stress
response or adaptation are significantly upregulated from a lower ‘basal’ level under certain
growth conditions. To investigate the putative physiological roles or biological functions of
proteins, various fractionation approaches may be used to establish their predominant
cellular localizations. In such approaches, whole cell proteomes may be compared with
various ‘sub-proteomes,’ which may include extracellular proteins, membrane or cell wall
associated proteins, DNA/RNA associated proteins, or cytoplasmic fractions.
3.1.5 Hypotheses
Although several groups have identified bacterial strains associated with GSL
degradation capacity, very little is known about bacterial proteins involved in the metabolism
of GSLs. In Chapter 2, putative bacterial GSL-degrading enzyme activity is shown to be likely
inducible by GSL. Therefore, it may be possible to identify these inducible proteins expressed
during GSL supplementation in bacterial cultures. The hypotheses of this chapter are as
follows:
GSL supplementation to bacterial cultures may produce different proteome maps on
2-DE gels when compared to those obtained from bacterial cultures without GSL
supplementation.
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Distinctively expressed or upregulated proteins found on 2-DE gels ontained from
bacterial cultures grown on media with sinigrin supplementation may be involved in
bacterial metabolism of GSL.
3.1.6 Objectives
The objective of this chapter is as follows:
To identify distinctively expressed or upregulated proteins in bacterial cultures grown
on media with sinigrin supplementation by comparatively analyzing 2-DE proteome
maps of bacterial cells isolated from cultures with- versus without- GSL
supplemetation and performing subsequent MS/MS analysis for protein identification.
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3.2 Materials and Methods
3.2.1 Sinigrin supplementation in media and bacterial cell collection
In the previous report, GSL-degrading enzyme activity L. agilis R16 was shown to be
inducible by sinigrin (Palop et al., 1995) and the results from Chapter 2 support this report.
The same result was obtained for E. coli O83:H1 NRG 857C. Due to time and resource
restriction, only two bacteria, L. agilis R16 (LA) and E. coli O83:H1 NRG 857C (ECO), were
studied in this chapter. The optimal GSL concentration to be used to induce bacterial GSL-
degrading enzyme was determined by incubating various concentrations of sinigrin in 1 mL
culture broths containg or E. coli O83:H1 NRG 857C cells for 8 h at 37°C under anaerobic
conditions. The GSL degradation and degradation production were assessed from each
substrate concentration. The sinigrin concentration that yielded the highest degradation of
sinigrin and highest AITC production was used for the next experiment.
An overnight culture (1 mL) of LA or ECO culture was sub-cultured into 40 mL modified
MRS broth (glucose omitted for LA) and NB broth (for ECO) containing 2 mM sinigrin in a 50
mL sterile falcon tube. The cultures were grown anaerobically using AnaeroGen sachets
(Oxoid, UK) in an AnaeroGen anaerobic-generating system (Oxoid, UK) for 8 h at 30°C for LA
and 37°C for ECO without shaking. For the control sample, 2 mM glucose was added instead
of sinigrin. After 8 h, the bacterial cultures were centrifuged in an Eppendorf 5415 D
centrifuge at 3,300g for 30 min at 4°C to pellet bacterial cells. The bacterial pellets were
washed twice with 30 mL PBS buffer and stored at - 80°C until analysis. The supernatants from
an overnight culture were subjected to HPLC analysis for the detection of sinigrin degradation,
and to GC-MS analysis for the detection of AITC/ANIT production as previously described in
Chapter 2.
3.2.2 Cell lysis and protein extraction
Two different protocols used for protein isolation were as follows.
(i) Extraction using R3 lysis reagent (Bio-Rad). Pelleted cells were suspended in 2 mL
of 2D lysis buffer [7 M urea, 2 M thiourea, 4% CHAPS, 2% IPG Buffer, 40 mM DTT], and 25 µL
protease inhibitor was added into a solution. Then bacterial cells were lysed using a one-shot
cell disruption system (Bugbuster, Constant system Ltd, UK) under 30k PSI (2000 bar). Cell
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lysates (2 mL) were aliquoted into a 2 mL eppendorf which was then centrifuged at 13.2 K
rpm at 4°C for 10 min. The clear supernatant 1 was carefully transferred into a 2 mL
Eppendorf tube. The remaining pellet was resuspended with 2 mL 2D lysis buffer by vigorous
vortexing for 2 min. The suspension was centrifuged at 16,100g at 4°C for 10 min. The
supernatant 2 was carefully transferred into a new 2 mL Eppendorf tube. Supernatants 1 and
2 (250 µL each) were mixed to make a total volume of 500 µL which was then concentrated
using Millipore Amicon Ultracentrifugal filters 0.5 mL 10K according to the company’s
instructions. The final volume of 100 µL concentrated supernatant was obtained and cleaned
using 2D clean-up kit (Bio-Rad) as per manual. Finally, the protein supernatant was adjusted
reach concentration of 200 µg/50 µL with 2D rehydration buffer (7 M urea, 2 M thiourea, 2%
CHAPS, 0.5/2% Pharmalyte or IPG Buffer, 0.002% bromophenol blue, 7 mg DTT per 2.5-ml
aliquot was added just prior to use) and stored at - 80°C until analysis.
(ii) Lysis by Enzymatic Treatment with Lysostaphin. After harvesting bacteria, cells
were washed twice with 5 mL of 0.1 M PBS buffer and once with 5 mL of digestion buffer (10
mM Tris-HCl, pH 7.6, 1 mM EDTA, 5 mM MgCl2). Cells were resuspended in 3 mL of digestion
buffer containing 10 µL of 100X protease inhibitor cocktail for bacterial cells (Melford, UK)
and 5U of lysostaphin (Sigma-Aldrich, UK). After incubation at 37°C for 30 min, the clear
supernatant was obtained by centrifugation at 8000g for 15 min at 4°C. The supernatant was
then treated with DNase (0.75 mg/mL) and RNase (0.5 mg/mL) by incubating for 15 min on ice
to remove nucleic acid contaminants. The supernatant was further treated with 20% v/v TCA
in ice for 30 min and the precipitate was collected by centrifugation at 16, 100g for 20 min at
4°C. The precipitated protein was washed with 200 µL of acetone to remove traces of TCA and
finally acetone was removed by speed vacuum treatment. Precipitated protein was re-
suspended in 2D rehydration buffer and stored at −80°C for later use.
3.2.3 Protein quantification
Since many of the reagents used in the preparation of 2-DE samples, including
detergents (SDS), reductants (DTT), chaotropes (thiourea, urea) and carrier ampholytes, are
incompatible with Bradford protein assay, a 2-DE Quant Kit (GE Healthcare, UK) was used to
determine the accurate quantity of protein in the samples. The procedure works by
quantitatively precipitating proteins while leaving interfering substances in the solution. The
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assay is based on the specific binding of copper ions to a protein. Precipitated proteins are re-
suspended in a solution containing copper, and unbound copper is determined with a
colorimetric agent. The color density inversely corresponds to the protein concentration.
Different amounts of bovine serum albumin (BSA, 2 mg/mL, provided in the kit) in a
range of 0.5–50 μg were added to 1.5 mL sterile Eppendorf tubes. Protein samples were
prepared in duplicate, and different volumes (1–50 μL) were used to ensure that protein
concentration fell within a useful range of the assay (0.5–50 μg). The precipitant (500 μL,
provided in the kit) was added to each tube and was thoroughly mixed by brief vortexing and
incubated at room temperature for 3 min. The co-precipitant (500 μL, provided in the kit) was
added to each tube and was mixed by inversion briefly and centrifuged at 9,000g for 5 min.
The supernatant was discarded, and the pellet was dissolved in a mixture of 100 μL copper
solution and 400 μL of distilled water. The color reagent (1 mL) was added to sample tubes
and incubated at room temperature for 15 min. The absorbance at 480 nm was measured
spectrophotometrically using distilled water as a reference. A calibration curve of BSA was
plotted (Figure 3.7), and the protein concentration can be determined from this.
Figure 3.7 BSA calibration curve. Various amounts (0.5–50 μg) of BSA from 2-D Quant Kit (GE Healthcare, UK) were plotted against absorbance at 480 nm.
y = -0.0159x + 1.3952 R² = 0.9795
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
0 10 20 30 40 50 60
Abso
rban
ce a
t 480
nm
BSA (µg)
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3.2.4 Two-dimensional polyacrylamide gel electrophoresis (2D-PAGE)
For the first-dimension electrophoresis, immobilized pH non-linear (NL) gradient (IPG)
Immobiline Drystrip gels (11 cm, pH 3-11 NL) (GE Healthcare, UK) were rehydrated in
Immobilline Drystrip dehydration tray (GE Healthcare, UK) for 17 h at room temperature.
These strips with the pH 3-11 NL gradient have an usual expansion from a middle range pH 5-
7 resulting in a sigmoidal pH gradient which means this range is less narrow separated than in
linear strips. Since most crude lysates from all species contain many polypeptides in this
middle pI range, a non-linear (NL) range should be used for a start. The following day, a total
of 250 µg of protein sample (in 50 μL) was applied onto each strip using a cup loader.
Isoelectro focusing (IEF) was carried out using IPGPhor III machine (GE Healthcare, UK) at 500
V (step and hold) for 6 h, 500-1000 V (gradient) for 1 h, then 1000-8000 V (gradient) for 5 h
and then 8000 V (gradient) for 5 h. The average run took approximately 52000 Vh in total. To
enhance the efficiency in protein transfer from the first to the second dimension, IPG strips
were incubated in reducing buffer (1.0% (w/v) DTT, 75 mM Tris-Hl pH 8.8, 6 M urea, 29.3%
(v/v) glycerol, 2% SDS, 0.002% bromophenol blue) for 15 min, followed by 15 min incubation
in alkylation buffer (2.5% (w/v) iodoacetamide, 75 mM Tris-Cl pH 8.8, 6 M urea, 29.3% (v/v)
glycerol, 2% SDS, 0.002% bromophenol blue). Strips were then overlaid on 4-12% pre-cast
Criterion XT Bis-Tris-SDS gels (13.3 x 8.7 cm (W x L), 1 mm thick) (Bio-Rad, UK) and sealed with
agarose solution (0.5% agarose, 1% bromophenol blue in a Laemmli SDS electrophoresis
buffer). Protein marker (7 µL), either Rainbow marker (GE healthcare, UK) (Figure 3.8A) or
Low Range unstained marker (Sigma-Aldrich) (Figure 3.8B), was loaded onto the marker well.
The second-dimension gel electrophoresis was carried out in 1X MES SDS running buffer (50
mM MES, 50 mM Tris-base, 3.47 mM SDS, 1.0 mM EDTA, pH 7.3) at 40 V for 10 min, and then
at 150 V until the dye front reached the bottom of the gel (~1 h). Gels were stained in ~ 25 mL
of InstantBlue Coomassie® stain (Expedeon, UK) untill the bands became visible. Gels were
washed with ultrapure water twice and kept in ultrapure water at 4°C till further analysis.
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Figure 3.8 Protein ladders used in 2-DE work. (A) Rainbow marker (GE healthcare, UK). (B) Low Range unstained marker (Sigma-Aldrich). 3.2.5 Image acquisition and analysis
Stained gels were scanned using the 2D gel CCD image analyzer Dyversity (Syngene,
UK) at a resolution of 100 microns for 1100 ms. The exposure time was adjusted to achieve a
value of ~55,000-63,000 pixel intensity as previously described (Brobey et al., 2006).
Subsequently the images were analyzed using Nonlinear Dynamics Progenesis v4 software
(Newcastle upon Tyne, UK). For the purpose of this experiment, each set of gel replicates
from either culture grown on media with or without sinigrin supplementation was combined
into average gels. The average gel represents reproducible spots present on both sets of the
replicate gels. The gel with the greatest number of spots was automatically selected as the
image for the reference gel, and unmatched spots from the other gels were added to this
image to give a comprehensive reference gel for matching spots on the different gels. Gel
images were aligned by automated calculation of six manually assigned alignment landmark
vectors. Scanned gels were analyzed by intra-gel (difference in-gel) and inter-gel (biological
variance) analysis. The automatically detected spots by the software were visually inspected
as well. Any artefacts were removed by manual spot filtering and editing to correct for spots
that did not split properly or were not automatically detected by the software. The spot
intensity levels were normalised by expressing the intensity of each protein spot in a gel as a
proportion of the total protein intensity detected for the entire gel (relative volume, %
volume) to study quantitative changes. A 2-fold increase threshold (spot volume ratio change
and ANOVA p < 0.05 and a false discovery rate of q < 0.05) was chosen as a criterion in the
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identification of differentially expressed protein candidates. Since the primary objective was
to search for inducible proteins or upregulated proteins with more likelihood to be putative
myrosinases, any spots with changes in downregulated expression upon sinigrin
supplementation were omitted from further analysis.
Each spot that met this criterion was visually verified to confirm whether it was
correctly detected, and the matching of the spots between the replicate sets was accurate.
Protein bands and spots were excised manually from the gels and subjected to in-gel tryptic
digestion.
3.2.6 Estimation of pI and molecular weight (Mr) of the proteins
By plotting the pH of an IPG strip as a function of its length, the pI of a protein can be
determined from its focused position on that strip (Figure 3.9A). This estimation method has
been routinely used in literature without the need to use IEF pH 3-11 marker (Furuhashi et al.,
2010) (Figure 3.9B). Likewise, by plotting the molecular weight (Mr) of proteins from Low
Range unstained marker (Sigma-Aldrich) as a function of migration distance, the Mr of a
protein can be determined from the distance it migrated on the gel (Figure 3.9C).
Figure 3.9 Calibration curves for pI and Mw determination. (A) The graph of pH 3-11 NL range versus the % length of IPG strip. (B) Representative 2-DE gel with pI values (3–11 NL) indication above the gel This figure was taken from Furuhashi et al. (2010). (C) The graph of Mr of proteins from Low Range unstained marker (Sigma-Aldrich) versus distance of migration.
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3.2.7 In-gel tryptic digestion
For mass spectrometric identification, protein extracts were digested with sequencing
grade trypsin as described by (Bouwman et al., 2004). The reagents used and their
compositions are shown in Table 3.1.
Table 3.1 Reagents used in in-gel tryptic digestion and their compositions
Reagents Compositions
100 mM ammonium bicarbonate (BDH, UK)
395.3 mg ammonium bicarbonate, up to 50 mL of HPLC water
100 mM ammonium bicarbonate in 50% acetonitrile
395.3 mg ammonium bicarbonate, 25 mL of HPLC acetonitrile, up to 50 mL of HPLC water
10 mM DTT (Melford, UK) 7.71 mg dithiothreitol (DTT), up to 5 mL of 100 mM ammonium bicarbonate *MAKE FRESH*
50 mM IAA (Sigma-Aldrich, UK) 56 mg iodoacetamide (IAA) reconstituted in 6.06 mL of ammonium bicarbonate *MAKE FRESH*
20 mM ammonium bicarbonate in 50% acetonitrile
10 mL of 100mM ammonium bicarbonate, 15 mL of HPLC water, 25 mL of HPLC acetonitrile
40 mM ammonium bicarbonate in 10% acetonitrile
20 mL of 100mM ammonium bicarbonate, 5mL of HPLC acetonitrile, 25mL of HPLC water
50 mM acetic acid (VWR) 144 μL of acetic acid, up to 50 mL of HPLC water
Trypsin Gold (Promega) solution
100 μL of 50 mM acetic acid, up to 5 mL of 40 mM ammonium bicarbonate in 10% acetonitrile aliquot into 500 μL Eppendorf Protein Lobind Tubes and store at -80°C.
50% acetonitrile/5% TFA 25 mL of HPLC acetonitrile, 2.5 mL Trifluoroacetic acid (TFA) (Sigma-Aldrich, UK), up to 50 mL HPLC water
The band was excised from the gel using a cutting blade and forceps (rinsed with 70%
ethanol before and after each band) into 1 x 1 mm pieces and place in a 1.5 mL Lobind
Eppendorf tube. All washing steps were carried out at a room temperature on a shaker unless
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otherwise stated. The gel pieces were rinsed with 300 μL of HPLC water for 15 min and
washed with 300 μL of HPLC acetonitrile for 15 min, and the supernatant discarded. Gel pieces
were washed with 300 μL of 100 mM ammonium bicarbonate for 15 min, and the supernatant
discarded. The gel pieces were washed with 300 μL of 100 mM ammonium bicarbonate in 50%
acetonitrile for 15 min, and the supernatant was discarded. The gel pieces were washed with
100 μL of HPLC acetonitrile for 5 min and the supernatant was discarded. Gel pieces were
dried in a speed vacuum Heto VR-1 (Heto-Holten, Denmark) for 5 min before 50 μL of 10 mM
DTT was added and incubated for 1 h at 60 °C. The supernatant was discarded before gel
pieces were added with 50 μL of 50 mM IAA and incubated for 30 min in the dark. The
supernatant was discarded before gel pieces were washed with 300 μL of 100 mM ammonium
bicarbonate for 15 min. The supernatant was discarded before gel pieces were washed with
300 μL of 20 mM ammonium bicarbonate in 50% acetonitrile for 15 min. The supernatant was
discarded before gel pieces were washed with 100 μL of HPLC acetonitrile for 5 min. The
supernatant was discarded, and gel pieces were dried in a speed vacuum for 5 min. The gel
pieces were added with 20 μL of 1 μg/μL trypsin solution and incubated for 1 h. After that, 40
mM ammonium bicarbonate in 10% acetonitrile was added to overlay the gel pieces and
incubated overnight at 37°C. The following day, the reaction tubes were added with 150 μL of
HPLC water, and incubated at 37°C for 10 min. The supernatants were transferred to a 1.5 mL
Lobind Eppendorf tube. The gel pieces were extracted twice with 50 μL of 50% acetonitrile/5%
TFA for 60 min each time. The extracts were pooled and dried in a speed vacuum. The dried
extracts were dissolved in 20 μL of 0.5% formic acid immediately before LC-MS/MS analysis.
3.2.8 LC-MS/MS Analysis
The samples were analyzed on an Applied Biosystems QTrap MS coupled to an Agilent
1100 LC stack. The Agilent stack consisted of a binary pump, capillary pump, well plate auto-
sampler and a column oven with integrated 6-port valve. The samples were loaded onto a
trap column (Agilent Zorbax SB 5 µm x 0.3 mm x 35 mm) using the binary pump; the trap
column was washed and then switched into the capillary flow; peptides were separated on a
capillary column (Agilent SB 5 μm 0.5 mm x 150 mm column). The LC was interfaced to the MS
with a turbo ion spray source. The loading/washing solvent was milli-Q H2O containing 0.2%
COOH, 0.02% TFA at a flow rate 150 μL/min and the resolving solvent was a linear gradient
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system of 0% B to 40% B over 60 min at a flow rate of 10 μL/min [(A) 94.9% H2O, 5% CH3CN,
0.1% COOH; (B) 94.9% CH3CN, 5% H2O, 0.1% COOH]. The column oven temperature was set to
40°C, and the valve was switched to direct the flow from the trap into the resolving column
after a 5 min wash. The MS parameters were normally set to Curtain Gas 10 psi, GS1 20 psi,
GS2 20 psi, interface heater on, temperature at 150°C, DP 65. The acquisition method
consisted of an enhanced mass spectrum (EMS) survey scan (350-1200m/z) followed by an
enhanced resolution (ER) scan and then enhanced product ion scans (100-1500 m/z) of
selected ions. The information dependant acquisition (IDA) was set for the top 4 most intense
peaks after dynamic background subtraction of the survey scan. The criteria include; m/z >
325 < 1200 with a charge state of 2-3, the ER scan was used to determine charge state, rolling
collision energy was used, +1 precursors were excluded for the dependant scans. Former
target ions were excluded after two occurrences for 2 min.
3.2.9 Database searching and protein identification
Mass spectrometric data was analyzed by the database search engine ProteinPilot
using the Paragon algorithm (4.0.0.0, 459) (Applied Biosystems). The sample parameters were
set to: trypsin digestion, cysteine alkylation set to iodoacetamide, urea denaturation and
acetylation emphasis. The C-terminal cleavage at lysine (Lys) and arginine (Arg) was selected
for trypsin specificity. “Biological modification” was set for processing parameters, and a
thorough ID search effort was selected. The peptide and fragment mass tolerances were < 10
ppm. During the search by Protein Pilot, an automatic mass recalibration of the data sets
based on highly confident peptide spectra was carried out. A first search iteration was
specifically performed to select high confidence peptide identifications. These were then used
to recalibrate both the MS and MS/MS data, which is automatically re-searched. Tandem MS
data were searched against Lactobacillus and E. coli O83:H1 NRG 857C database from UniProt
release 2012_01. All reported proteins were identified with at least two peptides having a
confidence (Conf.) interval of ≥ 95% (p < 0.05) as determined by ProteinPilot™ Unused scores
(≥ 1.3) with the corresponding false positive discovery rate below 1%. The winner protein
selected to represent the spot would have the highest unused ProScore with the theoretical
pI and Mr values close to the calculated ones (based on the spot location) and this protein was
found in all triplicates.
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3.3 Results
3.3.1 Optimum GSL concentration to induce bacterial GSL-degrading activity In Chapter 2, the putative bacterial GSL-degrading activity from all three bacteria
tested is likely to be inducible by GSL addition. It was also found that ITC and NIT production
peaked at 8 h following addition of most GSL substrates in cultures of L. agilis R16 and E. coli
O83:H1 NRG 857C. Therefore, bacterial cells were pelleted at 8 h so as to avoid possible
degradation or reduced expression of putative bacterial GSL-degrading activity, if any, rather
than collecting them later. In this chapter, the aim was to identify inducible proteins in
bacterial cells grown on GSL supplementation using the 2-DE approach as these identified
proteins may potentially be involved in the metabolism of GSLs in human gut bacteria.
Firstly, the optimal concentration of sinigrin to be supplemented during bacterial
fermentation to promote GSL-degrading activity was determined by measuring the
degradation percentage of several sinigrin concentrations tested and accordingly the AITC
production over 8 h in two bacteria, L. agilis R16 and E. coli O83:H1 NRG 857C. The highest
degradation of sinigrin and AITC formation in each bacterium were resulted from 2 mM
sinigrin (Figure 3.10). Therefore, 2 mM sinigrin was supplemented in bacterial cultures to
maximize myrosinase–like activity in both bacteria for 2-DE gel experiments.
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Figure 3.10 Sinigrin degradation and AITC production from various sinigrin concentrations at 8 h in bacterial fermentation. (A) Sinigrin degradation (%) of several sinigrin concentrations in L. agilis R16 anaerobic incubatiosn at 30˚C for 8 h. (B) AITC production (%) over digested sinigrin in L. agilis R16. (C) Sinigrin degradation (%) of several sinigrin concentrations in E. coli O83:H1 NRG 857C anaerobic incubatiosn at 37˚C for 8 h. (D) AITC production (%) over digested sinigrin by E. coli O83:H1 NRG 857C. Values are means ± SD, n = 3. Degradation (%) was calculated from the number of moles of sinigrin degraded over the number of moles of initial sinigrin in percentage. AITC production (%) was calculated from the number of moles of AITC produced over the number of moles of degraded sinigrin in percentage.
Comparative analysis of growth curves between cultures of both L. agilis R16 and E.
coli O83:H1 NRG 857C with and without 2 mM sinigrin supplementation over 8 h showed no
significant difference of growth kinetics in the same bacterium (Figure 3.11). Both bacteria
reached a stationary phase approximately the same time at 6 h. This result suggests that
sinigrin supplementation did not alter bacterial growths when compared with the control
cultures without its supplementation. The similarity in growth kinetics of the two cultures
(with and without sinigrin supplementation) of same bacterium would make the comparative
analysis of protein patterns from these bacteria justified.
At different growth phases, different proteins are produced and predominate e.g.
ribosomal proteins are predominant at log phase where there is high activity of protein
synthesis to support bacterial growth while proteolytic proteins are predominant at
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stationary phase where proteins are degraded and recycled. This would have posed a
problem in comparative analysis in interpreting protein expression patterns if the growth
rates of bacteria are far different.
Figure 3.11 Growth kinetics of bacteria with and without sinigrin supplementation over 8 h. Cultures of L. agilis R16 (LA) and E. coli O83:H1 NRG 857C (ECO) were grown on media either with sinigrin supplementation (S) or without it (N) for 8 h of anaerobic incubation at 30°C for LA and 37°C for ECO. The OD600nm values were plotted in log scale. Values are means, n = 3.
3.3.2 Optimization of protein sample preparation for 2-DE
Employing proteomics technologies to search for putative bacterial GSL-degrading
enzymes and possible key bacterial proteins involved in the metabolism of GSLs was set as the
ultimate goal. This could be achieved by establishing 2-DE as a tool to study protein
expression patterns of bacterial cells grown on media with and without sinigrin
supplementation. The key step to obtain a high quality 2-DE gel is to optimize the conditions
for protein extraction and protein content to be loaded on the 2-DE gel. There are several
ways for bacterial protein isolation using different lysis reagents or lysis methods. However,
the preliminary results suggest that cell disruption by a cell disruption machine led to a
greater release of protein content from a Gram-positive bacterium L. agilis R16 in comparison
with a method of sonication (Abdulhadi Albaser, PhD thesis). Therefore, a cell disruption
machine was used throughout for cell lysis.
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Initially, proteins from cells grown on media without sinigrin supplementation were
prepared by two different cell lysis procedures: (i) using R3 extraction reagent alone and (ii)
enzymatic lysostaphin treatment. Lysostaphin, as an endopeptidase, cleaves the pentaglycine
cross-bridges of the staphylococcal cell wall rapidly lysing the bacteria (Kusuma & Kokai-Kun,
2005; Kumar et al., 2008). This enzyme has been used to lyse cell walls of Gram-positive
bacteria and isolate membrane proteins from Gram-positive Staphylococcus aureus bacterium (Nandakumar, et al., 2005).
The results showed that method (i) yielded 1.04 µg/µL of isolated protein while
method (ii) yielded 7.35 µg/µL (which is approximately seven-fold higher than method (i)).
There was a similarity in protein distribution between these two samples, with the majority of
the proteins ranging from pI 4 to pI 6. Method (i) produced well-separated spots (Figure
3.12A) while method (ii) gave suboptimal resolution at the acidic end (pI < 5) (Figure 3.12B).
After careful automated and manual editing to correct for artifacts using Progenesis v4
software (Section 3.2.5), 210 spots were detected from method (i) (Figure 3.12A) and 523
spots from method (ii) (Figure 3.12B). Method (ii) yielded more than a two-fold increase of
the number of detectable spots. This indicates that addition of lysostaphin (5U) markedly
improved efficiency in protein isolation from Gram-positive bacterium L. agilis R16. Therefore,
enzymatic treatment with lysostaphin was used throughout to release as many proteins as
possible. It was also found that 250 µg was the optimal protein content for loading on the 2-
DE gel (Figure 3.12B).
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Figure 3.12 Comparison of protein patterns from two cell lysis methods. L. agilis R16 cells were grown in MRS broths without sinigrin supplementation and the cell-free extracts were analyzed on 2-DE gels. (A) Proteins prepared by ProteoPrep membrane extraction kit (Sigma-Aldrich) with 80 µg of protein loaded on the gel. (B) Proteins prepared by lysostaphin treatment with 250 µg of protein loaded on the gel. Approximate pI value (3–11 NL) is indicated above gel photo. Protein ladders (7 µL), Rainbow marker (GE healthcare, UK) was loaded in (A), Low Range unstained marker (Sigma-Aldrich) was loaded in (B). Only one replicate from each method was carried out.
In addition, three biological replicates of 2-DE gels from each set of L. agilis R16 grown
on media with and without sinigrin supplementation were compared to determine the
reproducibility of 2-DE technique. It was shown that 2-DE gels were fairly reproducible with a
similar number of protein spots, and expression patterns (Figure 3.13).
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Figure 3.13 Reproducibility of 2-DE gels from L. agilis R16. (A) Triplicates of proteins from cells grown on media without sinigrin. (B) Triplicates of proteins from cells grown on media with sinigrin.
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3.3.3 Comparative analysis of 2-DE maps of proteins isolated from cells grown on media
with and without sinigrin supplementation
To identify inducible proteins upon sinigrin supplementation in the cultures of L.
agilis R16 and E. coli O83:H1 NRG 857C, bacteria were grown on media with and without 2
mM sinigrin for 8 h and 2-DE maps obtained from these cultures were used for comparative
analysis. The 2-DE gels of each set of cultures (with or without sinigrin supplementation)
from each bacterium were produced in triplicates for L. agilis R16 and duplicates for E. coli
O83:H1 NRG 857C. These gels were subjected to gel analysis using Progenesis v4 software
(Section 3.2.5) for spot counting and identification of spots with changes in abundance.
Information about bacterial growth, spot numbers on 2D gels of each set of cultures (with or
without sinigrin supplementation) from each bacterium are shown in Table 3.2.
Table 3.2 Experimental results of each set of cultures (with or without sinigrin
supplementation) from each bacterium
Bacteriaa ORF no.b Spot no.c OD600nm Sinigrin degraded (μM)d
AITC + ANIT production
(μM)e
Percentage product
(%)
LA (S) 3,088
523 ± 19 0.758 ± 0.010 1000 654 ± 18 65
LA (N) 561 ± 25 0.714 ± 0.012 ND ND ND
ECO (S) 4,575
363 ± 27 0.531 ± 0.009 1000 611 ± 26 61
ECO (N) 354 ± 15 0.529 ± 0.011 ND ND ND aLA, L. agilis R16; ECO, E. coli O83:H1 NRG 857C; S, supplemented with sinigrin; N, without sinigrin. Bacterial fermentations were carried out at 30°C for LA and 37°C for ECO under anaerobic conditions for 8 h. bNumber of open reading frame (ORF) predicted in L. plantarum strain JDM1 and in E. coli O83:H1 NRG 857C by UniProt. cNumber of protein spots on 2D gels counted by Progenesis v4 software. d Determined by HPLC nalysis. e Determined by GC-MS nalysis. ND, Not detected; AITC, Allyl isothiocyanate; ANIT, Allyl nitrile. Values are means ± SD, n = 3 (for LA) and n = 2 (for ECO).
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Sinigrin was not completely metabolized to AITC and NIT products as shown by the
percentage product of 65% and 61% in L. agilis R16 and E. coli O83:H1 NRG 857C,
respectively (Table 3.2). This suggests that some metabolite products may be unaccounted
for in these bacteria, and they were not detected by current GC-MS analysis. Another reason
is possibly due to the instability of AITC in the culture broths (Chapter 2, section 2.3.4), and
thus it declined over time during bacterial fermentations. Higher numbers of protein spots
were observed in cells grown on media with sinigrin supplementation from both bacteria
(Table 3.2). However, more spots were detected in 2D maps of L. agilis R16. The number of
spots account for a sixth, and a tenth of open reading frames (ORFs) predicted for gene
products in L. agilis R16 and E. coli O83:H1 NRG 857C, respectively (Table 3.2). Since the
genome and proteome database of L. agilis R16 is not available, this analysis was carried out
using ORF data of the relative bacterium L. plantarum strain JDM1.
Representatives of 2-DE gels of each set of cultures from each bacterium were
shown in Figure 3.14. A majority of spots were found in a more acidic pI range of 4-5.5 in L.
agilis R16 (Figure 3.14A and 3.14B) which is a lactic acid bacterium (LAB) and a pI range of
4.5-6 in E. coli O83:H1 NRG 857C (Figure 3.14C and 3.14D). In E. coli O83:H1 NRG 857C, the
spots between 29-66 kDa and pI of 4.5-5.5 are not well-separated possibly due to non-
protein impurities at the acidic end (Figure 3.14C and 3.14D).
There are 32 and 35 spots in L. agilis R16 and E. coli O83:H1 NRG 857C with at least
two-fold increase in abundance in response to sinigrin were detected (Figure 3.14B and
3.14D, respectively). Any spots with changes in downregulated expression upon sinigrin
supplementation were omitted from further analysis (although these proteins may involve in
GSL metabolism) since the primary objective was to search for inducible proteins or
upregulated proteins which are more likely to be putative bacterial GSL-degrading enzymes.
These spots with at least two-fold increased intensity were excised from the gels
and enzymatically digested with trypsin (Section 3.2.7) prior to LC-MS/MS analysis for
protein identification. Unfortunately, some spots were lost during in-gel trypsin digestion
procedure involving multiple steps, and some protein samples were contaminated with
human skin proteins and/or dust that produced poor results in protein identification that did
not meet the criteria for protein identification used in ProteinPilot™ Software 4.0. These
unidentified spots were indicated in blue circles in Figure 3.14.
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A strict cut-off for protein identification was applied to minimize false positive
results. Unused ProtScore ≥ 1.3, which corresponds to a confidence (Conf.) limit of 95%, and
at least two peptides with 95% confidence were considered for protein identification
(Section 3.2.9). Therefore, only the protein spots with the highest unused ProScore with the
theoretical pI and Mr values close to the calculated ones and good % coverage were
presented in the next section (red circles in Figure 3.14).
194
Figure 3.14 Comparative analysis of representative 2-DE maps of bacterial proteins. The 2-DE proteome maps obtained from cells of (A) L. agilis R16 (LA) grown without sinigrin supplementation for 8 h at 30˚C. (B) L. agilis R16 culture with sinigrin. (C) E. coli O83:H1 NRG 857C (ECO) culture without sinigrin supplementation for 8 h at 37˚C. (D) E. coli O83:H1 NRG 857C culture with sinigrin. Both red and purple circles indicate protein spots with at least two-fold increase in abundance. Red circles with numbers indicate successfully identified proteins while purple circles indicate unidentified spots with low Conf. value (Progenesis v4 software). These gels are representatives of three replicates from LA and duplicates from ECO.
195
The increase in protein abundance was determined by using Progenesis v4
software (Section 3.2.5). The montage 3D comparison of the spot at the same
position between two 2-DE gels (with and without sinigrin supplementation) was
generated as an example (Figure 3.15).
Figure 3.15 Representative comparison of 3D montage of expression levels of protein spot. Intensity levels of spot no. 4 (oxidoreductase) from 2-DE maps of (A) L. agilis R16 culture grown on media without sinigrin supplementation and (B) L. agilis R16 culture grown on media with sinigrin supplementation were compared using Progenesis v4 software. A three-fold increase in spot intensity in (B) was shown. 3.3.4 LC-MS/MS analysis and protein identification
All upregulated proteins spots were subjected to in-gel digestion and
analyzed by LC-MS/MS. Both representative precursor MS and peptide sequence of
D-lactate dehydrogenase from L. agilis R16 (Figure 3.14B, spot no. 10) are shown in
Figure 3.16. Each peptide mass fingerprint obtained was used to search for the
positive protein using UniProt database (Consortium, 2012) via ProteinPilot™
software v4.0. The unused score (a confidence percentage) was calculated, and it
reflects the probability of a hit being a “false positive”. There is a false positive
identification probability of about 5% at the 95% confidence level. There are 28
upregulated proteins (12 from L. agilis R16 and 16 from E. coli O83:H1 NRG 857C)
that were successfully identified (Table 3.3).
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Figure 3.16 Representative MS and MS/MS spectra. The identified protein D-lactate dehydrogenase of L. agilis R16 (Figure 3.14B, spot no. 10) produced (A) MS spectrum of matched peptide sequence ‘AWHSSSETTAK’ with corresponding precursor MS region. The sequences were determined with a 99 score confidence (Conf.). (B) MS/MS spectrum of the matched peptide. Both spectra were generated by ProteinPilot software v4.0.
Since the proteome and genome database of L. agilis R16 is unavailable, the
identification of upregulated proteins in this bacterium relied on the homology to
proteins belonging to other Lactobacillus species including L. plantarum strain ATCC
BAA-793/strain JDM1. Thus, the observed Mr/pI of spots was different from their
theoretical Mr/pI (Table 3.3). This also re-occurred in E. coli O83:H1 NRG 857C that
has its genome/proteome available in the database. This might result from an
unusual posttranslational modification. In addition, when the proteins are focused
too long, cysteins become oxidised and the pI of the proteins change. Some proteins
become unstable at their isoelectric point. The modified proteins have a different pI
and start to migrate again with the horizontal streaks radiating from the spots (Lopez,
2007). This may also explain the differences in theoretical and experimental Mr and
pI values.
197 Table 3.3 Protein identification of upregulated spots (≥ 2 fold increase in spot volume ratio and ANOVA p ≤ 0.05 with ≥ 2 matched peptides) of L. agilis R16 (LA) and E. coli O83:H1 NRG 857C (ECO) anaerobically grown on media with 2 mM sinigrin supplementation for 8 h at 30˚C for LA and at 37˚C for ECO
Spot no.
Uniprot Accession
no. Protein description
Theoretical Mr
(kDa)/pI
Calculated Mr
(kDa)/pI
Unused ProtScorea
% Coverageb
Peptide matched
Relative spot
volume ratioc
L. plantarum (strain ATCC BAA-793/strain JDM1) Purine metabolism
1 C6VN56 Deoxyguanosine kinase 24.3/4.76 20.3/4.51 7.95 37.2 5 2.2 Proteolysis
2 C6VM88 ATP-dependent Clp protease proteolytic subunit 21.5/4.87 20.8/4.63 17.62 58.7 7 2.9 Oxidoreduction
4 C6VJP1 Oxidoreductase 20.4/5.02 17.6/5.05 16.92 68.2 9 3.3 6 C6VM58 Oxidoreductase 31.7/5.16 26.1/4.63 12.18 76.1 13 2.2 8 C6VNQ6 Oxidoreductase 35.9/5.19 35.8/5.43 11.32 72.7 10 2.3
Hydrolysis 5 C2FJX3 Haloacid dehalogenase (HAD) superfamily hydrolase 25.7/4.9 25.5/4.95 5.9 56.7 6 2.3
Carbohydrate metabolism 3 C6VMV8 Phosphoglycolate phosphatase 23.5/4.94 18.6/4.83 4.82 38.9 3 2.4 7 C6VNI4 Ribokinase 32.2/4.82 30/4.74 9.89 43.4 5 2.1 9 O32755 Glyceraldehyde-3-phosphate dehydrogenase 36.6/5.62 36.2/5.49 9.66 43.8 4 2.5
10 C0LJH4 D-lactate dehydrogenase 37.2/4.88 38/4.75 8.31 43.4 4 2.1 11 Q88V41 Acetate kinase 43.5/5.96 48/5.85 9.19 56.9 9 2.0
Transport 12 Q88ZZ2 Putative ABC transporter ATP-binding protein lp_0149 62.4/5.05 66/5.05 11.56 47.3 6 2.2
a Unused ProtScore is calculated using only peptides from th spectra that have not already been used to justify more confident proteins. It is a true indicator of protein confidence. b % coverage represents % of the no. of amino acids matching to ≥ 1 identified peptide divided by the total no. of amino acids in the protein sequence. C Increase in protein expression of the spots from the cultures with sinigrin versus control cultures without sinigrin as analyzed by ProteinPilot software v 4.0.
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Spot no.
Uniprot Accession
no. Protein description
Theoretical Mr
(kDa)/pI
Calculated Mr
(kDa)/pI
Unused ProtScorea
% Coverageb
Peptide matched
Relative spot
volume ratioc
E. coli O83:H1 NRG 857C
Sugar Transport 13 E4P223 Glucose-specific PTS system component 18.3/4.73 17.3/4.72 5.58 18.3 3 3.1
23 E4P2U5 Fused putative sugar transporter subunits of ABC superfamily: ATP-binding components 55.9/5.61 51.2/5.71 10.15 25.7 5 2.1
25 E4P9F3 N-acetyl glucosamine specific PTS system components IIABC 68.3/5.78 66.1/5.74 7.81 32.1 4 2.2
Carbohydrate metabolism 14 E4P7M3 Adenylate kinase 23.5/5.75 25.6/5.78 15.31 60.8 11 2.2 17 E4P1Z9 Glucokinase 34.7/5.95 37.2/5.85 4.69 15.9 2 2.1 19 E4PDZ4 Acetate kinase 43.3/5.85 43.3/5.66 20.23 50 8 2.5 20 E4PD26 Glucose-1-phosphatase/inositol phosphatase 45.7/5.60 46.4/5.60 5.53 18.9 3 2.8 22 E4P9L3 Glucose-6-phosphate dehydrogenase 55.7/5.56 51.5/5.68 10.98 45.3 5 2.4
Hydrolysis 15 E4PCB5 Putative hydrolase 29.28/5.57 29.0/5.81 19.15 58.3 12 2.2
Oxidoreduction 16 E4PD28 Flavoprotein WrbA 20.8/5.59 20.5/5.72 34.71 85.4 26 2.3
21 E4P7U4 Uncharacterized protein (Putative Oxidoreductase) 45.9/5.63 44.2/5.65 26.79 66.2 15 2.3
26 E4P8L1 Alkyl hydroperoxide reductase subunit C 20.8/5.03 16.7/4.87 20.38 59.6 12 2.5
27 E4P713 Superoxide dismutase 21.3/5.58 22.0/5.68 22.47 74.6 17 2 Proteolysis 28 E4P7I7 ATP-dependent Clp protease proteolytic subunit 23.2/5.52 23.8/5.70 26.08 50.7 10 2.4
Others 18 E4P96X Putative uncharacterized protein 39.6/6.0 41.3/5.77 11.92 48.5 6 2.3 24 E4PAW9 Uncharacterized protein 58/5.72 53.6/5.83 6.98 52.4 5 2.2
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A majority of upregulated proteins in L. agilis R16 belong to carbohydrate metabolism
and oxidoreduction system while the minority belong to purine metabolism, hydrolysis, and
proteolysis (Figure 3.17). Similarly, most upregulated proteins in E. coli O83:H1 NRG 857C were
found in carbohydrate metabolism, oxidoreduction system and sugar transport while the rest
found in hydrolysis, proteolysis and others (Figure 3.17).
Figure 3.17 Functional grouping of 28 upregulated proteins identified on 2-DE gels of L. agilis R16 (LA) and E. coli O83:H1 NRG 857C (ECO)
3.57%
7.14%
25%
7.14%
35.71%
14.29%
7.14%
Carbohydrate metabolism
Oxidoreduction
Sugar transport
Proteolysis
Hydrolysis
Others
Purine metabolism LA ECO
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3.4 Discussion
In this chapter, the usage of 2-DE combined with LC-MS/MS led to identification of
proteins involved in the transport system, proteolysis, oxidoreduction and carbohydrate
metabolism which potentially are important in GSL metabolism in L. agilis R16 and E. coli
O83:H1 NRG 857C. Since 2-DE analysis showed no identification of β-(thio)glucosidases (as
putative myrosinases) on any gels of either bacterium, it is speculated that bacterial GSL-
degrading enzymes may not have amino acid sequences similar to those found in aphid or plant
counterparts or they were not detected on our gels.
Due to the drawback of 2-DE, only the most abundant proteins in complex mixtures are
visualized. Additionally, a number of specific classes of proteins are relatively incompatible with
the isoelectric focusing step in 2-DE, including large, hydrophobic membrane proteins whose
limited solubility leads to protein precipitation and aggregation as well as very acidic or basic
proteins. If this is a case for bacterial GSL-degrading enzymes as a membrane protein that
precipitated or aggregated, it would not appear as a well-defined spot on 2-DE gels and thus it
was overlooked for further analysis.
It is also possible that bacterial GSL-degrading enzymes are low in abundance, yet
exhibit high degading activity towards sinigrin. Low abundance proteins, which often are crucial
to understand some biological changes and do the most important regulatory functions in a cell,
may be present in only a few copies per cell. If this is the case, then one may not be able to
detect a protein spot corresponding to bacterial GSL-degrading enzymes on 2-DE gels. There
are currently three major approaches to overcome the limitation when detecting low copy
number proteins in the presence of highly abundant “housekeeping” proteins.
(i) Ultrazoom gels, i.e. IPG strips which cover a series of narrow, overlapping ranges of pI
(e.g. IPG 4–5, 4.5–5.5, 5–6) for higher resolution and improved detection of low copy number
proteins. Furthermore, computer-aided image analysis and protein identification by MS are
simplified due to the smaller number of co-migrating protein species and the more reliable
database search results (Westbrook et al., 2001). Ultrazoom gels allow the detection of proteins
down to 300 copies due to their higher sample loading capacity (Hoving et al., 2000).
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(ii) Ultrasensitive protein stains such as silver staining which improves protein detection
up to five-fold as opposed to Coomassie brilliant blue R-250 that detects approximately 0.1 µg
of protein (Hoving et al., 2000).
(iii) Pre-fractionation steps to reduce the complexity of the sample and enrich low copy
number proteins.
Bacterial myrosinase was first successfully purified years ago (Tani et al., 1974). It was
active in-vitro, but its amino sequence was not identified due to lack of technology back in the
day. Since then, most bacterial myrosinases reported in literature were only active in intact
cells, but inactive in-vitro (Elfoul et al., 2001; Palop et al., 1995; Rabot et al., 1995). The finding
that bacterial myrosinase activity was mostly found in vivo renders purification and
identification of bacterial myrosinase more difficult.
Interestingly, myrosinase activity in vitro was detected in cell-free extracts of a Gram-
negative bacterium Citrobacter isolated from soil using enrichment culture containing only GSL
as an only source of carbon in M9 medium (Abdulhadi Albaser, PhD thesis). Although its cell-
free extracts exhibited myrosinase activity as tested positive using GOD-PERID assay, ITC/NIT
products were not detected from GSL degradation in resting cell experiments and bacterial
fermentation experiments. These findings were different from the results obtained from the
two bacteria (tested in this chapter) which did not exhibit myrosinase activity in vitro, but
produced ITC/NIT from GSL degradation in vivo (Chapter 2). All the results thus far suggest that
bacteria may have different mechanisms/enzymes to degrade GSLs and produce corresponding
products. The bacterial GSL-degrading enzyme system may be more complicated than
previously thought.
In addition to myrosinase, other proteins may play a role in the metabolism of GSL in
human gut bacteria. Thus, it is important to identify the proteins that are distinctively
expressed or upregulated upon GSL supplementation in bacterial cultures which may suggest
their involvement in GSL metabolism. The results showed that sinigrin supplementation
resulted in upregulated expression of several proteins in contrast to the control cultures
(without sinigrin supplementation) in both bacteria. Those putative uncharacterized proteins
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and putative hydrolase found in E. coli O83:H1 NRG 857C from 2-DE analysis may also be
important and involved in GSL metabolism as well as other proteins. It is perhaps best to keep
an open mind as very little is known about the GSL metabolism in human gut bacteria.
L. agilis R16 showed increased abundance in deoxyguanosine kinase. This enzyme
belongs to the family of transferase or kinases that specifically transfer phosphorus-containing
groups to an alcohol group as acceptor. This enzyme participates in metabolism of purines that
are respective building-blocks of DNA and RNA (Gower et al., 1979). The increased expression
of deoxyguanosine kinase may be associated with increased turnover of mRNA transcripts of
genes upregulated by sinigrin supplementation.
ATP-dependent Clp protease proteolytic subunit also had increased expression upon
sinigrin supplementation in both bacteria. This enzyme catalyzes the hydrolysis of proteins into
small peptides in the presence of ATP and Mg2+ ions (Gottesman et al., 1998). The increased
expression of this enzyme may be due to the high turnover of bacterial GSL-degrading enzyme
or its instability. L. agilis R16 was thought to have a very unstable myrosinase (Palop et al.,
1995). The increased abundance in ATP-dependent Clp protease proteolytic subunit may
indicate the presence of abnormal proteins or specific unstable proteins during sinigrin
metabolism.
Interestingly, a very recent study reported that iberin, an ITC derivative of glucoiberin,
significantly and highly upregulated the expression of an efflux transporter, an outer membrane
protein, components of ABC transporters and two (probable) oxidoreductases in Pseudomonas
aeruginosa (Jakobsen et al., 2012). This finding is in accordance with our results on increased
expressions of ABC transporter subunits and oxidoreductases found in L. agilis R16 upon
sinigrin supplementation. It was suggested that both the GSL metabolism and the formation of
its degradation products could affect the transport system supporting influx of GSL and efflux of
its degradation products out of bacterial cells. Oxidoreductases may be required to
biotransform either GSL substrate or ITC/NIT product or the unaccounted for metabolites to the
new more reduced or more oxidized product since 100% percentage product was never
achieved upon metabolism of any GSLs thus far (Chapter 2).
It has been known that the electrophilic feature of ITCs has facilitated its interaction
203
with some nucleophilic agents including amino, hydroxyl, thiol, carboxylic acids from small
peptides, amino acids and water (Zhang et al., 1996; Cejpek et al., 1998). For examples, dietary
ITCs namely sulforaphane, erucin, and iberin are found to play a vital role in the regulation of
redox status through the induction of thioredoxin reductase 1 (TrxR1) in human breast cancer
MCF-7 cells (Wang et al., 2005). AITC, after its formation by sinigrin hydrolysis, appeared to
inhibit bacteria by its interactions with amino acids and proteins and interference with the
action of important enzymes e.g. glutathione reductase, thioredoxin and acetate kinase
(Luciano et al., 2008; Luciano et al., 2009). Our findings with upregulated expressions of acetate
kinase and oxidoreductases may be a result from AITC products as inducers of these proteins
from sinigrin degradation by the studied bacteria.
Desulfation of GSL by putative bacterial sulfatase that consequently produces sulfate
and desulfo-glucosinolate (DS-GSL) may involve oxidoreductases in the metabolic fate of sulfate
and DS-GSL. In addition, GSL can be converted to NIT via a possible redox-cycling step of iron (II)
and iron (III) ions and involves an oxidoreductase (Hanschen et al., 2012). Therefore, increased
expressions of enzymes involved in oxidoreduction system e.g. flavoprotein WrbA, alkyl
hydroperoxide reductase subunit C and superoxide dismutase with oxidoreduction activity
were also observed in E. coli O83:H1 NRG 857C.
GSL, as a β-glucoside, may require phosphorylation modification prior to its degradation
by certain 6-phospho-β-glucosidases (Witt et al., 1993). Thus, some proteins involved in
phosphotransferase system (PTS), sugar transport subunits and kinases such as glucose-specific
PTS system component, N-acetyl glucosamine specific PTS system component IIABC and
glucokinase were identified. These proteins were upregulated upon sinigrin metabolism in E.
coli O83:H1 NRG 857C. Despite intensive studies of PTS permeases, the mechanism that couples
sugar translocation to phosphorylation in E. coli and the nature of the translocation apparatus
are not well-understood (Yagur-Kroll et al., 2009).
Once sinigrin is degraded by putative bacterial GSL-degrading enzyme, glucose and
aglycone are released. It is likely that some proteins involved in sugar/glucose metabolism were
upregulated upon sinigrin supplementation. For example, phosphoglycerate phosphatase,
glyceralaldehyde-3-phosphate dehydrogenase, D-lactate dehydrogenase, acetate kinases from
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L. agilis R16, and glucokinases, adenylate kinase, glucose-1-phosphatase, glucose-6-phosphate
dehydrogenase from E. coli O83:H1 NRG 857C may be affected at an expressional level.
From our results, greater numbers of protein spots were detected from 2-DE gels of L.
agilis R16 grown on media with and without sinigrin supplementation than E. coli counterparts.
The differences in protein expression between these two bacteria may be caused by differences
in inherent metabolisms of different bacterial strains and/or stimulating effects from different
compositions in growth media. Some ingredients found in modified MRS (glucose omitted)
media for L. agilis R16 e.g. Tween-80, K2HPO4, Na-acetate, (NH4)2 citrate, MgSO4 7H2O and
MnSO4-H2O (in addition to peptone, beef extract, yeast extract, and NaCl in NB media used for
E. coli O83:H1 NRG 857C growth) may stimulate/increase the expression of certain proteins.
These ingredients in bacterial broths may also be the cause of the increased expression of
certain proteins identified in this work.
To conclude, a majority of identified proteins with at least two fold increased
abundance upon sinigrin supplementation in both bacteria belong to transport system,
carbohydrate metabolism and oxidoreduction system. This work provides, for the first time,
identification of proteins that are potentially involved in the metabolism of GSL in human gut
bacteria. However, proteins that are expressed in response to the accumulation of GSL
degradation products including sulfate and ITC/NIT should be accounted for in addition to those
upregulated upon GSL metabolism as performed in this work. For a more comprehensive study,
the proteome change in response to the addition of ITC and NIT into bacterial cultures should
be investigated in the future.
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Chapter 4: Reverse proteomics approach to identify bacterial proteins potentially involved in the metabolism of GSLs 4.1 Introduction
In parallel to forward proteomics approach (Chapter 3), reverse proteomics
approach was used in this chapter to identify bacterial proteins potentially involved in the
metabolism of GSLs such as bacterial GSL-degrading enzymes, β-O-glucosidases or sulfatases.
Since the availability of genome database is a pre-requisite for reverse proteomics, only two
bacteria E. casseliflavus NCCP-53 and E. coli O83:H1 NRG 857C with accessible
genome/proteome database were studied in this chapter. Based on the results found in
literature and in chapter 2, the hypotheses of this chapter are shown in Figure 4.1.
Figure 4.1 Hypotheses of this chapter. See main texts for more details.
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The putative bacterial enzymes potentially involved in GSL metabolism to be searched
for in this chapter are as follows:
Bacterial GSL-degrading enzymes: From chapter 2, intact GSLs were metabolized
to ITC and/or NIT products by bacteria isolated from human faecal sample suggesting the
existence of bacterial GSL-degrading activity (a.k.a myrosinase-like activity) in these human gut
bacteria like in plant and aphid. Therefore, in this chapter, the putative bacterial GSL-degrading
enzyme was searched for using the sequence of the well-characterized myrosinase from B.
brassicae (cabbage aphid) as a reference. Aphid myrosinase was successfully characterized
using sequence alignment with white mustard myrosinase (Jones et al., 2002). Aphid
myrosinase has significant sequence similarity (35%) to plant myrosinases and other members
of glycosyl hydrolase family 1 (GH1) (Jones et al., 2002). Based on sequence similarity and
phylogenetic techniques, aphid myrosinase appears to be more similar to animal β-O-
glucosidases than to plant myrosinases. Aphid myrosinase is most similar to insect β-O-
glucosidases from the mosquito Anopheles gamblae (47%), the fruit fly Drosophila
melanogaster (45%), and the cockroach Leucophaea maderae (48%). These results strongly
suggest that myrosinase activity has evolutionarily diverged from β-O-glucosidases in plants and
animals (Jones et al., 2002). Aphid myrosinase is also similar to various bacterial β-glucosidases
Bacillius halodurans (37%), Clostridium acetobutylicum (35%), Thermoanaerobacter
tengcongensis (35%), and 6-phospho-β-glucosidase from E. coli (29%).
Myrosinase is a type of β-glucosidases. β-glucosidases (EC 3.2.1.21) catalyze the
hydrolysis of the glucosidic linkage of aryl- and alkyl-β-glucosides, and liberate terminal non-
reducing β-glucosyl residues from oligosaccharides. Based on amino acid sequence and
structural similarity, known β-glucosidases have been placed in Glycoside Hydrolase (GH)
Families GH1, GH3, GH5, GH9, GH30, and GH116 (Ketudat Cairns & Esen, 2010; Cantarel et al.,
2009; Sansenya et al., 2011). Therefore, one can expect bacterial GSL-degrading enzyme or
myrosinas-like enzyme to fall into one of these six GH families. At this writing, all characterized
myrosinases in plants and aphid come from GH1 family only. There is no report of myrosinase
that comes from other GH family. However, BLASTp results showed a few GH3 enzymes that
have certain degree of sequence similarity to aphid myrosinase (Table 4.10).
207
Bacterial sulfatases: From chapter 2, DS-GSL was found as a precursor to NIT
production in bacterial fermentation whereas intact GSL was a precursor to both ITC and NIT
production. This raised the question whether these bacteria may exhibit sulfatase activity that
transform GSL to DS-GSL by desulfation like in H. pomatia (Roman snail) and also they may
exhibit β-glucosidases that can transform DS-GSL to NIT products. In this chapter, the putative
bacterial sulfatase was searched for using the sequence of sulfatase from H. pomatia as a
reference.
4.1.1 Reverse proteomics
In classical proteomics, the starting materials are isolated proteins which are analyzed
via MS techniques, and proteins are identified using complete genome sequences. In contrast,
in reverse proteomics, the starting point is the genome sequence of an organism. First, the
transcriptome and proteome are predicted in silico and subsequently this information is used to
generate reagents for gene functional analysis. This reverse proteomics strategy includes
several steps such as cDNA cloning, protein expression (several systems from E. coli, S.
cerevisiae to mammals are available) and specific functional assays based on gene function
annotations (Figure 4.2). When reverse proteomics is applied downstream of a forward
proteomics pipeline, the experimental design will be focused on the genome subset
corresponding to the previously identified gene products.
208
Figure 4.2 Scheme of the reverse proteomics workflow. This figure was taken from Palcy & Chevet
(2006).
4.1.1.1 Molecular cloning
Molecular cloning is used to assemble recombinant DNA molecules and to direct their
replication within host organisms (Watson, 2007). The method entails the replication of a single
DNA molecule in a single cell as a starting point to generate a large population of cells
containing identical DNA molecules. The steps of molecular cloning are described as follows:
(1) Choosing cloning vector and host organism
E. coli and plasmid vectors are commonly used as they are versatile, technically
sophisticated, widely available, and allow rapid growth of recombinant organisms with minimal
equipment (Brown, 2006). The vector used has to contain four DNA segments that are of
209
significance to its function and experimental utility, (i) an origin of DNA replication is crucial for
the recombinant sequences adjacent to the vector to replicate inside the host organism, (ii) at
least one unique restriction endonuclease recognition sites are present where foreign DNA may
be inserted, (iii) a selectable genetic marker gene that enables the survival of cells that have
taken up vector, and (iv) an additional gene to be used for screening cells harbouring foreign
DNA (Brown, 2006).
(2) Vector DNA preparation
Restriction endonuclease is used to cleave the cloning vector at the specific restriction
site(s) where foreign DNA will be inserted. To generate compatible ends, the vector DNA and
foreign DNA are cleaved with the same restriction enzyme. Most modern vectors e.g. pGEM
(Promega) contain a variety of unique restriction sites that are located within a gene
(frequently β-galactosidase). This gene inactivation by foreign DNA insertion can be used to
distinguish recombinant from non-recombinant organisms during the screening process (Russell
& Sambrook, 2001).
(3) DNA insert preparation
The DNA to be cloned is extracted from the genomic DNA of an organism of interest.
Contaminating proteins, RNA (ribonuclease) and smaller molecules are removed from the DNA
prior to DNA amplification by polymerase chain reaction (PCR). DNA for cloning experiments
may also be obtained from complementary DNA (cDNA) cloning via RNA starting material using
reverse transcriptase, or in the form of synthetic DNA. The purified DNA is then digested with a
restriction enzyme to produce fragments with ends compatible with those of the vector (Russell
& Sambrook, 2001).
(4) Generation of recombinant DNA with DNA ligase
The vector DNA and foreign DNA insert are simply mixed together at appropriate
concentrations with DNA ligase that covalently links the ends together which is termed
‘ligation’.
210
(5) Introduction of recombinant DNA into the host organism
Various methods are used to introduce recombinant DNA into cells e.g. transformation,
transduction, transfection and electroporation (Howe, 2007). Competent host cells with a
physiological state that can take up DNA are introduced with recombinant DNA using either
above method. Competent cells are usually prepared through a special growth regime and
chemical treatment process depending on the specific species and cell types that are used.
Once cells have taken up and replicated DNA from their local environment, the process is
termed transformation (Lederberg et al., 1994).
(6) Selection of organisms containing vector sequences
The introduction of recombinant DNA into the host organism is usually a low efficiency
process. When host organisms are bacterial cells, the selection marker is usually a gene that
confers resistance to certain antibiotics e.g. ampicillin and kanamycin that would otherwise kill
the cells. Upon addition of antibiotics, cells harboring the vector will survive however those that
did not take up vector sequences will die (Brown, 2006).
(7) Screening for clones habouring desired DNA inserts and biological properties
Colonies of transformed cells can be distinguished from those containing the parental
vector (i.e. vector DNA with no recombinant sequence inserted) by using the blue-white
screening system. This system is enabled by the use of modern bacterial cloning vectors e.g.
pUC19 (Promega, UK) and more recent derivatives including the pGEM vectors (Howe, 2007).
Foreign DNA is introduced into a sequence encoding an essential part of β-galactosidase in
these vectors. This enzyme activity leads to formation of a blue-coloured colony on the agar
plate. Insertion of the foreign DNA into the β-galactosidase coding sequence disables the
function of the enzyme, so that colonies (clones) containing recombinant plasmids remain
colorless (white). A very broad range of experimental methods, including the use of polymerase
chain reaction, antibody probes, restriction fragment analysis, nucleic hybridization and/or DNA
sequencing can be used to confirm the presence of desired DNA construct in a number of
different clone (Howe, 2007).
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4.1.1.2 Recombinant protein expression
Since pET28b+ vector was used in this work, only pET expression system was reviewed
as follows. The pET expression system makes use of multiple cloning sites for the insertion of
different fusion partners, hybrid promoters and restriction sites, along with a high number of
genetic backgrounds modified for various expression purposes (Dubendorf & Studier, 1991;
Studier et al., 1990). Expression requires a BL21(DE3) host strain lysogenized by a DE3 phage
fragment encoding the T7 RNA polymerase (bacteriophage T7 gene 1) under the control of the
isopropyl β-D-1-thiogalactopyranoside (IPTG) inducible lacUV5 promoter (Sørensen &
Mortensen, 2005) (Figure 4.3). Both lacUV5 promoter and the T7/lac hybrid promoter encoded
by the pET expression plasmid are repressed by LacI repressor. The lacI gene has a copy in the E.
coli genome and in the pET plasmid. During IPTG induction, tetrameric LacI is released from the
lac operator upon IPTG binding, and T7 RNA polymerase is transcribed. As little as 50–100 μM
IPTG is usually sufficient to achieve full induction.
Figure 4.3 Recombinant expression mechanisms in pET expression system. A general pET plasmid configuration is shown on the right and a genomic configuration of BL21(DE3) host is shown on the left. This figure was taken from http://life.nthu.edu.tw/~b871614/protocols/pet.html.
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Transcription of the target gene from the T7/lac hybrid promoter (also repressed by
LacI) on the pET plasmid is subsequently initiated by T7 RNA polymerase produced by
BL21(DE3) host (Sørensen & Mortensen, 2005). The T7 promoter with a 20-nucleotide sequence
is not recognized by the E. coli RNA polymerase. T7 RNA polymerase transcribes five times
faster than E. coli RNA polymerase (50 nucleotides per second) at the maximum rate of 230
nucleotides per second. This system leads to the synthesis of large amounts of mRNA, and, in
most cases, the concomitant accumulation of the desired protein at very high concentrations
(40–50% of the total cell protein) (Baneyx, 1999).
4.1.1.3 Enzyme activity and assay
Enzyme activity is measured as the quantity of active enzyme present under defined
conditions (Passonneau & Lowry, 1993). It is performed in vitro under conditions that often do
not closely resemble those in vivo. The conditions used should be at the optimum pH,
‘saturating’ substrate concentrations, and at the optimum temperature. The factors e.g.
substrate concentrations(s), pH, ionic strength and nature of salts present, and temperature
can affect the activity of an enzyme. In some cases, the opposite direction to that of the
enzyme’s natural function is measured for the enzyme activity. A complete in vitro study of the
parameters affecting enzyme activity should enable one to extrapolate to the activity expected
to be occurring in vivo (Scopes, 1993).
Typically, enzyme assays measure either the appearance of product or the
disappearance of substrate over time. Several methods have been developed to determine the
concentration of substrates or products in a reaction. However, all enzyme assays can be
categorized into two types: (i) discontinuous and (ii) continuous assays.
(i) The discontinuous assay measures enzyme concentration in fixed periods of time. The
amount of substrate consumption or product production is determined from samples removed
from an enzyme reaction at intervals (Bergmeyer, 1974). Methods for stopping the reaction
include those which denature the enzyme, such as a strong acid, alkali or detergent, heat, or
treatments with irreversible inhibitors such as heavy metal ions. In some cases, the enzyme can
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be stopped by the addition of a complexing agent such as ethylenediaminetetraacetic acid
(EDTA), which chelates or removes metal ions essential for activity. Stopped assays should be
checked at least once with varying times of incubation to ensure that the rate is linear through
the period selected for the standard method. Examples of discontinuous assays include
radiometric assays that measure the incorporation of radioactivity into substrates or its release
from substrates, chromatographic assays that measure product generation by separating the
reaction mixture into its components by HPLC analysis.
(ii) The continuous assay follows the progress of the reaction as it occurs. This method is
much more convenient in that the result is seen immediately, and any deviation of the initial
rate from linearity can be observed. However, not all enzymes have an assay method that can
be observed continuously. The simplest continuous assay is designed to follow the action of the
enzyme itself by changes in absorbance (e.g. NAD(P)H at 340nm with dehydrogenases),
viscosity, pH, fluorescence or one of several other possible physical parameters. In many cases
of hydrolase assays, an artificial substrate which releases a coloured or fluorescent product is
used. Unfortunately, most enzymes do not produce any change in a readily detectable physical
parameter by their activity. This can be overcome using a coupled continuous method in which
the product is acted on further (usually by other enzymes that are added to the mixture) until
an ultimate product is formed which can be observed physically.
4.1.2 Hypotheses
Since very little is known about the enzymes involved in bacterial GSL metabolism, the
aim was to try as many techniques as possible to identify theses key proteins involved in GSL
metabolism such as GSL-degrading enzymes, β-O-glucosidases or sulfatase. In Chapter 3, the
sensitivity of forward proteomics approach may be limited if the protein of interest is low
abundance. Therefore, a complementary reverse proteomics approach was used in this chapter.
The hypothesis is as follows.
The bacterial genes/proteins involved in GSL metabolism can be identified using BLAST
search and can be characterized using molecular biology techniques.
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4.1.3 Objectives
To test the above hypothesis, objectives were set out as follows;
To use BLAST search in a search for putative bacterial GSL-degrading enzymes or
myrosinase-like enzymes, β-O-glucosidases or sulfatases based on known sequences of
the well-characterized proteins from cabbage aphid and Roman snail.
To clone and express genes of interest and subsequently perform enzyme activity assays
on those recombinant enzymes.
Since the availability of genome database is a pre-requisite for reverse proteomics, only
two bacteria E. casseliflavus NCCP-53 and E. coli O83:H1 NRG 857C with accessible
genome/proteome database were studied in this chapter. The characterization of enzymes of
interest found in this chapter will be investigated in Chapter 5.
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4.2 Materials and Methods
4.2.1 Sequence alignment and bioinformatic analysis:
Sequence similarity search was performed by BLASTX Network Service (NCBI) (Altschul
et al., 1990) (http://blast.ncbi.nlm.nih.gov/Blast.cgi). Detailed information on the proteins of
interest were retrieved from UniProt (Consortium, 2012) at www.UniProt.org. Multiple
sequence alignment was generated using ClustalW2 (Larkin et al., 2007)(http://www.ebi-
ac.uk/ClustalW). The default colour table for amino acids is shown in Figure 4.4. Amino acids
with similar properties are given similar colours.
Figure 4.4 Colour table referring to the labelling of amino acids (single letter code) used in ClustalW alignments.
The accessory application within ClustalW2 with default parameters (gap open penalty,
10; gap extension penalty, 0.05) (Thompson, 1995) was used to generate the alignments.
4.2.2 Genomic DNA extraction
Bacterial culture (2 mL) in corresponding culture broth (i.e. NB medium for E. coli
O83:H1 NRG 857C and WC medium for E. casseliflavus NCCP-53) was anaerobically grown
overnight at 37°C. Subsequently, the culture was centrifuged at 16,000g for 5 min to give a
bacterial pellet. Unless otherwise stated, an Eppendorf 5415 D centrifuge was used throughout
this work for centrifugation steps of small volumes (up to 2 mL per sample). Genomic DNA was
extracted directly from the bacterial pellet using the Wizard® Genomic DNA Purification Kit
(Promega) as per instructions provided with the kit.
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4.2.3 Primers
Primers with designated restriction sites for PCR experiments were synthesized by
Sigma-Aldrich primer synthesis service. These primers are listed in Table 4.1.
Table 4.1 Primers used in PCR experiments and their restriction sites are underlined
No. Name* Primer sequence (5’-3’) Restriction site
1 EC_bgl-F GGTTTGCCATATGTTTCACACAAACT NdeI 2 EC_bgl-R AGGGAGCTCTCATGTTTCACTTGTC SacI 3 EC_GH3#1-F GGTCATATGGAACAGCAGAAATTAACCGA NdeI 4 EC_GH3#1-R GTTGAGCTCTTACCTAACTAATTGCAGGG SacI
5 EC_GH1-F GGTTTGCCATATGGATCATAAACAACT NdeI 6 EC_GH1-R GTTGAGCTCCTAGCACTCTTGC SacI 7 EC_GH3#2-F GGTCATATGAAAAATCAAACACTGGTA NdeI 8 EC_GH3#2-R GTTGAGCTCTTACGTTCGACTGCC SacI 9 EC_GH3#3-F GGTGCTAGCATGAAAAATCAAACACTGG NheI
10 EC_GH3#3-R GTTGAGCTCTCATAGAAGTTCGAAAGTCG SacI 11 EC_6pbg1-F GGTTTGCCATATGTACATGCTTAAATTACC NdeI
12 EC_6pbg1-R CCAGAGCTCTTAAATAATCGTTTTGGTT SacI 13 EC_pBgl-F GGTCATATGGAGAAGCATATGATTGAG NdeI
14 EC_pBgl-R GTTGAGCTCTCATTCTTTTGCTCCTTT SacI 15 EC_SUL1-F GGTCATATGAAAAAAAATAAAGTATCCACC NdeI 16 EC_SUL1-R GTTGAGCTCTTATTCTCCGCTATCTTG SacI 17 ECO_SUL2-F GGTCATATGAAACGCCCCAATTTTCT NdeI 18 ECO_SUL2-R GTTGAGCTCTCAGAACTTCTGTTTTTTCT SacI 19 ECO_6pbg2-F GGTGCTAGCATGAGCCAGAAATTA NdeI 20 ECO_6pbg2-R GTTGAGCTCATGTGCTTTTTTAAGC SacI
*Referred to Table 4.10 for gene annotations. EC, E. casseliflavus NCCP-53; ECO, E. coli O83:H1 NRG
857C
4.2.4 Bacterial strains and plasmids
E. coli DH5α was used for gene cloning and E. coli BL21(DE3) was used for protein
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expression. Gene inserts of interest were ligated into pET28b(+) vectors. A list of bacterial
strains and plasmids used in this study are shown in Table 4.2.
Table 4.2 Bacterial strains and plasmids used in this study
Strain /plasmid Relevant characteristics Reference
Strains
DH5α F-, endA1, glnV44, thi-1 , recA1, relA1, gyrA96, deoR , nupG , Φ80dlacZΔM15, Δ(lacZYA-argF)U169, hsdR17(rK
- mK+), λ– Promega
BL21(DE3) F-, dcm, ompT, hsdS(rB- mB
-), gal λ(DE3) Stratagene Plasmids pET28b(+) Expression vector, IPTG-inducible, T7 promoter, His-tag, KmR Novagen
pET28b-bgl 1470 bp gene insert from E. casseliflavus ligated into pET28b+ vector This work
pET28b-GH3#1 2151 bp gene insert from E. casseliflavus ligated into pET28b+ vector This work
pET28b-GH1 1437 bp gene insert from E. casseliflavus ligated into pET28b+ vector This work
pET28b-GH3#2 1488 bp gene insert from E. casseliflavus ligated into pET28b+ vector This work
pET28b-GH3#3 2211 bp gene insert from E. casseliflavus ligated into pET28b+ vector This work
pET28b-6pbg1 1407 bp gene insert from E. casseliflavus ligated into pET28b+ vector This work
pET28b-pBgl 2256 bp gene insert from E. casseliflavus ligated into pET28b+ vector This work
pET28b-SUL2 1494 bp gene insert from E. coli O83:H1 ligated into pET28b+ vector This work
pET28b-6pbg2 1353 bp gene insert from E. coli O83:H1 ligated into pET28b+ vector This work
4.2.5 Polymerase chain reaction (PCR)
The genomic DNA was used as a template for gene amplification by Pfu DNA polymerase
(Promega) for 28 cycles. Each PCR reaction was mixed in a sterile, nuclease-free
microcentrifuge tube containing the components as shown in Table 4.3.
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Table 4.3 Components in one PCR reaction
Components Volume (µL)
Final Concentration
10X Pfu DNA Polymerase Buffer with MgSO4 5.0 1X
10 mM dNTP mix (Promega) 1.0 200 µM
10 µM Forward primer 1.0 0.2 µM
10 µM Reverse primer 1.0 0.2 µM
DNA template 1.0 < 0.5 µg/50 µL
Pfu DNA Polymerase, 2-3 U/µL (Promega) 0.5 1.25 U/50 µL
Nuclease-Free water to final volume of 40.5
Total volume 50.0
The PCR reaction carried out in Eppendorf Thermal Cycler MasterCycler Personal 5332
includes thermal cycling conditions as shown in Table 4.4.
Table 4.4 Thermal cycling conditions for Pfu DNA Polymerase-mediated PCR amplification
Step Temperature (°C) Time Cycle(s)
Initial denaturation 95 1 min 1
Denaturation 95 30 s
28 Annealing 58 30 s
Extension 72 2 min/kb
Final extension 72 5 min 1
Hold 4 Indefinite 1
4.2.6 PCR product purification The PCR products analyzed on a 0.8% agarose gel (Section 4.2.11) were excised using a
sterile blade and subsequently purified according to the manual of QIAquick PCR Purification Kit
(Qiagen). The DNA concentration was determined using a Nanodrop ND-1000
spectrophotometer (Thermo Scientific, UK).
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4.2.7 Ligation Ligations were performed using T4 DNA Ligase (Promega) according to the producers’
specifications. A 3:1 ratio of desired PCR insert to pET28b(+) vector (50 ng) was well-mixed by
pipetting in a microcentrifuge tube and incubated at 4°C overnight. Components in a ligation
mixture (10 µL) are shown in Table 4.5. A map of pET28b(+) vector is shown in Figure 4.5.
Table 4.5 Components in one ligation reaction
Component Volume (µL)
10X T4 Ligase Buffer (Promega) 1.0
T4 Ligase enzyme, 3 U/mL (Promega) 1.0
Cut pET28b+ vector 2.0
PCR product or gene insert 6.0
Total volume 10.0
Figure 4.5 Map of an expression vector, pET28b(+)
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4.2.8 Bacterial transformation with ligation mixture
A ligation mixture of 50 ng (approximately 2 µL) was added to a 50 µL aliquot of freshly
thawed competent E. coli DH5𝛼 cells. These were incubated on ice for 20 min then at 42°C for
90 s and stored on ice for 2 min. Subsequently, 950 µL of LB was added to suspend the cells
which were incubated in a shaker at 225 rpm, 37°C for 1 h. Following this, cells were
centrifuged at 3,300g for 1 min. The pellet was re-suspended in 200 µL of fresh LB broth and
spread on a selection plate (Section 4.2.9) containing 50 µg/mL kanamycin which allows
bacterial cells harbouring pET28b+ plasmids to grow.
4.2.9 Preparation of competent cells
The competent E. coli DH5α and BL21(DE) cells were prepared by diluting an overnight
bacterial culture 1:100 in 200 mL LB. When the OD600 reached 0.4 - 0.5, the cultures were
centrifuged at 3,220g for 20 min at 4°C using Eppendorf 5810 R centrifuge. An Eppendorf 5810
R centrifuge was used throughout this work for centrifugation step of large volume (up to 50
mL per sample). The resulting bacterial pellet was gently re-suspended in 5 mL of ice-cold 100
mM CaCl2. The suspension was kept on ice for 15 min followed by centrifugation at 3,220g for 5
min at 4°C. The bacterial pellet was gently re-suspended in a 1 mL mixture containing 700 µL of
cold 100 mM CaCl2 and 300 µL of 50% sterile glycerol stock (to make a final concentration of
15% glycerol). A 50 µL aliquot of cells was dispensed into a pre-cooled 1.5 mL Eppendorf tube
for each transformation and frozen at - 80°C. The competent BL21(DE3) cells were made the
same way without adding any antibiotics.
4.2.10 Selection of transformants To make selection plates, 15 g agar (Oxoid, UK) was added to 1 L of Luria-Bertani (LB)
medium (In 1 L: 10 g tryptone (Oxoid, UK), 5 g yeast extract (Oxoid, UK), 10 g NaCl (Sigma-
Aldrich, UK)) and was well-mixed before being autoclaved at 121°C for 15 min. The medium was
allowed to cool to 50°C before adding kanamycin (Sigma-Aldrich, UK) to a final concentration of
50 μg/mL. The transformant colonies harbouring recombinant gene-pET28b plasmids grown on
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the selection plates were selected. Subsequently, the selected colonies were subjected to a
colony PCR experiment to determine whether these colonies were of the right size for the gene
fragment of interest.
4.2.11 Colony PCR experiment This method was designed to quickly screen for plasmid inserts directly from
transformant colonies. To each PCR tube containing the PCR reaction (total volume of 25 µL) a
small amount of the colony was added as well as other components (Table 4.6). To do this, a
fine yellow pipette tip was used to touch the edge of the colony and the reaction was pipetted
up and down to mix. For colony PCR, Taq polymerase already included in 5X Crimson Tag
Reaction Buffer (Table 4.6) was used instead of Pfu polymerase. The vector forward primer, T7
promoter primer with the sequence 5’ TAATACGACTCACTATAGGG 3’ and the gene-specific
reverse primer (Table 4.1) were used to amplify both the gene region on the pET28b+ vector
and the gene of interest from the selected colonies in this experiment.
Table 4.6 Components in one colony PCR reaction
Component Volume (µL) Final Concentration
5X Crimson Taq Reaction Buffer (Biolabs, UK) 5.000 1X 10 mM dNTP (Promega) 0.500 200 µM
10 µM Forward Primer 0.500 0.2 µM
10 µM Reverse Primer 0.500 0.2 µM
Template DNA from a colony See text <1,000 ng
Crimson Taq DNA Polymerase (Biolabs, UK) 0.125 1.25 U/50 µL PCR
Nuclease-free water 18.375
Total volume 25.000
The colony PCR reaction carried out in Eppendorf Thermal Cycler MasterCycler Personal
5332 includes thermal cycling conditions as shown in Table 4.7.
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Table 4.7 Thermal cycling conditions for Taq DNA Polymerase-mediated colony PCR
amplification
Step Temperature (°C) Time Cycle(s)
Initial denaturation 95 30 s 1
Denaturation 95 30 s
30 Annealing 56 1 min
Extension 68 1 min/kb
Final extension 68 5 min 1
Hold 4 Indefinite 1
4.2.12 Restriction enzyme digestion
All restriction enzymes, NdeI, SacI and NheI (Fast Digest) were purchased from
Fermentas (UK). The total reaction volume of 30 µL contained ingredients shown in Table 4.8.
Table 4.8 Ingredients for restriction enzyme digestion
Ingredient Volume (µL) PCR product/pET28b+ vector 20 ddH2O 5 10X Tango buffer 3 NheI/NcoI 1 SacI 1 Total volume 30
4.2.13 Agarose gel electrophoresis
All PCR products and digested DNA fragments were resolved on a 0.8% agarose gel
(Sigma-Aldrich, UK). The gel (40 mL) was stained with 0.5 µL of SYBR® Safe DNA gel stain
(Invitrogen). To assign the molecular weight of the sample, 7 µL of Quick-Load 1 kb DNA ladder
molecular marker (BioLabs, UK) (Figure 4.6) was loaded into a separate well. Gels were
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visualised by Safe Imager™ blue light transilluminator (Invitrogen) and gel pictures were
captured by Quantity One® 1-D Analysis Software (Bio-Rad).
Figure 4.6 Quick-Load 1 kb DNA ladder molecular marker (BioLabs, UK) used in this chapter. 4.2.14 Plasmid extraction Transformant colonies were grown in 5 mL LB media supplemented with kanamycin at a
final concentration of 50 μg/mL overnight at 37°C. Subsequently, the overnight culture was
centrifuged at 16,100g for 5 min to collect a cell pellet. Plasmids of transformant colony were
isolated from the pellet using a Qiagen Plasmid Miniprep Kit as per manual.
4.2.15 DNA sequencing and sequence analysis
The extracted plasmid was sent for sequencing to the ‘GATC’ sequencing company (UK)
using the specific gene primer as a forward primer and the pET28b+ T7-TER primer as a reverse
primer. The obtained gene sequences were checked whether they are the same as the known
genes using BLAST search (Altschul et al., 1990)
4.2.16 Recombinant protein expression A pre-culture of transformed cells (5 mL) was grown overnight at 37C in LB broth
supplemented with 50 µg/mL kanamycin. On the following day, the pre-culture was inoculated
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into 1 L LB broth supplemented with kanamycin as in the start culture. The recombinant
BL21(DE3) cells were anaerobically grown to an OD600 of 0.6 and induced to express the
recombinant protein by the addition of 0.5 mM isopropyl β-D-1-thiogalactopyranoside (IPTG)
for overnight at 25C at 200 rpm. The cells from the induced liquid culture were centrifuged for
20 min at 3,220 at 4C in an Eppendorf 5810 R centrifuge. The pellets were re-suspended in 10
mL buffer (100 mM Tris-Cl pH 7.0) supplemented with 100 µL protease inhibitor cocktail (100X,
Melford, UK). The cells were lysed through two shots of a 30k psi disruption cycle in a tissue
disrupter (Constant Cell Disruption Systems, UK). The supernatants were recovered after
centrifugation at 16,100g at 4C for 30 min. These cell-free extracts were desalted against
buffer (0.1 M mM Tris-Cl, pH 7.0) on an Econo Pac 10 DG column (Bio-Rad, UK) (Section 4.2.18).
The protein concentrations of the eluted proteins were assessed using Bradford’s reagent
(Sigma, UK) as previously described (Chapter 2, section 2.2.20), and the purity was analyzed by
SDS-PAGE (Chapter 2, section 2.2.11). The desalted supernatant was stored at 4C until enzyme
activity assays.
4.2.17 SDS-PAGE analysis
SDS-PAGE analysis was carried out as previously described (Chapter 2, section 2.2.11).
The protein markers used in this chaper are shown in Figure 4.7.
Figure 4.7 Protein markers. (A) PageRuler pre-stained protein ladders (Thermoscientific, UK), (B) EZ-Run unstained ladders (Fisher, UK), (C) Broad Range pre-stained ladders (BioLabs) and (D) Low Range unstained marker (Sigma-Aldrich).
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4.2.18 Desalting recombinant enzymes
The appropriate buffer (20 mL of 0.1 M mM Tris-Cl, pH 7.0) was added to the Econo Pac
10 DG column (Bio-Rad, UK) to equilibrate it. The cell-free extract containing the recombianat
enzyme (3 mL) was added to the column, and the flow-through was discarded. The elution
buffer (4 mL of 0.1 M mM Tris-Cl, pH 7.0) was added to the column to elute the higher
molecular weight component(s) and the flow-through (4 mL) collected as ‘desalted cell-free
extract’ for further analysis.
4.2.19 GOD-PERID assay
This assay was used to determine glucose release upon GSL or β-glucoside breakdown
by myrosinase activity or β-thioglucosidase/β-O-glucosidase activity, respectively (Bones, 1990).
The GOD-PERID reagent consists of 2,2'-azino-bis(3-ethylbenzthiazoline-6-sulphonic acid) or
ABTS (1 mg/mL), glucose oxidase (8 U/mL) and peroxidase (0.35 U/mL) dissolved in Tris buffer
(1.2 g/100 mL) pH 7.2. To make 250 mL GOD-PERID reagent, 3 g of Tris was dissolved in distilled
water with adjustment to pH 7.2 by using HCl, 12.7 mg of glucose oxidase (157.5 U/mg) was
dissolved in 10 mL of Milli-Q water and then added to the Tris buffer, 4.7 mg peroxidase (148
U/mg) was dissolved in 20 mL Milli-Q water, and a 2.5 mL aliquot was added to Tris buffer, 250
mg ABTS was added and stirred to dissolve, and finally the mixture was made up to 250 mL with
Milli-Q water. This reagent was stored in dark cold place until use. All the chemicals were
purchased from Sigma-Aldrich, UK. GSL was added to GOD-PERID reagent as a substrate for
myrosinase, and if present, the breakdown of GSL would produce AITC and/or NIT and D-
glucose. This D-glucose acts as a substrate for glucose oxidase in the GOD-PERID reagent which
in turn leads to the formation of a green, soluble end-product catalyzed by peroxidase. The
assay scheme is shown in Figure 4.8. The green dye absorbance maximum of 420 nm light (ε =
3.6 × 104 M–1 cm–1) can easily be followed with a spectrophotometer (Shin & Lee, 2000), and
therefore one can easily determine whether an enzyme has myrosinase activity.
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Figure 4.8 GOD-PERID assay reaction principle. (1) GSL is hydrolyzed by myrosinase to produce an unstable aglucone and D-glucose. (2) D-glucose is converted by glucose oxidase to form D-glucono-1,4-lactone and also produced hydrogen peroxide (H2O2). (3) Peroxidise, with the help of hydrogen peroxide, converts 2,2'-azino-bis(3-ethylbenzthiazoline-6-sulphonic acid) or ABTS into a dark green and soluble end-product.
The reaction mixture (300 µL) contained protein solution (100 µL, ~ 200 µg), 10 mM
sinigrin (60 µL) and 0.1 M citrate phosphate buffer (140 µL) were mixed and aerobically
incubated at 37°C for 30 min. Subsequently, the mixture was boiled at 100°C for 5 min to
deactivate the enzymes and GOD-PERID solution (1 mL) was added to the mixture and
incubated at 37°C for 15 min. The mixture was then transferred to the cuvette, and the
absorbance was measured at 420 nm (A420nm) using LKB Novaspec II spectrophotometer
(Pharmacia, UK). Glucose release from the reaction can be determined by using a calibration
curve of known glucose amounts versus absorbance at 420 nm (Figure 4.9).
227
Figure 4.9 Calibration curve for GOD-PERID assay. A graph of A420nm versus various amounts of glucose was plotted. Values are means of triplicates.
One unit of myrosinase activity was defined as the amount of enzyme liberating 1 µmol
of glucose per min. Total activity and specific activity of enzyme can be determined from the
following formulae:
Total activity = Average of A420nm x Dilution factor x F Mr of glucose x 30 min
= X µmol glucose/min
(where F = gradient from calibration curve (i.e. extinction coefficient), Mr = molecular weight)
Specific activity = Total activity Total protein
= Y µmol glucose/min/mg
4.2.20 Substrates used in GOD-PERID assay
In addition to GSL, other substrates (with α- or β- glycosidic bonds) were also used in
GOD-PERID assay. The substrates including cellobiose, trehalose dihydrate, salicin, and methyl
β-D-glucopyranoside were dissolved in Milli-Q water to make up 10 mM solution stocks. All
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chemicals were purchased from Sigma-Aldrich, UK. Cellulose is a disaccharide consisting of two
glucose molecules linked by a β(1→4) bond. It can be hydrolyzed to glucose enzymatically or
with acid. Trehalose is a natural alpha-linked disaccharide formed by an α,α-1,1-glucosidic bond
between two α-glucose units. Salicin is an alcoholic β-glucoside. Methyl β-D-glucopyranoside is
a synthetic substrate. The GOD-PERID assays using these substrates were prepared as section
4.2.17. The structures of these compounds are shown in Figure 4.10.
Figure 4.10 Structures of substrates used in GOD-PERID assay. (A) Cellobiose. (B) Trehalose. (C) Salicin. (D) Methyl β-D-glucopyranoside.
4.2.21 β-O-glucosidase activity assay
The β-O-glucosidase activity was assayed by measuring the increase in absorbance at
400 nm due to the release of yellow p-nitrophenol (pNP) from colorless p-nitrophenyl-β-D-
glucopyranoside (pNPG) substrate (Figure 4.11).
Figure 4.11 β-O-glucosidase assay reaction principle. The colorless substrate, p-nitrophenyl-β-D-glucopyranoside (pNPG), is hydrolyzed by β-O-glucosidase to produce D-glucose and a yellow-coloured p-nitrophenol (pNP) product.
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The reaction mixture (1 mL) contained 10 µL of protein solution (~ 20 µg), 1 mM pNPG
(100 µL of 10 mM pNPG stock solution) and 100 mM citrate phosphate pH 7.0 (890 µL). After
incubation at 37°C for 5 min, the reaction was stopped by adding 5 mL of 0.1 M NaOH. The
absorbance was measured at 400 nm (A400nm) by LKB Novaspec II spectrophotometer
(Pharmacia, UK). The amount of pNP product from the reaction can be determined by using a
calibration curve of known pNP amounts versus A400nm (Figure 4.12). To make a calibration
curve, different dilutions of pNP ranging from 0.02 µmol to 0.6 µmol from a 10 mM pNP stock
solution dissolved in 100 mM citrate phosphate pH 7.0 were prepared in 1 mL and 5 mL of 0.1
M NaOH was added. The corresponding A400nm values of the total volume of 6 mL reaction
mixtures were plotted against those dilutions. All chemicals were purchased from Sigma-
Aldrich, UK. One unit of β-O-glucosidase activity was defined as the amount of enzyme
liberating 1 µmol of pNP per min. Total activity and specific activity of the enzyme can be
determined in a similar manner as shown in Section 4.2.18.
Figure 4.12 Calibration curve for β-O-glucosidase activity assay. A graph of A400nm versus various amounts of pNP was plotted. Values are means of triplicates.
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4.2.22 Arylsulfatase activity assay
Arylsulfatase activity was assayed by the method of Roy (1953). The arylsulfatase
activity was assayed by measuring the increase in absorbance at 510 nm (A510nm) due to the
release of p-nitrocatechol (pNC) from p-nitrocatechol sulfate (pNCS) substrate. The assay
scheme is shown in Figure 4.13.
Figure 4.13 Sulfatase assay reaction principle. The yellow substrate, p-nitrocatechol sulfate dipotassium (pNCS), is hydrolyzed by sulfatase to produce sulfate and a red-coloured p-nitrocatechol product (pNC) which was visible seen upon 0.2 M NaOH addition.
The reaction mixture (1 mL) contained 50 mM sodium acetate buffer pH 5.0 (890 μL), 1
mM pNCS (100 μL of 10 mM pNCS stock solution), and protein solution (10 μL, ~ 20 µg). The
mixture was incubated at 37°C for 5 min after which it was added with 5 mL of 0.1 M NaOH to
stop the reaction. The absorbance was measured at 510 nm by LKB Novaspec II
spectrophotometer (Pharmacia, UK). The amount of pNC product from the reaction can be
determined by using a calibration curve of known pNC amounts as a function of absorbance at
510nm (Figure 4.14). To make a calibration curve, different dilutions of pNC ranging from 0.02
µmol to 1 µmol from a 10 mM pNC stock solution dissolved in 50 mM sodium acetate buffer
(pH 5.0) were prepared in 1 mL and prepared in 1 mL and 5 mL of 0.1 M NaOH was added. The
corresponding A400nm values of the total volume of 6 mL reaction mixtures. The
corresponding A400nm values of the total volume of 6 mL reaction mixtures were plotted
against those dilutions. All chemicals were purchased from Sigma-Aldrich, UK. One unit of
arylsulfatase activity was defined as the amount of enzyme liberating 1 µmol of pNC per min.
231
Total activity and specific activity of the enzyme can be determined in a similar manner as
shown in Section 4.2.18.
Figure 4.14 Calibration curve for arylsulfatase activity assay. A graph of A510nm versus various amounts of pNC was plotted. Values are means of triplicates.
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4.3 Results
4.3.1 BLAST searches and sequence analysis of putative bacterial GSL-degrading
enzymes/sulfatases
In this chapter, the aim was to identify putative bacterial βaglucosidases with GSL-
degrading activity and bacterial sulfatases from the isolated GSL-degrading bacterial strains that
have accessible genome/proteome database (see Figure 4.1 for hypotheses). Thus, bacterial
proteins with some degrees of similarity to the existing well-characterised aphid myrosinase
from B. brassicae (UniProt accession no. Q95X01) were searched for. This is because aphid
myrosinase is assumingly more closely related to bacterial myrosinases than plant myrosinase
(Jones et al., 2002). In a search for bacterial sulfatases, the snail sulfatase from H. pomatia
(UniProt accession no. Q9NJU7) was used as a reference sequence. The genome/proteome
database of E. coli O83:H1 NRG 857C is available, but that of E. casseliflavus NCCP-53 is not.
However, the genome/proteome database of the close relative bacteria E. casseliflavus strain
EC10/EC20/EC30/ATCC 12755 is accessible. According to UniProt database, there are eleven β
leven ng to Unin each E. casseliflavus strain EC10/EC20/EC30/ATCC 12755 and six βix ain
EC10/EC20/E. coli O83:H1 str. NRG 857C (Table 4.9).
Table 4.9 Information on genome/proteome and the number of proteins of interest from the bacteria under study
Bacterium Size (Mb) GC % Gene no.
Protein no.
Bgl no. GH no. SUL
no.
E. coli O83:H1 NRG 857C 4.89 50.7 4690 4582 6 40 15
E. casseliflavus EC20* 3.42 42.5 3341 3292 11 44 4 *This strain was used as a representative of E. casseliflavus NCCP-53 GH = Glycosyl Hydrolase family; Bgl = β-glucosidases; SUL = Sulfatase
There are seven candidate GSL-degrading enzymes (25-50% similarity to aphid
myrosinase with different Max Scores) and one candidate sulfatase enzyme (25% similarity to
233
snail sulfatase) of E. casseliflavus EC10/EC20/EC30 to be cloned from genomic DNA of E.
casseliflavus NCCP-53 (Table 4.10). Also, there are one β-glucosidase protein (36%) and one
putative sulfatase protein (38%) from E. coli O83:H1 str. NRG 857C to be cloned (Table 4.10).
Table 4.10 List of putative bacterial GSL-degrading enzymes/sulfatases with high similarity to aphid myrosinase and snail sulfatase
UniProt assession no. Gene name Assigned
name Gene family
Gene length
(bp)
Protein size
(kDa) pI
% Sequence identity*
E. casseliflavus EC10/EC20/EC30
C9CJJ3 Glycoside Hydrolase GH3#1 GH3 2211 81 5.51 50 (16.9)
C9AZA4 Periplasmic β-glucosidase pBgl GH3 2256 83 5.93 33 (18.1)
C9AY94 Glycoside Hydrolase GH3#3 GH3 2151 79 4.73 32 (17.7)
C9AW70 Glycoside Hydrolase GH3#2 GH3 1488 54 5.15 25 (12.3)
C9ABS9 β-glucosidase bgl GH1 1470 56 5.21 34 (244)
C9AXB6 Glycoside Hydrolase GH1 GH1 1437 55 5.18 33 (234)
C9AZJ8 6-phospho-β-galactosidase 6pbg1 GH1 1407 54 5.18 30 (172)
C9ACP4 Sulfatase SUL1 SUL 2124 81 4.83 25 (31)
E. coli O83:H1 NRG 857C
E4P7X8 6-phospho-β-glucosidase 6pbg2 GH4 1353 50 5.90 36 (20)
E4P283 Sulfatase/phosphatase YidJ SUL2 SUL 1494 57 5.11 38 (74)
*Sequence identity (%) was from BLASTp search. Numbers in brackets are Max Score.
The genes chosen to be cloned from the two bacteria (Table 4.10) have met the
selection criteria; (i) Based on BLASTp searches, these candidate proteins showed at least 25%
sequence similarity to aphid myrosinase or snail sulfatase, (ii) The chosen proteins are ranked
within top 10 according to Max score (BLASTp search) from each GH1, GH3 and GH4 family that
have similar sequences to aphid myrosinase. Thus, other enzymes e.g. periplasmic β-
glucosidase and 6-phospho-β-glucosidase from GH3 and GH4 families, respectively were also
selected for cloning although they are not GH1 enzymes and have lower Max scores on BLASTp
search when compared with other GH1 enzymes. The rationale was that the putative bacterial
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GSL-degrading enzymes may come from any GH families than GH1 or they may be periplasmic
enzyme or 6-phospho-β-glucosidase.
Multiple sequence alignments among the above three putative bacterial β-glucosidases
from GH1 family (i.e. bgl, GH1 and 6pbg1) with the GH1 aphid myrosinase show the well-
conserved catalytic acid/base Glu (E) residues and the catalytic nucleophile Glu (E) residues and
several other conserved residues (Figure 4.15A). Four putative bacterial β-glucosidases from
GH3 family (i.e. GH3#1, GH3#2, GH3#3, pBgl) show high degree of alignment similarity among
one another containing the well-conserved catalytic nucleophile Asp (D) residues in place of Glu
(Figure 4.15B), but the second acid/base residues are not easily identified due to high variability.
However, their alignments (of GH3 enzymes) with the GH1 aphid myrosianse did not show
many conserved residues with the GH1 aphid myrosinase. Likewise, the alignments of the GH4
enzyme (i.e. 6pbg2) with the GH1 aphid myrosinase show less conserved residues with the GH1
aphid myrosinase when compared with other GH1 enzymes. The active residues of GH4 enzyme
include Tyr (Y) and Arg (R) (Figure 4.15C).
A GH1
bgl MMFHTNLDPFPENFLWGAASAAYQIEGAWAEDGKGPSIWDTYAQIPGNTFEE-TNGKVAI 59 GH1 -MDHKQLKEFPNDFLWGSASAAYQVEGAWQEDGKGASVWDDFVRIPGKTFKA-TNGDVAV 58 6pbg1 ----MYMLKLPEDFIFGGATAAYQVEGATKEGGKGAVAWDDFLEEQGR-----FSPDPAS 51 Aphid -----MDYKFPKDFMFGTSTASYQIEGGWNEDGKGENIWDRLVHTSPEVIKDGTNGDIAC 55 :*::*::* ::*:**:**. *.*** ** . . . . * bgl DHYHRYKEDVALMKQMGLKGYRFSVAWSRILPDGEG-AVNEAGVAFYEKLVDELLRQGVE 118 GH1 DHYHRFKEDVALMKEQGLKTYRFSIAWTRIFPEGRG-EVNQAGLDFYLALIDELIKAGIE 117 6pbg1 DFYHQYAKDIELCERFGVNGLRLSIAWSRIFPDGDG-EPNPEGIAFYHRVFEECAKRNVT 110 Aphid DSYHKYKEDVAIIKDLNLKFYRFSISWARIAPSGVMNSLEPKGIAYYNNLINELIKNDII 115 * **:: :*: : : .:: *:*::*:** *.* : *: :* :.:* : .: bgl PILTLYHWDLPQALQDKYLGWEGRETAEAFERYCRILFERLGKKVTYWVTMNEQNVFTSL 178 GH1 PMVTLYHWDLPRALQEEYGGWESRKIIEDFTNYAAVLFEAFRGKVHYWVSLNEQNIFTSL 177 6pbg1 PFVTLHHFDTPKRLFDQ-GDFLNRETIEAFVSYAIFCFHEF-KEVKVWSTFNEIYPVATN 168 Aphid PLVTMYHWDLPQYLQDL-GGWVNPIMSDYFKEYARVLFTYFGDRVKWWITFNEP-IAVCK 173 *::*::*:* *: * : .: . : * *. . * : .* * ::** . bgl GYRWAAHPPGLK-DLKRMYAANHIINLANAKAINLFHELVPQGKIG-PSFGYGPMYPFSC 236 GH1 GYLLAAHPPGVT-DPKRMYEVNHIANLANASVINKFHEMKIPGKIG-PSFAYSPNYPINS 235 6pbg1 QYLLGVFPPGIKYDFTKIIACLHNMMVAHARVVNYFKENELPGEIG-VVHSLETKYAATD 227 Aphid GYSIKAYAPNLNLKTTGHYLAGHTQLIAHGKAYRLYEEMFKPTQNGKISISISGVFFMPK 233 * ...*.:. . . * :*:. . . :.* : * . : bgl DPE---DVLAAENGEAFNNAWFLDVYCKGEYPKFVYKQLAKVGLAPEVT-----PEDQAL 288 GH1 DPK---NILAAENAEDLMAHYWLDVYLWGEYPIAAMNYLKEQGIAPTIE-----PGDMDL 287 6pbg1 APE---DKHAAFLDDALSIRFLLDATYLGYYSTETLTALDEICEANQASY-HFPEEDFVE 283
235
Aphid NAESDDDIETAERANQFERGWFGHPVYKGDYPPIMKKWVDQKSKEEGLPWSKLPKFTKDE 293 .: : :* : : : . * *. . : : bgl LKQAKP--DFLGINYYHGGTAQQNNLQKQSAEKKEFSKVDPYLMQAAAGEFSPEETMFAT 346 GH1 LRSAKP--DFLGINYYQTATNAYNPLDGVGAGKMNTTGKK------GSSEETGTPGMFKK 339 6pbg1 LKKASTRNDYLGINHYQ--CHFVKAYDGENAIHHNGTGEK-------GTSVYKVKGIGER 334 Aphid IKLLKGTADFYALNHYSSRLVTFGSDPN--------------------PNFNPDASYVTS 333 :: . *: .:*:* . bgl AENPHLKKTDWGWEID-PVGFRVALRRIQANYDLP--IFITENGLGAIDQLTEDKQIHDP 403 GH1 AENPFVERTNWDWEID-PQGLRIALRRITSRYRVP--VIITENGLGEYDKLTDDHQIHDQ 396 6pbg1 IYKEGIPRTDWDWLIY-PEGLYDLLLRIKSDYPHYNKIYITENGMGYKDQFEDG-IIMDQ 392 Aphid VDEAWLKPNETPYIIPVPEGLRKLLIWLKNEYGNP-QLLITENGYG------DDGQLDDF 386 : : .: : * * *: * : * : ***** * :. : * bgl YRITYLQEHLVELQKAITDG-VELIGYCAWSFTDLLSWLNGYKKRYGFVYVDRDNQSERQ 462 GH1 YRIDYLAGHVHAIKEAISDG-AEVLGYCTWSFTDLLSWLNGYQKRYGFVYVDQDETQEGS 455 6pbg1 PRIDYLRVYLESLSKAITAG-VNVKGYFLWSLMDLFSWTNGYNKRYGLFYVDFETQK--- 448 Aphid EKISYLKNYLNATLQAMYEDKCNVIGYTVWSLLDNFEWFYGYSIHFGLVKIDFNDPQR-- 444 :* ** :: :*: . :: ** **: * :.* **. ::*:. :* : . bgl LARIPKDSFYWYQEVIRTNGASLTSET 489 GH1 LARYKKDSFYWYQELIKTNGQEC---- 478 6pbg1 --RYPKESAYWYKLVSETKTII----- 468 Aphid -TRTKRESYTYFKNVVSTGKP------ 464 * ::* ::: : *
B GH3 GH3#2 MKNQTLVQLVNQLTLDEKIGQLVQ-LSGEFFHG-SDLSLGPQQKLGIEQQTIDVVGSVLN 58 GH3#3 MKNQTLVQLVNQLTLDEKIGQLVQ-LSGEFFHG-SDLSLGPQQKLGIEQQTIDVVGSVLN 58 GH3#1 MEQQKLTELLSEMTLDEKIDQLLQ-LAAAFYSDKAEEKTGPMGDLGLTQENINNAGTTLG 59 pBgl MEKHMIETLLRQMTLKEKIGQLNQRLYGWEVYEKTNGKIMLTETFKKEVARFGSLGWIYG 60 Aphid --------MDYKFPKDFMFGTSTASYQIEGGWNEDGKGENIWDRLVHTSPEVIKDGTNGD 52 : ::. . :. : . * . GH3#2 VTGAQ------------------VTRKIQTDYLRKSRHKIPLLFMADIIYGYR----TVF 96 GH3#3 VTGAQ------------------VTRKIQTDYLRKSRHKIPLLFMADIIYGYR----TVF 96 GH3#1 VSGAK------------------EAIRVQKEYIENNRLNIPTILMADIIHGFR----TIF 97 pBgl VFRADPWSGRNQQTGLTTAESYELSLMIQTYLQEHTRLGIPAFLSEECPHGHQGLEATTF 120 Aphid IACDS-----------------------------YHKYKEDVAIIKDLNLKFYR-----F 78 : . : : : . * GH3#2 PIPLGLGATWNPALIQSAYQAAAQEARAAGAHVTYAPMVDLVRDARWGRCLESTGEDPLL 156 GH3#3 PIPLGLGATWNPALIQSAYQAAAQEARAAGAHVTYAPMVDLVRDARWGRCLESTGEDPLL 156 GH3#1 PIPLGLGSSWDLAAAEKMAEVSAKEAAVSGLHVTFSPMVDLVRDPRWGRVMESTGEDPYL 157 pBgl PVNFSVGSSWNPDLYQAAQTITAQEIRAKGAHVGLVSALDIARDPRWGRTEECFSEDPFL 180 Aphid SISWARIAPSGVMNSLEPKGIAYYNNLIN--ELIKNDIIPLVTMYHWDLPQYLQDLG--- 133 .: . :. . : : .: : :. :*. . . GH3#2 NADFAKAMVEGIQQEKGGTLLG-IAACVKHFAAYGASEGGRDYNTVDMSERKLRQDYLSG 215 GH3#3 NADFAKAMVEGIQQEKGGTLLG-IAACVKHFAAYGASEGGRDYNTVDMSERKLRQDYLSG 215 GH3#1 NSRFAEAFVKGYQGDDLRTDFNRVAACVKHFAAYGAAIGGRDYNTVNMSERQLRESYLPG 217 pBgl TSSFTKAAVRGLQGLKTTIEKQNVLAVLKHFAAQGAGMGGHNAGPVAIGDREFREIHLPP 240 Aphid --GWVNPIMSDYFKEYARVLFTYFGDRVKWWITFNEP--------IAVCKGYSIKAYAPN 183 :.:. : . . :* : : . : : . : : . GH3#2 YKAAVEAGCKLVMTSFNTYDGIPATANQFLIKQILREEWQFDGVVISDYAAVQELIPHGI 275 GH3#3 YKAAVEAGCKLVMTSFNTYDGIPATANQFLIKQILREEWQFDGVVISDYAAVQELIPHGI 275 GH3#1 YKAALDAGAKLVMTSFNTVDGIPATANRWLFRDVLREEFGFEGVVISDWAAIKEVIAHGA 277 pBgl MKAGIAAGALGCMAAYNDLDGVPCHANAYLLQEVLREESGFAGIVMADGCGLDRIADWLG 300 Aphid LNLKTTGHYLAGHTQLIAHG----KAYRLYEEMFKPTQNGKISISISGVFFMPKNAESDD 239
236
: . : . * . . : .: ::. : . GH3#2 ATDDREAAKLAIEATNDIDMKTRCYAKELRPLLESGAIDQRLIDDAVYHVLKLKKDLGLF 335 GH3#3 ATDDREAAKLAIEATNDIDMKTRCYAKELRPLLESGAIDQRLIDDAVYHVLKLKKDLGLF 335 GH3#1 AEDEKHAAELAIKAGVDIEMMTTCYTDNLKELIAEGTVEEALVDEAVLRILTLKNELGLF 337 pBgl SRS--QAAAKSLTSGVDVSLWDEVFP-VLEEAVLDGLIAETVIDEAVRRVLLLKEKLGLF 357 Aphid DIETAERANQFERGWFGHPVYKGDYPPIMKKWVDQKSKEEGLPWSKLP------------ 287 . . * . . : :. :. : . : : . : GH3#2 EDPFRGSSEEVEAQILLSEENRKLARKVASEAIVLLQNKQEVLPLTPKKEKILLVGPYGD 395 GH3#3 EDPFRGSSEEVEAQILLSEENRKLARKVASEAIVLLQNKQEVLPLTPKKEKILLVGPYGD 395 GH3#1 ENPYRGADEAAEAATVLSQEHREIARDIAKKSMVLLKN-EGVLPLQ-KTEKVAIVGPGAH 395 pBgl KEVTP------HVSLPDKEKARQASLKLAEESVVLLEN-NGILPLKKTRQKIAVIGPHVK 410 Aphid --------------------------KFTKDEIKLLKGTADFYALNHYSSRLVTFGSDPN 321 ..:.. : **:. . .* .:: .*. . GH3#2 NQ-AMIGLWAVHGKTEDVTTLKTALQNTVSEKYVHYEPGCPLLEDDSILGDFGYTASGNS 454 GH3#3 NQ-AMIGLWAVHGKTEDVTTLKTALQNTVSEKYVHYEPGCPLLEDDSILGDFGYTASGNS 454 GH3#1 SR-DLLGAWSWQGKQEEVVTLVAGAQSLGADLLIGQEP-------------FDYFAP--- 438 pBgl QLYHQLGDYTPFKEEAMCMTLWEGLTKLNTHQVDFAYEKGCEIANGTTAQRRRACQIAED 470 Aphid PN--------FNPDASYVTSVDEAWLKPNETPYIIPVPEG-------------------- 353 . :: . . GH3#2 SSAAQQDLWLKEALKAGTEADIILFAMG-EHSLQSGEAGSRT------------------ 495 GH3#3 SSAAQQDLWLKEALKAGTEADIILFAMG-EHSLQSGEAGSRTDLHLPAVQRAFIKKMTAL 513 GH3#1 SEAA-----IQEAIELVKEADKVVLALG-EQEWMSGEAASRSDIRLPQAQLSLVETLKEY 492 pBgl ADVILVTIGGSSARDFTTDFDKNGAALRGSQEMTSGENIDLATLDLPQCQLDLLFALKKR 530 Aphid ------------------------------------------------LRKLLIWLKNEY 365 GH3#2 ------------------------------------------------------------ GH3#3 GKKNILINFSGRPLVLKEETKQMDAILQAWFPGTEGAQAIVDILFGKVNPSGRLSMSFPE 573 GH3#1 NEQLIVTLYNGRPLDLQG-VDAAKAIVEAWFPGTEGGNALAQILWGEYNPSGRLSMSFPE 551 pBgl KKPLIGIVISGRPHCLAPLKEVFDGLLYAGYPGQYGGEAIARILFGETVPSGKLAVSIPD 590 Aphid GNPQLLITENG-----YGDDGQLDDFEKISYLKNYLNATLQAMYEDKCNVIGYTVWSLLD 420 GH3#2 ------------------------------------------------------------ GH3#3 DVGQLPLYYNHFNTGRPLNSKTHTGRFVSKYLDCSNEPLFPFGYGLSFGEASYHSLKLSD 633 GH3#1 TVGQVPVYYNVDNTGRPYESAPDE-KYVSKYLDVSNYAKYPFGFGLSYSPVAYSTVTLDQ 610 pBgl TVGQLPVCYNYRNT-----------AFQKDYLDQNGTPVYSFGYGLSYASFTCSAVSAEY 639 Aphid NF------------------------------------EWFYGYSIHFG----------- 433 GH3#2 ------------------------------------------------------------ GH3#3 STMN--ETLEAEITIRNNSAYSRLETVQLYIRDHVGSVVRPVKELKKYKKIPLSPYEEIT 691 GH3#1 PTMTKDQTVTASITVTNQGTAAVWETVQCYIRDLVGEVVRPVKELKGFKKIWLEAGESTT 670 pBgl AGEG----IIVSGTLENHSAVSGKEVIQCYLKEYTKAYVPRKKVLCGFQKVWVPNQGQVA 695 Aphid ---------LVKIDFNDPQRTRTKRESYTYFKNVVSTGKP-------------------- 464 GH3#2 -------------------------------------------------------- GH3#3 VLFTITKEDLFYYQKDLTFGVEPGLFTLFIGKNS-----AEGEAATFELL------ 736 GH3#1 VQFEITEELLRYVHSNQQASSDPGKFHIMIGGNS-----RDTQQTTLQLVR----- 716 pBgl FQLVIDEASVQQLAISLKDTASFCLEVETTGQQYRFVFQRSNPDRTWQVTQKGAKE 751 Aphid --------------------------------------------------------
C GH4 Aphid MDYKFPKDFMFGTSTASYQIEGGWNEDGKGENIWDRLVHTSPEVIKDGTNGDIACDSYHK 60
237
6pbg2 MSQKLKVVTIGGGSSYTPELLEGFIKRYHELPVSELWLVD---VEGGKAKLDIIFDLCQR 57 *. *: : * *: : :: *: : : : : : * . :: ** * :: Aphid YKEDVAIIKDLNLKFYRFSISWARIAPSGVMNSLEPKGIAYYNNLINELIKNDIIPLVTM 120 6pbg2 MIDNAGVPMKLYKTLDRR-------------EALKDADFVTTQLRVGQLPARELDERIPL 104 ::..: .* .: * ::*: .:. : :.:* .:: :.: Aphid YHWDLPQYLQDLGGWVN-----PIMSDYFKEYARVLFTYFGDRVKWWITFNEPIAVCKGY 175 6pbg2 SHGYLGQETNGAGGLFKGLRTIPVIFDIVKDVEELCPN------AWVINFTNPAGMVT-E 157 * * * :. ** .: *:: * .*: .: . * *.*.:* .: . Aphid SIKAYAPNLNLKTTGHYLAGHTQLIAHGKAYRLYEEMFKPTQNGKISISISGVFFMPKN- 234 6pbg2 AVYRHTGFKRFIGVCNIPIGMKMFIRDVLMLKDCDDLSIDLFGLNHMVFIKDVLVNGKSR 217 :: :: .: . : * . :* . : ::: . : : *..*:. *. Aphid -AESDDDIETAERANQFERGWFGHPVYKGDYPPIMKKWVDQKSKEEGLPWSKLPKFTKDE 293 6pbg2 FAELLDGVASGQLKASGVKNIFDLPFSEG----LIRSLNLLPCSYLLYYFKQKEMLAIEM 273 ** *.: :.: . :. *. *. :* :::. .. :.: :: : Aphid IKLLKGTADFYALNHYSSRLVTFGSDPNPNFNPDASYVTSVDEAWLKPNETPYIIPVPEG 353 6pbg2 GEYYKGGARAQVVQKVEKQLFELYKNPELKVKPKE--LEQRGGAYYSDAACEVINAIYND 331 : ** * .::: ..:*. : .:*: :.:*. : . . *: . * .: :. Aphid LRKLLIWLKNEYGNPQ------LLITENGYGDDGQLDDFEKISYLKNYLNATLQAMYEDK 407 6pbg2 KQAEHYVNIPHHGHIDNIPADWAVEMTCTLGRDG-ATPHPRITHFDDKVMGLIHTIKGFE 390 : .:*: : : * ** . :*:::.: : . :::: : Aphid CNVIGYTVWSLLDNFEWFYGYS-IHFGLVKIDFNDPQRTRTKRESYTYFKNVVSTGKP-- 464 6pbg2 IAASNAALSGEFNDVLLALNLSPLVHSDRDAELLAREMILAHEKWLPNFADCIAELKKAH 450 . . :: . :::. . * : .. . :: : ::.: . * : :: *
Figure 4.15 Alignments of putative bacterial GSL-degrading enzyme sequences with B. brassicae `Aphid' myrosinase. (A) Alignments of proteins from GH1 family. The catalytic residues, a general acid/base Glu (E) (yellow) and a nucleophile Glu (E) (blue) are highlighted. (B) Alignments of proteins from GH3 family show the conserved catalytic Asp (D) residue (green), but the other active residue is less readily identified and highly variable. (C) Alignment of a protein from GH4 family. The catalytic residues Tyr (Y) (yellow) and Arg (R) (blue) are highlighted. The assigned gene names are referred to Table 4.10. The symbols ":" means that conserved substitutions have been observed and "." means that semi-conserved substitutions are observed. Amino acid color codes are referred to Figure 4.3 (Larkin et al., 2007).
Multiple sequence alignments between the putative bacterial sulfatase SUL2 with snail
sulfatase show the consensus ‘CXPXR’ sulfatase signature as an active site near the N’terminus and
a conserved stretch of polar amino acid residues around the active site (Figure 4.16).
Snail MCKCLLVLIAIITACAVADQSSASAGTRQDAGQPNIVFVLADDFGFHDVG-YHGSEIHTP 59 SUL2 ------------------------------MKRPNFLFIMTDTQATNMVGCYSGKPLNTQ 30 :**::*:::* . : ** * *. ::* Snail TLDALSASGVRLEN-YYVQPICTPTRSQLMSGRYQIHTGLQHGIINSCQPNALPNDSPTL 118 SUL2 NIDSLAAEGIRFNSAYTCSPVCTPARAGLFTGIYANQSGPWTNNVAP------GKNISTM 84 .:*:*:*.*:*::. * .*:***:*: *::* * ::* . : . :: .*: Snail ADKLKESGYATHMVGKWHLG---FYKQEYLPWNRGFDTYFGYLNAAEDYFNHNVPWRQVR 175 SUL2 GRYFKDAGYHTCYIGKWHLDGHDYFGIGECPPEWDADYWFDGANYLSELTEKEISLWRNG 144 . :*::** * :*****. :: * : . * :*. * .: ::::. :
238
Snail YLDLRDNNGPVRNETGQYSAHLFTGKAIDVVQSHN-TSKPLFLYLAYQSVHAPLEVPEKY 234 SUL2 LNSVEDLQANHIDET-FTWAHRISNRAVDFLQQPARADEPFLMVVSYDEPHHPFTCPVEY 203 .:.* :. :** ** ::.:*:*.:*. :.:*::: ::*:. * *: * :* Snail EHKYR----NITDKNRRTFAGMVSALDEGVANLTQALKDKGLWNNTVLIFSTDNGGQIHA 290 SUL2 LEKYTDFYYELGEKAEDDLANKPEHHRLWAQAMPSPVGDDGLYHHPLYFACNDFVDDQIG 263 .** :: :* . :*. . . :...: *.**:::.: : ..* .: . Snail GGNNYPLRGWKASLWEGGFHGVGFVSGGALKRSGAVSKGLIHVSDWFPTLVTLAGGNLNG 350 SUL2 RVINALTPEQRENTWVIYTSDHGEMMG-AHKLISKGAAMYDDITRIPLIIRSPQGERRQV 322 * : . * . * : * * * . : .:: : : * . : Snail TKPLDGFNQWDTISNETPSPREILLHNIDILYPQ--KGVPLYSNTWDTRVRAAIRVGDYK 408 SUL2 DTPVSHIDLLPTMMALADIEKPEILPGENILAVKEPRGVLVEFNRYEIEHDSFGGFIPVR 382 .*:. :: *: : : :* . :** : :** : * :: . : . : Snail LITGDPGNGSWVPPPDGHLY---FVPEIQESAAKNVWLFNITADPNEHNDLSSEKPLEVL 465 SUL2 CWVTDDFKLVLNLFTSDELYDRRNDPNEMHNLIDDIHFADVRSKMHDALLDYMDKIRDPF 442 . * : ....** *: .. .:: : :: :. :: :* : : Snail RLLQILVQFNNTAVPPRYP-----APDPRCDPALHGDVWGPWE------------ 503 SUL2 RSYQWNLRPWRKDAQPRWMGAFRPRPQDGYSPVVRDYDTGLPTQGVKVEEKKQKF 497 * * :: .. . **: *: .*.::. * Figure 4.16 Alignments of a putative bacterial sulfatase protein sequence with H. pomatia`Snail' sulfatase. The catalytic sulfatase signatures ‘CXPXR’ (yellow) at N’ terminus are highlighted. The active sites containing a stretch of polar residues (blue) are highlighted. The assigned gene names are referred to Table 4.10. The symbols "*" means that the residues or nucleotides in that column are identical in all sequences in the alignment, ":" means that conserved substitutions have been observed and "." means that semi-conserved substitutions are observed. Amino acid color codes are referred to Figure 4.3 (Larkin et al., 2007).
A phylogenetic tree for bacterial putative myrosinases and sulfatases was also
constructed (Figure 4.17). It shows that ‘Aphid’ myrosinase is more closely related to bacterial
bgl, GH1 and 6pbg1 which all come from the same GH1 family. Snail sulfatase is more closely
related to bacterial SUL2 than SUL1.
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Figure 4.17 Phylogenetic tree for bacterial putative myrosinases and sulfatases. ‘Aphid’ refers to aphid myrosinase from B. brassicae, ‘Snail’ refers to snail sulfatase from H. pomatia, and the rest refers to Table 4.10. This was constructed using the program ClustalW2 (Larkin et al., 2007). 4.3.2 Cloning of putative bacterial GSL-degrading enzymes/sulfatases
Ten candidate genes (Table 4.10) were cloned from genomic DNA of either E. coli
O83:H1 NRG 857C or E. casseliflavus NCCP-53 using the designed primers flanking the gene
regions of interest. The PCR gene products were analyzed by agarose gel electrophoresis, and
the expected sizes of the product bands from all ten genes were observed (Figure 4.18).
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Figure 4.18 Agarose gel electrophoresis of genomic PCR experiments: Lane M – 10k bp ladder (BioLabs, UK). Single PCR fragments were amplified with corresponding primers (Table 4.1) using genomic DNAs from E. casseliflavus NCCP-53 and E. coli O83:H1 NRG 857C; Lane bgl: expected length of 1470 bp; Lane GH1: expected length of 1437 bp; Lane GH3#2: expected length of 1488 bp; Lane 6pbg1: expected length of 1407 bp; Lane GH3#3: expected length of 2151 bp; Lane GH3#1: expected length of 2211 bp; Lane pBgl: expected length of 2256 bp; Lane SUL1: expected length of 2124 bp; Lane SUL1: expected length of 1494 bp; Lane 6pbg2: expected length of 1353 bp.
Each PCR product was ligated to a pET28b+ expression vector, and the resulting gene
construct was transformed into DH5α competent cells. The transformant colonies containing
the desire gene construct grown on the kanamycin selection plates were randomly selected for
colony PCR experiments using the vector forward primer and the gene-specific reverse primer.
The colony PCR results showed that there were the correct sizes of gene inserts in the vectors
(Figure 4.19).
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Figure 4.19 Agarose gel electrophoresis of colony PCR experiments: Lane M – 10k bp ladder (BioLabs, UK). Single PCR fragments were amplified with corresponding primers (Table 4.1) from two selected colonies habouring potential gene inserts; Lanes bgl: expected length of 1,470 bp; Lanes GH3#1: expected length of 1437 bp; Lanes GH3#2: expected length of 1488 bp; Lanes 6pbg1: expected length of 1407 bp; Lanes GH3#3: expected length of 2151 bp; Lanes GH3#1: expected length of 2211 bp; Lanes pBgl: expected length of 2256 bp; Lanes SUL1: expected length of 2124 bp; Lanes SUL1: expected length of 1494 bp; Lanes 6pbg2: expected length of 1353 bp.
These positive colonies were then grown in LB broth containing kanamycin overnight,
and their plasmids were isolated for restriction enzyme digestion experiments. No transformant
colonies for the SUL1 gene were obtained after several attempts, and thus the study of this
gene was discontinued. The restriction pattern of corresponding restriction enzyme confirmed
the presence of the gene inserts and pET28b+ expression vectors (Figure 4.20), showing three
genes as examples before the plasmids were sent to GATC company (UK) for gene sequencing,
and it was confirmed that all the genes had correct sequences (Appendix II).
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Figure 4.20 Agarose gel electrophoresis of restriction enzyme digestion experiments: Lane M – 10k bp ladder (BioLabs, UK); Lane 1: Uncut circular pET28b(+) vector with 5369 bp of size; Lane 2: Cut linearized pET28b(+) vector with the expected length of 5369 bp; Lane 3: Uncut pET28b-bgl plasmid; Lane 4: Uncut pET28b-GH1 plasmid; Lane 5: Uncut pET28b-GH3#2 plasmid; Lane 6: Cut pET28b-bgl plasmid by NdeI and Sac I enzymes with a linearized pET28b(+) fragment of 5369 bp and a bgl gene insert of 1470 bp ; Lane 7: Cut pET28b-GH1 plasmid by NdeI and Sac I enzymes with a linearized pET28b(+) fragment of 5369 bp and a GH1 gene insert of 1437 bp; Lane 8: Cut pET28b-GH3#2 plasmid by NdeI and Sac I enzymes with a linearized pET28b(+) fragment of 5369 bp and a GH3#2 gene insert of 1488 bp.
4.3.3 Recombinant protein expressions by IPTG induction
To express the desired genes recombinantly, the recombinant plasmids were
transformed into E. coli BL21(DE3) host cells for recombinant protein expression. SDS-PAGE
analysis indicated that large amounts of protein from each gene of interest is expressed in the
cell supernatant after induction by 0.5 mM IPTG for 6 h at 25°C under aerobic conditions (Figure
4.21) with the band size similar to the predicted molecular weight. The negative control, non-
recombinant BL21(DE3) culture was induced by IPTG in the same manner as other recombinant
cultures. However, there was no protein band of interest expressed in this control sample as
expected. These cell-free extracts were desalted to be ready for the following assays; GOD-
PERID assay, β-O-glucosidase activity assay and arylsulfatase activity assay. Protein
concentrations of cell-free extratcs were determined by Bradford’s method (Chapter 2, section
2.2.20).
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Figure 4.21 Recombinant protein expressions on SDS-PAGE. Recombinant cultures were aerobically induced by 0.5 mM IPTG for 6 h at 25°C once OD600nm reached 0.6. Cell-free extracts of recombinant enzymes were analyzed on SDS-PAGE. (A) Recombinant proteins from E. casseliflavus NCCP-53 with the expected sizes were shown in boxes; bgl (56 kDa), GH1 (55 kDa), GH3#2 (54 kDa), 6pbg1 (54 kDa), GH3#3 (79 kDa), pBgl (83 kDa) and GH3#1 (81 kDa). Lane M, Low Range unstained marker (Sigma-Aldrich); Lane C, Control non-recombinant cells. (B) Recombinant proteins from E. coli O83:H1 NRG 857C with the expected sizes were shown in red boxes; SUL2 (57 kDa) and 6pbg2 (50 kDa). Lane M, PageRuler pre-stained protein ladders (Thermoscientific, UK); Lane C, Control sample with proteins from non-recombinant BL21(DE3) cells. Each lane was loaded with 20 µg protein content. 4.3.4 Enzyme activity assays
The desalted cell-free extracts containing proteins of interest from the previous section
were analyzed for the myrosinase enzyme activity using the GOD-PERID assay, the β-O-
glucosidase enzyme activity and the arylsulfatase activity as follows.
4.3.4.1 Myrosinase activity using GOD-PERID assay
No myrosinase activity was detected in any of cell-free extracts of the recombinant
enzymes (Figure 4.22). AITC or/and ANIT were not detected by GC-MS analysis either. The
negative control containing cell-free extracts from BL21 (DE3) cells without recombinant
protein expression showed negative result. The positive control (with S. alba myrosinase)
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showed development of green-coloured product from sinigrin substrate. This is an indication of
myrosinase activity with specific activity of 28.3 ± 0.12 μmol/min/mg. This positive result from
the positive control proves the validity of GOD-PERID assay for testing myrosinase activity.
Figure 4.22 Myrosinase activity using GOD-PERID assay. Cell-free extracts of each recombinant protein (~ 200 µg) was aerobically incubated with 0.5 mM sinigrin in 0.1 M citate phosphate buffer pH 7.0 at 37°C for 30 min and was boiled for 5 min before 1 mL GOD-PERID reagent was added. The mixture was aerobically incubated at 37°C for 15 min. BL21 is a negative control, cell-free extract of BL21 without recombinant enzyme; GH1 is glycosyl hydrolase 1; GH3#3 is glycosyl hydrolase family 3; bgl is β-glucosidase; C is a positive control containing purified S. alba myrosinase (5 μg). From this result, it was hypothesized that the current pH 7.0 might not be optimal for
the myrosinase to function. Therefore, different pHs of 4.0, 5.0, 6.0 and 8.0 of 0.1 M citrate
phosphate buffer and also different buffers such as 0.1 M Tris-Cl, 0.1 M PBS, and 0.1 M sodium
phosphate buffer were used with the same sinigrin concentration under the same experimental
conditions. In spite of several trials, green product was still not detected in any recombinant
enzyme or in any buffer conditions (data not shown). Since most of the recombinant proteins
come from GH family which are supposed to hydrolyze β-O-glucosides such as cellobiose, salicin,
trehalose and methyl β-D-glucopyranoside, GOD-PERID assay was carried out with these
substrates to determine whether any of the recombinant enzymes can hydrolyze them. It was
found that GH1, GH3#1, bgl and GH3#3 enzymes all were able to hydrolyze cellobiose and
trehalose with GH3#3 having the highest specific activity (Figure 4.23A and 4.23C). In contrast,
only GH3#3 was able to hydrolyze salicin and methyl β-D-glucopyranoside (Figure 4.23B and
4.23D). The specific activity of GH3#3 on substrates in descending order is cellobiose >
trehalose > salicin > methyl β-D-glucopyranoside. The negative controls (cell-free extracts of
BL21(DE3) cells without any recombinant protein expression) showed no activity on most
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substrates except for trehalose. These results indicate that recombinant enzymes exhibit β-O-
glucosidase or glycosyl hydrolase activity upon natural β-O-glucoside substrates. This also
proves the validity of GOD-PERID assay.
(A) Apparent specific activity (μmol/min/mg) (B) Apparent specific activity (μmol/min/mg)
BL21 GH1 bgl GH3#1 GH3#3 GH1 bgl GH3#1 GH3#3
ND 1.43 0.87 1.47 6.48
ND ND ND 0.79
± 0.12 ± 0.06 ± 0.10 ± 0.11 ± 0.05
(C) Apparent specific activity (μmol/min/mg) (D) Apparent specific activity (μmol/min/mg) BL21 GH1 bgl GH3#1 GH3#3 GH1 bgl GH3#1 GH3#3 2.02 2.67 3.7 3.41 3.59
ND ND ND 0.09
± 0.07 ± 0.12 ± 0.09 ± 0.13 ± 0.08 ± 0.02 Figure 4.23 β-O-glucosidase activity using GOD-PERID assay. Cell-free extracts of each recombinant protein (~ 20 µg) was aerobically incubated with either 1 mM of (A) cellobiose, (B) salicin, (C) trehalose or (D) methyl β-D-glucopyranoside in 0.1 M citate phosphate buffer pH 7.0 at 37°C for 30 min and was boiled for 5 min before 1 mL GOD-PERID reagent was added. The mixture was then incubated at 37°C for 15 min. BL21 is a negative control, supernatant without recombinant enzyme; GH1 is glycosyl hydrolase family 1; bgl is β-glucosidase; GH3#1 is glycosyl hydrolase family 3; GH3#3 is glycosyl hydrolase family 3. Apparent specific activity of each enzyme was determined since each enzyme was not purified. Data of specific activity of each enzyme on each substrate was shown below the pictures. Values are means ± SD of triplicates. ND, Not detected.
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4.3.4.2 β-O-glucosidase activity assay
Since GOD-PERID assay only produced positive results when β-O-glucosides were used
as substrates, it was thought that these enzymes may not exhibit β-thioglucosidase (i.e.
myrosinase) activity to hydrolyze GSLs, but they may only have β-O-glucosidase activity.
Therefore, another experiment to reassure the existence of β-O-glucosidase activity of these
enzymes was carried out using p-nitrophenyl-β-D-glucopyranoside (pNPG) as a synthetic
substrate in 0.1 M citrate phosphate buffer pH 7. If β-O-glucosidase activity is present, the
breakdown of pNPG would produce D-glucose and a yellow-coloured p-nitrophenol (pNP)
product that can be determined spectrophotometrically at 400nm. It is important to note that
plant myrosinase from GH1 can also hydrolyze pNPG in addition to GSLs. It was found that
three enzymes GH1, bgl and GH3#3 produced yellow-coloured products suggesting β-O-
glucosidase activity of these enzymes on pNPG substrate (Figure 4.24). Since the GH3#3 enzyme
showed the highest specific activity on all β-O-glucosides tested, this enzyme was to be studied
in further details in Chapter 5.
Apparent specific activity (µmol/min/mg)
BL21 bgl GH1 GH3#2 6pbg1 GH3#3 GH3#1 pBgl 6pbg2
ND ND 0.43 ± 0.11 ND ND 1.54 ± 0.06 0.39 ± 0.08 ND ND
Figure 4.24 β-O-glucosidase activity assay. Cell-free extracts of the recombinant enzymes (~ 20 µg) were aerobically incubated with 1 mM pNPG in 1 mL of 0.1 M citate phosphate buffer pH 7.0 at 37°C for 5 min after which 5 mL of 0.1 M NaOH was added to the mixture. BL21 is a negative control, supernatant without recombinant enzyme; bgl is β-glucosidase; GH1 is glycosyl hydrolase family 1; GH3#2 is glycosyl
hydrolase family 3; 6pbg1 is 6-phospho- β-galactosidase; GH3#3 is glycosyl hydrolase family 3; GH3#1 is
glycosyl hydrolase family 3; pBgl is periplasmic β-glucosidase; 6pbg2 is 6-phospho- β-glucosidase. Apparent specific activity of each enzyme was determined since each enzyme was not purified. Data on
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specific activity of each enzyme on each substrate was shown below the pictures. Values are means ± SD of triplicates. ND, Not detected. 4.3.4.3 Arylsulfatase activity assay
To determine whether cell-free extracts of the recombinant SUL2 enzyme has
arylsulfatase activity, this enzyme was aerobically incubated with a synthetic substrate p-
nitrocatechol sulphate (pNCS). It was found that the recombinant SUL2 produced a red/orange-
coloured product of p-nitrocatechol (pNC) suggesting arylsulfatase activity that desulfated pNCS
substrate. The positive control containing the purified sulfatase from H. pomatia resulted in a
very strong red coloured pNC product indicating the validity of the assay (Figure 4.25). The
recombinant SUL2 enzyme with arylsulfatase activity was studied in further details in Chapter 5.
Specific activity (μmol/min/mg)
HP SUL SUL2 BL21
20.8 ± 0.18 1.21 ± 0.07* ND
Figure 4.25 Arylsulfatase activity assay at pH 7.0. Cell-free extracts of the recombinant SUL2 protein (~ 20 µg) or the purified H. pomatia sulfatase (~ 20 µg) was aerobically incubated with 1 mM pNCS substrate in 1 mL of 0.05 M sodium acetate buffer pH 5.0 at 37°C for 5 min after which 5 mL of 0.1 M NaOH was added to the mixture. HP SUL is a purified H. pomatia sulfatase positive control; SUL2 is a sulfatase from E. coli O83:H1 NRG 857C; BL21 is a negative control, cell-free extract of BL21 without recombinant enzyme. Data on specific activity of each enzyme was shown below the pictures. Values are means ± SD of triplicates. ND, not detected. *The value is apparent specific activity of SUL2 enzyme since this enzyme was not purified.
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4.4 Discussion
In addition to forward genetics approach (Chapter 3), a reverse genetics approach was
used to identify and express the bacterial putative genes for myrosinase/arylsulfatase activity in
this chapter. Ten genes from the two bacteria were cloned and expressed. No GSL-degrading
activity was detected in any recombinant enzymes tested. These enzymes may be inactive in
the pH buffers used or GSL substrate may need to be modified e.g. phosphorylation of the 6-OH
group before being hydrolyzed by these enzymes and only occur in intact cells where the
integrity of transport/phosphorylation system is intact. The previous study has shown that 6-
phosphoryl-β-D-glucopyranosyl hydrolase (P-β-glucosidase, EC 3.2.1.86) purified from
Fusobacterium mortiferum hydrolyzed several P-β-glucosides, including the isomeric
disaccharide phosphates cellobiose-6-phosphate, gentiobiose-6-phosphate, sophorose-6-
phosphate, and laminaribiose-6-phosphate, to yield glucose-6-phosphate and appropriate
aglycons (Thompson, 2002). These substrates had to be phosphorylated by a β-glucoside kinase
(BglK) of K. pneumonia bacteria prior to the hydrolysis by 6-P-β-glucosidases (Thompson et al.,
1997). Since GSLs are β-glucosides, it is thought that they may need to be phosphorylated by β-
glucoside kinase prior to being hydrolyzed by myrosinase which recognizes the phosphorylation
on the GSL structure. However, this hypothesis still remains untested.
Our results showed that crude extracts of some recombinant enzymes showed β-O-
glucosidase activity on some β-O-glucosides, but not GSL. This indicates that these recombinant
enzymes are at least active upon these substrates with different specific activities. Information
on β-O-glucosidases is currently limited to relatively few species of bacteria from the human
colonic ecosystem (Dabek et al., 2008). With this work, new data on β-O-glucosidases from E.
casseliflavus NCCP-53 has been provided. Among broad substrate specificity β-glucosidases
reported to date, a number of β-glucosidases have higher activity for aryl-glucosides e.g. methyl
β-D-glucopyranoside and pNPG than cellobiose (González-Pombo et al., 2008; Matsui et al.,
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2000; Parry et al., 2001). These enzymes have only 20–50% enzyme activity against cellobiose,
comparing to that for the pNPG. Some zymes have only 20–50% enzyme activity against
cellobiose, comparin(Hashimoto et al., 1998; Marques et al., 2003). In contrast, the
recombinant GH3#1, GH1, GH3#3 and bgl enzymes from E. casseliflavus NCCP-53 in this study
have higher activity on cellobiose than aryl-glucosides including methyl ose than aryl-
glucosidespNPG. Interestingly, all crude extracts of these recombinant enzymes and also the
extracts from the control BL21(DE3) without recombinant enzyme expression exhibited activity
for trehalose containing an α,α-1,1-glucosidic bond indicating that BL21(DE3) host expressed
endogeneous trehalase enzyme to hydrolyze trehalose. Therefore, the recombinant enzymes
need to be purified in order to determine whether they can hydrolyze trehalose. The
hydrolyzing activities of crude extracts of the recombinant GH3#1, GH1, and GH3#3 enzymes
were observed for substrates containing ified in order to deterpNPG and cellobiose. However,
no activity was observed for salicin and and methyl β-D-glucopyranoside (except for GH3#3).
The basis of the vast diversity in biological function of β-glucosidases from different GH
familes is the substrate aglycone specificity differences that determine their natural substrates
(Ketudat Cairns & Esen, 2010). There is also a difference in substrate specificity within the GH1
and GH3 groups (Ketudat Cairns & Esen, 2010). Thus, different members from different GH
families and even members in the same GH family can have different activity towards the same
substrate. As demonstrated in the results, the β-O-glucosidase activity towards pNPG was
detected from GH1, GH3#3 and GH3#1 whereas there was no activity from other members of
the same families. In addition, arylsulfatase activity towards pNCS substrate was detected in the
recombinant SUL2 enzyme from E. coli O83:H1 NRG 857C. Thus far, bacterial GSL-degrading
activity has not been found despite several experiments including cell-free extract experiment,
native activity gel analysis (Chapter 2), forward and reverse proteomics approaches (Chapter 3
and 4, respectively) were carried out. It was speculated that bacterial GSL-degrading enzyme
system may be more complicated than previously thought. Since 1974 when the first bacterial
myrosinase produced by Enterobacter cloacae was purified (Tani et al., 1974), other researchers
had no success in repeating it.
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To summarize, βoO-glucosidase activity with highest specific activity was found in the
recombinant GH3#3 enzyme, and arylsulfatase activity in the recombinant SUL2 enzyme. These
two enzymes may be of importance in GSL metabolism in human gut bacteria. Thus, these were
characterized in further details with the GH3#3 enzyme to be referred as GH3 in the next
chapter.
Chapter 5: Characterization of the recombinant SUL2 enzyme from E. coli O83:H1 NRG 857C and the recombinant GH3 enzyme from E. casseliflavus NCCP-53 5.1 Introduction
In chapter 4, β-O-glucosidase activity from the recombinant GH3 enzyme derived from E.
casseliflavus NCCP-53 and arylsulfatase activity from the recombinant SUL2 enzyme derived
from E. coli O83:H1 NRG 857C were detected in in vitro activity assays. These two enzymes may
be of importance in GSL metabolism in human gut bacteria. Based on the results from previous
chapters, the hypotheses of this chapter are shown in Figure 5.1.
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Figure 5.1 Hypothese of this chapter. See main text for more details.
The recombinant GH3 enzyme may be involved in the hydrolysis of DS-GSLs and the
production of corresponding NITs as detected during bacterial fermentations (Chapter 2,
section 2.3.5). The recombinant SUL2 enzyme may be involved in desulfonation of intact GSLs
to produce corresponding DS-GSLs. By combining these two recombinant enzymes together in
the same reaction tube, intact GSLs may be desulfated to produce DS-GSLs and thus NIT
products may be generated. Thus, these two recombinant enzymes GH3 and SUL2 were
characterized in further details in this chapter.
5.1.1 Sulfatases in nature
Sulfatases represent a large protein family that is involved in heterogeneous processes
in humans ranging from degradation of macromolecules to hormone biosynthesis and
modulation of developmental cell signaling (Hanson et al., 2004; Hopwood & Ballabio, 2001;
Kim & Singh, 2009; Parenti et al., 1997). Sulfatases catalyze the hydrolysis of sulfate esters (CO–
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S) as well as sulfamates (CN–S) (Figure 5.2, reactions (1) and (2), respectively) from different
sulfated substrates such as steroids, carbohydrates, proteoglycans and glycolipids.
Figure 5.2 Sulfatase reactions. Sulfatases catalyze the hydrolysis of sulfate esters such as (1) O-sulfates and (2) N-sulfates.
Their biological significance in humans is particularly emphasized by their association
with several inherited diseases such as mucopolysaccharidoses (Franco et al., 1995),
metachromatic leukodystrophy (von Figura et al., 1999), X-linked ichthyosis, chondrodysplasia
punctata (Selmer et al., 2004), and the rare multiple sulfatase deficiency syndrome (Parenti et
al., 1997; Schmidt et al., 1995). In prokaryotes, their function has been restrained to sulfate
supply. Nevertheless, sulfatases have been recently implicated in pathogenesis (Mougous et al.,
2002) notably in E. coli (Hoffman et al., 2000; Xie et al., 2004).
Sulfatases belong to at least three mechanistically distinct groups, namely the Fe (II) α-
ketoglutarate-dependent dioxygenases (Müller et al., 2004), the recently identified group of Zn-
dependent alkylsulfatase (Hagelueken et al., 2006) and the broad family of arylsulfatases
(Hanson et al., 2004). This latter family of enzymes, termed “sulfatases” in this chapter, is
certainly the most widespread among bacteria with some of them possessing more than one
hundred sulfatase genes in their genomes (Glöckner et al., 2003). The sulfatase activity on a
broad diversity of substrates leads to their classification by the International Union of
Biochemistry and Molecular Biology (IUBMB) into 17 classes (from EC 3.1.6.1 to EC 3.1.6.17).
Despite this apparent heterogeneity, sulfatases are a conserved family of enzymes sharing the
following features: (i) they have a similar size, ranging from 500 to 800 amino acids, (ii) they are
extensively glycosylated, (iii) they share significant sequence homology ranging from 20% to
60% over their entire length, and in particular in the N-terminal region carrying motif that is
unique for this class of enzymes, and (iv) the most distinguished characteristic of sulfatases is a
unique co- or post-translational modification that they undergo to produce a Cα-formylglycine
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(FGly) residue in their active site (Clarke, 2010; Franco et al., 1995; Hanson et al., 2004; Schmidt
et al., 1995). This residue is derived from the conversion of a cysteine (in prokaryotes and
eukaryotes) or a serine (in prokaryotes), hence defining two classes of sulfatases, the “Cys-type”
sulfatases and the “Ser-type” (Dierks et al., 1998b; Schmidt et al., 1995). One of two different
enzymes, formylglycine-generating enzyme (FGE) (Cosma et al., 2003; Dierks et al., 2003) and
AtsB (Szameit et al., 1999), is responsible for the unique modification and conversion of Cys or
Ser to FGly, respectively. Although these systems are highly divergent, they recognize the same
consensus motif “(C/S)XPXR” also known as the “sulfatase signature”. This consensus sequence
is crucial for the unique conversion of Cys or Ser to FGly and the correct conformation of the
catalytic site of sulfatases. This consensus sequence is conserved across all known members of
the sulfatase family (Dierks et al., 1999; Dierks et al., 1997; Sardiello, 2005).
Comparative analysis of the crystal structures of one bacterial and three human
sulfatases (Boltes et al., 2001; Bond et al., 1997; Hernandez-Guzman et al., 2003; Lukatela et al.,
1998) showed a highly similarity in three-dimensional structure with a superimposable core
region that constitutes the active site of the enzymes (Boltes et al., 2001; Hopwood & Ballabio,
2001). Crystallographic studies revealed the structures of the active sites of sulfatases which
contain a divalent metal ion located within the substrate-binding pocket and a highly conserved
Cys residue, which is the target of the posttranslational modification shared by all sulfatases
and required for enzymatic activity (Fey et al., 2001). Sulfatases are found in most species from
bacteria to eukaryotes, but some lower eukaryotes and most plants lack sulfatases. The
significant sequence conservation among different species strongly suggests that sulfatases are
members of an evolutionary conserved gene family sharing a common ancestor.
5.1.2 Bacterial sulfatases
Arylsulfatase activity has been identified in several species of enterobacteria, aquatic
bacteria, pathogenic bacteria, extremophilic bacteria, and soil bacteria. Most bacterial
arylsulfatase are upregulated during sulfur starvation indicating the role in scavenging
(Dodgson et al., 1982; Kertesz, 2000). Although their preferred substrates are unknown, it is
thought they may be sulfated carbohydrates (Hanson et al., 2004). To date, only a handful of
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bacterial sulfatases with different properties have been charcterized. For example, an
arylsulfatase (EC 3.1.6.1) extracted from Pseudomonas aeruginosa PAO1 shows maximal
activity at 57°C and pH 8.9, and a Km of 105 μM for pNCS (Beil et al., 2005).
The most thoroughly characterized bacterial sulfatase by crystal structure determined at
1.3 Å came from Pseudomonas aeruginosa (PARS) (Boltes et al., 2001). The folding and active
site region of PAS are strikingly similar to those of the known human sulfatases HARSA and
HARSB revealing a nearly spherical globular monomer with mixed α/β topology, which is
divided into two domains (Figure 5.3).
Figure 5.3 Crystal structures of Pseudomonas aeruginosa arylsulfatase (PARS). (A) Structure of PARS, characterized by two subdomains with mixed α/β topology. (B) Same structure of PARS, rotated 90°; the
strands of the large β-sheet within the N-terminal domain (numbered 1–10) and the small β-sheet in the
C-terminal domain (labeled a–d) are visible. Red cylinders: α-helices, yellow arrows: β-sheets. This picture was taken from Hanson et al., (2004).
The larger, N-terminal domain consists of α-helices surrounding a large mixed β-sheet,
which consists of 10 strands in PARS structure. The smaller, C-terminal domain contains a four-
stranded antiparallel β-sheet tightly packed against a long, solvent-exposed C-terminal α-helix.
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As is typical for the α/β family of enzymes (Branden, 1980), the active-site cavity is nestled at
the C-terminal end of the large β-sheet, with the FGly residue located at the bottom of a
narrow cleft lined with a stretch of highly interconnected polar residues and a divalent metal
cation unambiguously characterized as Ca2+ by the geometry of its coordination sphere (Boltes
et al., 2001). The catalytic N-terminal domain of sulfatases shows a high degree of structural
similarity to that of the alkaline phosphatases but differs dramatically in sequence (Sowadski et
al., 1985). Based on the structural data, a mechanism for sulfate ester cleavage of PARS has
been proposed (Figure 5.4). This involves a nucleophilic attack from an aldehyde hydrate of
FGly residue as the functional group on the sulfur atom in the sulfate ester substrate. The
alcohol is eliminated following by the formation of a reaction intermediate containing penta-
coordinated sulfur. Subsequent elimination of the sulfate from intermolecular rearrangement
of the intermediate regenerates the aldehyde, which is again hydrated. The Ca2+ ion is involved
in stabilizing the charge and anchoring the substrate during catalysis (Boltes et al., 2001).
Figure 5.4 Proposed mechanistic scheme for the hydrolysis of sulfate ester by the active-site aldehyde FGly of PARS. A transesterification–elimination mechanism was presented for hydrated aldehyde group present in the crystal structure of PARS. This picture was taken from Hanson et al., (2004). See main texts for details.
At this writing, no crystal structures of sulfatases bound to their natural substrates have
been solved, leaving the residues that play a role in substrate specificity largely unknown. It was
thought that the recognition of natural substrates occurs outside the narrow cleft containing
the conserved active-site residues. In general, the C-terminal region of sulfatases bears the
highest structural diversity and is likely to be responsible for the variation in substrate
specificity (Hanson et al., 2004; Ghosh, 2005).
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The properties of snail and bacterial sulfatases are summarized in Table 5.1.
Table 5.1 Properties of snail and bacterial sulfatases
Helix pomatia (snail) arylsulfatase
EC 3.1.6.1 – arylsulfatase
Reaction type: hydrolysis of sulfuric ester
Reaction: 4-nitrophenyl sulfate + H2O = 4-nitrophenol + sulfate (Roy, 1987)
Sinigrin + H2O = Desulfo-sinigrin + sulfate (Roy, 1987)
Activator: Cd2+ (Tokheim et al., 2005)
Inhibitor: Cu2+/SO42- (Tokheim et al., 2005; Roy, 1987)
pH optimum: 7.4 (Stawoska et al., 2010)
Temperature optimum: 30˚C (Stawoska et al., 2010)
Molecular weight: monomer, 1 * 66 kDa on SDS-PAGE (Roy, 1987)
Km: 1.2 mM for 4-Nitrophenyl sulfate at pH 7.1, at 30°C (Stawoska et al., 2010)
Pseudomonas aeruginosa (bacterium) arylsulfatase
EC 3.1.6.1 – arylsulfatase
Reaction type: hydrolysis of sulfuric ester
Reaction: 4-nitrophenyl sulfate + H2O = 4-nitrophenol + sulfate (Beil et al., 1995)
4-nitrocatechol sulfate + H2O = 4-nitrocatechol + sulfate (Beil et al., 1995)
4-nitrophenyl phosphate + H2O = 4-nitrophenol + phosphate (Olguin et al., 2008)
Activator: phosphate, sulphate activate hydrolysis of 4-nitrophenyl sulfate (Delisle & Milazzo, 1972)
pH optimum: 8.4 (hydrolysis of 4-nitrophenyl sulfate) (Delisle & Milazzo, 1972)
Temperature optimum: 57˚C (Beil et al., 2005)
pH range: 7.5 and 10.2 (Beil et al., 1995)
Temperature range: 40°C and 65°C (Beil et al., 1995)
Molecular weight: monomer, 1 * 57 kDa on SDS-PAGE (Beil et al., 1995)
Km: 0.55 mM for 2-methyl-4-nitrophenyl sulfate at pH 8.9, at 30°C (Hanson et al., 2006)
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0.105 mM for 4-nitrocatechol sulfate (Beil et al., 1995)
0.042 mM for 4-nitrophenyl sulfate at pH 8.9, at 30°C (Hanson et al., 2006)
5.1.3 The GH1 myrosinases
The plant myrosinase is a dimer with subunits of 60-70 kDa each (Björkman & Janson,
1972) linked by a zinc atom and has a characteristic (on,)8-barrel structure (Figure 5.5) in
common with GH1 enzymes which act through a mechanism that gives retention of the
anomeric configuration. The difference between plant myrosinases and β-O-glucosidases is
located at the level of the active site.
Figure 5.5 The overall structure of plant myrosinase. Plant myrosinase exists as a dimer held together by a zinc (green) atom, fluoroglucose (yellow) and carbohydrate (sticks). This picture was taken from Burmeister et al., (2000).
What makes plant myrosinases differ from plant β-O-glucosidases is that the catalytic
acids differ from together by a zinc (green) atom, fluoroglucose (yellow) and carbohydrate
(sticks). This picture was taken from Burmeister plant myrosinases and β -
000220000</publication_date><number>5</number><doi>10d by a correctly positioned water
258
molecule or by an activation of a water molecule by an ascorbate molecule acting as a catalytic
base entering the active site after departure of the aglycon (Burmeister et al., 2000). The
mechanism of the plant myrosinase is shown in Figure 5.6.
Figure 5.6 The ascorbate activated catalysis of GSL hydrolysis by plant myrosinase.
Interestingly an insect myrosinase has been purified and an X-ray structural
determination carried out (Husebye et al., 2005; Jones et al., 2001; Jones et al., 2002). In
common with the plant myrosinase the aphid enzyme has the characteristic (β/α)8-barrel
structure (Figure 5.7).
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Figure 5.7 The structure of aphid myrosinase showing the dimer. The two catalytic glutamic acid residues are shown in red (reproduced from Husebye et al., 2005).
Unlike the plant myrosinase, the aphid myrosinase is not activated by ascorbate and is
more like a β-O-glucosidase than a plant myrosinase (Husebye et al., 2005). Similar to in plant β
-O-glucosidases, aphid myrosinase has two catalytic glutamic acid residues. The only residue
specific for aphid myrosinase in proximity of the glycosidic linkage is Tyr180 which may have a
catalytic role (Husebye et al., 2005). The aglycone binding site is different from plant
myrosinase, whereas due to the presence of Trp424 in the glucose binding site, this part of the
active site is more similar to plant β-O-glucosidases, as plant myrosinases carry a phenylalanine
residue at this position (Husebye et al., 2005). The likely mechanism of the aphid enzyme is
shown in Figure 5.8.
Figure 5.8 The catalysis of glucosinolates by aphid myrosinase. This picture was taken from Bone & Rossiter (2006).
The aphid myrosinase is also a dimer as plant myrosinase, has a relatively high
temperature optimum, a low isoelectric point, and is active towards at least two structurally
different GSLs, one aliphatic and one aromatic, which is indicative of low substrate specificity
(Pontoppidan et al., 2001). This suggests coevolution of the cabbage aphid with its main food
source. The aphid has shown to employ a similar defense strategy as plants. Like its main food
source, the cabbage aphid compartmentalizes its native myrosinase and the GSL it ingests.
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When the cabbage aphid is attacked and its tissues are damaged, its stored GSLs are activated,
deterring herbivory from attacking other aphids (Bridges et al., 2002).
The properties of plant and aphid myrosinases are summarized in Table 5.2.
Table 5.2 Properties of plant and aphid myrosinases
S. alba (plant) myrosinase
EC 3.2.1.147-thioglucosidase
Reaction type: hydrolysis of a thioglucoside or an O-glucoside
Reaction: a thioglucoside + H2O = a sugar + a thiol
Sinigrin + H2O = a sugar + AITC (or ANIT depending on pH and co-factor)
Metal ion: a dimeric enzyme is stabilized by a Zn2+-ion bound on a twofold axis (Burmeister et al., 1997)
Activator: ascorbate (Bjoerkman & Loennerdal, 1973)
Inhibitor: 2-deoxy-2-fluoroglucotropaeolin (Cottaz et al., 1996)
pH optimum: 4.5 (hydrolysis of sinigrin, in citrate and phosphate buffer) (Palmieri et al., 1982)
Temperature optimum: 60˚C (Björkman & Lönnerdal, 1973)
pI: 4.8 (Bellostas et al., 2008)
Molecular weight: dimer, 2 x 60 kDa on SDS-PAGE (Bjoerkman & Janson, 1972)
Km: 0.156 mM for sinigrin at pH 7.0, at 30°C (Palmieri et al., 1982)
61 mM for p-nitrophenyl-beta-D-glucopyranoside (Botti et al., 1995)
Brevicoryne brassicae (aphid) myrosinase EC 3.2.1.147-thioglucosidase
Reaction type: hydrolysis of a thioglucoside or an O-glucoside
Reaction: a thioglucoside + H2O = a sugar + a thiol
sinigrin + H2O = a sugar + AITC
p-nitrophenyl beta-D-glucopyranoside + H2O = p-nitrophenol + D-glucose (Pontoppidan et al., 2001) Activator: ascorbate (0.3 mM, strong activation) (Pontoppidan et al., 2001) pH optimum: 5.5 (Jones et al., 2001)
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Temperature optimum: 40˚C (Pontoppidan et al., 2001)
pI: 4.9 (Pontoppidan et al., 2001)
Molecular weight: dimer, 2 x 53 kDa on SDS-PAGE (Jones et al., 2001) Km: 0.41 mM for sinigrin at pH 4.5, at 37°C (Pontoppidan et al., 2001)
0.52 mM for glucotropaeolin at pH 4.5, at 37°C (Pontoppidan et al., 2001)
5.1.4 The GH3 β-glucosidases
The β-glucosidases from GH3 glycoside hydrolase family is widely distributed in bacteria,
fungi and plants. GH3 enzymes perform multiple functions including cellulosic biomass
degradation, energy metabolism, plant and bacterial cell wall remodeling and pathogen
defense. The GH3 family contains > 2700 enzymes in the Carbohydrate-Active enZYmes (CAZy)
Database, including β-glucosidases (EC 3.2.1.21), glucan 1,3-β-glucosidases (EC 3.2.1.58) and
xylan 1,4-β-xylosidases (EC 3.2.1.37) (McAndrew et al., 2013). In many cases, the enzymes have
dual or broad substrate specificities with respect to monosaccharide residues, linkage position
and chain length of the substrate (Fincher et al., 2013). There are a few well-characterized
‘bifunctional’ enzymes in the family that have both β-D-xylopyranosidase activity and α-L-
arabinofuranosidase (Lee et al., 2003), and one characterized example of an N-acetyl-β-D-
glucosaminidase/β-glucosidase from Cellulomonas fimi (Nag3) (Mayer et al., 2006). At this
writing, there are only eight crystal structures of GH3 enzymes available in the Protein Data
Bank (McAndrew et al., 2013). Due to the high diversity of protein structural arrangements
found among GH3 members (see below), a robust subfamily classification is currently not
available.
The GH3 the high diversemploy the classic “retaining” mechanism (Hrmova et al., 1996;
Legler et al., 1979; Vocadlo et al., 2000) with the carboxylic acid side chains of two active-site
residues acting individually as a catalytic nucleophile and a general acid/base residue (Zechel &
Withers, 2000). The mechanism starts with the displacement of the leaving group (aglycone) by
the catalytic nucleophile, assisted by proton donation to the nucleofuge from the conjugate
acid form of the general acid/base residue. The second step involves the degradation of the
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resulting covalent glycosyl-enzyme intermediate by an incoming water molecule, which is
activated through deprotonation by the basic form of the general acid/base residue. The
catalytic nucleophile of GH3 has been conclusively identified as a conserved Asp residue via
mechanism-based active site labeling of several members (Vacadlo et al., 2000; Hrmova et al.,
2001; Dan et al., 2000; Paal et al., 2004). However, the catalytic acid–base residue appears to
be highly variable amongst GH3 members from bacteria, fungi, and plants, therefore it is less
readily identifiable (Paal et al., 2004; Litzinger et al., 2010; Varghes et al., 2000; Pozzo et al.,
2010).
A comparison between the GH1 enzyme family where plant and aphid myrosinases
come from and the GH3 enzyme family where the recombinant GH3 enzyme (used in this
chapter) comes form is summarized in Table 5.3.
Table 5.3 Properties of the GH1 and GH3 enzyme families in comparison
GH1 GH3
e.g. plant and aphid myrosinases e.g. the recombinant GH3 enzyme in this work
Substrate specificity
β-glucosidase (EC 3.2.1.21); β-galactosidase (EC 3.2.1.23); β-mannosidase (EC 3.2.1.25); β-glucuronidase (EC 3.2.1.31); β-D-fucosidase (EC 3.2.1.38); phlorizin hydrolase (EC 3.2.1.62); exo-β-1,4-glucanase (EC 3.2.1.74); 6-phospho-β-galactosidase (EC 3.2.1.85); 6-phospho-β-glucosidase (EC 3.2.1.86); strictosidine β-glucosidase (EC 3.2.1.105); lactase (EC 3.2.1.108); amygdalin β-glucosidase (EC 3.2.1.117); prunasin β-glucosidase (EC 3.2.1.118); raucaffricine β-glucosidase (EC 3.2.1.125); thioglucosidase (EC 3.2.1.147); β-primeverosidase (EC 3.2.1.149); isoflavonoid 7-O-β-apiosyl-β-glucosidase (EC 3.2.1.161); hydroxyisourate hydrolase (EC 3.-.-.-); β-glycosidase (EC 3.2.1.-)
β-glucosidase (EC 3.2.1.21); xylan 1,4-β-xylosidase (EC 3.2.1.37); β-N-acetylhexosaminidase (EC 3.2.1.52); glucan 1,3-β-glucosidase (EC 3.2.1.58); glucan 1,4-β-glucosidase (EC 3.2.1.74); exo-1,3-1,4-glucanase (EC 3.2.1.-); α-L-arabinofuranosidase (EC 3.2.1.55).
Mechanism Retaining Retaining
Clan
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GH-A None 3D structure
(β/α)8 (β/α)8 and (α/β)6 Catalytic Nucleophile/Base
Glu (E) Asp (D) Catalytic Proton Donor
Glu (E) Variable See main texts for more details.
The GH1- and GH3-type enzymes are different in substrate specificity and regulation
(Ketudat Cairns & Esen, 2010). The family GH1, members all have similar (β/α)8-barrel domains
that contain their active sites which are two conserved carboxylic acid residues on β-strands 4
and 7, serving as the catalytic acid/base and nucleophile, respectively (Vuong & Wilson, 2010).
In contrast, the GH3 β-glucosidases have a two-domain structure, a (β/α)8-barrel followed by an
α/β sandwich comprising a 6-stranded β-sheet sandwiched between three α-helices on either
side (Varghese et al., 2000). The active site of GH3 enzymes is situated between the (β/α)8-
barrel and (α/β)6-barrel sandwich domains, each of which contributes one catalytic carboxylate
residue. The basis of the vast diversity in biological function of β-glucosidases from different GH
familes is the substrate aglycone specificity differences that determine their natural substrates
(Ketudat Cairns & Esen, 2010). Structures of complexes of enzymes with inhibitors and mutant
enzymes with substrates, along with mutagenesis and chimera studies comparing similar
enzymes with divergent specificities, have suggested that the basis of aglycone specificity is
complex (Tribolo et al., 2007; Berrin et al., 2003).
5.1.5 Desulfation of intact GSLs and NIT production from DS-GSLs
One of the most-widely used arylsulfatase (ARS) in research is derived from the
intestinal juice of H. pomatia (Roman snail). This snail sulfatase comprises 503 amino acids and
shows 52% identity to human arylsulfatase B (HARSB) and 27% to human lysosomal
arylsulfatase A (HARSA) (Hanson et al., 2004; Holst & Williamson, 2004; Schmidt et al., 1995;
Wittstock et al., 2000). The residues that are characteristic for the active site in eukaryotic ARSs
are also present in the sequence of snail sulfatase (Wittstock et al., 2000). Snail sulfatase
exhibits sulfatase activity upon aryl (Dodgson and Powell, 1959), steroid (Jarrige, 1963) and GSL
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substrates (Thies, 1979). This is termed ‘GSL-sulfatase activity’. However, GSL-sulfatase activity
is rather different from the classical plant myrosinase (β-thioglucosidase glucohydrolase, EC
3.2.3.1), which also catalyzes sulfate release from GSLs. Snail sulfatase is a glycopolypeptide
with an apparent molecular weight of 66 kDa and a pI which ranges between 3.9 and 4.8 (Roy &
Williams, 1989). Like myrosinases, snail sulfatase is a stable enzyme that can be kept at 4–5°C
and pH 6–7 for many months without loss of activity. Snail sulfatase with GSL-sulfatase activity
has been widely used to produce DS-GSLs from intact GSLs for quantitative GSL analyzes of
plant extracts by HPLC (Sang & Truscott, 1984; Thies, 1979). DS-GSL is found to be a pre-cursor
of NIT production (Figure 5.9) in certain organisms. For example, Aspergillus flavus can
transform intact GSLs to NITs with an arylsulfatase and a β-O-glucosidase (Galletti et al., 2008).
Additionally, the recombinant β-O-glucosidase from Caldocellum saccharolyticum can hydrolyze
DS-GSLs to produce pure NITs (Wathelet et al., 2001) and the recombinant β-O-glucosidase
from the thermophilic bacterium Tp8 cloned into E. coli was able to hydrolyze a β-thioglucosidic
bond of a DS-GSL (Plant et al., 1988).
Figure 5.9 Proposed scheme of NIT production by desulfation of GSL via sulfatase and β-O-glucosidase.
GSL is desulfated by sulfatase to produce DS-GSL which is hydrolyzed by β-O-glucosidase or β-S-glucosidase to produce D-glucose, sulfate ion and NIT. This figure was modified from Galletti et al., (2008).
GSL-sulfatase activity has also been found in the diamondback moth Plutella xylostella
(Ratzka et al., 2002) and the desert locust Schistocerca gregaria (Falk & Gershenzon, 2007). A
GSL-sulfatase catalyzes the hydrolysis of GSLs to their corresponding DS-GSLs. These are no
longer substrates for hydrolysis by myrosinase, therefore eliminating the formation of toxic GSL
hydrolysis products such as ITCs. Interestingly, no bacterial sulfatases have yet to be shown to
265
accept GSL as substrates.
In larvae of Pieris rapae, however, a different method is employed by the insect for
circumventing the toxic effects of GSLs in its diet (Wittstock et al., 2004). P. rapae larvae
possess a “Nitrile-specifying protein” (NSP) in their gut. NSP prevents the formation of ITCs
during GSL hydrolysis, instead directing the aglycone of the GSL to form NITs which are less
toxic than ITCs. The presence of this enzyme allows P. rapae larvae to feed extensively on plants
containing GSLs.
5.1.6 Protein purification techniques
In this chapter, the recombinant SUL2 enzyme from E. coli O83:H1 NRG 857C and the
recombinant GH3 from E. casseliflavus NCCP-53 (Chapter 4) were to be further purified for
enzymatic assays and kinetic studies. A variety of purification techniques are available, but only
those used in this chapter are presented here.
Proteins can be purified in an active form on the basis of their characteristics e.g. size,
charge, solubility, and specific binding affinity. In general, protein mixtures are separated using
a series of separations to yield a pure protein which is concentrated using ultrafiltration. At
each step in the purification, the protein is assayed to determine its specific activity and its
concentration.
5.1.6.1 Desalting and buffer exchange
The goal of desalting process is to remove buffer salts from a protein sample in
exchange for water while buffer exchange process is aimed to exchange one set of buffer salts
in a sample for another set. Typically, it is necessary to remove salts, phenol or contaminated
nucleotides from protein solutions, and to separate excess cross-linking, labeling or
derivatization reagents from conjugated proteins to enable the enzyme activity. A protein
solution can be prepared in a more appropriate buffer using buffer exchange prior to
downstream applications such as affinity chromatography, ion exchange or electrophoresis
(Stryer et al., 2002).
266
5.1.6.2 Ultrafiltration
Ultrafiltration is used to separate extremely small particles and dissolved molecules
from fluids based on molecular size. Molecules from 1K to 1000K molecular weight (MW) are
retained by certain ultrafiltration membranes, while salts and water will pass through. Not only
ultrafiltration membranes are used to collect material retained by the filter, but also to purify
material passing through the filter. In general, ultrafiltration is used to separate proteins from
buffer components for buffer exchange, concentration or desalting. The most commonly used
membranes have a nominal molecular weight limit (NMWL) of 3 kDa to 100 kDa. Advantages of
ultrafiltration over precipitation process is that it is far gentler to solutes and more efficient
because it can simultaneously concentrate and desalt solutes.
5.1.6.3 Ion exchange chromatography
This is a process to separate proteins and other molecules in a solution on the basis of
differences in net charge. A particular net charge of a protein can be achieved by dissolving a
protein in a buffer that is either below or above its isoelectric point (pI). For example, a protein
with a pI of 5 in a buffer at pH 7 will gain a net negative charge, and can bind to positively
charged molecules e.g. diethylaminoethyl (DEAE) cross-linked to a solid support e.g. Sephadex,
known as an anion exchange column. In contrast, a protein with a pI of 7 in a buffer at pH 5 will
gain a positive charge, and can bind to a negatively charged solid support e.g. carboxymethyl
(CM)-Sephadex, known as a cation exchange column. In general, salts such as sodium chloride is
used to elute the bound protein irrespective of what type of the column is being used. The
chloride anion as the counter ion is used in an anion application to exchange for and then
release the target protein. The sodium cation as the counter ion is used in a cation application.
The strength of the electrostatic interaction between a protein and a solid support is
determined by the difference in the target protein pI and the buffer used. The more
concentrated the sodium chloride is needed to elute the protein with increasing electrostatic
charge (Stryer et al., 2002). Alternatively, target proteins can be eluted by altering the pH of the
buffer. For example, a protein with a pI of 5 bound to an anion column at pH 7 will be eluted by
267
decreasing the pH to below 5 (Stryer et al., 2002). Irrespective of whether they are buffering
agents or salts, ion exchangers are different in their effectiveness for specific applications. The
scheme of how ion-exchange chromatography works is shown in Figure 5.10.
Figure 5.10 Scheme of how ion-exchange chromatography works. (A) Negatively charged proteins are bound to an anion exchanger with positively charged stationary phase at low ionic strength. The bound proteins can be eluted either by increasing the ionic strength of the buffer or by adjusting the pH. The figure was modified from www.waters.com. (B) A cation exchange containing negatively charged beads that allow negatively charged proteins to go through. This figure was taken from Stryer et al. (2002).
A more biocompatible high-resolution separation of biopolymers of proteins can be
achieved by using fast protein liquid chromatography (FPLC). This high-performance
chromatography makes use of small-diameter stationary phases to provide high resolution. It
features include biocompatible aqueous buffer systems, high loading capacity, fast flow rates,
and availability of stationary phases in most common chromatography modes e.g. reversed
phase, ion exchange, affinity, and gel filtration (Sheehan & O' Sullivan, 2004). The protein
separation by FPLC is reproducible due to the involvement of a high level of automation
including gradient program control, auto-samplers, and peak collection (Madadlou et al., 2011).
This method is also applicable to other types of biological samples including plasmids and
268
oligonucleotides. The most common FPLC mode is anion exchange of proteins e.g. Mono Q HR
16/10 Columns pre-packed with Mono Q™ (GE Healthcare).
The most commonly used configuration for ion-exchange FPLC is shown in Figure 5.11.
The basic FPLC system consists of a program controller (LCC 500 Plus), two P-500 pumps (one
each for buffers A and B), a mixer, pre-filter, seven-port M-7 valve, assorted sample loops
(0.025–10 mL), a column, a UV-1 ultraviolet (UV) monitor (fitted with an HR-10 flow cell and
280-nm filter), and a Frac-100 fraction collector (Sheehan & O' Sullivan, 2004).
Figure 5.11 Format used for FPLC chromatography. The superloop may be incorporated using the arrangement shown within dashed lines. See text for more details. This figure was taken from Sheehan & O' Sullivan (2004).
A superloop, as associated equipment, may be incorporated to an eight-port M-8 valve
and a P-1 peristaltic pump for the sample load up to the volume of 10 mL. All the parts are
obtained from GE Healthcare. Mono Q HR5/5 anion-exchange column is obtained from GE
Healthcare and is stored in 20% ethanol. All reagents for buffer preparation are of analytic
grade, and milli-Q or HPLC-grade water should be used to prepare buffers. Examples of buffers
269
commonly used in FPLC are Buffer A: 10 mM Tris-HCl, pH 7.0 and Buffer B: 10 mM Tris-HCl, pH
7.0, 1 M NaCl. Salt is included in Buffer B to elute the desired proteins during the salt gradient.
5.1.6.4 Ni2+-affinity chromatography
This technique uses the ability of histidine amino acid (His) to bind nickel ion (Ni2+). Six
His residues at the end of a protein (either N or C terminus) are known as a 6X His tag. Ni2+ is
bound to an agarose bead by chelation using nitroloacetic acid (NTA) beads. The general
method involves mixing the NTA beads with the protein sample, and pouring the slurry of NTA
beads and proteins into the column to batch absorb the proteins onto the column. Low affinity
bound proteins are removed by using low concentrations of phosphate and imidazole. If
necessary, the imidazole can be increased to 20 mM before most His tagged proteins are eluted.
Finally, higher concentrations of imidazole are used to elute His-tagged proteins from the NTA-
beads. A scheme of how Ni2+-affinity chromatography works is shown in Figure 5.12.
Figure 5.12 Ni2+-affinity chromatography. Proteins with His tags were loaded on the Ni2–charged column. Upon increasing concentration of imidazole in the buffer, His-tagged protein is eluted from the column.
5.1.7 Hypotheses
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Since sulfatase activity of the recombinant SUL2 enzyme from E. coli O83:H1 NRG 857C
and β-O-glucosidase activity of the recombinant GH3 enzyme from E. casseliflavus NCCP-53
were detected in Chapter 4, several hypotheses regarding these two recombinant enzymes are
proposed to be tested in this chapter as follows:
The recombinant SUL2 enzyme may be able to desulfate intact GSLs to produce DS-GSLs.
There are differences in the efficiency of sulfatase activity on intact GSL substrates
between the commercially available H. pomatia sulfatase and the recombinant SUL2 enzyme.
There are differences in substrate specificity for sulfatase activity of the recombinant
SUL2 enzyme on different types of intact GSL substrates.
The recombinant GH3 enzyme can catalyse the hydrolysis of DS-GSL substrates to NIT
products as shown in Figure 5.1.
The sequential reaction from both the recombinant SUL2 enzyme and the recombinant
GH3 enzyme, in spite of different bacterial origins, can produce NIT products from intact GSL
substrates as shown in Figure 5.8.
5.1.8 Objectives
To test the above hypotheses, the aims were as follows:
To desulfate intact GSLs by purified H. pomatia sulfatase and the recombinant SUL2
enzyme in a partially purified form or crude extracts. The amounts of DS-GSLs produced from
two different sulfatases were compared.
To desulfate different types of intact GSLs at different concentrations by the
recombinant SUL2 enzyme. The amounts of DS-GSLs produced were used to determine enzyme
activities of sulfatase activity on different substrates.
To use different DS-GSLs as substrates for the recombinant GH3 enzyme. The hydrolysis
products were identified by GC-MS analysis.
To use Intact GSLs as substrates for a sequential reaction of both the recombinant SUL2
enzyme and the recombinant GH3 enzyme. The hydrolysis products were identified by GC-MS
analysis.
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5.2 Materials and Methods
5.2.1 Bioinformatics tools
Amino acid sequences of SUL2 was analyzed for sequence features (i.e. domains, motifs)
using PROSITE (Sigrist et al., 2013) (http://prosite.expasy.org). The sequence logo was generated
using InterProScan (Quevillon et al., 2005) (http://www.ebi.ac.uk/InterProScan/). Sequence logo
is a graphical version of a consensus sequence; where the height of the letter stack indicates
conservation and the height of each letter (within a stack) indicates the relative frequency of
that residue at each position. Amino acids are coloured according to their chemical properties:
polar amino acids (G,S,T,Y,C,Q,N) are green; basic (K,R,H) blue; acidic (D,E) red and hydrophobic
(A,V,L,I,P,W,F,M) black (Crooks et al., 2004).
5.2.2 Inducibility of a native SUL2 enzyme of E. coli O83:H1 NRG
Cell-free extracts (200 µL) from E. coli O83:H1 NRG 857C cultures (both induced and
non-induced with 1 mM gluconasturtiin overnight in 200 mL NB broths) were assayed for
sulfatase activity using 1 mM pNCS as a substrate as previously described (Chapter 4, section
4.2.21). Cell-free extract from E. coli BL21(DE3), as a negative control, was also assayed. Protein
concentrations were determined by Bradford assay (Bradford, 1976) as previously described
(Chapter 2, section 2.2.20).
5.2.3 Reverse transcriptase polymerase chain reaction (RT-PCR)
E. coli O83:H1 NRG 857C was grown in 2 mL NB and WC media, respectively
with/without 1 mM gluconasturtiin at specified time intervals within 24 h. At each time interval,
the bacterial cultures were pelleted and total RNA from the bacterial pellets extracted using
Trizol (Invitrogen) according to manufacturer’s instructions. RNA was purified using Pure Link
RNA minikit (Invitrogen, UK) with on-column DNase treatment to remove contaminating DNA.
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The primer pairs were designed using Primer 3 software (http://frodo.wi.mit.edu/primer3/) and
1 mg of total RNA was used as the template for reverse transcription of nine selected genes
with Omniscript reverse transcriptase by OneStep RT-PCR (Qiagen) according to manufacturer’s
instructions. PCR was carried out with the primer pairs of SUL2 gene (Table 5.1) in Eppendorf
Thermal Cycler MasterCycler Personal 5332 (50˚C for 30 min, 95˚C for 15 min, followed by 28
three-step cycles of 94˚C for 1 min, 56˚C for 1 min and 72˚C for 1 min). The transcripts of 16S
ribosomal RNA from E. coli O83:H1 NRG 857C (NCBI Reference Sequence: NC_017634.1) with
constitutive expression were used as positive controls. The primer pairs used in this experiment
are shown in Table 5.4.
Table 5.4 List of primers used in RT-PCT experiments
ECO, E. coli O83:H1 NRG 857C; SUL2, Sulfatase; 16S, 16S rRNA (as a control gene)
Total RNA and double stranded cDNA were quantified with a spectrophotometer (NanoDrop
1000, Thermo Scientific). The products were checked on a 0.8% agarose gel as previously described
(Chapter 4, section 4.2.11) to verify RNA/cDNA quality and fragment lengths. To control for equal
amounts of RNA used in the RT-PCR reactions, 1 μg of total RNA from each sample was analyzed by
agarose gel electrophoresis.
5.2.4 Purification of recombinant enzymes
After inducing BL21(DE3) bacterial cultures by IPTG, cells were lysed and cell-free
extracts containing the released recombinant enzymes were obtained as previously described
(Chapter 4, section 4.2.14). Those recombinant enzymes with His-tags were then purified for
further activity assays by two different purification methods as follows:
5.2.4.1 Ni2+-ffinity column chromatography
No. Name Primer sequence (5’-3’) Properties
1 ECO_SUL2-F ATGAAACGCCCCAATTTTCT Forward primer to flank SUL2 gene
2 ECO_SUL2-R TCAGAACTTCTGTTTTTTCT Reverse primer to flank SUL2 gene
3 ECO_16S-F GAGTTTGATCATGGCTCAG Forward primer to flank 16S rRNA gene
4 ECO_16S-R AAGGAGGTGACCAACCGCA Reverse primer to flank 16S rRNA gene
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The Ni2+-charged Profininty IMAC resin column (Bio-Rad, UK) (4 ml bed volume packed
in a mini Econo-Column gravity-flow, Bio-Rad, UK) was pre-equilibrated with equilibration
buffer (50 mM sodium phosphate pH 8.0, 300 mM NaCl). The cell supernatant containing
recombinant enzymes was loaded onto the column and the column washed with wash buffer
(50 mM sodium phosphate pH 8.0, 300 mM NaCl, 5 mM imidazole) (20 column volumes) at a
flow rate of 1.5 mL/min. The column was eluted with elution buffer (50 mM sodium phosphate
pH 8.0, 300 mM NaCl, 500 mM imidazole) (1 column volume/fraction for 5 fractions) at a flow
rate of 1.5 mL/min. Each fraction was assayed using enzyme activity assay to determine which
fraction contains recombinant enzymes. The protein concentration of the fractions was
assessed using Bradford’s reagent (Chapter 2, section 2.2.20) and purity assessed by SDS-PAGE
using the protocol as previously described (Chapter 2, section 2.2.21). The gel densitometry to
determine the purity of each fraction was analyzed by ImageJ 1.46 software (NIH government,
US). Fractions containing recombinant enzymes were pooled, concentrated and desalted
against buffer (50 mM sodium acetate pH 6.0 for SUL2 enzyme and 100 mM citrate phosphate
pH 7.0 for GH3 enzyme) using Amicon Ultra-15 Centrifugal filter units with 10K MWCO
(Millipore, Watford, UK). The proteins were stored at 4C (for no more than two weeks) until
required.
5.2.4.2 Ion-exchange column chromatography
The Sepharose HiTrap Q HP column (GE healthcare, UK)(5 mL bed volume) was
connected to FPLC system consisting of Waters 600S controller and Waters 626 pump. The
column was pre-equilibrated with equilibration buffer (100 mM Tris-Cl pH 7.0). The supernatant
containing recombinant enzymes was loaded onto the column, and the column eluted with a
salt gradient of equilibration buffer, A (100 mM Tris-Cl pH 7.0) and elution buffer, B (100 mM
Tris-Cl pH 7.0, 500 mM NaCl) at a flow rate of 0.6 mL/min. The steps to elute the proteins are
shown in Table 5.5. This method was used to purify SUL2 enzyme as an alternative to test
whether purity of SUL2 elution was improved from the use of affinity column chromatography.
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Table 5.5 Steps involved in the elution of the recombinant SUL2 enzyme using FPLC
At time (min) Flow (mL/min) Buffer A (%) Buffer B (%) Mode
0 0.6 100 0 Initial
15 0.6 100 0 Hold
60 0.6 0 100 Gradient
75 0.6 0 100 Hold
80 0.6 100 0 Gradient
105 0.6 100 0 Hold
105.1 0 0 0 Hold
The eluted fractions (3 mL) were collected using a Biologic Biofrac fraction collector (Bio-
Rad, UK). Each fraction (3 mL) was tested for sulfatase activity using sulfatase activity assay as
previously mentioned (Chapter 4, section 4.2.21) to determine which fractions contain the
recombinant enzymes. The protein concentration of the fractions was assessed using
Bradford’s reagent as previously described (Chapter 2, section 2.2.20) and purity assessed by
SDS-PAGE using the previous protocol (Chapter 2, section 2.2.21). Fractions containing
recombinant enzymes were pooled, concentrated and desalted against buffer (50 mM sodium
acetate pH 7.0 for the SUL2 enzyme) using Amicon Ultra-15 Centrifugal filter units with 10K
MWCO (Millipore, Watford, UK). The proteins were stored at 4C (for no more than two weeks)
until required.
5.2.5 Determination of pH and temperature optima
To investigate the pH and temperature optima for both recombinant enzymes, the
reaction mixtures consisting of typical assay conditions as previously described were carried out
in triplicates (Chapter 4, sections 4.2.20 and 4.2.21) with varying pH conditions in a range of pH
3.0 and pH 10.0 and varying temperatures in a range of 4C and 80C.
275
5.2.6 Measurements of apparent enzyme activities
5.2.6.1 Apparent enzyme activities of the recombinant SUL2 enzyme for intact GSLs
determined by a discontinuous assay using HPLC analysis
Since the partially purified recombinant SUL2 enzyme was unable to desulfate intact
GSLs, the non-purified crude extracts exhibiting GSL-sulfatase activity were used for this
experiment instead. The values determined throughout this work are apparent enzyme
activities since the recombinant SUL2 enzymes used in this experiment are not pure.
To determine the apparent specific activity towards 1 mM GSL, the crude extracts of the
recombinant SUL2 enzyme (1000 µg) were loaded on the DEAE-Sephadex column (Chapter 2,
section 2.2.3) to desulfate 1 mM GSL. In addition, desulfation of intact GSLs (1 mM) by the
purified H. pomatia (HP) sulfatase (100 µg) (0.3U/mL) was performed for comparative analysis.
Equilibrating buffer, 20 mM sodium acetate buffer pH 5.0 (for HP) or 50 mM sodium acetate
buffer pH 6.0 (for SUL2) was used throughout the on-column reactions that were incubated at
30˚C for 8 h. DS-GSLs produced by the recombinant SUL2 enzyme were eluted along with some
protein residues from the crude extracts from the DEAE-Sephadex column. To precipitate these
protein residues that may interfere with HPLC analysis, the 1.5 mL eluted DS-GSL solutions were
well-mixed with 150 µL of Pb(OAc)2:Ba(OAc)2 (1:1; each 0.5 M) solution. The mixture was
centrifuged at 16,100g for 2 min, and the clear supernatant was loaded onto the DEAE-
Sephadex column without desulfation step, and the 1.5 mL flow-through was collected and
analyzed by HPLC (Chapter 2, section 2.2.4).
To determine the apparent enzyme activities i.e. Km and Vmax, in vitro incubations of
crude extracts of the recombinant SUL2 enzyme (1000 µg) with varied concentrations of GSLs
(0.1-20 mM) in 1 mL of 50 mM sodium acetate buffer pH 6.0 in 1.5 mL Eppendorf tubes were
carried out at 30˚C for 8 h. After that, 100 µL supernatant from 1 mL reaction mixture was
collected for the on-column desulfation by 75 µL of the purified H. pomatia (HP) sulfatase
276
(0.3U/mL) as previously described (Chapter 2, section 2.2.3). The 1.5 mL flow-through was
collected from the DEAE-Sephadex column and analyzed by HPLC to determine the amounts of
GSLs remaining in the in vitro incubations. The negative controls containing only GSLs (0.1-20
mM) without recombinant SUL2 enzymes were also processed to determine the amounts of
GSLs present in the in vitro incubations, and therefore the amounts of GSLs disappearing (as DS-
GSLs) due to GSL-sulfatase activity of the recombinant SUL2 enzyme in the in vitro incubations
were determined. The apparent enzyme activities (.e. Km and Vmax,) of the recombinant SUL2
enzyme in crude extracts in desulfating intact GSLs were estimated from Michaelis-Menten
curves by the least squared fitting method with 95% confidence interval using GraphPad Prism
6.
5.2.6.2 Apparent enzyme activities of the recombinant SUL2 enzyme for pNCS
determined by a discontinuous assay using a spectrophotometric method
To measure apparent enzyme activities, the amount of a partially purified recombinant
SUL2 (100 µg) was kept constant, and the concentration of pNCS substrate (0.1-4 mM) was
varied. The reaction mixture was aerobically incubated for 5 min at 30˚C in 50 mM sodium
acetate buffer pH 6.0. A typical sulfatase activity was assayed as previously described (Chapter
4, section 4.2.21). The reaction rate of red-colored p-nitrocatechol (pNC) production from pNCS
substrate was calculated using a calibration curve (Chapter 4, Figure 4.13). The Vmax and Km
values were estimated from Michaelis-Menten curves by the least squared fitting method with
95% confidence interval using GraphPad Prism 6.
5.2.7 Effects of various compounds on arylsulfatase activity of the recombinant SUL enzyme
To measure the effects of various compounds on arylsulfatase activity of the partially
purified recombinant SUL2 enzyme for pNCS substrate, various compounds including Na2SO4,
NaHSO4, CoCl2, CaCl2, MgCl2, FeSO4, NiCl2, MnCl2, FeCl3 (Sigma-Aldrich, UK) were individually
added to a final concentration of 1.0 mM in a typical sulfatase activity assay as previously
described (Chapter 4, section 4.2.21). Each reaction contained 100 µg/mL of the recombinant
SUL2 enzyme with the control sample contained only the partially purified recombinant SUL2
277
enzyme without any compounds. The effect of each compound on the arylsulfatase activity was
determined as a percentage activity in relative to the control sample.
5.2.8 DS-GSLs as substrates for the recombinant GH3 enzyme
DS-GSLs (1 mM) obtained previously (Chapter 2, section 2.2.5) were used as substrates
for the purified recombinant GH3 enzyme (100 µL) aerobically incubated in a 1 mL buffer (100
mM citrate phosphate, pH 7.0) containing 1 mM Fe2+ or a 1 mL NB broth (pH 7.0) for 16 h at
37˚C. The negative controls include a reaction mixture with the recombinant GH3 enzyme alone
and the other with DS-GSL substrate alone. After that, the reaction mixtures were extracted
with the same volume of DCM as previously described (Chapter 2, section 2.2.11) in order to
identify GSL degradation products by GC-MS analysis.
5.2.9 Intact GSL as substrates in a reaction containing both the recombinant SUL2 enzyme and
the recombinant GH3 enzyme
GSLs (1 mM) obtained previously (Chapter 2, section 2.2.1) were used as substrates for a
reaction mixture containing both the purified recombinant GH3 enzyme (100 µg) and the crude
extracts of the recombinant SUL2 enzyme (1000 µg) incubated in a 1 mL NB broth (pH 7.0) for
16 h at 30˚C under aerobic conditions. Note that the temperature of 30˚C was used instead of
37˚C as it was optimal for the recombinant SUL2 enzyme. Also, crude extracts of the
recombinant SUL2 enzyme were filtered by 0.22 μm filter to obtain sterile solutions to be used
in sterile Eppendorf tubes in this experiment. The negative controls include the reaction
mixture containing either recombinant enzyme alone, the reaction without intact GSL substrate
and the other with intact GSL substrate alone. After 16 h, 900 µL of each reaction mixture was
extracted with the same volume of DCM as previously described (Chapter 2, section 2.2.11) in
order to identify the hydrolysis products by GC-MS analysis. The other 100 µL of supernatant
was desulfated as previously described (Chapter 2, section 2.2.3) and analyzed by HPLC
(Chapter 2, section 2.2.4) to determine the degradation of GSL substrate.
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5.3 Results
5.3.1 Bioinformatics results of a native SUL2 enzyme of E. coli O83:H1 NRG 857C
To determine whether the intracellular SUL2 enzyme of E. coli O83:H1 NRG 857C is a
‘Cys-type’ or ‘Ser-type’ sulfatase, bioinformatics research was carried out. SUL2 enzyme was
found to have alkaline phosphatase-like domain (Figure 5.13A). This is not surprising since all
sulfatase protein structures appear as globular monomers divided in two domains. The N-
terminal domain, spanning the active site, contains α-helices surrounded by a large β-sheet.
The structure of this domain shares significant similarities with that of alkaline phosphatases
(Bond et al., 1997). Cross-species sequence comparisons showed amino acid sequence
similarities between the active sites of sulfatases and those of phosphatases suggesting a
similar enzymatic mechanism and a common evolutionary origin between these two protein
families (Lukatela et al., 1998). There are two conserved sites for the sulfatase family located in
the N-terminal region of SUL2 enzyme (Figure 5.13B). The SULFATASE_1 site contains the
conserved arginine (R) which could be implicated in the catalytic mechanism; it is located four
residues after a position that, in eukaryotic sulfatases, is a conserved Cys residue (Galletti et al.,
2008) which has been shown to be modified to 2-amino-3-oxopropionic acid. In prokaryotes,
Cys is replaced by Ser. In spite of its prokaryotic origin, SUL2 enzyme is categorized into a ‘Cys-
type’ sulfatase (Figure 5.13B and 5.13C).
279
A
B PS00523 SULFATASE_1 Sulfatases signature 1 : PVCTPARagLFTG 50 – 62 PS00149 SULFATASE_2 Sulfatases signature 2 : GYhTcyIGK.WH 92 – 102 C
280
Figure 5.13 Bioinformatics details on SUL2 enzyme. (A) Sequence feature of SUL2 enzyme. The figure was retrieved from InterProScan (Quevillon et al., 2005). (B) Two sulfatase signatures found in SUL2 protein sequence. Yellow highlight indicates a strictly conserved sequence called “sulfatase signature” (C/S)XPXR where R is a putative active site residue. (C) Sequence logo for sulfatases signature 1 ‘CTPAR’ showing that SUL2 enzyme is a ‘Cys-type’ sulfatase. The information on (B) and (C) was retrieved from PROSITE (Sigrist et al., 2013). The maturation of the activity of all sulfatases require posttranslational modification
mediated by one of two different enzymes, FGE (Cosma et al., 2003; Dierks et al., 2003) and
AtsB (Szameit et al., 1999), responsible for the conversion of Cys or Ser to FGly, respectively.
Sequence analysis of many bacterial genomes reveals that both types of sulfatase modifying
factor genes, AtsB and SUMF1, are physically associated with sulfatase genes, indicating the
presence of sulfatase operons (Landgrebe et al., 2003). Therefore, the whole genomes of both E.
coli O83:H1 NRG 857C (as an origin of SUL2 enzyme) and E. coli BL21(DE3) (as a host to express
the recombinant SUL2 enzyme) were searched for the presence of AtsB or SUMF1 protein
homolog using BLAST search against the known anaerobic sulfatase-maturating enzyme
homolog, AslB from E. coli strain K12 (Uniprot accession no. P25550) (Benjdia et al., 2007). It is
important to note that anaerobic sulfatase-maturating enzyme homolog is named differently
from one bacterial strain to the next, but in most cases it is named AtsB. For example, it is
named AslB in E. coli strain K12 whereas it is named AtsB in Klebsiella pneumonia (Uniprot
accession no. Q9X758) (Szameit et al., 1999) and in other bacteria.
The results showed that there are three candidate proteins with low E-value for
sulfatase-maturating enzymes with sequence similarity to AslB in E. coli O83:H1 NRG 857C
genome (Table 5.6A). Likewise, three candidate proteins with low E-value for anaerobic
sulfatase maturation enzymes are found in E. coli BL21(DE3) genome (Table 5.6B). The
functionality of the recombinant SUL2 enzyme clearly validates the use of E. coli BL21(DE3) as
the recombinant expression system for the production of active sulfatase enzyme. The results
also logically point to the existence of the necessary sulfatase-modifying enzyme(s) encoded by
the E. coli BL21(DE3) genome. The heterologous expression of other catalytically active
sulfatases in E. coli host has also been reported (Boltes et al., 2001; Dierks et al., 1998a).
281
Table 5.6 Three proteins from E. coli O83:H1 NRG 857C and E. coli BL21(DE3) producing
significant alignments with anaerobic sulfatase-maturating enzyme homolog (AslB) from E.
coli strain K12
A Query = sp|P25550|ASLB_ECOLI Anaerobic sulfatase-maturating enzyme homolog AslB OS = E. coli strain K12, GN=aslB PE=3 SV=4 Object = E. coli O83:H1 NRG 857C Sequences producing significant alignments: Score E-value*
ref|YP_006122114.1| regulator of arylsulfatase activity 827 0.0
ref|YP_006119836.1| hypothetical protein NRG857_07390 330 4e-110
ref|YP_006122007.1| putative DNA-binding transcriptional regulator 45.1 1e-06
*The Expect value (E) is a parameter that describes the number of hits one can "expect" to see by chance when searching a database of a particular size. It declines exponentially as the Score of the match increases.
B Query = sp|P25550|ASLB_ECOLI Anaerobic sulfatase-maturating enzyme homolog AslB OS = E. coli strain K12, GN=aslB PE=3 SV=4 Object = E. coli BL21(DE3) Sequences producing significant alignments: Score E-value
ref|YP_003001361.1| anaerobic sulfatase maturation enzyme 830 0.0
ref|YP_002999279.1| anaerobic sulfatase maturation enzyme 334 1e-11
ref|YP_003001245.1| DNA-binding transcriptional regulator 44.3 3e-06
5.3.2 Inducibility of a native SUL2 enzyme of E. coli O83:H1 NRG 857C
282
It is known that GSL-sulfatase activity in desert locusts S. purpurea is induced ten-fold
when the locust are fed with GSLs after being maintained on a GSL-free diet, and activity
declines when GSLs are removed from the locust diet (Falk & Gershenzon, 2007). However,
sulfatase from H. pomatia was constitutively expressed, and bacterial sulfatase of C. perfringens
was also constitutively expressed with weak sulfatase activity of 0.25 nmol min–1mg–1 using a
synthetic substrate, p-nitrophenyl sulfate (pNPS) at neutral pH (Berteau et al., 2006). Therefore,
the inducibility of a native SUL2 enzyme of E. coli O83:H1 NRG 857C was determined in this
work.
Protein extracts from E. coli O83:H1 NRG 857C cells (both induced and non-induced with
1 mM gluconasturtiin overnight) were assayed for sulfatase activity using 1 mM pNCS as a
substrate. Protein extract from E. coli BL21(DE3), as a negative control, was also assayed. The
results showed that cell-free extracts from both non-induced and GSL-induced cells showed a
weak sulfatase activity of 0.07-0.09 µmol·min–1·mg–1 using pNCS as a substrate in 50 mM
sodium acetate buffer pH 5.0 (Figure 5.14A). In contrast, BL21(DE3) host did not exhibit active
endogenous sulfatase activity (Figure 5.14A) and hence suitable for heterologous expression of
the recombinant SUL2 enzyme from E. coli O83:H1 NRG 857C.
This constitutive expression of a native SUL2 enzyme was also reconfirmed by reverse
transcription–PCR (RT-PCR) analysis showing that the SUL2 transcript level remained constant
from 0 h to 24 h in E. coli O83:H1 NRG 857C cells with and without 1 mM gluconasturtiin
supplementation (Figure 5.14B). The 16S rRNA transcripts (as positive controls) from both types
of bacterial cells also showed constitutive expression (Figure 5.14B) supporting the validation of
RT-PCR analysis.
283
A (i) BL21(DE3) (ii) Induced (iii) Non-induced
Specific activity ND 0.09 ± 0.02 0.07 ± 0.04 (µmol·min–1·mg–1)
B
Figure 5.14 Inducibility test of a native SUL2 enzyme of E. coli O83:H1 NRG 857C. (A) Bacterial protein extracts were assayed for endogenous sulfatase activity using 1 mM pNCS as a substrate in 50 mM sodium acetate buffer pH 5.0. (i) E. coli BL21(DE3) showed no sulfatase activity (ii) E. coli O83:H1 NRG 857C induced with 1 mM gluconasturtiin overnight showed a weak sulfatase activity. (iii) E. coli O83:H1 NRG 857C non-induced with GSL also showed a weak sulfatase activity. Values are means ± SD of triplicates. (B) Reverse transcription–PCR (RT-PCR) analysis of SUL2 transcripts from E. coli O83:H1 NRG 857C cells over a time course of 24 h. (i) SUL2 transcripts from, non-induced E. coli O83:H1 NRG 857C cells (ii) SUL2 transcripts from gluconasturtiin-induced E. coli O83:H1 NRG 857C. (iii) 16S rRNA transcripts (as positive controls) from both types of bacterial cells. The experiments were independently repeated in triplicates with similar results.
5.3.3 Expression and purification of the recombinant SUL2 enzyme
284
To purify the recombinant SUL2 enzyme, two different protein purification methods;
Ni2+-affinity chromatography and ion-exchange chromatography were used. The elution profile
from the latter method is shown in Figure 5.15. The recombinant SUL2 enzyme eluted in the
fraction numbers 18, 19 and 20 during increasing salt gradient (Figure 5.15, step 2).
Figure 5.15 Purification of the recombinant SUL2 enzyme by ion-exchange chromatography. Step 1, Buffer A 100% (10 mM Tris-HCl, pH 7.0) without salt gradient; step 2 increasing salt gradient to Buffer B 100% (10 mM Tris-HCl, pH 7.0, 1 M NaCl); step 3, Buffer B 100% without salt gradient and step 4 decreasing salt gradient to Buffer A 100%. Dashed lines indicate purification steps and bold lines indicate protein concentration of each elution fraction collected. The 3 mL protein fraction was collected at a flow rate of 0.6 mL/min in a total of 105.10 min run.
The elution fractions from both purification methods were analyzed by SDS-PAGE
(Figure 5.16). The soluble recombinant SUL2 enzymes with a molecular weight of approximately
57 kDa (as predicted by UNIPROT) were found in the three eluted fractions from both methods.
Protein homogeneity a.k.a. protein purity was determined by densitometry analysis of proteins
on SDS-PAGE gels using ImageJ 1.46 software (NIH government, US). The use of Ni2+-affinity
column chromatography purification resulted in the partially purified recombinant SUL2
enzyme with 61% purity assessed by SDS-PAGE (Figure 5.16A, fraction E2), and the ion-
exchange column chromatography resulted in a protein with 65% purity (Figure 5.16B, fraction
number 19). The relative activity of each fraction from both methods is shown in Figure 5.16C
and 5.16D, respectively.
285
Figure 5.16 Purification of the recombinant SUL2 enzyme expressed in BL21(DE3). (A) The 4-12% SDS- PAGE analysis of protein fractions obtained from Ni2+-affinity chromatography; Lane C, total proteins from empty pET28b+ vector expressed in BL21(DE3) as a negative control; lane M, PageRuler pre-stained protein ladders (ThermoScientific, UK); lane S, supernatant of crude extracts from recombinant bacteria expressing SUL2 enzyme; lane FT, the flow-through fraction during purification; lane E1, elution fraction no. 1; lane E2, elution fraction no. 2; lane E3, elution fraction no. 3. (B) Relative activity of each eluted protein fraction with the same volume of 10 µL. (C) By ion-exchange chromatography, protein fractions are loaded in; Lane S, supernatant of crude extracts containing SUL2 enzyme; Lane 18, elution fraction no. 18; Lane 19, elution fraction no. 19; Lane 20, elution fraction no. 20; lane M, PageRuler pre-stained protein ladders (ThermoScientific, UK). Protein bands corresponding to SUL2 enzymes (57 kDa) are indicated by arrows. (D) Relative activity of each eluted protein fraction with the same volume of 10 µL using 1 mM pNCS as a substrate.
286
Both procedures gave similar purity levels of the eluted proteins, but Ni2+-affinity
column chromatography was used for further purification of the recombinant SUL2 enzyme as
it was much quicker. The purification scheme of the recombinant SUL2 by Ni2+-affinity column
chromatography is shown in Table 5.7.
Table 5.7 Purification scheme of the recombinant SUL2 enzyme using Ni2+-affinity column
chromatography
Purification Step Total activity (U)
Total protein (mg)
Specific activity (U/mg)
Purity (Fold) Yield (%)
Cell-free extract 268 206 1.3 1 100
Ni2+ affinity column chromatography 125 12 10.4 8 47
One unit (U) of sulfatase is defined as the amount of enzyme liberating 1 µmol min-1 of pNC product.
5.3.4 Temperature and pH optima of the recombinant SUL2 enzyme
The kinetics of the hydrolysis of small aryl substrate p-nitrophenyl sulfate (pNPS)
catalyzed by arylsulfatase from H. pomatia was studied at a wide range of temperatures as well
as at ambient and elevated pressures. It was found that pH 7.4 and 30˚C were pH and
temperature optima for H. pomatia sulfatase and the Km value of 2.5 mM for pNPS was
determined (Stawoska et al., 2010).
To determine the temperature and pH optima of the recombinant SUL2 enzyme, various
temperatures and pH conditions were tested in 50 mM sodium acetate buffer for sulfatase
activity. The recombinant SUL2 enzyme activity was found to be optimal at 30˚C and pH 6.0
when 1 mM pNCS was a substrate in arylsulfatase activity assays (Figure 5.17A and 5.17B).
Interestingly, 40% of the maximal sulfatase activity still remained at 4˚C.
287
A B
Figure 5.17 Temperature and pH optima of the recombinant SUL2 enzyme. (A) Effect of temperature on arylsulfatase activity using 1 mM pNCS as a substrate. (B) Effect of pH. Enzyme activity was expressed as the percentage of the activity at 30˚C and pH 6.0 in 50 mM sodium acetate buffer which was defined as 100%. Partially purified recombinant SUL2 enzyme (100 µg) was used in each reaction mixture. Values were means of triplicates.
5.3.5 Desulfation of intact GSLs by the recombinant SUL2 enzyme
To determine whether the recombinant SUL2 enzyme can desulfate GSL as desert locust
sulfatase and H. pomatia sulfatase, several intact GSLs (1 mM) were used as substrates for the
partially purified recombinant SUL2 enzyme in the DEAE-Sephadex column desulfation
procedure as previously described (Chapter 2, section 2.2.3). In Chapter 2, the column was left
at room temperature during desulfation of intact GSLs by H. pomatia sulfatase (100 µg)
overnight (16-24h). It was reported that a minimum of 11 hours is necessary for complete
desulfatation of various GSLs by H. pomatia sulfatase (activity at pH 5.8 and 30°C, 0.05 U/mL;
one activity unit (U) corresponds to the desulfation of 1 µmol of sinigrin per min) on the DEAE-
Sephadex column (Figure 5.18) (Wathelet et al., 2008). If necessary, the desulfation time can be
reduced to 2 h if a ten times concentrated sulfatase solution (activity: 0.5 U/mL) is used for a
broad spectrum of GSLs (allyl, benzyl, indolyl, methylthio, and methylsulfinyl) (Wathelet et al.,
2008). Based on this finding (Figure 5.18), the incubation time of 8 h was used to desulfate
intact GSLs by the recombinant SUL2 enzyme. In theory, this would give similar levels of
desulfation as overnight incubation.
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Figure 5.18 Kinetics of H. pomatia sulfatase activity (0.05 U/mL) in desulfation of intact GSLs. The experiment was carried out on the DEAE-Sephadex column at pH 5.8 and 30°C under aerobic conditions. This figure was taken from Wathelet et al. (2008).
To determine the specific activity of SUL2 enzyme towards 1 mM GSL, the crude extracts
of the recombinant SUL2 enzyme were loaded on the DEAE-Sephadex column at 30˚C for 8 h to
desulfate GSL that was added earlier. The desulfation of intact GSLs by the purified H. pomatia
(HP) sulfatase was also carried out for comparative analysis. DS-GSLs produced by the
recombinant SUL2 enzyme were eluted along with some protein residues from the crude
extracts from the DEAE-Sephadex column. The proteins were precipitated by a mixture of
Pb(OAc)2:Ba(OAc)2. The clear supernatant was loaded onto the DEAE-Sephadex column without
desulfation step, and the flow-through was collected and analyzed by HPLC. The areas of the
peaks on HPLC chromatograms corresponding to DS-GSL products were used to determine the
amount of DS-GSL production by the enzyme.
It was found that the partially purified recombinant SUL2 enzyme was unable to
desulfate intact GSLs on the DEAE-Sephadex column. In contrast, the non-purified crude
extracts of this enzyme was successful in desulfating intact GSLs on the DEAE-Sephadex column.
This led us to postulate that co-factors or co-proteins present in the crude extracts may be
essential for GSL-sulfatase activity of the recombinant SUL2 enzyme. Interestingly, arylsulfatase
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activity for pNCS substrate does not seem to require such factors since positive results were
detected in both the partially purified recombinant SUL2 enzyme and the crude extracts.
To compare the efficiency in GSL-sulfatase activity of these two sulfatases on intact GSLs,
1000 µg of crude extracts of the recombinant SUL2 enzyme and 100 µg of the purified H.
pomatia sulfatase were used in the DEAE-Sephadex on column desulfation procedure with
intact GSLs (1 mM). The results showed that the recombinant SUL2 enzyme was able to
desulfate intact GSLs with less efficiency than H. pomatia sulfatase (Figure 5.19). A negative
control including cell-free extracts from BL21(DE3) without recombinant enzyme expression of
SUL2 enzyme showed no desulfation of these GSLs tested as no DS-GSLs were detected on HPLC
chromatograms (Appendix III). This indicates that BL21(DE3) host did not exhibit endogenous
GSL-sulfatase activity.
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0 5 10 15 20
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Figure 5.19 HPLC chromatograms showing desulfation of intact GSLs by crude extracts of the recombinant SUL2 enzyme and the purified H. pomatia sulfatase on the DEAE-Sephadex column. Either crude extracts of the recombinant SUL2 enzyme, 1000 µg (black line) or the purified H. pomatia (HP) sulfatase, 100 µg (red line) was used to desulfate 1 mM GSL on the DEAE-Sephadex column for 8 h at 30˚C under aerobic conditions. Intact GSLs used are as follows; (A) Sinigrin. (B) Glucoerucin. (C) Gluconasturtiin and (D) Glucoiberin. The figures are representatives of triplicates.
The apparent specific activity of the recombinant SUL2 enzyme for intact GSL substrates
plus pNCS substrate is shown in Table 5.8. Its relative activity (%) was compared with H.
pomatia sulfatase. Glucoiberin with the highest polarity (in the side chain) has the lowest
specific activity and the lowest relative activity to H. pomatia sulfatase. The specific activity was
found in the descending order according to the degree of side chain polarity of GSLs as follows;
sinigrin > glucoerucin > gluconasturtiin > glucoiberin. This suggests that the side chain property
of GSL may influence the efficiency of GSL-sulfatase activity of the recombinant SUL2 enzyme.
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However, H. pomatia sulfatase seemed to desulfate these GSLs with the same efficiency as seen
from similar peak areas of DS-GSLs produced on-column from HPLC chromatograms (Figure
5.19).
Table 5.8 Specific activity and relative activity of crude extracts of the recombinant SUL2
enzyme in desulfation of intact GSL substrates
Substrates (1 mM) Apparent specific activity (U/mg)* Relative activity** (%)
pNCS 10.4 ± 0.25 51.0 ± 1.4
Sinigrin 0.71 ± 0.15 4.4 ± 1.1
Gluconasturtiin 0.38 ± 0.09 3.5 ± 0.7
Glucoerucin 0.66 ± 0.11 4.1 ± 0.3
Glucoiberin 0.11 ± 0.03 0.6 ± 0.2
*The values determined are apparent specific activities since the SUL2 enzymes are not pure. Aerobic incubation of the partially purified recombinant SUL2 enzyme (approximately 100 µg) with 1 mM pNCS in 50 mM sodium acetate buffer pH 6.0 was incubated for 15 min at 30˚C. One unit (U) of sulfatase was defined as the amount of enzyme liberating 1 µmol min-1 of pNC. For desulfation of 1 mM intact GSL substrate on the DEAE-Sephadex column for 8 h at 30˚C, crude extracts of the recombinant SUL2 enzyme (approximately 1000 µg) was used instead. One unit (U) of sulfatase was defined as the amount of enzyme liberating 1 nmol min-1 of DS-GSL. **Activity produced by crude extracts of the recombinant SUL2 enzyme (approximately 1000 µg) in (%) relative to that produced by the purified H. pomatia sulfatase (approximately 100 µg). Values were means ± SD of triplicates.
5.3.6 Apparent enzyme activities of the recombinant SUL2 enzyme
Since very little is known about the enzyme activities of bacterial sulfatases known to
date, the aim of this chapter was to determine these parameters of the recombinant SUL2
enzyme using pNCS and common intact GSL substrates. Note that the partially purified
recombinant SUL2 enzyme was used for pNCS substrate while crude extracts were used for GSL
substrates in this experiment. The Michaelis-Menten kinetic curve and the Lineweaver–Burk
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plot showed that the arylsulfatase activity of the recombinant SUL2 enzyme has the Michaelis–
Menten constant (Km) of 1.09 mM and the Vmax of 25.1 U/mg for pNCS (Figure 5.20).
Figure 5.20 Apparent enzyme activities of the partially purified recombinant SUL2 enzyme for pNCS substrate. (A) Michaelis-Menten curve of the recombinant SUL2 enzyme for pNCS. (B) Lineweaver–Burk plot of graph (A). Arylsulfatase activity was measured by monitoring the release of pNC from pNCS by the recombinant SUL2 enzyme (100 µg) in 50 mM sodium acetate buffer pH 6.0 for 5 min at 30˚C. Values are means ± SD of triplicates.
In addition to pNCS substrate, the enzyme activities for GSLs tested are presented in
Table 5.9. To determine the apparent enzyme activities i.e. Km and Vmax, in vitro incubations of
crude extracts of the recombinant SUL2 enzyme with varied concentrations of GSLs in
Eppendorf tubes were carried out at 30˚C for 8 h. After that, supernatant from a reaction
mixture was collected for the on-column desulfation by the purified H. pomatia (HP) sulfatase.
The flow-through was collected from the DEAE-Sephadex column and analyzed by HPLC to
determine the amounts of GSLs remaining in the in vitro incubations. The negative controls
containing only GSLs without recombinant SUL2 enzymes were also processed to determine the
amounts of GSLs present in the in vitro incubations, and therefore the amounts of GSLs
disappearing (as DS-GSLs) due to GSL-sulfatase activity of the recombinant SUL2 enzyme in the
in vitro incubations were calculated.
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Table 5.9 Apparent enzyme activities* of the recombinant SUL2 on different substrates
Substrate Km (mM) Vmax (U/mg) kcat (s-1) Kcat/Km (M-1 s-1)
pNCS 1.09 25.1 232 2.13 X 105
Sinigrin 9.68 11.1 9.94 x 10-3 1.02
Gluconasturtiin 15.7 8.81 7.87 x 10-3 0.502
Glucoiberin 0.480 0.169 1.51 x 10-4 0.314
*The values determined are apparent enzyme activities since the SUL2 enzymes are not pure. Aerobic incubation of the partially purified recombinant SUL2 enzyme (100 µg) with 1 mM pNCS in 50 mM sodium acetate buffer pH 6.0 for 15 min at 30˚C. One unit (U) of sulfatase was defined as the amount of enzyme liberating 1 µmol min-1 of pNC product. For desulfation of various concentrations of intact GSL substrates on the DEAE-Sephadex column for 8 h at 30˚C, crude extracts of the recombinant SUL2 enzyme (1000 µg) was used instead. One unit (U) of sulfatase was defined as the amount of enzyme liberating 1 nmol min-1 of DS-GSL. Values of Km and Vmax are estimated with a 95% confidence using GraphPad Prism 6.
The Vmax and catalytic efficiency (Kcat/Km) of the recombinant SUL2 enzyme were found
in the same descending order; pNCS > sinigrin > gluconasturtiin > glucoiberin, whereas the
order of Km was gluconasturtiin > sinigrin > glucoiberin > pNCS (Table 5.6). The highest Vmax with
the lowest Km of the recombinant SUL2 enzyme were found for pNCS substrate indicating the
SUL2 enzyme was most efficient in desulfating this synthetic substrate. Amongst the GSLs
tested, the most preferred substrate was sinigrin, and the least favored GSL was glucoiberin.
The corresponding Michaelis-Menten curves and Lineweaver-Burk plots of crude extract
of the recombinant SUL2 enzyme for all GSLs tested are shown in Figure 5.21.
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Figure 5.21 Apparent enzyme activities of crude extracts of the recombinant SUL2 enzyme for GSL substrates. (A) Michaelis-Menten curve of the recombinant SUL2 enzyme for sinigrin. (B) Lineweaver–Burk plot of graph (A); (C) Michaelis-Menten curve of SUL2 for gluconasturtiin; (D) Lineweaver–Burk plot of graph (C); (E) Michaelis-Menten curve of SUL2 for glucoiberin; (F) Lineweaver–Burk plot of graph (E). Values are means ± SD of triplicates. These graphs were generated using GrapPad Prism 6.
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5.3.7 Effects of compounds on arylsulfatase activity of the recombinant SUL2 enzyme
It was reported that H. pomatia sulfatase was activated by Cd2+, but was inhibited by
Cu2+ (Tokheim et al., 2005). Surprisingly, not many reports were found regarding the effect of
certain ions on bacterial sulfatases. Therefore, various compounds including Na2SO4, NaHSO4,
CoCl2, CaCl2, MgCl2, FeSO4, NiCl2, MnCl2, FeCl3 of 1.0 mM were tested for thier effects on
arylsulfatase activity of the recombinant SUL2 enzyme pr pNCS substrate.
Essentially, no effect was observed with most of the compounds and metal ions tested,
except for Fe2+, NaHSO4 and Na2SO4 that reduced arylsulfatase activity by 20, 75, and 50%,
respectively (Figure 5.22).
Figure 5.22 Effect of compounds on arylsulfatase activity of the partially purified recombinant SUL2 enzyme. Either 1 mM of Na2SO4, NaHSO4, CoCl2, CaCl2, MgCl2, FeSO4, NiCl2, MnCl2, FeCl3 was added with the partially purified recombinant SUL2 enzyme (100 µg) in 50 mM sodium acetate buffer pH 6.0 at 30˚C for 15 min. Relative activity (%) was shown. The control sample contained only the recombinant SUL2 enzyme without any compounds. Values are means ± SD of triplicates.
Since GSL-sulfatase activity of the recombinant SUL2 enzyme was found in crude
extracts (not in the purified fraction), it was highly speculated that metal ions or co-proteins
present in the crude extracts may be required to activate GSL-sulfatase activity of the
recombinant SUL2 enzyme in the purified fraction. This hypothesis still remains to be tested.
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5.3.8 Purification of the recombinant GH3 enzyme from E. casseliflavus NCCP-53
Since three of the candidate recombinant enzymes in Chapter 4 showed β-O-glucosidase
activity for pNPG substrate (Chapter 4, section 4.3.4.2), the recombinant GH3 enzyme with the
highest β-O-glucosidase activity was chosen to be studied in more details in this chapter.
The Ni2+-affinity chromatography was used to purify the recombinant GH3 enzyme as
previously described as per the recombinant SUL2 enzyme. The elution fractions were analyzed
on SDS-PAGE (Figure 5.23A). A soluble recombinant GH3 enzyme with a molecular weight of
approximately 79 kDa (as predicted by UNIPROT) was found in two elution fractions (E1 and E2).
It was clear that the purity of each fraction was of high purity (> 90%). These fractions were
much purer than the elution fractions of the recombinant SUL2 enzyme purified by the same
method with the same buffer conditions. The reason for the differences in these results is not
known. The activity of these elution fractions was determined using β-O-glucosidase activity
assay as previously described (Chapter 4, section 4.2.19). The relative activity of these fractions
is shown in Figure 5.23B.
Figure 5.23 Purification of the recombinant GH3 enzyme expressed in BL21(DE3). (A) The 4-12% SDS-PAGE analysis of protein fractions obtained from Ni2+-affinity chromatography. Lane S, the supernatant from recombinant bacteria expressing the recombinant GH3 enzyme; lane FT, the flow-through fraction during the purification; lane W, the wash fraction; lane M, PageRuler pre-stained protein ladders (ThermoScientific, UK); lane E1 and E2, elution fraction no. 1 and 2 containing the band of GH3 enzyme (79 kDa) is indicated by an arrow. (B) Elution fractions (10 µL) with relative β-O-glucosidase activity using 1 mM pNPG substrate.
The purification scheme of the recombinant GH3 enzyme by Ni2+-affinity column
chromatography is shown in Table 5.10.
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Table 5.10 Purification scheme of the recombinant GH3 enzyme from Ni2+-affinity column chromatography
Purification Step Total activity (U)
Total protein (mg)
Specific activity (U/mg)
Purity (Fold) Yield (%)
Crude extract 382 212 1.8 1 100 Ni2+ affinity column
chromatography 187 8 23.0 13 49
One unit (U) of GH3 enzyme was defined as the amount of enzyme liberating 1 µmol min-1 of pNP product
5.3.9 Temperature and pH optima of the recombinant GH3 enzyme
The temperature and pH optima of the recombinant GH3 enzyme for pNPG substrate
were determined using β-O-glucosidase activity assay as previously described (Chapter 4,
section 4.2.19). The β-O-glucosidase activity of the recombinant GH3 enzyme was found to be
optimal at pH 7.0 and 37°C (Figure 5.24A and 5.24B) in 0.1 M citrate phosphate buffer.
Figure 5.24 The pH and temperature optima of the recombinant GH3 enzyme. (A) Effect of pH on β-O-glucosidase activity using 1 mM pNPG as a substrate. (B) Effect of temperature. Enzyme activity was expressed as the percentage of the activity at 37˚C and pH 7.0 in 100 mM citrate phosphate buffer which was defined as 100%. Purified recombinant GH3 enzyme (100 µg) was used in each sample. Values were means of triplicates.
5.3.10 Effects of metal ions on β-O-glucosidase activity of the recombinant GH3 enzyme
To determine whether β-O-glucosidase activity of the purified recombinant GH3 enzyme
is influenced by metal ions, various metal ions including CoCl2, CaCl2, MgCl2, FeSO4, NiCl2, MnCl2,
FeCl3 of 1.0 mM were tested using 1 mM pNPG substrate in 0.1 M citrate phosphate buffer pH
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7.0. Essentially, no significant effect was observed with most metal ions tested, except for Mn2+
that promoted activity to 232% while Fe2+ declined activity to 84% (Table 5.11).
Table 5.11 Effects of metal ions on β-O-glucosidase activity of the recombinant GH3 enzyme
Metal cations Relative activity (%)*
No ion 100 (23.0 U/mg)
Fe3+ 97
Fe2+ 84
Mn2+ 232
Mg2+ 95
Ca2+ 95
Co2+ 99
Ni2+ 99 *Relative activity (%) was (%) activity relative to that of the purified recombinant GH3 enzyme without any ions added. Values are means of triplicates. Either 1 mM CoCl2, CaCl2, MgCl2, FeSO4, NiCl2, MnCl2, FeCl3 was added with the purified recombinant GH3 enzyme (10 µL) using 1 mM pNPG substrate in 0.1 M citrate phosphate buffer pH 7.0 at 37˚C for 5 min.
5.3.11 NIT production from DS-GSLs by the recombinant GH3 enzyme
It was reported that DS-GSLs were precursors for the recombinant β-O-glucosidase from
Caldocellum saccharolyticum to production of pure NITs (Wathelet et al., 2001). Whether this
holds true for the recombinant GH3 enzyme exhibiting β-O-glucosidase activity was to be
determined in the following experiments. It is known that NIT production from the metabolism
of intact GSLs by bacterial cells only occurred in the culture broths (Chapter 2, section 2.3.3)
and 0.1 M citrate phosphate buffer pH 7.0 with the presence of 5 mM Fe2+ ions for E. coli
O83:H1 NRH 857C resting cells (Chapter 2, section 2.3.7). Therefore, DS-glucoraphanin, DS-
glucoerucin and DS-gluconaturtiin (1 mM) were used as substrates for the recombinant GH3
enzyme of E. casseliflavus NCCP-53 (100 µg) in both NB broth and 0.1 M citrate phosphate
buffer pH 7.0 with the presence of 1 mM Fe2+ or Mn2+ (as found to promote β-O-glucosidase
activity of GH3 in Table 5.8)
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The negative controls containing either DS-GSL alone or the GH3 enzyme alone in NB
broth or the buffer showed no NIT production suggesting that these DS-GSLs were stable in
experimental conditions and not degradable to NIT (Appendix IV). There was no NIT production
from DS-glucoraphanin in either NB broth or the buffer (Figure 5.25A). This finding is in
agreement with the previous results showing that there was no NIT production from the
metabolism of intact glucoraphanin by E. casseliflavus NCCP-53 (Chapter 2, section 2.3.3). The
lack of NIT production from glucoraphanin may be due to inability of sulfatase of E. casseliflavus
NCCP-53, if any, to desulfate glucoraphanin to produce DS- glucoraphanin as a substrate for the
GH3 enzyme to produce NIT. The presence of the sulfoxide group of glucoraphanin may present
steric effects that make its hydrolysis by the GH3 enzyme difficult.
Figure 5.25 GC-MS chromatograms showing NIT production from DS-GSLs by the purified recombinant GH3 enzyme in NB broths. (A) No NIT product from DS-glucoraphanin by GH3 enzyme. (B) Erucin NIT, 1 was produced (17.44 min) from DS-glucoerucin by GH3 enzyme. (C) Phenethyl NIT, 2 was produced (18.57 min) from DS-gluconasturtiin by GH3 enzyme. All samples were incubated with the purified recombinant GH3 enzyme (100 µg) in NB broths (pH 7.0) for 16 h at 37˚C. The figures are representatives of triplicates.
It was found that erucin NIT production from DS-glucoerucin and phenethyl NIT from
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DS-gluconasturtiin (Figure 5.25B and 5.25C) by the recombinant GH3 enzyme were observed in
both NB broth and 0.1 M citrate phosphate buffer pH 7.0 with the presence of 1 mM Fe2+ and
Mn2+ with higher NIT products in NB broth (Table 5.12). No ITC products were detected as
expected. This result suggests that the presence of either Fe2+ or Mn2+ is required for NIT
production from DS-GSL hydrolysis by the recombinant GH3 enzyme in the buffer.
Table 5.12 NIT productions from DS-GSLs by GH3 enzyme
Substrate (500 µM) Product Nitrile production (µM)
Buffera LBb Fe2+ Mn2+ No ion
Desulfo-glucoraphanin ND ND ND ND
Desulfo-erucin ERN NIT 47.1 ± 4.06 63.9 ± 2.41 66.1 ± 3.56 Desulfo-gluconasturtiin PNIT 28.4 ± 7.76 43.3 ± 9.04 80.5 ± 1.57
a100 mM citrate phosphate buffer pH 7.0 with the presence of 1 mM metal ions. bLB broth pH 7.0 without any metal ion. Values are means ± SD of triplicates. ERN NIT, Erucin nitrile; PNIT, Phenethyl nitrile; ND, Not detected. 5.3.12 NIT production from intact GSLs by sequential action of the recombinant SUL2 enzyme
and the recombinant GH3 enzyme
It was reported that intact GSL was desulfated by H. pomatia sulfatase to produce DS-
GSL which was then hydrolyzed by the recombinant β-O-glucosidase from Caldocellum
saccharolyticum to produce D-glucose, sulfate ion and corresponding NIT product (Galletti et al.,
2008; Kopycki et al., 2011). To determine whether this holds true for both the recombinant GH3
enzyme and the recombinant SUL2, intact GSLs were used as substrates in the reaction tubes
containing these two enzymes in NB broths for 16 h at 30˚C. The NB broth was used in this
experiment as assumingly it contains any co-factors necessary for NIT production. The negative
controls containing either intact GSL alone or both enzymes alone showed no NIT product
suggesting that intact GSL was stable in experimental conditions and not degradable to NIT
(Appendix IV).
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Similar to the previous experiment (Section 5.3.10), erucin NIT production from
glucoerucin and phenethyl NIT from gluconasturtiin were observed (Table 5.13). There was no
NIT production from glucoraphanin (Table 5.13). However, the concentrations of NIT products
in this experiment (Table 5.13) were lower from those in Table 5.12. The lower production of
NIT may be due to the need for intact GSL substrates to be desulfated by the recombinant SUL2
enzyme in comparison with the readily available DS-GSL substrates used in the previous
experiments.
Table 5.13 Nitrile productions from glucosinolates by sequential action of the SUL2 enzyme and GH3 enzyme
GSL (1 mM) DS-GSL (µM)a NIT product NIT concentration (µM)b
Percentage product (%)c
Glucoraphanin ND ND ND ND
Glucoerucin 141 ± 5 (14%) Erucin nitrile 71 ± 8 50 ± 4
Gluconasturtiin 117 ± 5 (12%) Phenethyl nitrile 65 ± 9 55 ± 10
Reaction mixtures of each 1 mM glucosinolate substrate were incubated with purified GH3 enzyme (100 µg) and crude extracts of SUL2 enzyme (1000 µg) in 1 mL LB broths pH 7.0 for 16 h at 30˚C; ND, Not detected. Values are means ± SD of triplicates. aDesulfo-glucosinolates produced from desulfation of glucosinolates by crude extracts of SUL2 enzyme were determined by HPLC analysis. Numbers in brackets indicate the production of DS-GSL (mol) in (%) relative to the initial dose of GSL substrate (mol). bNitriles produced from desulfo-glucosinolates by rGH3 enzyme were determined by GC-MS anaylysis. cProduction of nitriles (nmol) in (%) product relative to the amounts of desulfo-glucosinolate intermediates (nmol) produced from glucosinolate substrates.
The DS-GSL production as a result of desulfation of intact GSL (1 mM) by crude extracts
of the recombinant SUL2 enzyme in the reaction tubes was shown to be 14 and 12% of the
initial amounts of glucoerucin and gluconasturtiin substrates, respectively (Table 5.13). This
result indicates that GSL-sulfatase activity of crude extract of the recombinant SUL2 enzyme can
be found as free enzyme in solution in a reaction tube and also as immobilized enzyme on the
DEAE-Sephadex column. The percentage NIT product from DS-GSL metabolism as a result of the
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reaction by the purified recombinant GH3 enzyme was shown to be 50 and 55% of the
corresponding DS-glucoerucin and DS-gluconasturtiin, respectively produced from the starting
intact GSL substrates by the recombinant SUL2 enzyme (Table 5.13). This suggests that the
sequential transformation from intact GSLs to DS-GSLs by SUL2 enzyme and then from DS-GSLs
to NITs by GH3 enzyme was possible, but far from 100% efficiency.
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5.4 Summary of key findings
The summary of key findings in this chapter is shown in Figure 5.26:
Figure 5.26 Reaction catalyzed by the recombinant enzymes SUL2 and GH3.
5.5 Discussion
In this work, bacterial recombinant sulfatase from human gut bacterium with GSL-
sulfatase activity that can desulfate intact GSLs to produce corresponding DS-GSLs was reported
for the first time. Also, it was the first report to show bacterial recombinant β-glucosidases of
GH3 glycoside hydrolase family from another human gut bacterium with hydrolytic activity
towards DS-GSLs that produces corresponding NIT products. The sequential reactions of both
recombinant sulfatase and GH3 enzymes derived from different bacterial origins to desulfate
GSLs and produce DS-GSL for NIT production were reported for the first time.
The recombinant SUL2 enzyme expressed in E. coli BL21(DE3), which was originally
cloned from a human gut bacterium E. coli O83:H1 NRG 857C, was purified as a soluble and
active enzyme with the purity of 61% and has the molecular weight of 57 kDa by SDS–PAGE as
predicted. This enzyme is a member of a highly conserved sulfatase family as defined by a
signature sulfatase domain located toward its amino terminus. This protein is soluble in the cell
crude extracts suggesting its location at the periplasmic space or in the cytosol which is
consistent with the previous observations of bacterial arylsulfatases in Alteromonas
carrageenovora (Barbeyron et al., 1995) and Pseudomonas C12B (Fitzgerald & George, 1977).
Thus far, nearly all active, recombinantly expressed sulfatase reported in the literature
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possesses a Cys within the active site sequence. Therefore, it seems likely that a Cys-specific
modifying machinery functionally exists in E. coli host. Although E. coli BL21(DE3) carries at least
one sulfatase-related gene, the aslA gene (Sofia et al., 1994), this species has not yet been
found to express active endogenous sulfatases. Conversion of Ser to FGly is catalyzed also by E.
coli as Klebsiella sulfatase can be expressed in E. coli as an active enzyme
To date, no bacterial sulfatase with GSL-sulfatase activity has been identified and
characterized. Notably, bacterial sulfatases appear to not generally accept GSLs as substrates (U.
Wittstock and B.A. Halkier, unpublished results). Also, only a little DS-sinigrin was produced
after 6 h or 12 h of incubation of sinigrin with rat intestinal microbiota suggesting its
glucosinolate-sulfatase activity, if any, may have a very low specificity toward sinigrin (Lu et al.,
2011). However, the recombinant SUL2 enzyme in crude extracts was found to be able to
desulfate different intact GSLs to different degrees. Pure NIT production can be obtained
without the formation of ITCs from DS-GSLs hydrolyzed by the recombinant GH3 enzyme of E.
casseliflavus NCCP-53. In addition, pure NIT production can be obtained from intact GSLs
hydrolyzed by the sequential action of the recombinant SUL2 enzyme in crude extracts and the
recombinant GH3 enzyme. Although these two enzymes are of two different bacterial origins,
they seemed to work in concert to produce pure NIT products. This indicates that the functional
redundancy may exist across different strains of human gut bacteria. This sequential action of
both bacterial sulfatase and glycosyl hydrolase procedure seems to be easily applied for
producing NITs, which looks appealing both as starting building blocks for synthesizing new
bioactive structures, and as important analytical standards. For example, in a recent report, the
sequential action of two recombinant enzymes, a sulfatase from H. pomatia and a β-O-
glucosidase from Caldicellulosiruptor saccharolyticus on GSLs allowed synthesis of
thiohydroximates (TH) from a structurally broad array of abundant precursors including
homochiral compounds of demonstrated biological activity (Kopycki et al., 2011). This
chemoenzymatic synthetic route would allow access to many of the thiohydroximate core
structures of the 200 known naturally occurring GSLs, if not all. The enrichment of this group for
compounds can have possible pharmacological potential.
Similar to the Schistocerca gregaria (desert locust) sulfatase and H. pomatia (snail)
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sulfatase, the recombinant SUL2 enzyme was able to desulfate both the synthetic substrate
pNCS (in its partially purified fraction) and the natural GSL substrates (in its crude extracts),
indicative of arylsulfatase activity as well as GSL-sulfatase activity. The desert locust sulfatase
displayed a sharp pH optimum at 6.5 (range tested: 2.5–11; half-maxima: 5.8 and 7.7) for
arylsulfatase activity (Falk & Gershenzon, 2007) while snail sulfatase has a pH optimum at 7.2
and temperature optimum at 30˚C. Likewise, the partially purified recombinant SUL enzyme
exhibited optimal arylsulfatase activity at a similar pH and temperature at pH 6.0 and 30˚C,
respectively. In general, bacterial arylsulfatases can be categorized into two groups on the basis
of the pH optimum, with one group showing optimal activity at pH values of 6.5–7.1, and the
group at higher pH values of 8.3–9.0 (Kertesz et al., 1993; Kertesz, 1999). Arylsulfatases from
Salmonella typhimurium (Henderson & Milazzo, 1979) and Klebsiella pneumonia (Okamura et
al., 1977) have their optimal pH values of 6.7 and 7.5, respectively, falling into the first group,
whereas arylsulfatases from Pseudomonas aeruginosa (Beil et al., 1995) and Pseudomonas
testosterone (Tazuke et al., 1998) were classified as the second group. However, the
recombinant SUL2 enzyme in this study displayed its maximal activity at pH 6.0, which does not
fall into either group.
The arylsulfatase activity of the recombinant SUL2 enzyme was not influenced by metal
ions indicating that it does not need metal ions during the desulfating of pNCS substrate. This is
different from a bacterial sulfatase from Pseudoalteromonas carrageenovora with its
arylsulfatase activity promoted by Mg2+ ion (Kima et al., 2005). Also, arylsulfatase activity is
increased by Ca2+, a co-factor found in most of the active sites of sulfatases studied thus far
(Bond et al., 1997; Lukatela et al., 1998; Hernandez-Guzman et al., 2003; Boltes et al., 2001).
However, arylsulfatase activity of the recombinant SUL2 enzyme was inhibited by Na2HSO4 and
Na2SO4. This is in accordance with the previous report that snail sulfatase was inhibited by
K2SO4 when using p-nitrophenyl sulfate (pNPS) as a substrate (Roy & Williams, 1989). Similarly,
the desert locust sulfatase activity was inhibited strongly by Na2SO3 and slightly by Na2HPO4
and NaF (Falk & Gershenzon, 2007).
The recombinant SUL2 enzyme in crude extracts was noticeably much less efficient in
GSL desulfation than snail sulfatase and desert locust sulfatase. For GSL-sulfatase activity of the
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latter two sulfatases, there seems to be no discrimination between different GSLs, and all are
desulfated at similar rates irrespective of the nature of the side chain. Interestingly, the
recombinant SUL2 enzyme desulfated intact GSLs tested in this work with much less efficiency
especially on GSLs with the more polar side chain such as glucoiberin. These differences may lie
in the different mechanisms in GSL metabolism in these three organisms. Desert locusts possess
a GSL-sulfatase in their alimentary canal, which catalyzes the cleavage of the sulfate group
efficiently from all GSLs tested, rendering them inert to myrosinase activity. The resulting DS-
GSLs are excreted in high quantities in the feces. GSL sulfatase was first described for larvae of
the diamondback (DMB) moth, Plutella xylostella (Ratzka et al. 2002). Both DMB and desert
locust sulfatases have broad specificity for aliphatic, indolic, and aromatic GSLs. The snail, as a
generalist herbivore, also possesses a GSL-sulfatase activity in its gut, but it is unclear whether
this enzyme is able to detoxify GSLs when the animal feeds on cruciferous plants (Ratzka et al.
2002). Human gut bacteria, however, may have a sophisticated system to deal with toxicity of
ITC products. Therefore, there is no need for bacterial sulfatase to be as efficient as sulfatases
found in locust and snail. In addition, it may well be that recombinant SUL2 enzyme was only
partially maturated (by posttranslational modifications) and thus the low GSL-sulfatase activity
of the enzyme. From the previous report, C. perfringens sulfatase expressed in E. coli BL21(DE3)
was only partially maturated as a large amount of the non-maturated peptide was detected
(Berteau et al., 2006) and this explained its low arylsulfatase activity. To determine whether the
rescombinant SUL enzyme undergoes the posttranslational modification of the Cys residue to a
FGly, matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) analysis is needed
for further experiments as previous performed (Schmidt et al., 1995; Dierks et al., 1997).
Interestingly, when the catalytic efficiencies (Kcat/Km) of various substrates were calculated for
desert locust sulfatase, the GSL-sulfatase activity is much more efficient (19.6 for sinigrin and
6.8 for (S)-2-hydroxy-3-butenyl GSL than the arylsulfatase activity (Vmax/Km = 0.017) on pNCS
substrate (Falk and Gershenzon, 2007). Snail sulfatase, on the other hand, has very similar
arylsulfatase and GSL-sulfatase activities for several substrates (Roy & Williams, 1989). In
contrast, our results showed that arylsulfatase activity for pNCS substrate (Kcat/Km = 6.36 x 105)
of the recombinant SUL2 enzyme was much more efficient than GSL-sulfatase activity (1.02 for
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sinigrin, 0.502 for gluconasturtiin and 0.314 for glucoiberin). This also suggests that the
presence of the more polar side chain of GSL i.e. glucoiberin may result in a very low efficiency
of GSL sulfatase activity of the recombinant SUL2 enzyme in desulfating this particular GSL.
The native SUL2 enzyme was found to be constitutive. This finding is in agreement with
the previous study showing that snail sulfatase is constitutively expressed (Falk & Gershenzon,
2007) and so is bacterial sulfatase of C. perfringens (Berteau et al., 2006). However, there is no
report on the inducibility of bacterial β-O-glucosidases to date. The physico-chemical properties
of recombinant β-O-glucosidase/glycosyl hydrolase are different from those of myrosinase,
which is a β-thioglucosidase. Myrosinase showed weak activity on the synthetic substrate pNPG,
however it was totally inactive towards DS-GSLs (Palmieri et al., 1987). Interestingly, the
recombinant GH3 enzyme discovered in this work was able to catalyse both the β-O-glucosidic
bond on pNPG substrate and also the β-thioglucosidic bond on certain DS-GSL substrates
obtained by sulfatase-assisted desulfation of natural intact GSLs (Chapter 2, section 2.2.4). This
finding clearly shows that this recombinant enzyme was able to catalyze the hydrolysis of not
only aryl-glycosides and disaccharides containing O-glucosidic bonds as previously reported
(Plant et al., 1988), but also a β-thioglycosidic bond, in contradiction with what was claimed in
the above-mentioned report. It was also shown that a series of DS-GSLs was transformed into
the corresponding NITs without any formation of ITCs or other products by exploiting this
glucosidase-catalyzed hydrolysis. Our result is in accordance with the reported use of
recombinant β-O-glucosidase derived from the thermophile bacterium Caldicellulosiruptor
saccharolyticus in generating NITs from DS-GSLs (Wathelet et al. 2001). NIT production from
DS-GSLs by the recombinant GH3 enzyme was detected in NB broth and the buffer with the
presence of Fe2+ ions. In Chapter 2, NIT production was not detected when the metabolism of
intact GSL by bacterial resting cells was carried out in the citrate phosphate buffer pH 7.0 unless
Fe2+ ions are present. These results proved that the recombinant GH3 enzyme requires Fe2+ ions
to hydrolyze DS-GSLs for NIT production, and DS-GSLs seem to be intermediates in GSL
metabolism. This is different from the previous report that NIT production from DS-GSL by the
recombinant β-O-glucosidase from C. saccharolyticum was found in 50 mM sodium phosphate
buffer pH 6.0 without the presence of Fe2+ ions (Wathelet et al., 2001). The recombinant GH3
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enzyme belongs to glycosyl hydrolase family 3 while the recombinant β-O-glucosidase derived
from Caldocellum saccharolyticum belongs to glycosyl hydrolase family 1. The differences in the
structures and origins of these two enzymes may explain the different requirement of metal
ions in their activity/mechanism of NIT production. The recombinant β-O-glucosidase of C.
saccharolyticus was capable of hydrolyzing a wide range of substrates (Love et al. 1988) and
able to generate NITs from DS-GSLs (Wathelet et al. 2001). Using DS-sinigrin as a substrate, the
maximum enzyme activity was found at pH 6.2 and in the temperature range of 65-70˚C.
To conclude, this is the first report of characterization of the bacterial sulfatase SUL2
with both GSL-sulfatase activity and arysulfatase activity. This is also the first report showing
that two bacterial enzymes of different origins, SUL2 enzyme from E. coli O83:H1 NRG 857C and
GH3 enzyme from E. casseliflavus NCCP-53 were able to work in concert to produce NIT
products from certain intact GSLs. The GH3 enzyme was characterized in this work and was
shown to be able to hydrolyze certain DS-GSLs to NIT products. This finding showed that human
gut microbiota is a valuable source for discovery of new enzymes.
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Chapter 6: General Discussion 6.1 Summary of findings To date, the mechanism of GSL degradation in human gut bacteria still remains elusive
and very little is known about the proteins involved in the bacterial metabolism of GSLs.
Therefore, this study was aimed to enhance our understanding of the influence of human gut
bacteria on the metabolic fate of GSLs. It was also aimed to identify bacterial proteins involved
in the metabolism of GSLs and to characterize these proteins at a molecular and a biochemical
level. This was achieved by a series of experiments (i) time-course fermentation of different
GSLs and DS-GSLs by human gut bacteria; (ii) 2-DE-based proteomics analysis; (iii) molecular
cloning of putative genes of interest; and (iv) protein purification and in vitro enzyme activity
assays.
In Chapter 2, six GSL-metabolizing bacterial strains isolated from human faecal sample
were reported for GSL-degrading capacity. Most bacteria were capable of producing both NITs
and ITCs from GSLs however Enterococcus sp. C213 while Enterococcus faecium KT4S13
produced only NITs. The three bacteria studied in this work, L. agilis R16, E. casseliflavus NCCP-
53 and E. coli O83:H1 NRG 857C, were able to metabolize a range of GSLs with different
efficiencies. These results underscore the importance of human gut bacteria in digestive ITC
formation from GSL degradation. Inter-individual differences in the appearance of bacterial
strains exhibiting myrosinase activity may result in very different hydrolytic activities, and lead
to apparent discrepancies in ITC exposure among humans (Holst & Williamson, 2004). In the
same chapter, the putative bacterial GSL-degrading enzymes responsible for producing NITs
and ITCs are inducible by GSL in the resting cells experiments. NIT production by bacterial cells
was only found during bacterial fermentations of GSLs in culture broths. However, NIT
production by bacterial resting cells did not occur in the buffer unless Fe2+ ions as co-factors are
present. These metal ions are likely to be a pre-requisite for NIT production in the buffer. In
Chapter 4 and Chapter 5, the recombinant SUL2 enzyme in crude extracts was found to exhibit
GSL-sulfatase activity that desulfates intact GSLs to produce DS-GSLs which then act as
substrates for the recombinant GH3 enzyme of E. casseliflavus NCCP-53. The product of this
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sequential enzymatic hydrolysis of intact GSL by these two enzymes of different bacterial
origins was pure NITs. This indicates that the mechanism of GSL metabolism may be very similar
among certain bacteria. Interestingly, E. coli O83:H1 NRG 857C produced methylthioalkyl ITCs
and NITs from methylsulfinylalkyl GSLs while E. casseliflavus NCCP-53 produced only
methylsulfinylalkyl ITCs from the same GSLs. This is explained by the presence of cytosolic
reductase enzyme in E. coli O83:H1 NRG 857C that reduces the sulfoxide group of GSLs to the
sulfide group. This GSL bioconversion is believed to facilitate further degradation to ITC and NIT
products by bacterial myrosinase-like enzyme or bacterial GSL-degrading enzyme. Since this
reductase enzyme was inducible by GSLs, it is hypothesized that there may be a sensor protein
that recognizes the structure of GSLs and leads to the expression of reductase. Likewise,
myrosinase, which is also inducible by GSL, may have a sensor protein to recognize the
structure of GSL which then leads to myrosinase expression. The proposed schematic
presentation of sulfoxide reduction on methylsulfinyl GSL by bacterial reductase and GSL
degradation by myrosinase of E. coli O83:H1 NRG 857C is shown in Figure 6.1.
Figure 6.1 Proposed scheme of myrosinase and reductase of E. coli O83:H1 NRG 857C induction by GSL. The GSL sensor protein may recognize the moiety of the GSL structure and then leads to to the transcription of myrosinase-like enzyme to degrade GSL(s) into ITC/NIT product(s) and possibly also leads to the transcription of reductase to reduce the sulfoxide group (if any) on GSL to the sulfide.
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The schematic presentation of GSL and DS-GSL metabolism by human gut bacteria and
by the characterized bacterial recombinant SUL2 and GH3 enzymes under various conditions is
shown in Figure 6.2.
Figure 6.2 Summarized scheme of GSL/DS-GSL metabolism by human gut bacteria and by bacterial recombinant enzymes under various conditions. (A) Bacterial fermentations in culture broths. (B) Bacterial resting cells in 0.1 M citrate phosphate buffer pH 7.0. (C) Recombinant enzymes SUL2 and GH3 in buffer and broth. Putative enzymes are indicated in italic and characterized enzymes are in capital. ECO, E. coli O83:H1 NRG 857C; EC, E. casseliflavus NCCP-53.
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From the cell-free extract experiments in Chapter 2, bacterial cell-free extracts showed
no myrosinase activity in vitro. Instead myrosinase activity was exclusive in intact cells in
fermentation/resting cell experiments suggesting that bacterial GSL-degrading enzyme activity
is membrane/cell-associated. Hypothetically, GSLs, as β-glucosides, may need to be
phosphorylated by phospho-kinases prior to degradation by myrosinase. The lack of
phosphorylation on GSL substrates used in vitro may explain the absence of myrosinase activity
in the cell-free extracts. Assumingly, bacterial phosphorylation system was no longer intact and
hence inactive.
The phosphoenolpyruvate (PEP)-dependent phosphotransferase system (PTS) is crucial
for carbohydrate acquisition in many bacteria (Postma et al. , 1993). The PTS involves several
proteins with a role in transportation of PTS-dependent carbohydrates in both Gram-positive
and Gram-negative bacteria. The PTS components consist of a heat-stable histidine protein
(HPr), a non-specific Enzyme I (EI) and a sugar-specific membrane associated Enzyme II (EII)
(Postma et al., 1993) with two cytoplasmic domains, EIIA and EIIB, and an integral membrane
domain EIIC (Saier et al., 1988). It is clear that the utilization of common dietary carbohydrates
has been facilitated by the PTS, but its role in β-glucoside utilization is much less clear (Cote et
al., 2000). Foods containing plant extracts tend to contain β-glucosides, such as salicin, arbutin,
esculin and cellobiose. The translocation of these β-glucosides has been associated with the PTS
in certain bacteria including B. subtilis, E. coli, C. longisporum and E. chrysanthemi (Brown &
Thomson, 1998; Fox & Wilson, 1968; Hassouni et al., 1990; Le Coq et al., 1995).
It was discovered that BglK as a β-glucoside kinase (EC 2.7.1.85), present in many
species of bacteria including K. Pneumonia (Thompson et al., 2002), is separate and distinct
from glucokinase (EC 2.7.1.2). The role of BglK is to phosphorylate β-glucoside, and this
phosphorylated product is a substrate for the phospho-β-glucosidase (P-β-glucosidase, EC
3.2.1.86). It was also found that P-β-glucosidase purified from Fusobacterium mortiferum
hydrolyzed several P-β-glucosides, including the isomeric disaccharide phosphates, cellobiose-
6-phosphate, gentiobiose-6-phosphate, sophorose-6-phosphate, and laminaribiose-6-
phosphate, to yield glucose-6-phosphate and appropriate aglycones (Thompson et al., 1997).
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Since GSLs are β-glucosides, it is thought that they may need to be phosphorylated by β-
glucoside kinase prior to being hydrolyzed by myrosinase which can recognize the
phosphorylation on GSL structure. There is also a possibility that myrosinase may be tightly
linked to the PTS system.
In Chapter 3, by using two-dimensional gel electrophoresis (2-DE) and liquid
chromatography mass spectrometry (LC-MS/MS) for the comparative analysis between GSL-
induced and non-induced cultures of L. agilis R16 and E. coli O83:H1 NRG 857C, upregulated
proteins that may be involved in the metabolism of GSLs by these bacteria were identified.
Some of those identified proteins belong to phosphotransferase system (PTS), glucokinase,
carbohydrate metabolism, glycosyl hydrolysis and oxidoreduction process. These results led to
the speculation that PTS system and/or β-glucoside kinase may be involved in the metabolism
of GSL and/or the activation of myrosinase in human gut bacteria.
From all the results in this work, the schematic presentation of GSL-metabolizing
mechanism in human gut bacteria has been proposed in Figure 6.3. In this scheme, the PTS
system catalyzes the synchronized uptake and phosphorylation of a GSL substrate. The PTS
comprises three proteins. In the cytoplasm, phosphoenolpyruvate (PEP) phosphorylates EI,
which then transfers the phosphoryl group to HPr. The phosphoryl group from HPr is
transferred to several EII proteins. Within EII, HPr donates the phosphoryl group to EIIA that
then transfers it to EIIB, whereupon EIIC initiates sugar translocation (Teplyakov et al., 2006).
This scheme also includes the roles of the bacterial reductase, sulfatase and glycosyl hydrolase
that were characterized in this work.
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Figure 6.3 Proposed schematic presentation of GSL-metabolizing mechanism in human gut bacteria. (A) The phosphoenolpyruvate (PEP): sugar phosphotransferase system (PTS). See texts for details. (B) Sulfoxide GSL is reduced by reductase to sulfide GSL which is phosphorylated by putative β-glucoside kinase prior to GSL degradation to NIT and ITC products by putative myrosinase. These products are released to outside of the cells. (C) GSL is desulfated by sulfatase to produce DS-GSL that is a substrate for glycosyl hydrolase/β-O-glucosidase to produce pure NITs.
Interestingly, a transporter seems to be required in both the sequestration of the GSLs
in the haemolymph and the transport of the GSL-3-sulfate in the gut of Athalia rosae sawflies
(Opitz et al., 2011). A successful transport through the gut epithelia, presumably through the
action of modified glucose transporter(s) may be determined by the chemical properties of the
sugar moieties of these GSL metabolites (Opitz et al., 2011). Nevertheless, very little is known
about the transport of glycosidically bound metabolites in insects (Kuhn et al., 2004; Discher et
al., 2009), no transporter has yet been identified. Similar to bacteria, how specific involved
transporter(s) function in these sawflies and how the glucosides are transported remain to be
determined.
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6.2 Future work
The results from this work have provided new interesting and important data for the
better understanding of GSL metabolism in human gut bacteria. However, there are more areas
that require further investigated as follows:
6.2.1 Identification of other GSL degradation metabolites from GSL metabolism
Since the total percentage products of all GSLs metabolized by the three bacteria never
reached 100% and the unaccounted loss was unknown, except for the instability of ITCs
(Chapter 2), this needs to be investigated further. Experiments like 1D and 2D TOCSY and gCOSY 1H NMR should be used both to elucidate the molecular structure of GSL derivatives and to
quantify the concentrations of metabolites. Different compounds of biochemical interest can
be analyzed simultaneously in NMR spectra, including GSL substrates and ITC/NIT degradation
products. Considering that the preparation of one sample takes 5 min and that recording a 1D 1H NMR spectrum and a 2D 1H NMR spectrum takes about 10 min and 60 min, respectively,
NMR spectroscopy is a very powerful technique and can be used routinely. Another advantage
is that this technique is without a priori hypothesis; consequently, unexpected metabolites,
such as the amine derivatives, can be detected. The 13C NMR can be also used for studying
carbon metabolism by the human digestive microbiota, using [6-13C] glucose/amino acid moiety
of a GSL as a substrate.
6.2.2 Further search for the putative bacterial GSL-degrading enzymes from other
bacteria
Since the gene encoding a bacterial myrosinase-like enzyme in human gut bacteria has
yet to be identified, a few approaches can be employed to identify bacterial GSL-degrading
gene/protein as follows:
(i) Mutants of GSL-degrading bacteria can be chemically or genetically created. These
mutants will be screened for lack of myrosinase activity. Based on the use of specific growth
media with sinigrin, a simple microtitre plate method (Bioscreen C system) will be developed.
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Myrosinase activity will be determined by following the decline in sinigrin concentration at
A230nm using a UV multiwell plate reader. By using this method, it will be possible to screen over
400 bacterial colonies. Those that show no myrosinase activity will be subject to genome
sequencing to identify the mutated gene that may encode for myrosinase.
(ii) The culture and sequence-independent approach of stable isotope probing (SIP) is
worth a try. SIP involves the 13C or 14C-labeling of the compound of interest; organisms able to
degrade the compound will assimilate the labeled carbon into their biomass (DNA, RNA, or fatty
acids). This provides a way to get at sequence and functional information from candidate
degraders (Radajewski et al., 2000). The 16S rRNA-based SIP can be used to assign metabolic
activities such as glucose and starch fermentation to specific members of the gut microbiota
(Egert et al., 2007; Kovatcheva-Datchary et al., 2009). SIP can also be used to monitor the
activity of specific members of the gut microbiota in response to changes in nutrient status by
monitoring de novo RNA synthesis (Reichardt et al., 2011).
(iii) Another strategy for screening microbial communities for genes involved in GSL
metabolism is a technique called substrate induced gene expression (SIGEX). SIGEX counts on
the fact that catabolic genes are often transcriptionally activated by their substrate (Uchiyama
& Watanabe, 2008) and in this case it is GSL. In SIGEX procedure, community DNA is extracted
from environmental samples, sheared to 5–10 kb in length, and then cloned into a green
fluorescent protein (GFP) expression vector. Fluorescence activated cell sorting (FACS) can then
be used to screen the resulting metagenomic library for clones that induce GFP upon growth in
media supplemented with GSL. This approach was successfully used to isolate a previously
characterized phenol degradation operon from Ralstonia eutropha, an organism isolated from
sludge, and aromatic-hydrocarbon responsive operons from petroleum-contaminated
groundwater (Uchiyama et al., 2004).
(vi) RNA-sequencing (RNA-seq) experiment can be performed to identify the genes with
transcriptional upregulation during GSL metabolism in human gut bacteria, and that may
potentially be a myrosinase gene. The traditional low-throughput expressed sequenced tag
(EST) sequencing by Sanger technology only detects the more abundant transcripts. However,
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this RNA-seq approach has initiated the revelation of the dynamics and complex landscape of
the transcriptome from yeast to human at an unprecedented level of sensitivity and accuracy
(Martin & Wang, 2011). A near-complete snapshot of a transcriptome, including the rare
transcripts that have regulatory roles, can be achieved by a typical RNA-seq experiment with
the massive sequencing depths (100–1,000 reads per base pair of a transcript). In contrast to
microarrays, base-pair-level resolution, a much higher dynamic range of expression levels, and
de novo annotation can also be achieved by RNA-seq (Martin & Wang, 2011).
6.2.3 Determination of whether GSL-6-P is a substrate for bacterial GSL-degrading
enzyme in vitro
It is hypothesized that phosphorylation of GSL may be a pre-requisite for its degradation
by bacterial GSL-degrading enzyme in cell-free extract experiments. To test this hypothesis, GSL
must be phosphorylated at the C6-glucose moiety either enzymatically or chemically to
generate GSL-6-P. To achive this, β-glucoside kinase (EC 2.7.1.85), extracted from K. Pneumonia
(Thompson et al., 2002) will be used to phosphorylate GSLs in the same manner it was done to
enzymatically phosphorylate β-glucosides, such as cellobiose, arbutin, salicin and esculin as
previously reported (Thompson et al., 2002). Although this has never been performed on GSLs
before, it is quite likely that β-glucoside kinase will phosphorylate GSL at C6. Interestingly, GSL
has a sulfate group in the aglycone, and this may present a problem for the simple procedure(s)
that was used to obtain other phosphorylated β-O-glycosides. Alternatively, chemical synthesis
would be an option although it would represent a challenging synthesis.
6.2.4 Purification of bacterial reductase
Since co-factors and optimal operating have been determined conditions for bacterial
reductase activity of E. coli O83:H1 NRG 857C, this will facilitate the purification of bacterial
reductase from its cell-free extracts. The cell-free extracts will be purified using ion-exchange
chromatography/gel filtration via FPLC machine. The collected fractions will be identified for
reductase activity upon the addition of NAD(P)H as a reducing co-factor plus Mg2+ ions. The
disappearance of NAD(P)H, as an indicator of reductase activity, can be monitored using UV/Vis
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spectrometer. Once the fractions containing reductase are identified, they will be analyzed and
purified by SDS-PAGE until a single band of interest is obtained. This protein band will be
subjected to protein identification. The amino acid sequence will lead to the identification of
the gene responsible for bacterial reductase activity. Subsequently, the cloning of the gene will
be carried out followed by the characterization of the protein. This reductase enzyme may be of
importance for the reduction of xenobiotics.
6.3 Conclusion
This study has identified six bacterial strains from human gut microbiota capable of
degrading GSLs and producing ITCs and/or NITs as degradation products. Different product
profiles by different bacteria highlight the importance of human gut microbiota in contribution
to promote human health due to chemopreventive effects of ITCs. The mechanism of GSL
degradation by human gut bacteria has been made clearer owing to identification and
characterization of bacterial sulfatase, glycosyl hydrolase and reductase involved in the
metabolism of GSLs. These findings provide a better understanding of the role of human gut
bacteria on the metabolic fate of GSLs. This urges further exploration of human gut microbiota
as a source for novel metabolites and novel enzymatic activity.
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APPENDIX: APPENDIX I
A) Representative GC-MS chromatogram showing no degradation products from the negative control containing only GSL substrate without bacterial cells or only bacterial cells without GSLs incubated in the culture broths for 24 h at 37˚C under anaerobic conditions.
B) Representative GC-MS chromatogram showing no degradation products from the negative control containing only DS-GSL substrate without bacterial cells incubated in the culture broths for 24 h at 37˚C under anaerobic conditions.
5 . 0 0 1 0 . 0 0 1 5 . 0 0 2 0 . 0 0 2 5 . 0 0 3 0 . 0 0 3 5 . 0 0 4 0 . 0 0
8 0 0 0
1 0 0 0 0
1 2 0 0 0
1 4 0 0 0
1 6 0 0 0
1 8 0 0 0
2 0 0 0 0
2 2 0 0 0
2 4 0 0 0
2 6 0 0 0
2 8 0 0 0
3 0 0 0 0
3 2 0 0 0
3 4 0 0 0
3 6 0 0 0
3 8 0 0 0
4 0 0 0 0
4 2 0 0 0
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5 . 0 0 1 0 . 0 0 1 5 . 0 0 2 0 . 0 0 2 5 . 0 0 3 0 . 0 0 3 5 . 0 0 4 0 . 0 0
1 0 0 0 0
1 5 0 0 0
2 0 0 0 0
2 5 0 0 0
3 0 0 0 0
3 5 0 0 0
4 0 0 0 0
4 5 0 0 0
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APPENDIX II List of gene sequencing results from the recombinant plasmids used in this work SUL2 gene >9643339.seq - ID: SUL2-T7 on 2012/5/10-11:58:12 automatically edited with PhredPhrap, start with base no.: 10 Internal Params: Windowsize: 20, Goodqual: 19, Badqual: 10, Minseqlength: 50, nbadelimit: 1 ctcnnaAAAtaTTTTtGTTTtACTTTAagnaggagaTATACCatgGGcAGCAGCcatcatcatCATcATCACAGCAGCGGCctGgtGCCGCGCGGCAGCCAggtCATATgAAACGCCCCAATTTTCTGTTCATCAtgACCGATACCCAGGCCACCAATATGGTCGGtTgCTATagCggtAAGCCGctgAATACGCAAAATATTGATAGTCTGGCGGCGGAAAGTATTCGCTTTAATTCCGCCTACACctgTTCACCGGTTTGTACACCTGCACGCGCCGGACTATTCACCGGTATCTACGCTAACCAGTCCGGCCCGTgGACCAACAACGTCGCGCCGGGCAAAAACATTTCCACCATGGGGCGCTACTTTAAGGATGCGGGCTATCACACCTGCTACATCGGCAAATGGCATCTCGATGGACATGACTATTTCGGCACTGGCgaGTGTCCGCCGGAGTGGGACGCtGATTACTGGTTCGATGGAGCGAACTATCTTAGTGAACTGACGgAGAAAGAGATTAGCCTGTGGCGCAATGGCCTAAACAGCGTtgAGGATTTACAGGCGAACCATATTGACGAAACCTTCACCTGGGCGCACCGCATCAGCAATCGGGCGGTGGATTTTCTGCAACAGCCCGCGCGCGCCGACGAACCTTTCCTGATGGTGATTTCGTATGATGAGCCGCATCACCCGTTCACCTGTCCGGTGGAGTATTTAGAGAAATACACTGATTTTTACTACGAACTGGGTGAGAAAGCAGAGGATGACCTGGCGAACAAACCGGAACATCACCGCTTATGGGCGCAGGCGATGCCATCGCCAGTCGGTGATGACGGGCTTTATCACCATCCGCTCTATTTTGCCTGCAATGACTTTGTTGATGACCAAATCggACGGGTCATCAACgccTTAACGCCAGagcAACGTGAAnATACGtGGGGTTATTTATACcnccnaTCACGGCGAAaatGATGGggcGCa GH3#1 gene >6831964.seq - ID: GH3/1-T7 on 2010/8/19-5:41:18 automatically edited with PhredPhrap, start with base no.: 21 Internal Params: Windowsize: 20, Goodqual: 19, Badqual: 10, Minseqlength: 50, nbadelimit: 1 AATCGGCCAATTGGTGCAGTTATCTGGAGAATTCTTTCACngnnncGatTTGTCTTTGGGTCCTCAGCAAAAACTTGGCATCGAACAACAAACCATCGATGTTGTCGGTTCGGTATTGAACGTCACAGGTGCCCAAGTAACTCGAAAGATTCAAACAGACTACTTAAGAAAAAGTCGACACAAAATCCCACTATTGTTCATGGCAGATATCATCTATGGATACCGAACAGTCTTTCCGATCCCTCTGGGATTGGGAGCAACCTGGAATCCAGCATTGATTCAAAGCGCCTATCAAGCCGCAGCACAAGAAGCAAGAGCGGCTGGCGCACACGTAACATATGCACCAATGGTCGACTTAGTACGCGATGCTCGATGGGGGCGATGCTTGGAGTCGACAGGAGAGGATCCGCTGCTAAATGCTGATTTTGCGAAAGCAATGGTAGAAGGCATTCAGCAAGAAAAAGGGGGAACACTGCTCGGAATCGCTGCCTGTGTTAAACATTTTGCTGCTTATGGTGCAGCAGAAGGGGGACGAGATTATAATACAGTTGATATGAGCGAACGCAAACTGCGTCAAGACTACTTAAGCGGCTATAAAGCGGCTGTCGaGGCTGGATGCAAACTAGTCATGACTTCTTTTAACACGTATGATGGTATTCCCGCTACtGCTAATCAATTTTTGATCAAACAAATTTTAAGAgAAGAntGGCAGTTTGATGgAgTCGTTATTTCgGATTATGCAGCTGTtCAAGAnTTAaTTCCTCATGGGAtTGCTGCGGAtGATCgAgAAgCGGCCAAATTAgCGATCGAAgCAaCAAAtGAcaTCGATATGAAAACCcGATGttaTGCgAAAnAnCttCntCcGCTGCtGgaAagtGGt GH3#3 gene >6831966.seq - ID: GH3/3-T7 on 2010/8/19-5:41:18 automatically edited with PhredPhrap, start with base no.: 20 Internal Params: Windowsize: 20, Goodqual: 19, Badqual: 10, Minseqlength: 50, nbadelimit: 1 cGATCaGTTGCTGCAaCTgGCAGCGGCTTTTTATTCAGATaannnnnaAgAgAAAACAGGTCCGATGGGCGACTTAGGACTGACACAAGAAAACATCAACAACGCGGGAACAACGCTAGGTGTTTCTGGTGCAAAAGAAGCGATCCGCGTCCAAAAAGAGTATATCGCCAATAACCGCTTGAATATCCCGACGATATTGATGGCGGACATCATTCACGGCTTTCGGACGATTTTCCCGATTCCATTAGGATTAGGTAGTTCATGGGATTTGGCAGCAGCGGAGAAAATGGCGGAAGTATCTGCCAAAGAAGCAGCTGTTTCTGGCTTGCATGTGACCTTTTCACCGATGGTGGACTTAGTAAGAGACCCA
355
CGCTGGGGCCGTGTCATGGAATCGACGGGGGAAGATCCTTACTTGAACAGTCGCTTCGCTGAAGCCTTCGTCAAAGGCTATCAAGGGGATGATCTGCGAACGGATTTCAACCGCGTGGCTGCTTGCGTCAAACATTTTGCGGCTTACGGTGCGGCTATCGGTGGTCGCGATTACAACACGGTCAATATGTCAGAACGCCAACTGCGAGAAAGTTATTTGCCAGGCTATAAAGCAGCCCTTGATGCTGGTGCTAAGCTGGTGATGACCTCCTTTAATACGGTAGACGGCATTCCAGCAACGGCCAATCGCTGGCTTTTCCGCGATGTTTTGCGAnAAGAATTCgGGTTTGAAGGcGTTGTGATCTCTGACTGGGCAGCaATCaAAGAAGTGATCGCTCAtGGcGCAnCGganGAtGAAAAACaTGCCGCTGAACTAnnCaTCAAgCTGGGGTCgAtATCnAGAtGAtGACna GH1 gene >6831968.seq - ID: GH1-T7 on 2010/8/19-5:41:14 automatically edited with PhredPhrap, start with base no.: 12 Internal Params: Windowsize: 20, Goodqual: 19, Badqual: 10, Minseqlength: 50, nbadelimit: 1 GttgGgnntCtccaTaTGGTCgacCTGCagGCGGCCGCGnATTCACTAGTGATTCCaGagCTCTTAAATAATCGTTTTGGTTTCACTGACCAACTTGTACCAGTAAGCTGATTCTTTTGGGTAACGCTTCTGGGTTTCAAAATCAACATAAAACAAGCCATACCTTTTGTTATACCCATTTGTCCATGAGAAAAGATCCATAAGCGACCACAAAAAATACCCCTTCACATTTACCCCGGCTGTTATCACCTTGCTTAAGGATTCCAAATAGACTCTCAAATAGTCGATTCTCGGCTGATCCATAATAATGCCATCTTCAAACTGATCTTTATACCCCATCCCGTTCTCAGTGATATAGATTTTGTTGTAATGTGGGTAATCGCTTTTAATTCGCAGCAACAAGTCATATAGACCTTCTGGATAAATCAGCCAGTCCCAAACAGTTCGAGGAATTCCTTCTTTATAAATACGTTCTCCGATTCCCTTCACTTTATAAACAGAGGTCCCTTTTTCACCCGTACCGTTATGATGGATTGCATTTTCTCCATCGTAAGCTTTGACAAAATGGCATTGGTAGTGATTGATCCCTAAGTAGTCATTACGTGTGGATGCTTTTTTCAATTCAACGAAACCTTCTTCAGGAAAATGATAGCTGGCCTGATTTGCTTCACATATCTCATCAAGAGCAGTCAAGGTTTCAGTTGAATAATAGCCTAAATAGGTAGCATCTAATAAGAAACGGATCGACAATGCATCGTCTAAAAAGGCAGCATGCTTATCTTCCGGCGCGTCTGTTGCCGCATATTTCGTCTCTAATGAGTGAACTACACCAATTTCACCCGGAAGTTCGTTTTCTTTGAAATAGTTCACTACACGGGCATGAGCAACCATCATATTATGAAGACAGGCGACGATCCTTGTAAAATCATATTTGATTCCTGGTgGGAAAACACCTAACAAAtATTGATTGGTTGCAACTGGatagaTTTCATTAAAGGTACTCCacaCCTTGACTTCTTTGAATTCATGAAAAcaAAAAATGGCATAGGAAacaAATGCTTCTATTGTTtnnnGATTCAAAAatctcCATGGTCAannAACGTTTAGGGGTatcnAAATGatgca GH3#2 gene >6831971.seq - ID: GH3/2-T7 on 2010/8/19-5:41:14 automatically edited with PhredPhrap, start with base no.: 21 Internal Params: Windowsize: 20, Goodqual: 19, Badqual: 10, Minseqlength: 50, nbadelimit: 1 AnTatTTTGTTTaCTTTAnGAnGGagaTaTaCCATGGGCAGCAGCcnncAtCaTCATcATCACAGCAGCGGCCTGGTGCCGCGCGGCAGCCATATGGTGACAACCAAGCAATGATTGGTTTATGGGCAGTACACGGAAAAACAGAGGATGTCACAACATTAAAAACGGCGCTCCAAAATACAGTGTCGGAAAAATATGTTCATTACGAACCAGGTTGTCCGCTTTTAGAAGATGATTCTATACTTGGAGACTTTGGCTATACTGCCAGCGGCAATTCCTCATCAGCTGCACAGCAAGATCTTTGGCTGAAAGAAGCGTTGAAAGCTGGCACTGAGGCAGACATTATTCTTTTTGCTATGGGGGAACACAGTTTGCAAAGTGGGGAAGCTGGCAGTCGAACGTAAGAGCTCCGTCGACAAGCTTGCGGCCGCACTCGAGCACCACCACCACCACCACTGAGATCCGGCTGCTAACAAAGCCCGAAAGGAAGCTGAGTTGGCTGCTGCCACCGCTGAGCAATAACTAGCATAACCCCTTGGGGCCTCTAAACGGGTCTTGAGGGGTTTTTTGCTGAAAGGAGGAACTATATCCGGATTGGCGAATGGGACGCGCCCTGTAGCGGCGCATTAAGCGCGGCGGGTGTGGTGGTTACGCGCAGCGTGACCGCTACACTTGCCAGCGCCCTAGCGCCCGCTCCTTTCGCTTTCTTCCCTTCCTTTCTCGCCACGTTCGCCGGCTTTCCCCGTCAAGCTCTAAATCGGGGGCTCCCTTTAGGGTTCCGATTTAGTGCTTTACGGCACCTCGACCCCAAAAAaCTTGATTAGGGTGATGGTTCACGTAGTGGGCCATCGCCCTGATAGACGGTTTTTCgcCCTTTGACGTTGGAGTCCACGTTCtTTAATAGTGGACTCTTgttCCaAACTGGAACAACaCTCAACCCTATCTCGGTcTATTCTTTTGATtnataAGGGAtTTTGCcgaTtTcGGCCTaTTGGTTAAAAAaTGagcTGATTtaacaAAAATTTAAcgnnaATTTTAAcAAAanntTAAcgcTTa
356
bgl gene >6831959.seq - ID: bgl-T7 on 2010/8/19-5:41:14 automatically edited with PhredPhrap, start with base no.: 21 Internal Params: Windowsize: 20, Goodqual: 19, Badqual: 10, Minseqlength: 50, nbadelimit: 1 cntggCGGCcgcGGgnaTTCGatTGGtTTGCcaTATGTTTCACACaAACTTAGATCCTTTCCCAGAAAACTTCTTATGGGGGGCAGCTTCGGCGGCCTATCAAATTGAAGGAGCATGGGCAGAAGACGGCAAAGGTCCGTCGATTTGGGACACCTATGCCCAAATTCCTGGCAATACTTTTGAGGAAACCAACGGCAAAGTGGCGATCGATCATTACCATCGATACAAAGAAGATATTGCCTTGATGAAGCAAATGGGCTTGAAAGCCTATCGCTTCAGCGTGGCGTGGTCGCGAATCTTGCCTGATGGCGAAGGCGCGGTCAATGAAGCGGGTGTGGCGTTTTACGAAAAGCTGGTGGATGAATTGCTTCGGCAAGGAGTAGAGCCGATTTTGACGCTGTATCATTGGGACCTTCCCCAGGCTTTGCAAGACAAATACTTAGGGTGGGAAGGTCGAGAAACAGCAGAAGCATTTGAACGGTATTGCCGGATCCTTTTTGAACGCCTAGGAAAGAAAGTCACCTATTGGGTCACCATGAATGAACAAAATGTCTTCACTTCTCTTGGGTACCGTTGGGCGGCACATCCGCCGGGCTTGAAGGACTTAAAACGGATGTATGCAGCCAATCATATCATCAACCTTGCCAATGCTAAGGCGATCAATTTGTTCCATGAGCTGGTTCCTCAGGGCAAGATCGGTCCAAGTTTTGGCTATGGACCGATGTATCCGTTTAGCTGTGACCCAGAAGATGTGCTGGCAGCAGAAAATGGCGAAGCCTTCAACAACGCATGGTTTTTAGATGTCTATTGCAAAGGTGAATACCCGAAATTTGTGTACAAGCAATTAGCCAAAGTTGGCTTgGCTCCTGAAGTCACTCCAGAAGATCAAGCACTATTAAAACAGGCAAAACCTGAtTTCTTAGgAATCAATTACTATCACGgtgGGACGGcCCAGCAAAACAATTTGCAAAAGCAGTCAGCTGAAAagaAagaAtTTTCTAAAGTcGaTTcgtAtTTGATGCAagcGGCAGCTGGtgagtTctcacCCGAagaaACCATgtTTGcgacaGcnnnAAATCCTcacTTGAannnAAcGGATTGGGGCTGGGaAAtngaTCCCGTTGGTTTccnt 6pbg1 gene >6831961.seq - ID: 6pbg1-T7 on 2010/8/19-5:41:18 automatically edited with PhredPhrap, start with base no.: 25 Internal Params: Windowsize: 20, Goodqual: 19, Badqual: 10, Minseqlength: 50, nbadelimit: 1 tggcgGCcgcgGgnaTTCGaTTGGtTTGCCATATGTTTcaCACaAACTTAGATCCTTTCCCAGAAAACTTCTTATGGGGGGCAGCTTCGGCGGCCTATCAAATTGAAGGAGCATGGGCAGAAGACGGCAAAGGTCCGTCGATTTGGGACACCTATGCCCAAATTCCTGGCAATACTTTTGAGGAAACCAACGGCAAAGTGGCGATCGATCATTACCATCGATACAAAGAAGATATTGCCTTGATGAAGCAAATGGGCTTGAAAGCCTATCGCTTCAGCGTGGCGTGGTCGCGAATCTTGCCTGATGGCGAAGGCGCGGTCAATGAAGCGGGTGTGGCGTTTTACGAAAAGCTGGTGGATGAATTGCTTCGGCAAGGAGTAGAGCCGATTTTGACGCTGTATCATTGGGACCTTCCCCAGGCTTTGCAAGACAAATACTTAGGGTGGGAAGGTCGAGAAACAGCAGAAGCATTTGAACGGTATTGCCGGATCCTTTTTGAACGCCTAGGAAAGAAAGTCACCTATTGGGTCACCATGAATGAACAAAATGTCTTCACTTCTCTTGGGTACCGTTGGGCGGCACATCCGCCGGGCTTGAAGGACTTAAAACGGATGTATGCAGCCAATCATATCATCAACCTTGCCAATGCTAAGGCGATCAATTTGTTCCATGAGCTGGTTCCTCAGGGCAAGATCGGTCCAAGTTTTGGCTATGGACCGATGTATCCGTTTAGCTGTGACCCAGAAGATGTGCTGGCAGCAGAAAATGGCGAAGCCCTCAACAACGCATGGTTTTTAGATGTCTATTGCAAAGGTGAATACCCGAAATTTGTGTACAAGCAATTAGCCAAAGTTGGCTTGGCTCCTGAAGTCACTCCAGAAGATCAAGCACTATTaAAACAGGCAAAACCTGATTTCTTAGGAATCAATTACTATCACggnngGGACGGcCCAGCAAAACAATTTGCAAAAGCAGTCAGCTGAAAagaAAgAATTTTCTAAAGTCgaTCCGTATTTGATGCAAGCGGCAGCTGGTgAGTTCtcacCCGAAgaAACCATgTTTGcgacaGCanaAAATCCTCacTTGAAAanaacgganntGGgnntgGGAnatcgnTcCCGTTGgtttcc 6pbg2 gene >6831963.seq - ID: 6pbg2-T7 on 2010/8/19-5:41:18 automatically edited with PhredPhrap, start with base no.: 22 Internal Params: Windowsize: 20, Goodqual: 19, Badqual: 10, Minseqlength: 50, nbadelimit: 1 cntggCGGccgcGGgnaTTCGaTTGGTTTGCCATATGTTTCACACaAACttAGATCCTTTCCCAGAAAACTTCTTATGGGGGGCAGCTTCGGCGGCCTATCAAATTGAAGGAGCATGGGCAGAAGACGGCAAAGGTCCGTCGATTTGG
357
GACACCTATGCCCAAATTCCTGGCAATACTTTTGAGGAAACCAACGGCAAAGTGGCGATCGATCATTACCATCGATACAAAGAAGATATTGCCTTGATGAAGCAAATGGGCTTGAAAGCCTATCGCTTCAGCGTGGCGTGGTCGCGAATCTTGCCTGATGGCGAAGGCGCGGTCAATGAAGCGGGTGTGGCGTTTTACGAAAAGCTGGTGGATGAATTGCTTCGGCAAGGAGTAGAGCCGATTTTGACGCTGTATCATTGGGACCTTCCCCAGGCTTTGCAAGACAAATACTTAGGGTGGGAAGGTCGAGAAACAGCAGAAGCATTTGAACGGTATTGCCGGATCCTTTTTGAACGCCTAGGAAAGAAAGTCACCTATTGGGTCACCATGAATGAACAAAATGTCTTCACTTCTCTTGGGTACCGTTGGGCGGCACATCCGCCGGGCTTGAAGGACTTAAAACGGATGTATGCAGCCAATCATATCATCAACCTTGCCAATGCTAAGGCGATCAATTTGTTCCATGAGCTGGTTCCTCAGGGCAAGATCGGTCCAAGTTTTGGCTATGGACCGATGTATCCGTTTAGCTGTGACCCAGAAGATGTGCTGGCAGCAGAAAATGGCGAAGCCTTCAACAACGCATGGTTTTTAGATGTCTATTGCAAAGGTGAATACCCGAAATTTGTGTACAAGCAATTAGCCAAAGTTGGCTTGGCTCCTGAAGTCACTCCAGAAGATCAAGCACTATTAAAACAGGCAAAACCTGATTTCTTAGGAATCAATTACTATCACGGTgGGACGGcCCAGCAAAACAATTTGCAAAAGCAGTCAGCTGAaAagaaagaAtTTTCTAAAGTCGaTCCGTATTTGATGCAancGGCancTGGTGagtTctcacCCGAagaAACCATgTTTGcgaCAGCAgaAAATCcTcacTTGAAanaaacGGattgggGCTGGGAnAtcgnTcCCGTTGGTTTcc pBgl gene >6831962.seq - ID: pBgl-T7 on 2010/8/19-5:41:14 automatically edited with PhredPhrap, start with base no.: 22 Internal Params: Windowsize: 20, Goodqual: 19, Badqual: 10, Minseqlength: 50, nbadelimit: 1 gaattcCCTCTagAnTatTTTGTTTaCTTTAnGAnGGagaTaTaCCATGGGCAGCAGCccncntnntcatCaTCACAGCAGCGGCCTGGTGCCGCGCGGCAGCCATATGTGCCGAGAAAAAAAGTCCTGTGTGGCTTTCAAAAAGTATGGGTGCCTAATCAAGGGCAAGTAGCTTTTCAACTCGTGATCGATGAAGCATCATTGCAGCAGCTGGCAATTTCTTTGAAAGATACTGCATCGTTTTGTCTGGAAGTCGAAACAGCAGGTCAGCAGTATCGATTTTTATTTCAACGATCCAACCCTGACCGTACGTGGCAGGTAACTCAGAAAGGAGCAAAAGAATGAGAGCTCCGTCGACAAGCTTGCGGCCGCACTCGAGCACCACCACCACCACCACTGAGATCCGGCTGCTAACAAAGCCCGAAAGGAAGCTGAGTTGGCTGCTGCCACCGCTGAGCAATAACTAGCATAACCCCTTGGGGCCTCTAAACGGGTCTTGAGGGGTTTTTTGCTGAAAGGAGGAACTATATCCGGATTGGCGAATGGGACGCGCCCTGTAGCGGCGCATTAAGCGCGGCGGGTGTGGTGGTTACGCGCAGCGTGACCGCTACACTTGCCAGCGCCCTAGCGCCCGCTCCTTTCGCTTTCTTCCCTTCCTTTCTCGCCACGTTCGCCGGCTTTCCCCGTCAAGCTCTAAATCGGGGGCTCCCTTTAGGGTTCCGATTTAGTGCTTTACGGCACCTCGACCCCAAAAAaCTTGATTAGGGTGATGGTTCACGTAGTGGGCCATCGCCCTGATAGACGGTTTTTCGCCCTTTGACGTTGGAGTCCACGTTCTTTAATAGTGGACTCTTGTTCCAAACTGGAACAACACTCAACCCTATCTCGGTCTATTCtTTTGATTTataAgGGATTTTGCCGatTTCGGCCTATTGGTTaAAAAATGagCTGATTTAACAAAAATTTAACGCgaATTTTAACAAAatatTAACGCTTAcAATTTAggngg
358
Appendix III
Representative HPLC chromatograms showing no DS-GSL production upon 8 h incubation of intact GSLs with crude extracts from BL21(DE3) on the DEAE-Sephadex column at 30˚C under aerobic conditions. Peaks between 20 and 30 min possibly correspond to dirt residues.
Appendix IV
Representative GC-MS chromatograms showing no NIT production in the negative controls containing DS-GSL alone, GSL alone, the GH3 enzyme alone, SUL2 enzyme alone or the two enzymes alone incubated in NB broth or in the buffer for 24 h at 30˚C under anaerobic conditions.
min5 10 15 20 25 30
mAU
45
50
55
60
65
ADC1 A, ADC1 CHANNEL A (F:\PHD\HPLC RAW DATA\SULFATASE\VIN160212SUL PHEN BEN\VIN16021201.D)
2.794
21.26
5 21
.647
22.53
5
24.60
9
26.02
1
5 . 0 0 1 0 . 0 0 1 5 . 0 0 2 0 . 0 0 2 5 . 0 0 3 0 . 0 0 3 5 . 0 0 4 0 . 0 0
1 5 0 0 0
2 0 0 0 0
2 5 0 0 0
3 0 0 0 0
3 5 0 0 0
4 0 0 0 0
4 5 0 0 0
5 0 0 0 0
5 5 0 0 0
6 0 0 0 0
6 5 0 0 0
7 0 0 0 0
7 5 0 0 0
8 0 0 0 0
8 5 0 0 0
9 0 0 0 0
9 5 0 0 0
1 0 0 0 0 0
1 0 5 0 0 0
1 1 0 0 0 0
1 1 5 0 0 0
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