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Discovery of antimicrobial peptides active against antibiotic resistant bacterial pathogens
A thesis submitted to the University of Manchester for the degree of
Doctor of Philosophy in the Faculty of Medical and Human Sciences
2015
Arif Felek
School of Medicine
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LIST OF CONTENTS
List of contents ....................................................................................................... 2
List of figures ......................................................................................................... 8
List of tables ......................................................................................................... 18
List of abbreviations ............................................................................................. 20
Declaration ........................................................................................................... 23
Copyright statement ............................................................................................. 24
Dedication ............................................................................................................ 25
Acknowledgements .............................................................................................. 26
Publications from this work ................................................................................. 27
1 Chapter 1 General Introduction .................................................................... 28
1.1 Downfall of novel antimicrobial discovery ........................................... 32
1.1.1 Movement of “big pharma” away from antimicrobial drug
discovery ....................................................................................................... 32
1.1.2 Overview of target based genetic approaches and their failure to
discover novel antibiotics ............................................................................. 34
1.2 Revitalising natural product screening as a source of novel antibiotics 36
1.3 Bacterially derived natural products of interest..................................... 39
1.4 Bacteriocins ........................................................................................... 41
1.5 Bacteriocins of Gram positive bacteria ................................................. 43
1.5.1 Class I - Lanthionine containing bacteriocins (Lantibiotics) ......... 43
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1.5.2 Class II non-lanthionine containing bacteriocins ........................... 48
1.5.3 Class III large proteins: .................................................................. 50
1.5.4 Class IV Cyclic peptides ................................................................ 51
1.6 Bacteriocins of Gram-negative bacteria ................................................ 52
1.6.1 Colicins .......................................................................................... 52
1.6.2 Microcins ....................................................................................... 54
1.7 Miscellaneous RiPP bacteriocins .......................................................... 58
1.7.1 Sactibiotics (Sulphur to α-carbon antibiotics) or sactipeptides ...... 58
1.7.2 Thiopeptides ................................................................................... 58
1.7.3 Bottromycins .................................................................................. 59
1.7.4 Glycocins ....................................................................................... 59
1.7.5 Linear azol(in)e-containing peptides (LAPs) and lasso peptides ... 60
1.8 Polyketides ............................................................................................ 61
1.9 Non-ribosomal proteins ......................................................................... 62
1.10 Lysins: ................................................................................................... 64
1.11 Advances in natural product screening.................................................. 65
1.11.1 Purification and identification of the active compound ................. 65
1.11.2 Identification of producer strains ................................................... 67
1.11.3 Genome mining and scanning for natural products ....................... 67
1.12 Aims and objectives .............................................................................. 72
2 Chapter 2 Methods ........................................................................................ 74
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2.1 In vitro antimicrobial peptide screening and characterisation ............... 75
2.1.1 Bacterial isolates ............................................................................ 75
2.1.2 Identification of the producer strains using 16S rRNA gene
sequencing .................................................................................................... 76
2.1.3 Agarose gel electrophoresis ........................................................... 78
2.1.4 Assays used for the assessment of antimicrobial activity .............. 78
2.1.5 Optimisation of antimicrobial peptide production ......................... 83
2.2 Proteomic analysis of the identified antimicrobial peptides.................. 84
2.2.1 Purification of antimicrobial peptides from the culture media ...... 84
2.2.2 SDS-PAGE analysis and gel diffusion agar overlay assay ............ 88
2.2.3 MALDI-ToF mass determination and ESI-MS scan of the RP-
HPLC Purified Active Fractions ................................................................... 89
2.2.4 De novo peptide sequencing (MS/MS) .......................................... 90
2.2.5 Genome sequencing and annotation of the draft genome of
producer strains ............................................................................................. 93
2.3 Characterization of the purified antimicrobial peptides ........................ 94
UV absorbing material leakage assay ........................................................... 95
2.3.1 Physicochemical analysis of purified antimicrobial peptides (heat
and enzyme stability tests) ............................................................................ 95
2.3.2 Determination of minimum inhibitory concentration .................... 96
2.3.3 Haemolysis assay ........................................................................... 96
2.3.4 Eukaryotic cell toxicity studies ...................................................... 97
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2.3.5 UV Absorbing material leakage assay ........................................... 99
2.4 In silico Genome mining and identification of putative bacteriocin leads
………………………………………………………………………...99
2.5 Cloning and expression methods ......................................................... 102
2.5.1 Insert construction and primer design for cell free protein
expression ................................................................................................... 102
2.5.2 In vitro cell-free expression ......................................................... 106
2.5.3 Proteomic analysis of peptide products generated following
expression studies ....................................................................................... 107
3 Chapter 3 Pumicin NI04, a novel antimicrobial peptide from Bacillus
pumilus, is homologous to the EsxA virulence determinant .............................. 108
3.1 Introduction ......................................................................................... 109
3.2 Results ................................................................................................. 113
3.2.1 Two antimicrobial agents are produced by B. pumilus J1 ........... 113
3.2.2 Bacteriocin production can be optimised by manipulation of
growth conditions ....................................................................................... 115
3.2.3 De novo peptide sequence determination of peptide NI04 using
mass spectrometry analysis and genome interrogation facilitates
identification of the pumicin NI04 locus .................................................... 117
3.2.4 Pumicin NI04 is stable to heat treatments and protease degradation
confirms a proteinaceous nature ................................................................. 125
3.2.5 Pumicin NI04 has potent activity against resistant Gram positive
pathogens .................................................................................................... 126
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3.2.6 UV absorbing material leakage assay .......................................... 127
3.2.7 Pumicin NI04 has low levels of in vitro toxicity ......................... 130
3.3 Discussion ........................................................................................... 132
4 Chapter 4 Discovery and Analysis Of Peptide NI05 produced by Klebsiella
pneumoniae strain A7 ........................................................................................ 141
4.1 Introduction ......................................................................................... 142
4.2 Results: ................................................................................................ 147
4.2.1 Simultaneous antagonism assays for preliminary analysis of the
antimicrobial activity spectrum of peptide NI05 ........................................ 147
4.2.2 Optimisation of antimicrobial peptide production ....................... 148
4.2.3 Purification ................................................................................... 149
4.2.4 Matrix Assisted Laser Desorption Ionisation – Time of Flight
(MALDI-ToF) mass determination ............................................................ 150
4.2.5 Genome sequence and annotation ................................................ 151
4.2.6 In silico analysis of the draft genome and discovery of the
MccE492 gene cluster:................................................................................ 152
4.3 Discussion ........................................................................................... 158
5 Chapter 5 Genome mining of anaerobic bacteria, known producer bacteria
and cell free expression of pumicin NI04 .......................................................... 166
5.1 Introduction ......................................................................................... 167
5.2 Results ................................................................................................. 170
5.3 Genome mining results ........................................................................ 170
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5.3.1 Lead 3 ........................................................................................... 176
5.3.2 Lead 12 ......................................................................................... 177
5.3.3 Lead 14 ......................................................................................... 178
5.3.4 Unique putative bacteriocin candidates ....................................... 178
5.4 Cloning Results ................................................................................... 181
5.4.1 Insert confirmation and validation following transformation ...... 182
5.4.2 In vitro expression of pumicin NI04 ............................................ 186
5.5 Discussion ........................................................................................... 188
Chapter 6 Concluding Remarks ......................................................................... 199
References .......................................................................................................... 205
Total words Count: 53,113
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LIST OF FIGURES
Figure 1.1 Timeline of antibiotic discovery versus outbreak of resistance among
bacteria [from (Clatworthy et al., 2007)] ............................................................. 29
Figure 1.2 The amount of antibiotics being introduced into the clinic has been
drastically decreasing in recent years [From (Boucher et al., 2013)] .................. 30
Figure 1.3 Graphical representation and comparison of the number of antibiotic
candidates going through clinical trials between 2011 and 2013 [from (Pucci and
Bush, 2013)]. ........................................................................................................ 31
Figure 1.4 The process of target based antimicrobial drug discovery [adapted
from (Mills, 2006; Pucci, 2007)]. ........................................................................ 34
Figure 1.5 Advantages of natural products (NP) as antibiotic drug leads ........... 36
Figure 1.6 Natural products of interest in the current project. The figure above
lists the natural products produced by bacteria that have the potential to be used
as antibiotics. These products are shortly reviewed in this study. ....................... 40
Figure 1.7 The "Universal” bacteriocin classification scheme. This figure by
Heng and Tagg, (2006) illustrates the two major classification schemes that are
used and how they propose to combine the respective advantages to construct a
universal scheme. ................................................................................................. 42
Figure 1.8 Bacteriocin mode of action. The class II bacteriocins such as sakacin
can insert into the cell membrane by interacting with membrane proteins and
cause pore formation and depolarisation of the cell membrane. The class I
bacteriocins on the other hand can have a single or multiple modes of action such
as nisin. Large protein bacteriocins such as lysostaphin can also act on the cell
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wall by hydrolysing the interpeptide bridges of the peptidogycan layer [adapted
from (Cotter et al. 2005)]. .................................................................................... 44
Figure 1.9 Four classes of the lanthipeptide family can be separated by the
modification enzymes involved in generation of their lanthionine bridges. Solid
lines indicate the conserved regions thought to play roles in the catalysis
including zinc ligands that are missing in class III [from (Knerr and van der
Donk, 2012)]. ....................................................................................................... 46
Figure 1.10 Class II-A bacteriocin action is dependent on the presence of IID
and IIC proteins, which are membrane proteins of the Man-PTS mechanism.
Class II a bacteriocin first binds to the extracellular loop and then to the
transmembrane helices of these peptides causing conformational changes that
leads to efflux and cell death [from (Kjos et al., 2011)] ...................................... 49
Figure 1.11 Mechanisms of cellular entry used by colicins. ExbB, ExbD
components in the TonB pathway are used by group B colicins and the Tol
pathway (TolA, TolB, TolQ and TolR) is employed by group A colicins [from
(Lloubès et al., 2012)]. ......................................................................................... 53
Figure 1.12 Class I microcin action. A) Microcin (Mcc) J25 gains access to the
cell through the outer membrane (OM) receptor FhuA and then utilises the
TonB/ExbB/ExbD complex and SbmA protein to translocate into the cytoplasm
where it inhibits transcription by attacking the RNA polymerase enzyme
(Mathavan et al., 2014). B) Mcc B17 targets the DNA gyrase enzyme that is
responsible for supercoiling of the DNA, it gains access to the inner membrane
(IM) using the OmpF porin on the OM and is translocated into the cell by
exploiting the SbmA protein. C) Although the entry mechanism of Mcc C7/C51
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is unknown, it acts by inhibiting aspartyl-tRNA synthetase [from (Duquesne et
al., 2007a)]. .......................................................................................................... 55
Figure 1.13 Class IIb microcin action MccE492 (A), MccM (B), MccH47(C)
and MccI47 (D)* all exploit the catechol-siderophore receptors and are
translocated into the periplasm in a TonB pathway dependent manner. Once
inside, MccE492, using the ManY and ManZ membrane proteins of the mannose
permease complex as docking stations, inserts itself into the inner membrane
where it disrupts the IM potential by allowing protons to leak. On the other hand,
MccH47 inhibits ATP synthase by interfering with the F0 component once it
gains access to the periplasm. The exact mechanism of action for the remaining
microcins of this group is not known [modified from (Duquesne et al., 2007a)] .
*MccI47 peptide has not been isolated, but on the basis of predicted amino acid
sequence it contains the serine rich C-terminal that is associated with siderophore
interaction. ............................................................................................................ 57
Figure 1.14 A diagram of Microcin J25 structure, demonstrating the lasso fold
[from (Maksimov et al., 2012)] ........................................................................... 60
Figure 1.15 Examples of NRP structures. Tyrocidine A is a good example for
macrocyclic NRPs, while surfactine is a good a good example of branched
macrocyclic NRPs [from (Schwarzer et al., 2003)] ............................................. 63
Figure 1.16 A hybrid NRP/PK. NRPS derived structure is coloured in blue while
PKS derived structures are red [from (Walsh and Fischbach, 2010)].................. 64
Figure 2.1 Simultaneous antagonism test, the antimicrobial activity of potential
inhibitor producers against two indicator E. coli species (414 at the top and
DH5α at bottom of the plate) was observed as clear zones of inhibition............. 79
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Figure 2.2 Deferred antagonism assay plate configuration and scoring system
[From (Tagg and Bannister, 1979)].* Producer is removed and plate is
chloroformed prior to inncoulation of the indicator strains. ................................ 81
Figure 2.3 Image above shows a well diffusion assay performed against
indicator organism M. luteus. ............................................................................... 82
Figure 2.4 Spot assay shown in the diagram illustrates antimicrobial activity of a
sample against M. luteus. ..................................................................................... 83
Figure 2.5 The three-step strategy used for peptide purification. A graphical
representation of the purification strategy employed in this project [from
(Amersham Biosciences)]. ................................................................................... 84
Figure 2.6 Overview of the proposed workflow described below for in silico
mining of genomic sequence data for novel AMPs ........................................... 101
Figure 2.7 Utilisation of NcoI cut site using the BsaI restriction site. .............. 103
Figure 3.1 Spot assay performed with Sep-Pak C18 purified fractions against S.
aureus. Peptide NI03 eluted at 40% acetonitrile concentration and peptide NI04
at 60 and 70% acetonitrile fractions. .................................................................. 114
Figure 3.2 Availability of peptide NI04 in tryptic soy broth and nutrient broth
culture media under different incubation temperatures over a 24 hour period.
Error bars represent the standard deviation in peptide NI04 activity between
replicates. ........................................................................................................... 116
Figure 3.3 RP-HPLC chromatogram of peptide NI04. Each peak on the graph
represents the molecules or molecule groups eluted during the RP-HPLC
procedure at different acetonitrile concentrations (green line indicates the
acetonitrile concentration). The readings are taken at 215nm UV intensity.
Active fractions are labelled............................................................................... 117
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Figure 3.4 ESI-MS scan of active HPLC fraction showing the detected mass of
peptide NI04 as 10722.993. Other peaks represent background noise and a
possible impurity with a mass of 10771.341 (not present in other spectrographs).
............................................................................................................................ 118
Figure 3.5 A graphical representation of the differences between the genomes of
the B. pumilus SAFR-32 strain (inner ring) and B. pumilus J1 (outer, purple
ring). Comparisons were made with BRIG software. ........................................ 119
Figure 3.6 Protein sequence alignment of pumicin NI04 and the 10 most
homologous peptides identified using the PSI-BLAST algorithm (Altschul et al.,
1997). Also included are the known EsxA peptide sequences (EsxA [M.
tuberculosis] and virulence factor EsxA [S.aureus]) that are experimentally
confirmed to play a role in the virulence of their respective host organisms
(boxed in Green) and the highly similar EsxA homolog YukE peptide of
unknown function from B. subtilis (boxed in orange). Secondary structure
prediction, performed using jnetpred, is illustrated at the bottom of the
alignments and confirms the helix turn helix structure of WXG-100 peptides is
preserved in pumicin NI04 together with the W-X-G motif. ............................. 122
Figure 3.7 Neighbour joining tree calculated using the % identity of aligned
WXG family peptides. Branches are labelled with the % difference in the identity
of the amino acid sequences to each other. ........................................................ 123
Figure 3.8 Organisation of the biosynthetic cluster predicted to be involved in
the production and secretion of pumicin NI04 encoded in the producer B.
pumillus J1 genome and organisation of other operons encoding homologous
EsxA peptides, M. tuberculosis ESX1 locus (Burts et al., 2005), B. subtilis Yuk
locus (Huppert et al., 2014) and S. aureus Ess locus (Kneuper et al., 2014). Esx
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substrates are highlighted in red and proteins that are known to be involved in
regulation and secretions of ESX substrates are coloured blue, proteins that are
predicted to be involved in transport or regulation of these factors are highlighted
in green, proteins that have unknown or unrelated function are coloured grey
(Burts et al., 2005; Kneuper et al., 2014; McLaughlin et al., 2007; Ramsdell et
al., 2015). PROKKA 03052 (70.8% identity with YukBA [UniProt ref: C0SPA7]
), YukD (73% identity with YukD [UniProt ref: P71071]), YukC (100% identity
[UniProt ref: P71070]), PROKKA 03051 (45.86% identity with YueB [UniProt
ref: O32101]), PROKKA 03050 (33.5% identity with YueC [UniProt ref:
O32100]). ........................................................................................................... 124
Figure 3.9 The SDS-PAGE gel analysis of the Sep-Pak C18 purified samples,
against SeeBlu 2 protein marker. Gel overlay assay performed following analysis
demonstrated the peptide band at the expected mass interval has inhibitory
activity. The band indicated with the orange arrow was used for MS/MS
fragmentation and de novo amino acid sequencing. .......................................... 125
Figure 3.10 Release of UV absorbing materials from A) M. luteus and B) S.
aureus cells over time following treatment with pumicin NI04 at 1xMIC of
the test organism compared with pumicin NI04 solution (1xMIC) in test buffer
without any microbial inoculum to account for the absorbance inferred by
pumicin NI04. .................................................................................................... 129
Figure 3.11 Comparison of neutral red uptake of Vero cells against negative
(growth media) and positive (2% triton X-100) controls, following incubation
with differing concentrations of pumicin NI04 of up to 18x the MIC recorded
against M. luteus................................................................................................. 131
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Figure 3.12 Cell survival data collected using the trypan blue exclusion assay,
following a 24 hour incubation of keratinocyte cells with pumicin NI04
supplemented medium against negative (growth media) and positive (20mg/ml
SDS) controls. .................................................................................................... 131
Figure 3.13 A representation of the multidomain ATPase involved in ESX
substrate secretion. It is believed that the first domain of YukBA generates the
energy required for the translocation (dark blue) and the remaining two interact
with the substrate (lighter shades of blue) such as pumicin NI04 [from (Ramsdell
et al., 2015)] . ..................................................................................................... 140
Figure 4.1 Activity spectrum of prominent carbapenemases found in
enterobacteriaceae species [adapted from (Nordmann, 2014)]. ......................... 143
Figure 4.2 Prevelance of NDM related cases per country (Dortet et al., 2014)
............................................................................................................................ 144
Figure 4.3 HPLC chromatogram of the active fractions I3 and I4 obtained during
purification of peptide NI05. .............................................................................. 149
Figure 4.4 Mass spectrogram of three separate active HPLC fractions from
individual purification runs. The spectrum encompassed molecules up to 10kDa
in size, however the only detectable peaks were perceived below 2500Da....... 150
Figure 4.5 Draft genome sequence of producer organism K. pneumoniae A7
compared with the reference K. pneumoniae strain XH209 and K. pneumoniae
strain RYC492 that is known to express MccE492, using BRIG software. The
identical regions between both genomes are represented in solid colours and
differences are represented with faded colours or gaps. .................................... 152
Figure 4.6 Alignment of sequences of the structural genes encoding microcins
MccM, MccH47, MccE492 and MccG492 reveals striking homology at the C-
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terminus. Red arrow indicates the residue (Serine 84) where the post translational
moiety DHBS is attached to the MccE492 and red line indicates that the region
around this location that is also conserved in other members of the group. The
green line indicates the conserved GG/GA motif where leader sequences are
cleaved from the active peptide.......................................................................... 155
Figure 4.7 MceK3 peptide sequence is homologous to the MccM N terminus
prior to the stop codon TAG (Green arrow) that is also observed in the sequence
derived for the MceK fusion peptide. However, the fragment following the stop
codon also resembles and aligns with the serine rich C terminal of the classIIb
bacteriocins including the serine 84 (Red arrow) region where the DHBS
molecule is docked (Mercado et al., 2008). ....................................................... 156
Figure 4.8 Genome maps of the biosynthetic gene clusters involved in
production, export and immunity of peptides, MccE492 (mceA), MccG492
(mceL), MccH47 (mchB), MccM (mcmA). Peptides that are of the same colour
are homologues to each other [adapted from (Vassiliadis et al., 2010)]............ 157
Figure 4.9 Post translational modification pathway of MccE492 with the DHBS
siderophore moiety. 1) gycolysation of enterobactin by MceC. 2) cleavage of
enterobactin to achieve linear Glc-DHBS3, 3) attachment of the linear Glc-
DHBS3 and derivatives to the MccE492 precursor peptide (MceA) [from
(Vassiliadis et al., 2007)]. .................................................................................. 161
Figure 5.1 Graphical result representation of BAGEL3 software analysis. The
gene cluster belongs to lead 4 (see below), a putative class II lantibiotic
identified during this study and is surrounded by important motifs. LanK and
LanR are known to be involved regulation of class II bacteriocins, the ABC
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transporter is responsible for secretion) and SacCD encodes the SAM enzyme
that introduces sulphur bridges. ......................................................................... 168
Figure 5.2 A) Amino acid sequence alignments of lead 3 with two component
members of the class II lanthipeptide family, including lichenicidin A2 (orf023).
B) The biosynthetic cluster of lead 3 as predicted by BAGEL 3 software. ....... 176
Figure 5.3 A) Lead 12 sequence alignment shows conserved regions with
ruminococcicin, lacticin 481 and salivaricin 9. B) The putative bacteriocin is
accompanied by LanM and LanC modification components, multiple ABC
transporters and two bacteriocin related genes GerE and HisKA 3 with unknown
functions, as predicated by BAGEL 3................................................................ 177
Figure 5.4 A) the amino acid sequence alignment of lead 14 with circular
bacteriocins Enterocin AS-48, Leucocyclicin Q and Circularin A. B) The
anticipated biosynthetic gene cluster consists of two modification genes, HttB
and HttC and an ABC transporter. ..................................................................... 179
Figure 5.5 Unique bacteriocin sequences predicted by BAGEL 3 software. A)
Lead 4 is a predicted sactipeptide, B) lead 7 is a predicted LAPs peptide, C) lead
19 is a putative bottromycin and D) lead 9 is a likely class II lanthipeptide family
bacteriocin. ......................................................................................................... 180
Figure 5.6 Digested NI04 structural gene insert (left) and pET28a vector DNA
products (right) prior to gel purification. ........................................................... 182
Figure 5.7 Gel image displaying the comparison of colony PCR amplified pmnA
bands from the clones (CL) to those amplified from the producer. Positive
control (+) was insert DNA amplified from producer B. pumilus J1 DNA and the
negative control (-) was amplification from pET28a plasmid DNA with no insert
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(the template vector is visible in the negative control lane). Expected product
length was 319bp. .............................................................................................. 183
Figure 5.8 Insert orientation was confirmed using pmnA gene forward primers
and the T7 promoter region reverse primers. The expected product length was
435bp. ................................................................................................................. 184
Figure 5.9 CL1 and CL2 insert region sequence alignments with the expected
pET28a plasmid T7 region containing the pumicin NI04 gene pmnA. The
alignments showed that while CL2 encoded the correct sequence, the CL1 insert
had a mutation in the 3’ end and possibly encodes a non-functional peptide .... 185
Figure 5.10 Reverse purification of the in vitro expressed pumicin NI04
indicated with red arrows and positive control DHFR indicated with black
arrows, (1) Ni-NTA purified DHFR, (2) Ni NTA purified pumicin NI04, (3)
DHFR 100kDa ultrafiltration flow through, (4) pumicin NI04 100kDa
ultrafiltration flow through, (5) DHFR whole reaction protein, (6) pumicin NI04
whole reaction protein. ...................................................................................... 187
Figure 5.11 Enterocin AS-48 and cicularin A gene cluster arrangements [from
(van Belkum et al., 2011)] ................................................................................. 194
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LIST OF TABLES
Table 1.1 A list of recently introduced systemic antimicrobials with novel modes
of action [adapted from (Butler et al., 2013; Leach et al., 2011)]. ...................... 31
Table 2.1 A summary of the characterisation assays performed on each agent
identified during proteomic analysis .................................................................... 95
Table 2.2 A list of primers employed during the study. Blue nucleotides indicate
the restriction enzyme cut site, while red nucleotides highlight the start and stop
codons. ............................................................................................................... 103
Table 2.3 The content of the PCR reaction mixture used for amplification of the
inserts for use in construction of plasmid vector. .............................................. 104
Table 3.1 Antimicrobial activity of peptides NI03 and NI04 against indicator
species. Results were obtained using the spot on lawn assay with Sep-Pak C18
fractions. Activity was recorded as (+) if a visible inhibition zone was present
and (-) if no zone of inhibition was present. ...................................................... 114
Table 3.2 Effect of various media and additives on the production and
availability of peptide NI04, following overnight incubation at 37oC. .............. 115
Table 3.3 The unique sequence tags for peptide NI04 obtained from the de novo
peptide sequencing efforts. Common modifications that can occur were also
accounted............................................................................................................ 118
Table 3.4 Effect of a wide array of hydrolytic enzymes on the antimicrobial
activity of pumicin NI04. ................................................................................... 126
Table 3.5 Minimum inhibitory concentration (MIC) of pumicin NI04 against a
wide selection of Gram positive bacteria. MIC was calculated in AU/ml and
µg/ml in a selection of indicators using highly purified peptide........................ 127
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Table 3.6 Percentage of haemolysis that occurred following the addition of
pumicin NI04 to mouse erythrocytes. Triton-X100 detergent was used to achieve
absolute haemolysis and was used as the positive control. ................................ 130
Table 4.1 Peptide NI05 spectrum of activity determined through simultaneous
antagonism assays .............................................................................................. 147
Table 4.2 Effect of various media and additives on the production and
availability of peptide NI05, following overnight incubation at 37oC. .............. 148
Table 5.1 The short list of promising bacteriocin leads identified in the genomes
of 35 species of anaerobic bacteria of the genera Clostridium and
Propionibacterium and the producer bacteria K. pneumoniae A7 and B. pumilus
J1. Unique leads are novel leads that do not share homology with known
bacteriocins but are located with bacteriocin related genes. .............................. 172
List of abbreviations
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LIST OF ABBREVIATIONS
ACN - Acetonitrile
AMP - Antimicrobial peptide
AMR - Antimicrobial resistance
AU - Arbitrary unit
BHI - Brain heart infusion (broth)
CAB - Columbia agar base
CA-MHB - Cation adjusted Muller
Hinton broth
CBA - Columbia blood agar
CLSI - Clinical and Laboratory
Standards Institute
CV - Column volume
FT - Flow through
HTS - High throughput screening
HVS - High vaginal swab
ESBL - Extended spectrum β-
lactamase
ESI - Electrospray ionisation
HPLC - High pressure liquid
chromatography
KPC - Klebsiella pneumoniae
carbapenemase
LAB - Lactic acid bacteria
LAP - Linear azol(in)e-containing
peptide
LC - Liquid chromatography
MALDI-TOF - Matrix assisted laser
desorption/ionisation time of flight
Mcc - Microcin
MIC - Minimum inhibitory
concentration
MRSA - Meticillin resistant
Staphylococcus aureus
MS - Mass spectrometry
MS/MS - Tandem mass spectrometry
NB - Nutrient broth
NDM-1 - New Delhi Metalloprotease
1
NP - Natural product
NRP - Non ribosomal peptide
NRPS – Non ribosomal peptide
Synthase
NMR - Nuclear Magnetic Resonance
OM - Outer membrane
PBS - Phosphate buffered saline
PK - Polyketide
PKS - Polyketide synthase
List of abbreviations
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PTM - Post translational modification
RiPP - Ribosomally synthesised and
post translationally modified peptide
RP-HPLC - Reverse phased high
pressure liquid chromatography
SDS-PAGE - Sodium dodecyl
sulphate polyacrylamide gel
electrophoresis
TFA - Trifluoroacetic acid
TSB - Tryptic soy broth
WT - Wash through
YE - Yeast extract
UV - Ultra violet
Abstract
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Abstract The University of Manchester, 2015
For the degree of Doctor of Philosophy - Arif Felek Discovery of antimicrobial peptides active against antibiotic resistant bacterial
pathogens Rapid development of antimicrobial resistance (AMR) among bacteria,
combined with diminished new antibiotic discovery rates, is an increasing threat to human health. Bacterially derived antimicrobial peptides (AMP) hold excellent potential as potent novel therapeutics. This study embraces traditional natural AMP discovery methods and the newer in silico genome mining tool BAGEL 3 to facilitate identification of novel antimicrobial agents. The traditional screening efforts led to the discovery of two promising antimicrobial producer strains; Bacillus pumilus J1 producing two AMPs, peptides NI03 and NI04, and Klebsiella pneumoniae A7, which produced peptide NI05. In silico mining of the B. pumilus J1 and K. pneumoniae A7 genomes and those from under exploited anaerobic bacteria using BAGEL 3 yielded 18 putative bacteriocin structures that were associated with multiple known and relevant bacteriocin accessory genes and/or carried significant homologies to known bacteriocins. Peptide NI04 proved to be active against Gram positive species only, including meticillin resistant Staphylococcus aureus and vancomycin resistant enterococci and peptide NI03, in addition to these pathogens, showed activity against E. coli. Peptide NI05 was active against Gram-negative pathogens including extended spectrum β-lactamase producing E. coli. All isolated peptides were observed to be proteinaceous in nature and highly heat stable.
Peptides were purified or partially purified using solid phase extraction followed by RP-HPLC. The mass of the peptides was determined using ESI or MALDI-TOF mass spectrometry. Tandem MS fragmentation of peptide NI04 generated several sequence tags. Draft genome sequences of the B. pumilus J1 and K. pneumoniae A7 producer strains were obtained using the Illumina MiSeq platform. This allowed identification of the genes encoding peptide NI04, which was confirmed to be novel and was named pumicin NI04. Further characterisation of pumicin NI04 demonstrated it was non-toxic to keratinocytes, Vero cells and non-haemolytic up to at least 18x the minimum inhibitory concentration. The discovery revealed that pumicin NI04 belongs to the WXG-100 peptide superfamily, having homology with the mycobacterial and staphylococcal virulence factor EsxA. This represents the first report of antimicrobial activity in a WXG-100 peptide and has intriguing evolutionary implications.
Although it was not possible to fully characterise peptides NI03 and NI05, when BAGEL 3 was used to mine the B. pumilus J1 genome, a promising putative bacteriocin candidate was identified that was homologous to Enterocin AS-45, which also confers anti Gram-negative activity and may be related to the activity observed for NI03, however more evidence is required. Investigations of the K. pneumoniae A7 bacteriocin on the other hand helped establish that the K. pneumoniae microcin E492 pathway was present and highly conserved in strain A7, and is likely to be responsible for the activity observed indicating that NI05 was not a novel peptide.
Declaration
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DECLARATION
No portion of the work referred to in the thesis has been submitted in support of an
application for another degree or qualification of this or any other university or other
institute of learning.
Arif Felek
Copyright statement
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COPYRIGHT STATEMENT
1. The author of this thesis (including any appendices and/or schedules to this thesis) owns certain copyright or related rights in it (the “Copyright”) and s/he has given The University of Manchester certain rights to use such Copyright, including for administrative purposes.
2. Copies of this thesis, either in full or in extracts and whether in hard or electronic copy, may be made only in accordance with the Copyright, Designs and Patents Act 1988 (as amended) and regulations issued under it or, where appropriate, in accordance with licensing agreements which the University has from time to time. This page must form part of any such copies made.
3. The ownership of certain Copyright, patents, designs, trade marks and other intellectual property (the “Intellectual Property”) and any reproductions of copyright works in the thesis, for example graphs and tables (“Reproductions”), which may be described in this thesis, may not be owned by the author and may be owned by third parties. Such Intellectual Property and Reproductions cannot and must not be made available for use without the prior written permission of the owner(s) of the relevant Intellectual Property and/or Reproductions.
4. Further information on the conditions under which disclosure, publication and commercialisation of this thesis, the Copyright and any Intellectual Property and/or Reproductions described in it may take place is available in the University IP Policy (see http://www.campus.manchester.ac.uk/medialibrary/policies/intellectual-property.pdf), in any relevant Thesis restriction declarations deposited in the University Library, The University Library’s regulations (see http://www.manchester.ac.uk/library/aboutus/regulations) and in The University’s policy on presentation of Theses.
Dedication
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DEDICATION
I dedicate this thesis to my family;
To my wife Emine, for always being there for me with her endless love and
understanding, she is the light in my life. Also to my mother Ayten, father Osman and
brother Ismail for all of their support, sacrifices and unconditional love. I am very
lucky to have them in my life and without them none of this would have been
possible.
Acknowledgements
26 | P a g e
ACKNOWLEDGEMENTS
First of all I would like to express my deepest thanks to my
supervisor Dr. Mathew Upton, for all of his support and guidance. He was always
there to listen with all his invaluable advice, I could not have asked for more. I am
also ever so grateful to John Moat and Audrey Coke for their exceptional technical
help. The support they gave me went far beyond the laboratory. I am also indebted
to Dr. Catherine O’Neil for taking me on following the departure of Dr. Mathew
Upton from Manchester University. She was always very kind and understanding.
I would like to also thank Marjorie
Howard, Dr. Stacy Warwood and Dr. David Knight for training me on HPLC, Mass
spectrometry and de-novo peptide sequencing techniques and also express my
gratitude to Dr. Vikram Sharma for allowing me to use the proteomics facility at the
Plymouth University and Mathew Emery for his tireless support during my time in
Plymouth University.
I am also grateful to Majed Al-Ghoribi for his friendship and all of his
support during our PhD journey together. Finally I would like to thank everybody in
the Microbiology and Virology unit at Manchester University and the department of
Biomedical Sciences at Plymouth University. It has been an honour to be a part of
these teams and I look forward to continue working with everybody mentioned here
in the future.
Publications
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PUBLICATIONS FROM THIS WORK
This study has produced the following published work, which includes
conference presentations (oral and poster) and manuscripts to be submitted
for publication.
Manuscript Felek A, Upton M. (2015) Pumicin NI04, a novel antimicrobial peptide from Bacillus pumilus, is homologous to the EsxA virulence determinant (in preparation) Oral and Poster Presentations Antibiotic alternatives for the new millennium, Eroscicon (November 2014) London UK, Peptide antibiotics for nasal decolonisation of MRSA carriage (Invited oral presentation). Society for General Microbiology Annual Conference (April 2014) Liverpool UK, Discovery of antimicrobial peptides active against antibiotic resistant bacterial pathogens (poster presentation) North West Microbiology Group Meeting (September 2013) Liverpool UK Developing Inhibitors of Antimicrobial Resistant Gram Negative Bacteria. (Poster presentation) Society for General Microbiology Spring Conference (March 2013) Manchester UK Discovery of Antimicrobial peptides active against Gram Negative Pathogens. (Poster presentation) Society for General Microbiology Spring Conference (March 2012) Dublin- Ireland. Developing Inhibitors of Antimicrobial Resistant Gram Negative Bacteria. (Poster presentation)
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Introduction
1 CHAPTER 1
GENERAL INTRODUCTION
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Introduction
Antibiotics are undoubtedly one of the most essential building blocks of
modern health care. As well as treatment of infected patients, they also play a key
role in preventing post-operative infections in surgery patients, which in turn
decreases the due morbidity and mortality rates considerably (Rice, 2008). However,
since the introduction of the first antimicrobial compounds into medicine, bacterial
resistance has been an ever increasing problem in antibiotic therapy, developing and
spreading rapidly amongst pathogens shortly after introduction of virtually any
antibiotic (Figure 1.1) (Clatworthy et al., 2007; Davies and Davies, 2010).
Nevertheless, in the early days resistance was not deemed very important, due
largely to the fact that before 1987 and especially during the 1940s-1960s (the
‘Golden Era’ of antibiotic discovery) humanity lived through a period of
unprecedented antibiotics wealth with high discovery rates (Silver, 2011).
Figure 1.1 Timeline of antibiotic discovery versus outbreak of resistance among bacteria [from (Clatworthy et al., 2007)]
Together, when combined with the idea that infectious diseases could be
wiped out, this wealth resulted in the abuse of antibiotics through unnecessary usage,
only to fuel the increasing development of antibiotic resistance within the bacterial
community and to this day antibiotic overuse and misuse continues both in clinics
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Introduction
and in agriculture (Aarestrup, 2005; Besser, 2003; Laxminarayan et al., 2013; Lee et
al., 2014; Shallcross and Davies, 2014; Tripathi et al., 2012).
Although appropriate measures are currently being implemented in the form
of improved antibiotic stewardship, better infection control measures and rising
public awareness to prevent the spread of antibiotic resistance, the slow introduction
of novel antimicrobials into the clinic (Figure 1.2 and Table 1.1) makes us face a
dramatically decreasing number of treatment options against multidrug resistant
(MDR) pathogens (Boucher et al., 2013; Livermore, 2011; White, 2011). The
Infectious Disease Society of America have listed six of the most problematic MDR
bacteria, namely the ESKAPE group of pathogens which are Enterococcus faecium,
Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii,
Pseudomonas aeruginosa and Enterobacter species (Rice, 2008). Among these there
are pan-antibiotic resistant species that cannot be treated with any conventional
antibiotics (Telang et al., 2011; Walsh and Toleman, 2012). In addition to its clinical
impact, antimicrobial resistance also has a severe effect on the economy with a
worldwide estimated cost of 100 trillion US dollars by 2050 (O’Neill, 2014).
Figure 1.2 The amount of antibiotics being introduced into the clinic has been drastically decreasing in recent years [From (Boucher et al., 2013)]
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Table 1.1 A list of recently introduced systemic antimicrobials with novel modes of action [adapted from (Butler et al., 2013; Leach et al., 2011)].
Class Example agent Date approved
Oxazolidinones Linezolid 2000
Lipopeptides Daptomycin 2003
Lipoglycopeptides Telavancin 2009
Bedaquiline Diarylquinoline 2012
Nevertheless, the positive effect of increasing awareness, implication of
programs such as the IDSA’s “10 × ’20 initiative” that encourages the scientific
community to develop and obtain regulatory approval for 10 systematically
deliverable novel antibiotics by 2020 and proposals to change the policy on
antimicrobials has already started improving the future outlook positively (Boucher
et al., 2013; Infectious Diseases Society of America, 2010; Spellberg et al., 2011).
This can be observed in the rising number of antibiotics going through clinical trials
in 2013 compared with 2011 (Figure 1.3) (Pucci and Bush, 2013).
Figure 1.3 Graphical representation and comparison of the number of antibiotic candidates going through clinical trials between 2011 and 2013 [from (Pucci and Bush, 2013)].
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Introduction
However, it has been never more clear than today that this is an arms race that
will be fought for years to come and thus science must come up with new lucrative
novel antimicrobial discovery platforms and sources. Hence, it is important to
discuss the reasons behind the lack of investment in novel antimicrobial discovery
and to explore innovative approaches that may bring the breakthrough that is
urgently required.
1.1 DOWNFALL OF NOVEL ANTIMICROBIAL DISCOVERY
It is important to understand the causes of the problem before seeking
solutions. Literature agrees in two fundamental changes that are believed to have led
to the lack of antimicrobial discovery, the first one is the failure of adopted genetic
approaches that were meant to replace natural product screening for antimicrobial
discovery (Lewis, 2013). The second reason, which is also directly related to the
first, is the movement of “big pharma” away from antimicrobial drug discovery due
to the high cost and low success of development; as a result currently the main
drivers of antimicrobial discovery are smaller pharmaceutical and biotechnology
companies.
1.1.1 Movement of “big pharma” away from antimicrobial drug discovery
The retreat of big pharma from the field can be summarised under two
sections. The first reason is the fact that when the discovery and development costs
and the difficult route to receiving regulatory approval for antibiotics are taken into
account, these agents generate significantly lower revenues compared with
therapeutics for chronic diseases such as cholesterol reduction, diabetes and cancer
treatment (Livermore, 2011; Projan, 2003). This is mainly due to their short
treatment course and the fact that to prevent the rapid development of resistance, the
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Introduction
new antibiotics would be kept as a last resort, affecting initial revenues meaning
patents expire before costs are recovered (Bérdy, 2012; Katz et al., 2006; Livermore,
2011; Projan, 2003).
The second reason is the fact that value of the drug will drop rapidly once
resistant strains emerge and adapting to new resistance mechanisms is proving very
hard due to the unpredictability of mutations (Livermore, 2011; Livermore et al.,
2011). For example, the emergence of New Delhi metalloprotease-1(NDM-1) has
rendered both the β-lactams and β-lactamase inhibitors such as clavulanic acid less
valuable (Kumarasamy et al., 2010; Nordmann, 2014) and vancomycin resistance
had the same effect although less dramatic on vancomycin (De Vriese and
Vandecasteele, 2014; Harbarth et al., 2002; Livermore, 2007; Meziane-Cherif et al.,
2014).
However, investing only in countermeasures for NDM-1 isn’t enough. This
is due to the fact that resistance against β-lactams and β-lactamase inhibitors can
develop through more than one mechanism. One of the most important is the rapidly
spreading Klebsiella pneumoniae carbapenemase (KPC) (Nordmann, 2014; Robilotti
and Deresinski, 2014). KPC is also active against β-lactams as NDM-1, yet
structurally it is different, demanding individualised research (Nordmann, 2014).
When there are multiple targets, adaptation of counter measures against them is even
harder and more expensive (Livermore et al., 2011). However, steps are
implemented to improve the economic positon of pharmaceutical companies to
incentivise antibiotic development through legislation. GAIN (Generating Antibiotic
Incentives Now) act is one attempt approved by the US government, it increases
exclusivity of antibiotics and requires the food and drug administration to provide
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Introduction
updated clinical trial guidance and list pathogens that pose a relatively higher threat
to public health to provide a clearer path (US Congress, 2011).
1.1.2 Overview of target based genetic approaches and their failure to
discover novel antibiotics
In 1995, the genome sequence of Haemophilus influenzae was published and
this was quickly followed by many others; today there are 45,076 bacterial genomes
available in the joint genome institute (JGI) genomes online database (GOLD)
(https://gold.jgi-psf.org/, last access: 30/06/15). These advances were rapidly
followed by development of powerful bioinformatic tools that enable rapid
comparative analysis of gene libraries and soon the potential
of these resources, with regards to increasing antimicrobial discovery, was
realised (Bansal, 2005; Livermore, 2011). This has led to investigators abandoning
natural product screening methods that did not fit in with the prospect of rapid
antimicrobial discovery through utilisation of the rapid nature of new techniques to
establish target based high throughput screening (HTS) platforms (Lewis, 2013;
Livermore, 2011; Silver, 2011). The HTS methods, which use synthetic product
libraries, were quickly adopted by most drug companies. The approach is outlined in
Figure 1.4.
Figure 1.4 The process of target based antimicrobial drug discovery [adapted from (Mills, 2006; Pucci, 2007)].
Target identification
Target validation
Screening: isolated enzyme
Screening: whole cell
analysis
Hit & lead development
Clinical development
& Drug
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Introduction
Although powerful and much faster than natural product screening, the target
based genetic approaches have failed to produce any antimicrobials worthy of
introduction into clinical practice. The literature points to two main issues that limit
the target based methods. The first one is that many target based, high throughput
screening efforts are conducted in silico. This creates complications with
accessibility of the target site by selected compound, as this is not predictable
(Livermore, 2011). Although to overcome this issue, physical screening studies
targeting whole cell growth inhibition are performed, the exclusive nature of the
synthetic compound libraries used, which only or predominantly include compounds
that fit into Lipinski’s rule of five becomes a limiting factor (Lewis, 2013;
Livermore, 2011).A number of synthetic compounds that were discovered using the
whole cell screening approach also failed to make it through lead development due
to non-specific membrane activity that caused lysis of non-target cells including
erythrocytes during early analysis (Payne et al., 2007, 2004).
Lipinski’s rule of five is an algorithm that is used to identify possible drug
compounds according to their solubility and permeability within the body. In a
paper, Lipinski et al. (1997) state that the parameters which should be used to asses
suitability of a compound as a drug candidate is; molecular weight (less than 500Da),
Log P (not greater than 5), the number of H bond donors (not more than 5) and H
bond acceptors (not more than 10). However, as also noted by Lipinski et al. 2001,
some antibiotics lie outside the rule of five (Lipinski et al., 2001), some antibiotics
such as aminoglycosides and β-lactams are larger and more hydrophilic and thus
outside the parameters (Payne et al., 2007). This information alone identifies these
libraries as a limiting factor. The synthetic product libraries are designed for
physiological conditions in the human body, not for interacting with bacteria. As
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Introduction
bacteria come into contact and interact with small compounds constantly, many of
which could be harmful, they have developed coping mechanisms such as efflux
pumps to regulate entry of these compounds (Delcour, 2009; Wong et al., 2014;
Wright, 2014).
1.2 REVITALISING NATURAL PRODUCT SCREENING AS A SOURCE OF
NOVEL ANTIBIOTICS
Failure of the target based HTS approach has caused researchers to explore
other platforms of antibiotic discovery and the focus has been shifted back to the
natural product screening also named the “Waksman platform” (Lewis, 2013).
Although this shift is influenced by the advancements of methods employed for
natural product screening, it’s also due to the inherent advantages of the natural
products summarised in Figure 1.5 (Lewis, 2013).
NP
Effective killing action
Novel target discovery
Structural diversity
Rational modification
Untapped sources
Figure 1.5 Advantages of natural products (NP) as antibiotic drug leads
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Introduction
Natural antimicrobial products, unlike those found in synthetic product
libraries, have evolved with their host, among other reasons, for one particular job, to
infiltrate or interact with the target bacterial cell and kill it (Wright, 2014). Hence,
natural products suffer proportionally less from issues such as reduced cell
permeability, unlike many synthetic products, and in some cases readily contain the
properties required from an antibiotic, meaning that they will need less lead
optimisation (Lam, 2007). In addition, natural products have already been
successfully implemented in the clinic and the majority of antibiotics are derived
from these products (Wright, 2014). Thus, on many occasions in current literature
natural antimicrobials are referred to as “privileged compounds” with regards to their
potential as antibiotic candidates (Tan et al., 2015; Wright, 2014).
In addition, natural products cover a unique and large chemical space with
unmatched structural diversity. To give a few examples, these include stereogenic
centers such as chiral centers, heterocyclic substituents and polycyclic structures
(Dobson, 2004; Genilloud, 2014; Rosén et al., 2009; Szychowski et al., 2014). This
increases the value of natural product discovery two fold as these unique structures
can provide examples for combinatorial chemistry and create a vision for templates
to be used to modify and improve the activity of known and used compounds (e.g.
tigecycline from tetracycline) (Lam, 2007) or bring out the hidden potential in
previously dismissed compounds such as Linezolid (Newman, 2008), earning them
back for medicine.
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Introduction
The peptidomimetics approach is another creation of natural product inspired
synthetic chemistry. This involves replacement or rearrangement of the original
structure of an antimicrobial peptide (AMP) with a mimic to generate libraries with
increased activity or decreased toxicity (Morrison and Hergenrother, 2014). There
are many strategies to achieving mimics, one of which is replacing the α-amino acid
backbone with a β-amino acid containing mimic to make the antimicrobial more
stable against proteases while reducing the toxicity (Godballe et al., 2011; Johnson
and Gellman, 2013). Another strategy is to transfer the active region of the
antimicrobial to a backbone nitrogen on an N-substituted glycine (peptoid) molecule,
which in turn can also potentially decrease the toxicity and increase the proteolytic
stability (Godballe et al., 2011; Miller et al., 1994; Rotem and Mor, 2009;
Zuckermann et al., 1992). It is also possible to manipulate certain compounds to
mimic and improve upon the desirable properties of a known antimicrobial, such a
study conducted by Tan et al. (2015) which had successfully managed to create a
antimicrobially active library of pramanicin mimics derived from pyroglutamic acid
(Tan et al., 2015). It is also important to note here that, the value of natural products
is not only limited to their potential as drug leads but they may also play a crucial
part in discovery or understanding of novel drug targets, pathogenicity mechanisms
and other bacterial processes (Lam, 2007).
Nonetheless, natural product screening was largely abandoned. Some of the
disadvantages associated with this move can be attributed to the slow pace of
discovery associated with natural product research, concerns about large scale
production and patenting. However, rediscovery of existing compounds is often
accepted as the main reason (Harvey, 2008; Livermore, 2011; Newman, 2008).
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Introduction
However, recent estimates show that only 10% of the potential natural
products have been discovered from the known producer species and most bacterial
species are not yet cultivated in laboratories (Curtis et al., 2006; Walsh and
Fischbach, 2010). This means that there is still a plethora of possibilities waiting to
be discovered contrary to the prevailing belief in 1990s that natural products had
reached their limits, and the recent developments in natural product screening
methods are very promising. Advances in cultivation techniques such as the isolation
chip (iChip), a high throughput diffusion chamber system that allows culture of
many non-cultivable bacteria using traditional cultivation methods (Ling et al., 2015;
Nichols et al., 2010), and developments in analytical technologies (see Section 1.11)
have removed most of the difficulties associated with the older methods that caused
researchers to abandon natural product discovery and are encouraging the return to
natural products. Some significant antimicrobial peptide classes have been reviewed
in the following section.
1.3 BACTERIALLY DERIVED NATURAL PRODUCTS OF INTEREST
The antagonistic activity of some bacterial species against each other was
first recorded by Pasteur and Joubert in 1877 as they observed “common bacteria”
(likely E. coli) adversely effecting the growth of Bacillus anthracis. After this
discovery, colicin V one of the oldest known bacteriocins (currently classified as a
microcin, see below), was isolated from E. coli strain V and others (Cascales et al.,
2007; Davies et al., 1981). This was followed by many others and initially all were
named colicins but further research showed that many other bacteria were producing
colicin like substances and some of these substances were fundamentally very
different from each other, either in their production pathways or structurally (Jack et
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Introduction
al., 1995). Thus, many divisions had emerged for the classification of these
antimicrobially active natural products. Some of the most promising classes that this
project focuses on are listed in Figure 1.6 below.
Figure 1.6 Natural products of interest in the current project. The figure above lists the natural products produced by bacteria that have the potential to be used as antibiotics. These products are shortly reviewed in this study.
Antimicrobials of interest
Lysins Ribosomal peptides
Bacteriocins
Bacteriocins of Gram positive
bacteria
Class I Lantibiotics
Class II un-modified
Class III Large proteins
Clsass IV cyclic peptides
Bacteriocins of Gram negative
bacteria
Colicins
Microcins
Miscellaneous
Non-ribosomal peptides Polyketides
Modular polyketides
Aromatic polyketides
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Introduction
1.4 BACTERIOCINS
Bacteriocins are ribosomally produced AMPs, to which the producing
bacteria are immune (Cascales et al., 2007; Jack et al., 1995). It is suggested that
these peptides are produced to give an edge to the producing bacteria against other
competing bacterial species in the environment, as these agents generally target
closely related species (Cascales et al., 2007; Jack et al., 1995). However, their
activity ranges from broad spectrum agents that have interspecies activity, to very
narrow spectrum agents that are only active against other strains of the same species
[e.g. Cerein isolated from Bacillus cereus is observed to be only active against other
species of B. cereus] (Naclerio et al., 1993).
Although the term bacteriocin did not exist at the time of their discovery,
colicins are the first recorded bacteriocins to be discovered. At the time, a list of key
properties were created to identify colicins and a classification scheme was produced
according to the entry route of the agent into the cell (Cascales et al., 2007).
However, as research uncovered numerous new colicin like substances with
substantial structural differences from each other both from coliform and non-
coliform bacteria, the colicin based identification system was no longer applicable
and the need for a new classification scheme arose (Jack et al., 1995).
The first detailed classification system was proposed by Klaenhammer et al.
(1993) that separated bacteriocins into four groups according to their structural
components (Klaenhammer, 1993). This scheme is currently accepted and used by
many scientists, however, updated classification schemes by Kemperman et al.
(2003) and Cotter et al. (2005) have also been proposed and widely accepted
creating some confusion. In response, Heng and Tagg (2006) have produced a
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Introduction
universal scheme that combines the Klaenhammer et al (1993) and Cotter et al
(2005) classifications in an optimal scheme with some added updates to create a
proposal that encompassed the majority of the known bacteriocins at the time (Figure
1.7) (Heng and Tagg, 2006). It is important to note here that a rift exists between
classification of Gram positive and negative bacterial bacteriocins and the
aforementioned classifications schemes, with the exception of the Heng and Tagg
(2006) schema, are useful for differentiation of bacteriocins derived from Gram
positive bacteria. However, Kempermen et al. (2003) did use the Gram-negative
bacteriocin microcin J25 as an exemplar for their proposal.
Yet, with each new bacteriocin discovered the number of peptides with
additional unique structures continue to accumulate and as a result additional groups
that had not been covered by any of the previously described bacteriocin schemes
Figure 1.7 The "Universal” bacteriocin classification scheme. This figure by Heng and Tagg, (2006) illustrates the two major classification schemes that are used and how they propose to combine the respective advantages to construct a universal scheme.
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Introduction
have arisen, such as the sactibiotic and lasso peptide families (Arnison et al., 2013;
Mathur et al., 2014). Indeed, with new discoveries the existing classes such as
lantibiotics, within these schemes have also become even more varied and the
aforementioned bacteriocin classification schemes can’t justifiably describe the
groups (Arnison et al., 2013). What follows is an introduction of common
bacteriocin classes and the general titles of the universal Heng and Tagg scheme will
be retained. However, the groups that fall under the Ribosomally synthesised and
post-translationally-modified peptides (RiPPs) will be supplemented with the
recommendations form the universal nomenclature study for the greater class of
RiPPs by Arnison and colleagues (Arnison et al., 2013). Based on the same study, an
independent miscellaneous peptide family has been added to address the newly
arising RiPP bacteriocin groups that share conserved properties that differentiate
them from existing classes and justify their existence as a separate class; these
peptides may and do span Gram positive and negative producers.
1.5 BACTERIOCINS OF GRAM POSITIVE BACTERIA
1.5.1 Class I - Lanthionine containing bacteriocins (Lantibiotics)
These bacteriocins contain multiple ring structures that are linked to each
other by lanthionine (Lan) or 3-methyllanthionine (MeLan) bonds between
dehydrated residues. They widely contain dehydrated amino acids and undergo
extensive post-translational modifications (eg. Nisin) (Fujita et al., 2007; McAuliffe
et al., 2001). These antimicrobial peptides gather particular interest from researchers
for they are commonly produced by food grade lactic acid bacteria (LAB).
Moreover, some lantibiotics, like nisin have dual actions on the target cell, a feature
not seen in conventional antimicrobials that contributes to increased stability against
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Introduction
antimicrobial resistance (Figure 1.8) (Cotter et al., 2005; Mantovani and Russell,
2001). Nisin acts by either inhibiting cell wall synthesis through blocking the lipid II
transporter that is responsible for the transfer of peptidoglycan subunits from the
cytoplasm, or it exploits lipid II to insert itself into the cell membrane and form
pores that cause lysis leading to cell death (Cotter et al. 2005). Nisin, isolated in
1928 (Rogers, 1928), is one of the most well studied lantibiotics and also it is one of
the most widely used preservatives in the food industry. However, resistance to nisin
is extremely rare compared with conventional antibiotics (Mantovani and Russell,
2001).
Figure 1.8 Bacteriocin mode of action. The class II bacteriocins such as sakacin can insert into the cell membrane by interacting with membrane proteins and cause pore formation and depolarisation of the cell membrane. The class I bacteriocins on the other hand can have a single or multiple modes of action such as nisin. Large protein bacteriocins such as lysostaphin can also act on the cell wall by hydrolysing the interpeptide bridges of the peptidogycan layer [adapted from (Cotter et al. 2005)].
Nisin Sakacin LysostaphiLysostaphin Nisins Sakacin
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Introduction
Many bacteriocins like nisin act by forming pores in bacterial cell
membranes however it’s important to note that some bacteriocins may also act
intracellularly. Although these mechanisms are not as well defined some these
modes of action include, stabilisation of DNA gyrase (microcins B17) (Collin et al.,
2013; Thompson et al., 2014) and cleavage of RNA (carocin S2) (Chan et al.,
2011) and ribosomal RNA (colicin E2) (Cavera et al., 2015; Ng et al., 2010).
Lantibiotics in the Heng and Tagg (2006) scheme were divided into 3 sub-
groups, type A, B and C. Type A lantibiotics contain elongated structures and a
cationic charge. These peptides act by forming pores on the bacterial cell wall, while
type B lantibiotics are globular peptides and act by preventing the execution of vital
cell processes such as cell wall synthesis, through inhibition of key enzymes (Cotter
et al., 2005; McAuliffe et al., 2001; Nishie et al., 2012). Subtype C was added later
to account for the multi component lantibiotics (Heng and Tagg, 2006; Snyder and
Worobo, 2014).
However, the growing number of lantibiotic structures, biosynthetic
pathways and the discovery of non-antimicrobial lanthionin containing peptides, for
instance SapB (Kodani et al., 2004) and SapT (Kodani et al., 2005) [both involved in
aerial mycelium formation of streptomycetes], has strained the classification scheme
and the broader term “lanthipeptide” was adopted to encompass these non-
antimicrobials (Arnison et al., 2013; Goto et al., 2010). Lantibiotics became a large
subgroup of lanthipeptides of the RiPP family and a new classification scheme has
been created that divides the lanthipeptides into four groups according to
components involved in their maturation (Knerr and van der Donk, 2012) (Figure
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1.9). It is the belief of this study that application of this classification to categorise
lantibiotics is the more efficient approach.
The classification of these bacteriocins that is proposed as part of the current
study, as also agreed by the nomenclature study performed by Arnison et al. (2013),
is as follows:
1.5.1.1 Lanthipeptide class I
This class is characterised by the presence of two individual enzymes LanB and
LanC that are involved in the production of its members. LanB is a dehydrogenase
enzyme that is responsible for dehydration of Ser and Thr residues (Karakas Sen et
al., 1999; Kluskens et al., 2005; Koponen et al., 2002) while LanC is a cyclase that
facilitates the circularisation of the dehydrated residues through intramolecular
cysteine bonds (Koponen et al., 2002; Li et al., 2006; Lubelski et al., 2008). This
class contains members of the previously named type A lantibiotics such as Nisin
(Rogers, 1928), subtilin (Banerjee and Hansen, 1988) and epidermin (Allgaier et al.,
1985).
Figure 1.9 Four classes of the lanthipeptide family can be separated by the modification enzymes involved in generation of their lanthionine bridges. Solid lines indicate the conserved regions thought to play roles in the catalysis including zinc ligands that are missing in class III [from (Knerr and van der Donk, 2012)].
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1.5.1.2 Lanthipeptide class II
Class II contains the lanthipeptides that are dehydrated and cyclised by a
bifunctional LanM enzyme that consists of two domains; a dehydratase and a LanC-
like cyclase domain (Arnison et al., 2013; Begley et al., 2009; Knerr and van der
Donk, 2012; Singh and Sareen, 2014). Many peptides in this class were classified as
type B lantibiotics, actagardine (previously gardimycin) (Boakes et al., 2009) and
mersacidin (Bierbaum et al., 1995) are some examples. Class II also contains the two
component lantibiotics such as haloduracin (Lawton et al., 2007; McClerren et al.,
2006) and lacticin 3147 (Martin et al., 2004; McAuliffe et al., 1998; Ryan et al.,
1999).
1.5.1.3 Lanthipeptide class III
These lanthipeptides are modified with a tri-domain LanKC modification
enzyme that incorporates an N-terminal lyase domain, a central kinase domain to
dehydrate the Ser and Thr residues and a C-terminal putative cyclase that differ from
the cyclases of other classes as it lacks the three metal binding domains conserved in
the cyclases of these classes (Krawczyk et al., 2012; Müller et al., 2010). Some
examples of lantibiotics that belong to this class are erythreapeptin, avermipeptin,
griseopeptin (Völler et al., 2012) and curvopeptin (Krawczyk et al., 2012).
1.5.1.4 Lanthipeptide class IV
Similar to the class III lanthipeptides, class IV also employs a multicomponent
enzyme with a lyase and a kinase domain, however unlike Class III, LanL contains a
LanC like C-terminal domain (Arnison et al., 2013; Goto et al., 2011, 2010). To the
best of our knowledge there is only one putative lantibiotic, venezuelin, identified for
this class (Goto et al., 2010).
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1.5.2 Class II non-lanthionine containing bacteriocins
These are small bacteriocins that differ from lantibiotics by the fact that they are
not subjected to post translational modifications, except disulfide bridges and they
exhibit different modes of action (Figure 1.8) (Cotter et al., 2005; Kjos et al., 2011;
Nissen-Meyer et al., 2009). Class II bacteriocins are divided further into groups A, B
and C (Heng and Tagg, 2006). Here a slight change to the scheme is suggested and
class II two peptide bacteriocins are placed in group-B and the miscellaneous class II
bacteriocins in group-C, as this is the accepted nomenclature in current literature:
1.5.2.1 Class II-A pediocin-like bacteriocins
These bacteriocins are renowned for their effectiveness against Listeria
species. They contain a highly conserved YGNG(V/L) (“pediocin box”) amino acid
string encoded on their N-terminus. This consensus can be further extended to
YGNG(V/L)xCxxxxCxVxWxxA (Eijsink et al., 1998; Héchard and Sahl, 2002; Kjos
et al., 2011). The first member of the family discovered was the pediocin PA-1
(Gonzalez and Kunka, 1987) and thus they are often defined as pediocin like
substances. A study performed on 50 representatives of this class has shown that
they could be further divided into eight subgroups according to their primary and 3D
structures and mode of action (Cui et al., 2012). Some prominent examples of this
group include Enterocin P (Cintas et al., 1997), Bavaricin MN (Kaiser and
Montville, 1996) and divercin V41(Bhugaloo-Vial et al., 1999).
A connection between the mode of action of Class II-A bacteriocins and the
mannose phosphotransferase system (man-PTS) was suspected (Gravesen et al.,
2002; Ramnath et al., 2000), however a study using the Lactococcin A has proven
these suspicions through deletion of man-PTS components which confirms that the
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action of Lactococcin A, and likely other pediocin like peptides, is dependent on the
presence of IID and IIC transmembrane proteins of the Man-PTS (Figure 1.10) (Diep
et al., 2007; Kjos et al., 2011).
1.5.2.2 Class II-B two component bacteriocins
These bacteriocins are composed of two peptides that work together to
achieve lethal activity. Although occasionally some antimicrobial effect is observed
from one of the components only, the optimal activity is achieved when each peptide
is present and components from different pairs don’t complement each other
(Garneau et al., 2002; Oppegard et al., 2007). This was observed very clearly when
Anderssen et al. (1998) tested Plantaricins EF and JK and found that both pairs were
103 times more active than individual components and cross combinations of
subunits of each pair didn’t yield any complementary activity (Anderssen et al.,
1998; Oppegard et al., 2007). Genetic evidence also suggests that Class II-B
bacteriocins evolved to act as one unit as the genes encoding both subunits are
located close to each other and only one immunity gene is present for each pair, such
as is seen with lactocin 705 and Enterocin 1071 (Cuozzo et al., 2000; Franz et al.,
2002; Oppegard et al., 2007).
Class II a bacteriocin
Figure 1.10 Class II-A bacteriocin action is dependent on the presence of IID and IIC proteins, which are membrane proteins of the Man-PTS mechanism. Class II a bacteriocin first binds to the extracellular loop and then to the transmembrane helices of these peptides causing conformational changes that leads to efflux and cell death [from (Kjos et al., 2011)]
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1.5.2.3 Class II-C Miscellaneous bacteriocins
This class is made up of linear class II bacteriocins that do not fit into any
other class. Epidermicin NI01 (Sandiford and Upton, 2012), LSEI 2163 (Kuo et al.,
2013), Lacticin Q (Fujita et al., 2007) and Lacticin Z (Iwatani et al., 2007) are some
of the best examples of this group. They contain no leader peptide or pediocin box
and don’t carry any post translational modifications (Cotter et al., 2005; Heng and
Tagg, 2006; Kjos et al., 2011; Nissen-Meyer et al., 2009).
1.5.3 Class III large proteins:
These bacteriocins are traditionally defined as structurally large and heat
labile molecules, however, Cotter et al. (2005) had proposed a modification to the
definition of Class III bacteriocins, defining them as non-bacteriocin lytic proteins
and suggested naming the class as bacteriolysins. However as Heng and Tagg (2006)
pointed out, many of these peptides including lysostaphin and zoocin A carry
bacteriocin like properties (Beatson et al., 1998; Thumm and Gotz, 1997). In
addition while some large bacteriocins (lysostaphin) kill through lysis (Figure 1.8,
page 44), some such as dysgalacticin don’t; this heat stable large peptide acts by
inhibiting glucose fermentation (Cotter et al., 2005; Joerger and Klaenhammer,
1986; Swe et al., 2009). Thus, instead of using the term bacteriolysins, Heng and
Tagg (2006) suggested the name “large proteins” and divide the group into two;
bacteriolytic and non-bacteriolytic large peptides.
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1.5.4 Class IV Cyclic peptides
These peptides are head to tail cyclysed (cyclisation occurs through bonding
between C to N termini, not by intramolecular cyclisation) to assume their distinctive
form (Arnison et al., 2013; Gabrielsen et al., 2014). All 10 members of this group
are exclusively produced by Gram positive bacteria and recent observations have
shown that they share common properties and can be divided into two sub-groups
(Gabrielsen et al., 2014; Martin-Visscher et al., 2009). The first group (Class I)
contains the enterocin AS-48 like peptides that have a high isoelectric point and are
positively charged peptides while preserving the overall cationic charge (Arnison et
al., 2013; Gabrielsen et al., 2014). Enterocin AS-48 is a potent antimicrobial peptide
(José et al., 2014) and it’s the best known member of the cyclic peptides. Other
examples of this group include circularin A (Kemperman et al., 2003a, 2003b) and
lactocyclicin Q (Sawa et al., 2009).
The second sub-group (Class II) is much smaller with only two affiliates
gassericin A (Kawai et al., 1998) and butyrivibriocin AR10 (Kalmokoff et al., 2003).
These peptides are anionic and tend to be neutral or positive in charge when under
physiological conditions and have a low isoelectric point (Arnison et al., 2013;
Gabrielsen et al., 2014). Also, it must be mentioned that some circular bacteriocins
contain sulphur to α-carbon bonds and are currently classified under the sactibiotic
group such as the subtilosin A (Gabrielsen et al., 2014; Kawulka et al., 2003) (see
Section 1.7.1).
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1.6 BACTERIOCINS OF GRAM-NEGATIVE BACTERIA
Although the term bacteriocin is generally associated with AMP produced by
Gram positive bacteria, the term was devised to include AMPs derived from both
Gram positive and negative bacteria (Jack et al., 1995). Gram-negative bacteriocins
in general can be divided into two main categories, the colicins and the microcins
depending on the size of the AMP, and very much like their Gram positive relatives,
they carry the bacteriocin traits described in Section 1.4.
1.6.1 Colicins
Colicins can be distinguished from microcins primarily with their larger size
(̴ 25-80kDa). There are four known modes of action for colicins; these are (1) pore
formation in the cytoplasmic membrane [e.g. Colicin A (Braun et al., 1994)], (2)
DNA degeneration [Colicin E2, E7, E9 (Mora and de Zamaroczy, 2014)] (3)
inhibition of protein synthesis [Colicin DF 13, E3 (Gillor et al., 2004; Mora and de
Zamaroczy, 2014)] and (4) inhibition of lipopolysaccharide and murein synthesis
[Colicin M (Gillor et al., 2004)]. However, the colicin must first gain access to the
target.
To gain access to the target site, each colicin binds to a specific receptor on
the target bacteria that is involved in the uptake of various nutrients and they are
translocated into the cell using either the Tol or the TonB pathways (Figure 1.11)
(Cascales et al., 2007; Gillor et al., 2004).
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The class of a colicin, is also dictated by the pathway it exploits to gain
access to the target cell. The colicins that use the Tol pathway are classified as Group
A colicins and utilise TolA, TolB, TolQ and TolR (Figure 1.11) (Lloubès et al.,
2012). Group A colicins are encoded by small plasmids and are secreted into the
media. Although colicin producing strains code for immunity proteins that confer
resistance to the producing bacteria, the production mechanism of group A colicins
is dependent on the SOS pathway and is accompanied by the production of a lysis
protein lethal to the producing cell (Cascales et al., 2007; Gillor et al., 2004). Thus,
group A colicin production may be defined as an altruistic process as the production
is initiated under depleting nutrient availability and the release results in death of the
producer and in turn that of nearby sensitive bacteria providing advantage to the
remaining cells of the producer population in the competition for nutrients (Cascales
et al., 2007). The colicins that gain access to the target using the ExbB–ExbD–TonB
pathway (Figure 1.11) are classified as Group B colicins (Lloubès et al., 2012). In
Figure 1.11 Mechanisms of cellular entry used by colicins. ExbB, ExbD components in the TonB pathway are used by group B colicins and the Tol pathway (TolA, TolB, TolQ and TolR) is employed by group A colicins [from (Lloubès et al., 2012)].
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contrast to Group A, the colicins in Group B are encoded by large plasmids and
unlike Group A they are not actively secreted into the media from the producer
(Cascales et al., 2007). However, it should be noted that colicins from both groups
can have shared properties (Cascales et al., 2007; Pilsl and Braun, 1995).
1.6.2 Microcins
The term microcin (Mcc) was first proposed in 1975 by Asensio and Perez-
Diaz, after they had discovered 10 antimicrobials from a culture of human faecal
bacteria, all of which had a molecular weight less than "1000" (Asensio and Pérez-
Díaz, 1976). Although microcins and colicins are mainly distinguished in the basis
of weight, there are other key differences between them, most importantly microcin
production does not depend on the SOS pathway and is non-lethal to the producing
bacteria (Duquesne et al., 2007a). In addition, colicins are found encoded on
plasmids, whereas operons encoding microcis can be found on both plasmids and the
bacterial chromosome.
Unlike other bacteriocins, very few microcins have been identified so far and
even less have been structurally characterised. With the recent discovery of microcin
S by Zschuttig et al. (2012) only 19 microcins have been identified to date (Zschüttig
et al., 2012). These figures are based on literature searches and examination of
entries in the BactiBase database (http://bactibase.pfba-lab-tun.org/main.php) carried
out before 1st July 2015. All known microcins, except microcin C, are translated as
propeptides that consists of a leader sequence that is cleaved later in the maturation
process and a core peptide (Duquesne et al., 2007a; Rebuffat, 2012). Both the
propeptide and the core peptide may go through post translational modifications. As
a result, within this small collection, there is vast structural diversity and varied
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modes of action (Figure 1.12 and Figure 1.13).Hence, until recently microcins did
not have a well-defined classification scheme. In 2000 Gaillard-Gendron et al. had
suggested classifying microcins in two groups and Pons et al. (2002) later elaborated
on this attempt and proposed the first microcin classification scheme (Gaillard-
Gendron et al., 2000; Pons et al., 2002). According to this scheme, microcins were
divided into two groups depending on their action site, size and any post
translational modification. Class I mirocins are defined by their activity against
intracellular targets and have a mass of <5kDa. These microcins are post
translationally modified. In contrast, Class II microcins are defined as cell
membrane active agents with a mass of more than >5kDa and they contain no post
translational modifications (Pons et al., 2002).
Figure 1.12 Class I microcin action. A) Microcin (Mcc) J25 gains access to the cell through the outer membrane (OM) receptor FhuA and then utilises the TonB/ExbB/ExbD complex and SbmA protein to translocate into the cytoplasm where it inhibits transcription by attacking the RNA polymerase enzyme (Mathavan et al., 2014). B) Mcc B17 targets the DNA gyrase enzyme that is responsible for supercoiling of the DNA, it gains access to the inner membrane (IM) using the OmpF porin on the OM and is translocated into the cell by exploiting the SbmA protein. C) Although the entry mechanism of Mcc C7/C51 is unknown, it acts by inhibiting aspartyl-tRNA synthetase [from (Duquesne et al., 2007a)].
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Following identification of the secreted post translationally modified form of
microcin E492 by Duquesne et al. (2006), which has a mass of 7906.02,
classification parameters suggested by Pons et al. (2002) were not sufficient and this
prompted Duquene et al. (2007) to propose a revised and a more detailed
classification method. According to this classification scheme, the classes are
assigned according to the “presence and type of the posttranslational modifications,
the gene cluster organisation and the leader peptide sequences” (Duquesne et al.,
2007a). Although the two schemes do share similarities, the classification scheme by
Duquesne et al. (2007) also divides classes initially according to their size, placing
low molecular weight microcins into Class I and microcins with a higher molecular
weight into Class II. Class I microcins are defined by extensive post translational
modifications on their peptide backbone and include microcin C (or C7–C51), the
only microcin that is post translationally modified with a nucleotide attachment, and
J25, a lassopeptide that contains a lasso fold (Arnison et al., 2013; Duquesne et al.,
2007a; Mathavan et al., 2014; Rebuffat, 2012).
Class II microcins, however, are further divided into an additional two
subgroups. The Class II microcins with no post translational modifications other than
disulphide bonds are placed under Class IIa (microcins L, V and N), while linear
microcins that may contain C-terminal post translational modifications are collected
under Class IIb (microcins E492, G492, M, H47, I47) (Duquesne et al., 2007a;
Rebuffat, 2012). It is also possible to refer to Class IIb microcins as the siderophore
microcins as all the current members of the group are modified with a siderophore
moiety attached to the C terminal.
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Siderophores are secreted to bind and transport a single Fe3+ iron molecule
into the cells through the catechol-siderophore (FepA Cir, Fiu) receptors (Figure
1.13). Once attached to the microcin, it facilitates the trojan horse mode of action of
the microcin (Nolan and Walsh, 2008; Nolan et al., 2007; Rebuffat, 2012; Thomas et
al., 2004; Vassiliadis et al., 2010, 2007).
Figure 1.13 Class IIb microcin action MccE492 (A), MccM (B), MccH47(C) and MccI47 (D)* all exploit the catechol-siderophore receptors and are translocated into the periplasm in a TonB pathway dependent manner. Once inside, MccE492, using the ManY and ManZ membrane proteins of the mannose permease complex as docking stations, inserts itself into the inner membrane where it disrupts the IM potential by allowing protons to leak. On the other hand, MccH47 inhibits ATP synthase by interfering with the F0 component once it gains access to the periplasm. The exact mechanism of action for the remaining microcins of this group is not known [modified from (Duquesne et al., 2007a)] . *MccI47 peptide has not been isolated, but on the basis of predicted amino acid sequence it contains the serine rich C-terminal that is associated with siderophore interaction.
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1.7 MISCELLANEOUS RIPP BACTERIOCINS
There have been a number of new RiPP bacteriocin families that have recently
emerged as sources of antimicrobial peptides that are too different to be classified
under the current bacteriocin classification schemes. In this section, some of the
more significant groups are described.
1.7.1 Sactibiotics (Sulphur to α-carbon antibiotics) or sactipeptides
Sactibiotic is the name given to the antimicrobially active members of the
sactipeptide family that are defined by the intramolecular bonds formed between
cysteine sulphur and α-carbon residues during the post translational modification of
these peptides (Arnison et al., 2013; Lohans and Vederas, 2013). Example
sactibiotics identified to date include thuricin CD (Rea et al., 2010), thurincin H (Sit
et al., 2011), subtilosin A (Kawulka et al., 2003) and propionicin F (Brede et al.,
2004).
1.7.2 Thiopeptides
Also known as thiazolyl or pyridinyl polythiazolyl peptides, are a large group
with over 100 members and they are best known for their antimicrobial activity
(Arnison et al., 2013; Bagley et al., 2005; Just-Baringo et al., 2014) but they also
exert anti-cancer (Pandit and Gartel, 2011) and anti-malarial traits (Aminake et al.,
2011). The complex structure of a thiopeptide is often composed with a macrocycle
supporting thiazole rings and the most distinguishing feature is the six membered
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nitrogen containing central ring that can be located at three oxidation sites,
piperidine, dehydropiperidine, or pyridine (Arnison et al., 2013; Bagley et al., 2005;
Just-Baringo et al., 2014). One of the best known examples of thiopeptides is the
micrococcin (Su, 1948), and more recent discoveries include philipimycin (Zhang et
al., 2008a) and thiazomycin A (Zhang et al., 2008b).
1.7.3 Bottromycins
Bottromycins have established themselves as a unique class following the
solving of their structure in 2009 by Shimamura and colleagues through their studies
on bottromycin A2 and the ribosomal nature of bottromycin production was revealed
following subsequent studies on the biosynthesis pathway of bottromycin derivatives
including A2 and D (Crone et al., 2012; Gomez-Escribano et al., 2012; Hou et al.,
2012; Huo et al., 2012; Shimamura et al., 2009). Distinctive properties of
bottromycin structure include macrocyclic amidine and a decarboxylated C-terminal
thiazole ring (Arnison et al., 2013). Bottromycins are effective inhibitors of MRSA
and VRE isolates (Kobayashi et al., 2010).
1.7.4 Glycocins
These are a group of glycolpeptide bacteriocins that are glycosylated on
cysteine residues. The group contains two representatives; sublancin 168 and
glycocin F produced by Bacillus subtilis 168 and Lactobacillus plantarum KW30,
respectively (Arnison et al., 2013; Garcia De Gonzalo et al., 2014; Oman et al.,
2011; Stepper et al., 2011; Venugopal et al., 2011) .
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1.7.5 Linear azol(in)e-containing peptides (LAPs) and lasso peptides
These are the two RiPP groups that cover a rather grey area. Although there
have been only a few antimicrobially active representatives identified so far, the
group includes AMPs produced by both Gram-negative (MccB17 [Linear azol(in)e-
containing peptide - LAP] and MccJ25 [lasso peptide] from E. coli) (Arnison et al.,
2013; Lee et al., 2008; Li et al., 1996; Salomón and Farías, 1992) and Gram positive
(Plantazolicin [LAP] from Bacillus amyloliquefaciens FZB42 (Scholz et al., 2011)
and lariatins A and B [lasso peptide] from Rhodococcus jostii K01-B0171(Iwatsuki
et al., 2007)) species. Lasso peptides are set apart from the other RiPPs by the lasso
fold that that forms a knotted structure that gives these peptides high stability against
enzymes and denaturing agents (Figure 1.14) (Arnison et al., 2013; Maksimov et al.,
2012; Mathavan et al., 2014). This is a good way of demonstrating how much more
we can learn from bacteriocins and as we learn more how the classification schemes
may further blur and we must expect these schemes to morph to accommodate newer
classes soon.
Figure 1.14 A diagram of Microcin J25 structure, demonstrating the lasso fold [from (Maksimov et al., 2012)]
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1.8 POLYKETIDES
Polyketides (PK) are natural products biosynthesised by protein structures
called polyketide synthases (PKS). Polyketides show notable biological activity and
some of the most important antibiotic classes such as the macrolides (erythromycin)
belong in this family as well as important immunosuppressants and anti-tumour
agents. Until recently, PKs produced by bacteria were divided into two main
categories according to the PKS that they are derived from. Modular polyketides
were derived from PKS type 1 (PKS 1) while aromatic polyketides were derived
from PKS type 2 (PKS 2) (McDaniel et al., 2005). However, PKS type 3 driven
aromatic polyketides previously only observed in fungi and plants have been
recently observed in bacteria as well (Gross et al., 2006; Saruwatari et al., 2011).
PKS 1 consists of large multifunctional proteins and the polyketides derived
from it are modular with complex structures. These compounds are generally hard to
modify using chemical methods; however, they are much more responsive in
comparison with PKS 2 derived compounds (Watanabe et al., 2007). Erythromycin
is a PKS 1 derived antibiotic (McDaniel et al., 2005). Although there is not much
reference to their antimicrobial potential, it is noteworthy to state that PKS 2 consists
of monofunctional proteins, while unlike any of its cousins, PKS 3 is a single protein
(Watanabe et al., 2007).
PKS 1, involved in the production erythromycin, also played a key role in the
process of understanding the ribosome independent assembly systems. In 1990,
Cortes et al. and in 1991 Donadio et al. cloned three genes that were involved in the
production of this PK, unlocking the mystery behind the production of these
ribosome independent assembly lines and making genetic manipulations possible
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(Cortes et al., 1990; Donadio et al., 1991). Although chemically hard to modify,
these compounds are now observed to be very flexible in terms of genetic
modifications (McDaniel et al., 2005). The main limitation that polyketide discovery
was facing, is now known to be the fact that many of the PKS assembly lines are
encoded by silent genes (Gross et al., 2006).
1.9 NON-RIBOSOMAL PROTEINS
In 1963, Mach et al. performed an experiment using a series of antibiotics
that inhibited ribosomal protein synthesis in Bacillus brevis, yet the group observed
that the cyclic protein tyrocidine was produced in each case, presenting the science
community with the very first evidence of ribosome independent peptide synthesis
(Felnagle et al., 2008; Mach et al., 1963). Some of the most important and widely
used antibiotics, such as penicillin, vancomycin and some of the recently introduced
antibiotics such as the lipopeptide, daptomycin are non-ribosomal peptides (NRP)
(Felnagle et al., 2008). Indeed NRPs are still a lucrative source of antimicrobial
discovery (Cochrane and Vederas, 2014).
Like PKs, NRPs are also assembled by proteins called non-ribosomal protein
synthetases (NRPS), these synthetases are encoded ribosomally and then work
together to assemble a protein and thus these proteins are considered independent of
ribosomal protein synthesis. The assembly mechanism contains a minimum of three
indispensable components; (1) an adenylation domain, (2) a peptidyl carrier protein
domain and (3) a condensation domain (Marahiel et al., 1997; Schwarzer et al.,
2003; Tambadou et al., 2014). Ribosome independence provides the NRPs with a
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number of unique structures that clearly distinguish them from their ribosomally
synthesised counterparts, adding to their value as chemical templates (e.g. more
variety for combinatorial chemistry). These proteins are generally found as
macrocyclic, branched macrocylic, dimers or as trimers (Figure 1.15) (Schwarzer et
al., 2003). Also, unlike their counterparts, these compounds can commonly contain
non-proteogenic amino acids (e.g. N-methylated residues and ornithine), heterocylic
rings (e.g. oxazoline), fatty acids and glycolysations (Schwarzer et al., 2003; Sieber
and Marahiel, 2003).
Figure 1.15 Examples of NRP structures. Tyrocidine A is a good example for macrocyclic NRPs, while surfactine is a good a good example of branched macrocyclic NRPs [from (Schwarzer et al., 2003)]
Although very different from each other in many ways, PKS and NRPS
systems share substantial similarities; both systems employ Ppan carriers to achieve
covalent bonding of monomers and elongation of the chain. In fact the similarities
between PKS and NRPS machineries go as deep as to allow hybrid assembly lines
and thus hybrid products to appear (Figure 1.16). Some important hybrids include
epothilone D and ramapycin (Stein, 2005; Walsh and Fischbach, 2010).
Tyrocidine A
Surfactine
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1.10 LYSINS:
This review concentrates on bacterially derived antimicrobials and because
the lysins referred to here are endolysins (commonly called lysins in the literature)
and are encoded by double stranded DNA bacteriophages, they will not be reviewed
in detail. However, they are interesting natural products and it is worth mentioning
that the lysogenised DNA of bacterial cells, with assistance from bioinformatics, can
be a good source for identifying these peptides (Fischetti, 2010). Bacterial genetic
libraries that now contain a large number of gene sequences are expected to contain
lysogenised bacterial DNA sequences (Schmitz et al., 2011). Thus, they also contain
the lysin genetic code embedded inside their gene sequence, which is required for the
production of the lysin encoded by the phage; Schmitz et al. (2011) identified a lysin
PlyCM in such a way.
Figure 1.16 A hybrid NRP/PK. NRPS derived structure is coloured in blue while PKS derived structures are red [from (Walsh and Fischbach, 2010)]
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1.11 ADVANCES IN NATURAL PRODUCT SCREENING
1.11.1 Purification and identification of the active compound
Rediscovery of known compounds beyond doubt is the biggest hurdle for
natural antimicrobial discovery. It has a high cost in terms of equipment, money and
most importantly time. However, some of the most significant developments in the
field have occurred in purification and de-replication methods. Especially, rapid
identification methods with easily accessible electronic libraries makes de-
replication (differentiation of novel and known products from each other) immensely
easier. Older methods that required milligrams of sample have been replaced with
advanced equipment that is sensitive enough to work with small quantities of
peptides that are likely to be achieved through initial purification efforts (Wright,
2014). Mass spectrophotometry (MS) is generally preferred for the task and with the
introduction of highly sensitive systems such as the orbirtrap, it has become possible
to rapidly fragment peptides using tandem mass spectrometry (MS/MS) and perform
de novo peptide sequencing to identify the amino acid sequences of unknown agents
(Bouslimani et al., 2014; Potterat and Hamburger, 2013).
Nuclear Magnetic Resonance (NMR) is also a useful tool that is becoming
widely used, as in addition to higher field strengths the improvements in the system
allows better room temperature data collection and for the equipment to be installed
in non-specialised enclosures (Breton and Reynolds, 2013; Leeds et al., 2006;
Wright, 2014). Here it should be also noted that UV based detection methods are
also available, but not commonly used (Leeds et al., 2006).
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High pressure liquid chromatography (HPLC) is still the gold standard
accepted for purification and recovery of natural products prior to identification.
However, both HPLC and solid phase separation techniques that can be used in
conjunction with HPLC have become more convenient and efficient (Lam, 2007;
Leeds et al., 2006).
By physically combining purification and de-replication methods explained
above, streamlined system can be set-up to increase the speed and sensitivity of
purification and identification. Examples of these systems include preparative LC-
MS, LC-MS/MS, LC-NMR and many others (Harrigan and Goetz, 2005; Leeds et
al., 2006; Nielsen et al., 2011). The data obtained from all of the methods above can
be collected in respective or interchangeable data banks that can be cross checked in
the future, making these methods highly amenable to high throughput screening
(Ibrahim et al., 2012; Wright, 2014; Yang et al., 2013).
In addition, next generation gene sequencing platforms (Pac-Bio, Roche 454,
Illumina MiSeq, Ion Torrent) have significantly increased the overall capacity and
the speed and sensitivity of genome sequencing while driving the costs down; this
feeds into the refreshed natural product discovery process seamlessly (Quail et al.,
2012; Wright, 2014). Through these approaches the need for time consuming reverse
genetics is eliminated and the coding gene sequence of the antimicrobial of interest
can be identified rapidly using the de novo sequencing data obtained from the
MS/MS analysis to query the draft genome of the producer bacteria directly. In
addition, easier access to efficient genome sequencing tools are helping create an
immense library of bacterial genomes making genome mining for natural products a
very feasible and attractive option (Genilloud, 2014).
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1.11.2 Identification of producer strains
Isolation and identification of strains producing putative novel natural
products is crucially important both for yield optimisation and further studies. Older
methods have relied on microscopic observation and biochemical tests, which have a
decreased chance of identifying closely related species from each other or present
unrelated species as similar. The development of PCR based identification methods
such as 16S rRNA gene sequence analysis has become an invaluable and reliable
way of rapid bacterial identification (Marchesi et al., 1998; Woo et al., 2008). The
analysis of the data achieved by this approach has helped show the limited
biodiversity between the previously isolated producer species (Davies, 2011).
1.11.3 Genome mining and scanning for natural products
Although target based approaches have failed, some of the reasons behind the
switch are still valid. Conventional methods of natural product research in the pre-
genomic era involved screening of hundreds of bacteria against indicator strains
using methods such as overlay and stab inoculation assays. Although still effective,
these methods are time consuming and have limitations as in order for any activity to
be observed, bacteria of interest should be producing sufficient amounts of the
antimicrobial compound that achieves inhibition of the indicator strain. However,
bacteria may not produce enough of the active agent if optimal conditions are not
achieved and in some cases a gene may be cryptic or can be switched off under lab
conditions (Davies, 2011; Kang and Brady, 2013; Scherlach and Hertweck, 2009).
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Cryptic genes are being recognised as a promising untapped source of natural
products including antimicrobial compounds (Zhu et al., 2012). It is possible to
initiate expression of the genes through manipulation of culture conditions or to
improve the production of certain peptides (Rigali et al., 2008; Zhu et al., 2014). A
good example is the isolation of a polythioamide antibiotic from Clostridium
cellulolyticum through addition of aqueous soil extract to the growth media (Lincke
et al., 2010). However, it is also possible to use in silico genomic homology based
techniques that take advantage of rapidly advancing and more affordable whole and
metagenomic sequencing tools. Complimentary bioinformatics software can detect
shared homologies between bacteriocins and when combined with improved
recombinant cloning techniques that can deal better with toxic genes (Guan et al.,
2013; Guo and Jia, 2014) and novel expression procedures (eg: in vitro expression)
(Whittaker, 2013), cryptic genes could be expressed without media optimisation.
These homology approaches rely on motifs, conserved sequences shared
between the genes or gene clusters encoding natural antimicrobials, derived from
existing genetic data to identify in vitro or in silico other gene sequences that may
yield active natural products. Motifs can be whole structures involved in the
synthesis of the antimicrobial or after its modification. The 6-Deoxyerythronolide B
synthase (DEBS), for example, is an essential part of the PKS machinery involved in
erythromycin production and is known to be conserved among biosynthesis
pathways of multiple other polyketide antibiotics belonging to the 14-membered
macrolide family including megalomicin and oleandomycin PKS (McDaniel et al.,
2005). On the other hand LanB, LanM, LanKC and LanT are essential within the
lantibiotic gene loci and, as discussed in Section 1.5.1, contain highly conserved
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domains to carry out their activity. These features can be employed to drive genome
mining studies (Arnison et al., 2013; Begley et al., 2009; Blin et al., 2014; McDaniel
et al., 2005; Singh and Sareen, 2014).
Motifs can also be short sequences preserved within the structure of certain
classes of antimicrobial peptides. A good example is the extended pediocin box
YGNG(V/L)xCxxxxCxVxWxxA motif conserved among the class IIa bacteriocins
(Eijsink et al., 1998; Héchard and Sahl, 2002; Kjos et al., 2011). Another sequence
conserved in Gram positive producers of the class II bacteriocins and some in class I,
is the double glycine motif “LSX2ELX2IXGG”, which has been discovered to also
be present in the leader peptide sequence of Gram-negative bacterial microcins,
including MccV (colicin V) and multiple class II microcins (Dirix et al., 2004;
Havarstein et al., 1994). Later, this motif was identified more widely in Gram-
negative bacteria and has been exclusively extended and refined to
“M(R/K)ELX3E(I/L)X2(I/V)XG(G/A)” for Gram-negative organisms and
successfully used to identify in silico other possible antimicrobial peptides (Dirix et
al., 2004; Wang et al., 2011).
Bioinformatic approaches to antimicrobial peptide discovery don’t only
revitalise identification of actively produced natural products, but they open up a
world of new opportunities, for they may efficiently allow the identification of the
cryptic gene clusters effectively (Zazopoulos et al., 2003). Many methods have been
developed to aid in this effort but the first example is a study performed by Challis
and Ravel (2000), who compared known NRPS motifs to the genome of
Streptomyces coelicolor group, a novel NRPS that is involved in the production of
Coelichelin was isolated. Coelichelin is a peptide with siderophore activity. This
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study marks the discovery of the first novel secondary metabolite identified by
relying solely on genomic homology (Challis and Ravel, 2000; Taylor and Wright,
2008).
Another early genome scanning procedure developed by Zazopoulos et al.
(2003) is an approach that is more laboratory oriented than in silico. It involves using
DNA fragments generated by shotgun DNA sequencing of high molecular weight
genome fragments for a cloning based screening approach. The larger fragments
generated are inserted into cosmid and bacterial artificial chromosome (BAC)
vectors to produce a cluster identification library (CIL) that possibly contains whole
natural product biosynthetic pathways. The shorter fragments are used in the
generation of genome sequence tags (GST). By comparing the GSTs to a database
containing gene sequences involved in natural product biosynthesis pathways (E.g.
PKS or NRPS coded antibiotics), matching GSTs that are possibly involved in such
processes are flagged to be used as probes to scan the CIL to identify members that
contain matching genes, these plasmids are then processed and sequenced to yield a
complete natural product biosynthesis pathway (Zazopoulos et al., 2003).
Using this method, several active compounds were identified including
antimicrobial, antifungal and anti-cancer drugs (Banskota et al. 2006; Zazopoulos et
al. 2003). An example is the identification of a PKS from the bacterium
Amycolatopsis orientalis that is involved in the production of polyketide ECO-0501,
an agent with significant antimicrobial activity, among 10 other additional secondary
metabolites during the course of the study (Banskota et al. 2006). This demonstrates
the efficiency of in silico based approaches and the possibilities it can unlock.
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Today there are web-based programs that utilise and streamline the above
principles to identify similar gene sequences to that of conserved sequences of
known antimicrobial compounds, in order to define new natural products that can
possess potential antimicrobial activity. The Bacteriocin Genome Location tool
(BAGEL3) (http://bagel.molgenrug.nl/index.php/bagel3, last access: 21/05/15) (de
Jong et al., 2010) and secondary metabolite identification tool antiSMASH are two
good examples (Blin et al., 2013). More background for BAGEL software is given
in Chapter 5 of this thesis.
Through all the above methods, structural predictions can be made from the
genetic information obtained, as the physicochemical properties of the active
compound produced are essential for devising assays to detect the compound and/or
to promote conditions that will invoke its production (Lautru et al., 2005) as well as
allowing its cloning and expression.
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1.12 AIMS AND OBJECTIVES
The literature review above was written to highlight the increasing threat that
antimicrobial resistance poses and expose the significance of, and underlining
reasons for diminished antibiotic discovery rates. Also, the intention was to
emphasise the wealth of natural antimicrobial products that are present in the
microbial world and highlight their continuing potential for development as novel
antibiotic leads. In addition, the review introduced some of the new methods and
technologies that can remove the barriers that have been plaguing more recent efforts
in novel natural product based antibiotic discovery.
It is the aims of this study to:
1. Help address the problem of antibiotic resistance by developing novel
inhibitors of prominent pathogenic bacteria. This will be achieved by
embracing traditional natural product screening approaches and combining
them with cutting edge dereplication and protein identification techniques.
The following objectives were set to achieve the stated aim:
a. A screening program will be conducted using bacteria from
environmental and clinical samples, to identify potent inhibitors of
Gram positive and Gram-negative bacteria.
b. Purification and dereplication of identified agents is going to be
facilitated through a combination of chromatography, mass
spectrometry and next generation sequencing techniques.
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c. Following preliminary characterisation of the inhibitors to confirm
the physicochemical properties and the spectrum of activity, the
toxicity of the identified agents against eukaryotic cells will be
assessed.
2. Explore in silico homology searching software as an alternative means of
natural product antibiotic discovery. In addition, to develop an in house cell
free expression model that will enable expression of these in silico identified
peptides or, if possible, more efficient production of agents discovered as part
of the traditional screening approach. The objectives set to achieve this are as
follows:
a. The in silico bacteriocin discovery software tool BAGEL 3 will be
employed to screen the genomes of a selection of publicly available
anaerobic bacteria. After manual inspection, promising putative
bacteriocin candidates will be short listed for possible expression.
b. An expression model will be built around the PURExpress cell free
expression system and a T7 promoter regulated expression plasmid.
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2 CHAPTER 2
METHODS
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2.1 IN VITRO ANTIMICROBIAL PEPTIDE SCREENING AND
CHARACTERISATION
2.1.1 Bacterial isolates
For the natural product discovery programme samples from two sources
(clinical and environmental) were collected between September 2011 and February
2012. Clinical samples were collected from plates inoculated with high vaginal
swabs (HVS) as part of the Central Manchester Foundation Trust routine
bacteriology laboratory activities between January and February in 2012. Plates that
were found to be negative for carriage of likely agents of sexually transmitted
diseases were kindly made available for use in this project. Isolated bacterial
colonies from these plates were screened for antimicrobial agent production by Mr
John Moat (University of Manchester) using the simultaneous antagonism assay (see
below), and the antimicrobial producers were made available for further
identification and characterisation.
The environmental samples used were collected from settle plates placed at
various locations around the Microbiology Department at the University of
Manchester, soil samples were obtained from Whithworth and Platt fields parks in
Manchester, UK and isolates were recovered from swabs of table and cupboard tops
within the Manchester Royal Infirmary. An attempt was made to increase the chance
of discovering bacteriocins that would be effective against clinically relevant
bacteria, by collecting samples from clinical settings and human body that possibly
co-reside with clinically relevant bacteria as bacteriocins are known to be effective
against closely related bacteria (Cascales et al., 2007; Jack et al., 1995). These
samples were inoculated onto Columbia agar base (CAB) (Oxoid Ltd., Basingstoke,
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England) and Columbia blood agar (CBA) plates (oxoid), which were incubated at
37oC for 24 hours.
Routine propagation of strains under investigation was carried out using
CAB. Liquid cultures were prepared by inoculation of tryptone soy broth (TSB) and
incubated at 37oC for 24 hours. Bacteria that were retained for future study, in this
and other projects, were stored at -80oC in microbank beads (Fisher scientific,
Loughborough, UK). Single colonies isolated from the above screening plates were
tested for antimicrobial activity using the simultaneous antagonism assay (see
Section 2.1.4.1). Bacterial strains displaying promising activity were identified using
16S rRNA gene sequence determination (see Section 2.1.2). The producer
organism/s that displayed strong antimicrobial activity against indicator species were
chosen for further assessment.
2.1.2 Identification of the producer strains using 16S rRNA gene sequencing
The 16S rRNA gene sequencing was performed to identify the organisms
producing inhibitors (producer organisms) of interest. It is one of the most accurate,
time efficient and reliable identification methods currently available (Marchesi et al.,
1998). Chromosomal DNA was extracted from 0.5 ml of a 10ml overnight tryptic
soy broth (TSB) culture of the target producer using the PrepManTM Ultra extraction
kit (Applied Biosystems, California, USA) according to the manufacturer’s
instructions.
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PCR amplification of the 16S rRNA gene was performed using a set of
universal PCR primers allowing analysis of almost the entire target. These primers
were 63f (5'-CAG GCC TAA CAC ATG CAA GTC-3') and 1387r (5'-GGG CGG
WGT GTA CAA GGC-3') (Eurofins, Germany) (Marchesi et al., 1998) (10pmol/µl
final concentration). The PCR reactions were carried out using 2x BioMix™ Red
(Bioline Reagents Ltd. London, UK), ready to use reaction mixture that included an
ultra-stable Taq DNA polymerase, with 1µl of template DNA extract. The reaction
was carried out on an Biorad T100 thermal cycler (Biorad) and parameters consisted
of an initiation cycle at 94ºC for 2 min, followed by 35 cycles of a denaturation step
at 94ºC for 1 min, primer-annealing step at 60 ºC for 1 min and an extension step at
72ºC for 1 min. The reaction was completed with an extension step at 72ºC for 5
min, and the product was kept at 4ºC prior to clean up for PCR. The product was
visualised using gel electrophoresis (see Section 2.1.3) and quality and quantity was
assessed using a Nanodrop 1000 spectrophotometer (Thermo Scientific, Hemel
Hempstead, UK).
Prior to sequencing, the PCR product was purified using ExoSAP-IT PCR
Clean-up Kit (Affymetrix, High Wycombe, UK). ExoSAP-IT is a combined enzyme
kit that removes any remaining dNTPs and master mix residues that may interfere
with the sequencing reaction. Reagent from the kit (2 µl) was directly added to the
PCR product (5 µl) in 500 µl Eppendorf tubes (Eppendorf, Stevenage, UK). The
mixture was brought to and kept at 37ºC for 15 min to activate the enzymes and
perform the clean-up. Then the enzymes were denatured at 80ºC for 15 minutes.
The DNA sequencing reaction was performed by the staff of Manchester
University sequencing services (Stopford Building) using BigDye® Terminator v3.1
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Cycle Sequencing Kit (Applied Biosystems) and an Applied Biosystems 3730 (48-
capillary) Genetic Analyzer. The identity of the organisms was obtained by
comparing the 16S rRNA gene sequence to RDP data base (http://rdp.cme.msu.edu/
index.jsp).
2.1.3 Agarose gel electrophoresis
The gels were prepared by dissolving low melting point agarose (Fisher)
between 0.8%-1.5% (W/V) depending on the size of the sample in 1xTAE buffer by
heating in a microwave. The dissolved agarose was cooled to 42oC in a water bath
and 0.01% SYBR safe DNA stain was added and gently mixed. The gel was poured
using an appropriate gel tray and sample comb. Hyper ladder 1Kb (Bioline) and
hyperladder V (Bioline) were used as molecular weight markers and the required
amount of 6x loading buffer (Bioline) was mixed with the desired amount of sample
(~8 µl) to obtain a 1x final concentration solution, which was loaded onto the gel.
Loaded samples were resolved by electrophoresis between 45-60 minutes at 60-90
volts depending on the size of the nucleic acid fragments being examined.
2.1.4 Assays used for the assessment of antimicrobial activity
2.1.4.1 Simultaneous antagonism
The simultaneous antagonism test (Sandiford and Upton, 2012; Tagg and
Bannister, 1979) was initially used to screen and identify potential producer species
and to determine the activity spectrum of the antimicrobials they elicited. The test
involved inoculating the whole surface of an agar plate with an indicator isolate.
Indicator bacteria were chosen for their high susceptibility towards antibacterial
agents to increase the sensitivity of screening. For initial detection, four indicators
were chosen; M. luteus and S. aureus 1195 were chosen to assess presence of anti-
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Gram positive activity and E. coli DH5α and 414 were used to detect anti-Gram-
negative activity of the tested organism.
Following the initial identification of potential inhibitor producers, various
other indicator strains were included to extend the spectrum of activity being
measured (see Section 2.1.4.2). The inoculua for Gram positive indicators were
adjusted to a suspension equivalent to 0.5 McFarland standard and diluted 1:10.
However, for Gram-negative indicators, the inoculua were diluted 1:100, as
indicated by The British Society for Antimicrobial Chemotherapy (BSAC), for
determination of susceptibility to conventional antibiotics (Andrews et al., 2001).
Afterwards, potential or known antimicrobial producers were stab inoculated onto
the agar using a straight wire.
The experiments were carried out on both CBA and CAB (Oxoid) as
production of certain antimicrobials may depend on availability of specific nutrients
(Patzer et al., 2003; Zhu et al., 2014). The plates were incubated overnight and
observed for inhibition zones (Figure 2.1). Promising producers were taken further
through optimisation and antimicrobials of interest was purified and characterised.
Figure 2.1 Simultaneous antagonism test, the antimicrobial activity of potential inhibitor producers against two indicator E. coli species (414 at the top and DH5α at bottom of the plate) was observed as clear zones of inhibition.
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2.1.4.2 Deferred antagonism
This experiment was performed to assess the preliminary spectrum of activity
demonstrated by producer strains and followed the guidelines set out by Tagg and
Bannister (1979). Prior to the experiment a heavy inoculum of the producer strain
was streaked diagonally across a CBA plate and incubated aerobically at 37oC
overnight to allow diffusion of the antimicrobial into the agar. In parallel indicator
strains (E. coli 414, vancomycin resistant Enterococcus, B. subtilis, M. luteus, S.
aureus ACTC 1195, S. aureus 308, Meticillin resistant S. aureus, C. difficile,
Klebsiella pneumoniae 169, Klebsiella aerogenes, C. diphtheriae, extended
spectrum beta lactamase (ESBL) producing E. coli M2, ESBL E. coli 169, N.
gonorrhoea, Salmonella Typhimirium and P. aeruginosa 257 (all strains provided by
Manchester University Medical Microbiology laboratory, Manchester, England)
were grown in TSB broth (Oxoid) aerobically at 37oC overnight prior to experiment,
except C. difficile that was tested separately and was grown under anaerobic
conditions using Oxoid AnaeroGen packets in sealed culture jars (Oxoid) and N.
gonorrhoea grown on chocolate agar (Oxoid) and brain heart infusion broth (BHI) in
5% CO2.
The following day, the producers’ growth was removed by using a glass slide and
then the plate was chloroformed. In a fume hood, 5ml of chloroform was applied on
to a tissue placed in the middle of a wide glass petri dish, the agar plate was placed
upside down on the tissue and the agar was subjected to chloroform vapour for 30
minutes to eliminate producer bacteria and possible contaminants. After 30 minutes
the agar was aerated under the fume hood for at least 15 minutes. Following the
completion of the chloroforming process the indicator strains were streaked across
the plate perpendicular to the producer organism’s previous growth location using a
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sterile cotton swab (Figure 2.2) and the plates were incubated according to the
requirements of the indicator organisms on the plate. On the following day, unless
dictated otherwise by the recommended growth conditions of the indicator bacteria,
the results were processed according to extent of inhibition of the indicators by the
antimicrobial using the scoring system demonstrated below (Figure 2.2).
Figure 2.2 Deferred antagonism assay plate configuration and scoring system [From (Tagg and Bannister, 1979)].* Producer is removed and plate is chloroformed prior to inncoulation of the indicator strains.
2.1.4.3 Well diffusion assay
The well diffusion assay was primarily employed to record results of the
experiments that required semi-quantitative analysis of the antibacterial activity. The
test was performed by piercing up to eight equidistant holes onto a CBA or a CAB
plate with a flame sterilised cork-borer (7mm diameter) and the agar disk was
removed (Figure 2.3). The bases of the wells were sealed with low melting point
agarose before introducing the sample, to prevent leakage. Once sealed, 50µl of a
test material was loaded into each well and allowed to diffuse for 30 minutes or until
the well was dry.
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After wells had dried, the agar surface was exposed to chloroform vapour as
described above and spread inoculated with the appropriate indicator organism and
incubated appropriately. The results were recorded in arbitrary units per millilitre
(AU/ml) using the following formula (Saeed et al., 2004):
𝑨𝑨𝑨𝑨/𝒎𝒎𝒎𝒎 =(𝐑𝐑𝐑𝐑𝐑𝐑𝐑𝐑𝐑𝐑𝐑𝐑𝐑𝐑𝐑𝐑𝐑𝐑𝐑𝐑 𝐑𝐑𝐨𝐨 𝐡𝐡𝐑𝐑𝐡𝐡𝐡𝐡𝐑𝐑𝐡𝐡𝐡𝐡 𝐑𝐑𝐑𝐑𝐡𝐡𝐑𝐑𝐚𝐚𝐑𝐑 𝐝𝐝𝐑𝐑𝐑𝐑𝐝𝐝𝐡𝐡𝐑𝐑𝐑𝐑𝐝𝐝) 𝐱𝐱 𝟏𝟏𝟏𝟏𝟏𝟏𝟏𝟏
𝑽𝑽𝑽𝑽𝒎𝒎𝑽𝑽𝒎𝒎𝑽𝑽 𝑽𝑽𝒐𝒐 𝒕𝒕𝒕𝒕𝑽𝑽 𝒔𝒔𝒔𝒔𝒎𝒎𝒔𝒔𝒎𝒎𝑽𝑽
2.1.4.4 Spot assay
The spot assay was performed as a time efficient qualitative assessment of
antibacterial activity on liquid samples. This test was conducted by placing 20 µl
equidistant spots of test material onto a CBA, CAB or ISO sensitivity plates (Oxoid)
(Figure 2.4). The spots were allowed to dry and then chloroformed before the
indicator organism was spread inoculated onto the agar base. The inoculated plate
was incubated appropriately depending on the test organism and assessed for
inhibition zones.
Figure 2.3 Image above shows a well diffusion assay performed against indicator organism M. luteus.
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2.1.5 Optimisation of antimicrobial peptide production
Media used for production and purification of antimicrobial peptides was
optimised, taking into account effects of incubation time and temperature on the final
yield measured in AU/ml. Culture broths assessed included nutrient broth (NB)
(Oxoid), brain heart infusion broth (BHI) (Oxoid), TSB and supplemented forms of
TSB media. A 10ml sample of each broth was inoculated with an overnight starter
culture of B. pumilus J1 or K. pneumoniae A7 and incubated with shaking in a 37oC
incubator at 120rpm overnight. The following day, cultures were centrifuged in a
desktop microfuge at 15000xg, pellets were discarded and supernatants were
individually harvested and serially diluted in sterile distilled water. Dilutions were
assessed for antimicrobial activity using the agar well diffusion assay (see Section
2.1.4.3).
Following the results of this assay the broths that produced the best yield were
examined under different incubation temperatures (370C and 300C) over a 24 hour
period. Every 2 hours, a 1 ml aliquot was removed and tested as described above to
determine when the peptide production was initiated and identify the optimal
fermentation time and temperature for highest possible harvest yield.
Figure 2.4 Spot assay shown in the diagram illustrates antimicrobial activity of a sample against M. luteus.
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2.2 PROTEOMIC ANALYSIS OF THE IDENTIFIED ANTIMICROBIAL
PEPTIDES
2.2.1 Purification of antimicrobial peptides from the culture media
Purification of antimicrobial agents from the culture media was achieved in 3
steps; (1) capture, (2) intermediate purification and (3) polishing (Figure 2.5).
Purification cultures were initiated by inoculating a 1.5L TSB broth using an
overnight starter culture of the producer organism. The inoculated broth was then
incubated for 18 hours for B. pumilus J1 and 24 hours for K. pneumoniae A7 in a
shaking incubator at 120rpm. Following this, the culture medium was centrifuged at
3600xg at 40C for 20 minutes to remove the cells from the media. An overview of
the purification process is given here and details are provided in sections below. The
initial capture of the peptide from the harvested medium was facilitated using the
polymeric strata-XL liquid chromatography columns that retains samples based on
three properties; pi-pi bonding, hydrogen bonding as well as hydrophobic interaction
(Phenomenex, Macclesfield, UK) (see Section 2.2.1.1).
Figure 2.5 The three-step strategy used for peptide purification. A graphical representation of the purification strategy employed in this project [from (Amersham Biosciences)].
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The active fractions were pooled and rotary evaporated under pressure using
a Heidolph Laborota 4000 rotary evaporator (Heidolph, Essex, UK) to remove the
residual methanol from strata XL purification. The concentrate was then applied to
Sep-Pak C-18 columns (Waters, Elstree, UK) for intermediated purification (see
Section 2.2.1.2). Sep-Pak C18 cartridges (Waters) are excellent for capturing small
peptides as C18 columns contain longer side chains compared the C4 and C8
columns. However, this also makes them highly hydrophobic. Elution buffer was
removed from the active fractions using an Eppendorf concentrator-plus
(Eppendorf). AMPs of interest were isolated from the resulting semi-pure peptide
mixture using RP-HPLC with a Proteo C-12 HPLC column (Phenomonex) attached
to an AKTA purifier HPLC system (Amersham/GE Healthcare, Little Chalfont, UK)
(see Section 2.2.1.3).
2.2.1.1 Capture using STRATA –XL column:
Elution buffers for use in the Strata XL column [column volume (CV) =
15ml] were prepared with increasing concentrations of acidified methanol [30% v/v,
50% v/v and 90% v/v in water + 0.01% trifluoroacetic acid (TFA)] to gradually strip
the bound peptides from the column. Fractions were collected using a 50ml syringe.
Before loading the sample, the column had to be conditioned to enhance the
binding of the peptides and to remove any impurities that may remain from the
manufacturing process. The conditioning involved washing the column with 60ml (4
CV) of 99.9% HPLC grade methanol (Fisher Scientific) to strip any protein residues
from the column. Then, 120 ml of milli-Q water at pH7 was passed through the
column to remove methanol and conclude the conditioning process.
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Prior to loading, the sample pH was adjusted to pH 5.8-6.2 to improve
binding of the peptide to the column. TFA (Sigma-Aldrich) was used to decrease the
sample pH and sodium hydroxide (NaOH) (Fisher scientific) to increase it. A 20µl
aliquot was used for spot assay on a CBA and/or CAB plate as a control to ensure
the sample was active. Once the pH was adjusted, the sample was loaded onto the
column and the resulting fractions were slowly collected and labelled as flow
through (FT). During the elution, at every 200 ml a 20µl spot was placed onto a
labelled agar plate to determine the saturation point of the column. The column
saturation was reached at around 500ml for all samples tested. After the desired
amount of sample was passed through, the column was washed with 60ml of ultra-
pure water at pH7 to remove any unbound sample. The resulting fraction was
labelled as wash through (WT).
Subsequently, 45mls of 50% methanol was introduced to the column to strip
molecules that were weakly bound. Finally, peptides attached to the column were
gradually eluted in four 15 ml fractions of 90% methanol (pH2). All fractions
collected for B. pumilus J1 were tested against M. luteus and for K. pneumoniae A7
against E. coli DH5α using the spot assay to confirm presence of the AMP of
interest.
2.2.1.2 Intermediate sample cleaning with Sep-Pak C18 columns
Two different buffers were required for the experiment, Buffer A [MiliQ
water + 0.01% TFA and 2 % Acetonitrile (ACN) (TFA, Sigma-Aldrich; Acetonitrile,
Fisher scientific)] and Buffer B [ACN + 0.01% TFA]. Prior to sample loading, Sep-
Pak C18 cartridges were also conditioned; the column was stripped of protein
residues by passing 1 CV (Sep-Pak C18 light cartridge CV= 1ml; Sep-Pak C18 plus
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cartridge CV= 5ml) of Buffer B through and equilibrating with 2 CV of Buffer A.
The 2% ACN in buffer A prevents highly hydrophobic side chains of Sep-Pak C18
cartridge from ‘matting down’ in an attempt to cluster away from the water by
slightly reducing the surface tension.
After column conditioning, 1ml of Strata-XL purified active sample adjusted
to ~pH 2 using TFA to achieve optimal sample binding was loaded on to the Sep-
Pak C18 columns. The sample was then eluted and the FT fraction was collected and
tested for activity in every 250µl to determine the column’s saturation point. One
column volume of sample was observed to be the limit for each agent examined.
Then the cartridge was washed with 2 CV of Buffer A to remove unbound
sample and the WT fraction was collected. Bound peptides were eluted using 1 CV
of increasing concentrations of ACN, in 10% increments (10-90% v/v in 0.01%
TFA) and the resulting fractions were collected in 1.5 ml eppendorf tubes
(Eppendorf).
2.2.1.3 Reverse Phase High Pressure Liquid Chromatography
HPLC allows very high-resolution separation of the peptides present within a
sample. For this project, reverse phased-HPLC (RP-HPLC) was performed on the
Sep-Pak C18 purified and concentrated active fractions, as the polishing step. The
Jupiter C18 250x10mm HPLC columns (CV= 10ml; Phenomonex) were used
together with an AKTA purifier system (GE Healthcare).
The buffers were the same as those used for Sep-Pak C18 cartridges,
however buffers A and B were degassed by vacuum filtration for the HPLC
procedure. This prevents pressure build up as liquids are non-compressible when
mixed with gases. Pressure increases during HPLC may cause compression of the
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column contents causing erratic baseline readings or rupture the column. Buffer A
and B were connected to the AKTA purifier via the designated tubing. The following
procedures were carried out using the software provided by the manufacturer.
The column was conditioned by running 2 CV of Buffer B, followed by 5 CV
of Buffer A. For the initial elution, a program with a complete continuous gradient
from 0% Buffer A and 100% Buffer B leading towards 100% Buffer A in 8 CV at a
flow rate of 1ml/min, was entered to the AKTA purifier management software.
During the elution, 0.5ml fractions were collected in individual eppendorf tubes and
labelled. Each fraction represented a 0.53% increase in ACN concentration. The
proteins eluted during the purification process were visualised and recorded using
215 nm and 280 nm UV absorbance. Once the initial elution was completed, all
fractions collected were tested manually using the spot assay. Once the elution
fractions for each AMP were determined, to cater for a more time efficient run the
gradient was adjusted to 30% ACN+0.01% TFA and rising to 90% ACN+0.01%
TFA in 4 CV at a flow rate of 1ml/min. Where possible, the procedure was repeated
multiple times until the highest possible purity was obtained.
2.2.2 SDS-PAGE analysis and gel diffusion agar overlay assay
Sodium dodecyl sulphate polyacrylamide gel electrophoresis (SDS-PAGE)
electrophoresis using 4-12% Nu PAGE Bis-Tris Bolt gels (Life Technologies) was
employed to visualise the gross content of Sep-Pak C18 and HPLC purified active
fractions and the products of in vitro expression studies (see Section 2.5.10 below).
Prior to electrophoresis, the samples were treated with lithium dodecyl sulphate
(LDS) sample buffer (Life Technologies) and reduction agent (Life Technologies) as
per manufacturer’s instructions to denature and reduce the sample. See Blu 2 (Life
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Technologies) pre-stained protein ladder was used to estimate the protein masses.
The gels were run on Bolt mini gel (Life Technologies) electrophoresis tanks with
MES (2-ethanesulfonic acid) buffer (Life Technologies). The protein bands were
stained and visualised using the Coomassie brilliant blue R-250 (Fisher Scientific).
Antimicrobial activities of the visualised bands were tested with a gel
diffusion agar overlay assay. Assay detected bands were excised after multiple wash
cycles with milli-Q water for at least 4 hours. Excised gel strips were then gently
placed on the surface of a CAB plate. Simultaneously, 10ml CAB aliquots were
melted and cooled to 450C and, while still aqueous, the agar was inoculated with a
0.5 McFarland standard suspension of M. luteus cells equivalent to a 1:10 dilution.
The inoculated agar was poured over the gel strips and allowed to solidify and the
plate incubated at 37oC overnight.
2.2.3 MALDI-ToF mass determination and ESI-MS scan of the RP-HPLC
Purified Active Fractions
The molecular masses of the peptide particles recovered within the active
fractions obtained from the RP-HPLC purification process were analysed for
dereplication purposes using the matrix assisted laser desorption/ionisation time of
flight (MALDI-TOF) technique. Prior to analysis, 1ml of matrix was prepared by
mixing 10 mg α-cyano-4-hydroxycinnamic acid (Sigma-Aldrich) with 0.5ml ACN
(50%) and 0.5ml ethanol (50%) (Fisher Scientific). Then, 1μl of the sample was
placed on a 96 well ground steel MALDI plate (Bruker, Coventry, UK.) followed by
1μl of the matrix and the mixture was left to air dry at room temperature. Once
dried, the samples were processed using the Bruker Daltonics Ultraflex II TOF/TOF
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(Bruker), as per manufacturer’s instructions. On average, five shots were fired at
randomly picked locations on the sample well and added to the generated spectra.
The spectra were analysed using the predefined peak selection method designed by
the Biomolecular Analysis Facility, Michael Smith building, The University of
Manchester, using the on-board software. Samples with prominent peaks were also
analysed using electro spray ionisation mass spectrometry (ESI-MS) using an
Orbitrap mass spectrometer (Thermo Scientific) for further confirmation. This was
performed as a service by staff at the Biomolecular Analysis Facility.
The mass assigned to the active peptide was checked against the online
bacteriocin database, Bactibase (Hammami et al., 2010) and the published literature
to identify any other previously identified bacteriocins that contain an identical mass.
2.2.4 De novo peptide sequencing (MS/MS)
De novo peptide sequencing is a powerful tool that uses tandem mass
spectrophotometry to fragment and analyse peptides to determine the sequence of
constituent amino acids. The analysis of the subsequent data yields strings of amino
acid sequences that are called peptide tags. These tags can be compared with draft
genome sequence data (see Section 2.2.5) to search for a unique match. This
approach was used to search for the genes encoding AMPs in the B. pumilus J1 and
K. pneumoniae A7 strains.
The procedure is initiated with digestion of the query peptide with modified
sequencing grade trypsin (Promega, Southampton, UK). This procedure could be
performed both in gel and in solution; both versions were performed in this project.
This was done to enable the comparison of the results for greater confidence and also
by running the SDS gel overlay assay samples simultaneously in the same gel (see
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Section 2.2.2), it was possible to link the physically observable antimicrobial protein
band to the peptide tags obtained to antimicrobial activity.
2.2.4.1 In solution digestion
Dried peptide fraction was suspended in 100μl of 6 M Urea in Tris buffer
(pH 7.8). To ensure specific cleavage by trypsin, the peptide was reduced by adding
5μl of 10 mM dithiothreitol (DTT) (Sigma-Aldrich) to the suspension, vortexed and
allowed to react for 30- 60 minutes at room temperature. Reduced peptide was then
alkylated using 20μl of 50 mM 2-chloroacetamide (Sigma-Aldrich), the reaction
mixture was incubated in a dark place at room temperature for 30-60 minutes. This
was followed with re-treatment with 20μl DTT for a further 30-60 minutes. Prior to
addition of trypsin, the Urea was diluted with 775μl MilliQ water. Sequencing grade
modified trypsin (Promega) was added to the solution at a 1:50 ratio and mixed.
Digestion was carried out overnight in a 37oC incubator.
The digested peptide was recovered using Stage Tips (Stop and Go
Extraction Tips) containing stanched monolithic C18 adsorbent (Waters). The Stage
tips were treated as miniature Sep-Pak C18 columns (see Section 2.2.1.2), suspended
through the lid of an Eppendorf tube. The buffers or the samples were loaded into the
tip and the apparatus was centrifuged on a desktop microfuge briefly to facilitate the
flow of the sample and the buffers. Sample was eluted from the column using 80%
ACN + 0.01%TFA in a single step. Eluted peptide was dried down using the speed
vac and re-suspended in solution A (see Section 2.2.1). MS/MS fragmentation of the
digested peptide was performed using the Orbitrap LC-MS (Thermo-scientific) by
the Biomolecular Analysis Facility, Michael Smith building, The University of
Manchester.
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2.2.4.2 In gel digestion
In gel digestion was performed on excised gel fragments obtained following
the SDS PAGE gel analysis (see Section 2.2.2) of the Sep-Pak C18 purified active
fractions. The mass of the excised bands chosen for this experiment corresponded to
the HPLC purified peptide and to the correct molecular weight interval determined
by the See Blu 2 protein weight marker. Replicates of the gel fragments were tested
for antimicrobial activity using the agar gel overlay assay (see Section2.2.2). The
excised fragments were cut into smaller cubes prior to digestion and washed by
suspension in 100% ACN for 5 minutes and then in MilliQ water to remove the
coomassie blue stain. This step was repeated 3 times. After this point, the digestion
procedure was applied as explained in Section 2.2.4.1. However, prior to Stage Tip
recovery, the digested peptide was removed from the gel pieces by vigorous
vortexing and the supernatant was applied to the Stage Tips for peptide recovery.
The recovered peptide was subjected to the same analysis as the in solution digest.
2.2.4.3 Bioinformatics analysis of the generated data
De novo peptide sequencing was conducted both manually and with analysis
software packages PEAKS studio7 (Zhang et al., 2012) (Bioinformatics Solutions,
Waterloo, Canada) and MASCOT (Perkins et al., 1999) (Matrix Science, London,
UK) on the raw data resultant from the MS/MS fragmentation. Generated peptide
tags were compared with the draft genome of the producer organism (see Section
2.2.5) using the BLAST facility within the CLC main workbench 7 (Qiagen). Where
required, multiple alignments of the identified amino acid sequences were performed
in Jalview (Waterhouse et al., 2009) using the ClustalW alignment facility (Larkin et
al., 2007). Neighbour joining trees were also created in Jalview. Secondary structure
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prediction was carried out using Jnet secondary structure prediction service (Cole et
al., 2008; Cuff and Barton, 2000).
2.2.5 Genome sequencing and annotation of the draft genome of producer
strains
DNA for genome sequence determination was extracted from cells contained
in 0.5ml of an overnight culture of B. pumilus J1 or K. pneumoniae A7, which had
previously been inoculated with a single colony from CBA plates and incubated at
37oC. DNA extractions were carried out in house using the Blood and Tissue kit
(Qiagen, Manchester, UK) as per manufacturer’s instructions. Integrity of the DNA
was observed by loading an 8μl sample onto a 1% agarose gel in TAE, followed by
electrophoresis, and the concentration was measured using a Qbit device (Life
Technologies), as per the manufacturer’s instructions. DNA was stored at -20oC until
required for analysis.
The draft genome sequence was determined using the services of the Centre
for Genome Research, University of Liverpool. A shotgun library of DNA fragments
was sequenced using an Illumina HiSeq device with 150bp paired end reads. The
raw data was presented trimmed of Illumina adapter sequence using Cutadapt.
Sickle, a window based quality trimming software which uses a sliding window to
monitor the read quality and length, was set to trim the sequences when the read
quality score within the window was below 20 and remove the sequence if total read
length was below 10bp (Del Fabbro et al., 2013; Joshi and Fass, 2011). Raw data
were assembled using the CLC Main Workbench 7 de novo assembly tool. The
assembled sequences were annotated using the PROKKA prokaryotic genome
annotation software tool (Seemann, 2014) and by using xBASE genome annotation
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pipeline (Chaudhuri et al., 2008), for B. pumilus J1 using B. pumilus SAFR-32
(Accession number NC_009848) as a reference and using Klebsiella pneumoniae
XH209 (Accession number NZ_CP009461) as the reference for K. pneumoniae A7.
The annotated genome was visualised using Artemis software (Rutherford et al.,
2000) and the assembled draft sequences were compared with reference genomes
using the BLAST ring image generator (BRIG) (Alikhan et al., 2011) software to
generate a graphical representation of the differences between B. pumilus J1 and K.
pneumoniae A7 with their respective reference organisms. Where required, genome
annotations were corrected manually by direct pairwise gene alignments via Jalview
(Waterhouse et al., 2009) and/or database search with the position-specific iterated
BLAST (PSI-BLAST) (Altschul et al., 1997) algorithm using predicted peptide
sequences generated by six frame translation of the genome.
2.3 CHARACTERIZATION OF THE PURIFIED ANTIMICROBIAL PEPTIDES
Three promising antimicrobial peptides were isolated following the application
of above methodology. From B. pumilus J1, characteristics of peptides NI03 and
NI04 are described in Chapter 3 and from K. pneumoniae A7, the peptide NI05 is
addressed in Chapter 4. Due to reasons discussed in respective chapters concerning
the individual peptides, not all characterisation steps were performed on each
peptide, and the Table below (Table 2.1) summarises the tests performed for each
peptide.
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Table 2.1 A summary of the characterisation assays performed on each agent identified during proteomic analysis
Test Peptide NI03 Peptide NI04 Peptide NI05
Deferred Antagonism* Physicochemical analysis Minimum inhibitory concentration determination
Haemolysis assay
Eukaryotic Cell toxicity studies
UV absorbing material leakage assay
*Deferred antagonism assay was performed to characterise the spectrum of activity of the producer strains being tested. The activity observed represents the combined activity of any antimicrobial agents that might be expressed by the organism of interest.
2.3.1 Physicochemical analysis of purified antimicrobial peptides (heat and
enzyme stability tests)
Preliminary investigation of the physicochemical properties of the detected
peptides was carried out using heat and enzyme stability assays. For the heat stability
assay, a known concentration of peptide NI04 was incubated at 800C in a heating
block for up to 4 hours. For enzyme stability assay aliquots of known concentrations
of NI04 were treated with the hydrolytic enzymes α-amylase, α-chymotrypsin,
lipase, protease and trypsin (Sigma-Aldrich) at 1 mg/ml, while proteinase K (Sigma-
Aldrich) was used at 10mg/ml. NI04 was incubated with each of these enzymes for 4
hours.
The effect of both heat and enzyme stability assays were measured by
making doubling dilutions of the treated peptide aliquots and comparing the
consequent reduction in antimicrobial activity to that of the untreated peptide
sample, using the well inhibition assay described above.
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2.3.2 Determination of minimum inhibitory concentration
The minimum inhibitory concentration (MIC) of AMPs were determined
using broth micro-dilution of the Sep-Pak C18 cleaned peptide fractions following
CLSI guidelines (CLSI, 2012). The total protein content of pooled dried and
suspended fractions was calculated using the bicinchoninic acid assay (BCA assay)
(Smith et al., 1985) with the Pierce BCA Protein Assay Kit (Thermo Scientific) as
per manufacturer’s instructions. Two fold dilutions of the peptide were prepared in
cation adjusted Mueller-Hinton broth (CA-MHB) (Oxoid) and dispensed into the
wells in 0.1ml fractions. A bacterial suspension was prepared using colonies directly
from agar surface in CA-MHB and adjusted to 0.5 McFarland standard (1 × 108
colony forming units (CFU)/mL). Within 15 minutes of preparation the suspension
was diluted 1:20 in CA-MHB and the AMP containing broths were inoculated with
10ul (0.01ml) of this inoculum to yield approximately 5 × 104 CFU/well as
suggested by the CLSI. The prepared test plate was incubated in a 37°C incubator for
20 hours in an aerobic atmosphere.
2.3.3 Haemolysis assay
Haemolysis assays were performed to assess the toxicity of the
antimicrobial peptide of interest towards mice red blood cells (RBC) (kindly donated
by Dr Peter Warn, University of Manchester). The test was conducted using mice
RBCs, which were harvested by centrifugation at 400xg, washed with phosphate
buffered saline (PBS) and suspended at a concentration of 5% in PBS containing the
AMP of interest at doubling dilutions from 1:10 to 1:160. Haemolytic activity was
measured using a spectrophotometer at 490 nm with 1% Triton-X 100 as control.
The haemolytic activity was calculated using the following formula (Vaucher et al.,
2010):
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%Haemolysis =𝐴𝐴𝐴𝐴𝐴𝐴 𝑜𝑜𝑜𝑜 𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝 𝑝𝑝𝑡𝑡𝑡𝑡𝑝𝑝𝑝𝑝𝑝𝑝 𝐴𝐴𝑏𝑏𝑜𝑜𝑜𝑜𝑝𝑝 × 𝐴𝐴𝐴𝐴𝐴𝐴 𝑜𝑜𝑜𝑜 𝑢𝑢𝑢𝑢𝑝𝑝𝑡𝑡𝑝𝑝𝑡𝑡𝑝𝑝𝑝𝑝𝑝𝑝 𝐴𝐴𝑏𝑏𝑜𝑜𝑜𝑜𝑝𝑝
𝐴𝐴𝐴𝐴𝐴𝐴 𝑜𝑜𝑜𝑜 𝑇𝑇𝑡𝑡𝑝𝑝𝑝𝑝𝑜𝑜𝑢𝑢𝑇𝑇100 𝑝𝑝𝑡𝑡𝑝𝑝𝑡𝑡𝑝𝑝𝑝𝑝𝑝𝑝 𝐴𝐴𝑏𝑏𝑜𝑜𝑜𝑜𝑝𝑝 × 𝐴𝐴𝐴𝐴𝐴𝐴 𝑜𝑜𝑜𝑜 𝑢𝑢𝑢𝑢𝑝𝑝𝑡𝑡𝑝𝑝𝑡𝑡𝑝𝑝𝑝𝑝𝑝𝑝 𝐴𝐴𝑏𝑏𝑜𝑜𝑜𝑜𝑝𝑝× 100
2.3.4 Eukaryotic cell toxicity studies
Toxicity of peptide NI04 against eukaryotic cells was measured using the
trypan blue exclusion assay on keratinocyte cell lines and neutral red uptake assays
on Vero cells. The experiments were conducted using semi-purified stock peptide
fractions at up to 18x MIC concentrations for M. luteus, diluted in cell culture
growth media. SDS (20mg/ml) (Fisher Scientific) was used as a positive control and
neat maintenance medium as the negative control. Cells were incubated in 5% CO2
at 37oC overnight.
2.3.4.1 Trypan blue exclusion assay with keratinocytes
For the trypan blue exclusion assay (Louis and Siegel, 2011), old culture
media was removed from 100% confluent keratinocyte tissue culture monolayers
(kindly donated by Dr Catherine O’Neil, University of Manchester) and replaced
with keratinocyte growth medium 2 (PromoCell, Heidelberg, Germany) containing
doubling dilutions of stock peptide from a starting concentration of 18X MIC (M.
luteus). Cells were incubated in 5% CO2 at 37oC overnight. The following day, the
keratinocytes were observed under the microscope for possible cytopathic effects
and following microscopic evaluation, medium was removed and cells were
harvested using trypsinisation. Harvested cells were then diluted 1:1 with 0.4%
trypan blue (Fisher Scientific) and cell viability was assessed visually under an
inverted microscope using a haemocytometer. Both viable cells (non-stained) and
dead (stained) ones were counted.
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2.3.4.2 Neutral red uptake assay
The neutral red assay is based on the ability of live cells to incorporate the
neutral red dye in their lysosomes. The variation of this quantitative viability test,
performed on Monkey Vero cell lines in this project, has been based on the method
by Repetto and colleagues (Repetto et al., 2008). A 40 mg/ml neutral red solution
(Fisher Scientific) was prepared by dissolving the powdered dye in distilled water.
The cells were grown in 96 well tissue culture plates (Corning, Amsterdam,
Netherlands) with antibiotic free DMEM growth media (Dulbecco's Modified Eagle
Medium, DMEM+10% foetal bovine serum) (Life Technologies) to half confluence
overnight at 370C in 5% CO2. Half confluent cell monolayers were then treated with
growth medium (without phenol red) containing doubling dilutions of peptide NI04
up to 18x MIC, with negative (DMEM growth media) and positive [2% Triton X-
100 (Fisher Scientific)] controls set up in triplicate. Treated cells and the neutral red
solution were incubated separately overnight in a 370C, 5%CO2 incubator. Once
incubation had concluded, cells were inspected under a microscope for
morphological abnormalities.
Once the observations were noted, the treatment media was removed from
the wells and replaced with 100μl neutral red solution and incubated for 2 hours at
5% CO2 at 37oC. Following the exposure, neutral red solution was removed and cells
were washed with 150μl of PBS. Then 150μl of neutral red de-stain solution was
added into the wells, which were shaken for 10 minutes until a homogenous solution
was obtained. The OD of the resulting solution was measured in a plate reader at
540nm.
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2.3.5 UV Absorbing material leakage assay
This assay was performed to gather preliminary data concerning the mode of
activity of peptide NI04. Overnight broths of M. luteus and S. aureus 1195 cells were
prepared in TSB broth and diluted to OD 1.0 (at 600nm) using a spectrophotometer.
Adjusted cell suspensions were transferred into an Eppendorf tube and the bacterial
cells were harvested by centrifugation at 3600xg for 10 minutes. Supernatant was
discarded and the cell pellet was washed twice with PBS and then suspended in PBS
solution containing 1xMIC concentration of Sep-Pak purified antimicrobial peptide
(S. aureus 20μg/ml and M. luteus 10μg/ml) and incubated for four hours at 370C
aerobically. Every hour, a 150μl sample was taken and centrifuged at 15000xg for 10
minutes in a desktop centrifuge to remove bacterial cells. Then, 100μl of the cell free
supernatant was transferred into a 96 well UVstar (Grenier) UV transparent plate and
UV absorbance was measured at 260nm using a FLUOstar Omega (BMG-Labtech,
Ortenberg, Germany) UV/VIS spectrophotometer.
2.4 IN SILICO GENOME MINING AND IDENTIFICATION OF PUTATIVE
BACTERIOCIN LEADS Draft bacterial genomes of the producers B. pumilus J1 and K. pneumoniae A7
(as described in Chapters 3 and 4) were subjected to bioinformatic analyses, together
with genomes of 35 anaerobic bacteria from Clostridium and Proprionibacterium
genera (Clostridium acetobutylicum ATCC 824, Clostridium acidurici 9a,
Clostridium acetobutylicum 824, Clostridium beijerinckii NCIMB 8052, Clostridium
botulinum A ATCC 19397, Clostridium botulinum BKT015925, Clostridium
botulinum A2 strain Kyoto, Clostridium botulinum A3 strain Loch Maree,
Clostridium botulinum B strain Eklund 17B, Clostridium botulinum B1 strain Okra,
Clostridium botulinum Ba4 strain 657, Clostridium botulinum E3 strain Alaska E43,
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Clostridium botulinum H04402 065, Clostridium cellulolyticum H10, Clostridium
cellulovorans 743B, Clostridium_kluyveri DSM 555, Clostridium lentocellum DSM
5427, Clostridium ljungdahlii DSM 13528, Clostridium novyi NT, Clostridium
perfringens SM101, Clostridium perfringens strain 13, Clostridium phytofermentans
ISDg, Clostridium saccharolyticum WM1, Clostridium saccharoperbutylacetonicum
N1 4HMT, Clostridium species BNL1100, Clostridium species SY8519, Clostridium
stercorarium DSM 8532, Clostridium sporogenes strain DSM 795, Clostridium
tetani E88, Clostridium tetani 12124569, Clostridium thermocellum ATCC 27405,
Propionibacterium acidipropionici ATCC 4875, Propionibacterium acnes SK137,
Propionibacterium acnes TypeIA2 Pacn17, Propionibacterium propionicum
F0230a),using the bacteriocin research tool BAGEL3
(http://bagel.molgenrug.nl/index.php/bagel3) (van Heel et al., 2013) (Figure 2.6).
Annotated putative bacteriocin candidates/clusters returned by BAGEL software
were then short-listed. Those putative bacteriocins that had significant homology to
known bacteriocins with an E value less than 0.001, as identified by BAGEL or
through use of PSI BLAST and the Bactibase (Hammami et al., 2010)internal
BLAST homology tool, were included in this short-list.
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Figure 2.6 Overview of the proposed workflow described below for in silico mining of genomic sequence data for novel AMPs.
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2.5 CLONING AND EXPRESSION METHODS
2.5.1 Insert construction and primer design for cell free protein expression
To validate the concept that functional antimicrobial peptides can be obtained
from mined putative bacteriocin sequences using commercially available cell free
expression systems, assuming they conferred antimicrobial activity, attempts were
made to clone and express the pumicin NI04 structural gene, pmnA using a cell free
expression system. What follows is an overview of the approaches used and a
detailed description of each stage in the process.
Once the target gene (insert) was selected, using sticky ends generated by
restriction enzymes, it was inserted into the chosen expression vector, pET28a,
where expression is tightly controlled by the T7 promoter region. Prior to insertion,
the target gene was PCR amplified using manually designed PCR primers flanked by
restriction enzyme sites, Nco1 and BamH1 to exclude the polyhistidine-tagged (His-
tagged) region of the pET28a expression vector. This was done to avoid any possible
interference to antimicrobial activity that may occur due to inclusion of a His-tag.
Restriction sites were followed by 4 base long random overhangs to improve
restriction enzyme binding (Green and Sambrook, 2001) (Table 2.2). The target
binding portion of the primers were designed to contain between the first 18-22 base
pairs of the 3’ and 5’ ends of the target gene, depending on suitability of the
nucleotide content.
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Table 2.2 A list of primers employed during the study. Blue nucleotides indicate the restriction enzyme cut site, while red nucleotides highlight the start and stop codons.
However, a modification had to be made for the pmnA gene to utilise the
NcoI cut site as it contains the ATG start codon and dictates the first nucleotide of
the inserted sequence as Guanine. To overcome this problem pmnA gene primers
were designed with an alternative, BsaI, cut site. BsaI cuts downstream of its binding
site and creates an NcoI compatible overhang (Figure 2.7).
The pET28a plasmids were extracted and purified from transformed E. coli
XL-1 blue cells (Agilent Technologies, Stockport, UK) from the laboratory stock
using a QIAprep spin miniprep kit (Qiagen) as per manufacturer’s instructions.
Bacterial DNA extraction was performed using the Qiagen blood and tissue kit
(Qiagen). Purified DNA was quantified using a nanodrop spectrophotometer
(Thermoscientific) and was visualised by agarose gel electrophoresis (see Section
2.1.3). In addition, 0.8% agarose gels were used to check integrity of extracted
genomic DNA and plasmids. All samples were stored at -200C.
Target Forward primer (5’end of target) Reverse primer (3’end of target)
pmnA gene 5’-GCCG(GGTCTC)TCATG TCAGGAATTATTCGCGTAACC
-3’
5’-GCC(GGATCC)TTA GCCGCGGATTTGGCTAGC-
3’
T7 sequencing
primers TAATACGACTCACTATAGGG GCTAGTTATTGCTCAGCGG
Figure 2.7 Utilisation of NcoI cut site using the BsaI restriction site.
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The target gene sequence (insert) was amplified using Phusion® high-fidelity
PCR master mix with HF buffer (Thermoscientific) for the cloning procedure and
Biomix Red (Bioline) for routine diagnostic PCR checks. Reaction mixture and
conditions are recorded in Table 2.3 below. The PCR reactions were carried out in a
Bio-Rad thermal cyclers. PCR products were purified by Qiagen PCR clean up kit
(Qiagen) and eluted from columns in 50µl for storage at -20oC.
Table 2.3 The content of the PCR reaction mixture used for amplification of the inserts for use in construction of plasmid vector.
Component 50µl Reaction
2x Phusion® high-fidelity PCR master mix with HF buffer
25µl
Forward Primer 0.5µM
Reverse Primer 0.5µM
Template DNA 50-250ng
DMSO (100%) 1.5µl
dH2O Make up to 50µl final volume
Amplified inserts were analysed by agarose gel electrophoresis (see Section
2.1.3; 1.5 % gels) and a Nanodrop Spectrophotometer (Thermoscientific) was
employed to estimate product yield and purity.
Double restriction digests were then set up for both the plasmid and the
insert, using restriction enzymes BsaI-HF (New England Biosciences, Herts, UK
[NEB]) and BamHI-HF (NEB). The reactions (50µl) were prepared according to the
manufacturer’s instructions and conducted for at least 1 hour. The products were
purified using gel electrophoresis (see Section 2.1.3) followed by gel extraction of
the desired bands using the QIAquick gel extraction kit (Qiagen), as per
manufacturers instructions.
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In the following step, the digested and gel-purified pET28a plasmid and
inserts were ligated using the T4 DNA ligase (NEB). The reaction was performed
with 3:1 vector to insert ratio and carried out according to manufacturer’s
instructions in a 50µl reaction volume at room temperature. The following formula
was used to calculate the appropriate amount of insert to be used in relation to the
employed vector:
The ligase was heat inactivated at 65°C for 10 minutes and the ligated
product was used in transformation of competent cells. The completed plasmid
construct was transformed into the chemically competent E. coli XL1 Blue cells
were used as host for the transformation. Three transformation reactions were set up;
a) Positive control with pUC18 control plasmid (Agilent Technologies), b) Negative
control with cut but un-ligated vector and without addition of insert and c) Ligated
experimental construct.
The transformation procedure was also carried out according to the
manufacturer’s instructions and the transformation mixture was plated onto a Luria
agar base containing 50µg/ml kanamycin (LB/Kan) and incubated overnight at 370C
aerobically. Colonies that developed on the antibiotic selection plates were tested for
presence of the insert with colony PCR. Reactions were carried out using the insert
specific primers. Colonies were picked off the agar surface using a pipette tip and
suspended in 50μl of dH2O (DNA and RNA free) (Fisher). DNA was then extracted
by heating the samples to 95°C for 5 minutes in a heating block to lyse the cell and
deactivate enzymes. Following heat treatment, samples were spun briefly in a
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microfuge to collect any condensation. Collected samples were used as template for
the PCR reaction (see Section 2.5.3).
The size of the insert was confirmed using pmnA gene cloning primers
against pmnA amplified from the native B. pumilus J1 genome and the insert
orientation was confirmed using pmnA forward primer and T7 reverse primer.
Results were visualised by gel electrophoresis (see Section 2.1.3).
The DNA sequence of the recombinant pmnA gene from selected constructs
was confirmed by sequencing from T7/pET sequencing primer sites (Table 2.2)
following PCR using Biomix Red mastermix (Bioline). The amplicons were
sequenced by the staff of Manchester University Sequencing Services (Stopford
building) (see Section 2.1.2).
2.5.2 In vitro cell-free expression
In vitro expression was carried out using the PURExpress® In Vitro Protein
Synthesis Kit (NEB). The experiment was carried out using the manufacturer
provided method to express from the pET28a-pmnA plasmid. The assay contains all
necessary reagents and substrates required for the synthesis of the desired peptide
encoded within a T7 promoter regulated operon and omits the use of bacterial cells,
which eliminates most of the complications associated with recombinant expression.
Manufacturer provided DHFR plasmid was used as a control; this expresses
dihydrofolate reductase enzyme, which can be easily monitored using SDS-PAGE
gel electrophoresis to indicate successful performance of the protocol. The assay
produces analytical amounts of peptide that were easily purified using HisPur nickel-
nitrilotriacetic acid (Ni-NTA) agarose beads (Thermoscientific) as all components
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involved in the synthesis process are supplied with an attached histidine tag (His-
Tag).
2.5.3 Proteomic analysis of peptide products generated following expression
studies
Peptide expression was tested using the well diffusion assay and SDS-PAGE
gel electrophoresis (see Sections 2.1.4.3 and 2.2.2). Prior to analysis, to reduce the
total peptide content and increase the resolution, the cell free expression products
were subjected to 100kDa centrifugal filtration using Amicon ultra 0.5 ml centrifugal
filters (Merck Millipore, Hertfordshire, UK). Analysis of the filtered cell free
expression products were conducted using both un-purified products and Ni-NTA
agarose bead purified (as per manufacturer’s instructions) peptide.
Part of the peptide mixture obtained was used for well diffusion assays (see
Section 2.1.4.3; 50μl/well) to check for antimicrobial activity. The remaining lysate
was used for SDS-PAGE analysis (see Section 2.2.2) to investigate the recombinant
peptide yield and size.
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3 CHAPTER 3
PUMICIN NI04, A NOVEL ANTIMICROBIAL PEPTIDE FROM
BACILLUS PUMILUS, IS HOMOLOGOUS TO THE ESXA VIRULENCE
DETERMINANT
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3.1 INTRODUCTION
It only took two years for the first meticillin resistant strain of Staphylococcus
aureus to emerge after introduction of penicillinase stable β-lactams in 1951 (Barber,
1961; Chambers and Deleo, 2009). Although improved infection control and
hygiene interventions have led to a significant decrease in infections caused by
meticillin resistant S. aureus (MRSA), it is still one of the most prominent antibiotic
resistant pathogens encountered in hospital and community infections and is a
member of the ESKAPE group (Boucher et al., 2009). In fact, antibiotic resistance
has become one of the most pressing challenges that modern medicine faces, with
resistance traits accumulating and spreading rapidly among bacterial pathogens
(Barriere, 2015; Cosgrove, 2006; Jean and Hsueh, 2011; Livermore, 2007; Martínez
and Baquero, 2014). This challenge must be met urgently since introduction of
antibiotics has not only decreased human morbidity and mortality resulting from
bacterial infections, but as prophylactics their use allows many modern medical
procedures to be performed; the reality of a post antibiotic era cannot be easily
imagined (Rice, 2008). Rapid resistance acquisition or development is fuelled in part
by misuse of antibiotics and especially high selective pressure is applied in hospitals.
This is further complicated by rapid dissemination of antibiotic resistant pathogens
through advancing global transport (Hede, 2014; Hsueh, 2012; W. Li et al., 2014;
Zhang et al., 2006). In tandem, the antibiotic discovery pipeline is poorly populated,
while the time taken by bacteria to develop resistance towards new antibiotics
decreases (W. Li et al., 2014; Livermore, 2011).
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Although the outlook is considerably less bleak for infections caused by the
Gram positive bacteria with the introduction of five new in classes of antibiotics
since 2000, therapy of infectious diseases still relies heavily on use of derivatives of
existing antibiotics, and has done so since the 1970s (Butler et al., 2013). However,
the number of derivatives that can be developed from existing classes is finite and
further development grows more expensive (Coates et al., 2011). Worryingly,
resistance is already emerging towards some recently introduced drugs, including
daptomycin and linezolid (Cavalcante et al., 2014; Fessler et al., 2014; McElvania
TeKippe et al., 2014; Montero et al., 2008).
A supply of antibiotics from new classes, with novel modes of action is
required more consistently. Bacteriocins, bacterially derived antimicrobial peptides,
are important candidates, not only for their potential medical applications but the
wealth of knowledge that we could learn via studying these antimicrobials developed
through the sieve of evolution (Walsh and Fischbach, 2010).
Bacteriocins are generally active against species closely related to the
producing bacteria (the producers) and have unique structures, varied modes of
action mediating rapid killing and the fact that they are ribosomally encoded allows
the native peptides to be rationally modified to improve efficacy and stability or
reduce toxicity (Abriouel et al., 2011; Cotter et al., 2005; Godballe et al., 2011).
Bacteriocins are also observed to be affected less by cross resistance with other
antibiotics, although limited evidence is emerging to support the suggested
occurrence of cross resistance, even if it is indirectly through promotion of bacterial
competition (Koch et al., 2014).
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Introduction
Another factor compounding the deficiency in antibiotic discovery is the lack
of success with the genetic approaches that were adopted to replace time consuming
and laborious natural product screening (Livermore, 2011; Newman, 2008).
However, recent improvements in screening and discovery technologies, especially
the advancement of rapid dereplication methods that are able to work with small
sample volumes, such as high resolution mass spectrometry (eg. Orbitrap) has
reignited interest in both bacteriocin research and in wider aspects of natural product
discovery. Most recently, innovative techniques have been developed that allow
culture and screening of previously uncultivable bacteria and introduction of the
iChip device led to the discovery of the non-ribosomal peptide teixobactin, a potent
first in class antibiotic (Ling et al., 2015). Such innovations will help promote the
revolution in natural product discovery.
In the present study, by taking advantage of these new technologies, we have
characterised a potent inhibitor of Gram positive bacteria, peptide NI04, which is one
of two bacteriocins recovered from an environmental isolate, Bacillus pumilus strain
J1. This unusual and effective antimicrobial peptide has shown particular similarities
to the Esx-A protein, which is described as a significant virulence factor in other
bacteria including Mycobacterium tuberculosis and some species of S. aureus (Burts
et al., 2005; De Jonge et al., 2007; Sundaramoorthy et al., 2008). However, B.
pumilus is not known for its pathogenicity towards humans and, in our toxicity tests,
no adverse effects were observed. Our addition to the understanding of EsxA-like
peptides indicates that this family of peptides may have evolved in a divergent
manner to exploit membrane-damaging activity for different means. The second
active agent that was isolated from B. pumillus strain J1 was peptide NI03, which is
active against both Gram positive and negative species. However, due to suboptimal
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Introduction
production and stability concerns, detailed study of this peptide was not conducted,
though some promising data relating to NI03 were recovered following in silico
studies conducted during analysis of the producer’s genome (See Chapter 5).
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3.2 RESULTS
3.2.1 Two antimicrobial agents are produced by B. pumilus J1
From the environmental samples collected for analysis in this study, sixty-
eight individual colonies were isolated and of these, ten showed strong antimicrobial
activity. Among these, strain J1, isolated from a settle plate, showed striking
antimicrobial activity towards Gram positive bacteria and also, to a lesser degree,
towards Gram-negative species and thus strain J1 was chosen for detailed
examination. The 16S rRNA gene sequence data revealed that this bacteria was a
member of B. pumilus species and it was designated as B. pumilus strain J1.
Following identification of this strain as a producer of antimicrobial activity, and
preliminary investigation of the inhibitory spectrum of the strain, efforts were made
to purify the active agent(s) from liquid culture.
Following Strata-XL and then Sep-Pak C18 fractionation of supernatants
from TSB broth cultures, two antimicrobial agents with different activity spectra
were isolated from the producer organism B. pumilus J1. The first inhibitor, which
eluted in 40% ACN+0.01TFA fractions (Figure 3.1) was named peptide NI03 and
was active against Gram positive and negative indicator strains.
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Figure 3.1 Spot assay performed with Sep-Pak C18 purified fractions against S. aureus. Peptide NI03 eluted at 40% acetonitrile concentration and peptide NI04 at 60 and 70% acetonitrile fractions.
Peptide NI04 was active against only Gram positive bacteria, except the
Gram negative bacterium N. gonorrhoea (Table 3.1). This peptide eluted in 60 and
70% ACN+0.01TFA fractions (Figure 3.1). However, peptide NI03 was not
subsequently present in all purification batches and did not respond to optimisation
studies. Thus, efforts were concentrated on the identification of peptide NI04 and
NI03 was not progressed.
Table 3.1 Antimicrobial activity of peptides NI03 and NI04 against indicator species. Results were obtained using the spot on lawn assay with Sep-Pak C18 fractions. Activity was recorded as (+) if a visible inhibition zone was present and (-) if no zone of inhibition was present.
Gram negative indicator strains NI03 NI04
Gram positive indicator strains NI03 NI04
E. coli 414 + - B. subtilis - - E. coli DH5a + - C. difficile + + ESBL E. coli M2 + - C. diphtheriae + + ESBL E. coli 169 + - M. luteus + + K. aerogenes - - S. aureus 308 + + K. pneumoniae 169 - - S. aureus 1195 + + N. gonorrhoea - + MRSA + + P. aeruginosa 257 - - VR Enterococci + + Salmonella Typhimirium
+ -
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3.2.2 Bacteriocin production can be optimised by manipulation of growth
conditions
A variation in the level of recovery of peptide NI04 was observed early on in
the project. To address these variations, an optimisation study was performed using
various media and additives and two incubation temperatures, over a 24 hour period.
Peptide concentration was measured in AU/ml with the well diffusion assay using
the indictor organism M. luteus. Observations revealed that TSB and NB produced
the highest yields of peptide NI04, while the use of TSB supplemented with YE (1%
w/w), lactose (1% w/w) and maltose (1% w/w) had a negative effect on the yield
(Table 3.2). Sucrose supplementation (1% w/w) of TSB YE, while having no
negative effects did not enhance the production compared with basic TSB. BHI
medium was also revealed to be suboptimal for peptide NI04 production (Table 3.2).
Table 3.2 Effect of various media and additives on the production and availability of peptide NI04, following overnight incubation at 37oC.
Broth Additives Peptide NI04
(AU/ml) TSB* - 640 TSB YE* (1%) 320 TSB YE (1%), Lactose (1%) 320 TSB YE (1%), Sucrose (1%) 640 TSB YE (1%), Maltose (1%) 320 TSB Sucrose (1%) 640 BHI* - 320 NB* - 640
* TSB-(Tryptic Soy Broth), YE-(Yeast extract), BHI-(Brain heart infusion broth), NB-(Nutrient broth)
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Following on from these results, a time-controlled experiment was performed
assessing the effect of incubation temperature and time on the quantity of peptide
available. Overall, TSB proved to be the most consistent medium, reaching the
highest observed yield of 2560AU/ml at both 30oC and 37oC (Figure 3.2). However,
peptide NI04 availability was also influenced by incubation time, with the amount of
recoverable peptide declining significantly after 18 hours when B. pumilus J1 was
incubated at 370C (Figure 3.2). Optimal production was seen between 12 and 18
hours under all test conditions.
Figure 3.2 Availability of peptide NI04 in tryptic soy broth and nutrient broth culture media under different incubation temperatures over a 24 hour period. Error bars represent the standard deviation in peptide NI04 activity between replicates.
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3.2.3 De novo peptide sequence determination of peptide NI04 using mass
spectrometry analysis and genome interrogation facilitates identification
of the pumicin NI04 locus
Active Sep-Pak C18 fractions that eluted at 60% and 70% ACN+0.01%TFA
were pooled and applied to RP-HPLC column. Active fractions obtained from the
RP-HPLC eluted at ~ 45% acetonitrile concentration (Figure 3.3) and were subjected
to ESI-MS analysis. Mass spectrometric evaluation of the RP-HPLC purified peptide
NI04 suggested a mass of 10722.993Da (Figure 3.4). The detected mass was queried
against online bacteriocin data-bases and published literature for de-replication
purposes. The query search resulted in no matches, indicating that peptide NI04 had
a novel mass.
Figure 3.3 RP-HPLC chromatogram of peptide NI04. Each peak on the graph represents the molecules or molecule groups eluted during the RP-HPLC procedure at different acetonitrile concentrations (green line indicates the acetonitrile concentration). The readings are taken at 215nm UV intensity. Active fractions are labelled.
Active fraction H13
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Figure 3.4 ESI-MS scan of active HPLC fraction showing the detected mass of peptide NI04 as 10722.993. Other peaks represent background noise and a possible impurity with a mass of 10771.341 (not present in other spectrographs).
MS analysis was followed by de novo peptide sequencing using MS/MS
fragmentation. The unique sequence tags generated from the raw data using the
MASCOT software and manual investigations are listed in Table 3.3. These peptide
tags can be used to interrogate the bacterial genome to facilitate the discovery of the
gene(s) responsible for the production of the AMP. Thus, the Draft genome of B.
pumilus J1 was generated using the illumina MiSeq platform.
Table 3.3 The unique sequence tags for peptide NI04 obtained from the de novo peptide sequencing efforts. Common modifications that can occur were also accounted.
Sequence Length Modifications QYGVESQEVLNQVDR 15 Unmodified MSDLLTDVSNQLDQTANTLESTDQDIASQIR 31 Unmodified GMWEGASSEAFADQYEQLKPSFIK 24 Oxidation (M) MISDLK 6 Unmodified MSGIIR 6 Acetyl (Protein
N-term)
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The draft genome sequence was assembled from a total of 2,998,202 raw
sequence reads having an average length of 62 bp. Assembly resulted in 1490
contigs comprising a draft genome of 4,421,862 bp [N50 = 9581 (50% of the genome
was contained in contigs of greater than 9,581 bp)]. From the draft data, it was
estimated that average genome coverage was 193 fold. The genome was annotated
using the PROKKA genome annotation software. The B. pumilus SAFR-32 stain
was used as the reference during the assembly and annotation. The differences
between the genomes of the B. pumilus J1 and the reference strain are graphically
represented in the diagram generated using the BRIG software (Figure 3.5).
Figure 3.5 A graphical representation of the differences between the genomes of the B. pumilus SAFR-32 strain (inner ring) and B. pumilus J1 (outer, purple ring). Comparisons were made with BRIG software.
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Sequence tags generated from the MS/MS fragmentation data were mapped
back to the draft bacterial genome, both manually using the BLAST facility in CLC
Main Workbench and using the built in search features of PEAKS studio 7 and
MASCOT software. This allowed identification of the peptide NI04 amino acid
sequence as
-MSGIIRVTPEELRATAKQYGVESQEVLNQVDRLNRMISDLKGMWEGASSE
AFADQYEQLKPSFIKMSDLLTDVSNQLDQTANTLESTDQDIASQIRG-
Sequence tags generated that helped to identify the sequence are highlighted
in different colours on the peptide sequence with a predicted mass of 10854.207.
This differed from the observed mass by 131.214Da, which implies cleavage of the
N-methionine from the amino acid sequence (Frottin et al., 2006).
The encoding gene sequence in the B. pumilus J1 genome was annotated as
esxA using the PROKKA annotation tool. The annotation was based on an observed
30.7% identity with a virulence factor from S. aureus, EsxA, which is secreted
through a specialised T7SS pathway called the ESX (Ess/Yuk) pathway. Another
EsxA virulence factor that shared homology with peptide NI04 was Mycobacterium
tuberculosis EsxA, which is secreted by the ESX-1 pathway. However, further
analysis using the PSI-BLAST algorithm revealed that peptide NI04 shared most
identity with another EsxA homolog observed in B. subtilis, namely YukE (91.7%)
(See, Figure 3.6 and Figure 3.7). The function of YukE is unknown, although its
secretion mechanism has been studied (Baptista et al., 2013; Huppert et al., 2014;
Sysoeva et al., 2014).
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EsxA peptides are classified in the WXG protein superfamily (Pfam:
PF06013), which encompasses proteins of approximately 100 amino acids with
various functions including virulence, cell wall maintenance and sporulation (Akpe
San Roman et al., 2010; Ates et al., 2015; Fyans et al., 2013; Garces et al., 2010;
Huppert et al., 2014; Sundaramoorthy et al., 2008). We propose that this novel
antimicrobial peptide be named pumicin NI04 and that it is encoded by pmnA.
Further analysis of the gene locus around pmnA also revealed the presence of other
T7SS pathway components such as a predicted ATPase (PROKKA 03052) sharing
70.8% identity with YukBA (UniProt ref: C0SPA7) that is essential for substrate
secretion via the B. subtilis ESX (Yuk) pathway (Huppert et al. 2014). In addition,
homologs of other Yuk loci transport and accessory proteins were also uncovered in
the pumicin NI04 biosynthesis cluster; YukD (UniProt ref: P71071) (73% identity
with YukD), YukC (UniProt ref: P71070) (100% identity), PROKKA 03051 (45.9%
identity with YueB (UniProt ref: O32101), PROKKA 03050 (35% identity with
YueC (UniProt ref: O32100) (Figure 3.8) (Huppert et al., 2014).
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Figure 3.6 Protein sequence alignment of pumicin NI04 and the 10 most homologous peptides identified using the PSI-BLAST algorithm (Altschul et al., 1997). Also included are the known EsxA peptide sequences (EsxA [M. tuberculosis] and virulence factor EsxA [S.aureus]) that are experimentally confirmed to play a role in the virulence of their respective host organisms (boxed in Green) and the highly similar EsxA homolog YukE peptide of unknown function from B. subtilis (boxed in orange). Secondary structure prediction, performed using jnetpred, is illustrated at the bottom of the alignments and confirms the helix turn helix structure of WXG-100 peptides is preserved in pumicin NI04 together with the W-X-G motif.
WXG motif
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Figure 3.7 Neighbour joining tree calculated using the % identity of aligned WXG family peptides. Branches are labelled with the % difference in the identity of the amino acid sequences to each other.
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Figure 3.8 Organisation of the biosynthetic cluster predicted to be involved in the production and secretion of pumicin NI04 encoded in the producer B. pumillus J1 genome and organisation of other operons encoding homologous EsxA peptides, M. tuberculosis ESX1 locus (Burts et al., 2005), B. subtilis Yuk locus (Huppert et al., 2014) and S. aureus Ess locus (Kneuper et al., 2014). Esx substrates are highlighted in red and proteins that are known to be involved in regulation and secretions of ESX substrates are coloured blue, proteins that are predicted to be involved in transport or regulation of these factors are highlighted in green, proteins that have unknown or unrelated function are coloured grey (Burts et al., 2005; Kneuper et al., 2014; McLaughlin et al., 2007; Ramsdell et al., 2015). PROKKA 03052 (70.8% identity with YukBA [UniProt ref: C0SPA7] ), YukD (73% identity with YukD [UniProt ref: P71071]), YukC (100% identity [UniProt ref: P71070]), PROKKA 03051 (45.86% identity with YueB [UniProt ref: O32101]), PROKKA 03050 (33.5% identity with YueC [UniProt ref: O32100]).
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Further confirmation was achieved by demonstrating that the identified
peptide had antimicrobial activity and the expected mass using SDS-PAGE gel
electrophoresis with an agar overlay (Figure 3.9). A clear zone of inhibition was
present around the band of interest. Analysis of the purified peptide was performed
in triplicate and revealed a band visible at the expected interval between the 6kDa
and 14kDa protein standards used.
Figure 3.9 The SDS-PAGE gel analysis of the Sep-Pak C18 purified samples, against SeeBlu 2 protein marker. Gel overlay assay performed following analysis demonstrated the peptide band at the expected mass interval has inhibitory activity. The band indicated with the orange arrow was used for MS/MS fragmentation and de novo amino acid sequencing.
3.2.4 Pumicin NI04 is stable to heat treatments and protease degradation
confirms a proteinaceous nature
The proteinaceous structure of pumicin NI04 was confirmed using enzyme
stability assays (Table 3.4). As expected, proteolytic enzymes such as protease,
pepsin and proteinase K abolished the antimicrobial activity, while interestingly
trypsin had reduced but not neutralised the activity and α-chymotrypsin had no
effect. Lipid active lipase and carbohydrate active amylase enzymes had no visible
effect either. Pumicin NI04 was also observed to be highly heat stable; exposure to
800C for up to 4 hours had no noticeable effect on the antimicrobial activity (data not
shown).
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Results Table 3.4 Effect of a wide array of hydrolytic enzymes on the antimicrobial activity of pumicin NI04.
Enzyme Retained antimicrobial activity
Protease 0%
Pepsin 0%
Proteinase K 0%
Trypsin 25%
α-Chymotrypsin 100%
Lipase 100%
α-Amylase 100%
3.2.5 Pumicin NI04 has potent activity against resistant Gram positive
pathogens
Pumicin NI04 was shown to have activity against a broad spectrum of Gram
positive bacteria (Table 3.5). Two sets of results are reported in the table below, in
one column the AU/ml value is reported where a higher value represents a higher
level of inhibitory activity and in the second column the actual MIC in µg/ml is
recorded. Low MIC/high activity values were recorded for multiple indicator
organisms including Streptococcus pneumoniae, S. aureus and antimicrobial
resistant species such as MRSA, but VRE species, especially strain 20, were
observed to be surprisingly more susceptible to pumicin NI04, compared with other
Gram positive bacteria tested.
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Results Table 3.5 Minimum inhibitory concentration (MIC) of pumicin NI04 against a wide selection of Gram positive bacteria. MIC was calculated in AU/ml and µg/ml in a selection of indicators using highly purified peptide.
Indicator organism* MIC AU/ml MIC µg/ml
M. luteus 2560 10
S. aureus 308 320 20
S. aureus 1195 320 20 MSSA 27 107 ND MRSA 6 160 40 MRSA 13 213 ND MRSA 37 133 ND MRSA 226 107 ND VRE 16 213 ND VRE 17 160 ND VRE 18 320 20 VRE 19 160 ND VRE 20 2560 ND VRE 21 160 ND Strep. pneumoniae 1 427 20 Strep. pneumoniae 2 640 ND Strep pneumoniae 4 160 ND Strep. pneumoniae 6 640 ND Strep. pneumoniae 7 107 ND Strep. pneumoniae 11 320 ND
3.2.6 UV absorbing material leakage assay
The UV absorbing material leakage experiments were performed to gain
insight into the mode of action of pumicin NI04. The results revealed that soon after
the addition of pumicin NI04 to M. luteus cells, there was a steady release of UV
absorbing materials from the M. luteus cells; at the end of three hours there was a
0.047OD change in the measurable UV absorbing materials (Figure 3.10).
*-Meticillin sensitive S. aureus (MSSA), Methicillin resistant S. aureus (MRSA) Vancomycin resistant Enterococcus faecium (VRE), ND: Not determined due to low quantity of purified peptide
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Observations obtained from S. aureus cells were slightly different; instead of
a swift and constant release of UV absorbing particles, a delayed but rapid release
was observed. Also, the overall recorded difference in the absorbance was higher for
S. aureus, with a reading of 0.099 OD obtained at 4 hours (Figure 3.10).
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Figure 3.10 Release of UV absorbing materials from A) M. luteus and B) S. aureus cells over time following treatment with pumicin NI04 at 1xMIC of the test organism compared with pumicin NI04 solution (1xMIC) in test buffer without any microbial inoculum to account for the absorbance inferred by pumicin NI04.
A
B
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3.2.7 Pumicin NI04 has low levels of in vitro toxicity
In haemolysis assays, no haemolytic activity was recorded, irrespective of the
concentration of pumicin NI04 tested (Table 3.6). Dilutions were made from peptide
concentrations of 18x the MIC for M. luteus.
Table 3.6 Percentage of haemolysis that occurred following the addition of pumicin NI04 to mouse erythrocytes. Triton-X100 detergent was used to achieve absolute haemolysis and was used as the positive control.
Pumicin NI04 concentration (AU/ml) 256
128
64
32
16 Triton-X 100 (2%)
% Haemolysis 1.63 0.90 1.08 1.08 0.90 100
% STDEV 1.73 0.36 0.55 0.85 0.54 -
Promising results were also obtained in toxicity studies performed against
human keratinocytes and monkey Vero cells using peptide concentrations of up to
18x the MIC for M. luteus. In the neutral red assay, no difference was perceived in
the ability of the Vero cells to incorporate neutral red into their lysosomes, regardless
of the concentration of pumicin present in the culture medium (Figure 3.11).
Assessment of keratinocyte cell viability data using the trypan blue exclusion
assay also indicated that the presence of pumicin NI04 up to 18x M. luteus MIC had
no toxic effect (Figure 3.12). In addition, during the microscopic examination of
both cell lines following treatment, no visible abnormalities were detected between
the treated and untreated cultures. Total cell destruction occurred in the wells
containing either SDS or Triton X-100.
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Figure 3.11 Comparison of neutral red uptake of Vero cells against negative (growth media) and positive (2% triton X-100) controls, following incubation with differing concentrations of pumicin NI04 of up to 18x the MIC recorded against M. luteus.
Figure 3.12 Cell survival data collected using the trypan blue exclusion assay, following a 24 hour incubation of keratinocyte cells with pumicin NI04 supplemented medium against negative (growth media) and positive (20mg/ml SDS) controls.
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3.3 DISCUSSION
Using a natural product screening effort, B. pumilus strain J1 was isolated from
settle plates placed around the Manchester Royal Infirmary Clinical Sciences
Building. The strain produced two antimicrobial peptides with distinct spectra of
activity, which eluted at two different solvent concentrations from Sep-Pak C18
columns. Peptide NI03 demonstrated antagonism towards both Gram positive and, to
a lesser degree, towards Gram-negative species. However, this peptide was only
expressed in adequate quantities in a small number of fermentation batches. It is well
documented that expression of some bacteriocins is highly dependent on culture
conditions, however, optimisation studies performed failed to improve the
consistency and the yield and it is likely a more tailored approach specific to peptide
NI03 is required, such as removal of key media ingredients or addition of
components from the natural niche of B. pumilus in an effort to ‘elicit’ production of
the peptide (Lincke et al., 2010; Rigali et al., 2008; Zhu et al., 2014). Peptide NI03
is discussed in more detail later in this thesis (see Chapter 5, Sections 5.3.3 and 5.5).
In contrast, peptide NI04 was active against a wide variety of Gram positive
bacteria and, although its expression was also erratic, it was recoverable in good
yields following optimisation of growth media and incubation time. Thus, until
more information can be gathered regarding peptide NI03 that may guide
optimisation, it is not an efficient use of resources to pursue this inhibitor. A decision
was made to focus efforts on recovery and characterisation of peptide NI04. As a
result, the novel antimicrobial peptide pumicin NI04 has been identified. The peptide
was observed to be proteinaceous in structure, heat stable and have a mass of
10722.993Da. De-novo sequencing of the active peptide using MS/MS helped to
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trace the sequence back to a gene identified as an esxA homolog in the draft genome
of the producer B. pumilus strain J1. The esxA homolog identified in the genome
encoded a peptide with a predicted mass of ~10854.207, which differed from the
observed mass by 131.214Da. This mass difference suggests cleavage of the N-
terminal methionine from the peptide sequence by the bacteria that causes 131Da
mass shift (Demirev et al., 2001; Frottin et al., 2006). One of the peptide tags
generated by the MASCOT driven de novo peptide sequencing, also suggested that
pumicin NI04 contains an N-terminal acylation which may occur prior to or after the
cleavage of N-terminal methionine but the expected 42Da mass shift wasn’t
observed on the MS analysis of the whole peptide (Arnesen, 2011; Helbig et al.,
2010; Parker et al., 2010). Nevertheless, it is important to note that the EsxA
peptides of mycobacteria are N-α-terminally acetylated (Mba Medie et al., 2014;
Okkels et al., 2004).
EsxA peptides belong to the WXG 100 superfamily of peptides. These are
peptides released into the environment by Gram positive bacteria through the ESX
(ESAT-6/Ess/Yuk) secretion system, an ortholog of the T7SS dedicated to secretion
of ESX substrates, such as EsxA, EsxB, EsxC and YukE (Burts et al., 2005; Huppert
et al., 2014; Kneuper et al., 2014). The WXG 100 superfamily is constituted of
proteins with approximately 100 amino acids and are identified by their helix-turn-
helix structure and conserved W-X-G motif (Pallen, 2002). These properties are
found in pumicin NI04 (Figure 3.6). EsxA peptides are generally associated with
virulence in organisms such as Mycobacterium tuberculosis, S. aureus and B. subtilis
(Burts et al., 2005; De Jonge et al., 2007; Sundaramoorthy et al., 2008). However,
there are exceptions, as demonstrated by the plant pathogen Streptomyces scabies.
Fyans and colleagues witnessed that abrogating EsxA production in this organism
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didn’t affect the pathogenicity, but led to deficits in the development of the bacterial
cell (Fyans et al., 2013). Furthermore, presence of ESX genes in non-virulent
bacterial strains, such as Streptomyces coelicolor provides proof that these peptides
are not obligatory virulence factors (Akpe San Roman et al., 2010; Converse and
Cox, 2005; Huppert et al., 2014). In addition, B. pumilus, although a pathogen of
fish, like many other bacillus species rarely causes infections in humans (Bentur et
al., 2007; Tena et al., 2007).
Possible functional divergences amongst EsxA homologs can be explained by
the fact that, although strong similarities in predicted structures are present
between EsxA peptides, there are also considerable variations. In an iterative study,
Poulsen and co-workers managed to group a selection of WXG 100 proteins into
three categories, namely CFP-10 (10kDa culture filtrate protein) often referred to as
EsxB, ESAT-6 (6kDa early secreted antigenic target) and sagEsxA like. The latter
two categories are often referred to as EsxA (Poulsen et al., 2014).
A homolog of the identified antimicrobial peptide pumicin NI04 is present
within the previously described peptides; BPUM2860 (UniProt ref: A8FGZ8) groups
together with the sagEsxA like category (Poulsen et al., 2014). These WXG 100
proteins are encoded by mono-cystronic genes and diverge from the CFP-10 and
ESAT-6 like proteins that are encoded by bi-cistronic operons (Poulsen et al., 2014).
CFP-10 and ESAT-6 are mutually dependent and form heterodimers, while sagEsxA
like peptides form homo-dimers explaining the absence of EsxB (CFP-10) from the
pumicn NI04 operon (Poulsen et al., 2014). The homo-dimeric nature of these
peptides is also supported by the findings of Sysoeva and colleagues (2014), where
they suggested recognition of the YukE homo-dimer facilitates the secretion of this
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peptide. It is also suggested that these dimers are secreted as a single unit (Baptista et
al., 2013; Sysoeva et al., 2014). However, in the current study there was no evidence
from the MS studies or SDS-PAGE analysis that would imply presence of dimers of
pumicin NI04 in the purified fractions, although they were not actively sought. In
addition, within each category including the sagEsxA group there are considerable
variations in the amino acid sequences between members, as noted by Poulsen et al.
(2014). This can also be observed in Figure 3.6. Without experimental evidence, it is
not possible to comment on the specific effect of the observed sequence variations
amongst the EsxA peptide family, regarding their general function or between B.
subtilus YukE and pumicin NI04. However, the deduction that can be made from the
aforementioned results of this study, combined with the functional diversity
observed between EsxA like peptides in the literature and the presence of these
proteins in non-virulent bacteria (Akpe San Roman et al., 2010; Ates et al., 2015;
Fyans et al., 2013; Garces et al., 2010; Huppert et al., 2014; Sundaramoorthy et al.,
2008), indicate that these proteins may have evolved divergently to fulfil different
functions within the particular bacterial niche being inhabited. There has been no
experimental evidence published showing antimicrobial activity of EsxA like
peptides or other peptides belonging to the WXG 100 superfamily, making pumicin
NI04 unique in this respect. It would be logical to assess the antimicrobial activity of
pumicin NI04 homologs from other Bacillus species including YukE. Also, in the
absence of reports where such assays have been performed on members of
Mycobacterium or Staphylococcus, it would also be interesting to investigate the
wider phenotype of EsxA proteins from these genera.
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It is important to note that membrane lysis, which may form the basis of
antibacterial activity in antimicrobial peptides (Destoumieux-Garzón et al., 2003;
Diep et al., 2007; Hobbs et al., 2008; Ooi et al., 2009) (See Sections 1.5.2 and 1.6.2),
has been demonstrated as a mode of virulence employed by M. tuberculosis and S.
aureus and is facilitated through homologs of EsxA peptides, specifically ESAT-6
(EsxA) and CFP-10 (EsxB) (De Jonge et al., 2007; Gao et al., 2004; Guinn et al.,
2004; Hsu et al., 2003; Mba Medie et al., 2014). In contrast, while pumicin NI04
was toxic to bacterial cells, during the in vitro toxicity studies pumicin NI04 was
observed to be non-toxic towards human keratinocyte and monkey Vero cell lines at
up to 18x the MIC values. It is also worth investigating the particular effects that
pumicin NI04 may have on macrophages, considering the lytic mode of action
suggested for EsxA peptides is often described to be directed towards macrophages
(Gao et al., 2004; Mba Medie et al., 2014; Simeone et al., 2012).
The UV absorbing material leakage assay performed in this study is used for
assessing pore formation on the bacterial cell membrane and the results obtained
established the leakage of UV absorbing materials from S. aureus and M. luteus cells
in response to pumicin NI04 (Devi et al., 2010; Eumkeb et al., 2012; Su et al., 2012;
Yildirim et al., 2004; Zhou et al., 2008). These results are in line with the
observation made concerning the membrane lysis action of EsxA like peptides
during virulence. Although the above data suggest that pumicin NI04 is interfering
with the integrity of the bacterial cell membrane, it is not sufficient by itself to draw
final conclusions regarding the mode of action of pumicin NI04 and further studies
must be conducted.
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Discussion
In addition, pumicin NI04 shares properties associated with bacteriocins in
many respects, such as activity against closely related bacterial species (Table 3.5),
heat stability and self-immunity (Cascales et al., 2007; Cotter et al., 2005). It also
proved to be an efficient antimicrobial against antibiotic resistant species such as
MRSA and VRE. However, given the combination of structural and
physicochemical characteristics exhibited by pumicin NI04, it is not possible to
classify it using the commonly accepted bacteriocin classification schema, as NI04
has a mass greater than 10kDa, yet it is heat stable.
In the most recently suggested bacteriocin classification scheme, Heng and
Tagg (2006) combined the widely accepted classification schema from Cotter and
colleagues (2005) and Klaenhammer (1993) into one, dividing the known peptides
into four categories: lantibiotics; unmodified peptides; large proteins; and cyclic
peptides. Granted there is a group allocated to large bacteriocins by the scheme,
but it is defined by heat liability (Heng & Tagg 2006; Klaenhammer 1993) and
includes heat labile large bacteriocins such as Dysgalacticin and Linocin M18.
Therefore, pumicin NI04 cannot be classified to this group (Swe et al., 2009;
Valdés-Stauber and Scherer, 1994), though pumicin NI04 is not the only large heat-
stable antimicrobial peptide; Propionicin SM1 (Miescher et al., 2000), isolated from
Propionibacterium jensenii DF1 is also heat stable, yet it should be noted that this
protein is much larger than NI04 having a mass of 19,942Da.
The only antimicrobial peptide previously identified from members of B.
pumilus is the heat stable bacteriocin, pumilicin 4 from the WAPB4 strain (Aunpad
and Na-Bangchang, 2007). However, due to a lack of structural data, it is not
possible to make a direct comparisons of these AMP’s, though pumicin NI04 is
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Discussion
significantly larger than pumilicin 4, which has a reported mass of 1994.62 Da
(Aunpad and Na-Bangchang, 2007).
Analysis of the gene loci around pmnA suggests that, like other WXG 100
peptides, pumicin NI04 is also secreted by an ESX secretion pathway; though it does
have some sequence variations, it is mainly orthologous to the Yuk pathway of B.
subtilis. In the absence of EsxB, it contains a homolog of the ubiquitin like yukD
gene similar to the B. subtilis Yuk pathway (Figure 3.8). YukD like protein family
members are conserved with T7SS and associated secretion systems and are shown
to have ubiquitin like structures but with a distinctly shorter C-terminal sequence
lacking the GG motif required for covalent bonding with other peptides (van den Ent
and Löwe, 2005). Ubiquitins are mainly eukaryote associated proteins that are
involved in a process called ubiquitination; once an ubiquitin bonds to a peptide it
signals proteolytic degradation or post translational modification of the bonded
peptide (Pickart, 2001; van den Ent and Löwe, 2005). However, as YukD lacks the
GG motif, the exact function of this protein is unknown (Hershko and Ciechanover,
1998; Pickart, 2001; van den Ent and Löwe, 2005). Nevertheless, instead of
virulence like EsxB, YukD was observed to be somehow involved in the export of
YukE from Bacillus subtilis (Burroughs et al., 2011; Burts et al., 2008; Huppert et
al., 2014; Iyer et al., 2006). Nevertheless, the YukD homolog EsaB in the S. aureus
Newman strain Ess pathway, where it’s found together with EsxA, B and C, was
observed to be unnecessary for the export of EsxA and B peptides but it acted post
translationally as a negative regulator of EsxC (Burts et al., 2008; Kneuper et al.,
2014). Thus, due to a lack of consensus function, Kneuper and colleagues (2014)
offered that this peptide is a regulatory peptide that may fulfil different roles
demanded by different encoding strains. Indeed, if it does interact with the pumicin
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Discussion
NI04 in a manner similar to that observed in eukaryotic ubiquitins or as a negative
regulator, it may fulfil the role of an immunity protein in the pumicin NI04 cluster
and thus it would be interesting to observe the effect of its deletion from the pumicin
NI04 cluster in B. pumilus strain J1.
The pumicin NI04 biosynthesis cluster also contains the predicted ATPase,
PROKKA 03052, that shares 70.8% identity with yukBA. ESX secretion pathways
employ members of the FtsK-SpoIIIE ATPase family that contain three ATPase
domains to facilitate secretion of their substrates (Ramsdell et al., 2015), except in
the Ess pathway where EssC mediated secretion requires only one ATPase domain
(Burts et al., 2005; Ramsdell et al., 2015). YukBA is a member of this family that is
translated as a single protein containing all three ATPase domains necessary for
substrate translocation (Huppert et al., 2014; Ramsdell et al., 2015; Sysoeva et al.,
2014). These proteins are also found in two component configurations such as in the
eccCa (1domain) and eccCb (2 domains) encoded ATPase from the Mycobacteria
ESX-1 pathway. The EccCb component in this pathway is essential for interaction
with the EsxB substrate (Champion et al., 2006; McLaughlin et al., 2007; Ramsdell
et al., 2015). Pumicin NI04 ATPase is predicted, by comparison with NCBI's
conserved domain database, to encode three ATPase domains, like YukBA (Figure
3.13) (Marchler-Bauer et al., 2014; Ramsdell et al., 2015). The structure of ESX
ATPases suggest that they are membrane bound and the yueB gene observed in Ess
and Yuk pathways, which is suggested to encode a phage receptor, may be the
membrane associated part of the complex (Huppert et al., 2014; Kneuper et al.,
2014; São-José et al., 2006, 2004). YukC and YueC are also shown to be involved in
secretion of YukE, yet their exact function in the Yuk pathway is still unknown
(Baptista et al., 2013; Burts et al., 2005; Huppert et al., 2014).
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Figure 3.13 A representation of the multidomain ATPase involved in ESX substrate secretion. It is believed that the first domain of YukBA generates the energy required for the translocation (dark blue) and the remaining two interact with the substrate (lighter shades of blue) such as pumicin NI04 [from (Ramsdell et al., 2015)] .
In conclusion, pumicin NI04 has proved to be a rather intriguing
antimicrobial peptide with potent activity and high thermal stability, with the closest
homologs having unknown functions or being previously reported to be virulence
factors. This is the first evidence of a peptide belonging to the WXG 100 protein
family displaying antimicrobial activity, suggesting that it is exported from the
producing cell by the ESX secretion system. Although many questions still remain,
one of the most important is whether this peptide is an exception or if there are other
EsxA or WXG 100 peptides that have evolved to have antimicrobial properties.
Pumicin NI04 may have proven to be a potent and non-toxic antimicrobial agent, but
esxA encoded peptides are reported to be highly immunogenic, which may suggest
the possibility of allergic complications if pumicin NI04 were to be applied in vivo,
though the immunogenic properties of pumicin were not investigated. Overall,
pumicin NI04 may not be the immediate answer we were looking for to overcome
antibiotic resistance (in Gram positive bacteria), but it has revealed an interesting
perspective on the evolution and properties of the WXG 100 protein family.
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4 CHAPTER 4
DISCOVERY AND ANALYSIS OF PEPTIDE NI05 PRODUCED BY
KLEBSIELLA PNEUMONIAE STRAIN A7
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4.1 INTRODUCTION
Gram-negative bacteria have become especially problematic amongst
multidrug resistant pathogens; the fact that four of the six ESKAPE pathogens are
Gram-negative bacteria is just one indication (Rice, 2008). The main reason is that
while there are a number of Gram positive active antibiotics making their way into
the clinic, development is proving more challenging for agents active against Gram-
negative bacteria (Boucher et al., 2009; Cornaglia, 2009; Page and Heim, 2009;
Pucci and Bush, 2013).
All the while, Gram-negative bacteria are getting rapidly more resistant and
treatment options are becoming limited. The high levels of resistance in Gram-
negative bacteria can be mainly linked to the emergence and rapid spread of
extended spectrum β-lactamase enzymes (ESBLs), carbapenemases and other
substrate specific β-lactamases (Cantón et al., 2012; Nordmann, 2014). This rapid
spread can be attributed to the fact that these genes are carried by plasmids that are
efficiently transferable (Cantón et al., 2012; Händel et al., 2015; Kumarasamy et al.,
2010; Rasheed et al., 2013). It is also disturbing that these resistance traits were
observed to spread and be retained amongst normal flora, creating a readily
accessible resistance reservoir to pathogenic species (Kumarasamy et al., 2010; J. W.
Lee et al., 2014; Walsh and Toleman, 2012).
Carbapenemase mediated resistance is one particularly concerning resistance
trait, as these enzymes are active against all β-lactam antibiotics including
carbapenems, against which ESBL enzymes are inactive (Nordmann, 2014). There
are different classes of carbapenemases that confer different levels of resistance to a
broad spectrum of β-lactams, the classification scheme used is called the Ambler
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classification (Nordmann, 2014). Particularly significant carbapenemases include the
penicillinase KPC and oxacillinase OXA-48, but the metallo enzyme New Delhi
Metallo-β-lactamase (NDM-1) that confers resistance to almost all known β-lactam
antibiotics including carbapenems is especially concerning (Figure 4.1) (Dortet et
al., 2014; Nordmann, 2014; Robilotti and Deresinski, 2014).
Figure 4.1 Activity spectrum of prominent carbapenemases found in enterobacteriaceae species [adapted from (Nordmann, 2014)].
This is important as imipenem was long considered the gold standard for
treating infections caused by Gram-negative bacteria (Bush, 2010; López-Rojas et
al., 2011). NDM-1 enzymes have been described in all of the four Gram-negative
ESKAPE species, in both individual cases and outbreaks affecting a growing number
of countries including the UK, France, Spain, Italy, India and the USA (Figure 4.2)
(Berrazeg et al., 2014; Bush, 2010; Dortet et al., 2014; López-Rojas et al., 2011;
Nordmann, 2014; Perry et al., 2011; Robilotti and Deresinski, 2014).
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Although NDM-1 does not hydrolyse the β-lactam aztreonam, it is commonly
observed that the organisms carrying NDM-1 encode multiple β-lactamases (in some
cases up to eight), where at least one is active against aztreonam (Barguigua et al.,
2013; Bush, 2010; Mitchell et al., 2015). What makes the situation even more
concerning is the co-existence of non-β-lactam antibiotic resistance mechanisms
within most β-lactam resistant Gram-negative pathogens. These are also found in
combinations that confer resistance to most or all non-β-lactam antibiotics (Liu et
al., 2006), giving rise to ‘pan-resistant’ pathogens.
Flouroquinolone and aminoglycoside resistance mechanisms are commonly
found in co-existence with β-lactamase resistance mechanisms (Doumith et al.,
2012; Matsumura et al., 2013). Flouroquinolone resistance is mostly mediated
through the mutation of target enzymes DNA gyrase and DNA topoisomearase IV as
well as various efflux mechanisms (Jacoby, 2005; Ribera et al., 2004).
Figure 4.2 Prevelance of NDM related cases per country (Dortet et al., 2014)
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Aminoglycoside resistance is achieved by production of modifying enzymes that
deactivate the aminoglycosides (Bou et al., 2000; Ribera et al., 2004; Van Looveren
and Goossens, 2004). The combination of these mechanisms leave tigecyline (Lam,
2007) and colistin, notable for its toxic nature, as the only treatment options in most
cases (Boucher et al., 2009; Rodríguez-Hernández et al., 2006). However, colistin
resistance is also spreading in strains of A. baumannii and clinical failure of colistin
therapy has been reported by a number of studies, further underlining the urgent need
for novel antibiotic discovery and development (Rodríguez-Hernández et al., 2006;
Telang et al., 2011).
While bacteriocins of Gram positive bacteria present a significant potential
resource to be developed as antibiotics against related species or genera, they lack
the same efficacy against Gram-negative bacteria. Instead, colicins and microcins
present the same opportunity for Gram-negative bacteria (Cotter et al., 2013).
Although potency of microcins as chemotherapeutics is far less studied compared
with their Gram positive cousins, many microcins have been shown to have
significant activity against clinically important pathogens. This includes both narrow
spectrum agents such as MccPDI active against Shigella species and E. coli
(including enterohemorrhagic E. coli O157:H7 and O26 strains) (Eberhart et al.,
2012) and broader spectrum agents such as MccB17 that demonstrates activity
against a collection of Citrobacter, Klebsiella, Salmonella, Shigella and
Pseudomonas species (Cotter et al., 2013). Analysis of microcin C and its analogues
for potential chemotherapeutics produced some promising results and are reviewed
by Vondenhoff and Van Aerschot (2011).
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Thus, a screening effort was initiated that targeted inhibitors of Gram-negative
bacteria and yielded a promising candidate isolated from an HVS sample. The
isolated K. pneumoniae strain A7 has been identified to contain a gene cluster
responsible for production of microcin MccE492/G492.
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4.2 RESULTS:
4.2.1 Simultaneous antagonism assays for preliminary analysis of the
antimicrobial activity spectrum of peptide NI05
Peptide NI05 was partially purified from a non-capsulated Klebsiella
pneumoniae strain, which was identified using 16S rRNA gene sequence analysis.
This bacterium was identified from a collection of 96 isolates recovered from
screening plates, which had been inoculated with bacteria grown from HVS samples.
The producer K. pneumoniae strain and the partially purified antimicrobial peptide,
NI05, was significantly active against K. pneumoniae species but was also
particularly efficacious against E. coli strains, including ESBL producers (Table 4.1).
Table 4.1 Peptide NI05 spectrum of activity determined through simultaneous antagonism assays
Gram-negative indicator strains NI05 Gram positive
indicator strains NI05
E. coli 414 +3 B. subtilis -
E. coli DH5a +4 C. difficile -
ESBL E. coli M2 +3 C. diphtheriae -
ESBL E. coli 169 +1 M. luteus -
K. aerogenes - S. aureus 308 -
K. pneumoniae 169 +3 S. aureus 1195 -
N. gonorrhoea - MRSA -
P. aeruginosa 257 +1 VR Enterococci -
Salmonella Typhimirium
+1
*Extended spectrum β-lactamase producing E. Coli (ESBL E. coli), Methicillin resistant S. aureus (MRSA), Vancomycin resistant Enterococcus faecium (VRE)
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No activity was observed against Gram positive species, which is an
interesting contrast to pumicin NI04, a Gram positive active agent that was active
against a Gram-negative bacterium, N. gonorrhoea.
4.2.2 Optimisation of antimicrobial peptide production
Although clear activity was observed during simultaneous antagonism assays
on solid media, production of peptide NI05 in liquid culture was very poor with no
detectable antimicrobial activity following incubation in TSB. The quantities that
achieved inhibition of the E. coli strain DH5α were only attainable through 1% yeast
extract supplementation (Table 4.2). Other additives included were observed to have
no effect. In addition, changing the incubation temperature from 370C to 300C and
increasing incubation time up to 48 hours failed to increase the amount of peptide
that was available. During the time controlled experiment, peptide NI05 reached
quantities detectable by well diffusion assay at 14 hours (data not shown).
Table 4.2 Effect of various media and additives on the production and availability of peptide NI05, following overnight incubation at 37oC.
Broth Additives Peptide NI04 (AU/ml)
TSB* - 0
TSB YE* (1%) 80
TSB YE (1%), Lactose (1%) 80
TSB YE (1%), Sucrose (1%) 80
TSB YE (1%), Maltose (1%) 80
TSB Sucrose (1%) 0
BHI* - 0
NB* - 0
* TSB-(Tryptic Soy Broth), YE-(Yeast extract), BHI-(Brain heart infusion broth), NB-(Nutrient broth)
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4.2.3 Purification
The low abundance of the peptide NI05 in culture media made purification of
this agent more challenging. It prevented vigorous purification as following multiple
chromatography steps, the peptide likely became too dilute and the anticipated active
fractions lost their activity, thus only a single pass of RP-HPLC purification
produced a fraction with detectable antimicrobial activity (20 AU/ml). Better activity
was observed following Strata and Sep-Pak C18 purification (80 AU/ml). The
peptide eluted from the Sep-Pak C18 column at 50% ACN+0.01TFA concentration.
During these studies, an interesting observation was made. When Strata-XL
fractions were not subjected to chloroform vapour, the detectable activity rose from
80 AU/ml to 160 AU/ml during the well diffusion assays. It was also observed that,
both RP-HPLC and Sep-Pak C18 purified fractions rapidly lost their activity,
especially after day two. During the polishing stage, with some possible impurities,
active fractions were obtained from HPLC fractions I3 and I4 (Figure 4.3). These
fractions were analysed using MALDI ToF spectrometry.
Figure 4.3 HPLC chromatogram of the active fractions I3 and I4 obtained during purification of peptide NI05.
Active fractions I3 and I4
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4.2.4 Matrix Assisted Laser Desorption Ionisation – Time of Flight (MALDI-
ToF) mass determination
The active fractions obtained from the RP-HPLC were subjected to MALDI-
ToF analysis to determine the mass of the peptide responsible for the antimicrobial
activity. Analysis of the active fractions produced a number of peaks under 2000Da,
however all masses observed were also present in fractions lacking antimicrobial
activity (Figure 4.4). Thus, at the present concentrations we were unable to detect a
peptide peak that could consistently be associated with antimicrobial activity.
Figure 4.4 Mass spectrogram of three separate active HPLC fractions from individual purification runs. The spectrum encompassed molecules up to 10kDa in size, however the only detectable peaks were perceived below 2500Da.
I3
I3
I4
Inactive
Mass (M/Z)
Inte
nsity
(Au)
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4.2.5 Genome sequence and annotation
Genome sequencing results were obtained as trimmed contiguous sequences
(contigs) from the University of Liverpool’s Centre for Genome Research. The
obtained data was assembled in house using the CLC Main Workbench software.
The draft genome sequence was assembled from a total of 3,455,707 raw sequence
reads having an average length of 142.9. Assembly resulted in 180 contigs
comprising a draft genome of 5,415,176 bp [N50 299,210 (50% of the genome was
contained in contigs of 299,210)]. From the draft data, it was estimated that average
genome coverage was 181 fold. The draft genome was designated as K. pneumoniae
A7 and annotated with the xBASE annotation service using the K. pneumoniae strain
XH209 as reference and also with PROKKA annotation software for confirmation. A
visual circular comparison of the K. pneumoniae strain A7 to strains XH209 and
RYC492 genomes was generated. This showed that compared with the RYC492 and
XH209, K. pneumoniae A7 contained a number of regions that were not as well
conserved in the genome of the reference Klebsiella strains (Figure 4.5).
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Figure 4.5 Draft genome sequence of producer organism K. pneumoniae A7 compared with the reference K. pneumoniae strain XH209 and K. pneumoniae strain RYC492 that is known to express MccE492, using BRIG software. The identical regions between both genomes are represented in solid colours and differences are represented with faded colours or gaps.
4.2.6 In silico analysis of the draft genome and discovery of the MccE492 gene
cluster:
Although it was not possible to identify a specific mass through MALDI
analysis, peptide NI05 had some peculiar properties, such as low abundance/activity
in a spectrum of broths and susceptibility to chloroform. Based on these
observations, literature relating to a collection of similar antimicrobials was
examined leading to the following deductions (A) the only antimicrobial peptide
previously isolated from K. pneumoniae was MccE492 (Lorenzo, 1984) and there is
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a newly discovered putative peptide MccG492 (Vassiliadis et al., 2010) from the
same cluster, though no physicochemical data are yet available on this antimicrobial,
(B) MccM, a microcin from E. coli also shows susceptibility to chloroform vapour
(Patzer et al., 2003; Vassiliadis et al., 2010) and (C) MccH45 is a microcin that
shares the same cluster as peptide MccM (Vassiliadis et al., 2010). Data relating to
these previously reported peptides were included in subsequent studies to drive an
homology based analysis.
A multiple alignment of the candidate amino acid sequences was performed
(Figure 4.6) and portions of the consensus sequence and the leader sequence of each
individual sequence were queried against the draft genome of the K. pneumoniae A7
genome. These enquiries yielded multiple matching regions and two of these regions
were identified as MccE492/MccG492 and MceS2. In addition, an MceK like region
that was also homologous to the MccM leader sequence was identified in strain A7.
Some of these peptides, such as MccE492, were not recognised by the annotation
software used (xBASE/PROKKA), thus the regions of interest were only discovered
following the above analysis.
This process revealed the presence of the complete MccE492/G492 locus
from K. pneumoniae RYC492 in the K. pneumoniae A7 genome indicating that
peptide NI05 is most probably not a novel antimicrobial, but is an additional
example of MccE492/G492. The only difference observed in strain A7 was the fact
that instead of the truncated MceK fusion protein, two ORF’s were observed in this
location; one that was homologous to McmA was named MceK2 and one that was
homologous to MccM was named MceK3, in line with the current consensus
nomenclature. MceK3 was also truncated at the same location as MceK (Figure 4.7).
The identified genetic locus is represented in Figure 4.8. It contains both putative
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microcin candidates and a complete set of the genes orthologous to those that encode
MccE492, H47 and I47 transport and modification machinery in K. pneumoniae
RYC492, E. coli H47 and E. coli CA46.
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Figure 4.6 Alignment of sequences of the structural genes encoding microcins MccM, MccH47, MccE492 and MccG492 reveals striking homology at the C-terminus. Red arrow indicates the residue (Serine 84) where the post translational moiety DHBS is attached to the MccE492 and red line indicates that the region around this location that is also conserved in other members of the group. The green line indicates the conserved GG/GA motif where leader sequences are cleaved from the active peptide.
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Figure 4.7 MceK3 peptide sequence is homologous to the MccM N terminus prior to the stop codon TAG (Green arrow) that is also observed in the sequence derived for the MceK fusion peptide. However, the fragment following the stop codon also resembles and aligns with the serine rich C terminal of the classIIb bacteriocins including the serine 84 (Red arrow) region where the DHBS molecule is docked (Mercado et al., 2008).
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Figure 4.8 Genome maps of the biosynthetic gene clusters involved in production, export and immunity of peptides, MccE492 (mceA), MccG492 (mceL), MccH47 (mchB), MccM (mcmA). Peptides that are of the same colour are homologues to each other [adapted from (Vassiliadis et al., 2010)].
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4.3 DISCUSSION
Microcins of Gram-negative bacteria are far less well explored with only 19
representatives compared with 209 representatives from the Gram positive bacteria
recorded in the Bactibase database (http://bactibase.pfba-lab-tun.org/, date accessed:
09/05/2015). Most of these are derived from Escherichia species and there is only
one biochemically identified entry from K. pneumoniae. Nevertheless, their small
number contains a vast structural diversity making classification of these peptides
difficult (Duquesne et al., 2007b). Broadly speaking, bacteriocins of Gram-negative
bacteria are divided into two groups, microcins that are smaller than 10kDa and
larger colicins, which are over 10kDa in mass.
Microcins can be further sub divided into class I microcins that are 5kDa or
smaller, plasmid encoded, post translationally modified (PTM) peptides and class II
microcins that are larger than 5kDa. Class II microcins that contain PTMs are
categorised under Class IIb and those that don’t contain PTMs are collected under
Class IIa (see Section 1.6.2) (Rebuffat, 2012). During the current study, a K.
pneumoniae strain designated A7, identified from an HVS sample, presented potent
antimicrobial activity exclusively directed towards Gram-negative indicator strains,
including P. aeruginosa and Salmonella Typhimurium but was especially effective
against E. coli strains.
Although partial purification of the antimicrobial agent was successful, the
RP-HPLC fractions obtained were not sufficient to isolate a distinctive mass or for
further detailed evaluation, such as tandem mass spectrometry. Hence, an alternative
approach was chosen using the physicochemical properties of peptide NI05 to gather
similar AMPs for a comparative analysis. The amino acid sequences of these
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Discussion
antimicrobials were employed as a guide for an in silico bacteriocin search within
the K. pneumoniae A7 genome.
The only other bacteriocin previously isolated from K. pneumoniae is
MccE492, which belongs to the Class IIb microcin group. In addition, peptide NI05
was a heat stable molecule that was expressed poorly by the producer strain in
culture media and it was labile to chloroform vapour. A literature search revealed
that another microcin MccM produced by E. coli and classed in the IIb group
showed similar characteristics (Patzer et al., 2003). Chloroform susceptibility is
observed in other bacteriocins such as nisin Z and pediocin N5P from Gram positive
bacteria and is utilised as a characterisation trait (Banerjee et al., 2013; Pasteris et
al., 2014; Strasser de Saad and Manca de Nadra, 1993). Thus, the search criteria
were based around members of the Class IIb group of microcins.
Efforts culminated in the discovery of the MccE492/G492 gene cluster in
strain A7. Both microcins encoded in this cluster belong to the class IIb microcin
family and share a conserved serine rich C terminus, where a siderophore moiety is
attached that binds to a single iron molecule to facilitate their Trojan horse like
activity (Thomas et al., 2004). Hence, members of this group are also defined as
“siderophore microcins” (Rebuffat, 2012). Siderophores are chelating agents
secreted by the bacterial cell to bind and facilitate the transport of highly insoluble
iron (Fe+3) molecules into the bacterial cell (Saha et al., 2015). These complexes are
recognised by cell surface receptors and translocated into the cell. Among these
receptors are Cir, FepA and in particular Fiu that recognise the salmochelin
siderophore resultant from enterobactin (Arnison et al., 2013; Fischbach et al., 2006;
Strahsburger et al., 2005; Vassiliadis et al., 2007). Enterobactin itself is formed by
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three N-(2,3-dihydroxybenzoyl)-L-serine (DHBS) molecules that are bound together
to form a cyclic trimer by NRP machinery making salmochelin bacteriocin hybrid
NRP/RiPP peptides (Fischbach et al., 2006; McIntosh et al., 2009). This machinery
is also encoded in the K. pneumoniae A7 genome. In addition to MccE492, MccM
and MccH47 (Vassiliadis et al., 2010) were also shown to exploit this pathway by
carrying a postranslationally attached DHBS molecule on their C terminus that is
recognised by the salmochelin receptors. The resulting translocation of the microcin
into the cell is driven by a TonB and mannose permease dependent pathway (Bieler
et al., 2005; Poey et al., 2006). Mechanisms of this modification are studied most
extensively in MccE492. It was observed to greatly enhance the antimicrobial
activity of unmodified MccE492 (Destoumieux-Garzón et al., 2006) and although a
modified version was initially referred to as MccE492m, it is now considered to be
the mature peptide (Duquesne et al., 2007a).
The modification pathway is most extensively described by Vassiliadis and
colleagues (2007) and involves the MceACDIJ gene cluster (Figure 4.9); the putative
glucosyl transferase MceC is involved in the glycosylation of the enterobactin (step 1
in Figure 4.9). Once enterobactin is glycosylated, it is cleaved by an enterobactin
esterase (MceD) to achieve linearized glc-DHBS3. If the glc-DHBS3 is not utilised
this cleavage process was observed to be continuous until a single glc-DHBS
molecule is achieved and thus gives rise to intermediate MccE492 products
MccE492-glc-DHBS2 and MccE492-glc-DHBS (Step 2). The linearized glc-DHBS3
is then attached to the C-terminal serine-84 of EccE492, through covalent bonding
aided by the MceI peptide homologous to the RTX toxin acyltransferase family
(Mercado et al., 2008), which are involved in fatty acid acylation and activation of
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protoxins such as E. coli haemolysin (Destoumieux-Garzón et al., 2006; Duquesne et
al., 2007a; Trent et al., 1999) (Step 3).
Although its contribution to this mechanism is still unknown MceJ,
homologous to the MchC from the MccH47 gene cluster, is conserved in
biosynthetic gene clusters of E. coli CA46 and H47 strains and also conserved in the
K. pneumoniae A7 cluster (Duquesne et al., 2007a; Vassiliadis et al., 2010).
However, it is observed to be necessary for the production of a functional MccE492
peptide and is believed to have a role in the process where glc-DHBS3 is fused to the
precursor peptide using serine-84 for docking (Mercado et al., 2008)(Lagos et al.,
2001; Thomas et al., 2004; Vassiliadis et al., 2007). The genes involved in
biosynthesis of MccE492 were shown to be exchangeable with their counterparts
involved in MccH47 and MccM biosynthesis (Vassiliadis et al., 2010).
Figure 4.9 Post translational modification pathway of MccE492 with the DHBS siderophore moiety. 1) gycolysation of enterobactin by MceC. 2) cleavage of enterobactin to achieve linear Glc-DHBS3, 3) attachment of the linear Glc-DHBS3 and derivatives to the MccE492 precursor peptide (MceA) [from (Vassiliadis et al., 2007)].
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Since the description of this mechanism, there have not been significant
updates, except the discovery that the adenylation domain of EntF, a protein
involved in enterobactin production, was also essential for Mcc492 maturation in a
manner unrelated to enterobactin production (Mercado et al., 2008). Also, since the
discovery of MccH47 and MccM in 2010 no new members of this group have been
identified. However, research into microcins that utilise similar Trojan horse like
activity such as MccJ25 that carries a lasso fold conferring additional stability to the
microcin (Arnison et al., 2013; Hammami et al., 2015; Mathavan et al., 2014),
MccB17 (Mathavan and Beis, 2012; Thompson et al., 2014) and nucleic acid
carrying MccC (Vondenhoff and Van Aerschot, 2011; Zukher et al., 2014) has
generated some more interest in this group of AMPs.
K. pneumoniae A7 also carried the MceG and MceH genes that together
encode a functional ATP-binding cassette (ABC) transporter unit that provides
energy for transport and release of the MccE492. These genes are commonly found
in bicistronic conformation, as in the K. pneumoniae A7 cluster (Vassiliadis et al.,
2010). The MceF protein is also thought to play a role in transport however its
function is still not clear (Duquesne et al., 2007a; Lagos et al., 2009, 2001;
Vassiliadis et al., 2010). These regions are also related to mchF and mchE genes that
encode an ABC transporter in E. coli CA46 and H47 (Azpiroz and Lavina, 2004;
Azpiroz et al., 2001). These observations demonstrate that the K. pneumoniae A7
operon encodes a complete set of putative genes required for export and modification
of siderophore microcins.
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It was interesting to see that the MccE492/G492 cluster is conserved wholly
between the two Klebsiella species including the truncated MceK like peptides,
MceK2 that shares similarities with the mcmI gene product, which confers self-
immunity to MccM by encoding the immunity protein McmA (Braun et al., 2002;
Duquesne et al., 2007a; Vassiliadis et al., 2010). Also present is the truncated
MceK3 peptide that shares a high degree of homology with the MccM leader
sequence (Vassiliadis et al., 2010). MceK3 was highlighted as a putative bacteriocin
candidate by the BAGEL analysis of the K. pneumoniae A7 genome, which
identified the region as including a predicted class II bacteriocin gene (see, Chapter
5)
The gene encoding MceK3 was also truncated at the same location as MceK
by a premature TAG stop codon that occurs after the GG motif, where the leader
cleavage of the microcin prepetide is expected to occur before the serine rich C-
terminal (Figure 4.7). Intriguingly, a similarly truncated MccM sequence is also
observed in E. coli strain H47 (Vassiliadis et al., 2010). In addition to MceK, the
MhcS2 coding region also shares N terminal homologies with MccI47 but lacks the
serine rich C-terminal region (Vassiliadis et al., 2007).
It is known that MccE492 is still active without its posttranslational
modification, although less so (Duquesne et al., 2007b; Thomas et al., 2004), which
may explain the conservation of this region. However, an interesting attribute of
MccE492 is its ability to form amyloids (Arranz et al., 2012; Bieler et al., 2005). In
the case of MccE492 it is suggested that these amyloids may be involved in
bacteriocin regulation and act as microcin reservoirs or protect the producer (Arranz
et al., 2012) and it was also observed that successful post translational modification
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Discussion
of the bacteriocin impedes the amyloid formation (Marcoleta et al., 2013b). Thus, it
will be interesting, considering the close relationship of this family (Vassiliadis et
al., 2010), to investigate if the truncated peptide is capable of exerting bactericidal
activity and/or forming amyloids that may be involved directly or indirectly in
another desirable process and thus are conserved.
Amyloid formation is mainly associated with neurodegenerative conditions
such as Alzheimer’s disease in humans due to defective peptides such as N-
terminally truncated Aβ peptides (Dobson, 1999; Lashuel et al., 2002; Oberstein et
al., 2015). However, in bacteria amyloids were also described in constructive
processes such as hyphae formation in Streptomyces coelicolor (Claessen et al.,
2003) and the curli and Fap amyloids that are involved in biofilm formation in
Salmonella enteritidis and P. aeruginosa (Austin et al., 1998; Chapman et al., 2002;
Dueholm et al., 2013), respectively, which are only some examples.
In conclusion, during this study it has been demonstrated that the draft
genome of K. pneumoniae strain A7, which was isolated from an HVS sample,
encodes the MccE492/G492 gene cluster in its entirety, suggesting that this a well
conserved region and is possibly important in the ecology of K. pneumoniae strains.
Thus, closer inspection of the uncharacterised genes in this cluster will be important.
It was disappointing to see these well-studied regions were not annotated by the
software used and had to be manually uncovered. While isolation of peptide NI05
was not readily possible, in light of the current findings, it is most likely that the
antimicrobial activity observed from strain A7 was, at least in part if not wholly,
conferred by MccE492. It may be concluded that the peak representing the peptide
was masked during MALDI-ToF as result of its low abundance in the purified
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Discussion
fractions, due to presence of high intensity contaminants such as those at 1795Da
and 926Da, as all the necessary components for its production and secretion are
present and the physicochemical properties of NI05 and MccE492 are so similar.
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5 CHAPTER 5
GENOME MINING OF ANAEROBIC BACTERIA, KNOWN PRODUCER
BACTERIA AND CELL FREE EXPRESSION OF PUMICIN NI04
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5.1 INTRODUCTION
Ribosomal peptides such as bacteriocins that are the focus of this study are
hard to locate in genome sequence data as they can be encoded by poorly conserved
and small open reading frames (ORFs). These can be overlooked by programs such
as BLAST that relies on sequence to sequence homology (Lee et al., 2008; Schmidt
et al., 2005). There are some powerful search tools that can identify more distant
relationships, such as PSI BLAST, which profiles homology and HHpred that
generates Hidden Markov Model (HMM) to HMM profile comparisons (Altschul et
al., 1997; Söding et al., 2005). However, novel antimicrobial discovery using these
tools is labour intensive. A LanT peptide driven study performed by Singh and
Sareen (2014) is one such study.
Comparatively, BAGEL and antiSMASH are convenient, free to use web
based tools (Blin et al., 2013; de Jong et al., 2010, 2006). They combine homology
searches with contextual analysis to improve antimicrobial peptide discovery. Thus,
in addition to screening for homology between known bacteriocin ORFs and the
query sequence, they also scan for additional ORFs that are located in the immediate
surroundings of known bacteriocins. These genes mostly code for the proteins that
are required for processing, transport, modification, regulation and producer self-
immunity to the bacteriocin (de Jong et al., 2010, 2006) and include LanR, LanK,
LanM and ABC transporters (see Section 1.5.1) (Arnison et al., 2013; Dirix et al.,
2004; Dischinger et al., 2009; Herzner et al., 2011; Siezen et al., 1996; Singh and
Sareen, 2014). An example result output can be seen in Figure 5.1.
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In silico analysis offers a unique angle to antimicrobial peptide research as it
makes it easier to screen hard to grow bacteria, including some toxigenic species
(Eg: Clostridium botulinum), and allows analysis of metagenomic data (Kang and
Brady, 2013).
Anaerobic bacteria are an emerging source for discovery of antimicrobial
peptides. Many studies have proven their capability to produce a plethora of
secondary metabolites and antibiotics; perfrin, clostrubin and ruminococcin C are
only some examples (Crost et al., 2011; Letzel et al., 2014; Pidot et al., 2014;
Timbermont et al., 2014).
In addition, although anaerobes are proving a rich source to mine in silico,
heterologous anaerobic expression of these metabolites will still require extensive
exploration and optimisation of growth conditions. This could be circumvented
through molecular cloning, recombinant expression of the candidate peptide in
aerobic hosts or cell free expressions, which are viable options. In this study, we
Figure 5.1 Graphical result representation of BAGEL3 software analysis. The gene cluster belongs to lead 4 (see below), a putative class II lantibiotic identified during this study and is surrounded by important motifs. LanK and LanR are known to be involved regulation of class II bacteriocins, the ABC transporter is responsible for secretion) and SacCD encodes the SAM enzyme that introduces sulphur bridges.
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sought to investigate the ability of BAGEL 3 software to generate reliable leads that
were likely produce an active product following cloning and expression.
Bacteriocins were identified from anaerobic bacteria, mainly focusing on
Clostridium species that are known for their toxigenic nature (Hatheway, 1990) and
Propionibacterium species that have probiotic applications (Darilmaz and Beyatli,
2012; Ekinci and Gurel, 2008; Filya et al., 2004). Having generated genome
sequence data for the two producers isolated during this study (see Chapters 3 and
4), it was decided that these data should also be included. As a proof of concept and
to assess the feasibility and convenience of the direct cloning approach, cloning and
cell free expression of the pumicin NI04 structural gene was attempted, given that
this had been characterised as encoding an active peptide during the current study.
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5.2 RESULTS
5.3 GENOME MINING RESULTS
Mining the genomes of 35 anaerobic bacteria for putative antimicrobial
peptides using BAGEL 3 software yielded 33 possible producer bacteria and 66
predicted putative bacteriocins (Table 5.1). Most of the identified products belonged
to two major groups, class II bacteriocins and sactipeptides. Other identified peptides
included those from class III, class IV, LAPs, bottromycins, lasso peptides and the
lanthipeptides. In addition, analysis of the producer bacteria B. pumilus J1 and K.
pneumoniae A7, identified during this project, yielded seven additional putative
bacteriocin candidates (one has been described and discussed above, in Chapter 4).
Pumicin NI04, described in Chapter 3, was not identified by BAGEL, which is not
surprising given its lack of homology to previously identified bacteriocins.
Closer inspection of the data obtained revealed that 19 out of the 73 putative
bacteriocins were promising leads, as they were either homologs to known
bacteriocins or accompanied by multiple genes that are relevant to bacteriocin
production, including modification, immunity and transport proteins. Five of these
leads only shared significant identities (E value < 0.001) with previously defined
bacteriocins and weren’t located with any other bacteriocin related accessory genes,
except ABC transporters; lead 11 with lactococcin 972 (38%), lead 10 with linocin-
M18 (47.9%), lead 13 and 15 with garvicin ML (both 20%) and leads 16 and 17 with
UviB (25%) (Table 5.1).
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The leads that displayed both homology to known bacteriocins and were also
co-located with bacteriocin related biosynthetic clusters are described in more detail
below. The only exception is lead 18 that was homologous to MccM (71.2%); this
peptide was discovered during the work described in Chapter 4 and is in fact a
truncated MccM like peptide.
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Table 5.1 The short list of promising bacteriocin leads identified in the genomes of 35 species of anaerobic bacteria of the genera Clostridium and Propionibacterium and the producer bacteria K. pneumoniae A7 and B. pumilus J1. Unique leads are novel leads that do not share homology with known bacteriocins but are located with bacteriocin related genes.
Lead No Bacteria Location Type Amino acid sequence Significant
homologies Anaerobes
1 Clostridium
acetobutylicum 824 (NC003030)
Chromosome Sactipeptides MNFLKNFYSCVLHNSVSNILCILLYFCLLGNNTIIYYFCKIGKIKKVA Unique
2 Clostridium beijerinckii
NCIMB8052 (NC0090617)
Chromosome ClassIII
MKKQLRKVMILAVSLLMLLGQSPNIVFAATSPNISSSAYNSENIFTQSGYKGQCTWFVWGRAYEKLGIKLNSQFYGNAKQWWNETTYPKGQTPAANSIAVFGNGSAGHVVFIESVSGDTVYFNEANYHVSKAYDGAEENQTVSAFKSRSANFLGFIYLQGNPSEPSDPTQSGFTYPNNAQVSGDFLYVRDSSGNIISGRRVDDGDKITVLDVSYSTQLALIEYPTPNGVRTGYVTNATNIIKYFNDGAWKNGSTSENVYDSNGNVIGSLSPGETATPLYRKNGKLSVVYNTSKGANTKSGFVVYNGGFNKY
Unique
3 Clostridium cellulovorans
743B (NC014393) Chromosome Lant. class_II
MQNYESKAGFISEMELDELVSNKTVGGATTVPCAIAIIGITLSAGICPTSACSKDCPWNN
lichenicidin A2
(35%)
4 Clostridium lentocellum DSM 5427 (NC015275)
Chromosome Sactipeptides MELCTIDGLKLDKFEDLKSTELEEVNGGGAGAVIAVVVVICVIAFAVGVYNGYQDNKK
Unique
5
Clostridium saccharolyticum WM1
(NC014376) Chromosome Sactipeptides MKENLQMHLILPLLIRCGKMNPKEDTAAGQENK
Unique
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Lead No Bacteria Location Type Amino acid sequence Significant
homologies
6 Clostridium stercorarium DSM 8532 (NC020887)
Complete Genome
Sactipeptides MKQVQPQGFLNCVLICVGGCLTCISDGPVIIVDFVSGGTAASTGSSA
Unique
7
Clostridium botulinum A strain ATCC 19397
(NC009697) Chromosome LAPs VAPGSCCCCSCCCCVSVSVGGGSASTGGGAAAGQGGN Unique
8 Clostridium perfringens strain 13 (NC003366)
Chromosome Lasso peptide MVSKLISLDSIVSQKEGIDVTELNGEKVMMDLDKGKYFMLNETGSTIWDAINEPKSVSEIIEATIKEYDIDRETCESKVLEYLEKLRHEEIVFIN
Unique
9 Clostridium species
BNL1100 (NC016791) Chromosome Lant. class_II MSHSTIGFAFEDLGEKEMAASQNASSSANSIVTIYSLTGT
CLPSITVTICQVTVPVTITVTAAN Unique
10
Propionibacterium acidipropionici ATCC
4875 (NC019395)
Complete Genome
ClassIII
MNNLHRELAPISEAAWKQIDDEARDTFSLRAAGRRVVDVPEPAGPTLGSVSLGHLETGSQTDGVQTSVYRVQPLVQVRVPFTVSRADIDDVERGAVDLTWDPVDDAVAKLVDTEDTAILHGWEEAGITGLSEASVHQPVQMPAELEQIDDAVSGACNVLRLADVEGPYDLVLPQQLYTQVSETTDHGVPVVDHLTQLLSGGEVLWAPAARCALVVSRRGGDSCLFLGRDVSIGYLSHDAQTVTLYLEESFTFRVHQPDAAVALV
Linocin-M18
(47.9%)
11
Propionibacterium acnes TypeIA2 Pacn17
(NC016512)
Complete Genome
ClassII (unmodified)
MTLSLLLAMKRFSRRSYKEEIVSTVWRHFAAVPITGLLLASTATIAMADTVNPPEGGVWRYGRGYSDYFHGSKKHGSSVQGVNFVRSPCVKAGSWSYARTDAARFGNKAWYRTC
Lactococcin 972 (38%)
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Lead No Bacteria Location Type Amino acid sequence Significant
homologies
12
Propionibacterium propionicum F0230a
(NC018142)
Complete Genome Lant. class_II MQSNYDDQILDNLAELSDTEIEELLGAGWGSIFSFTHECN
TNTMTQLFTCCF Ruminococcicin A (38.30%)
Producers
13 B. pumilus J1 Draft Genome Head to tail
cyclised peptide
MTKATDSKFYALLSLSLLAVTLIALVIGNGSLIAANLGVSTGTAFTIVNFLDAWSSVATVITIVGMFTGVGTISAGVAASILAIIKKKEKSKAAAF
Garvicin ML
(20%)
14 B. pumilus J1 Draft Genome Head to tail
cyclized peptide
MTETRNEIKLHVLFGALAVGFLMLALFSFSLQVLPVADLAKEFGIPGSVAAVVLNVVEAGGAVTTIVSILTAVGSGGLSLIAAAGKETIRQYLKNEIKKKGRKAVIAW
enterocin AS-48
(80%)
15 B. pumilus J1 Draft Genome Head to tail
cyclized peptide
MGSSEGIASLASIDFNSGNQFALDLATNLGISRKTAYAAIGVIMTTGDVLTILSLLAVVLGGTGLVTAAMVATAKKLATKHGKKYAAEW
Garvicin ML
(20%)
16 B. pumilus J1 Draft Genome Class 2 VEMDLTQYLMTQGPFAVLFCWVLFYVLNTTKERENKLNEQIEAQNDVLAKFSEKYDVVIDKLDKIERNLK
UviB
(25%)
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Lead No Bacteria Location Type Amino acid sequence Significant
homologies
17 B. pumilus J1 Draft Genome Class 2 MVEMDLAQYLMTQGPFAVLFCWVLLYVLNTTKERESKLNEQIEAQNEVLAKFSEKYDVVIDKLDKIERNLK
UviB
(25%)
18 K. pneumoniae A7 Draft Genome Microcin MRKLSENEIKQVSGGDGNDGQAELIAIGAIAGTFLSPGIGSIAGAYVQWSLALEWRSAL
Microcin M
(71.20%)
19 K. pneumoniae A7 Draft Genome Bottromycin MPVPNHRHDENVLSIDEIFQLKLTSAFINKPAKTIAYYLLSHLFSSSG
Unique
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5.3.1 Lead 3
Lead 3 had significant homology with the A2 component of lichenicidin
(35%) (Begley et al., 2009; Letzel et al., 2014), a two peptide class II lanthipeptide
bacteriocin. It also aligned with beta components of two other peptide lantibiotics,
including entrocin W beta (29%) (Sawa et al., 2012) and plantaricin W (26.7%)
(Holo et al., 2001), especially in the C terminal portions (Figure 5.2). While the
cluster contains two sets of LanM class II lanthipeptide modification proteins and
two sets of LanT transporter proteins, BAGEL 3 did not pick up a partner peptide to
lead 3 (Figure 5.2). Although a visual inspection of the intergenic region was not
carried out, Letzel et al. (2014) have identified a companion peptide.
Figure 5.2 A) Amino acid sequence alignments of lead 3 with two component members of the class II lanthipeptide family, including lichenicidin A2 (orf023). B) The biosynthetic cluster of lead 3 as predicted by BAGEL 3 software.
A
B
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5.3.2 Lead 12
Lead 12 is another promising bacteriocin candidate that shares homology
with class II lanthipeptides and strong sequence alignment with ruminococcicin A
(38.3%) (Dabard et al., 2001), lacticin 481 (36%) (Piard et al., 1992) and salivaricin
9 (26%) (Wescombe et al., 2011) (Figure 5.3). The genome cluster also contained an
ABC transporter gene involved bacteriocin secretion, in addition to class II
lanthipeptide modification genes LanC and LanM.
Figure 5.3 A) Lead 12 sequence alignment shows conserved regions with ruminococcicin, lacticin 481 and salivaricin 9. B) The putative bacteriocin is accompanied by LanM and LanC modification components, multiple ABC transporters and two bacteriocin related genes GerE and HisKA 3 with unknown functions, as predicated by BAGEL 3.
A
B
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5.3.3 Lead 14
Lead 14, predicted from the producer B. pumilus J1, is intriguing as it is 80%
identical and has strong C terminal alignments to enterocin AS-48, a circular class
IV inhibitor of Gram positive and negative bacteria (José et al., 2014), as well as
Circularin A (28.95%) (Kemperman et al., 2003b) and Leucocyclicin Q (29.7%)
(Masuda et al., 2011). However, lead 14 has a significantly longer N-terminal
sequence and a higher predicted mass of 9684.398Da compared with 7186.77Da for
enterocin AS-48 (Figure 5.4). The cluster contains two putative modification
proteins and an ABC transporter (Figure 5.4).
5.3.4 Unique putative bacteriocin candidates
The mining efforts also yielded some genes encoding unique putative
bacteriocins that were flanked by multiple bacteriocin related biosynthesis genes and
did not exhibit significant homology with known bacteriocins (E value>0.001); these
were leads 1, 2, 4, 5, 6, 7, 8, 9 from anaerobic bacteria and lead 19 from K.
pneumoniae A7. A selection of genome maps from these predicted bacteriocins are
displayed below (Figure 5.5).
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Figure 5.4 A) the amino acid sequence alignment of lead 14 with circular bacteriocins Enterocin AS-48, Leucocyclicin Q and Circularin A. B) The anticipated biosynthetic gene cluster consists of two modification genes, HttB and HttC and an ABC transporter.
B
A
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Figure 5.5 Unique bacteriocin sequences predicted by BAGEL 3 software. A) Lead 4 is a predicted sactipeptide, B) lead 7 is a predicted LAPs peptide, C) lead 19 is a putative bottromycin and D) lead 9 is a likely class II lanthipeptide family bacteriocin.
A
B
C
D
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5.4 CLONING RESULTS
The outcome of in silico bacteriocin mining work was analysed and a short
list of likely putative bacteriocins was created. However, the only way to confirm the
antimicrobial potential of the identified leads is through direct observation of
bacterial inhibition in response to presence of the suspected bacteriocin lead. This
also requires an understanding of the potential target bacteria, which would be used
in screening assays.
With a robust recombinant or cell free expression system in place that can
generate sufficient quantities of the peptide of interest, identified leads can be
assessed in a cost and time efficient manner. The proposed system in this project was
based around the PURExpress cell free expression system, where expression is
controlled and facilitated by the pET-28a plasmid vector. As a proof of concept, the
efficiency of this system was assessed by attempting the expression of pumicin
NI04.
To initiate the process, pET-28a plasmids were extracted from pre
transformed E. coli XL1 blue cells using the Qiagen miniprep kit. The insert was
amplified from the B. pumilus J1 genome using PCR. Both the plasmid and the insert
were digested using the appropriate restriction enzymes (see Section 2.5). Digested
products were gel purified (Figure 5.6) and ligated. Transformation reactions were
performed using the T4 DNA ligase and plated out on LB/Kan selection plates.
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5.4.1 Insert confirmation and validation following transformation
Following the transformation reactions, 26 colonies were observed for the
pmnA construct on the LB/Kan selection plates. These colonies were checked for the
presence of an insert using the colony PCR method. Results indicated that 22 out of
26 colonies contained an amplifiable product of the pmnA insert (Figure 5.7). The
correct product length was confirmed using the PCR amplified insert DNA from the
producer organism B. pumilus.
Figure 5.6 Digested NI04 structural gene insert (left) and pET28a vector DNA products (right) prior to gel purification.
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Figure 5.7 Gel image displaying the comparison of colony PCR amplified pmnA bands from the clones (CL) to those amplified from the producer. Positive control (+) was insert DNA amplified from producer B. pumilus J1 DNA and the negative control (-) was amplification from pET28a plasmid DNA with no insert (the template vector is visible in the negative control lane). Expected product length was 319bp.
After the confirmation of the clones (CL) carrying the insert from the
selection plate, CL1 and CL2 were picked at random to carry out expression studies.
However, before committing to expression studies, the orientation of the inserts was
validated by substituting the reverse primer with the T7 downstream primer and
performing PCR amplification. The amplicons generated were at the expected ladder
interval, located between 400-500bp markers (Figure 5.8). Once correct orientation
was confirmed, the nucleotide sequence for both clones was validated by sequencing
the insert region within the plasmid.
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Consensus nucleotide sequences generated for each clone were then aligned
to the expected nucleotide sequence. The results indicated that, while the insert
carried by CL2 encoded the correct peptide, the 3’ end of the insert carried by CL1
had errors and encoded a faulty protein (Figure 5.9). As a result, expression studies
were conducted using plasmids generated from the CL2 stocks.
Figure 5.8 Insert orientation was confirmed using pmnA gene forward primers and the T7 promoter region reverse primers. The expected product length was 435bp.
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Figure 5.9 CL1 and CL2 insert region sequence alignments with the expected pET28a plasmid T7 region containing the pumicin NI04 gene pmnA. The alignments showed that while CL2 encoded the correct sequence, the CL1 insert had a mutation in the 3’ end and possibly encodes a non-functional peptide
.
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5.4.2 In vitro expression of pumicin NI04
Following the in vitro expression reaction, the resulting peptide mixtures for
the DHFR control and the experimental sample were filtered using a 100kDa cut off
filter and the filtrate was reverse purified using the Ni-NTA His pure beads. A
sample from the whole mixture, the 100kDa flow through and the final purification
product of each reaction was tested for antimicrobial activity using the agar well
diffusion assay. The bioassay of the final purification products using the well
diffusion assay failed to produce inhibition zones around the wells that contained
both the purified experimental peptide and the control peptide (DHFR). However
when the whole reaction mixture and the 100kDa cut-off filtrate were tested there
were inhibition zones surrounding all test samples including the negative control that
contained only the reaction mixture without the added pET28a-pmnA or the DHFR
plasmid (data not shown). This indicates that the reaction buffer contained an
inhibitor that needed to be excluded prior to antimicrobial bioassays in order to
reveal any activity specific to the recombinant pumicin NI04.
Subsequent SDS- PAGE gel analysis of the samples exposed two bands that
aligned with the expected protein weight marker intervals for both the experimental
and control mixtures (Figure 5.10). However, the expression of the experimental
peptide was observed to produce a considerably lower yield than that of the DHFR
peptide expressed by the control plasmid. Although it is possible that the peptide was
diluted past its MIC during the purification process, it was not possible to test
antimicrobial activity without purification of the product due to the antimicrobial
properties of the reaction components mentioned above.
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1 2 3 4 5 6Ladder
3
6
14
17
28
38
49
~MW (kDa)
Figure 5.10 Reverse purification of the in vitro expressed pumicin NI04 indicated with red arrows and positive control DHFR indicated with black arrows, (1) Ni-NTA purified DHFR, (2) Ni NTA purified pumicin NI04, (3) DHFR 100kDa ultrafiltration flow through, (4) pumicin NI04 100kDa ultrafiltration flow through, (5) DHFR whole reaction protein, (6) pumicin NI04 whole reaction protein.
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5.5 DISCUSSION
Mining of publicly available genomic data for putative bacteriocin candidates
produced by anaerobic bacteria, B. pumilus J1 and K. pneumoniae A7 with BAGEL
3 software has yielded 73 different predicted bacteriocin candidates that are referred
to as the “leads”. Many of the peptides identified belonged to the class II unmodified
and miscellaneous sactipepetide families. However, LAPs, large bacteriocins, lasso
and lanthionine containing peptides were also predicted, demonstrating that a large
spectrum of bacteriocin classes may be accessible from anaerobic bacteria. From the
bacteriocin library created, nineteen candidates were chosen as promising leads and
short listed for possible cloning in future projects. In order to be considered
“promising”, leads had to either be clustered with multiple bacteriocin accessory
genes and/or exhibit homologies with known bacteriocins. The putative bacteriocins
that contained both desirable properties are discussed below.
The first promising lead that stood out was the putative class II lanthipeptide
lead 3. This peptide formed alignments with two-peptide bacteriocins of this group
and specifically with the lichenicidin A2 peptide, instead of the A1 moiety (Begley
et al., 2009; Dischinger et al., 2009; Shenkarev et al., 2010), and with enterocin W
and plantaricin W beta peptides, but not the alpha components (Holo et al., 2001;
Sawa et al., 2012). These results, and the presence of two LanM proteins, indicated
that there should be a second AMP structural gene, but BAGEL 3 had only returned
a single predicted bacteriocin. However, other mining studies have revealed a second
putative bacteriocin, ClocelDRAFT_0418 (equivalent to an anticipated lead 3 A1),
which was identified from the same cluster that precedes the lanM gene and is
located upstream of lead 3 A2 (de Jong et al., 2010; Letzel et al., 2014). The putative
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lead 3 A1 (Letzel et al., 2014) is 35% identical to lichenicidin A1 and also forms
alignments with Enterocin W and plantaricin W alpha peptides, especially following
the conserved GG/GA motif where the precursor peptide leader sequence is likely to
be cleaved (Caetano et al., 2014). The putative biosynthetic machinery identified is
also similar to that of lichenicidin, which contains two sets of LanM and one LanT
peptide (Begley et al., 2009; Dischinger et al., 2009; Shenkarev et al., 2010). Thus, a
complete set of prepeptides, modification and transport components are present in
the identified gene cluster for production of an active two-component class II
lanthipeptide. It is quite interesting that BAGEL 3 software did not pick up the
putative A1 component of the lead 3 cluster, especially as a paper published by de
Jong et al. using BAGEL 2, has actually reported the presence of this putative A1
component, but not the A2 homolog (de Jong et al., 2010). The BAGEL3 software
does not discard the previously described bacteriocins.
Lead 12 on the other hand was predicted to be another significant class II
lanthionine containing peptide candidate that was homologous to ruminococcicin A,
an inhibitor of Clostridium perfringens, which is produced by another anaerobic
bacterium Ruminococcus gnavus (Dabard et al., 2001). Ruminococcicin A is an
intriguing peptide that is produced in the presence of trypsin (Gomez et al., 2002;
Marcille et al., 2002). In addition to the presence of a LanM protein for modification
and an ABC transporter for secretion, it is possible that the predicted “unknown
related” peptides GerE and histidine kinase HiskA3, which play roles in signal
transduction and regulation can be involved in regulation of expression of this
putative bacteriocin (Attwood et al., 2007; Ducros et al., 2001; Wolanin et al.,
2002). Salivaricin 9 (Barbour et al., 2013; Wescombe et al., 2011) and lacticin
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481(Piard et al., 1992), two potent Gram positive active agents were also related to
lead 12.
Lead 11 on the other hand is a putative class II bacteriocin similar to
lactococcin 972 encoded by P. acnes TypeIA2 Pacn17 that exerts its activity by
binding to lipid II cell wall precursor (Martínez et al., 2008). It was observed in a
previous study that most propionibacteria possessed a lactococcin 972 like peptide
(Letzel et al., 2014), however, BAGEL3 analysis of propionibacteria sequences in
the current study only yielded one such peptide. The reason we have selected this
peptide for the short list is the ease of successful functional cloning of class II
bacteriocins as they don’t require complex modification machineries (Olejnik-
Schmidt et al., 2014; Sandiford and Upton, 2012).
Amongst two putative large class III peptides chosen for the “short list”, the
one identified from P. acidipropionici was the most interesting. Large bacteriocins
have been previously identified from anaerobic bacteria, propionicin SM1 being one
example identified from P. jensenii DF1 (Miescher et al., 2000). However, what
makes P. acidipropionici an intriguing candidate is the fact that the peptide it
encodes is homologous to linocin M18, a large bacteriocin produced by the Gram
positive bacterium Brevibacterium linen, which was isolated from a cheese product
(Valdés-Stauber and Scherer, 1994). Propionibacterium species, including P.
acidipropionici, are commonly found in dairy products, such as yoghurt and cheese
and are also used as additives in animal feed and observed to improve the fungistatic
and antimicrobial properties of these products in multiple studies (Darilmaz and
Beyatli, 2012; Ekinci and Gurel, 2008; Filya et al., 2004). The significance of this
result is that it highlights another application of in silico discovery methods, namely
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producer identification. If functional production of putative linocin M18 like
bacteriocin from P. acidipropionici can be confirmed this may aid in its
incorporation in new probiotic products for human or animal use.
The remaining large class III bacteriocin had significant homology to
bacteriocin BCN5 according to the BAGEL 3 software. Production of this
bacteriocin was shown to be activated following DNA damage due to UV exposure
and it will thus be interesting to attempt its cloning to see if it would be possible to
bypass this activation using an inducible promoter (Dupuy et al., 2005).
In addition to those peptides that shared homology with known bacteriocins,
there were also eight putative unique bacteriocin clusters, which were observed to
contain a selection of bacteriocin related genes and some are discussed here. Lead 1
is a good example for sactipeptides; it carries a predicted SacCD region, a radical S-
adenosylme-thionine (SAM) enzyme that is involved in formation of sulphur to
carbon bonds in sactipeptides (Flühe et al., 2012), as well as an ABC transporter. In
addition, lanthipeptide response regulator genes encoding LanK and LanR are visible
upstream that indicate there may be a putative lanthipeptide structural gene present
upstream as well (Dischinger et al., 2009; Herzner et al., 2011; Siezen et al., 1996).
Lead 7 is a predicted LAP that is accompanied by a member of the YcaO like
protein family related to the cyclodehydratase C and D components (LapBotD) in its
cluster. These proteins are required together for the maturation of LAPs (Dunbar et
al., 2014, 2012). Lead 9 on the other hand contains the LanM modification gene that
defines the class II lanthipeptide group. Although these are unique leads for their
respective classes, whether or not they exhibit any antimicrobial traits requires
further analysis.
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Another aim of this study was to identify the presence of possible additional
cryptic bacteriocin genes in the producers K. pneumoniae A7 and B. pumilus J1,
which were also analysed using the BAGEL 3 software. Results obtained provided
an interesting contrast to the wet laboratory results reported in previous Chapters.
Two predicted bacteriocins were discovered from the K. pneumoniae A7 genome,
one bottromycin and one microcin candidate. Furthermore, five putative bacteriocin
genes were identified from the producer B. pumilus J1 strain three of which encoded
head to tail cyclised peptides and two class II bacteriocins.
It isn’t uncommon for a single bacterium to produce multiple bacteriocins.
For example some strains of Streptococcus salivarius carry transferable mega
plasmids that encode multiple bacteriocins (Burton et al., 2013; Wescombe et al.,
2006), and strains of E. coli (Gordon and O’Brien, 2006), Enterococcus faecium
(Gaaloul et al., 2015; Izquierdo et al., 2008) and Lactobacillus salivarius (O’Shea et
al., 2011) have also been shown to be multiple bacteriocin producers.
Lead 14 was the most interesting of those identified from B. pumilus J1, as it
may be the elusive peptide NI03 observed during laboratory studies. This lead,
according to the BAGEL 3 software, carries significant homology to the bacteriocin
enterocin AS-48. Like peptide NI03 fraction, enterocin AS-48 is also active against
Gram positive and Gram-negative species (José et al., 2014). In addition its
intriguing that leucocyclicin Q that was revealed to share homologies with lead 14
also possesses Gram-negative activity at high concentrations (Masuda et al., 2011).
Expression of enterocin AS-48 requires the gene cluster as-48ABCC1DD1 EFGH
(Figure 5.11) (Sánchez-Hidalgo et al., 2011; van Belkum et al., 2011). BAGEL 3
also revealed two putative genes that were related to this biosynthesis pathway. One
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Discussion
of them, belongs to the DUF (domain of unknown function) 95 family, that are
observed in most head to tail cyclised peptide bacteriocin clusters (Arnison et al.,
2013; Livermore, 2007; Mu et al., 2014; van Belkum et al., 2011). Httb was also
identified and the corresponding domain in the enterocin AS-48 cluster is encoded
by as-48C and HttB is homologous to the CirB peptide from the Circularin A
biosynthetic cluster that combines with CirD to form an ABC transporter and also
contributes to self-immunity, fulfilling the same function as the AS-48B protein
encoded by the as-48B gene (Kemperman et al., 2003a; van Belkum et al., 2011).
Through manual analysis of the genome, it has been possible to identify another
protein “PROKKA_02416” present in the lead 14 gene cluster that is homologous to
the AS-48C1 protein that follows HttC and precedes the putative ABC transporter.
This protein is also involved in enterocin AS-48 production (Sánchez-Hidalgo et al.,
2011; van Belkum et al., 2011), however it was not annotated by BAGEL 3. It was
not possible to link any other remaining un-annotated genes around lead 14 to the
enterocin AS-48 cluster using PSI-BLAST, but there is sufficient evidence that this
predicted peptide is a potential bacteriocin, with anti-Gram-negative activity to
warrant experimental analysis of the cluster. However, as it has not been confirmed
that there was a single peptide species in the NI03 containing fraction, the link
between NI03 and this putative peptide is purely theoretical and must be supported
by additional data.
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Figure 5.11 Enterocin AS-48 and cicularin A gene cluster arrangements [from (van Belkum et al., 2011)]
Analysis of the K. pneumoniae A7 draft genome yielded two putative
bacteriocins, lead 18 produced significant alignments with MccM (Vassiliadis et al.,
2010) and 19 was predicted to be a unique bottromycin candidate. The MccM
homolog, lead 18, is also homologous to MceK found in the MccE492 gene cluster
and is discussed in detail in Chapter 4. In contrast, lead 19 is an unlikely candidate
as bottromycins are known as anti-Gram positive agents, isolated from Gram
positive bacteria (Arnison et al., 2013; Hou et al., 2012; Shimamura et al., 2009;
Tanaka et al., 1966; Waisvisz et al., 1957) and K. pneumoniae A7 did not
demonstrate any antagonism towards Gram positive species, during this project.
However, homology is not a conclusive parameter and it is compelling to suggest
attempted expression of this gene. As Dirix and colleagues (2004) have shown,
microcin V (colicin V) carries motifs that are shared between Gram positive and
Gram negative bacteriocins (Havarstein et al., 1994) that don’t necessarily share a
related spectrum of activity. The LapBotD modification protein identified in the
cluster is observed to play roles in both LAP maturation and in bottromycin
synthesis. However, the bottromycin gene clusters don’t encode the C component of
this peptide. It is believed that during bottromycin synthesis LapBotD plays a role in
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Discussion
macrocyclodehydration and cyclodehydration during thiazol ring formation (Arnison
et al., 2013; Dunbar et al., 2014; Hou et al., 2012; Huo et al., 2012).
As the anaerobic bacteria mentioned above were not available in culture
collections during the current project, to test the feasibility and efficiency of a direct
cloning approach and in parallel to test the achievability of the functional production
of recombinant pumicin NI04, recombinant expression of pumicin NI04 was
attempted. Successful recombinant expression of a functional peptide confers some
significant advantages such as controlled expression and better yields (Ingham et al.,
2005; Olejnik-Schmidt et al., 2014). Expression of active recombinant bacteriocins
has been demonstrated in previous studies, though many of these are unmodified
class II bacteriocins. Some examples are epidermicin NI01 (Sandiford and Upton,
2012), enterocin P (Gutiérrez et al., 2005), enterocin A (Martín et al., 2007) and
divercin AS7 (Olejnik-Schmidt et al., 2014). For this study however, in vitro
expression was attempted as this provides two main advantages over traditional E.
coli based recombinant expression; the first of which is the omission of E. coli cells.
Many non-indigenous peptides are not secreted from the host E. coli and the cells
have to be lysed to recover the peptide, which is less than optimal as cell lysis
introduces multiple impurities that can interfere with stability and complicate the
purification process (Stiege and Erdmann, 1995; Whittaker, 2013). The second
advantage of PURExpress in vitro expression kit used in this study is the fact that it
allows relatively simple reverse purification of an untagged recombinant peptide.
Cell free expression systems are suspensions of specific cell components that are
involved in the ribosomal protein synthesis that include ribosomes, tRNA,
translation factors (10 in PURExpress) and aminoacyl-tRNA synthases (20 in
PURExpress), which, in the presence of ATP are capable of producing protein
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Discussion
(Catherine et al., 2013; Chong, 2014; Shimizu et al., 2005). In the PURExpress
system these components are all individually purified to minimise inhibition due to
nucleases (Shimizu et al., 2005).
Results showed that a peptide was purified, forming bands on SDS PAGE at
the expected mass interval for pumicin NI04. However, bands obtained were faint
and the purified fraction was inactive suggesting a sub-MIC translation reaction
yield. In vitro expression is often associated with low yields or production of a non-
functional peptide due to the in vitro transcription kit lacking the ability to support
possible post translational processes or formation of intramolecular bonds (Gutiérrez
et al 2005). However, as yet, no data are available to suggest that pumicin NI04 has
any intramolecular bonds. The issue of low yield can be addressed using a
continuous exchange system where ATP and other consumable components of the
reaction are continuously replenished during the reaction through a semipermeable
membrane, as these systems are observed to produce higher yields of the functional
product in contrast to the batch kit employed here (Chen et al., 2012). It is also
possible to introduce modifications into the in vitro expression systems such as
chaperone proteins that can enhance total protein yield as well as favourably increase
the proportion of the functional protein produced. In a study by Li and colleagues
(2014), the yield of functional peptide was improved up to 95%, through addition of
chaperons such as GroEL/ES and DnaK/DnaJ/GrpE. However, the resulting effects
were observed to be protein specific rather than universal (J. Li et al., 2014; Zawada
et al., 2011). Nevertheless, commercial systems are still relatively expensive; hence
further exploration of an E. coli based recombinant expression system is still
desirable.
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Indeed, it is also possible that pumicin NI04 may require additional
components of its gene cluster to be expressed in order to achieve its full potential. It
is known that YukD carries homologies with ubiquitins that interact with the
proteins; it is associated with marking them for digestion, modification or transport
and is later cleaved from the peptide. While it is suggested to play a role in secretion,
the manner of the interaction is not clear and, thus, YukD may play a further role in
the functionalisation of pumicin NI04. However, this theory must be proven
experimentally through cloning of the whole gene cluster both in E. coli or in a Gram
positive host more closely related to B. pumilus.
The results obtained here prove that there is still a place for use of both in
silico and traditional antimicrobial peptide discovery approaches. While in silico
based lead discovery has proven to be extremely fast, cloning and expression of a
functional peptide, was not possible and has proven to be time consuming in the case
of pumicin NI04. However, in light of the limited success of pumicin NI04 cloning,
it is possible that this could be more successful with another system that produces
higher yields or with another lead. For example, the peptide identified as lead 3 in
the current study, which is a homolog of the two peptide bacteriocin lichenicidin.
Lichenicidin was efficaciously expressed and studied in an E. coli host (Caetano et
al., 2014).
A number of very promising putative bacteriocin leads were observed during the
genome mining efforts that should be carried forward. Nevertheless, in silico natural
product discovery is still ultimately constrained by our understanding of known
structures and motifs. The best example is the incapability of the BAGEL 3 software
to identify the pumicin NI04 gene from the B. pumillus J1 genome as it is encoded
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Discussion
by an unusual gene cluster for bacteriocins. In addition, it should also be noted that
BAGEL 3 failed to identify the well characterised MccE492 gene from the K.
pneumoniae A7 genome, highlighting the continued importance of, and need for,
classical natural product screening.
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CONCLUDING REMARKS
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Natural product drug discovery has entered a new era. The techniques employed
are faster, more sensitive, more capable and more accessible than those used in
previous programmes. During this project, a number of these methods were
employed. MALDI TOF and Orbitrap MS systems were used for quick derepliction
of the peptide and rapid creation of peptide sequence tags through de novo peptide
sequencing. These techniques are quickly replacing Edman degradation to become
the primary amino acid sequencing methods (Medzihradszky and Chalkley, 2015;
Standing, 2003; Taylor and Johnson, 1997) and they are widely employed in
bacteriocin identification (Borrero et al., 2011; Sandiford and Upton, 2012; Tulini et
al., 2014). Next generation genome sequencing was also employed to quickly create
a reliable draft genome to put the peptide tags generated by MS into a genomic
context. In addition, a number of bioinformatic tools were used to analyse the
generated data including; Jalview (Waterhouse et al., 2009), Artemis (Rutherford et
al., 2000), BAGEL 3 (van Heel et al., 2013), CLC Main Workbench, BRIG (Alikhan
et al., 2011), PSI-BLAST (Altschul et al., 1997), BLAST (Altschul et al., 1990),
PROKKA (Seemann, 2014), xBASE (Chaudhuri et al., 2008), MASCOT (Perkins et
al., 1999) and Peaks studio 7 (Zhang et al., 2012).
The product of combining these cutting edge methods was the discovery of
pumicin NI04, a heat stable AMP that showed potent activity towards Gram positive
species including MRSA, VRE and Streptococcus pneumoniae. The 10kDa size of
pumicin NI04 makes it less desirable for development as an antimicrobial but the
activity observed following the trypsin and α-chymotrypsin treatment during enzyme
stability test indicates that truncated versions of pumicin NI04 are likely to produce
active leads for further development, a similar phenomenon was observed with
plantaricin Y (Chen et al., 2014). Also Salvucci and colleagues showed that short
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Conclusion
peptides derived from enterocin CRL35 demonstrated antibacterial activity (Salvucci
et al., 2007). Trypsin is used in MS/MS as it cleaves peptides at very specific
locations, and thus this information can be easily used to guide preliminary
modification studies (Steen and Mann, 2004).
Pumicin NI04 is also an interesting peptide in an evolutionary perspective as
it exhibits a close relationship to an emerging bacterial peptide family, the WXG-100
superfamily. These proteins first attracted attention following the discovery of the
ESAT-6 (EsxA) peptide of the ESX-1 secretion pathway in M. tuberculosis, which
was noted for its immunogenicity (Pallen, 2002; Sørensen et al., 1995). Pumicin
NI04 is the first WXG-100 peptide that displays antimicrobial properties and it is
most similar to peptide YukE, an EsxA homolog found in B. subtilis (Huppert et al.,
2014). The function of YukE, and many other homologs, is as of yet unknown. Thus,
screening pumicin NI04 homologues for antibacterial activity in other bacteria may
yield more AMPs; it may be the first of multiple antimicrobials to come.
Bioinformatic tools have become an integral part of microbiology. These
approaches played an important role in the discovery of pumicin NI04 and were
crucial in the investigations conducted into peptide NI05 and its producer organism
K. pneumoniae A7. Although the results suggest that peptide NI05 is not novel, the
time taken to reach a verdict concerning whether or not to further pursue the peptide
was quite short, although not straightforward; the MS-based dereplication of peptide
NI05 was not successful. However, the information that was extracted from
preliminary characterisation studies, literature research and the genome sequencing
data obtained, enabled the identification of the MccE492 cluster that was most likely
responsible for the antimicrobial activity observed.
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Conclusion
Although not the desired result, it revealed some thought provoking
information concerning the unidentified members of the Ecc492 cluster as it is
wholly conserved including truncated genes, in two K. pneumoniae species that were
separated by a significant time frame, strain RYC492 being recovered prior to 1984
while strain A7 was recovered in 2012. In addition, RYC492 was isolated from a
human stool (Lorenzo, 1984; Marcoleta et al., 2013a) and K. pneumoniae A7 came
from an HVS sample, although it could be argued that HVS flora are likely derived
from faeces.
Indeed, homology based bacteriocin and secondary metabolite search engines
are becoming established as effective in silico discovery tools (Blin et al., 2014; van
Heel et al., 2013). The opportunity presented by these tools for antimicrobial peptide
research is immense and BAGEL 3 is one of the best examples of the currently
available software that identifies RiPP based putative bacteriocins using direct and
contextual homology to known motifs associated with these antimicrobials (van Heel
et al., 2013). This tool was extensively used in the current project and 19 promising
putative bacteriocin candidates were identified from the relatively poorly explored,
hard to grow anaerobic bacteria.
Expression of pumicin NI04 was possible in the cell free expression system
employed, however the band observed on SDS-PAGE was faint, indicating a low
yield and, most likely due to this reason, no antimicrobial activity was observed from
the purified peptide solution. It is likely that an E. coli based recombinant expression
system could be more successful for the expression of pumicin NI04 or the gene
sequence of lead 14 and its accessory genes, which may encode the peptide named
Chapter 6
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Conclusion
NI03, however as mentioned further study and data is required to prove this
connection.
This study also helped highlight some of the shortcomings of genomic
analysis and annotation software. It became apparent that major parts of the
MccE492 gene cluster, although clearly defined on the reference genome and in the
literature, was not annotated by either PROKKA software or xBASE. This was also
apparent in the annotation of the B. pumilus J1 genome, as many genes, such as the
pmnA gene, were annotated based on outdated information. This gene was annotated
as esxA of the S. aureus Ess pathway yet it carried higher homology to yukE of B.
subtilis. Also “PROKKA 03052” that was homologous to yukBA was annotated by
PROKKA as eccCa1 prior to manual correction based on UniProt entry “O69735”
that was obsolete and eccCa1 is a lower homology match. Most annotations were
based on genes that carried significantly less homology to the genes of interest than
should have been the case. Furthermore, BAGEL3 also failed to annotate the Ecc492
gene a prominent microcin, though it did pick up the truncated peptide MceK and
most of the accessory genes associated with the MccE492 biosynthetic gene cluster
(Vassiliadis et al., 2010). Overall, this demonstrates that these tools are not perfected
yet, which warrants the need to use a combination of approaches and not rely
exclusively on one tool or method.
The discovery of pumicin NI04 demonstrates the strengths of the “Waksman
platform” empowered with new techniques that were absent during its conception
(Lewis, 2013). However, there are still shortcomings, as one single rule remains
unchanged; for it to succeed the peptide of interest must be expressed under
laboratory conditions and although significantly smaller quantities are needed for
Chapter 6
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Conclusion
dereplication (Bouslimani et al., 2014), the yield must be sufficient enough for
efficient purification of the agent. Peptide NI03 and NI05 were not obtained in such
yields under the conditions tested in this study. While it is possible to improve
peptide yield through media optimisation, these approaches are not universal and can
be rather ‘peptide specific’ (Rigali et al., 2008; Sánchez et al., 2010; Zhu et al.,
2014). Without knowing what the peptide is, it is hard to pinpoint what may trigger
its production. Screening and identification of AMPs is still a time consuming
endeavour but the current tools involved in the identification of natural peptides are
amenable to high throughput analysis. High throughput screening systems coupled
with LC-MS identification are likely to be the future of natural AMP screening
(Inglin et al., 2015; Rouse et al., 2007; Sandiford, 2014; Simone et al., 2013).
Supplementation of the “Waksman platform” with in silico tools will also help
alleviate some complications by identifying putative bacteriocins that maybe
produced by the strain under investigation and it is possible to directly express the
peptide in a recombinant host or even in a cell free environment. While tools used
for their identification will change, natural products remain to be the main source for
discovery of novel antibiotics.
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