Foodomics: food science in the post-genomic eraAlejandro Cifuentes

Laboratory of Foodomics, CIALNational Research Council of Spain (CSIC)

Madrid, Spain

CEICS Forum 2011, Tarragona

CURRENT CHALLENGES IN FOOD SCIENCE

Food safety, quality and traceability(ideally as a whole) using omics

approaches

Develop, produce and monitor newtransgenics foods

Production of new functional foods(with scientifically proved claims)

Explain the different answers from individuals to food: personalized diet (Nutrigenetics)

Understand the effects of gene-food interaction onhuman health (Nutrigenomics)

CURRENT CHALLENGES IN FOOD SCIENCE

Food safety, quality and traceability(ideally as a whole) using omics

approaches

Develop, produce and monitor newtransgenics foods

Production of new functional foods(scientifically proved claims)

Explain different answers from individuals to food: personalized diet (Nutrigenetics)

Understand the effects of gene-food interaction onhuman health (Nutrigenomics)

Newne

eds,

new

answ

ers:F

oodo

mics

FoodomicsWe have defined Foodomics for the first time in a SCI journal as:

A discipline that studies the Food and Nutrition domains throughthe application of advanced omics technologies to improve

consumer’s well-being, health, and confidence. (Cifuentes et al.; J. Chromatogr. A 1216 (2009) 7109;

Electrophoresis 31 (2010) 205; Mass Spectrom. Rev. 2011, DOI 10.1002/mas).

The interest in Foodomics coincides with a clear shift in

medicine and biosciencestoward prevention of future

diseases.

BioinformaticsToxicity assaysIn-vitro assaysIn-vivo assaysClinical trials

NutrigenomicsNutrigenetics

Development of:Nutraceuticals

Functional foodsGM foodsNew foods

Food safety

GM foods monitoring

Epidemiologicalstudies

FOODOMICS

Food quality

Foodomics: A new omics for a new food era

To improve consumerswell-being and confidence

fulfilling legislation

Goal

-A. Cifuentes“Food Analysis and Foodomics”J. Chromatogr. A 1216 (2009) 7109-7110.

-M. Herrero, V. García-Cañas, C. Simo, A. Cifuentes“Recent advances in the application of CE methods for food analysis and foodomics”Electrophoresis 31 (2010) 205-228

-C. Simó, E. Domínguez-Vega, M.L. Marina, M.C. García, G. Dinelli, A. Cifuentes “CE-TOF MS analysis of complex protein hydrolyzates from genetically modifiedsoybeans. A tool for Foodomics”Electrophoresis 31 (2010) 1175–1183

-M. Herrero, C. Simó, V. García-Cañas, E. Ibáñez, A. Cifuentes“Foodomics: MS-based strategies in modern Food Science and Nutrition”Mass Spectrom. Rev. 2011, DOI 10.1002/mas

Foodomics papers from our group

(impact factor: 3.569)Special issue on:

“Advanced Food Analysis and Foodomics”

Editor: Alejandro Cifuentesa.cifuentes@csic.es

(to be published in summer 2012)

A book is now under preparation on:

“FOODOMICS:ADVANCED MASS SPECTROMETRY IN

MODERN FOOD SCIENCE AND NUTRITION”

Editor: Alejandro Cifuentesa.cifuentes@csic.es

(to be published in autumn 2012)

Transcriptomics

Proteomics

Metabolomics

Genomics & Epigenomics

Foodomics

FOODOMICS: CURRENT CHALLENGES

Production of new functional foods(scientifically proved claims)

Food safety, quality and traceability(ideally as a whole) using omics

approaches

Develop, produce and monitor newtransgenics foods

Explain the different answers from individuals to food: personalized diet (Nutrigenetics)

Understand the effects of gene-food interaction onhuman health (Nutrigenomics)

Transgenic maize (Bt corn)A new CryIA(b) gene (encodes for a Bacillus thuringiensis protoxin) isinserted by recombinant DNA techniques into the maize genome. The new protoxin acts as insecticide against lepidopters.

Transgenic soybean (RR soybean)A new CP4 EPSPS gene from Agrobacterium (that encodes for a CP4 5-enolpyruvylshikimate-3-phosphate sintase, CP4-EPSPS) is inserted by recombinant DNA techniques into the soy genome. The new CP4-EPSPS enzyme allows to the GM plant to resistthe effect of the herbicide glyphosate.

Can the new inserted genes give rise to other unintended effects?The European Food Safety Agency (EFSA) recommends thedevelopment of profiling techniques to study these unexpected effects.

Second Generation GMOs

Macronutrients:Proteins

Amino acid compositionFunctionality, e.g. bread dough

CarbohydratesStarch composition, inulin, monosaccharides

Vegetable oilsHigh-PUFA (e.g., oleic acid)

Micronutrients:Vitamins, anti-oxidants (Golden rice)Minerals (iron-fortified rice)

Miscellaneous:Hypoallergenic foodsDrought toleranceProlonged ripening

Drought tolerance

THEIR SUCCESS WILL DEPEND (AMONG OTHER FACTORS) ON PROVIDING STRONG SCIENTIFIC EVIDENCES ON:

-THEIR (HEALTH) BENEFITS FOR CONSUMERS-THE EQUIVALENCE WITH THEIR NATURAL COUNTERPARTS

-NO ENVIRONMENTAL RISKS

Ideal Foodomics platform for GMO analysis

DNA/mRNAsPROTEINS

METABOLITES

GENOMICS/TRANSCRIPTOMICS

PROTEOMICSMETABOLOMICS

STATISTICS

GMO biomarkersMetabolite expression

Proteinexpression

Geneexpression

Data

integration

SYSTEMS BIOLOGY

GMO

Unintended effects

GMO detectionTraceability

GMO labeling

GMO safetyLegal issues

GMO removedor improved

Development of a novel analytical methodology, based on MLGA-CGE-LIF, to simultaneously detect multiple GMOs in a single reaction

CGE-LIF

5’Fwd primer

5’

Rev primer5’

III. Circular DNA enrichment (exonuclease treatment)

I. Digestion of gDNA with specific endonucleases

II. Ligation of targets(Circularization)

Multiplex ligation dependent genome amplification (MLGA)

Vector (universal sequence)Long oligonucleotide

probe (Selector)

Target 3

Target 2

Target 1

5’

Target 3

Target 2 Target 1

5’ 3’

5’ 3’

3’Target 1

Target 2

Target 3

IV. Linearization of targets and PCR

Targets

V. Detection of PCR products

21 3

DNA analysis by CGE-LIF

Minutes0 2 4 6 8 10 12 14 16 18 20 22 24

RFU

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

Adh (199 bp)

Mon810 (172 bp)

mon863 (155 bp)

Ga21 (131 bp)

1% GA21, 1% MON863 & 1% MON810 maize mixture

CGE-LIF

Calculated LODs (S/N=3)0.2% GA21 maize 0.3% MON863 maize 0.1% MON810 maize

MLGA is very flexible since the incorporationof new additional selector probes to the ligationstep requires minor adjustments of the selector concentration to detect all the DNA target withLODs below 1%

adh V2 selectormon810 selector

mon863 selectorga21 selector

vector

Digestedgenomic

DNA

Ligation

& Enrichment

Circular DNA targets

Fwd primer

Rev primer

Linearization

&

PCR

Adh V2 selector (2.5 nM)

MON863 selector (5 nM)

Mon810 selector (2.5 nM)

GA21 selector (5 nM)

Simultaneous detection of multiple GMOs with MLGA-CGE-LIF

SOYBEAN Protein content 40 %

Well-known difficulties in protein separation:

Different physico-chemical properties (size, isoelectric point, hydrophobicity) within a wide range of concentrations.

Difficult to separate complex mixtures of proteins.

Challenging identification of (large) proteins.

SHOTGUN PROTEOMICS by CE-TOF-MS:GM vs. wild soybean

PROTEIN EXTRACTION

PEPTIDE ANALYSIS BY

CE-TOF-MS

ENZYMATICHYDROLYSIS

DATA ANALYSIS

GM soybean

Wild soybean

SHOTGUN PROTEOMICS by CE-TOF-MS

Analysis of peptides obtained after hydrolysis of complex protein mixtures

Optimizationrequired

5 10 15 20 25 300

(min)5 10 15 20 25 300

Time(min)

0

1

2

3

4x105Intens.

Rel

ativ

e in

tens

ity

Base peak electropherogram

Some (63) extracted ion electropherograms

0.0

2.5

5.0

0 5 10 15 20 25 30 Time(min)

A

BC

D

E

F

G H

BPESoy Protein Isolate

M+H417.2570

M+H641.3511 Mass spectra

(9.5 min, peak A)

0

1

2

3

4

5

Intens.

200 300 400 500 600 700 800 900 m/z

M+H685.3153

x104

M+H631.3779

M+5H587.4964

M+4H734.1155

0.0

0.5

1.0

1.5

2.0

2.5

Intens.

400 600 800 1000 1200 1400 1600 m/z

Mass spectra(15.2 min, peak C)

x105

M+3H978.4777

M+1H658.3186 0.0

0.2

0.4

0.6

0.8

Intens.

M+2H1378.6605

500 1000 1500m/z

Mass spectra(25.7 min, peak G)

M+3H919.4486

x105

Complexity of the Peptidic Map Automated interpretation

CE-TOF MS ANALYSIS UNDER SELECTED CONDITIONS

Use of deconvolution tool → Study of the peptides obtained in 5 consecutive injections

Mr (3)640.3

0.0

0.5

1.0

Intens.

200 300 400 500 600 700 800 900 m/z

Mr (2)630.4

Mr (4)684.3

M+H417.2570

M+H641.3511 Mass spectra

(9.5 min, peak A)

0

1

2

3

4

5

Intens.

200 300 400 500 600 700 800 900 m/z

M+H685.3153

Deconvolutedmass spectra

(9.5 min, peak A)

x105x104

M+H631.3779

Mr (1)416.2

5 % Cutoff The same peptides were notfound in all the injections

15 % Cutoff

↑ cutoff in order to eliminateunstable signals

The same peptides were found in all injections(simultaneous analysis of more than 150 peptides)

OPTIMIZATION OF AUTOMATED INTERPRETATION

0.0

1.5

3.0

Intens.x105

4.5

6.0

Time(min)

0 5 10 15 20 25 30

BPE7.5

SHOTGUN PROTEOMICS by CE-TOF-MS:

GM vs. wild soybean

SIMILAR PEPTIDE PROFILE

No differences were observed between the GM and wild soybean when a 15% abundance cutoff was used for the automatic

deconvolution of the detected ions

Conventional

Transgenic

Mass resolution: >600.000 in full scanMass accuracy: <0.1 ppm

>10.000 signals/mass spectra>300 elementary composition assignements

(depending on the extraction conditions)

12 tesla FT-ICR-MS at GSF/Munich GermanyP. Schmitt Kopplin

Details on m/z 438.239

175.06122 257.11426

276.98773

301.03528

339.09313

380.99850

477.06693

515.12475

577.13423

605.19248

150 200 250 300 350 400 450 500 550 600 m/z0

2

4

6

8x10Intens.

-MS438.23902

439.24247440.24610

438.23873

439.24213440.24498

438.23899

439.24044440.23478

0

1

2

3

49x10Intens.

0

500

1000

1500

2000

2500

0

500

1000

1500

2000

438.0 438.5 439.0 439.5 440.0 440.5 m/z

GMO

Theoretical compoundC25H32N3O4 Lunarine

Theoretical compoundC4H50N6O6S5

438.23902

439.24247440.24610

438.23873

439.24213440.24498

438.23899

439.24044440.23478

0

1

2

3

49x10Intens.

0

500

1000

1500

2000

2500

0

500

1000

1500

2000

438.0 438.5 439.0 439.5 440.0 440.5 m/z

GMO

Theoretical compoundC25H32N3O4 Lunarine

Theoretical compoundC4H50N6O6S5

METABOLOMICS by FT-ICR-MS, PLE and CE-TOF-MS:GM vs. wild corn

Although the high resolution and sensitivity provided by FT-MS allows the detectionand identification of an impressive number of compounds, PLE and CE-TOF-MS can provide additional information useful to corroborate (or not) the metabolites

identification.

FT-ICR-MS of wild maize

Extraction by PLE with:

Hexane

Methanol

Water

METABOLOMICS by FT-ICR-MS, PLE and CE-TOF-MS:GM vs. wild corn

Mass resolution: >600.000 in full scan; Mass accuracy: <0.1 ppm; Signals/mass spectra: > 10.000Elementary composition assignements: >300 (depending on the extraction conditions)

PROCEDURE FOR THE TENTATIVE CHARACTERIZATIONOF METABOLITES BASED ON FT-MS and CE-TOF-MS DATA

MOLECULAR ION DETERMINATION

ISOTOPIC PATTERN

MOLECULAR FORMULAE ASSIGNATION

SEARCH IN DATABASES

EXPECTED ELECTROPHORETIC MOBILITY

DATA ANALYSIS

SAMPLES CLASSIFICATION/BIOMARKERS DETECTION

Partial least squares–discriminant analysis (PLS-DA)(Q2(cum)=0.52 and R2(Y)=0.99) with sixdifferent maize varieties analyzed by FT-MS.

Maize samples: A) PR33P66; B) PR33P66 Bt; C) Tietar; D) Tietar Bt; E) Aristis; and F) Aristis Bt.

The score scatter plot underlines a differentpattern for the transgenic (they are represenrepresented in blue color)

and wild lines (red color). The differentproperties of the discriminative masses

(represented in blue and red in the loading plot) are investigated with MassTRIX.

The model was built up with the data measured in negative mode.

Problem to be solved:Number of available samples

Publicaciones de nuestro grupo sobre GMOs-C. Simó, R. González, C. Barbas, A. CifuentesAnal. Chem. 77 (2005) 7709-7716 ---Proteomics

-M. Herrero, E. Ibáñez, P.J. Martin-Alvarez, A. Cifuentes Anal. Chem. 79 (2007) 5071-5077---Metabolomics

-T. Levandi, C. Leon, M. Kaljurand, V. Garcia-Cañas, A. CifuentesAnal. Chem. 80 (2008) 6329-6335 ---Metabolomics

- V. García-Cañas, M. Mondello, A. CifuentesElectrophoresis 31 (2010) 2249–2259 ---Genomics

-C. Leon, I. Rodriguez, M. Lucio, V. Garcia-Cañas, P. Schmitt-Kopplin, A. CifuentesJ. Chromatogr. A 1216 (2009) 7314-7323---Metabolomics

-C. Simó, E. Domínguez-Vega, M.L. Marina, M.C. García, G. Dinelli, A. Cifuentes Electrophoresis 31 (2010) 1175–1183---Proteomics

-V. García-Cañas, C. Simó, C. León, E. Ibáñez, A. Cifuentes Mass Spectrom. Rev. 30 (2011) 396– 416 –Proteomics + Metabolomics

Running Foodomics projects at our lab on

bioactivity of new functional ingredients on:

Alzheimer Colon cancer Leukemia

Population study

Biological sample:Cebrospinal fluid

(CSF)

Human cell lines

Biological samples:DNA, RNA,proteins andmetabolites

Human cell lines

Biological samples:DNA, RNA,proteins andmetabolites

In collaboration withKarolinska Institute(Stockholm, Sweden)

In collaboration withUniv. Miguel Hernandez, Elche, SpainUniversity of Granda, Granada, Spain

Diabetic children

Clinical trial

Biological samples:Urine and Plasma

In collaboration withGSF

(Munich, Germany)La Paz Hospital(Madrid, Spain)Univ. CEU-SP(Madrid, Spain)

Foodomics is a suitable approach to solve new

challenges in Food Science and Nutrition…

GENERAL CONCLUSION

CHAIRMAN: Alejandro Cifuentes (National Research Council of Spain, CSIC, Spain)CO-CHAIRMAN: Javier Hernández-Borges (University of La Laguna, Tenerife, Spain)

20th International Symposium on Electro- and Liquid-Phase Separation Techniques

6-9 October, 2013

Thank you!