Metabolic phenotyping of maize stem extracts using DIESI-MS

Supervisor: Dr. Axel TiessenLab Metabolomics & Molecular Physiology

Irapuato, Gto., January 23, 2013

1st. National Workshop on Fodder Maize

MC Martín García Flores

“Metabolic phenotyping of maize stem extracts

using DIESI-MS”

Outline

• Introduction– Forage maize– Genotype-Phenotype dilemma

• Experimental strategy and Methods– Workflow Metabolomics– Harvesting and sample prep– Mass spectrometry (DIESI-MS)

• Control experiments• Results

– Spectral comparisons, heatmaps

Forage production

http://www.siap.gob.mx/ 22/01/2013

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Phenotype dilemma

Genotype

Phenotype

Environment

DNA

BiomassGrain Yield

Agronomy

Tiessen, 2009

Genotype

• Genetic information• DNA (Nuclear. Mit, Chl)

• Sequence (Base order)

• Unique identity• Variety, Species, Genus

Epi-genotypeHeredable modificationsMethylationHistone-AcetylationmicroRNAs, etcProtein-states, etc

Phenotype

• Measurable characteristics• Agronomic traits• Morphological traits• Physiological traits• Biochemical traits• Depends on both Gen,Env, and Gen x Env

Phenotype dilemma

Genes

Proteins

Metabolites

Genotype

Phenotype

Environment

RNA

DNA

Activity

BiomassGrain Yield

Translation

Transcription

GrowthDevelopmentPartitioning

Epigenetic modifications

Photosynthesis

Signal transduction

Physiology

Agronomy

Tiessen, 2009

Metabolomics• Characterization, identification and

quantification of all metabolites

• Functional genomics (function of genes)• Physiology• Phenotyping, Breeding• QTL analysis

• Metabolic Engineering

ThroughputAnalytic methods:• HPLC-DAD (20 sa/day)• GC-FID (30 sa/day)• GC-EI-MS (18 sa/day)

• DIESI-MS (80 sa/day)

• Enzymatic and colorimetric assays (384 sa/day)

High through-put.Sample pre-treatment.Omitted fractioning and separation.Reduction of analysis time.Minimizes influence of sample manipulation.Brings down costs.

Typical workflow in Metabolomics

Koek et al., 2011

Biological questionsWhat is the function of the stem in the maize plant?

Which metabolites change under different field conditions?

Experimental design (Lattice)

Texcoco: 11 Genotypes, 6 biological samples, 3 technical samples (Low Nitrogen and Normal Nitrogen)

Tlaltizapan:14 Genotypes, 6 biological samples, 3 technical samples (Water stress and Well watered)

Genetic materialCIMMYT; experimental fields

Texcoco: Low Nitrogen Tlaltizapan: Water Stress

Entry Pedigree

1 H-55

6 HID-15

8 CMT 099001 (CML457/CHWE235)//CHWE231

4 P1684

*9 CMT 099003 (CML457/CHWL147)//CHWE229 (NN)

7 (CML457/CML459)//IML-6

5 ASPROS-823

2 H-57

11 TESTIGO LOCAL#!

10 CMT 099027 (CML457/CHWE235)//CHWE233

*3 CV-702 (LN)

Entry Pedigree

*8 DTPYC9-F143-5-4-1-2-B*5/CML312SR (WW and WS)

20 DTPWC9-F24-2-3-1-1-B*5/CML312SR

26 CML323-BB/CML312SR

69 LaPostaSeqC7-F78-2-1-1-1-B*4/CML312SR

72 CML486-BB/CML312SR

87 CML311/MBRC3BcF95-2-2-1-B*7/CML312SR

89 LaPostaSeqC7-F96-1-2-1-3-B*4/CML312SR

104[[KILIMAST94A]-30/MSV-03-1-10-B-1-BB-1xP84c1F27-4-1-6-B-5-B]F8-3-2-2-

1xG16SeqC1F47-2-1-2-1-B*5-xP84c1F26-2-2-6-B-3-B]-3-1-B/CML395]-1-1-BB/CML312SR

125CML311xCML311/CML311xMBRC1BcF94-3-1-1-B*4-1-1-

B*7/CML312SR

132CLQ-RCWQ83=(CML146xCML150)-B-32-1-2-B-1-B*4/

CML312SR

143 CL02450Q/CML451QLocalCheckQPM2

147LaPostaSeqC7-F64-2-6-2-2-BB/

CML495=Check2IntermediateMaturity

91 DTPYC9-F69-3-5-1-1-B*4/CML312SR

99 LaPostaSeqC7-F64-2-6-2-2-BB/CML312SR

Sampling

Grounding and collection of extracted juice sample, 1 ml

Experimental field trial

Maize stem sampling

Physiological data recording

Freezing in 96-well microplates, dry ice for 30 s. and storaged in liquid “N”

(-80 °C).

Defreezing in ice bath for 1 hr

Centrifugate for 10 min, 4000 rpm, 4 °C.

Supernatant filtration: 0.45µm mesh PVDF, activated carbon treatment, 100

µL aliquotes in 96-well microplates

Freezing (-18 °C) before DIESI-MS

García-Flores et al., 2012

Sample preparation

Filter 0.45 µm mesh PVDF; 10 µL sample and 990 µL De-Ionizade H2O (1:100 dilution). Add 25 µL formic acid to 475 µL sample, mix 3 min and Read: DIESI-MS.

Data acquisition

García-Flores et al., 2012

DIESI ConditionsWater micromass Q/Z spectrometer

ES (+) source.Voltages: Capillary (Kv) 3.0 Temperatures. Cone (V) 60 source ·C 80 Extractor (V) 3 desolvation ·C 150 Rf lens (V) 0.5

Gas flow.Desolvation (L/hr) 250Cone (L/hr) 50

Syringe.Pump flow (µl/min) 10

Analyzer.LM resolution 15HM resolution 15Ion energy 0.5Multiplier 650

Direct infusion electron spray ionization mass spectrometry (DIESI-MS).

Waters micromass (Z/Q).

Mass spectrometer (m/z).

Mass Spectrometer components

Warwick, 2007

Electrospray ionization

Martín, 2012

Capillary column, small quantities of sample,continuos flow, vacuum interlock. Electro-ionization.

Data processing

TOPPAS Software

Data acquisition and spectrum analysis

Input files

Output files

Output files

Output files

Output files

File Convert

er

Spectra Merger

NoiseFiltersgolay

TextExporter

File Convert

er

Peak Picker

wavelet

Winkler, 2011

Data processing

Average of 6 spectra

Control experiments

Default machine peaks

Top Peak: (m/z) 43.26, Intensity: 217896000

Top Peak: (m/z) 29.62, Intensity: 8164352

Solvent Water

CLQ-RCWQ83=(CML146xCML150)-B-32-1-2-B-1-B*4/CML312SR

Tlaltizapan

Drought stress (SS)

Deinonized Water

Formic acid

DilutionsGreen: 1:100

Red: 1:1000

Blue: 1:10000

Peak discrimination

Aminoacid (M.W.)+H Arginine 175.01

Asparagine 133.00

Glutamine 147.06

Proline 116.06

Serine 106.04

Tryptophan 205.08

Threonine 120.05

Tyrosine 182.07

Leucine 132.17

Metabolites of interest

Lysine

Mass positive: 147.10

C6H14N2O2

Fragments

m/z intensity

147.14 6 600 192

Lysine

LysineLysine

REP 1

REP 2 REP 3

Valine

Valine: (m/z) 118.08

Solvent Peak: (m/z) 43.32

AAs:Most common signals

m/z Histidine Isoleucine Lysine Methionine Valine Serine Threonine Cysteine Tryptophan Phenylalanine

39.451 6.89E+06 5.09E+06 7.55E+06 1.47E+07 4.76E+06 7.01E+06 5.74E+06 7.44E+06 2.10E+06 5.97E+06

47.4482 3.93E+08 3.97E+08 4.83E+08 4.05E+08 4.32E+08 4.92E+08 4.45E+08 4.20E+08 3.74E+08 3.88E+08

48.5103 8.85E+06 6.08E+06 2.22E+07 6.85E+06 1.68E+07 2.18E+07 1.74E+07 1.42E+07 6.08E+06 6.05E+06

59.3195 8.44E+07 3.48E+07 4.29E+07 3.59E+07 3.75E+07 4.59E+07 3.74E+07 3.05E+07 3.13E+07 2.80E+0661.3814 3.13E+07 1.77E+07 2.18E+07 2.23E+07 2.00E+07 2.45E+07 2.12E+07 1.80E+07 1.59E+07 1.59E+0769.1918 6.18E+06 4.37E+06 1.39E+07 1.04E+07 8.09E+06 1.59E+07 8.23E+06 8.84E+06 3.50E+06 4.97E+06

75.1904 3.86E+07 2.27E+08 4.37E+07 1.77E+08 5.75E+07 6.10E+07 1.75E+08 1.50E+08 2.18E+08 1.68E+0889.0626 1.53E+07 1.05E+07 1.11E+07 1.15E+07 1.06E+07 1.29E+07 1.20E+07 1.01E+07 9.94E+06 9.92E+0689.9376 1.52E+06 7.38E+05 1.09E+06 1.63E+06 8.09E+05 1.04E+06 9.51E+05 8.96E+05 6.84E+05 6.83E+0593.0619 5.30E+08 5.98E+08 6.49E+08 6.03E+08 6.14E+08 6.82E+08 6.42E+08 6.27E+08 5.85E+08 5.86E+0894.3742 2.53E+07 3.12E+07 3.86E+07 3.52E+07 3.25E+07 4.27E+07 3.97E+07 3.53E+07 3.07E+07 3.00E+0797.1238 4.59E+06 3.34E+07 4.33E+06 4.98E+07 7.11E+06 8.88E+06 2.97E+07 3.40E+07 2.90E+07 2.83E+07

101.1232 5.28E+07 4.13E+07 3.48E+07 4.55E+07 3.90E+07 4.56E+07 4.55E+07 3.84E+07 3.92E+07 3.71E+07102.873 4.02E+06 2.57E+06 2.70E+06 3.09E+06 2.58E+06 3.09E+06 3.43E+06 2.54E+06 2.73E+06 2.44E+06

105.0602 1.93E+07 1.16E+07 1.10E+07 1.31E+07 1.08E+07 1.04E+07 1.30E+07 1.18E+07 1.15E+07 1.07E+07107.2475 1.19E+07 8.35E+06 9.39E+06 9.74E+06 8.45E+06 1.10E+07 9.67E+06 8.48E+06 8.01E+06 7.38E+06117.1841 6.74E+07 5.23E+07 4.31E+07 6.18E+07 4.40E+07 5.64E+07 5.94E+07 4.86E+07 5.14E+07 4.79E+07121.0588 1.07E+07 1.35E+08 1.03E+07 1.13E+08 2.21E+07 2.02E+07 1.02E+08 9.64E+07 1.40E+08 1.05E+08131.9958 1.70E+06 6.48E+07 1.10E+06 2.60E+06 9.43E+05 1.07E+06 1.02E+06 9.49E+05 8.62E+05 0.00E+00171.0599 1.05E+07 8.64E+06 1.83E+07 1.29E+07 6.67E+06 1.72E+07 1.29E+07 1.22E+07 9.88E+06 7.95E+06191.9376 1.33E+07 2.13E+07 1.50E+07 1.66E+07 2.75E+07 2.59E+07 2.31E+07 1.96E+07 1.82E+07 2.01E+07238.0731 7.07E+06 1.62E+07 1.01E+07 1.35E+07 1.93E+07 1.88E+07 1.86E+07 1.78E+07 1.47E+07 1.64E+07

HigherLower

AAs most common signals Plot

39.4

5

47.4

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48.5

1

59.3

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69.1

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75.1

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94.3

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101.

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87

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C1

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C10

Intensity

m/z

AAs

AAs Surface Plot

0.00E+00-2.00E+08 2.00E+08-4.00E+08 4.00E+08-6.00E+08 6.00E+08-8.00E+08

PheTryCysThrSerValMetLysIsoHis

C1C2C3C4C5C6C7C8C9C10

0.00E+00

1.00E+08

2.00E+08

3.00E+08

4.00E+08

5.00E+08

6.00E+08

7.00E+08

Int

m/z

AAs

AAs Surface Plot

0.00E+00-1.00E+08 1.00E+08-2.00E+08 2.00E+08-3.00E+083.00E+08-4.00E+08 4.00E+08-5.00E+08 5.00E+08-6.00E+086.00E+08-7.00E+08

PheTryCysThrSerValMetLysIsoHis

Excel 2003

AA’s fragments Summary AA Ionize Intensity FragmentsHistidine Low 56 452 120.08, 121.09, 123.06

Glutamic acid Low 2 749 184 112.88, 114.09, 130.90

Aspartic acid Low 3 822 336 99.03, 101.03, 117.03

Isoleucine Standard 13 760 512 98.09, 99.09, 115.98

Arginine Low 3 046 144 139.97, 140.98, 157.97

Lysine Standard 6 600 192 112.19, 113.16, 130.16

Alanine High-quality 134 176 768 75.50, 87.43, 89.50

Methionine Low 3 736 320 115.91, 116.92, 132.87

Glutamine High-quality 94 728 192 128.83, 129.87, 147.06

Valine Standard 11 805 696 101.07, 116.03, 117.06

Serine High-quality 63 971 328 102.99, 103.99, 104.99

Threonine High-quality 64 405 504 102.96, 117.94, 118.85

Asparagine Low 6 648 576 111.88, 112.88, 115.85

Tyrosine Low 2 569 472 148.92, 162.94, 164.88

Cysteine Standard 19 729 408 101.98, 102.96, 104.90

Proline Standard 13 458 432 100.20, 115.11, 232.15

Glycine High-quality 103 301 120 75.43, 151.06, 226.17

Tryptophan Low 897 216 170.11, 172.09, 188.06

Phenylalanine Low 4 782 336 130.90, 146.92, 162.94

Leucine High-quality 3 208 960 100.17, 117.32, 131.40

Results

García-Flores et al., 2012

Results DIESI-MS spectrum

Comparison

¿Which MS peaks vary according to the environmental conditions?

Comparison of spectra

CLQ-RCWQ83=(CML146xCML150)-B-32-1-2-B-1-B*4/CML312SR

Tlaltizapan

Control (WW)

Drought stress (SS)

CLQ-RCWQ83=(CML146xCML150)-B-32-1-2-B-1-B*4/CML312SR

Tlaltizapan

Control (WW)

Drought stress (SS)

Control-Low nitrogen spectra

Control (NN)

CV-702 Batan

Low Nitrogen

CV-702 HL Batan

Control (NN)

Low Nitrogen

Can we use the MS info for classifying samples?

Statistical analysis with R

ANOVA analysisHerarchical clusteringHeatmap bicluster

Metabolic HeatMap

Evaluating the physiological state of maize (Zea mays L.) plants by direct-injection electrospray mass

spectrometry (DIESI-MS).Martín García Flores; Sheila Juárez Colunga; Josaphat Miguel Montero Vargas; Janet

Ana Isabel López Arciniéga; Alicia Chagoya; Axel Tiessen and Robert Winkler.

Molecular Biosystems García-Flores et al., 2012

ConclusionsDIESI-MS has high throughput. It is the cheapest and fastest MS strategy. We have successfully set up the method at CINVESTAV.

We can detect >200 of different ms peaks. We can measure more that 80 samples per day.

Some peaks vary acording to Gen and Env effects

Biochemical phenotyping of maize stem fluids enables the rapid evaluation of the physiological state of plants.

It also allows to discriminate between genotypes ( breeding)

Metabolic heatmaps are useful for MS data representation

Perspectives

The method will be applied at large scale for investigating the metabolic stress response of various Zea mays L. genotypes.

We hope we can detect biomarkers for selection

Derived metabolic markers can complement the DNA based markers for breeding.

Acknowledgments

• CIMMYT MasAgro-IMIC– Dr. Marc Rojas (IMIC)– Dr. Felix San Vicente (CIMMYT)

• CONACYT Grants• Dr. Axel and Dr. Robert

• Laboratory team: Mayela, Andrés, Adrián, Erandi, Sheila, Obed, Iván, Julio, Viviana, Daniel, etc

LaboratoryMetabolomics & Molecular Physiology

Questions?Many thanks for

being here.

CINVESTAV IRAPUATO

Plant Biotechnology