1st. National Workshop on       Fodder Maize“Metabolic phenotyping of maize stem extracts    using DIESI-MS”           MC ...
Outline• Introduction  – Forage maize  – Genotype-Phenotype dilemma• Experimental strategy and Methods  – Workflow Metabol...
Forage production                                             2012 Year Forage production      1600000      1400000      1...
Average Yield                                                                           2012 year.                        ...
Phenotype dilemmaGenotype           DNA          Environment        AgronomyPhenotype  Biomass  Grain Yield               ...
Genotype•   Genetic information•   DNA (Nuclear. Mit, Chl)   Epi-genotype                              Heredable modificat...
Phenotype•   Measurable characteristics•   Agronomic traits•   Morphological traits•   Physiological traits•   Biochemical...
Phenotype dilemmaGenotype                DNA            Genes                  Epigenetic                Transcription    ...
Metabolomics• Characterization, identification and  quantification of all metabolites     •   Functional genomics (functio...
ThroughputAnalytic methods:• HPLC-DAD (20 sa/day)• GC-FID (30 sa/day)• GC-EI-MS (18 sa/day)                               ...
Typical workflow in Metabolomics                          Koek et al., 2011
Biological questionsWhat is the function of the stem inthe maize plant?Which metabolites change underdifferent field condi...
Genetic material      CIMMYT; experimental fields      Texcoco: Low Nitrogen                                   Tlaltizapan...
Sampling             Experimental field trial              Maize stem sampling          Physiological data recording    Gr...
Sample preparationFilter 0.45 µm mesh PVDF; 10 µL sample and990 µL De-Ionizade H2O (1:100 dilution).Add 25 µL formic acid ...
Data acquisition      DIESI Conditions          Water micromass Q/Z          spectrometer     ES (+) source.              ...
Direct infusion electron spray ionization   mass spectrometry (DIESI-MS).        Waters micromass (Z/Q).                  ...
Mass Spectrometer components                   Warwick, 2007
Electrospray ionizationCapillary column, small quantities of sample,continuos flow, vacuum                    interlock. E...
Data processing     TOPPAS Software     Data acquisition and   Output                             files     spectrum analy...
Data processing     Average of 6 spectra
Control experiments
Default machine peaks        Top Peak: (m/z) 43.26, Intensity:                           Top Peak: (m/z) 29.62, Intensity:...
Deinonized WaterFormic acid
Peak discrimination                                  Green: 1:100                      Dilutions   Red:    1:1000         ...
Metabolites of interestAminoacid        (M.W.)+HArginine           175.01Asparagine         133.00Glutamine          147.0...
Lysine                 REP 1Fragments                                           Lysinem/z         intensity        C6H14N2...
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     Cystein...
AAs most common signals Plot                              AAs Surface Plot                                                ...
AA’s fragments SummaryAA               Ionize Intensity FragmentsHistidine          Low                56 452   120.08, 12...
Results
Results DIESI-MS spectrum                     García-Flores et al., 2012
Comparison¿Which MS peaks vary according to the environmental conditions?
Comparison of spectra                   Control (WW)                 Drought stress (SS)  CLQ-RCWQ83=(CML146xCML150)-B-32-...
Control(WW) Drought stress (SS)      CLQ-RCWQ83=(CML146xCML150)-B-32-1-2-B-1-B*4/CML312SR                            Tlalt...
Control-Low nitrogen spectra         Control (NN)         Low Nitrogen        CV-702   Batan
Control (NN)Low Nitrogen               CV-702 HL Batan
Can we use the MS info for  classifying samples?   Statistical analysis with R   ANOVA analysis   Herarchical clustering  ...
Metabolic HeatMap
Evaluating the physiological state of maize (Zea mays   L.) plants by direct-injection electrospray mass               spe...
ConclusionsDIESI-MS has high throughput. It is the cheapest andfastest MS strategy. We have successfully set up themethod ...
PerspectivesThe method will be applied at large scale forinvestigating the metabolic stress response of variousZea mays L....
Acknowledgments• CIMMYT MasAgro-IMIC  – Dr. Marc Rojas (IMIC)  – Dr. Felix San Vicente (CIMMYT)• CONACYT Grants• Dr. Axel ...
LaboratoryMetabolomics & Molecular Physiology
Questions?Many thanks for  being here.
CINVESTAV     IRAPUATO Plant Biotechnology
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Metabolic phenotyping of maize stem extracts using DIESI-MS

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Taller Nacional de Maiz Forrajero, 1er; Guanajuato (Mexico); 23 enero 2013

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Metabolic phenotyping of maize stem extracts using DIESI-MS

  1. 1. 1st. National Workshop on Fodder Maize“Metabolic phenotyping of maize stem extracts using DIESI-MS” MC Martín García Flores Supervisor: Dr. Axel Tiessen Lab Metabolomics & Molecular Physiology Irapuato, Gto., January 23, 2013
  2. 2. 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
  3. 3. Forage production 2012 Year Forage production 1600000 1400000 1200000 1000000Ton 800000 600000 400000 200000 0 QUERETARO AGUASCALIENTES PUEBLA MEXICO GUANAJUATO ZACATECAS CHIHUAHUA DURANGO COAHUILA JALISCO State http://www.siap.gob.mx/ 22/01/2013
  4. 4. Average Yield 2012 year. Yield maize 70 62 61 60 51 48 50 44 40 40 40 35Ton/ha 31 30 30 20 10 0 MEXICO GUERRERO HIDALGO DURANGO QUERETARO COAHUILA OAXACA GUANAJUATO AGUASCALIENTES BAJA CALIFORNIA SUR State http://www.siap.gob.mx/ 22/01/2013
  5. 5. Phenotype dilemmaGenotype DNA Environment AgronomyPhenotype Biomass Grain Yield Tiessen, 2009
  6. 6. Genotype• Genetic information• DNA (Nuclear. Mit, Chl) Epi-genotype Heredable modifications• Sequence (Base order) Methylation Histone-Acetylation• Unique identity microRNAs, etc• Variety, Species, Genus Protein-states, etc
  7. 7. Phenotype• Measurable characteristics• Agronomic traits• Morphological traits• Physiological traits• Biochemical traits• Depends on both Gen,Env, and Gen x Env
  8. 8. Phenotype dilemmaGenotype DNA Genes Epigenetic Transcription modifications Signal RNA transduction Environment Translation Agronomy Proteins Photosynthesis ActivityPhenotype Growth Development Partitioning Metabolites Biomass Physiology Grain Yield Tiessen, 2009
  9. 9. Metabolomics• Characterization, identification and quantification of all metabolites • Functional genomics (function of genes) • Physiology • Phenotyping, Breeding • QTL analysis • Metabolic Engineering
  10. 10. ThroughputAnalytic methods:• HPLC-DAD (20 sa/day)• GC-FID (30 sa/day)• GC-EI-MS (18 sa/day) High through-put. Sample pre-treatment.• DIESI-MS (80 sa/day) Omitted fractioning and separation. Reduction of analysis time. Minimizes influence of sample manipulation. Brings down costs.• Enzymatic and colorimetric assays (384 sa/day)
  11. 11. Typical workflow in Metabolomics Koek et al., 2011
  12. 12. Biological questionsWhat is the function of the stem inthe maize plant?Which metabolites change underdifferent field conditions?Experimental design (Lattice)Texcoco: 11 Genotypes, 6 biological samples, 3 technicalsamples (Low Nitrogen and Normal Nitrogen)Tlaltizapan:14 Genotypes, 6 biological samples, 3technical samples (Water stress and Well watered)
  13. 13. Genetic material CIMMYT; experimental fields Texcoco: Low Nitrogen Tlaltizapan: Water StressEntry Pedigree Entry Pedigree 1 H-55 *8 DTPYC9-F143-5-4-1-2-B*5/CML312SR (WW and WS) 6 HID-15 20 DTPWC9-F24-2-3-1-1-B*5/CML312SR 26 CML323-BB/CML312SR 8 CMT 099001 (CML457/CHWE235)//CHWE231 69 LaPostaSeqC7-F78-2-1-1-1-B*4/CML312SR 4 P1684 72 CML486-BB/CML312SR *9 CMT 099003 (CML457/CHWL147)//CHWE229 (NN) 87 CML311/MBRC3BcF95-2-2-1-B*7/CML312SR 7 (CML457/CML459)//IML-6 89 LaPostaSeqC7-F96-1-2-1-3-B*4/CML312SR 5 ASPROS-823 [[KILIMAST94A]-30/MSV-03-1-10-B-1-BB-1xP84c1F27-4-1-6-B-5-B]F8-3-2-2- 104 1xG16SeqC1F47-2-1-2-1-B*5-xP84c1F26-2-2-6-B-3-B]-3-1- 2 H-57 B/CML395]-1-1-BB/CML312SR CML311xCML311/CML311xMBRC1BcF94-3-1-1-B*4-1-1- 11 TESTIGO LOCAL#! 125 B*7/CML312SR 10 CMT 099027 (CML457/CHWE235)//CHWE233 CLQ-RCWQ83=(CML146xCML150)-B-32-1-2-B-1- 132 B*4/CML312SR *3 CV-702 (LN) 143 CL02450Q/CML451QLocalCheckQPM2 LaPostaSeqC7-F64-2-6-2-2- 147 BB/CML495=Check2IntermediateMaturity 91 DTPYC9-F69-3-5-1-1-B*4/CML312SR 99 LaPostaSeqC7-F64-2-6-2-2-BB/CML312SR
  14. 14. Sampling Experimental field trial Maize stem sampling Physiological data recording Grounding and collection of extracted juice sample, 1 ml Freezing in 96-well microplates, dry ice for 30 s. and storaged in liquid “N” (-80 °C).
  15. 15. Sample preparationFilter 0.45 µm mesh PVDF; 10 µL sample and990 µL De-Ionizade H2O (1:100 dilution).Add 25 µL formic acid to 475 µL sample, mix 3min and Read: DIESI-MS. 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
  16. 16. Data acquisition DIESI Conditions Water 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) 250 Cone (L/hr) 50 Syringe. Pump flow (µl/min) 10 Analyzer. LM resolution 15 HM resolution 15 Ion energy 0.5 Multiplier 650 García-Flores et al., 2012
  17. 17. Direct infusion electron spray ionization mass spectrometry (DIESI-MS). Waters micromass (Z/Q). Mass spectrometer (m/z).
  18. 18. Mass Spectrometer components Warwick, 2007
  19. 19. Electrospray ionizationCapillary column, small quantities of sample,continuos flow, vacuum interlock. Electro-ionization. Martín, 2012
  20. 20. Data processing TOPPAS Software Data acquisition and Output files spectrum analysisInput File Spectra NoiseFilt Output files Convert Merger ersgolay files er File PeakOutput Text Output Convert Picker files Exporter files er wavelet Winkler, 2011
  21. 21. Data processing Average of 6 spectra
  22. 22. Control experiments
  23. 23. Default machine peaks Top Peak: (m/z) 43.26, Intensity: Top Peak: (m/z) 29.62, Intensity: 217896000 8164352 Solvent WaterDrought stress (SS) CLQ-RCWQ83=(CML146xCML150)-B- 32-1-2-B-1-B*4/CML312SR Tlaltizapan
  24. 24. Deinonized WaterFormic acid
  25. 25. Peak discrimination Green: 1:100 Dilutions Red: 1:1000 Blue: 1:10000
  26. 26. Metabolites of interestAminoacid (M.W.)+HArginine 175.01Asparagine 133.00Glutamine 147.06Proline 116.06Serine 106.04Tryptophan 205.08Threonine 120.05Tyrosine 182.07Leucine 132.17
  27. 27. Lysine REP 1Fragments Lysinem/z intensity C6H14N2O2147.14 6 600 192Mass positive: 147.10 REP 2 REP 3 Lysine Lysine
  28. 28. Valine Valine: (m/z) 118.08 Solvent Peak: (m/z) 43.32
  29. 29. 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+06 61.3814 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+07 69.1918 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+08 89.0626 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+06 89.9376 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+05 93.0619 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+08 94.3742 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+07 97.1238 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+07101.1232 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+07 102.873 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+06105.0602 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 Higher Lower
  30. 30. AAs most common signals Plot AAs Surface Plot AAs Surface Plot Phe C10 7.00E+08 Phe Try C9 Try Cys 6.00E+08 C8 Cys Thr C7 Thr 5.00E+08 Ser Ser Val C6 4.00E+08 ValInt Met C5 Met 3.00E+08 Lys Lys Iso C4 2.00E+08 Iso C10 His C3 His C9 C8 1.00E+08 C7 C2 C6 C5 AAs 0.00E+00 C4 Intensity C1 AAs C3 C2 39.45 48.51 61.38 75.19 89.06 93.06 97.12 47.44 59.31 69.19 89.93 94.37 102.87 191.93 101.12 105.06 107.24 117.18 121.05 131.99 171.05 238.07 C1 m/z m/z 0.00E+00-1.00E+08 1.00E+08-2.00E+08 2.00E+08-3.00E+08 3.00E+08-4.00E+08 4.00E+08-5.00E+08 5.00E+08-6.00E+08 6.00E+08-7.00E+08 0.00E+00-2.00E+08 2.00E+08-4.00E+08 4.00E+08-6.00E+08 6.00E+08-8.00E+08 Excel 2003
  31. 31. AA’s fragments SummaryAA Ionize Intensity FragmentsHistidine Low 56 452 120.08, 121.09, 123.06Glutamic acid Low 2 749 184 112.88, 114.09, 130.90Aspartic acid Low 3 822 336 99.03, 101.03, 117.03Isoleucine Standard 13 760 512 98.09, 99.09, 115.98Arginine Low 3 046 144 139.97, 140.98, 157.97Lysine Standard 6 600 192 112.19, 113.16, 130.16Alanine High-quality 134 176 768 75.50, 87.43, 89.50Methionine Low 3 736 320 115.91, 116.92, 132.87Glutamine High-quality 94 728 192 128.83, 129.87, 147.06Valine Standard 11 805 696 101.07, 116.03, 117.06Serine High-quality 63 971 328 102.99, 103.99, 104.99Threonine High-quality 64 405 504 102.96, 117.94, 118.85Asparagine Low 6 648 576 111.88, 112.88, 115.85Tyrosine Low 2 569 472 148.92, 162.94, 164.88Cysteine Standard 19 729 408 101.98, 102.96, 104.90Proline Standard 13 458 432 100.20, 115.11, 232.15Glycine High-quality 103 301 120 75.43, 151.06, 226.17Tryptophan Low 897 216 170.11, 172.09, 188.06Phenylalanine Low 4 782 336 130.90, 146.92, 162.94Leucine High-quality 3 208 960 100.17, 117.32, 131.40
  32. 32. Results
  33. 33. Results DIESI-MS spectrum García-Flores et al., 2012
  34. 34. Comparison¿Which MS peaks vary according to the environmental conditions?
  35. 35. Comparison of spectra Control (WW) Drought stress (SS) CLQ-RCWQ83=(CML146xCML150)-B-32-1-2-B-1-B*4/CML312SR Tlaltizapan
  36. 36. Control(WW) Drought stress (SS) CLQ-RCWQ83=(CML146xCML150)-B-32-1-2-B-1-B*4/CML312SR Tlaltizapan
  37. 37. Control-Low nitrogen spectra Control (NN) Low Nitrogen CV-702 Batan
  38. 38. Control (NN)Low Nitrogen CV-702 HL Batan
  39. 39. Can we use the MS info for classifying samples? Statistical analysis with R ANOVA analysis Herarchical clustering Heatmap bicluster
  40. 40. Metabolic HeatMap
  41. 41. 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
  42. 42. ConclusionsDIESI-MS has high throughput. It is the cheapest andfastest MS strategy. We have successfully set up themethod at CINVESTAV.We can detect >200 of different ms peaks. We canmeasure more that 80 samples per day.Some peaks vary acording to Gen and Env effectsBiochemical phenotyping of maize stem fluids enablesthe rapid evaluation of the physiological state of plants.It also allows to discriminate between genotypes (breeding)Metabolic heatmaps are useful for MS datarepresentation
  43. 43. PerspectivesThe method will be applied at large scale forinvestigating the metabolic stress response of variousZea mays L. genotypes.We hope we can detect biomarkers for selectionDerived metabolic markers can complement the DNAbased markers for breeding.
  44. 44. 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
  45. 45. LaboratoryMetabolomics & Molecular Physiology
  46. 46. Questions?Many thanks for being here.
  47. 47. CINVESTAV IRAPUATO Plant Biotechnology

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