Metabolite Databases for Plant Biotechnology Metabolomics approaches - PowerPoint PPT Presentation

Workshop Argentina-Japan “Bioscience and Biotechnology for the promotion of Agricutulure and Food Production – August 3 rd to 7 th 2009- Metabolite Databases for Plant Biotechnology Metabolomics approaches for Agro-Biotechnology Kazusa DNA Res Inst. Daisuke Shibata

Japan Chiba Prefecture State Government supports financially KDRI. Dep. Plant Genomics Dep. Human Genomics Dep. Biotechnology Kazusa DNA Research Institute (KDRI) KDRI KDRI

December 2000 Kazusa DNA Res. Inst. (Tabata’s lab) sequenced about 30Mb (28% Arabidopsis contribution) in the Arabidopsis thaliana genome sequencing of 116 Mb. KDRI KDRI

Plant-related Genome Sequencing at KDRI Synechocystis sp. strain PCC 6803 (1996) Photosynthetic Anabaena sp. PCC 7120 (2001) Bacteria Thermosynechococcus elongatus BP-1 (2002) Gloeobacter violaceus PCC7421 (2003) → Photosynthesis Mesorhizobium loti MAFF303099 (2000) Nitrogen- Bradyrhizobium japonicum USDA110 (2002) fixation Lotus japonicus (Legume) (2008) bacteria → Nitrogen fixation Plants Arabidopsis (Chromosome 3 &5) (2000) → Model plant Eucalyptus (for pulp) In progress Tomato (Chromosome 8) (2009) → Agricultural and industrial application

Metabolomics approaches in agricultural biotechnology Researches in the Japan Society for Bioscience, Biotechnology , and Agrochemistry are diverged ; Cop and vegetable breeding Fermentation Genetically modified crops Food production Wood utilization More,,,, “Metabolomics” approaches

High-through-put tools for metabolite analysis LC-IT-MS LC-MS UPLC-Q-TOF-MS UPLC-TOF-MS FT-IR GC-TOF-MS x 2 CE-MS x2 LC-FT/ICR-MS CE-MS GC-TOF-MS LC-IT-MS LC-FT-MS UPLC-MS # of analyzed ： > 80,000 at KDRI GPC-MALS LC-PDA x2

What is the problem? Carbon oxide, water & nutrients Primary metabolites (Common in plants) Secondary metabolites (Specific to each plant) >200,000 metabolites in the plant kingdom Is it possible to identify all?

Liquid Liquid Chromatography Fourier Transf Chromatography Fourier Transform orm Ion Cyclotron Resona Ion Cyclotron Resonance Ma nce Mass Spectrom ss Spectrometer eter LC – FT/ICR-MS Ultra-high mass accuracy, ~ 1 ppm Ultra-high mass accuracy, ~ 1 ppm Using internal standards 0.5~0.2 ppm Using internal standards 0.5~0.2 ppm Coupling LC prior to MS Coupling LC prior to MS Prevents ion suppression Prevents ion suppression allows UV/Vis spectrum acquisition allows UV/Vis spectrum acquisition Separates i Separates isomers somers LTQ-FT allows acquisition of Retention Time allows acquisition of Retention Time (Thermo Electron Co.) Magnetic field: 7 T RT information is useful RT information is useful to discriminate to discriminate isotopic ions isotopic ions adduct ions adduct ions spontaneously fragmented ions spontaneously fragmented ions Automated MS/MS acquisition Automated MS/MS acquisition LC-FT-Orbitrap-MS

Ultra-high mass accuracy measurement For example: 1ppm accuracy: m/z=500.0000 ± 0.0005 [M + H] + ＝ 410.0908 12 C = 12 13 C = 13.003355 1 H = 1.0078250319 C 18 H 19 O 8 NS 16 O = 15.9949146223 14 N = 14.0030740074 31 P = 30.973763 MS/MS 32 S = 31.972071 Structure Speculation

Speculation of Molecular Formula by FT-ICR-MS 12 C ＝ 12.000000 1 H=1.007825 、 14 N=14.003074 、 16 O=15.994915 433.11270 C 21 H 20 O 10 [+H] + 433.11270 C H O N S 21 21 10 0 0 433.112 7 2 3 3 13 25 12 2 1 433.112 2 7 1 4 11 13 2 16 1 433.112 2 6 0 8 14 29 7 2 3 433.113 1 3 9 8 11 21 1 12 3 433.111 7 9 1 8 ・ ・ ・ ・ ・ ・ ・ ・ ・ ・ ・ ・ Milli mass values give a limited number of formulas.

LC-FTICR-MS analysis of tomato fruit 3.38 TOM-RED #3204 RT: 21.36 AV: 1 NL: 2.70E5 microAU F: FTMS + c ESI Full ms [ 200.00- 2000.00] 290000 PDA 280000 270000 25000 260000 250000 240000 230000 220000 210000 200000 uAU 190000 20000 180000 170000 21.36 256.00 160000 356.00 150000 5.02 140000 3.13 130000 120000 15000 110000 540.00 554.00 580.00 608.00 640.00 100000 424.00 454.00 482.00 500.00 uAU 90000 250 300 350 400 450 500 550 600 650 wavelength (nm) 13.38 10000 2.83 40.06 24.02 0.10 5000 9.74 16.82 12.95 26.21 29.60 34.78 6.72 30.28 15.01 40.64 12.50 19.04 21.10 35.65 30.86 37.37 0 0 5 10 15 20 25 30 35 40 Time (min) (MS) n FT-full MS 303.09119 611.16063 100 100 OH 95 95 90 90 C 27 H 31 O 16 [M+H] + OH 85 85 80 80 1 75 75 HO O 70 70 Ref. MW=611.160659 65 65 OH 60 60 candidate HO Relative Abundance 55 O 55 ∆ mmu=0.03 OH O Relative Abundance 50 50 CH 2 OH O 45 45 1243.29956 40 40 63 O 35 35 464.90631 30 30 25 25 O candidates H 3 C 271.18848 20 20 Rutin HO 15 15 680.12244 1297.21826 HO 305.58121 OH 10 10 355.05716 1122.00220 763.10211 1395.23816 1828.67859 5 899.07928 5 385.39160 519.14050 1067.26428 1595.28479 267.17194 415.08997 576.66516 721.90173 792.68030 0 0 200 300 400 500 600 700 800 900 1000 1100 1200 200 400 600 800 1000 1200 1400 1600 1800 2000 m/z m/z MS/MS Fragmentation Metabolite UV absorption (PDA) Database

Annotation, but not identification Get all peak data m/z (>150,000 peaks) Data processing Giving chemical information Retention time to each metabolite (Metabolite Annotation)

Gene and Metabolite annotation Genomics Metabolomics Genomics Metabolomics Green # 965-17747 RT: 3.01-55.00 AV: 4196 NL: 2.22E5 T: FTMS + c ESI Full ms [ 98.00-1500.00] 578.40667 690.37457 1034.55654 27000 26000 25000 24000 23000 22000 21000 20000 294.26376 19000 18000 17000 16000 15000 14000 457.15625 13000 Intensity 12000 1092.56290 1100 0 416.35317 10000 9000 135.59411 8000 7000 636.41178 872.50475 740.46138 6000 5000 1122.57120 391.28404 918.50678 4000 325.11314 1457.31837 3000 827.26076 2000 1004.54375 1365.55024 1000 1221.31557 0 100 200 300 400 500 600 700 800 900 1000 1100 1200 1300 1400 1500 m/z Identify gene region Identify gene region Identify molecular ion Identify molecular ion DNA sequence DNA sequence m/z, MS m/z, MS n , Rt, , Rt, λ max max (Structural) Annotation (Structural) Annotation Coding protein Coding protein molecular fo molecular formula rmula Prediction of function, Homology search Prediction of function, Homology search Consistent identification of components across datasets Consistent identification of components across datasets Expression, GO Expression, GO (Functional) Annotation (Functional) Annotation Accumulation, Pathway Accumulation, Pathway

Comprehensive analysis of tomato metabolites Tissues Number of detected peaks Number of detected peaks Fruit 4 stages, 2 tissues ESI (Methanol fraction ） G Y O R 6000 6000 pos pos Peel (P), flesh (F) neg neg 5000 5000 Leaf, Root, Flower 4000 4000 Extraction 3000 3000 70% methanol 100% chloroform 2000 2000 1000 1000 LC C18, C30 Ionization ESI (positive, negative) 0 0 GP GP GF GF YP YP YF YF OP OP OF OF RP RP RF RF APPI (positive, negative) Green Green Yellow Yellow Orange Orange Red-ripe Red-ripe Iijima et al. (2008) Plant J.

How many metabolites ? 70% MeOH LC-ESI-based MS extraction Description of availability of supporting evidence Total: 869 non-redundant metabolites Including 494 metabolites not in the databases

Annotation of other metabolites Finished at molecular formula-level Approx. 5600 non-redundant peaks Checking candidate formulas, providing Evidences. Detected Ionization Formula GF GP YF YP OF OP RF RP Speculated 104.0704 Ep C4H9NO2 GABA 130.0498 Ep C5H7NO3 Pyroglutamic acid 134.0449 Ep C4H7NO4 Aspartic acid 138.0549 Ep C7H7NO2 p-Aminobenzoic acid 147.0765 Ep C5H10N2O3 glutamine 147.1128 Ep C6H14N2O2 L-Lysine 148.0605 Ep C5H9NO4 L-Glutamic acid 156.0768 Ep C6H9N3O2 L-Histidine 166.0863 Ep C9H11NO2 L-Phenylalanine 175.0966 Ep C8H14O4 Suberic acid 175.1190 Ep C6H14N4O2 L-arginine 189.1598 Ep C9H20N2O2 191.1026 Ep C7H14N2O4 meso-2,6-Diaminoheptanedioate 193.0344 Ep C6H8O7 citric acid 205.0971 Ep C11H12N2O2 Tryptophan 207.1128 Ep C11H14N2O2 12-Hydroxycytisine 212.0919 Ep C10H13NO4 219.1492 Ep C13H18N2O 230.0151 Ep C5H11NO5S2 245.0769 Ep C9H12N2O6 5-Ribosyluracil 251.0696 Ep C8H14N2O5S 251.1390 Ep C13H18N2O3 N-Caffeoylputrescine 261.0370 Ep C6H13O9P 263 1392 Ep C14H18N2O3 Iijima et al. (2008) Plant J.