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GeorgiiMetaboLightsPublicDirect infusion MS -Gas Chromatography MS -<p><strong>FT-ICR-MS:</strong></p><p>A Solarix FT-ICR mass spectrometer (Bruker Daltonics, Bremen, Germany) coupled to a 12 Tesla magnet (Magnex, UK) was used for the experimental study. The electrospray ionization source (Apollo II, Bruker Daltonics, Bremen, Germany) was used in the negative ionization mode to ionize the studied analytes in 50% methanolic solution (Lichrosolv, Sigma-Aldrich, Schnelldorf, Germany). The sample solutions were injected directly to the ionization source by the use of a microliter pump at a flow rate of 2 µL/min. A source heater temperature of 200 °C was maintained and no nozzle – skimmer fragmentation was performed in the ionization source. The instrument was previously calibrated by the use of Arginine negative cluster ions starting from a methanolic arginine solution of 5 mg/L. Ions were accumulated in the collision cell for 300 ms for thermalization and enrichment prior to ICR ion detection. The base pressure in the ICR vacuum chamber was 7 x 10^-10 mbar and in the quadrupole and hexapole regions 3 x 10^-6 mbar. High pressure in the quadrupole and hexapole regions is necessary to co-linearize the ions in the radial plane and decelerate the radial components of the ion kinetic energy. 300 scans were accumulated for each mass spectrum. The instrumental mass range m/z 147-1000 amu was scanned.</p><p><br></p><p><strong>GC-TOF-MS:</strong></p><p>The transfer line, connecting the GC and the TOF-MS, was set to 250 °C as well as the ion source where the instreaming metabolites got ionized and fractionated by an ion pulse of 70 eV. Mass spectra were recorded at 20 scans/s with an m/z 35-800 scanning range using a LECO Pegasus HT TOFMS. Chromatograms and mass spectra were evaluated using ChromaTOF 4.5 and TagFinder 4.1 software<strong>[1]</strong>. There are 2 files for each sample, splitless (suffix '_SL') and split 10 (suffix '_Split'). Highly abundant metabolites (sugars, organic acids) were measured in split mode, and other metabolites in splitless mode. The sample naming is consistent with the processed files.</p><p><br></p><p><strong>Ref:</strong></p><p><strong>[1]</strong> Luedemann A, Strassburg K, Erban A, Kopka J. (2008) TagFinder for the quantitative analysis of gas chromatography - mass spectrometry (GC-MS)-based metabolite profiling experiments. Bioinformatics, 24, 732-737. DOI: 10.1093/bioinformatics/btn023.</p><p><strong>FT-ICR-MS:</strong></p><p>No chromatography was performed in this assay.</p><p><br></p><p><strong>GC-TOF-MS:</strong></p><p>A volume of 1 μL of each sample was injected into a GC-TOF-MS system (Pegasus HT, Leco, St Joseph, USA). Samples were derivatized and injected by an autosampler system (Combi PAL, CTC Analytics AG, Zwingen, Switzerland). Helium acted as carrier gas at a constant flow rate of 1 mL/min. Gas chromatography was performed on an Agilent GC (7890A, Agilent, Santa Clara, USA) using a 30 m VF-5ms column with 10 m EZ-Guard column. The injection temperature of the split/splitless injector (Agilent, Santa Clara, USA) was set to 250 °C. Transfer line and ion source were set to 250 °C. The initial oven temperature (70 °C) was permanently increased to a final temperature of 320 °C by 9 °C/min. To avoid solvent contaminations the solvent delay was set to 340 s. Metabolites that passed the column were released into the TOF-MS.</p>Relationships between drought, heat and air humidity responses revealed by transcriptome-metabolome co-analysis. 10.1186/s12870-017-1062-y. PMID:28693422Helmholtz Zentrum MünchenArabidopsis thalianamass spectrometry<p><strong>FT-ICR-MS (extraction):</strong></p><p>Samples were ground at 2500 rpm for 2.5 min using the mixer mill MM 400 (Retsch, Germany), and 100 mg powder used for metabolite extraction. Metabolite extraction was performed as described previously<strong>[1]</strong> with slight modifications. Briefly, 44 μg/mL loganin and 3 μg/mL nitrophenol were added to extraction buffer 1 (methanol/chloroform/H2O 2.5:1:1 v/v/v) as internal standards. Next 2 mL pre-cooled extraction buffer 1 (-20 °C) was added to 100 mg plant material and mixed at 4 °C for 30 min. After centrifugation (10 min, 14,000 rpm, 4 °C), 1 mL of the supernatant (supernatant A) was transferred into a fresh 2 mL Eppendorf tube and the remaining pellet was extracted in a second step with 1 mL pre-cooled (4 °C) extraction buffer 2 (methanol/chloroform 1:1 v/v). After a second centrifugation, 500 μL of the supernatant (supernatant B) were mixed with supernatant A. The chloroform phase was then separated from the water/methanol phase by addition of 250 μL of HPLC grade water (4 °C, Merck). The aqueous phase was divided into several 200 μL aliquots and dried completely using a Speed-Vac.</p><p><br></p><p><strong>GC-TOF-MS (extraction and derivatization):</strong></p><p>For the extraction ~100 mg plant material (fresh weight) was ground in 900 µL cold (-20 °C) 80% methanol containing 20 μL ribitol (0.2 mg/mL in water) and 10 μL 13C-sorbitol (0.2 mg/mL in water), which were added as internal standards for the quantification of metabolite abundances. After incubation at 70 °C for 15 min, the extract was centrifuged for 15 min at 25,000 x g. For further analysis, 50 μL of the supernatant was dried in vacuo. The pellet was resuspended in 10 μL of methoxyaminhydrochloride (20 mg/mL in pyridine) and derivatized for 90 min at 37 °C. After the addition of 20 µL of BSTFA (N,O-Bis[trimethylsilyl]trifluoroacetamide) containing 5 μL retention time standard mixture of linear alkanes (n-decane, n-dodecane, n-pentadecane, n-nonadecane, n-docosane, n-octacosane, n-dotriacontane), the mix was incubated at 37 °C for further 45 min<strong>[2][3][4]</strong>. </p><p><br></p><p><strong>Refs:</strong></p><p><strong>[1]</strong> Weckwerth, W., Wenzel, K., Fiehn, O. (2004) Process for the integrated extraction, identification and quantification of metabolites, proteins and RNA to reveal their co-regulation in biochemical networks. Proteomics 4(1), 78–83. doi:10.1016/j.biosystems.2005.05.017</p><p><strong>[2]</strong> Roessner U, Luedemann A, Brust D, Fiehn O, Linke T, Willmitzer L, Fernie AR. (2001) Metabolic profiling allows comprehensive phenotyping of genetically or environmentally modified plant systems. Plant Cell, 13, 11-29. doi: http://dx.doi.org/10.1105/tpc.13.1.11</p><p><strong>[3]</strong> Lisec J, Schauer N, Kopka J, Willmitzer L, Fernie AR. (2006) Gas chromatography mass spectrometry-based metabolite profiling in plants. Nature Protocols, 1, 387-396. DOI:10.1038/nprot.2006.59</p><p><strong>[4]</strong> Erban A, Schauer N, Fernie AR, Kopka J. (2007) Nonsupervised construction and application of mass spectral and retention time index libraries from time-of-flight gas chromatography-mass spectrometry metabolite profiles. Methods in Molecular Biology, 358,19-38. DOI:10.1007/978-1-59745-244-1_2</p>https://www.ebi.ac.uk/metabolights/MTBLS355Elisabeth Georgii. elisabeth.georgii@helmholtz-muenchen.de.Anton Schäffner. schaeffner@helmholtz-muenchen.de.<p><strong>FT-ICR-MS:</strong></p><p>The spectra were merged across samples with an error tolerance of 1 ppm. The intensities in each sample were normalized by total ion current (TIC). To focus on reliably detected masses, we selected the 663 masses detected in at least two thirds of the samples in at least one condition. The data were log2 transformed and corrected for experiment and measurement batch effects using the nlme package in R<strong>[1]</strong>. Missing values are marked as NA; they did not exceed the detection threshold of 5e^+05.</p><p><br></p><p><strong>GC-TOF-MS:</strong></p><p>The data were log2 transformed and corrected for experimental batch effect with the nlme package<strong>[1]</strong>.</p><p><br></p><p><strong>Ref:</strong></p><p><strong>[1]</strong> Pinheiro JC, Bates DM. (2000) Mixed-Effects Models in S and S-PLUS, Springer.</p>StimulusGenotype<p>The plants were grown on soil in climate simulation chambers with 11/13 h light/dark cycle (light 08:30 am to 07:30 pm), 200 μmol/m^2/s photosynthetic photon flux density, 22 °C air temperature and 0.79 kPa VPD, corresponding to 70% relative air humidity. 3-week-old plants were flooded with water up to 60% of the pot height for 15 min by an automatic flooding system. After flooding, the plants used for drought stress (D) and combined drought and heat stresses (DH) stopped being watered and the soil moisture was regularly monitored. When the soil water content dropped to approximately 20% of the initial water content after 1 week, heat stress (H) was applied to both well-watered plants and drought-treated plants, raising the temperature to 33 °C for 6 h from 11:00 am to 5:00 pm. For one set of plants, the absolute air humidity was kept unchanged during the temperature increase, resulting in 37% relative air humidity and 3.17 kPa VPD; this condition is labeled 'LrH' (low relative air humidity). For another set of plants, the heat treatments were done with supplemented air humidity at 84% relative air humidity, to maintain the VPD at 0.79 kPa; the condition is labeled 'HrH' (high relative air humidity). In total 5 replicates of each genotype were generated for each environmental scenario; they were randomly distributed in the chambers to exclude position effects. Each replicate consisted of 7 or 8 rosettes that were harvested after treatment, collected into plastic bags (4 oz. 118 mL, Whirl-Pak), immediately frozen in liquid nitrogen and stored at -80 °C until use. Samples from all conditions were harvested at the same time (within 15 min starting at 5:00 pm).</p>Metabolomicsstimulus or stress designgas chromatography-mass spectrometryuntargeted metabolitestargeted metabolitesgenotype designstimulus or stress designgas chromatography-mass spectrometryuntargeted metabolitestargeted metabolitesgenotype designrosette leaf<p><strong>FT-ICR-MS:</strong></p><p>Mapping of masses to putative metabolites was performed with MassTRIX<strong>[1]</strong> and ChemSpider<strong>[2]</strong> using the metabolism data sources ChEMBL, BioCyc, AraCyc, MassBank, KEGG and Golm Metabolome Database. </p><p><br></p><p><strong>GC-TOF-MS:</strong></p><p>Chromatograms and mass spectra were evaluated using ChromaTOF 4.5 and TagFinder 4.1 software<strong>[3]</strong>.</p><p><br></p><p><strong>Refs:</strong></p><p><strong>[1]</strong> Suhre K, Schmitt-Kopplin P. (2008) MassTRIX: mass translator into pathways. Nucleic Acids Research, 36, W481–W484. https://doi.org/10.1093/nar/gkn194</p><p><strong>[2]</strong> Pence HE, William A. (2010) ChemSpider: An Online Chemical Information Resource. J Chem Educ 87: 1123–1124. DOI: 10.1021/ed100697w </p><p><strong>[3]</strong> Luedemann A, Strassburg K, Erban A, Kopka J. (2008) TagFinder for the quantitative analysis of gas chromatography - mass spectrometry (GC-MS)-based metabolite profiling experiments. Bioinformatics, 24, 732-737. DOI: 10.1093/bioinformatics/</p>Benzoic acidProline (2TMS)Ascorbic acidSucroseGlucoheptoseMannoseGlucoseGlutaric acid, 3-oxo-ErythritolSpermidineAdenosine, 5-methylthio-Phosphoric acidThreonineSuccinyl-lactateMethionineGlycerolGlucosamine, N-acetyl-UreaRibonic acidLysineCysteine, N-acetyl-Galactosamine, N-acetyl-Trehalose-6-phosphateGlutamic acidThreonine, allo-Pyrrole-2-carboxylic acidGalactonic acidGlycineBenzoic acid, 2,5-dihydroxy-Butyric acid, 2-amino-, DL-ArginineN-CarboxyglycineGlycolic acidPyroglutamic acidXylulosePropane-1,3-diol, 2-amino-2-methyl-Pyruvic acid, 3-hydroxy-Trehalose, alpha,alpha'-, D-AlaninePhenylalanineLevulinic acidErythroseIsomaltoseTryptophanGalactinolAlanine, beta-Glucose-6-phosphateCitric acidValineAsparagineMannose-6-phosphateGlutaric acid, 2-oxo-Erythronic acidNicotinic acidProline, 4-hydroxy-, trans-GlyceraldehydeRibose-5-phosphateDehydroascorbic acid dimerShikimic acidGlycerophosphoglycerolGlucuronic acid-3,6-lactoneInositol, myo-Maleic acidMalic acidSuccinic semialdehydeCytosineGlyceric acidSalicylic acid-glucopyranoside1,3-DihydroxyacetonGluconic acidThreoseMaltoseXyloseLyxonic acid-1,4-lactoneArabitolN-methyl trans-4-hydroxy-L-prolineSuccinic acidOrnithineGlutaric acid, 3-hydroxy-3-methyl-beta-D-Galactopyranoside, 1-isopropyl-, 1-thio-Malonic acidCysteineSerineMannopyranoside, 1-O-methyl-, alpha-Nicotinic acid, 6-hydroxy-Lyxonic acidHydroxyureaButanoic acid, 2,4-dihydroxy-PutrescineLeucineOxamideGlutamine, DL-Malic acid, 2-methyl-ArabinoseRibosePhosphoric acid monomethyl esterAspartic acidIsoleucineEthanolamineValeric acid, 2-oxo-Lactic acid, 3-phenyl-AdenineThreonic acidUric acidTartaric acidFructosePropanoic acid, 2-amino-2-methyl-3-hydroxy-Glycerol-2-phosphateXylitolFumaric acidButyric acid, 2,4-diamino-, DL-Homocysteine<h4>Background</h4>Elevated temperature and reduced water availability are frequently linked abiotic stresses that may provoke distinct as well as interacting molecular responses. Based on non-targeted metabolomic and transcriptomic measurements from Arabidopsis rosettes, this study aims at a systematic elucidation of relevant components in different drought and heat scenarios as well as relationships between molecular players of stress response.<h4>Results</h4>In combined drought-heat stress, the majority of single stress responses are maintained. However, interaction effects between drought and heat can be discovered as well; these relate to protein folding, flavonoid biosynthesis and growth inhibition, which are enhanced, reduced or specifically induced in combined stress, respectively. Heat stress experiments with and without supplementation of air humidity for maintenance of vapor pressure deficit suggest that decreased relative air humidity due to elevated temperature is an important component of heat stress, specifically being responsible for hormone-related responses to water deprivation. Remarkably, this "dry air effect" is the primary trigger of the metabolomic response to heat. In contrast, the transcriptomic response has a substantial temperature component exceeding the dry air component and including up-regulation of many transcription factors and protein folding-related genes. Data level integration independent of prior knowledge on pathways and condition labels reveals shared drought and heat responses between transcriptome and metabolome, biomarker candidates and co-regulation between genes and metabolic compounds, suggesting novel players in abiotic stress response pathways.<h4>Conclusions</h4>Drought and heat stress interact both at transcript and at metabolite response level. A comprehensive, non-targeted view of this interaction as well as non-interacting processes is important to be taken into account when improving tolerance to abiotic stresses in breeding programs. Transcriptome and metabolome may respond with different extent to individual stress components. Their contrasting behavior in response to temperature stress highlights that the protein folding machinery effectively shields the metabolism from stress. Disentangling the complex relationships between transcriptome and metabolome in response to stress is an enormous challenge. As demonstrated by case studies with supporting evidence from additional data, the large dataset provided in this study may assist in determining linked genetic and metabolic features as candidates for future mechanistic analyses.Relationships between drought, heat and air humidity responses revealed by transcriptome-metabolome co-analysis.Georgii Elisabeth E, Jin Ming M, Zhao Jin J, Kanawati Basem B, Schmitt-Kopplin Philippe P, Albert Andreas A, Winkler J Barbro JB, Schäffner Anton R ARWater, other disease, Effects, plasma membrane intrinsic protein 2A, Metabonomic, A4, Metabonomics, Drought, Arabis thaliana, TYPE, Long Term, CG7826, CG11121, DAGA4, period, old, diseases, DmelCG11121, Hot, CG7835, 1, disease or disorder, CG42273, Heat, diseases and disorders, Min, Metabolomic, MAM, SCG3, Effect, DmelCG42273, Vapor, portion of tissue, human disease, somda, reference sample, Longterm, Tissue, uniform, Vapor Pressures, min, mAPC, plants, Long-Term, SO, Genotypes, non-neoplastic, AI047805, PLASMA MEMBRANE INTRINSIC PROTEIN 2, thale-cress, Humidities, disorder, Homo sapiens disease, Long-Term Effect, Controlled., ICR, Long-Term Effects, So, Controlled, Drl, Water Channel Protein, constant, Controlling, DYRK1, Arbisopsis thaliana, land plants, Proteins, disorders, Longterm Effect, Dmel_CG7826, Columbia-0, function, medical condition, Mdu, LGMD2C, Experiment, Channel, Temperatures, Genogroup, Dm1, mda, Channel Proteins, Pressure, Protein, Long Term Effects, tissue portion, Arabidopsis thaliana (thale cress), condition, simple tissue, Dyrk1, Channel Protein, ami, Dmel_CG7835, Aquaporin, PIP2, thale cress, Mnb, MNB, mouse-ear cress, AU020952, Temperature, Water Channels, DMDA1, med, Channels, CC1, Water Channel Proteins, Plant, AW124434, OAF2, Longterm Effects, ME-IV, Genogroups, disease, higher plants, DMDA, SCARMD2, Water Channel, Hot Temperatures, timethale cress, mouse-ear cress, portion of tissue, somda, simple tissue., Arbisopsis thaliana, med, land plants, Tissue, Metabonomic, Plant, Metabonomics, plants, SO, Arabis thaliana, Mdu, CG11121, thale-cress, higher plants, old, DmelCG11121, mda, tissue portion, Arabidopsis thaliana (thale cress), Metabolomic, ami, So, DrlWater, projections, extent, biochemical pathways, Metabolic Process, Materials, Globular Protein Folding, A., postnatal development, Metabolic Concepts, Metabonomic, Mbp1, Gene Expression Profile, Metabonomics, growth and development, Profiles, beta-tubulin folding, Drought, Cardaminopsis, flavonoid formation, primary metabolites, Arabidopsis thalianas, diseases, Hot, A. thalianas, responsivity, Concepts, Heat, diseases and disorders, Metabolism Concept, Phenomenon, myd, present in fewer numbers in organism, hereditary., Metabolic Profiles, human disease, availability, rya-r44F, catabolism, Mouse-ear Cress, hypoplasia, Vapor Pressures, Mbp-1, metabolic process resulting in cell growth, elevated, behavioral response to stimulus, Signatures, Mouse-ear, Folding, endocrine, Rya-R44F, genetic, chaperonin-mediated tubulin folding, decreased, dehydrated, CG10844, Expression Signature, papilla, dya, Transcriptomes, biotransformation, Homo sapiens disease, Arabidopses, Catabolism, single-organism behavior, anatomical protrusion, Data Set, Process, completeness, gyltl1b-b, metabolism resulting in cell growth, Expression Profiles, lamina, familial, Up-Regulation (Physiology), flanges, A. thaliana, INSDC_feature:misc_RNA, results, Acceptance Processes, Programs, chaperone activity, Gene Expression, Acceptance Process, Globular Protein, co-chaperonin activity, MDDGA6, Expression Signatures, mKIAA0609, shelf, Genetic Materials, alpha-tubulin folding, secretion, Protein Foldings, Expression Profile, Genetic Material, Hydrogen Oxide, Transcriptome Profiles, fg, Epistemology, Factors, gyltl1b, growth pattern, RyR, Upregulation, non-developmental growth, shelves, mdc1d, expanded, projection, ridge, disease, MDC1D, Arabidopsis, co-chaperone activity, Globular Protein Foldings, enr, Breedings, enlarged, RYR, Ryr, Material, spine, metabolites, response to biotic stress, multichaperone pathway, Hot Temperatures, Cistron, inherited genetic, flavonoid synthesis, big, other disease, ryr, Transcriptome Profile, lamellae, Processes, Foldings, secondary metabolites, Gene, flavonoid anabolism, Metabolic Processes, Transcription Factor, process of organ, froggy, Gyltl1a, protrusion, lamella, large, reduced, subnumerary, chaperonin ATPase activity, Metabolism, Water Deprivations, RyRs, thalianas, disease or disorder, non-chaperonin molecular chaperone ATPase activity, glycoprotein-specific chaperone activity, tiny, Metabolomic, Globular, Metabolic Profile, Metabolism Phenomena, Vapor, study, reactivity, Transcription, hormones, Genetic, Cresses, Receptor Up-Regulation, Metabolomes, MDDGB6, Profile, Up Regulation, response to heat shock, Metabolic Concept, ridges, decreased number, Maintenances, non-neoplastic, Deprivation, BPFD#36, great, Protein Folding, Humidities, disorder, Cress, DmelCG10844, Deprivations, Mouse ear, Behaviors, laminae, constitutitional genetic, high elevation, flavonoid biosynthesis, behaviour, small, data, DRR, Transcriptome, DRY, degradation, anatomical process, Arabidopsis thaliana, disorders, Factor, medical condition, Cistrons, Concept, Metabolic Phenomena, development, Metabolism Concepts, Temperatures, dry, Pressure, Protein, Gene Expression Signatures, Phenomena, condition, Gene Expression Signature, background, protein complex assembly, metabolism, flange, organ process, Metabolic Phenomenon, Temperature, Acceptance, multicellular organism metabolic process, l(2)k00424, distinct, dRyR, biodegradation, underdeveloped, Metabolic, postnatal growth, thaliana, metabolite, Mouse-ear Cresses, introduction, processes, process, l(2)k04913, single-organism metabolic process, behavioural response to stimulus, Gene Expression Profiles, processus, response to abiotic stress, regulation, response, Signature, growth, Rya-r76CD, AnabolismTemperature, Transcriptome, Metabolic, determination, Transcriptome Profile, Metabolomes, Profile, Expression Profiles, Gene Expression Profile, chemical analysis., Gene, Profiles, Drought, Signatures, Gene Expression, Temperatures, Expression Signature, Gene Expression Profiles, Hot, Expression Signatures, Humidities, Gene Expression Signatures, Transcriptomes, Heat, Hot Temperatures, Gene Expression Signature, assay, Signature, Expression Profile, Metabolic Profile, Transcriptome Profiles, Metabolic Profiles0.00.00.00.00.00trueNontargeted and targeted metabolomics measurements of abiotic stress responses in three-week-old Arabidopsis thaliana plants' rosette leaf tissueNontargeted and targeted metabolomics measurements of abiotic stress responses in three-week-old Arabidopsis thaliana plants' rosette leaf tissue for Col-0 wild type plants and double/triple knockout mutants of aquaporins (pip2;1 pip2;2 and pip2;1 pip2;2 pip2;4) treated with drought, heat at different air humidities, or combined drought-heat stress at different air humidities. This experiment contains FT-ICR-MS measurements for 103 Arabidopsis thaliana rosette leaf samples covering three genotypes under six different environmental conditions. The three genotypes comprise the Col-0 wildtype and two loss-of-function mutants of aquaporins, a pip2;1 pip2;2 double mutant and a pip2;1 pip2;2 pip2;4 triple mutant (respective AGI locus identifiers: AT3G53420, AT2G37170, AT5G60660). The six conditions include control condition (well-watered, 22 °C, 70% relative air humidity), drought stress (one week without watering), heat stress without changing the absolute humidity of the ambient air (6 hours at 33 °C, 37% relative air humidity), heat stress with supplemented air humidity to maintain a constant vapor pressure deficit before and during the heat episode (6 hours at 33 °C, 84% relative air humidity), and the combinations of drought pretreatment with each of the two heat stress variants (one week of drought followed by 6 hours of heat stress). Samples from all conditions were harvested at the same time (within 15 min starting at 5 pm). For validation, GC-TOF-MS measurements were done for two genotypes (wildtype, double mutant) and two conditions (drought, control) on partially overlapping samples.2017-07-172016-06-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:27897CHEBI:28189CHEBI:24266CHEBI:16119CHEBI:15428CHEBI:15674CHEBI:18268CHEBI:16000CHEBI:44423CHEBI:86348CHEBI:18300CHEBI:22599CHEBI:61448CHEBI:24898CHEBI:33946CHEBI:33947CHEBI:30794CHEBI:48248CHEBI:33942CHEBI:26271CHEBI:15940CHEBI:5457CHEBI:18257CHEBI:16199CHEBI:33033CHEBI:18012CHEBI:64307CHEBI:132138CHEBI:59640CHEBI:30841CHEBI:27353CHEBI:29016CHEBI:28044CHEBI:14314CHEBI:6650CHEBI:17306CHEBI:17799CHEBI:5445CHEBI:28718CHEBI:17151CHEBI:17270CHEBI:20392CHEBI:78679CHEBI:35621CHEBI:16449CHEBI:16610CHEBI:17822CHEBI:22605CHEBI:18237CHEBI:17148CHEBI:37654CHEBI:17268CHEBI:28300CHEBI:16958CHEBI:30746CHEBI:15356CHEBI:17775CHEBI:87757CHEBI:16168CHEBI:18222CHEBI:90765CHEBI:17497CHEBI:16040CHEBI:28939CHEBI:26078CHEBI:33508CHEBI:340824CHEBI:16708CHEBI:30915CHEBI:43943CHEBI:15741CHEBI:16831CHEBI:87766CHEBI:16551CHEBI:15584CHEBI:25017CHEBI:26986CHEBI:616988CHEBI:26984CHEBI:28800CHEBI:22660CHEBI:33511CHEBI:17509CHEBI:30769CHEBI:16811CHEBI:25094CHEBI:17505CHEBI:37684CHEBI:134543CHEBI:134544CHEBI:17754CHEBI:17113CHEBI:17234CHEBI:16265CHEBI:991CHEBI:36751CHEBI:17992CHEBI:17230CHEBI:22652CHEBI:22653CHEBI:28757CHEBI:18283CHEBI:27266CHEBI:45630CHEBI:16016CHEBI:88950CHEBI:17189CHEBI:134539CHEBI:25998CHEBI:24149CHEBI:16010CHEBI:134538