BioModelsapplication/xmlhttps://www.ebi.ac.uk/biomodels/model/download/MODEL1507180013?filename=MODEL1507180013.pdfhttps://www.ebi.ac.uk/biomodels/model/download/MODEL1507180013?filename=MODEL1507180013-biopax3.owlhttps://www.ebi.ac.uk/biomodels/model/download/MODEL1507180013?filename=MODEL1507180013-biopax2.owlhttps://www.ebi.ac.uk/biomodels/model/download/MODEL1507180013?filename=MODEL1507180013_urn.xmlhttps://www.ebi.ac.uk/biomodels/model/download/MODEL1507180013?filename=MODEL1507180013_url.xmlhttps://www.ebi.ac.uk/biomodels/model/download/MODEL1507180013?filename=MODEL1507180013.mhttps://www.ebi.ac.uk/biomodels/model/download/MODEL1507180013?filename=MODEL1507180013.pnghttps://www.ebi.ac.uk/biomodels/model/download/MODEL1507180013?filename=MODEL1507180013.scihttps://www.ebi.ac.uk/biomodels/model/download/MODEL1507180013?filename=MODEL1507180013.xpphttps://www.ebi.ac.uk/biomodels/model/download/MODEL1507180013?filename=MODEL1507180013.vcmlprimaryOK200Nicolas Le NovèreNon-curatedconstraint-based modelL3V1https://www.ebi.ac.uk/biomodels/MODEL150718001317573341falseBioModelsSBMLModelsOh2007 Genome scale metabolic network of Bacillus subtilis (iYO844)2007MODEL1507180013Non KineticOh YK, Palsson BO, Park SM, Schilling CH, Mahadevan ROh YK17573341,
In this report, a genome-scale reconstruction of Bacillus subtilis metabolism and its iterative development based on the combination of genomic, biochemical, and physiological information and high-throughput phenotyping experiments is presented. The initial reconstruction was converted into an in silico model and expanded in a four-step iterative fashion. First, network gap analysis was used to identify 48 missing reactions that are needed for growth but were not found in the genome annotation. Second, the computed growth rates under aerobic conditions were compared with high-throughput phenotypic screen data, and the initial in silico model could predict the outcomes qualitatively in 140 of 271 cases considered. Detailed analysis of the incorrect predictions resulted in the addition of 75 reactions to the initial reconstruction, and 200 of 271 cases were correctly computed. Third, in silico computations of the growth phenotypes of knock-out strains were found to be consistent with experimental observations in 720 of 766 cases evaluated. Fourth, the integrated analysis of the large-scale substrate utilization and gene essentiality data with the genome-scale metabolic model revealed the requirement of 80 specific enzymes (transport, 53; intracellular reactions, 27) that were not in the genome annotation. Subsequent sequence analysis resulted in the identification of genes that could be putatively assigned to 13 intracellular enzymes. The final reconstruction accounted for 844 open reading frames and consisted of 1020 metabolic reactions and 988 metabolites. Hence, the in silico model can be used to obtain experimentally verifiable hypothesis on the metabolic functions of various genes.. null, 282.
Department of Bioengineering, University of California at San Diego, La Jolla, California 92093-0412, USA.n.lenovere@gmail.comThe Babraham InstituteIn this report, a genome-scale reconstruction of Bacillus subtilis metabolism and its iterative development based on the combination of genomic, biochemical, and physiological information and high-throughput phenotyping experiments is presented. The initial reconstruction was converted into an in silico model and expanded in a four-step iterative fashion. First, network gap analysis was used to identify 48 missing reactions that are needed for growth but were not found in the genome annotation. Second, the computed growth rates under aerobic conditions were compared with high-throughput phenotypic screen data, and the initial in silico model could predict the outcomes qualitatively in 140 of 271 cases considered. Detailed analysis of the incorrect predictions resulted in the addition of 75 reactions to the initial reconstruction, and 200 of 271 cases were correctly computed. Third, in silico computations of the growth phenotypes of knock-out strains were found to be consistent with experimental observations in 720 of 766 cases evaluated. Fourth, the integrated analysis of the large-scale substrate utilization and gene essentiality data with the genome-scale metabolic model revealed the requirement of 80 specific enzymes (transport, 53; intracellular reactions, 27) that were not in the genome annotation. Subsequent sequence analysis resulted in the identification of genes that could be putatively assigned to 13 intracellular enzymes. The final reconstruction accounted for 844 open reading frames and consisted of 1020 metabolic reactions and 988 metabolites. Hence, the in silico model can be used to obtain experimentally verifiable hypothesis on the metabolic functions of various genes.Genome-scale reconstruction of metabolic network in Bacillus subtilis based on high-throughput phenotyping and gene essentiality data.Oh You-Kwan YK, Palsson Bernhard O BO, Park Sung M SM, Schilling Christophe H CH, Mahadevan Radhakrishnan RBacillus subtilis var. natto, scale tissue, Bacillus natto, scale, Genomes, Vibrio subtilis, Bacillus mesentericus, Bacillus subtilis subsp. natto, plant peltate hair, peltate hair, Bacillus subtilis8, Bacillus uniflagellatus., scale (sensu Metazoa), Natto Bacteria, Bacillus globigii, scales, Bacillus subtilis/Bacillus globigii, Bacillus subtilis (natto)biochemical pathways, scale tissue, Metabolic Process, rasGAP, nucleocytoplasm, Materials, single-organism developmental process, determination, Sequence Determination, postnatal development, Metabolic Concepts, 10538, Mbp1, growth and development, ras p21 protein activator, GAP1, Reading Frame, brl, solute:solute exchange, GADPH, primary metabolites, CG8893, gap1, Bacillus subtilis subsp. natto, GRP1, Grp1, Concepts, PKWS, ORFs, Analysis, Metabolism Concept, Phenomenon, myd, Unassigned, FBgn 32821, Unassigned Reading Frame, Unidentified Reading Frames, enzymes, Genomes, Analyses, Bacillus mesentericus, Determination, catabolism, plant peltate hair, PTPSTEP, Gapd, Open, Mbp-1, mip, metabolic process resulting in cell growth, Sequence Determinations, d-CdGAPr, Protein Coding, l(2)k08110, biotransformation, CM-AVM, s, Strains, Catabolism, DmelCG8893, Protein Coding Regions, intracellular, GPH, Process, gyltl1b-b, metabolism resulting in cell growth, RASA, Expanded, Determinations, single-organism transport, MDDGA6, 1270, mKIAA0609, sxt, 3.1.3.48, Genetic Materials, secretion, GAP, Gap, internal to cell, p120RASGAP, Region, Genetic Material, fg, Ras-GAP, ORF, CG10538, gyltl1b, growth pattern, Step, CG11628, non-developmental growth, mdc1d, expanded, Ex, Striatum-enriched protein-tyrosine phosphatase, INSDC_feature:gene, gap, Bacillus subtilis (natto), Phenotypes, MDC1D, enr, enlarged, STEP, Material, Ras p21 protein activator, metabolites, Biocatalyst, l(2)ey, small molecule transport, Cistron, Bacillus globigii, Genetic Material., Strains and Sprains, big, GRP1/cytohesin 1, Open Reading Frame, Processes, Biocatalysts, GAPDH II, peltate hair, GTPase-activating protein, secondary metabolites, Gene, Gapdh13F, Metabolic Processes, Bacillus uniflagellatus, froggy, Gyltl1a, CG11633, cytohesin/GRP1, Unidentified Reading, large, DmelCG4114, Metabolism, Unassigned Reading Frames, Metabolism Phenomena, Sprains, protoplasm, Frame, sORF, Genetic, protoplast, RasGAP, MDDGB6, GA3PDH, Bacillus subtilis8, Gap 1, Coding Region, l(2)SH2 0323, Metabolic Concept, GAPDH2, Unidentified Reading Frame, BPFD#36, Enzyme, Gapdh-2, Neural-specific protein-tyrosine phosphatase, Vibrio subtilis, great, scale (sensu Metazoa), CG6721, Natto Bacteria, Sequence Analyses, Protein Coding Region, data, degradation, Sprain, CG4114, stepk, enzyme activity, Bacillus subtilis/Bacillus globigii, RASGAP, Cistrons, Concept, Metabolic Phenomena, development, Metabolism Concepts, Sequence, Gapdh, chemical analysis, Protein, Phenomena, Strain, RASA1, rI533, Small Open Reading Frames, scales, p120GAP, metabolism, l(2)SH0323, GAPDH, Metabolic Phenomenon, CYH1, Bacillus subtilis var. natto, Bacillus natto, multicellular organism metabolic process, DmelCG6721, scale, biodegradation, Metabolic, DmelCG10538, postnatal growth, metabolite, CMAVM, Unidentified, DmelCG11628, l(2)01270, single-organism metabolic process, Small Open Reading Frame, assay, growth, hypothesis, Anabolismbiochemical pathways, extent, scale tissue, Metabolic Process, rasGAP, nucleocytoplasm, Materials, Public Sectors, PLXN5, single-organism developmental process, determination, Sequence Determination, postnatal development, Metabolic Concepts, Nl1, 10538, Mbp1, growth and development, ras p21 protein activator, GAP1, Reading Frame, brl, SeP, Bacillus <firmicutes>, solute:solute exchange, GADPH, hereditary late onset Parkinson disease, CEH, CG8893, gap1, Bacillus subtilis subsp. natto, GRP1, Grp1, Park, Concepts, NEPII, NL1, PKWS, NL2, ORFs, Analysis, SEH, Metabolism Concept, Public Enterprise, Phenomenon, myd, Unassigned, FBgn 32821, Unassigned Reading Frame, Sep, SEP, Unidentified Reading Frames, Parkinson disease, enzymes, Genomes, Analyses, Bacillus mesentericus, Determination, catabolism, plant peltate hair, PTPSTEP, Gapd, Open, Bacillus bacterium, Public Domains, Mbp-1, mip, metabolic process resulting in cell growth, Bacillus rRNA group 1, Sequence Determinations, sEP, d-CdGAPr, Protein Coding, l(2)k08110, biotransformation, CM-AVM, s, Strains, Catabolism, DmelCG8893, Protein Coding Regions, intracellular, GPH, Multifactorial, late onset Parkinson disease, Process, gyltl1b-b, completeness, metabolism resulting in cell growth, LOPD, Bacillus, RASA, Expanded, Determinations, late onset Parkinson's disease, MMEL2, single-organism transport, Public Domain, MDDGA6, 1270, mKIAA0609, sxt, 3.1.3.48, Domains, Genetic Materials, secretion, GAP, Gap, internal to cell, p120RASGAP, Region, Genetic Material, Domain, hereditary late-onset Parkinson disease, fg, Ras-GAP, ORF, CG10538, gyltl1b, growth pattern, Step, CG11628, non-developmental growth, susceptibility to, mdc1d, expanded, Ex, INSDC_feature:gene, Striatum-enriched protein-tyrosine phosphatase, gap, Bacillus subtilis (natto), late-onset, experimental procedures, CG10523, Phenotypes, MDC1D, Sector, enr, enlarged, STEP, Material, Ras p21 protein activator, Biocatalyst, l(2)ey, small molecule transport, Cistron, Eph2, Bacillus globigii, Strains and Sprains, big, Sectors, GRP1/cytohesin 1, experimental, Open Reading Frame, Processes, Biocatalysts, GAPDH II, peltate hair, number, GTPase-activating protein, Gene, PLEXIN-B1, Gapdh13F, Copyrights, Metabolic Processes, presence, Bacillus uniflagellatus, froggy, Gyltl1a, CG11633, cytohesin/GRP1, Unidentified Reading, Prkn, large, DmelCG4114, SD01679, Metabolism, Unassigned Reading Frames, Metabolism Phenomena, Sprains, Enterprises, protoplasm, Frame, CG2916, sORF, methods, Genetic, protoplast, RasGAP, experimental section, MDDGB6, GA3PDH, Bacillus subtilis8, Gap 1, Coding Region, autosomal dominant late-onset Parkinson disease, l(2)SH2 0323, Metabolic Concept, GAPDH2, Public Enterprises, dpk, Unidentified Reading Frame, BPFD#36, Enzyme, Abstract, Gapdh-2, Neural-specific protein-tyrosine phosphatase, Vibrio subtilis, great, SELP, scale (sensu Metazoa), CG6721, Natto Bacteria, Enterprise, Sequence Analyses, Protein Coding Region, data, modifier, degradation, Sprain, CG4114, Bacillus <walking sticks>, Mell1, stepk, enzyme activity, Bacillus subtilis/Bacillus globigii, RASGAP, Cistrons, Concept, Metabolic Phenomena, sep5, development, Metabolism Concepts, count in organism, Sequence, Public, Gapdh, chemical analysis, Protein, Phenomena, Strain, RASA1, rI533, Small Open Reading Frames, scales, p120GAP, metabolism, l(2)SH0323, GAPDH, Data Base, Metabolic Phenomenon, age of onset, late-onset Parkinson disease, CYH1, Bacillus subtilis var. natto, Bacillus natto, multicellular organism metabolic process, DmelCG6721, scale, biodegradation, Metabolic, PARK, DmelCG2916, DmelCG10538, postnatal growth, CMAVM, Dpark, Unidentified, DmelCG11628, l(2)01270, single-organism metabolic process, Small Open Reading Frame, PD, Public., DmelCG10523, assay, quantitative, growth, NEP2, hypothesis, Anabolism, presence or absence in organismBacillus subtilis var. natto, scale tissue, Bacillus natto, scale, Genomes, Vibrio subtilis, Bacillus mesentericus, data., Bacillus subtilis subsp. natto, plant peltate hair, peltate hair, Bacillus subtilis8, scale (sensu Metazoa), Natto Bacteria, Bacillus globigii, INSDC_feature:gene, scales, Bacillus subtilis/Bacillus globigii, Bacillus subtilis (natto), Bacillus uniflagellatusfalseOh2007 - Genome-scale metabolic network of Bacillus subtilis (iYO844)
Oh2007 - Genome-scale metabolic network of
Bacillus subtilis (iYO844)
This model is described in the article:
Genome-scale reconstruction
of metabolic network in Bacillus subtilis based on
high-throughput phenotyping and gene essentiality data.
Oh YK, Palsson BO, Park SM,
Schilling CH, Mahadevan R.
J. Biol. Chem. 2007 Sep; 282(39):
28791-28799
Abstract:
In this report, a genome-scale reconstruction of Bacillus
subtilis metabolism and its iterative development based on the
combination of genomic, biochemical, and physiological
information and high-throughput phenotyping experiments is
presented. The initial reconstruction was converted into an in
silico model and expanded in a four-step iterative fashion.
First, network gap analysis was used to identify 48 missing
reactions that are needed for growth but were not found in the
genome annotation. Second, the computed growth rates under
aerobic conditions were compared with high-throughput
phenotypic screen data, and the initial in silico model could
predict the outcomes qualitatively in 140 of 271 cases
considered. Detailed analysis of the incorrect predictions
resulted in the addition of 75 reactions to the initial
reconstruction, and 200 of 271 cases were correctly computed.
Third, in silico computations of the growth phenotypes of
knock-out strains were found to be consistent with experimental
observations in 720 of 766 cases evaluated. Fourth, the
integrated analysis of the large-scale substrate utilization
and gene essentiality data with the genome-scale metabolic
model revealed the requirement of 80 specific enzymes
(transport, 53; intracellular reactions, 27) that were not in
the genome annotation. Subsequent sequence analysis resulted in
the identification of genes that could be putatively assigned
to 13 intracellular enzymes. The final reconstruction accounted
for 844 open reading frames and consisted of 1020 metabolic
reactions and 988 metabolites. Hence, the in silico model can
be used to obtain experimentally verifiable hypothesis on the
metabolic functions of various genes.
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2015-07-282015-07-302015-07-18MODEL150718001317573341MODEL1507180013