BioModelsapplication/xmlhttps://www.ebi.ac.uk/biomodels/model/download/MODEL1507180059?filename=MODEL1507180059.pdfhttps://www.ebi.ac.uk/biomodels/model/download/MODEL1507180059?filename=MODEL1507180059-biopax3.owlhttps://www.ebi.ac.uk/biomodels/model/download/MODEL1507180059?filename=MODEL1507180059-biopax2.owlhttps://www.ebi.ac.uk/biomodels/model/download/MODEL1507180059?filename=MODEL1507180059_urn.xmlhttps://www.ebi.ac.uk/biomodels/model/download/MODEL1507180059?filename=MODEL1507180059_url.xmlhttps://www.ebi.ac.uk/biomodels/model/download/MODEL1507180059?filename=MODEL1507180059.xpphttps://www.ebi.ac.uk/biomodels/model/download/MODEL1507180059?filename=MODEL1507180059.mhttps://www.ebi.ac.uk/biomodels/model/download/MODEL1507180059?filename=MODEL1507180059.scihttps://www.ebi.ac.uk/biomodels/model/download/MODEL1507180059?filename=MODEL1507180059.pnghttps://www.ebi.ac.uk/biomodels/model/download/MODEL1507180059?filename=MODEL1507180059.vcmlprimary200OKNicolas Le NovèreNon-curatedconstraint-based modelL3V1https://www.ebi.ac.uk/biomodels/MODEL150718005918364711falseBioModelsSBMLModelsChavali2008 Genome scale metabolic network of Leishmania major (iAC560)2008MODEL1507180059Non KineticArvind K Chavali, Jeffrey D Whittemore, James A Eddy, Kyle T Williams, Jason A PapinArvind K Chavali18364711, Systems analyses have facilitated the characterization of metabolic networks of several organisms. We have reconstructed the metabolic network of Leishmania major, a poorly characterized organism that causes cutaneous leishmaniasis in mammalian hosts. This network reconstruction accounts for 560 genes, 1112 reactions, 1101 metabolites and 8 unique subcellular localizations. Using a systems-based approach, we hypothesized a comprehensive set of lethal single and double gene deletions, some of which were validated using published data with approximately 70% accuracy. Additionally, we generated hypothetical annotations to dozens of previously uncharacterized genes in the L. major genome and proposed a minimal medium for growth. We further demonstrated the utility of a network reconstruction with two proof-of-concept examples that yielded insight into robustness of the network in the presence of enzymatic inhibitors and delineation of promastigote/amastigote stage-specific metabolism. This reconstruction and the associated network analyses of L. major is the first of its kind for a protozoan. It can serve as a tool for clarifying discrepancies between data sources, generating hypotheses that can be experimentally validated and identifying ideal therapeutic targets.. null, 4. Department of Biomedical Engineering, University of Virginia, Charlottesville, VA 22908, USA.n.lenovere@gmail.comThe Babraham InstituteSystems analyses have facilitated the characterization of metabolic networks of several organisms. We have reconstructed the metabolic network of Leishmania major, a poorly characterized organism that causes cutaneous leishmaniasis in mammalian hosts. This network reconstruction accounts for 560 genes, 1112 reactions, 1101 metabolites and 8 unique subcellular localizations. Using a systems-based approach, we hypothesized a comprehensive set of lethal single and double gene deletions, some of which were validated using published data with approximately 70% accuracy. Additionally, we generated hypothetical annotations to dozens of previously uncharacterized genes in the L. major genome and proposed a minimal medium for growth. We further demonstrated the utility of a network reconstruction with two proof-of-concept examples that yielded insight into robustness of the network in the presence of enzymatic inhibitors and delineation of promastigote/amastigote stage-specific metabolism. This reconstruction and the associated network analyses of L. major is the first of its kind for a protozoan. It can serve as a tool for clarifying discrepancies between data sources, generating hypotheses that can be experimentally validated and identifying ideal therapeutic targets.Systems analysis of metabolism in the pathogenic trypanosomatid Leishmania major.Chavali Arvind K AK, Whittemore Jeffrey D JD, Eddy James A JA, Williams Kyle T KT, Papin Jason A JAbiochemical pathways, Thinkings, Agent Based Modeling, Metabolic Process, Thinking, Agent-Based Modelings, Leishmania tropica major, degradation, Process, Processes, Complexity, metabolism resulting in cell growth, System Dynamics Analysis, Metabolic Concepts, tropica major, leishmania major, major, Systems Oriented, tropica majors, Leishmania leishmania major, Metabolic Processes, System Dynamics Analyses, Concept, Metabolic Phenomena, Dynamics Analyses, Metabolism Concepts, System Dynamics, Dynamics Analysis, Leishmania leishmania, Metabolism, Systems, Phenomena, Concepts, secretion, Analysis, Systems Thinking, Approach, Metabolism Concept, Complexity Analysis, Phenomenon, Metabolism Phenomena, metabolism, Systems Medicines, Metabolic Phenomenon, Complexity Analyses, Approachs, multicellular organism metabolic process, Leishmania tropica majors, biodegradation, Analyses, Metabolic, Systems Approachs, catabolism, Modeling, System, Systems Analyses, majors, Metabolic Concept, Leishmania leishmania majors, metabolic process resulting in cell growth, Systems Medicine, Agent-Based, Systems Approach, Agent-Based Modeling, Leishmania majors, Medicine, biotransformation, Medicines, Systems Oriented Approachs, Leishmania, Systems Oriented Approach, Modelings, Leishmania (Leishmania) major., Catabolism, Leishmania tropica, Systems Thinkings, Anabolismscale tissue, Leishmania leishmania, Leishmania tropica majors, scale, Leishmania tropica major, Genomes, plant peltate hair, peltate hair, Leishmania majors, tropica major, leishmania major, majors, major, Leishmania leishmania majors, Leishmania, whole genome, scales, tropica majors, Leishmania leishmania major, Leishmania (Leishmania) major., Leishmania tropicabiochemical pathways, Metabolic Networks, Networks, Cognitive Function, IPP2A2, Metabolic Process, Materials, postnatal development, Metabolic Concepts, growth and development, Leishmania leishmania major, 5730420M11Rik, Dynamics Analyses, primary metabolites, Leishmaniases, pathogenesis, Concepts, Analysis, Metabolism Concept, animal, Phenomenon, SET, Leishmania tropica majors, Analyses, Genomes, Systems Approachs, TAF-I, catabolism, majors, Pathways, metabolic process resulting in cell growth, Deletions, Cutaneous Leishmaniases, Source of Information, DmelCG4299, IGAAD, set, Cognitions, DmelCG10574, Functions, Medicine, Therapies, biotransformation, Medicines, New World Leishmaniasis, Leishmania tropica, Catabolism, Asian desert cutaneous leishmaniasis, phapii, Therapy, Thinkings, Pathway, zone of skin leishmaniasis, Process, Complexity, metabolism resulting in cell growth, leishmania 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leishmaniasis, phapii, Thinkings, zone of skin leishmaniasis, Process, completeness, Complexity, metabolism resulting in cell growth, leishmania major, StF-IT-1, Systems Oriented, Leishmania <subgenus>, Oriental, organism, Leishmania leishmania, l(2)br3, l35Bb, Leishmaniasis, Public Domain, Domains, Genetic Materials, secretion, Genetic Material, Domain, Systems Medicines, Approachs, whole organism, HLA-DR-associated protein II, DI-2, growth pattern, Modeling, non-developmental growth, System, I-2Dm, Systems Analyses, Cutaneous Leishmaniasis, Leishmania leishmania majors, whole genome, leproid leishmaniasis, CG4299, l(2)SH2 1330, Agent-Based, I-2PP1, American Leishmaniasis, Sector, Leishmania (Leishmania), TAF-IBETA, Material, Koerper, Cistron, TAF-Ibeta, BG:DS01219.1, Systems Oriented Approachs, Modelings, i2pp2a, Systems Thinkings, Cutaneous, Agent Based Modeling, Sectors, Thinking, multi-cellular organism, Leishmania tropica major, Agent-Based Modelings, mol, Processes, peltate hair, developmental stage, tropica major, System Dynamics Analysis, number, Gene, Copyrights, Metabolic Processes, DmelCG4482, presence, PHAPII, Gene Deletions, Metabolism, Metabolism Phenomena, Enterprises, Leishmania leishmanias, l(2)br23, Complexity Analyses, American, Genetic, Oriental Sore, viannias, ipp2a2, Metabolic Concept, 2pp2a, Deletion, Public Enterprises, CG10574, Leishmanias (Leishmania), PAPIN, Abstract, 2PP2A, taf-ibeta, Leishmanias, leishmanial form, dSET, dSet, species, Systems Oriented Approach, Enterprise, PIN1, Leishman-Donovan body, Sore, degradation, CG4482, body, l(2)35Bb, igaad, major, whole body, tropica majors, Cistrons, System Dynamics Analyses, New World, group, Concept, Metabolic Phenomena, development, Metabolism Concepts, System Dynamics, count in organism, leishmanias, Dynamics Analysis, Leishmania viannia, I-2PP2A, Public, aflagellate form, Systems, Dm I-2, Phenomena, I2PP2A, Systems Thinking, scales, Approach, Complexity Analysis, metabolism, Old World, Data Base, Metabolic Phenomenon, multicellular organism metabolic process, scale, biodegradation, Metabolic, ensemble, postnatal growth, CG15268, Leishmania (Leishmania) major, Systems Medicine, br3, dSET/TAF-Ibeta, 2610030F17Rik, Systems Approach, Agent-Based Modeling, cutaneous leishmaniasis, Leishmania majors, NIP, Public., Leishmania, AA407739, growth, Old World Leishmaniasis, AnabolismfalseChavali2008 - Genome-scale metabolic network of Leishmania major (iAC560) Chavali2008 - Genome-scale metabolic network of Leishmania major (iAC560) This model is described in the article: Systems analysis of metabolism in the pathogenic trypanosomatid Leishmania major. Chavali AK, Whittemore JD, Eddy JA, Williams KT, Papin JA. Mol. Syst. Biol. 2008; 4: 177 Abstract: Systems analyses have facilitated the characterization of metabolic networks of several organisms. We have reconstructed the metabolic network of Leishmania major, a poorly characterized organism that causes cutaneous leishmaniasis in mammalian hosts. This network reconstruction accounts for 560 genes, 1112 reactions, 1101 metabolites and 8 unique subcellular localizations. Using a systems-based approach, we hypothesized a comprehensive set of lethal single and double gene deletions, some of which were validated using published data with approximately 70% accuracy. Additionally, we generated hypothetical annotations to dozens of previously uncharacterized genes in the L. major genome and proposed a minimal medium for growth. We further demonstrated the utility of a network reconstruction with two proof-of-concept examples that yielded insight into robustness of the network in the presence of enzymatic inhibitors and delineation of promastigote/amastigote stage-specific metabolism. This reconstruction and the associated network analyses of L. major is the first of its kind for a protozoan. It can serve as a tool for clarifying discrepancies between data sources, generating hypotheses that can be experimentally validated and identifying ideal therapeutic targets. This model is hosted on BioModels Database and identified by: MODEL1507180059. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information. 2015-07-292015-07-302015-07-18MODEL150718005918364711MODEL1507180059