BioModelsapplication/xmlhttps://www.ebi.ac.uk/biomodels/model/download/MODEL2304270001?filename=iCstr1054FB23.omexprimary200OKAndreas DrägerNon-curatedconstraint-based model0.1FROGhttps://www.ebi.ac.uk/biomodels/MODEL2304270001falseBioModelsModelsCOMBINE archiveiCstr1054FB23: Genome scale metabolic model of Corynebacterium striatum strain FDAARGOS 10542023MODEL2304270001Famke BäuerleFamke Bäuerle, Gwendolyn O. Döbel, Laura Camus, Simon Heilbronner, Andreas Dräger10.3389/fbinf.2023.1214074, Introduction: Genome-scale metabolic models (GEMs) are organism-specific knowledge bases which can be used to unravel pathogenicity or improve production of specific metabolites in biotechnology applications. However, the validity of predictions for bacterial proliferation in in vitro settings is hardly investigated. Methods: The present work combines in silico and in vitro approaches to create and curate strain-specific genome-scale metabolic models of Corynebacterium striatum. Results: We introduce five newly created strain-specific genome-scale metabolic models (GEMs) of high quality, satisfying all contemporary standards and requirements. All these models have been benchmarked using the community standard test suite Metabolic Model Testing (MEMOTE) and were validated by laboratory experiments. For the curation of those models, the software infrastructure refineGEMs was developed to work on these models in parallel and to comply with the quality standards for GEMs. The model predictions were confirmed by experimental data and a new comparison metric based on the doubling time was developed to quantify bacterial growth. Discussion: Future modeling projects can rely on the proposed software, which is independent of specific environmental conditions. The validation approach based on the growth rate calculation is now accessible and closely aligned with biological questions. The curated models are freely available via BioModels and a GitHub repository and can be used. The open-source software refineGEMs is available from https://github.com/draeger-lab/refinegems.. , 3. 1) Computational Systems Biology of Infections and Antimicrobial-Resistant Pathogens, Institute for Bioinformatics and Medical Informatics (IBMI), Eberhard Karl University of Tübingen, Tübingen, Germany 2) Interfaculty Institute of Microbiology and Infection Medicine Tübingen (IMIT), Eberhard Karl University of Tübingen, Tübingen, Germany 3) Department of Computer Science, Eberhard Karl University of Tübingen, Tübingen, Germany 4) German Center for Infection Research (DZIF), Partner Site Tübingen, Tübingen, Germany 5) Cluster of Excellence “Controlling Microbes to Fight Infections (CMFI)”, Eberhard Karl University of Tübingen, Tübingen, Germany 6) Faculty of Biology, Microbiology, Ludwig Maximilian University of Munich, Munich, Germanyandreas.draeger@informatik.uni-halle.de10.3389/fbinf.2023.1214074Martin Luther University Halle-Wittenbergstrain, scale tissue, scale, Genomes, Bacterium striatum, plant peltate hair, peltate hair, Sprain, Strain., cultivar, Strains, whole genome, scales, Sprains, Strains and Sprains, ecotypedorsal striatum, caudate-putamen, scale tissue, scale, corpus striatum (Zilles)., Genomes, plant peltate hair, peltate hair, Sprain, striatum, whole genome, Neostriatum, neostriatum, ecotype, strain, striated nucleus, corpus striatum, caudate putamen, striated body, striate body, Strain, caudateputamen, cultivar, Strains, scales, caudate putamen (striatum), Sprains, Strains and SprainsfalseiCstr1054FB23: Genome-scale metabolic model of Corynebacterium striatum strain FDAARGOS_1054Strain-specific genome-scale metabolic model of C. striatum FDAARGOS_1054.2024-01-092024-04-182023-04-27MODEL2304270001MODEL230427000110.3389/fbinf.2023.1214074