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dc.contributor.authorHeinken, Almut
dc.contributor.authorKhan, M Tanweer
dc.contributor.authorPaglia, Giuseppe
dc.contributor.authorRodionov, Dmitry A
dc.contributor.authorHarmsen, Hermie J M
dc.contributor.authorThiele, Ines
dc.date.accessioned2015-06-05T12:40:17Zen
dc.date.available2015-06-05T12:40:17Zen
dc.date.issued2014-09en
dc.identifier.citationJ. Bacteriol. 2014, 196 (18):3289-302 J. Bacteriol.en
dc.identifier.issn1098-5530en
dc.identifier.pmid25002542en
dc.identifier.doi10.1128/JB.01780-14en
dc.identifier.urihttp://hdl.handle.net/2336/556456en
dc.descriptionTo access publisher's full text version of this article click on the hyperlink at the bottom of the pageen
dc.description.abstractThe human gut microbiota plays a central role in human well-being and disease. In this study, we present an integrated, iterative approach of computational modeling, in vitro experiments, metabolomics, and genomic analysis to accelerate the identification of metabolic capabilities for poorly characterized (anaerobic) microorganisms. We demonstrate this approach for the beneficial human gut microbe Faecalibacterium prausnitzii strain A2-165. We generated an automated draft reconstruction, which we curated against the limited biochemical data. This reconstruction modeling was used to develop in silico and in vitro a chemically defined medium (CDM), which was validated experimentally. Subsequent metabolomic analysis of the spent medium for growth on CDM was performed. We refined our metabolic reconstruction according to in vitro observed metabolite consumption and secretion and propose improvements to the current genome annotation of F. prausnitzii A2-165. We then used the reconstruction to systematically characterize its metabolic properties. Novel carbon source utilization capabilities and inabilities were predicted based on metabolic modeling and validated experimentally. This study resulted in a functional metabolic map of F. prausnitzii, which is available for further applications. The presented workflow can be readily extended to other poorly characterized and uncharacterized organisms to yield novel biochemical insights about the target organism.
dc.description.sponsorshipinfo:eu-repo/grantAgreement/EC/FP7/249261 Luxembourg National Research Fund (FNR) FNR/A12/01en
dc.language.isoenen
dc.publisherAmer Soc Microbiologyen
dc.relationinfo:eu-repo/grantAgreement/EC/FP7/249261en
dc.relationinfo:eu-repo/grantAgreement/EC/FP7/249261en
dc.relation.urlhttp://dx.doi.org/ 10.1128/JB.01780-14en
dc.relation.urlhttp://www.ncbi.nlm.nih.gov/pmc/articles/PMC4135701/en
dc.rightsopenAccessen
dc.subject.meshBacterial Proteinsen
dc.subject.meshDatabases, Factualen
dc.subject.meshGene Expression Regulation, Bacterialen
dc.subject.meshGenome, Bacterialen
dc.subject.meshGram-Positive Bacteriaen
dc.subject.meshTranscriptomeen
dc.titleFunctional metabolic map of Faecalibacterium prausnitzii, a beneficial human gut microbe.en
dc.typearticleen
dc.contributor.departmentUniv Luxembourg, Luxembourg Ctr Syst Biomed, Belval, Luxembourg [ 2 ] Univ Iceland, Ctr Syst Biol, Reykjavik, Iceland [ 3 ] Univ Groningen, Univ Med Ctr Groningen, Dept Med Microbiol, Groningen, Netherlands [ 4 ] Sanford Burnham Med Res Inst, La Jolla, CA USA [ 5 ] Russian Acad Sci, AA Kharkevich Inst Informat Transmiss Problems, Moscow, Russiaen
dc.identifier.journalJournal of bacteriologyen
dc.rights.accessOpen Access - Opinn aðganguren
html.description.abstractThe human gut microbiota plays a central role in human well-being and disease. In this study, we present an integrated, iterative approach of computational modeling, in vitro experiments, metabolomics, and genomic analysis to accelerate the identification of metabolic capabilities for poorly characterized (anaerobic) microorganisms. We demonstrate this approach for the beneficial human gut microbe Faecalibacterium prausnitzii strain A2-165. We generated an automated draft reconstruction, which we curated against the limited biochemical data. This reconstruction modeling was used to develop in silico and in vitro a chemically defined medium (CDM), which was validated experimentally. Subsequent metabolomic analysis of the spent medium for growth on CDM was performed. We refined our metabolic reconstruction according to in vitro observed metabolite consumption and secretion and propose improvements to the current genome annotation of F. prausnitzii A2-165. We then used the reconstruction to systematically characterize its metabolic properties. Novel carbon source utilization capabilities and inabilities were predicted based on metabolic modeling and validated experimentally. This study resulted in a functional metabolic map of F. prausnitzii, which is available for further applications. The presented workflow can be readily extended to other poorly characterized and uncharacterized organisms to yield novel biochemical insights about the target organism.


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