Please use this identifier to cite or link to this item: https://doi.org/10.1002/biot.201800445
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dc.titleMeta‐Omics‐ and Metabolic Modeling‐Assisted Deciphering of Human Microbiota Metabolism
dc.contributor.authorBrendan Fu‐Long Sieow
dc.contributor.authorToni Juhani Nurminen
dc.contributor.authorLING HUA
dc.contributor.authorChang,Matthew Wook
dc.date.accessioned2020-05-11T01:52:15Z
dc.date.available2020-05-11T01:52:15Z
dc.date.issued2019-09-01
dc.identifier.citationBrendan Fu‐Long Sieow, Toni Juhani Nurminen, LING HUA, Chang,Matthew Wook (2019-09-01). Meta‐Omics‐ and Metabolic Modeling‐Assisted Deciphering of Human Microbiota Metabolism. Biotechnology Journal 14 (9) : e1800445. ScholarBank@NUS Repository. https://doi.org/10.1002/biot.201800445
dc.identifier.issn1860-6768
dc.identifier.issn1860-7314
dc.identifier.urihttps://scholarbank.nus.edu.sg/handle/10635/167909
dc.description.abstractThe human microbiota is a complex community of commensal, symbiotic, and pathogenic microbes that play a crucial role in maintaining the homeostasis of human health. Such a homeostasis is maintained through the collective functioning of enzymatic genes responsible for the production of metabolites, enabling the interaction and signaling within microbiota as well as between microbes and the human host. Understanding microbial genes, their associated chemistries and functions would be valuable for engineering systemic metabolic pathways within the microbiota to manage human health and diseases. Given that there are many unknown gene metabolic functions and interactions, increasing efforts have been made to gain insights into the underlying functions of microbiota metabolism. This can be achieved through culture-independent metagenomic approaches and metabolic modeling to simulate the microenvironment of human microbiota. In this article, the recent advances in metagenome mining and functional profiling for the discovery of the genetic and biochemical links in human microbiota metabolism as well as metabolic modeling for simulation and prediction of metabolic fluxes in the human microbiota are reviewed. This review provides useful insights into the understanding, reconstruction, and modulation of the human microbiota guided by the knowledge acquired from the basic understanding of the human microbiota metabolism.
dc.description.urihttps://onlinelibrary.wiley.com/doi/abs/10.1002/biot.201800445
dc.language.isoen
dc.publisherWiley-VCH Verlag
dc.subjectGenome‐scale modeling
dc.subjectHuman microbiota
dc.subjectMetabolic networks
dc.subjectMeta‐omics
dc.typeReview
dc.contributor.departmentBIOCHEMISTRY
dc.description.doi10.1002/biot.201800445
dc.description.sourcetitleBiotechnology Journal
dc.description.volume14
dc.description.issue9
dc.description.pagee1800445
dc.published.statePublished
dc.grant.idNRF‐NRFI05‐2019‐0004
dc.grant.idDPRT/943/09/14
dc.grant.idMOE/2014/T2/2/128,SBP‐P2,SBP‐P7
dc.grant.idNUHSRO/2016/053/SRP/05
dc.grant.idICP1600012
dc.grant.fundingagencyNational Research Foundation Singapore
dc.grant.fundingagencyNational University of Singapore
dc.grant.fundingagencyMinistry of Education - Singapore
dc.grant.fundingagencyMinistry of Defence
dc.grant.fundingagencyNational University Health System
dc.grant.fundingagencyIndustry Alignment Fund‐Industry Collaboration Project
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