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Biotechnol J. 2019 Sep;14(9):e1800445. doi: 10.1002/biot.201800445. Epub 2019 Jul 8.

Meta-Omics- and Metabolic Modeling-Assisted Deciphering of Human Microbiota Metabolism.

Sieow BF1,2,3, Nurminen TJ1,2,3, Ling H1,2, Chang MW1,2,3.

Author information

1
Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, 8 Medical Drive, Singapore, 117597, Singapore.
2
NUS Synthetic Biology for Clinical and Technological Innovation (SynCTI), Life Sciences Institute, National University of Singapore, Singapore, 117456, Singapore.
3
NUS Graduate School of Integrative Sciences and Engineering (NGS), University Hall, Tan Chin Tuan Wing, National University of Singapore, Singapore, 119077, Singapore.

Abstract

The 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.

KEYWORDS:

genome-scale modeling; human microbiota; meta-omics; metabolic networks

PMID:
31144773
DOI:
10.1002/biot.201800445
[Indexed for MEDLINE]

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