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More than just a gut feeling: constraint-based genome-scale metabolic models for predicting functions of human intestinal microbes

Authors :
Clara Belzer
Kees C. H. van der Ark
Willem M. de Vos
Ruben G. A. van Heck
Vitor A. P. Martins dos Santos
Source :
Microbiome, Vol 5, Iss 1, Pp 1-13 (2017), Microbiome, Microbiome 5 (2017) 1, Microbiome, 5(1), 78-78
Publication Year :
2017
Publisher :
Springer Science and Business Media LLC, 2017.

Abstract

The human gut is colonized with a myriad of microbes, with substantial interpersonal variation. This complex ecosystem is an integral part of the gastrointestinal tract and plays a major role in the maintenance of homeostasis. Its dysfunction has been correlated to a wide array of diseases, but the understanding of causal mechanisms is hampered by the limited amount of cultured microbes, poor understanding of phenotypes, and the limited knowledge about interspecies interactions. Genome-scale metabolic models (GEMs) have been used in many different fields, ranging from metabolic engineering to the prediction of interspecies interactions. We provide showcase examples for the application of GEMs for gut microbes and focus on (i) the prediction of minimal, synthetic, or defined media; (ii) the prediction of possible functions and phenotypes; and (iii) the prediction of interspecies interactions. All three applications are key in understanding the role of individual species in the gut ecosystem as well as the role of the microbiota as a whole. Using GEMs in the described fashions has led to designs of minimal growth media, an increased understanding of microbial phenotypes and their influence on the host immune system, and dietary interventions to improve human health. Ultimately, an increased understanding of the gut ecosystem will enable targeted interventions in gut microbial composition to restore homeostasis and appropriate host-microbe crosstalk.

Details

ISSN :
20492618
Volume :
5
Database :
OpenAIRE
Journal :
Microbiome
Accession number :
edsair.doi.dedup.....5ec2fcde017ee36e689dd6b7f126b2ce
Full Text :
https://doi.org/10.1186/s40168-017-0299-x