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bioRxiv · 10.1101/2020.01.09.900761

Expression-Based Inference of Human Microbiome Metabolic Flux Patterns in Health and Disease

Wang, Y.·Gu, Z.
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Abstract

1Metagenomic sequencing has revealed that the composition of the gut microbiome is linked to several major metabolic diseases, including obesity, type 2 diabetes (T2D), and inflammatory bowel disease (IBD). However, the exact mechanistic link between the gut microbiome and human host phenotypes is unclear. Here we used constraint-based modeling of the gut microbiome, using a gene-expression based algorithm called FALCON, to simulate metabolic flux differences in the microbiome of controls vs. metabolic disease patients. We discovered that several major pathways, previously shown to be important in human host metabolism, have significantly different flux between the two groups. We also modeled metabolic cooperation and competition between pairs of species in the microbiome, and use this to determine the compositional stability of the microbiome. We find that that the microbiome is generally unstable across controls as well as metabolic microbiomes, and metabolic disease microbiomes even more unstable than controls.

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Wang, Y., Gu, Z.. 2020-01-09. Expression-Based Inference of Human Microbiome Metabolic Flux Patterns in Health and Disease. https://doi.org/10.1101/2020.01.09.900761

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