Abstract
Changes in the human gut microbiome are associated with altered human metabolism and health, yet the mechanisms of interactions between microbial species and human metabolism have not been clearly elucidated. Next-generation sequencing has revolutionized the human gut microbiome research, but most current applications concentrate on studying the microbial diversity of communities and have at best provided associations between specific gut bacteria and human health. However, little is known about the inner metabolic mechanisms in the gut ecosystem. Here we review recent progress in modeling the metabolic interactions of gut microbiome, with special focus on the utilization of metabolic modeling to infer host–microbe interactions and microbial species interactions. The systematic modeling of metabolic interactions could provide a predictive understanding of gut microbiome, and pave the way to synthetic microbiota design and personalized-microbiome medicine and healthcare. Finally, we discuss the integration of metabolic modeling and gut microbiome engineering, which offer a new way to explore metabolic interactions across members of the gut microbiota.
Highlights
The human gut microbiome, represented by trillions of microorganisms colonized in the human gut, is a major contributor to human metabolism and health (Backhed et al, 2005; Turnbaugh and Gordon, 2009)
nextgeneration sequencing (NGS)-based sequencing has dramatically expanded our knowledge of the gut microbiome, current cultureindependent metagenomics generate mixed data to reflect community-level characteristics rather than species-specific features
Even though our understanding of the gut microbiome has advanced rapidly with NGS, genomic sequencing based analysis is not sufficient to decipher the mechanisms of how the microbiome affects human health
Summary
Specialty section: This article was submitted to Bioinformatics and Computational
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