University of Illinois Urbana-Champaign

Evidence for a multi-level trophic organization of the human gut microbiome

Wang, Tong; Goyal, Akshit; Dubinkina, Veronika; Maslov, Sergei

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https://hdl.handle.net/2142/106054

Description

Title
Evidence for a multi-level trophic organization of the human gut microbiome
Author(s)
  • Wang, Tong
  • Goyal, Akshit
  • Dubinkina, Veronika
  • Maslov, Sergei
Issue Date
2019-12-19
Keyword(s)
  • Metabolites
  • Metabolomics
  • Microbiome
  • Biomass
  • Microbial metabolism
  • Metagenomics
  • Microbial ecosystems
  • Metabolic processes
Abstract
The human gut microbiome is a complex ecosystem, in which hundreds of microbial species and metabolites coexist, in part due to an extensive network of cross-feeding interactions. However, both the large-scale trophic organization of this ecosystem, and its effects on the underlying metabolic flow, remain unexplored. Here, using a simplified model, we provide quantitative support for a multi-level trophic organization of the human gut microbiome, where microbes consume and secrete metabolites in multiple iterative steps. Using a manually-curated set of metabolic interactions between microbes, our model suggests about four trophic levels, each characterized by a high level-to-level metabolic transfer of byproducts. It also quantitatively predicts the typical metabolic environment of the gut (fecal metabolome) in approximate agreement with the real data. To understand the consequences of this trophic organization, we quantify the metabolic flow and biomass distribution, and explore patterns of microbial and metabolic diversity in different levels. The hierarchical trophic organization suggested by our model can help mechanistically establish causal links between the abundances of microbes and metabolites in the human gut.
Publisher
PLoS
Series/Report Name or Number
PLoS Computational Biology; vol 15, no. 12, 2019
Type of Resource
text
Language
en
Permalink
http://hdl.handle.net/2142/106054
DOI
https://doi.org/10.1371/journal.pcbi.1007524
Copyright and License Information
Copyright 2019 Tong Wang, Akshit Goyal, Veronika Dubinkina, and Sergei Maslov

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