Visualization of metabolic interaction networks in microbial communities using VisANT 5.0

Granger, Brian R.; Chang, Yi -Chien; Wang, Yan; DeLisi, Charles; Segre, Daniel; Hu, Zhenjun

doi:10.1371/journal.pcbi.1004875

Title: Visualization of metabolic interaction networks in microbial communities using VisANT 5.0

Journal Article · Fri Apr 15 00:00:00 EDT 2016 · PLoS Computational Biology (Online)

DOI:https://doi.org/10.1371/journal.pcbi.1004875· OSTI ID:1262270

Granger, Brian R. ^[1]; Chang, Yi -Chien ^[2]; Wang, Yan ^[2]; DeLisi, Charles ^[3]; Segre, Daniel ^[4]; Hu, Zhenjun ^[5]

Boston Univ., Boston, MA (United States). Bioinformatics Program
Boston Univ., Boston, MA (United States). Bioinformatics Program; Center for Advanced Genomic Technology
Boston Univ., Boston, MA (United States). Center for Advanced Genomic Technology; Dept. of Biomedical Engineering
Boston Univ., Boston, MA (United States). Bioinformatics Program; Dept. of Biomedical Engineering; Dept. of Biology
Boston Univ., Boston, MA (United States). Center for Advanced Genomic Technology

Here, the complexity of metabolic networks in microbial communities poses an unresolved visualization and interpretation challenge. We address this challenge in the newly expanded version of a software tool for the analysis of biological networks, VisANT 5.0. We focus in particular on facilitating the visual exploration of metabolic interaction between microbes in a community, e.g. as predicted by COMETS (Computation of Microbial Ecosystems in Time and Space), a dynamic stoichiometric modeling framework. Using VisANT's unique meta-graph implementation, we show how one can use VisANT 5.0 to explore different time-dependent ecosystem-level metabolic networks. In particular, we analyze the metabolic interaction network between two bacteria previously shown to display an obligate cross-feeding interdependency. In addition, we illustrate how a putative minimal gut microbiome community could be represented in our framework, making it possible to highlight interactions across multiple coexisting species. We envisage that the "symbiotic layout" of VisANT can be employed as a general tool for the analysis of metabolism in complex microbial communities as well as heterogeneous human tissues.

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Research Organization:: Boston Univ., MA (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Biological and Environmental Research (BER)

Grant/Contract Number:: SC0004962

OSTI ID:: 1262270

Journal Information:: PLoS Computational Biology (Online), Vol. 12, Issue 4; ISSN 1553-7358

Publisher:: Public Library of ScienceCopyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 22 works

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