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

Abstract

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.

Authors:
 [1];  [2];  [2];  [3];  [4];  [5]
  1. Boston Univ., Boston, MA (United States). Bioinformatics Program
  2. Boston Univ., Boston, MA (United States). Bioinformatics Program; Center for Advanced Genomic Technology
  3. Boston Univ., Boston, MA (United States). Center for Advanced Genomic Technology; Dept. of Biomedical Engineering
  4. Boston Univ., Boston, MA (United States). Bioinformatics Program; Dept. of Biomedical Engineering; Dept. of Biology
  5. Boston Univ., Boston, MA (United States). Center for Advanced Genomic Technology
Publication Date:
Research Org.:
Boston Univ., MA (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
OSTI Identifier:
1262270
Grant/Contract Number:  
SC0004962
Resource Type:
Accepted Manuscript
Journal Name:
PLoS Computational Biology (Online)
Additional Journal Information:
Journal Name: PLoS Computational Biology (Online); Journal Volume: 12; Journal Issue: 4; Journal ID: ISSN 1553-7358
Publisher:
Public Library of Science
Country of Publication:
United States
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES; biology markup language; flux balance analysis; systems biology; user-interface; models; reconstruction; platform; project; gene; metabolic networks; metabolics; network analysis; special interactions; enzyme metabolism; enzymes; consortia; microbial ecosystems

Citation Formats

Granger, Brian R., Chang, Yi -Chien, Wang, Yan, DeLisi, Charles, Segre, Daniel, and Hu, Zhenjun. Visualization of metabolic interaction networks in microbial communities using VisANT 5.0. United States: N. p., 2016. Web. doi:10.1371/journal.pcbi.1004875.
Granger, Brian R., Chang, Yi -Chien, Wang, Yan, DeLisi, Charles, Segre, Daniel, & Hu, Zhenjun. Visualization of metabolic interaction networks in microbial communities using VisANT 5.0. United States. doi:10.1371/journal.pcbi.1004875.
Granger, Brian R., Chang, Yi -Chien, Wang, Yan, DeLisi, Charles, Segre, Daniel, and Hu, Zhenjun. Fri . "Visualization of metabolic interaction networks in microbial communities using VisANT 5.0". United States. doi:10.1371/journal.pcbi.1004875. https://www.osti.gov/servlets/purl/1262270.
@article{osti_1262270,
title = {Visualization of metabolic interaction networks in microbial communities using VisANT 5.0},
author = {Granger, Brian R. and Chang, Yi -Chien and Wang, Yan and DeLisi, Charles and Segre, Daniel and Hu, Zhenjun},
abstractNote = {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.},
doi = {10.1371/journal.pcbi.1004875},
journal = {PLoS Computational Biology (Online)},
number = 4,
volume = 12,
place = {United States},
year = {2016},
month = {4}
}

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