Metabolic network modeling of microbial communities

Biggs, Matthew B.; Medlock, Gregory L.; Kolling, Glynis L.; Papin, Jason A.

doi:10.1002/wsbm.1308

Cited by 124Microbial Metabolic Engineering and BioproductionBioinformatics and Genomic NetworksGene Regulatory Network Analysis

Metabolic network modeling of microbial communities

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Biggs, Matthew B., Medlock, Gregory L., Kolling, Glynis L., Papin, Jason A.·2015·WIREs Systems Biology and Medicine

DOI 10.1002/wsbm.1308PMC PMC4575871

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Abstract

Abstract Genome‐scale metabolic network reconstructions and constraint‐based analyses are powerful methods that have the potential to make functional predictions about microbial communities. Genome‐scale metabolic networks are used to characterize the metabolic functions of microbial communities via several techniques including species compartmentalization, separating species‐level and community‐level objectives, dynamic analysis, the ‘enzyme‐soup’ approach, multiscale modeling, and others. There are many challenges in the field, including a need for tools that accurately assign high‐level omics signals to individual community members, the need for improved automated network reconstruction methods, and novel algorithms for integrating omics data and engineering communities. As technologies and modeling frameworks improve, we expect that there will be corresponding advances in the fields of ecology, health science, and microbial community engineering. WIREs Syst Biol Med 2015, 7:317–334. doi: 10.1002/wsbm.1308 This article is categorized under: Analytical and Computational Methods > Computational Methods Biological Mechanisms > Metabolism

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One key question is how microbial species, their metabolic networks, and interspecies interactions should be represented.
“One of these key questions is how microbial species, their metabolic networks, and interspecies interactions should be represented (Biggs et al., 2015).”
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Authors: Biggs, M. B., Medlock, G. L., Kolling, G. L., & Papin, J. A.
Affiliations: University of Virginia (US)
Corresponding author: Papin, Jason A.
ORCID: Biggs, Matthew B.
Medlock, Gregory L.
Kolling, Glynis L.
Papin, Jason A.
Venue: WIREs Systems Biology and Medicine
Publisher: Wiley
Published: 2015-06-24
Volume: 7
Issue: 5
Pages: 317-334
ISSN: 1939-005X (ISSN-L)
1939-5094
DOI: 10.1002/wsbm.1308
PMC: PMC4575871
OpenAlex: W1903478710
Cited by: 124
References: 131
Citations by year: 2026: 8 · 2025: 9 · 2024: 13 · 2023: 6 · 2022: 9 · 2021: 17 · 2020: 6 · 2019: 17 · 2018: 13 · 2017: 19 · 2016: 6 · 2015: 1
FWCI: 1.26
Type: journal article
Language: en
Open access: green
www.ncbi.nlm.nih.gov
Licence: onlinelibrary.wiley.com/termsAndConditions#vor (vor)
Locations: WIREs Systems Biology and Medicine (publishedVersion)
PubMed (publishedVersion)
PubMed Central (acceptedVersion)
Funders: National Institutes of Health (GM008715, GM108501)
Jefferson Trust Big Data Fellowship
Topics: Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Microbial Metabolic Engineering and Bioproduction
Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
Keywords: genome-scale metabolic reconstruction, constraint-based analysis, microbial communities, multiscale modeling, multi-omics integration
MeSH terms: Algorithms, Models, Biological, Systems Biology, Metabolomics, Microbial Consortia, Metabolic Engineering

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