ArticlePLoS computational biology2022
COMMIT: Consideration of metabolite leakage and community composition improves microbial community reconstructions.
Article in PLoS computational biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed.
- Selecting methods for draft GEM generation in multicellular eukaryotes: a comparative analysis.BMC bioinformatics · 2026Article
- Constraint-based metabolic modeling reveals metabolic properties underpinning the unprecedented growth of Chlorella ohadii.The New phytologist · 2025Article
- Article
- Integration of metatranscriptomics data improves the predictive capacity of microbial community metabolic models.The ISME journal · 2025Article
- Comparative analysis of metabolic models of microbial communities reconstructed from automated tools and consensus approaches.NPJ systems biology and applications · 2024Article
- Strategies for tailoring functional microbial synthetic communities.The ISME journal · 2024Review
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Abstract
Composition and functions of microbial communities affect important traits in diverse hosts, from crops to humans. Yet, mechanistic understanding of how metabolism of individual microbes is affected by the community composition and metabolite leakage is lacking. Here, we first show that the consensus of automatically generated metabolic reconstructions improves the quality of the draft reconstructions, measured by comparison to reference models. We then devise an approach for gap filling, termed COMMIT, that considers metabolites for secretion based on their permeability and the composition of the community. By applying COMMIT with two soil communities from the Arabidopsis thaliana culture collection, we could significantly reduce the gap-filling solution in comparison to filling gaps in individual reconstructions without affecting the genomic support. Inspection of the metabolic interactions in the soil communities allows us to identify microbes with community roles of helpers and beneficiaries. Therefore, COMMIT offers a versatile fully automated solution for large-scale modelling of microbial communities for diverse biotechnological applications.
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