ArticleJournal of the Royal Society, Interface2019
Metabolite-mediated modelling of microbial community dynamics captures emergent behaviour more effectively than species-species modelling.
Article in Journal of the Royal Society, Interface, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Toward the Next Generation of In Silico Modeling of Dynamic Host-Microbiota Interactions in the Skin.JID innovations : skin science from molecules to population health · 2025Review
- Diagnosing and engineering gut microbiomes.EMBO molecular medicine · 2024Review
- Article
- Inferring microbial interactions with their environment from genomic and metagenomic data.PLoS computational biology · 2023Article
- Article
- Structural Identifiability and Observability of Microbial Community Models.Bioengineering (Basel, Switzerland) · 2023Article
- Controlling the human microbiome.Cell systems · 2023Review
- Competition for nutrients increases invasion resistance during assembly of microbial communities.Molecular ecology · 2022Article
- Ecological modelling approaches for predicting emergent properties in microbial communities.Nature ecology & evolution · 2022Review
- Chemical-Mediated Microbial Interactions Can Reduce the Effectiveness of Time-Series-Based Inference of Ecological Interaction Networks.International journal of environmental research and public health · 2022Article
- Minimizing the number of optimizations for efficient community dynamic flux balance analysis.PLoS computational biology · 2020Article
- Modeling microbial cross-feeding at intermediate scale portrays community dynamics and species coexistence.PLoS computational biology · 2020Article
- Experimental and computational approaches to unravel microbial community assembly.Computational and structural biotechnology journal · 2020Review
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
Personalized models of the gut microbiome are valuable for disease prevention and treatment. For this, one requires a mathematical model that predicts microbial community composition and the emergent behaviour of microbial communities. We seek a modelling strategy that can capture emergent behaviour when built from sets of universal individual interactions. Our investigation reveals that species-metabolite interaction (SMI) modelling is better able to capture emergent behaviour in community composition dynamics than direct species-species modelling. Using publicly available data, we examine the ability of species-species models and species-metabolite models to predict trio growth experiments from the outcomes of pair growth experiments. We compare quadratic species-species interaction models and quadratic SMI models and conclude that only species-metabolite models have the necessary complexity to explain a wide variety of interdependent growth outcomes. We also show that general species-species interaction models cannot match the patterns observed in community growth dynamics, whereas species-metabolite models can. We conclude that species-metabolite modelling will be important in the development of accurate, clinically useful models of microbial communities.
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Registered trials
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