ArticlePloS one2017
Model-based quantification of metabolic interactions from dynamic microbial-community data.
Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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Who cites it
25 citing papers in PubMed.
- AlphaGEM enables precise genome-scale metabolic modelling by integrating protein structure alignment with deep-learning-based dark metabolism mining.Nature communications · 2026Article
- Constraint-Based Metabolic Modeling Approach for Microbial Communities.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Moving from genome-scale to community-scale metabolic models for the human gut microbiome.Nature microbiology · 2025Review
- Article
- Applications of genome-scale metabolic models to investigate microbial metabolic adaptations in response to genetic or environmental perturbations.Briefings in bioinformatics · 2023Review
- Conversion of Carbon Monoxide to Chemicals Using Microbial Consortia.Advances in biochemical engineering/biotechnology · 2022Article
- Constraint-Based Reconstruction and Analyses of Metabolic Models: Open-Source Python Tools and Applications to Cancer.Frontiers in oncology · 2022Review
- Review
- GPRuler: Metabolic gene-protein-reaction rules automatic reconstruction.PLoS computational biology · 2021Article
- Genome Scale Modeling to Study the Metabolic Competition between Cells in the Tumor Microenvironment.Cancers · 2021Review
- gapseq: informed prediction of bacterial metabolic pathways and reconstruction of accurate metabolic models.Genome biology · 2021Article
- Predicting microbial growth dynamics in response to nutrient availability.PLoS computational biology · 2021Article
- Addressing uncertainty in genome-scale metabolic model reconstruction and analysis.Genome biology · 2021Review
- Novel antimicrobial development using genome-scale metabolic model of Gram-negative pathogens: a review.The Journal of antibiotics · 2021Review
- Metabolic modelling approaches for describing and engineering microbial communities.Computational and structural biotechnology journal · 2021Review
- Dynamic co-culture metabolic models reveal the fermentation dynamics, metabolic capacities and interplays of cheese starter cultures.Biotechnology and bioengineering · 2021Article
- Modeling microbial cross-feeding at intermediate scale portrays community dynamics and species coexistence.PLoS computational biology · 2020Article
- Metabolic Modelling as a Framework for Metabolomics Data Integration and Analysis.Metabolites · 2020Review
- ReCodLiver0.9: Overcoming Challenges in Genome-Scale Metabolic Reconstruction of a Non-model Species.Frontiers in molecular biosciences · 2020Article
- A systematic assessment of current genome-scale metabolic reconstruction tools.Genome biology · 2019Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
An important challenge in microbial ecology is to infer metabolic-exchange fluxes between growing microbial species from community-level data, concerning species abundances and metabolite concentrations. Here we apply a model-based approach to integrate such experimental data and thereby infer metabolic-exchange fluxes. We designed a synthetic anaerobic co-culture of Clostridium acetobutylicum and Wolinella succinogenes that interact via interspecies hydrogen transfer and applied different environmental conditions for which we expected the metabolic-exchange rates to change. We used stoichiometric models of the metabolism of the two microorganisms that represents our current physiological understanding and found that this understanding - the model - is sufficient to infer the identity and magnitude of the metabolic-exchange fluxes and it suggested unexpected interactions. Where the model could not fit all experimental data, it indicates specific requirement for further physiological studies. We show that the nitrogen source influences the rate of interspecies hydrogen transfer in the co-culture. Additionally, the model can predict the intracellular fluxes and optimal metabolic exchange rates, which can point to engineering strategies. This study therefore offers a realistic illustration of the strengths and weaknesses of model-based integration of heterogenous data that makes inference of metabolic-exchange fluxes possible from community-level experimental data.
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