ArticleBMC bioinformatics2024
Flux sampling in genome-scale metabolic modeling of microbial communities.
Article in BMC bioinformatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 19 citations in OpenAlex.
- Atomic elementary flux modes explain the steady state flow of metabolites in large-scale flux networks.Cell reports methods · 2026Article
- Flux sampling and graph neural networks for improved gene essentiality prediction in mammalian genome-scale metabolic models.NPJ systems biology and applications · 2026Article
- Cancer-associated fibroblasts drive metabolic heterogeneity in colorectal cancer cells: predictions from metabolic modeling.NPJ systems biology and applications · 2026Article
- Modeling Microbiome Modulation of Tumor Metabolic Networks to Predict Synergistic Therapies.bioRxiv : the preprint server for biology · 2026Article
- Flux sampling and context-specific genome-scale metabolic models for biotechnological applications.Trends in biotechnology · 2026Review
- DMoVGPE: predicting gut microbial associated metabolites profiles with deep mixture of variational Gaussian Process experts.BMC bioinformatics · 2025Article
- Metabolic modeling of host-microbe interactions.Computational and structural biotechnology journal · 2025Review
- Comparative analysis of metabolic models of microbial communities reconstructed from automated tools and consensus approaches.NPJ systems biology and applications · 2024Article
- Integrating Genome-Scale Metabolic Models with Patient Plasma Metabolome to Study Endothelial Metabolism In Situ.International journal of molecular sciences · 2024Article
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3 authors at 1 institution in 1 country.
Funding
Abstract
backgroundMicrobial communities play a crucial role in ecosystem function through metabolic interactions. Genome-scale modeling is a promising method to understand these interactions and identify strategies to optimize the community. Flux balance analysis (FBA) is most often used to predict the flux through all reactions in a genome-scale model; however, the fluxes predicted by FBA depend on a user-defined cellular objective. Flux sampling is an alternative to FBA, as it provides the range of fluxes possible within a microbial community. Furthermore, flux sampling can capture additional heterogeneity across a population, especially when cells exhibit sub-maximal growth rates.
resultsIn this study, we simulate the metabolism of microbial communities and compare the metabolic characteristics found with FBA and flux sampling. With sampling, we find significant differences in the predicted metabolism, including an increase in cooperative interactions and pathway-specific changes in predicted flux.
conclusionsOur results suggest the importance of sampling-based approaches to evaluate metabolic interactions. Furthermore, we emphasize the utility of flux sampling in quantitatively studying interactions between cells and organisms.
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