ArticleBioinformatics (Oxford, England)2024
BN-BacArena: Bayesian network extension of BacArena for the dynamic simulation of microbial communities.
Article in Bioinformatics (Oxford, England), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Probiotic-Plant Bioactive Synergy in Gut Health: Mechanisms, Antimicrobial Activity, and Translational Challenges.Nutrients · 2026Review
- Article
- Evaluating changes in attractor sets under small network perturbations to infer reliable microbial interaction networks from abundance patterns.Bioinformatics (Oxford, England) · 2025Article
- Recent advances in precision nutrition and cardiometabolic diseases.Revista espanola de cardiologia (English ed.) · 2025Review
- DRpred: A Novel Deep Learning-Based Predictor for Multi-Label mRNA Subcellular Localization Prediction by Incorporating Bayesian Inferred Prior Label Relationships.Biomolecules · 2024Article
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Authors and funding
9 authors.
Funding
Abstract
motivationSimulating gut microbial dynamics is extremely challenging. Several computational tools, notably the widely used BacArena, enable modeling of dynamic changes in the microbial environment. These methods, however, do not comprehensively account for microbe-microbe stimulant or inhibitory effects or for nutrient-microbe inhibitory effects, typically observed in different compounds present in the daily diet.
resultsHere, we present BN-BacArena, an extension of BacArena consisting on the incorporation within the native computational framework of a Bayesian network model that accounts for microbe-microbe and nutrient-microbe interactions. Using in vitro experiments, 16S rRNA gene sequencing data and nutritional composition of 55 foods, the output Bayesian network showed 23 significant nutrient-bacteria interactions, suggesting the importance of compounds such as polyols, ascorbic acid, polyphenols and other phytochemicals, and 40 bacteria-bacteria significant relationships. With test data, BN-BacArena demonstrates a statistically significant improvement over BacArena to predict the time-dependent relative abundance of bacterial species involved in the gut microbiota upon different nutritional interventions. As a result, BN-BacArena opens new avenues for the dynamic modeling and simulation of the human gut microbiota metabolism. AVAILABILITY AND IMPLEMENTATION: MATLAB and R code are available in https://github.com/PlanesLab/BN-BacArena.
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