ArticlePLoS computational biology2023
Genome-scale metabolic modeling of the human gut bacterium Bacteroides fragilis strain 638R.
Article in PLoS computational biology, 2023. 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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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
6 citing papers in PubMed, 10 citations in OpenAlex.
- Integrated metabolomics and metagenomics reveal divergent caecal metabolic signatures following commercial gut health interventions in broilers.Animal microbiome · 2026Article
- An anaerobic pathogen rewires host metabolism to fuel oxidative growth in the inflamed gut.Cell · 2026Article
- Integrative systems biology approaches for analyzing microbiome dysbiosis and species interactions.Briefings in bioinformatics · 2025Review
- Effects ofFoods (Basel, Switzerland) · 2025Article
- Targeted isolation of Methanobrevibacter strains from fecal samples expands the cultivated human archaeome.Nature communications · 2024Article
- PathogenicbioRxiv : the preprint server for biology · 2024Article
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
Bacteroides fragilis is a universal member of the dominant commensal gut phylum Bacteroidetes. Its fermentation products and abundance have been linked to obesity, inflammatory bowel disease, and other disorders through its effects on host metabolic regulation and the immune system. As of yet, there has been no curated systems-level characterization of B. fragilis' metabolism that provides a comprehensive analysis of the link between human diet and B. fragilis' metabolic products. To address this, we developed a genome-scale metabolic model of B. fragilis strain 638R. The model iMN674 contains 1,634 reactions, 1,362 metabolites, three compartments, and reflects the strain's ability to utilize 142 metabolites. Predictions made with this model include its growth rate and efficiency on these substrates, the amounts of each fermentation product it produces under different conditions, and gene essentiality for each biomass component. The model highlights and resolves gaps in knowledge of B. fragilis' carbohydrate metabolism and its corresponding transport proteins. This high quality model provides the basis for rational prediction of B. fragilis' metabolic interactions with its environment and its host.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.