ArticleJournal of applied microbiology2019
Metabolic modelling of chronic wound microbiota predicts mutualistic interactions that drive community composition.
Article in Journal of applied microbiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it, 17 citations in OpenAlex.
- The gut-skin axis in wound healing: a bibliometric analysis of intestinal flora and chronic wounds (2005-2025).Frontiers in cellular and infection microbiology · 2026Pooled it
- Oxygen-dependent partitioning of acetate assimilation via Acs and AckA-Pta pathways inJournal of bacteriology · 2026Article
- Bacterial enzyme-responsive hydrogels for triggered delivery of antibiotics to infected wounds.Science advances · 2026Article
- Effect of microbial interactions on performance of community metabolic modeling algorithms: flux balance analysis (FBA), community FBA (cFBA) and SteadyCom.Bioprocess and biosystems engineering · 2024Article
- The wound microbiota: microbial mechanisms of impaired wound healing and infection.Nature reviews. Microbiology · 2024Review
- Logic programming-based Minimal Cut Sets reveal consortium-level therapeutic targets for chronic wound infections.NPJ systems biology and applications · 2024Article
- Bacterial Interactions in the Context of Chronic Wound Biofilm: A Review.Microorganisms · 2022Review
- The Chronic Wound Phageome: Phage Diversity and Associations with Wounds and Healing Outcomes.Microbiology spectrum · 2022Article
- Chronic Inflammation in Non-Healing Skin Wounds and Promising Natural Bioactive Compounds Treatment.International journal of molecular sciences · 2022Review
- Bacterial metabolism and pathogenesis intimate intertwining: time for metabolic modelling to come into action.Microbial biotechnology · 2022Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
aimsTo identify putative mutualistic interactions driving community composition in polymicrobial chronic wound infections using metabolic modelling. METHODS AND
resultsWe developed a 12 species metabolic model that covered 74% of 16S rDNA pyrosequencing reads of dominant genera from 2963 chronic wound patients. The community model was used to predict species abundances averaged across this large patient population. We found that substantially improved predictions were obtained when the model was constrained with genera prevalence data and predicted abundances were averaged over 5000 ensemble simulations with community participants randomly determined according to the experimentally determined prevalences. Staphylococcus and Pseudomonas were predicted to exhibit a strong mutualistic relationship that resulted in community growth rate and diversity simultaneously increasing, suggesting that these two common chronic wound pathogens establish dominance by cooperating with less harmful commensal species. In communities lacking one or both dominant pathogens, other mutualistic relationship including Staphylococcus/Acinetobacter, Pseudomonas/Serratia and Streptococcus/Enterococcus were predicted consistent with published experimental data.
conclusionsMutualistic interactions were predicted to be driven by crossfeeding of organic acids, alcohols and amino acids that could potentially be disrupted to slow chronic wound disease progression. SIGNIFICANCE AND IMPACT OF THE STUDY: Approximately 2% of the US population suffers from nonhealing chronic wounds infected by a combination of commensal and pathogenic bacteria. These polymicrobial infections are often resilient to antibiotic treatment due to the nutrient-rich wound environment and species interactions that promote community stability and robustness. The simulation results from this study were used to identify putative mutualistic interactions between bacteria that could be targeted to enhance treatment efficacy.
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