ArticleBMC systems biology2016
Metabolic modeling of a chronic wound biofilm consortium predicts spatial partitioning of bacterial species.
Article in BMC systems biology, 2016. 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, 64 citations in OpenAlex.
- Artificial intelligence applications in biofilm research: computational approaches for biofilm analysis and antimicrobial prediction.Frontiers in microbiology · 2026Review
- Coupling flux balance analysis with reactive transport modeling through machine learning for rapid and stable simulation of microbial metabolic switching.Scientific reports · 2025Article
- Towards improved biofilm models.Nature reviews. Microbiology · 2025Review
- Article
- Logic programming-based Minimal Cut Sets reveal consortium-level therapeutic targets for chronic wound infections.NPJ systems biology and applications · 2024Article
- From microbiome composition to functional engineering, one step at a time.Microbiology and molecular biology reviews : MMBR · 2023Review
- Article
- The Use of Interdisciplinary Approaches to Understand the Biology ofMicroorganisms · 2022Review
- Milieu matters: AnBiofilm · 2021Article
- Integrating Systems and Synthetic Biology to Understand and Engineer Microbiomes.Annual review of biomedical engineering · 2021Review
- Pseudomonas aeruginosa reverse diauxie is a multidimensional, optimized, resource utilization strategy.Scientific reports · 2021Article
- Metabolic modelling approaches for describing and engineering microbial communities.Computational and structural biotechnology journal · 2021Review
- Metabolic Modeling to Interrogate Microbial Disease: A Tale for Experimentalists.Frontiers in molecular biosciences · 2021Review
- Advances in flux balance analysis by integrating machine learning and mechanism-based models.Computational and structural biotechnology journal · 2021Review
- Staphylococcal Biofilm Development: Structure, Regulation, and Treatment Strategies.Microbiology and molecular biology reviews : MMBR · 2020Review
- Quorum sensing-induced phenotypic switching as a regulatory nutritional stress response in a competitive two-species biofilm: An individual-based cellular automata model.Journal of biosciences · 2020Article
- High Levels of Oxidative Stress Create a Microenvironment That Significantly Decreases the Diversity of the Microbiota in Diabetic Chronic Wounds and Promotes Biofilm Formation.Frontiers in cellular and infection microbiology · 2020Article
- Challenges of biofilm control and utilization: lessons from mathematical modelling.Journal of the Royal Society, Interface · 2019Article
- Characterization of Mixed-Species Biofilm Formed byFrontiers in microbiology · 2019Article
- Review and perspective on mathematical modeling of microbial ecosystems.Biochemical Society transactions · 2018Review
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundChronic wounds are often colonized by consortia comprised of different bacterial species growing as biofilms on a complex mixture of wound exudate. Bacteria growing in biofilms exhibit phenotypes distinct from planktonic growth, often rendering the application of antibacterial compounds ineffective. Computational modeling represents a complementary tool to experimentation for generating fundamental knowledge and developing more effective treatment strategies for chronic wound biofilm consortia.
resultsWe developed spatiotemporal models to investigate the multispecies metabolism of a biofilm consortium comprised of two common chronic wound isolates: the aerobe Pseudomonas aeruginosa and the facultative anaerobe Staphylococcus aureus. By combining genome-scale metabolic reconstructions with partial differential equations for metabolite diffusion, the models were able to provide both temporal and spatial predictions with genome-scale resolution. The models were used to analyze the metabolic differences between single species and two species biofilms and to demonstrate the tendency of the two bacteria to spatially partition in the multispecies biofilm as observed experimentally. Nutrient gradients imposed by supplying glucose at the bottom and oxygen at the top of the biofilm induced spatial partitioning of the two species, with S. aureus most concentrated in the anaerobic region and P. aeruginosa present only in the aerobic region. The two species system was predicted to support a maximum biofilm thickness much greater than P. aeruginosa alone but slightly less than S. aureus alone, suggesting an antagonistic metabolic effect of P. aeruginosa on S. aureus. When each species was allowed to enhance its growth through consumption of secreted metabolic byproducts assuming identical uptake kinetics, the competitiveness of P. aeruginosa was further reduced due primarily to the more efficient lactate metabolism of S. aureus. Lysis of S. aureus by a small molecule inhibitor secreted from P. aeruginosa and/or P. aeruginosa aerotaxis were predicted to substantially increase P. aeruginosa competitiveness in the aerobic region, consistent with in vitro experimental studies.
conclusionsOur biofilm modeling approach allows the prediction of individual species metabolism and interspecies interactions in both time and space with genome-scale resolution. This study yielded new insights into the multispecies metabolism of a chronic wound biofilm, in particular metabolic factors that may lead to spatial partitioning of the two bacterial species. We believe that P. aeruginosa lysis of S. aureus combined with nutrient competition is a particularly relevant scenario for which model predictions could be tested experimentally.
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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.