Metabolic modeling of a chronic wound biofilm consortium predicts spatial partitioning of bacterial species. Issue 1 (December 2016)

• Record Type: Journal Article
• Authors: Phalak, Poonam; Chen, Jin; Carlson, Ross; Henson, Michael
• Is Part Of: BMC systems biology. Volume 10:Issue 1(2016)
• Page Start: 1
• Page End: 20
• Publication Date: 2016-12
• Subjects: Metabolic modeling -- Biofilms -- Wound infections; Biological systems -- Periodicals; Biology -- Research -- Periodicals; Cell physiology -- Periodicals; Genes -- Analysis -- Periodicals; 571
• DOI: 10.1186/s12918-016-0334-8
• Languages: English
• ISSNs: 1752-0509

Abstract

Abstract Background Chronic 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. Results We developed spatiotemporal models to investigate the multispecies metabolism of a biofilm consortium comprised of two common chronic wound isolates: the aerobePseudomonas aeruginosa and the facultative anaerobeStaphylococcus 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, withS. aureus most concentrated in the anaerobic region andP. aeruginosa present only in the aerobic region. The two species system was predicted to support a maximum biofilm thickness much greater thanP. aeruginosa alone but slightly less thanS. aureus alone, suggesting an antagonistic metabolic effect ofP. aeruginosa onS. aureus . When each species was allowed to enhance its growth through consumption of secreted metabolic byproducts assuming identical uptake kinetics, the competitiveness ofP. aeruginosa was further reduced due primarily to the more efficient lactate metabolism ofS. aureus . Lysis ofS. aureus by a small molecule inhibitor secreted fromP. aeruginosa and/orP. aeruginosa aerotaxis were predicted to substantially increaseP. aeruginosa competitiveness in the aerobic region, consistent with in vitro experimental studies. Conclusions Our 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 thatP. aeruginosa lysis ofS. aureus combined with nutrient competition is a particularly relevant scenario for which model predictions could be tested experimentally.