Center for Biofilm Engineering (CBE)
Permanent URI for this communityhttps://scholarworks.montana.edu/handle/1/9334
At the Center for Biofilm Engineering (CBE), multidisciplinary research teams develop beneficial uses for microbial biofilms and find solutions to industrially relevant biofilm problems. The CBE was established at Montana State University, Bozeman, in 1990 as a National Science Foundation Engineering Research Center. As part of the MSU College of Engineering, the CBE gives students a chance to get a head start on their careers by working on research teams led by world-recognized leaders in the biofilm field.
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Item Experimental Designs to Study the Aggregation and Colonization of Biofilms by Video Microscopy With Statistical Confidenc(Frontiers Media SA, 2022-01) Pettygrove, Brian A.; Smith, Heidi J.; Pallister, Kyler B.; Voyich, Jovanka M.; Stewart, Philip S.; Parker, Albert E.The goal of this study was to quantify the variability of confocal laser scanning microscopy (CLSM) time-lapse images of early colonizing biofilms to aid in the design of future imaging experiments. To accomplish this a large imaging dataset consisting of 16 independent CLSM microscopy experiments was leveraged. These experiments were designed to study interactions between human neutrophils and single cells or aggregates of Staphylococcus aureus (S. aureus) during the initial stages of biofilm formation. Results suggest that in untreated control experiments, variability differed substantially between growth phases (i.e., lag or exponential). When studying the effect of an antimicrobial treatment (in this case, neutrophil challenge), regardless of the inoculation level or of growth phase, variability changed as a frown-shaped function of treatment efficacy (i.e., the reduction in biofilm surface coverage). These findings were used to predict the best experimental designs for future imaging studies of early biofilms by considering differing (i) numbers of independent experiments; (ii) numbers of fields of view (FOV) per experiment; and (iii) frame capture rates per hour. A spreadsheet capable of assessing any user-specified design is included that requires the expected mean log reduction and variance components from user-generated experimental results. The methodology outlined in this study can assist researchers in designing their CLSM studies of antimicrobial treatments with a high level of statistical confidence.Item Multiscale Flux-Based Modeling of Biofilm Communities(Society for Industrial & Applied Mathematics, 2020-01) Zhang, T.; Parker, A.; Carlson, R.P.; Stewart, Philip S.; Klapper, I.Models of microbial community dynamics generally rely on a subscale description for microbial metabolisms. In systems such as distributed multispecies communities like biofilms, where it may not be reasonable to simplify to a small number of limiting substrates, tracking the large number of active metabolites likely requires measurement or estimation of large numbers of kinetic and regulatory parameters. Alternatively, a largely kinetics-free framework is proposed combining cellular level constrained, steady state flux analysis of metabolism with macroscale microbial community models. This multiscale setup naturally allows coupling of macroscale information, including measurement data, with cell scale metabolism. Further, flexibility in methodology is stressed: choices at the microscale (e.g., flux balance analysis or elementary flux modes) and at the macroscale (e.g., physical-chemical influences relevant to biofilm or planktonic environments) are available to the user. Illustrative computations in the context of a biofilm, including comparisons of systemic and Nash equilibration as well as an example of coupling experimental data into predictions, are provided.Item Physiology of Pseudomonas aeruginosa in biofilms as revealed by transcriptome analysis(2010) Folsom, James P.; Richards, Lee A.; Roe, Frank L.; Ehrlich, Garth D.; Parker, Albert E.; Mazurie, Aurélien J.; Stewart, Philip S.BACKGROUND: Transcriptome analysis was applied to characterize the physiological activities of Pseudomonas aeruginosa grown for three days in drip-flow biofilm reactors. Conventional applications of transcriptional profiling often compare two paired data sets that differ in a single experimentally controlled variable. In contrast this study obtained the transcriptome of a single biofilm state, ranked transcript signals to make the priorities of the population manifest, and compared rankings for a priori identified physiological marker genes between the biofilm and published data sets.RESULTS: Biofilms tolerated exposure to antibiotics, harbored steep oxygen concentration gradients, and exhibited stratified and heterogeneous spatial patterns of protein synthetic activity. Transcriptional profiling was performed and the signal intensity of each transcript was ranked to gain insight into the physiological state of the biofilm population. Similar rankings were obtained from data sets published in the GEO database (www.ncbi.nlm.nih.gov/geo). By comparing the rank of genes selected as markers for particular physiological activities between the biofilm and comparator data sets, it was possible to infer qualitative features of the physiological state of the biofilm bacteria. These biofilms appeared, from their transcriptome, to be glucose nourished, iron replete, oxygen limited, and growing slowly or exhibiting stationary phase character. Genes associated with elaboration of type IV pili were strongly expressed in the biofilm. The biofilm population did not indicate oxidative stress, homoserine lactone mediated quorum sensing, or activation of efflux pumps. Using correlations with transcript ranks, the average specific growth rate of biofilm cells was estimated to be 0.08 h-1.CONCLUSIONS: Collectively these data underscore the oxygen-limited, slow-growing nature of the biofilm population and are consistent with antimicrobial tolerance due to low metabolic activity.Item Reaction-diffusion theory explains hypoxia and heterogeneous growth within microbial biofilms associated with chronic infections(2016-06) Stewart, Philip S.; Zhang, Tian-Yu; Xu, Ruifang; Pitts, Betsey; Walters, Marshall C., III; Roe, Frank L.; Kikhney, Judith; Moter, AnnetteReaction–diffusion models were applied to gain insight into the aspects of biofilm infection and persistence by comparing mathematical simulations with the experimental data from varied bacterial biofilms. These comparisons, including three in vitro systems and two clinical investigations of specimens examined ex vivo, underscored the central importance of concentration gradients of metabolic substrates and the resulting physiological heterogeneity of the microorganisms. Relatively simple one-dimensional and two-dimensional (2D) models captured the: (1) experimentally determined distribution of specific growth rates measured in Pseudomonas aeruginosa cells within sputum from cystic fibrosis patients; (2) pattern of relative growth rate within aggregates of streptococcal biofilm harboured in an endocarditis vegetation; (3) incomplete penetration of oxygen into a Pseudomonas aeruginosa biofilm under conditions of exposure to ambient air and also pure oxygen; (4) localisation of anabolic activity around the periphery of P. aeruginosa cell clusters formed in a flow cell and attribution of this pattern to iron limitation; (5) very low specific growth rates, as small as 0.025 h−1, in the interior of cell clusters within a Klebsiella pneumoniae biofilm in a complex 2D domain of variable cell density.Item Robustness analysis of culturing perturbations on Escherichia coli colony biofilm beta-lactam and aminoglycoside antibiotic tolerance(2010-07) Zuroff, Trevor R.; Bernstein, Hans C.; Lloyd-Randolfi, J.; Jimenez-Taracido, L.; Stewart, Philip S.; Carlson, Ross P.BACKGROUND: Biofilms are ubiquitous. For instance, the majority of medical infections are thought to involve biofilms. However even after decades of investigation, the in vivo efficacy of many antimicrobial strategies is still debated, suggesting there is a need for better understanding of biofilm antimicrobial tolerances. The current study's goal is to characterize the robustness of biofilm antibiotic tolerance to medically and industrially relevant culturing perturbations. By definition, robust systems will return similar, predictable responses when perturbed, while non-robust systems will return very different, and potentially unpredictable, responses. The predictability of an antibiotic tolerance response is essential to developing, testing, and employing antimicrobial strategies. RESULTS: The antibiotic tolerance of Escherichia coli colony biofilms was tested against beta-lactam and aminoglycoside class antibiotics. Control scenario tolerances were compared to tolerances under culturing perturbations including 1) different nutritional environments 2) different temperatures 3) interruption of cellular quorum sensing and 4) different biofilm culture ages. Here, antibiotic tolerance was defined in terms of culturable biofilm cells recovered after a twenty four hour antibiotic treatment.Colony biofilm antibiotic tolerances were not robust to perturbations. Altering basic culturing parameters like nutritional environment or temperature resulted in very different, non-intuitive antibiotic tolerance responses. Some minor perturbations—like increasing the glucose concentration from 0.1 to 1 g/L—caused a ten-million fold difference in culturable cells over a twenty four hour antibiotic treatment. CONCLUSIONS: The current study presents a basis for robustness analysis of biofilm antibiotic tolerance. Biofilm antibiotic tolerance can vary in unpredictable manners based on modest changes in culturing conditions. Common antimicrobial testing methods, which only consider a single culturing condition, are not desirable since slight culturing variations can lead to very different outcomes. The presented data suggest it is essential to test antimicrobial strategies over a range of culturing perturbations relevant to the targeted application. In addition, the highly dynamic antibiotic tolerance responses observed here may explain why some current antimicrobial strategies occasionally fail.Item General theory for integrated analysis of growth, gene, and protein expression in biofilms(2013-12) Zhang, Tian-Yu; Pabst, Breana; Klapper, Isaac; Stewart, Philip S.A theory for analysis and prediction of spatial and temporal patterns of gene and protein expression within microbial biofilms is derived. The theory integrates phenomena of solute reaction and diffusion, microbial growth, mRNA or protein synthesis, biomass advection, and gene transcript or protein turnover. Case studies illustrate the capacity of the theory to simulate heterogeneous spatial patterns and predict microbial activities in biofilms that are qualitatively different from those of planktonic cells. Specific scenarios analyzed include an inducible GFP or fluorescent protein reporter, a denitrification gene repressed by oxygen, an acid stress response gene, and a quorum sensing circuit. It is shown that the patterns of activity revealed by inducible stable fluorescent proteins or reporter unstable proteins overestimate the region of activity. This is due to advective spreading and finite protein turnover rates. In the cases of a gene induced by either limitation for a metabolic substrate or accumulation of a metabolic product, maximal expression is predicted in an internal stratum of the biofilm. A quorum sensing system that includes an oxygen-responsive negative regulator exhibits behavior that is distinct from any stage of a batch planktonic culture. Though here the analyses have been limited to simultaneous interactions of up to two substrates and two genes, the framework applies to arbitrarily large networks of genes and metabolites. Extension of reaction-diffusion modeling in biofilms to the analysis of individual genes and gene networks is an important advance that dovetails with the growing toolkit of molecular and genetic experimental techniques.Item Development of a laboratory model of a phototroph-heterotroph mixed-species biofilm at the stone/air interface(2015-11) Villa, Federica; Pitts, Betsey; Lauchnor, Ellen G.; Cappitelli, Francesca; Stewart, Philip S.Recent scientific investigations have shed light on the ecological importance and physiological complexity of subaerial biofilms (SABs) inhabiting lithic surfaces. In the field of sustainable cultural heritage (CH) preservation, mechanistic approaches aimed at investigation of the spatiotemporal patterns of interactions between the biofilm, the stone, and the atmosphere are of outstanding importance. However, these interactions have proven difficult to explore with field experiments due to the inaccessibility of samples, the complexity of the ecosystem under investigation and the temporal resolution of the experiments. To overcome these limitations, we aimed at developing a unifying methodology to reproduce a fast-growing, phototroph-heterotroph mixed species biofilm at the stone/air interface. Our experiments underscore the ability of the dual-species SAB model to capture functional traits characteristic of biofilms inhabiting lithic substrate such as: (i) microcolonies of aggregated bacteria; (ii) network like structure following surface topography; (iii) cooperation between phototrophs and heterotrophs and cross feeding processes; (iv) ability to change the chemical parameters that characterize the microhabitats; (v) survival under desiccation and (vi) biocide tolerance. With its advantages in control, replication, range of different experimental scenarios and matches with the real ecosystem, the developed model system is a powerful tool to advance our mechanistic understanding of the stone-biofilm-atmosphere interplay in different environments.