Project description:Multispecies biofilms are the predominant form of bacterial growth in natural and human-associated environments. Although the pathways involved in monospecies biofilm have been well characterized, less is known about the metabolic pathways and emergent traits of a multispecies biofilm community. Here, we performed a transcriptome survey of the developmental stages of a 3-species biofilm community and combined it with quantitative imaging and growth experiments. We report the remodelling of central metabolism of two of the three species in this community. Specifically, we observed an increase in the expression of genes associated with glycolysis and pentose phosphate pathways in K. pneumoniae. Similarly, a decrease in the expression of the same pathways in P. protegens was observed along with an increase in expression of glyoxalate cycle genes when grown as a mixed species biofilm, suggesting reorganisation of metabolic pathways and metabolite sharing for the community biofilms. To test the possibility of cross-feeding for the community, planktonic growth experiments revealed that both the Pseudomonads grew well in TCA cycle intermediates, while K. pneumoniae grew poorly when given those carbon sources. Despite this poor growth in mono-culture, K. pneumoniae was still the dominant species in mixed species biofilms cultivated in TCA intermediates as the sole source of carbon. The biofilm growth data, combined with the transcriptomics data, suggests there is reorganisation of metabolism for the community members and may allow for cross-feeding that allows K. pneumoniae to dominate the community. We also demonstrated that sdsA1 of P. aeruginosa was induced upon exposure to the surfactant SDS and that this gene was essential in protecting mono and mixed species biofilms from surfactant stress. This also suggests that the community members can share defence mechanisms. Overall, this study describes a comprehensive transcriptomics level investigation of shared resources, metabolites and stress defence that may underpin the emergent properties of mixed species biofilm communities.
Project description:We developed a spatially resolved method to profile the spatial transcriptome of biofilm. In detail, we used fluorescent dyes to label the different regions of biofilm cultured in a microfluidic chip. After staining, the bacterial cells in biofilm were sorted into relevant bins according to their spatial information marked by the fluorescent pattern. Finally, miniBac-seq (RNA-seq) method was applied to capture the transcriptome of each bin.
Project description:Biofilm formation is an important mechanism of survival and persistence for many bacterial pathogens. These multicellular communities contain subpopulations of cells that display vast metabolic and transcriptional diversity along with high recalcitrance to antibiotics and host immune defenses. Investigating the complex heterogeneity within biofilm has been hindered by the lack of a sensitive and high-throughput method to assess stochastic transcriptional activity and regulation between bacterial subpopulations, which requires single-cell resolution. We have developed an optimized bacterial single-cell RNA sequencing method, BaSSSh-seq, to study Staphylococcus aureus diversity during biofilm growth and transcriptional adaptations following immune cell exposure.
Project description:Prolific heterotrophic biofilm growth is a common occurrence in airport receiving streams containing deicer and anti-icer runoff. This study investigated relations of heterotrophic biofilm prevalence and community composition to environmental conditions at stream sites upstream and downstream of Milwaukee Mitchell International Airport in Milwaukee, WI, during two deicing seasons (2009–2010 and 2010–2011). Modern genetic tools (such as microarray) have not previously been applied to biofilm communities in this type of setting. We used microarray results to characterize biofilm community composition as well as the response of the biofilm community to environmental factors (i.e., organic content (using chemical oxygen demand concentration) and temperature).