Dr. Simon van Vliet

Research Project  | 2 Project Members

Microbial infections are a leading cause of death and especially for chronic infections we still lack effective treatment strategies. To find new treatments, we first need a thorough understanding of the dynamics and functioning of the microbial communities that cause these chronic infections. In the past, bacterial pathogenesis has mostly been studied using single species grown in batch cultures. In contrast, many chronic infections are caused by multiple species growing in spatially structured biofilms. Interactions between these species can affect the growth, virulence, and stress tolerance of cells and can thus affect disease outcome, yet we still poorly understand these dynamics. Here, we will address this knowledge gap by studying how intra- and interspecies interactions affect the development and function of the multispecies biofilms that cause chronic lung infections. WE will focus on three species that often co-occur: the two major pathogens Pseudomonas aeruginosa and Staphylococcus aureus and the mucus-degrading commensal Streptococcus parasanguinis . Previous studies have found a complex set of interactions between these species. However, these interactions are not constant in space and time: each interaction has a different spatial range and is important during different phases of biofilm development, yet for most interactions these spatiotemporal properties have not been characterized. Moreover, we lack a quantitative approach to predict how these interactions combine to affect the development and function of biofilms. Here, we will use recent technological advances to measure the activity of cells in biofilms at high spatiotemporal resolution to characterize the spatiotemporal properties of intra- and interspecies interactions. Moreover, we will develop a quantitative framework to predict how these interactions combine to affect the development, virulence gene expression, and antibiotic tolerance of the biofilms that cause chronic infections. We will use a combination of single-cell microscopy and transcriptomics to characterize the spatiotemporal properties of known intra- and interspecies interactions and to identify novel interactions. We will integrate these interactions in a mathematical model which will allow us to identify which interactions have the strongest effects on biofilm development, virulence gene expression, and antibiotic tolerance. By identifying these interactions, we could potentially identify new strategies that can be used to suppress biofilm development or to reduce antibiotic tolerance. Moreover, the concepts and approaches developed here can help us better understand how cell-cell interactions affect the development and function of other microbial communities that play important roles in health and disease, industry, and the environment.