Biofilms are microbial communities encased in a layer of extracellular polymeric substances (EPS). The EPS matrix provides several functional purposes for the biofilm, such as protecting bacteria from environmental stresses, and providing mechanical stability. Quorum sensing is a cell-cell communication mechanism used by several bacterial taxa to coordinate gene expression and behaviour in groups, based on population densities.

A central question to biology is how pathogenic bacteria initiate acute or chronic infections. Here we describe a genetic program for cell-fate decision in the opportunistic human pathogen Staphylococcus aureus, which generates the phenotypic bifurcation of the cells into two genetically identical but different cell types during the course of an infection. Whereas one cell type promotes the formation of biofilms that contribute to chronic infections, the second type is planktonic and produces the toxins that contribute to acute bacteremia. We identified a bimodal switch in the agr quorum sensing system that antagonistically regulates the differentiation of these two physiologically distinct cell types. We found that extracellular signals affect the behavior of the agr bimodal switch and modify the size of the specialized subpopulations in specific colonization niches. For instance, magnesium-enriched colonization niches causes magnesium binding to S. aureusteichoic acids and increases bacterial cell wall rigidity. This signal triggers a genetic program that ultimately downregulates the agr bimodal switch. Colonization niches with different magnesium concentrations influence the bimodal system activity, which defines a distinct ratio between these subpopulations; this in turn leads to distinct infection outcomes in vitro and in an in vivo murine infection model. Cell differentiation generates physiological heterogeneity in clonal bacterial infections and helps to determine the distinct infection types.

Autoinducer signals enable coordinated behaviour of bacterial populations, a phenomenon originally described as quorum sensing. Autoinducer systems are often controlled by environmental substances as nutrients or secondary metabolites (signals) from neighbouring organisms. In cell aggregates and biofilms gradients of signals and environmental substances emerge. Mathematical modelling is used to analyse the functioning of the system. We find that the autoinducer regulation network generates spatially heterogeneous behaviour, up to a kind of multicellularity-like division of work, especially under nutrient-controlled conditions. A hybrid push/pull concept is proposed to explain the ecological function. The analysis allows to explain hitherto seemingly contradicting experimental findings.

Diabetes mellitus is a group of metabolic diseases with increased blood glucose concentration as the main symptom. This can be caused by a relative or a total lack of insulin which is produced by the β-cells in the pancreatic islets of Langerhans. Recent experimental results indicate the relevance of the β-cell cycle for the development of diabetes mellitus. This paper introduces a mathematical model that connects the dynamics of glucose and insulin concentration with the β-cell cycle. The interplay of glucose, insulin, and β-cell cycle is described with a system of ordinary differential equations. The model and its development will be presented as well as its mathematical analysis. The latter investigates the steady states of the model and their stability. Our model shows the connection of glucose and insulin concentrations to the β-cell cycle. In this way the important role of glucose as regulator of the cell cycle and the capability of the β-cell mass to adapt to metabolic demands can be presented. Simulations of the model correspond to the qualitative behavior of the glucose-insulin regulatory system showed in biological experiments. This work focus on modeling the physiological situation of the glucose-insulin regulatory system with a detailed consideration of the β-cell cycle. Furthermore, the presented model allows the simulation of pathological scenarios. Modification of different parameters results in simulation of either type 1 or type 2 diabetes.

Quorum sensing is a widespread process in bacteria that controls collective behaviours in response to cell density. Populations of cells coordinate gene expression through the perception of self-produced chemical signals. Although this process is well-characterized genetically and biochemically, quantitative information about network properties, including induction dynamics and steady-state behaviour, is scarce. Here we integrate experiments with mathematical modelling to quantitatively analyse the LasI/LasR quorum sensing pathway in the opportunistic pathogen Pseudomonas aeruginosa . We determine key kinetic parameters of the pathway and, using the parametrized model, show that quorum sensing behaves as a bistable hysteretic switch, with stable on and off states. We investigate the significance of feedback architecture and find that positive feedback on signal production is critical for induction dynamics and bistability, whereas positive feedback on receptor expression and negative feedback on signal production play a minor role. Taken together, our data-based modelling approach reveals fundamental and emergent properties of a bacterial quorum sensing circuit, and provides evidence that native quorum sensing can indeed function as the gene expression switch it is commonly perceived to be.