Background

Infectious diseases are a major worldwide threat. Novel control strategies are urgently required but rational development of such strategies is impaired by the complexity of multifactorial host-pathogen interactions. Pathogen heterogeneity in infected tissues is one aspect of this complexity that has major impacts on course of infection and efficacy of antibiotic treatments. In a mouse Salmonella infection model for human typhoid fever, Salmonella growth is partially controlled in mature neutrophil-rich infection foci but new infection foci are continuously established at high rate. Mechanisms that are responsible for this heterogeneous growth dynamic are unclear.

Working Hypothesis

We will test the hypothesis that complex host mechanisms contribute to Salmonella growth control in mature infection foci.

Specific Aims

(i)        To determine the role of candidate control mechanisms in mature infection foci including ROS/RNS stress, oxygen limitation and differential nutrient availability (2.3.2);

(ii)      to use these data to build a metabolic network reconstruction for Salmonella in mature foci that predicts additional perturbations for extensive validation of relevant mechanisms (2.3.3);

(iii)    to obtain complementary unbiased information on additional control mechanisms in mature foci using Salmonella proteomics, network analysis, and functional validation using mutants (2.3.4).

Experimental Design and Methods

We will test three likely candidate mechanisms using Salmonella mutants that are highly susceptible to such control mechanisms. More severe mutant phenotypes in mature compared to new infection foci would provide evidence for a potential involvement of the respective mechanisms. We will integrate the resulting data in a genome-scale Salmonella reconstruction to check for consistency, identify non-obvious network effects, and predict additional Salmonella mutations for experimental validation. We will complement this targeted approach by a non-biased analysis that uses network analysis tools to interpret proteome data for Salmonella from mature and new infection foci. Highlighted network modules and deduced regulatory events are experimentally validated using Salmonella mutants and mouse infections experiments.

Expected Value of the Proposed Project

Heterogeneity of host-pathogen interactions may have major implications for effective control of infectious diseases but little experimental data are available. In this project, we will develop concepts and methodology to elucidate mechanisms causing heterogeneous Salmonella growth in a mouse typhoid fever model. The results might reveal the relevance of heterogeneous host control and might provide a basis for innovative control strategies that specifically attack refractory, slowly replicating pathogen subpopulations.