How do danger signals originating from mechano-sensing of invasive bacteria integrate with the immune response to infection?

Rapid detection and response to infection are essential first steps in the establishment of a successful immune response. Detection of conserved molecules, termed microbe-associated molecular patterns (MAMPs), by pattern-recognition receptors (PRRs) induces the production of inflammatory mediators (Fig 1A). However, as PRRs detect conserved microbial products, this detection system cannot discriminate between innocuous microbes and pathogens.
Bacterial pathogens manipulate host cell processes, including membrane and cytoskeletal dynamics, to establish their replicative niche. For example, intracellular bacteria such as the enteropathogen Shigella invade epithelial cells, causing dramatic ruffles that cause mechanical tension at the membrane (Fig. 1B).
Advanced light microscopy techniques provide invaluable insights into the complex dynamics of Shigella infection and have shown that alterations to host cell physiology during infection release small molecules and ions such as Ca2+. We hypothesise that these fluxes of Ca2+ constitute a danger signal, alerting the host to specific pathogen activity. We reason that this signal is detected and decoded by the host cell through the Ca2+ sensor Calmodulin (CaM). CaM signals integrate with PRR signaling, augmenting the innate immune response to infectious agents. The importance of this pathway is highlighted by the fact that Shigella has evolved virulence factors that inhibit CaM, as identified by the Odendall lab (Fig. 1C).
Specific molecules and structures within live, infected cells will be visualized through fluorescence microscopy, which will help us capture the dynamic interactions between Shigella and host cells. Future work will investigate the importance of this axis in mouse models of Shigella infection.
This project aims to determine :
Aim1: The Shigella-induced perturbations and mechanical events that are sensed as danger signals and activate CaM
Aim2: How these signals integrate with pattern recognition to activate optimal inflammatory signaling
Aim3: The importance of this signaling axis in mouse models of Shigella infection.
Techniques involved include: fluorescence lifetime imaging microscopy, CRISPR-Cas gene editing, biochemistry, in vitro and in vivo bacterial infection models.