Discovery Early Career Researcher Award - Grant ID: DE240100316
Funder
Australian Research Council
Funding Amount
$435,431.00
Summary
Population genomic methods for modelling bacterial pathogen evolution. This project aims to develop novel techniques to model bacterial genome evolution and improve our understanding of how major agricultural and human pathogens, including Enterococcus, Salmonella and E. coli, evolve. The project expects to generate new knowledge about how horizontal gene transfer shapes the evolution of bacteria and how these dynamics vary over different temporal scales. Expected outcomes include methodological ....Population genomic methods for modelling bacterial pathogen evolution. This project aims to develop novel techniques to model bacterial genome evolution and improve our understanding of how major agricultural and human pathogens, including Enterococcus, Salmonella and E. coli, evolve. The project expects to generate new knowledge about how horizontal gene transfer shapes the evolution of bacteria and how these dynamics vary over different temporal scales. Expected outcomes include methodological advances that will enable the analysis of massive contemporary datasets. These methods and resulting analyses will provide significant benefits including informing the design of superior long-term interventions to reduce bacterial disease in both agriculture and health that are robust to the evolution of bacteria.Read moreRead less
Dissecting bacterial signal transduction. Bacteria have feelings. They sense and respond to changes using proteins called two-component signalling systems (TCSS). These comprise a sensor which activates a DNA binding protein in response to specific cues (signals). Using state-of-the-art genetic techniques and a synthetic biology approach, this research aims to reveal for the first time how these complex bacterial TCSS networks interact. The outcomes will be a fundamental, new understanding of ho ....Dissecting bacterial signal transduction. Bacteria have feelings. They sense and respond to changes using proteins called two-component signalling systems (TCSS). These comprise a sensor which activates a DNA binding protein in response to specific cues (signals). Using state-of-the-art genetic techniques and a synthetic biology approach, this research aims to reveal for the first time how these complex bacterial TCSS networks interact. The outcomes will be a fundamental, new understanding of how bacteria sense and respond to environmental signals; a deep dive into how bacteria feel. This knowledge will be the basis for innovative approaches to harness bacteria in biotech such as vaccine production, biofuels, or clever therapeutic interventions to stop bacterial infections.Read moreRead less