Obiettivo
Gene circuits exhibit fluctuations (‘noise’) in the levels of key components such as regulatory proteins. Increasingly, noise appears to play functional roles, e.g it can enable a subpopulation of cells to enter a transient antibiotic-resistant state, enhancing their survival. By ensuring that cells do not all exist in the same transcriptional state, the colony can ‘bet-hedge’ against future environmental changes.
Studying bet-hedging is critical to our understanding of how bacterial gene circuits have evolved in an ever changing and hostile environment. It is also important for public health. The spread of infectious diseases can depend on activation of alternative genetic programs, such as competence, general stress response, and antibiotic persistence in bacteria. I seek to understand the mechanisms by which cells enter these alternate states.
Previous gene expression assays used bulk averages over thousands of cells, causing individual cell behaviour to be lost. I will develop new approaches to attack this problem. I will use single-cell time-lapse microscopy to examine the generality of bet-hedging (Aim 1). I will construct and screen reporter strains for ~120 key pathways in B. subtilis. After screening for pathways that show variable gene expression, I will use synthetic biology and mathematical modelling techniques to discover the gene circuit mechanisms that allow cells to probabilistically enter these alternative states (Aim 2).
In order to test the function of the variable gene expression observed in our reporter strain for each candidate gene I will test whether, upon addition of antibiotics or other stresses, cells that are highly expressing the candidate protein survive or grow faster than cells that are not. I will do this using a novel microfluidic device (Aim 3). This work will lead to a comprehensive understanding of how and why alternative transcriptional states are generated in bacteria.
Campo scientifico
- natural sciencesbiological sciencesmicrobiologybacteriology
- natural sciencesbiological sciencessynthetic biology
- natural sciencesbiological sciencesbiochemistrybiomoleculesproteins
- medical and health sciencesbasic medicinepharmacology and pharmacypharmaceutical drugsantibiotics
- natural sciencesmathematicsapplied mathematicsmathematical model
Invito a presentare proposte
FP7-PEOPLE-2012-CIG
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Meccanismo di finanziamento
MC-CIG - Support for training and career development of researcher (CIG)Coordinatore
CB2 1TN Cambridge
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