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Metabolic Control of Persistence in Individual Bacteria

$395,854R35FY2020GMNIH

Cornell University, Ithaca NY

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Abstract

PROJECT SUMMARY: Cells must robustly sense, decode, and transmit information at the molecular level in order to ef?ciently respond to changing environments, a process that typically necessitates the coordination of many reg- ulatory elements (ie. RNA, DNA, proteins). Since a suboptimal response to environmental insults can be enormously costly, several failsafe and protection mechanisms are in place to enhance cell survival under harsh environments. In particular, bacteria ?hedge their bets? by allowing a very small fraction of their population to enter a non-growing state called persistence to survive enormous amounts of antibiotics. The precise way persistence rates are controlled is currently unknown, but recent exper- iments in E. coli suggested that imbalances in toxin/antitoxin levels that cause growth arrest during starvation are also involved in persistence. While this hints at the existence of a fundamental link be- tween the regulation of metabolism and persister states, it is still dif?cult to investigate how metabolism is involved in the active regulation of persistence rates as a bet-hedging strategy using current ap- proaches. Our goal is to combine new advances in quantitative single-cell microscopy and synthetic biology with mathematical modeling to investigate three core aspects of persistence and bet-hedging in bacteria. First, we will investigate how persistence is controlled by quantifying the metabolite pro?le of cells under environmental perturbations and tracking energy levels during persister pathogenesis using quantitative single-cell microscopy. Second, we will investigate how persistence is activated by studying how metabolic network perturbations trigger persistence using high-throughput CRISPR interference assays. Third, we will investigate how cells recover from a persister state by targeting metabolic pathways to tune the rates of persistence and developing data-driven metabolic models of antibiotic tolerance. Over the next ?ve years, these studies will unravel the interconnected relation- ships between growth, metabolism and environmental stress, and they will help uncover how metabolic networks regulate persistence as a bet-hedging strategy in bacteria. These efforts can help us better understand and hopefully control persistence, which is critical in our ongoing ?ght against antimicrobial resistance.

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