Yale University

To understand mechanistically how cellular information-processing enables and bounds the ability of bacteria to carry out key functions such as environmental navigation and cell-cell communication

  • Amount $1,275,000
  • City New Haven, United States
  • Investigator Benjamin Machta
  • Year 2023
  • Program Research
  • Sub-program Matter-to-Life

This grant supports Ben Machta at Yale University who will use tools from information theory and statistical physics to explore how bacteria process signals from their environment, and how they use this information to drive behavior. Machta will use bacteria to study one aspect of information processing: how noise (spurious signal accompanying the information-carrying signal) limits bacterial behavior. Specifically, Machta  will investigate how bacteria navigate their local chemical environment through chemotaxis (movement along a concentration gradient of a substance) and how they communicate with one another through quorum sensing (chemical signaling that reflects the density of nearby bacteria). Grant funds will allow Machta to determine the theoretical limit on the rate at which E. coli acquire behaviorally-relevant information (the concentration of so-called attractant molecules) and to measure this information-acquisition rate, to provide the first direct measurement of whether any organism’s biochemical sensory system approaches the performance limits imposed by the laws of physics. Additionally, Machta and colleagues will study how E. coli amplify signals without introducing noise via experiments that will test whether equilibrium or non-equilibrium models do a better job of describing chemotactic signal amplification. Finally, the researchers will use V. cholerae bacteria as a model organism to study the fidelity of information transmission as multiple signals propagate through the quorum sensing signal processing pathway. Collectively, these experiments will provide an important demonstration of how the tools of  information theory and statistical physics can be used to gain mechanistic insight into the information processing that drives behavior in simple living systems. 

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