The ability of motile bacteria to follow/avoid spatial gradients of favourable/unfavourable chemicals is termed chemotaxis. The chemotactic pathway of Escherichia coli is one of the best studied networks in biology, biological physics and engineering. Rightly so, the network displays some remarkable features (e.g. perfect adaptation , high sensitivity , yet at the same time flexibility and remodelling ) whose understanding would enable the identification of new principles to build better bioinspired systems (several tasks in engineering, for example path-planning in autonomous robotics, can be mapped onto a chemotaxis-like behaviour). What allows bacteria to explore the environment around them so effectively?
Over 40 years of systematic dissection can be briefly summarized as follows: upon binding to a molecule “antenna” proteins on the cell membrane change their activation state and trigger an intracellular signalling cascade that eventually determines whether the flagellar motors rotate clockwise (the cell stops and “chooses” a new direction) or counterclockwise (the cell swims straight).
Interestingly, while receptors do generally respond to specific compounds only (either attractants or repellents), it has been shown that some chemicals can “trick” the chemotactic machinery inducing a conformational change that activates the receptor itself . How do cells cope with such an unspecific response? How does this phenomenon affect cells’ ability to robustly follow chemical gradients? Can we build an external control system to steer chemotaxis at will?
This project sets out to address the above questions combining in-vivo experiments using microfluidics, high-speed video microscopy, back focal plane interferometry and mathematical modelling.
The project is ideally suited for students with background in engineering, physics or applied mathematics with a keen interest in understanding how biology solved signal processing and directed movement.
Applications from students with a background in Applied Mathematics, Physics and Engineering are encouraged.
 Yi, T. M., Huang, Y., Simon, M. I., & Doyle, J. (2000). Robust perfect adaptation in bacterial chemotaxis through integral feedback control. Proceedings of the National Academy of Sciences of the United States of America, 97(9), 4649–4653. http://doi.org/10.1073/pnas.97.9.4649
 Mello, B. A., & Tu, Y. (2003). Quantitative modeling of sensitivity in bacterial chemotaxis: the role of coupling among different chemoreceptor species. Proceedings of the National Academy of Sciences of the United States of America, 100(14), 8223–8228. http://doi.org/10.1073/pnas.1330839100