Berlin 2024 – wissenschaftliches Programm

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DY: Fachverband Dynamik und Statistische Physik

DY 53: Statistical Physics of Biological Systems III (joint session BP/DY)

DY 53.8: Vortrag

Freitag, 22. März 2024, 11:45–12:00, H 2032

Optimal Memoryless Chemotaxis — •Jacob Knight¹, Paula García-Galindo², Johannes Pausch¹, and Gunnar Pruessner¹ — ¹Department of Mathematics, Imperial College London, South Kensington, London SW7 2BZ, UK — ²Department of Chemical Engineering and Biotechnology, University of Cambridge, Philippa Fawcett Drive, Cambridge CB3 0AS, UK

A wide array of biological systems can navigate in shallow gradients of chemoattractant with remarkable precision. Whilst previous models approach such systems using coarse-grained chemical density profiles, we construct a model consisting of a chemotactic cell responding to discrete cue particles, giving rise to novel phenomenology. For a cell without internal memory, we derive an effective velocity with which the cell approaches the source. This effective velocity is independent of the chemoattractant diffusivity, which can be tuned such that the cell can navigate in arbitrarily shallow chemical gradients. The effective velocity becomes negative beyond some homing radius, which represents an upper bound on the distance within which chemotaxis can be reliably performed.

Keywords: Chemotaxis; Active matter; Gradient sensing; Searching; Random walks