Berlin 2018 – wissenschaftliches Programm
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BP: Fachverband Biologische Physik
BP 29: Statistical Physics of Biological Systems I (joint session BP/DY)
BP 29.10: Vortrag
Donnerstag, 15. März 2018, 12:15–12:30, H 2013
Statistical inference of bacterial chemotaxis strategies — •Maximilian Seyrich1, Zahra Alirezaei2, Carsten Beta2, and Holger Stark1 — 1Institut für Theoretische Physik, Technische Universität Berlin, 10623 Berlin, Germany — 2Institut für Physik und Astronomie, Universität Potsdam, 14476 Potsdam, Germany
Bacteria like E. coli move with alternating runs and tumbles. Modern imaging techniques provide a high-throughput access to these run-and-tumble trajectories. However, good tumble recognition analysis is still a bottleneck and needs to set a-priori threshold parameters. We present a high-throughput inference technique, which allows to infer all swimming parameters of the bacterium without such a need.
We set up a random-walk model that describes runs and tumbles as a stochastic process of the bacterium’s swimming direction and speed extending our previous work [1]. The dynamics of the swimming direction is described by enhanced rotational Brownian motion during tumbling, while thermal and shot noise together with a relaxational drift analogously to an Ornstein-Uhlenbeck process govern the speed dynamics. In order to infer the relevant swimming parameters, moments and autocorrelation functions are calculated for our model and matched to the ones determined from experimental trajectories. We first show that our method identifies the classical bacterial chemotaxis strategy of E. coli, i.e., the tumble rate decreases when swimming along the chemical gradient. We also find evidence that a fast subpopulation of E. coli reduces its mean tumble angle in this direction.
[1] O. Pohl et al.,
PLoS Comp. Biol. 13, 1 (2017).