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Main Title: Inferring the Chemotactic Strategy of P. putida and E. coli Using Modified Kramers-Moyal Coefficients
Author(s): Pohl, Oliver
Hintsche, Marius
Alirezaeizanjani, Zahra
Seyrich, Maximilian
Beta, Carsten
Stark, Holger
Type: Article
Language Code: en
Abstract: Many bacteria perform a run-and-tumble random walk to explore their surrounding and to perform chemotaxis. In this article we present a novel method to infer the relevant parameters of bacterial motion from experimental trajectories including the tumbling events. We introduce a stochastic model for the orientation angle, where a shot-noise process initiates tumbles, and analytically calculate conditional moments, reminiscent of Kramers-Moyal coefficients. Matching them with the moments calculated from experimental trajectories of the bacteria E. coli and Pseudomonas putida, we are able to infer their respective tumble rates, the rotational diffusion constants, and the distributions of tumble angles in good agreement with results from conventional tumble recognizers. We also define a novel tumble recognizer, which explicitly quantifies the error in recognizing tumbles. In the presence of a chemical gradient we condition the moments on the bacterial direction of motion and thereby explore the chemotaxis strategy. For both bacteria we recover and quantify the classical chemotactic strategy, where the tumble rate is smallest along the chemical gradient. In addition, for E. coli we detect some cells, which bias their mean tumble angle towards smaller values. Our findings are supported by a scaling analysis of appropriate ratios of conditional moments, which are directly calculated from experimental data.
Issue Date: 23-Jan-2017
Date Available: 26-Nov-2020
DDC Class: 610 Medizin und Gesundheit
Subject(s): bacteria
bacterial motion
stochastic model
E. coli
Pseudomonas putida
cell tracking
Sponsor/Funder: DFG, 87159868, GRK 1558: Kollektive Dynamik im Nichtgleichgewicht: in kondensierter Materie und biologischen Systemen
Journal Title: PLOS Computational Biology
Publisher: Public Library of Science (PLoS)
Publisher Place: San Francisco, Calif.
Volume: 13
Issue: 1
Article Number: e1005329
Publisher DOI: 10.1371/journal.pcbi.1005329
EISSN: 1553-7358
ISSN: 1553-734X
Appears in Collections:FG Statistische Physik weicher Materie und biologischer Systeme » Publications

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