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Inferring the Chemotactic Strategy of P. putida and E. coli Using Modified Kramers-Moyal Coefficients
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...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5293273/ https://www.ncbi.nlm.nih.gov/pubmed/28114420 http://dx.doi.org/10.1371/journal.pcbi.1005329 |
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author | Pohl, Oliver Hintsche, Marius Alirezaeizanjani, Zahra Seyrich, Maximilian Beta, Carsten Stark, Holger |
author_facet | Pohl, Oliver Hintsche, Marius Alirezaeizanjani, Zahra Seyrich, Maximilian Beta, Carsten Stark, Holger |
author_sort | Pohl, Oliver |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-5293273 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-52932732017-02-17 Inferring the Chemotactic Strategy of P. putida and E. coli Using Modified Kramers-Moyal Coefficients Pohl, Oliver Hintsche, Marius Alirezaeizanjani, Zahra Seyrich, Maximilian Beta, Carsten Stark, Holger PLoS Comput Biol Research Article 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. Public Library of Science 2017-01-23 /pmc/articles/PMC5293273/ /pubmed/28114420 http://dx.doi.org/10.1371/journal.pcbi.1005329 Text en © 2017 Pohl et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Pohl, Oliver Hintsche, Marius Alirezaeizanjani, Zahra Seyrich, Maximilian Beta, Carsten Stark, Holger Inferring the Chemotactic Strategy of P. putida and E. coli Using Modified Kramers-Moyal Coefficients |
title | Inferring the Chemotactic Strategy of P. putida and E. coli Using Modified Kramers-Moyal Coefficients |
title_full | Inferring the Chemotactic Strategy of P. putida and E. coli Using Modified Kramers-Moyal Coefficients |
title_fullStr | Inferring the Chemotactic Strategy of P. putida and E. coli Using Modified Kramers-Moyal Coefficients |
title_full_unstemmed | Inferring the Chemotactic Strategy of P. putida and E. coli Using Modified Kramers-Moyal Coefficients |
title_short | Inferring the Chemotactic Strategy of P. putida and E. coli Using Modified Kramers-Moyal Coefficients |
title_sort | inferring the chemotactic strategy of p. putida and e. coli using modified kramers-moyal coefficients |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5293273/ https://www.ncbi.nlm.nih.gov/pubmed/28114420 http://dx.doi.org/10.1371/journal.pcbi.1005329 |
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