The Mathematical Institute, University of Oxford, Eprints Archive

Novel methods for analysing bacterial tracks reveal persistence in rhodobacter sphaeroides

Rosser, G and Fletcher, A G and Wilkinson, D A and de Beyer, J A and Yates, C A and Armitage, J P and Maini, P. K. and Baker, R. E. (2013) Novel methods for analysing bacterial tracks reveal persistence in rhodobacter sphaeroides. PLOs Computational Biology, 9 (10). e1003276-(18 pages).

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Abstract

Tracking bacteria using video microscopy is a powerful experimental approach to probe their motile behaviour. The trajectories obtained contain much information relating to the complex patterns of bacterial motility. However, methods for the quantitative analysis of such data are limited. Most swimming bacteria move in approximately straight lines, interspersed with random reorientation phases. It is therefore necessary to segment observed tracks into swimming and reorientation phases to extract useful statistics. We present novel robust analysis tools to discern these two phases in tracks. Our methods comprise a simple and effective protocol for removing spurious tracks from tracking datasets, followed by analysis based on a two-state hidden Markov model, taking advantage of the availability of mutant strains that exhibit swimming-only or reorientating-only motion to generate an empirical prior distribution. Using simulated tracks with varying levels of added noise, we validate our methods and compare them with an existing heuristic method. To our knowledge this is the first example of a systematic assessment of analysis methods in this field. The new methods are substantially more robust to noise and introduce less systematic bias than the heuristic method. We apply our methods to tracks obtained from the bacterial species Rhodobacter sphaeroides and Escherichia coli. Our results demonstrate that R. sphaeroides exhibits persistence over the course of a tumbling event, which is a novel result with important implications in the study of this and similar species.

Item Type:Article
Subjects:A - C > Biology and other natural sciences
Research Groups:Centre for Mathematical Biology
ID Code:1755
Deposited By: Philip Maini
Deposited On:26 Oct 2013 09:53
Last Modified:29 May 2015 19:27

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