ArticlePLoS computational biology2013
Novel methods for analysing bacterial tracks reveal persistence in Rhodobacter sphaeroides.
Article in PLoS computational biology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Approximate Solutions of a General Stochastic Velocity-Jump Model Subject to Discrete-Time Noisy Observations.Bulletin of mathematical biology · 2025Article
- Swimming Using a Unidirectionally Rotating, Single Stopping Flagellum in the Alpha ProteobacteriumFrontiers in microbiology · 2022Review
- Tumble Kinematics of Escherichia coli near a Solid Surface.Biophysical journal · 2020Article
- Mechanism of Signalling and Adaptation through theInternational journal of molecular sciences · 2019Article
- The impact of temporal sampling resolution on parameter inference for biological transport models.PLoS computational biology · 2018Article
- Cell morphology governs directional control in swimming bacteria.Scientific reports · 2017Article
- Inferring the Chemotactic Strategy of P. putida and E. coli Using Modified Kramers-Moyal Coefficients.PLoS computational biology · 2017Article
- Micro-object motion tracking based on the probability hypothesis density particle tracker.Journal of mathematical biology · 2016Article
- Modeling of chemotactic steering of bacteria-based microrobot using a population-scale approach.Biomicrofluidics · 2015Article
- From Birds to Bacteria: Generalised Velocity Jump Processes with Resting States.Bulletin of mathematical biology · 2015Article
- Modelling and analysis of bacterial tracks suggest an active reorientation mechanism in Rhodobacter sphaeroides.Journal of the Royal Society, Interface · 2014Article
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Authors and funding
8 authors.
Funding
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.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.