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.
Highlights
The motile behaviour of bacteria underlies many important aspects of their actions, including pathogenicity, foraging efficiency, and ability to form biofilms
Rotational Brownian motion prevents them from swimming continuously in a straight line, many motile species such as the multiflagellate Escherichia coli move in a series of approximately straight ‘runs’, interspersed by reorientating ‘tumbles’ in a process known as taxis [4]
In this work we have demonstrated the effective application of novel analysis methods based on a modified hidden Markov model (HMM) to tracking data acquired using a simple and relatively inexpensive experimental protocol
Summary
The motile behaviour of bacteria underlies many important aspects of their actions, including pathogenicity, foraging efficiency, and ability to form biofilms. The study of this phenomenon is of biomedical and industrial importance, with implications in the control of disease [1] and biofouling [2]. The flagellar motors in E. coli turn counterclockwise, causing the helical flagella to form a rotating bundle that propels the cell forward. A related motile mechanism exists in the uniflagellate bacterium Rhodobacter sphaeroides, in which reorientations are, instead, effected by stopping the flagellar motor [5]. The biochemical pathways responsible for chemotaxis in R. sphaeroides are less well studied than those in E. coli, and are known to be more complex [8]
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