Novel Methods for Analysing Bacterial Tracks Reveal Persistence in Rhodobacter sphaeroides

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

Mathematical modelling and analysis of aspects of bacterial motility

The motile behaviour of bacteria underlies many important aspects of their actions, including pathogenicity, foraging efficiency, and ability to form biofilms. In this thesis, we apply mathematical modelling and analysis to various aspects of the planktonic motility of flagellated bacteria, guided by experimental observations. We use data obtained by tracking free-swimming Rhodobacter sphaeroides under a microscope, taking advantage of the availability of a large dataset acquired using a recently developed, high-throughput protocol. A novel analysis method using a hidden Markov model for the identification of reorientation phases in the tracks is described. This is assessed and compared with an established method using a computational simulation study, which shows that the new method has a reduced error rate and less systematic bias. We proceed to apply the novel analysis method to experimental tracks, demonstrating that we are able to successfully identify reorientations and record the angle changes of each reorientation phase. The analysis pipeline developed here is an important proof of concept, demonstrating a rapid and cost-effective protocol for the investigation of myriad aspects of the motility of microorganisms. In addition, we use mathematical modelling and computational simulations to investigate the effect that the microscope sampling rate has on the observed tracking data. This is an important, but often overlooked aspect of experimental design, which affects the observed data in a complex manner. Finally, we examine the role of rotational diffusion in bacterial motility, testing various models against the analysed data. This provides strong evidence that R. sphaeroides undergoes some form of active reorientation, in contrast to the mainstream belief that the process is passive

Cell morphology governs directional control in swimming bacteria

The ability to rapidly detect and track nutrient gradients is key to the ecological success of motile bacteria in aquatic systems. Consequently, bacteria have evolved a number of chemotactic strategies that consist of sequences of straight runs and reorientations. Theoretically, both phases are affected by fluid drag and Brownian motion, which are themselves governed by cell geometry. Here, we experimentally explore the effect of cell length on control of swimming direction. We subjected Escherichia coli to an antibiotic to obtain motile cells of different lengths, and characterized their swimming patterns in a homogeneous medium. As cells elongated, angles between runs became smaller, forcing a change from a run-and-tumble to a run-and-stop/reverse pattern. Our results show that changes in the motility pattern of microorganisms can be induced by simple morphological variation, and raise the possibility that changes in swimming pattern may be triggered by both morphological plasticity and selection on morphology

The impact of temporal sampling resolution on parameter inference for biological transport models

Imaging data has become widely available to study biological systems at various scales, for example the motile behaviour of bacteria or the transport of mRNA, and it has the potential to transform our understanding of key transport mechanisms. Often these imaging studies require us to compare biological species or mutants, and to do this we need to quantitatively characterise their behaviour. Mathematical models offer a quantitative description of a system that enables us to perform this comparison, but to relate these mechanistic mathematical models to imaging data, we need to estimate the parameters of the models. In this work, we study the impact of collecting data at different temporal resolutions on parameter inference for biological transport models by performing exact inference for simple velocity jump process models in a Bayesian framework. This issue is prominent in a host of studies because the majority of imaging technologies place constraints on the frequency with which images can be collected, and the discrete nature of observations can introduce errors into parameter estimates. In this work, we avoid such errors by formulating the velocity jump process model within a hidden states framework. This allows us to obtain estimates of the reorientation rate and noise amplitude for noisy observations of a simple velocity jump process. We demonstrate the sensitivity of these estimates to temporal variations in the sampling resolution and extent of measurement noise. We use our methodology to provide experimental guidelines for researchers aiming to characterise motile behaviour that can be described by a velocity jump process. In particular, we consider how experimental constraints resulting in a trade-off between temporal sampling resolution and observation noise may affect parameter estimates.Comment: Published in PLOS Computational Biolog

Data-driven models for cell motility in complex 2- and 3-dimensional environments

Studying cell motility is of vital importance for health, for knowing how cells behave and are affected by, and can themselves cause, disease. Mathematical modelling of such behaviour has proved beneficial for furthering knowledge of important motility processes in many different cell types. This work aims to define and analyse data-integrated mathematical models for cell motility in 2 and 3 dimensions, specifically applied to glioblastoma tumour cells and surface-attached P. aeruginosa bacterial cells. Models are outlined, tested on in silico data, parametrized where possible and assumptions are studied in detail. As a result, recommendations are made for how subsequent data could be collected to further improve the prediction and validation of these models. A comprehensive framework is developed for the analysis of cell tracking data in 2 and 3 dimensions which allows a user to study various aspects of the Persistent Random Walk model as applied to these tracks, looking at speeds, persistence time, mean squared displacement and root mean squared speed. In silico simulations show good agreement with model predictions, however the model is incapable of describing the experimental data, as evidenced by lack of agreement in speed distributions and the speed parameter changing with time. A Bayesian approach to estimating these parameters is also considered, with estimates of persistence time seen to be inflated here compared to those from the frequentist approach. A newly-observed twiddling mechanism used in chemotaxis by P. aeruginosa is also studied, through rigorous hypothesis testing of assumptions about this motion. An individual-based model is employed to simulate the resulting chemotactic motion, which shows good agreement with results from the specified analytic model, though the model cannot currently be validated against experimental data due to lack of appropriate data for parameter estimation

Growth switching, motility and application of Bdellovibrio bacteriovorus

Bdellovibrio bacteriovorus, is a small mono-flagellate Gram-negative delta-proteobacterium, which has a bi-phasic lifecycle, consisting of a predatory phase; in which they invade on other Gram-negative bacteria and digest the prey cell’s content to grow and septate, or host independent phase; in which they can grow and septate in media rich in amino acids as well as vitamins and cofactors. As B. bacteriovorus can kill other Gram-negative bacteria including pathogens, they have potential to be used as a ‘living antibiotic’. I have been part of this field since 2004, a time at which the first B. bacteriovorus genome (HD100) had just been sequenced and made available, and only one study into making deletion mutants had been published. During my time in this field, the research has expanded almost exponentially, with the understanding of core pathways and systems that make B. bacteriovorus so novel being highlighted and greatly understood. In addition new techniques and methodologies never before attempted in B. bacteriovorus research have been made possible and I have been lucky to be a part of this and carried out some of the work myself. In particular I have worked on the mutation and phenotype testing of genes encoding pathways for motility, prey cell lysis, B. bacteriovorus intra-cellular signalling, and bi-phasic growth switching. These advances from my work including an animal trial into the predatory nature of B. bacteriovorus have laid the foundation for its use as a novel ‘living antibiotic’ in the future

Growth switching, motility and application of Bdellovibrio bacteriovorus

Bdellovibrio bacteriovorus, is a small mono-flagellate Gram-negative delta-proteobacterium, which has a bi-phasic lifecycle, consisting of a predatory phase; in which they invade on other Gram-negative bacteria and digest the prey cell’s content to grow and septate, or host independent phase; in which they can grow and septate in media rich in amino acids as well as vitamins and cofactors. As B. bacteriovorus can kill other Gram-negative bacteria including pathogens, they have potential to be used as a ‘living antibiotic’. I have been part of this field since 2004, a time at which the first B. bacteriovorus genome (HD100) had just been sequenced and made available, and only one study into making deletion mutants had been published. During my time in this field, the research has expanded almost exponentially, with the understanding of core pathways and systems that make B. bacteriovorus so novel being highlighted and greatly understood. In addition new techniques and methodologies never before attempted in B. bacteriovorus research have been made possible and I have been lucky to be a part of this and carried out some of the work myself. In particular I have worked on the mutation and phenotype testing of genes encoding pathways for motility, prey cell lysis, B. bacteriovorus intra-cellular signalling, and bi-phasic growth switching. These advances from my work including an animal trial into the predatory nature of B. bacteriovorus have laid the foundation for its use as a novel ‘living antibiotic’ in the future

Transcription initiation in Streptomyces coelicolor A3(2)

Recent studies into the stringent response and the discovery of a number of RNA polymerase binding proteins suggests that the model for bacterial transcription initiation in Actinobacteria may differ from that in Escherichia coli. In E. coli, the alarmone ppGpp, together with DksA, binds to RNA polymerase to elicit the stringent response. However, the ppGpp binding site on RNA polymerase is not conserved in S. coelicolor, although the organism possesses a DksA homologue. Deletion of DksA did not affect the growth and development of S. coelicolor, although its overexpression stimulated antibiotic production. Evidence is presented that suggests that this occurs through binding to the RNA polymerase secondary channel. The biological role of this protein remains unknown. CarD and RbpA are two RNA polymerase­‐binding proteins present in all Actinobacteria, including S. coelicolor and M. tuberculosis. Both proteins are critical for growth and have been identified as transcriptional activators from σHrdB­‐dependent promoters in vitro. Here it was demonstrated that CarD and RbpA activate transcription from rRNA promoters with a poorly conserved ­‐35 element. Surprisingly it was also found that both proteins can inhibit transcription from synthetic promoters with highly conserved ­‐35 elements. Chromatin immunoprecipitation followed by high throughput sequencing (ChIP­‐seq) experiments revealed that CarD and RbpA are found exclusively at promoter regions. RbpA is localised only at promoters recognised by σHrdB, whereas CarD also co‐localises with the alternative sigma factor σR during oxidative stress indicating that it lacks RNA polymerase holoenzyme specificity. The sigma specificity of RbpA was tested by the generation of sigma mutants that were defective in binding. In vivo, in vitro and ChIP­‐seq data presented in this study suggest that CarD and RbpA have an overlapping role in transcription initiation at σHrdB­‐dependent promoters in S. coelicolor