Osmotaxis in Escherichia coli

Bacterial motility, and in particular repulsion or attraction towards specific chemicals, has been a subject of investigation for over 100 years, resulting in detailed understanding of bacterial chemotaxis and the corresponding sensory network in many bacterial species including Escherichia coli. E. Coli swims by rotating a bundle of flagellar filaments, each powered by an individual rotary motor located in the cell membrane. When all motors rotate counter-clockwise (CCW), a stable bundle forms and propels the cell forward. When one or more motors switch to clock-wise (CW) rotation, their respective filaments fall out of the bundle, leading to the cell changing orientation. Upon switching back to CCW, the bundle reforms and propels the cell in a new direction. Chemotaxis is performed by the bacterium through prolonging runs by suppressing CW rotation when moving towards nutrients and facilitating reorientation by increasing CW bias when close to a source of a harmful substance. Chemicals are sensed through interaction with membrane bound chemosensors. These proteins can interact with a very specific set of chemicals and the concentrations they are able to sense are in the range between 10-⁶ and 10-² M. However, experiments have shown that the osmotic pressure exerted by large (> 10-¹ M) concentrations of solutes, which have no specificity for binding to chemosensors (e.g. sucrose), is able to send a signal down the chemotactic network. Additionally, clearing of bacterial density away from sources of high osmolarity has been previously observed in experiments with agar plates. This behaviour has been termed osmotaxis. The aim of this doctoral thesis work is to understand how different environmental cues influence the tactic response and ultimately, combine at the network output to direct bacterial swimming. As tactic responses to chemical stimuli have been extensively studied, I focus purely on the response to non-specific osmotic stimuli, using sucrose to elevate osmolarity. I monitor the chemotactic network output, the rotation of a single bacterial flagellar motor, using Back Focal Plane Interferometry over a variety of osmotic conditions. Additionally, in collaboration with Vincent Martinez, I studied the effect of elevated osmolality on swimming speed of large (104) bacterial populations, using differential dynamic microscopy (DDM). I have found that sudden increases in media osmolarity lead to changes of both motor speed and motor clockwise bias, which is the fraction of time it spends rotating clockwise. Changes in CW Bias proceed in two phases. Initially, after elevating the osmolarity, CW Bias drops to zero, indicating that the motor is exclusively in the ‘cell run’ mode. This phase lasts from 2-5 minutes depending on the magnitude of the change in solute concentration. What follows then is a distinct second phase where the CW Bias is elevated with respect to the initial levels and this phase lasts longer than 15-20 minutes. In comparison, for defined chemical stimuli, the motor output resets after several seconds, a behaviour termed perfect adaptation. For changes of 100 mOsm/kg and 200 mOsm/kg in magnitude the motors speed up, often by as much as a factor of two, before experiencing a gradual slow down. Despite the slow down, motors still rotate faster 15-20 minutes after the change in osmolarity, than they did before. For changes of 400 mOsm/Kg in magnitude the motors decrease sharply in speed, coming to a near halt, recovering after 5 minutes and eventually, on average, speeding up. DDM studies of free swimming bacteria have shown that elevated osmolality leads to higher swimming speeds, in agreement with single motor data. Using theoretical models of bacterial swimming from the literature, it is discussed how this motor output, although different to what is expected for chemotaxis, is able to drive bacteria away from regions of space with high osmolalities. Additionally, I have started extending the work done with sucrose, to another solute often used to elevate osmolality, sodium chloride. While sucrose is outer membrane impermeable, NaCl can cross the outer membrane into the periplasmic space. Another layer of complexity is that NaCl has some specificty for the chemoreceptors. The preliminary results are shown and qualitatively agree with those obtain with sucrose

Steady state running rate sets the speed and accuracy of accumulation of swimming bacteria

We study the chemotaxis of a population of genetically identical swimming bacteria undergoing run and tumble dynamics driven by stochastic switching between clockwise and counterclockwise rotation of the flagellar rotary system, where the steady-state rate of the switching changes in different environments. Understanding chemotaxis quantitatively requires that one links the measured steady-state switching rates of the rotary system, as well as the directional changes of individual swimming bacteria in a gradient of chemoattractant/repellant, to the efficiency of a population of bacteria in moving up/down the gradient. Here we achieve this by using a probabilistic model, parametrized with our experimental data, and show that the response of a population to the gradient is complex. We find the changes to the steady-state switching rate in the absence of gradients affect the average speed of the swimming bacterial population response as well as the width of the distribution. Both must be taken into account when optimizing the overall response of the population in complex environments

Formation and emergent dynamics of spatially organized microbial systems

Spatial organization is the norm rather than the exception in the microbial world. While the study of microbial physiology has been dominated by studies in well-mixed cultures, there is now increasing interest in understanding the role of spatial organization in microbial physiology, coexistence and evolution. Where studied, spatial organization has been shown to influence all three of these aspects. In this mini review and perspective article, we emphasize that the dynamics within spatially organized microbial systems (SOMS) are governed by feedbacks between local physico-chemical conditions, cell physiology and movement, and evolution. These feedbacks can give rise to emergent dynamics, which need to be studied through a combination of spatio-temporal measurements and mathematical models. We highlight the initial formation of SOMS and their emergent dynamics as two open areas of investigation for future studies. These studies will benefit from the development of model systems that can mimic natural ones in terms of species composition and spatial structure

Osmotaxis in Escherichia coli through changes in motor speed

Bacterial motility, and in particular repulsion or attraction towards specific chemicals, has been a subject of investigation for over 100 years, resulting in detailed understanding of bacterial chemotaxis and the corresponding sensory network in many bacterial species. For Escherichia coli most of the current understanding comes from the experiments with low levels of chemotactically-active ligands. However, chemotactically-inactive chemical species at concentrations found in the human gastrointestinal tract produce significant changes in E. coli's osmotic pressure, and have been shown to lead to taxis. To understand how these nonspecific physical signals influence motility, we look at the response of individual bacterial flagellar motors under step-wise changes in external osmolarity. We combine these measurements with a population swimming assay under the same conditions. Unlike for chemotactic response, a long-term increase in swimming/motor speeds is observed, and in the motor rotational bias, both of which scale with the osmotic shock magnitude. We discuss how the speed changes we observe can lead to steady state bacterial accumulation.Comment: 24 pages, 11 figure

Osmotaxis in E. coli through changes in motor speed

Several DataShare deposits in the Pilizota Lab Collection of DataShare.Osmotic shock data and other data from the paper "Osmotaxis in E. coli through changes in motor speed" (in press).Rosko, Jerko; Pilizota, Teuta. (2017). Osmotaxis in E. coli through changes in motor speed - Osmotic shock dataset, [dataset]. University of Edinburgh. Centre for Synthetic and Systems Biology. http://dx.doi.org/10.7488/ds/211

Bacterial flagellar motor as a multimodal biosensor_data supporting figures

Data set supports figures 3, 5 and 6 of the published manuscript "Bacterial flagellar motor as a multimodal biosensor". Folder "Figure 3": "Traces": Contains .txt files with Fourier transform (rotational speed) of bead coordinates for 1 Wild type (WT) cell, and 4 mutant strain (delCheZ) cells. Time is given in seconds, speed in Hz. Folder also contains .txt file with data format explanation. The traces were used to calculate biases plotted in figure 3B. 3B_Biases.xlsx: Points used for plotting figure 3B. Bias was calculated from the traces described above with 5 second sliding window. Biases are given for 4 delCheZ cells and 1 WT cell. Folder "Figure 5": "5C traces": folder contains .txt files (1 file for an individual cell) with rotational speed (in Hz) sampled at 100 points per second rate. Folder also contains .txt file with data format explanation. Individual traces were used for calculating mean trace with the standard deviation plotted in Fig. 5C. 5B and 5C points.xlsx: Points used for plotting figures 5B and 5C (individual traces for 5B were kindly provided by Dr. Ashley Nord). Normalised mean speed is given. Folder "Figure 6": Contains points used for figure 6. CW and CCW speed in Hz is given for different experimental buffers and bead sizes (indicated in left column).Rosko, Jerko; Barboza-Perez, Uriel; Krasnopeeva, Ekaterina; Pilizota, Teuta. (2020). Bacterial flagellar motor as a multimodal biosensor_data supporting figures, 2014-2020 [dataset]. University of Edinburgh. School of Biological Sciences. https://doi.org/10.7488/ds/2914