Peritrichously flagellated bacteria carry out chemotaxis by modulating the frequency of switching between smooth swimming and tumbling. The tumbling frequency is controlled by a signal transduction cascade in which transmembrane receptors modulate the activity of a histidine kinase CheA that transfers phosphate to its cognate response regulator CheY. The proteins of the chemotaxis signaling cascade are localized to clusters found primarily at the poles of cells. In this work, the localization of the CheZ protein, a phosphatase that dephosphorylates CheY~P, is examined. Using a CheZ-GFP fusion protein, we show that CheZ was localized to the polar receptor patch via interaction with the short form of CheA (CheAS). Aromatic residues of CheZ near one end of the elongated CheZ four-helix bundle were determined to be critical for localization. Aliphatic residues in CheAS were also determined to be critical for CheZ localization to the receptor patch and substitution of these residues conferred a tumble bias to swimming cells. A mechanism of CheZ localization is proposed in which the CheZ apical loop interacts with a binding site formed by dimerization of the P1 domain of CheAS. The potential role of CheZ localization as a means of coordinating the rotation state of peritrichously distributed flagella is discussed.

The key control step in E. coli chemotaxis is regulation of CheA kinase activity by a set of four transmembrane chemoreceptors. The receptor dimers can form trimeric complexes (trimers of dimers), and these trimers can be joined by a bridge thought to consist of a CheW monomer, a CheA dimer, and a second CheW monomer. It has been proposed that trimers of receptor dimers may be joined by CheW-CheA dimer-CheW links to form an extended hexagonal lattice that may be the structural basis of the chemoreceptor patches seen in E. coli. The receptor/CheA/CheW ternary complex is a membrane-spanning allosteric enzyme whose activity is regulated by protein interactions. The study presented in this dissertation investigated intermolecular and intramolecular interactions that affect the chemotactic signal processing. I have examined functional interactions between the serine receptor Tsr and the aspartate receptor Tar using a receptor coupled in vitro phosphorylation assay. The results reveal the emergent properties of mixed receptor populations and emphasize their importance in the integrated signal processing that underlies bacterial chemotaxis. A mutational analysis of the extreme C-terminus (last fifty residues) of Tar is also presented. The results implicate the receptor C-terminus in maintenance of baseline receptor activity and in attractant-induced transmembrane signaling. They also suggest how adaptive methylation might counteract the effects of attractant binding.

Bacterial chemotaxis is the movement of bacteria towards or away from chemical stimuli in the surrounding media. Bacteria respond to chemotactic signals through chemoreceptors which bind specific ligands and transduce signals through a modified two-component system. Typical chemoreceptors bind a ligand in the periplasm and signal across the inner membrane to the cytoplasmic chemosensory array through the inner membrane. Bacterial chemoreceptors must integrate multiple signals within an array of different receptor homologues to a single output. Chemoreceptors act cooperatively to allow a rapid signal spread across the array and large signal gain. Chemoreceptors adapt to a signal by chemical modification of their cytoplasmic domains in order respond across a wide range of effector concentrations. How bacterial chemoreceptors transduce signals through the inner membrane, integrate multiple effector responses, signal cooperatively and adapt to result in a single output signal is not currently fully known. In Rhodobacter sphaeroides, additional complexity arises from the presence of multiple homologues of various chemotactic components, notably the array scaffold protein CheW. Decoding this signalling mechanism and heterogeneity involved in this system is important in decoding the action of a biological system, with implications for biotechnology and synthetic biology. This study used the two model systems Escherichia coli and R. sphaeroides to analyse the mechanism of signalling through bacterial chemoreceptors. Rational design of activity-shifting chemoreceptor mutations was undertaken and these variants were analysed in phenotypic and fluorescence localisation studies. Molecular-dynamics simulations showed an increase in flexibility of chemoreceptors corresponds to a decrease in kinase output activity, which was determined by the computational tracking of bacteria free-swimming in media. Fluorescence recovery after photobleaching was used to show that this increase in flexibility results in a decrease in binding of receptors to their array scaffold proteins. A two-hybrid screen also suggested that inter-receptor affinity is also likely to decrease. These results show that signalling through chemoreceptors is likely through a mechanism involving the selective flexibility of chemoreceptor cytoplasmic domains. Analysis of R. sphaeroides chemoreceptors and CheW scaffold proteins in E. coli showed that it should be possible to design, from the bottom-up, a functional bacterial chemotaxis system in order to analyse individual protein specificity. Expression of R. sphaeroides MCPs in this E. coli system show the reconstitution of a chemotactic array, but not one capable of signalling specifically to proposed attractants. Results gained from this system suggest the R. sphaeroides CheW proteins are not homologous and their differential binding affinities may allow array activity 'fine-tuning'.

Em sentido geral, a quimiotaxia é o movimento dirigido que desenvolvem alguns seres vivos em resposta aos gradientes químicos presentes no seu ambiente. Uma bactéria é um organismo unicelular que usa a quimiotaxia como mecanismo de mobilização para encontrar os nutrientes de que precisa para sobreviver e para escapar de ambientes nocivos. Evoluída durante milhões de anos pela natureza, a quimiotaxia de bactérias é um processo altamente otimizado de busca e exploração em espaços desconhecidos. Graças aos avanços no campo da computação, as estratégias quimiotácticas das bactérias e sua excelente capacidade de busca podem ser modeladas, simuladas e emuladas para desenvolver métodos de otimização inspirados na natureza que sejam uma alternativa aos métodos já existentes. Neste trabalho, desenvolvem-se dois algoritmos baseados em estratégias quimiotácticas de bactérias: o BCBTOA (Bacterial Chemotaxis Based Topology Optimization Algorithm) e o BCMOA (Bacterial Chemotaxis Multiobjective Optimization Algorithm) os quais são um algoritmo de otimização topológica e um algoritmo de otimização multi-objetivo, respectivamente. O desempenho dos algoritmos é avaliado mediante a sua aplicação à solução de diversos problemas de prova e os resultados são comparados com os de outros algoritmos atualmente relevantes. O algoritmo de otimização multi-objetivo desenvolvido, também foi aplicado na solução de três problemas de otimização de projeto mecânico de eixos. Os resultados obtidos e os analise comparativos feitos, permitem concluir que os algoritmos desenvolvidos são altamente competitivos e demonstram o potencial do processo de quimiotaxia de bactérias como fonte de inspiração de algoritmos de otimização distribuída, contribuindo assim, a dar resposta à constante demanda por técnicas de otimização mais eficazes e robustas. / In general, chemotaxis is the biased movement developed by certain living organisms as a response to chemical gradients present in their environment. A bacterium is a unicellular organism that uses chemotaxis as a mechanism for mobilization that allows it to find nutrients needed to survive and to escape from harmful environments. Millions of years of natural evolution became bacterial chemotaxis a highly optimized process in searching and exploration of unknown spaces. Thanks to advances in the computing field, bacterial chemotactical strategies and its excellent ability in searching can be modeled, simulated and emulated developing bio-inspired optimization methods as alternatives to classical methods. Two algorithms based on bacterial chemotactical strategies were designed, developed and implemented in this work: i) the topology optimization algorithm, BCBTOA (Bacterial Chemotaxis Based Topology Optimization Algorithm) and ii) the multi-objective optimization algorithm, BCMOA (Bacterial Chemotaxis Multiobjective Optimization Algorithm). Algorithms performances were evaluated by their applications in the solution of benchmark problems and the results obtained were compared with other algorithms also relevant today. The BCMOA developed here was also applied in the solution of three mechanical design problems. The results obtained as well as the comparative analysis conducted lead to conclude that the algorithms developed were competitive. This also demonstrates the potential of bacterial chemotaxis as a process in which distributed optimization techniques can be inspired.

Em sentido geral, a quimiotaxia é o movimento dirigido que desenvolvem alguns seres vivos em resposta aos gradientes químicos presentes no seu ambiente. Uma bactéria é um organismo unicelular que usa a quimiotaxia como mecanismo de mobilização para encontrar os nutrientes de que precisa para sobreviver e para escapar de ambientes nocivos. Evoluída durante milhões de anos pela natureza, a quimiotaxia de bactérias é um processo altamente otimizado de busca e exploração em espaços desconhecidos. Graças aos avanços no campo da computação, as estratégias quimiotácticas das bactérias e sua excelente capacidade de busca podem ser modeladas, simuladas e emuladas para desenvolver métodos de otimização inspirados na natureza que sejam uma alternativa aos métodos já existentes. Neste trabalho, desenvolvem-se dois algoritmos baseados em estratégias quimiotácticas de bactérias: o BCBTOA (Bacterial Chemotaxis Based Topology Optimization Algorithm) e o BCMOA (Bacterial Chemotaxis Multiobjective Optimization Algorithm) os quais são um algoritmo de otimização topológica e um algoritmo de otimização multi-objetivo, respectivamente. O desempenho dos algoritmos é avaliado mediante a sua aplicação à solução de diversos problemas de prova e os resultados são comparados com os de outros algoritmos atualmente relevantes. O algoritmo de otimização multi-objetivo desenvolvido, também foi aplicado na solução de três problemas de otimização de projeto mecânico de eixos. Os resultados obtidos e os analise comparativos feitos, permitem concluir que os algoritmos desenvolvidos são altamente competitivos e demonstram o potencial do processo de quimiotaxia de bactérias como fonte de inspiração de algoritmos de otimização distribuída, contribuindo assim, a dar resposta à constante demanda por técnicas de otimização mais eficazes e robustas. / In general, chemotaxis is the biased movement developed by certain living organisms as a response to chemical gradients present in their environment. A bacterium is a unicellular organism that uses chemotaxis as a mechanism for mobilization that allows it to find nutrients needed to survive and to escape from harmful environments. Millions of years of natural evolution became bacterial chemotaxis a highly optimized process in searching and exploration of unknown spaces. Thanks to advances in the computing field, bacterial chemotactical strategies and its excellent ability in searching can be modeled, simulated and emulated developing bio-inspired optimization methods as alternatives to classical methods. Two algorithms based on bacterial chemotactical strategies were designed, developed and implemented in this work: i) the topology optimization algorithm, BCBTOA (Bacterial Chemotaxis Based Topology Optimization Algorithm) and ii) the multi-objective optimization algorithm, BCMOA (Bacterial Chemotaxis Multiobjective Optimization Algorithm). Algorithms performances were evaluated by their applications in the solution of benchmark problems and the results obtained were compared with other algorithms also relevant today. The BCMOA developed here was also applied in the solution of three mechanical design problems. The results obtained as well as the comparative analysis conducted lead to conclude that the algorithms developed were competitive. This also demonstrates the potential of bacterial chemotaxis as a process in which distributed optimization techniques can be inspired.

Attenuated bacterial strains have been investigated on the premise of selective tumor colonization and drug delivery potential for decades. Salmonella Typhimurium VNP20009 was derived from the parental strain 14028 through genetic modification and tumor targeting ability, being well studied for anticancer effects in mice. In 2001 Phase 1 Clinical Trials, patients diagnosed with melanoma were introduced with VNP20009, resulting in safe delivery of the strain and targeting to the tumor, however no anticancer effects were observed. Recently, it was discovered that VNP20009 contains a SNP in cheY, which encodes the chemotaxis response regulator of flagellar motor function, rendering the strain deficient in chemotaxis. Replacement of cheY with the 14028 wild-type copy resulted in a 70% restoration of phenotype in traditional chemotaxis capillary assays compared to the parental strain. We attempted to optimize the chemotactic potential of VNP20009 but were unable without reversing the attenuated state of VNP20009. Due to the role of chemotaxis in bacterial tumor colonization and eradication remaining unclear, we aimed to compare VNP20009 and VNP20009 cheY+ primary tumor colonization and impact on metastasis in an aggressive 4T1 mouse mammary carcinoma model. Bacterial tumor colonization and metastatic potential of the cancerous cells to the lungs appear bacterial chemotaxis independent. Moreover, mice bearing tumors exposed to Salmonella exhibited increased morbidity that was associated with significant liver disease. Our results suggest that in our timeline VNP20009 may not be safe or efficacious when used in the context of immunocompetent animals with aggressive, metastatic breast cancer. In a novel approach, we aimed to understand the bacterial-cancer cell relationship within the tumor microenvironment, with an emphasis on gene expression changes occurring within the eukaryotic transcriptome. We employed the B16-F10 mouse melanoma model because VNP20009 is known to colonize and eradicate these tumors in mice. First, we optimized a timeline for Salmonella treatment of mouse melanoma, finding a dramatic delay in tumor growth between 2 and 7 days due to the presence of Salmonella. Additionally, we observed upregulation of the IFN-gamma signaling pathway within tumor tissue upon exposure to Salmonella after 7 days. In future studies, we aim to analyze the bacterial transcriptome in the tumor microenvironment to gain unique understanding and contribute to knowledge supporting bacterial-mediated cancer therapies. / Ph. D. / Bacteria have become our allies in the fight against cancer. Strains of Salmonella, normally thought of as a cause of gastrointestinal discomfort, are able to target cancer in the body and effectively shrink tumors in several animal models. Specifically, a strain of Salmonella Typhimurium called VNP20009, has shown great promise as an anticancer agent. Research on VNP20009 culminated in a Phase 1 Clinical Trial in which safe delivery of the strain and targeting to the tumor were achieved, however no anticancer effects were observed. We hypothesized further targeting of Salmonella could be achieved using chemotaxis, the coordination of flagellar driven movement with sensing environmental chemical gradients, akin to the nose of the bacterium. We discovered strain VNP20009 to be defective in chemotaxis, due to a genetic mutation that occurred during the strain’s construction. We were able to restore chemotaxis of the strain, at least partially, and discovered we could not further optimize chemotaxis without compromising the safety profile of VNP20009. We tested the effect of chemotaxis on tumor colonization in a mouse breast cancer model and found that the bacteria had an additive effect in causing liver disease and morbidity of the mice. We finally examined genome-wide gene expression changes occurring in the tumor microenvironment, as a response to anticancer agent VNP20009 colonization in a mouse melanoma model of cancer. Overall, this work contributes significantly to the understanding of VNP20009 chemotaxis and its tumor targeting abilities.

Perceiving and responding to the environment is key to survival. Using the prokaryotic equivalent of a nervous system – the chemotaxis system – bacteria sense chemical stimuli and respond by adjusting their movement accordingly. In chemotactic bacteria, such as the well-studied E. coli, environmental nutrient sensing is achieved through a membrane embedded protein array that specifically clusters at the cell poles. Signalling to the motor is performed by activation of the CheA kinase, which phosphorylates CheY and CheB. CheY-P tunes the activity of the flagellar motor while CheB-P, together with CheR is involved in adaptation to the stimulus. In E. coli, a dedicated phosphatase terminates the signal. Most bacterial species however, have a much more complex chemotaxis network. Rhodobacter sphaeroides, a model organism for complex chemotaxis systems, has one membrane-embedded chemosensory array and one cytoplasmic chemosensory array, plus several homologs of the E. coli chemotaxis proteins. Signals from both arrays are integrated to control the rotation of a single start-stop flagellar motor. The phosphorelay network has been studied extensively through in vitro phosphotransfer while in vivo studies have established the components of each array and the requirements for formation. Mathematical modelling has also contributed towards inferring connectivities within the signalling network. Starting by constructing a two-hybrid-based interaction network focused on the components of the cytoplasmic chemosensory array, this thesis further addresses its associated adaptation network through a series of in vivo techniques. The swimming behaviour of series of deletion mutants involving the adaptation network of R. sphaeroides is characterised under steady state conditions as well as upon chemotactic stimulation. New connectivities within the R. sphaeroides chemotaxis network are inferred from analysing these data together with results from in vivo photoactivation localisation microscopy of CheB₂. The experimental results are used to propose a new model for chemotaxis in R. sphaeroides.

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.

Biological signal processing can help us gain knowledge about biological complexity, as well as using this knowledge to engineer better systems. Three areas are identified as critical to understanding biology: 1) understanding DNA, 2) examining the overall biological function and 3) evaluating these systems in environmental (ie: turbulent) conditions. DNA is investigated for coding structure and redundancy, and a new tandem repeat region, an indicator of a neurodegenerative disease, is discovered. The linear algebraic framework can be used for further analysis and techniques. The work illustrates how signal processing is a tool to reverse engineer biological systems, and how our better understanding of biology can improve engineering designs. Then, the way a single-cell mobilizes in response to a chemical gradient, known as chemotaxis, is examined. Inspiration from receptor clustering in chemotaxis combined with a Hebbian learning method is shown to improve a gradient-source (chemical/thermal) localization algorithm. The algorithm is implemented, and its performance is evaluated in diffusive and turbulent environments. We then show that sensor cross-correlation can be used in solving chemical localization in difficult turbulent scenarios. This leads into future techniques which can be designed for gradient source tracking. These techniques pave the way for use of biologically-inspired sensor networks in chemical localization.