Research on bacteria in their biofilm form is limited by the ability to artificially culture bacterial biofilms in a system that permits the visualization of individual cells. The experiments comprising this thesis research are on-going investigations of bacterial culture systems engineered to provide an environment that mimics biofilms while enabling real-time microscopy. Specifically, the microfluidic systems developed and assessed as part of this thesis permit the visualization of individual bacteria cells within consortia growing within a narrow space provided by a microfluidic device. This research demonstrates the versatility of these microfluidic systems across potentially high-throughput microbiological experiments utilizing genetically engineered Escherichia coli. Before demonstrating the efficacy of these systems, the development of the field of synthetic biology over the past half century is reviewed, focusing on synthetic genetic circuits and their applications (Chapter 2). The first and main microfluidic device explored in this research was developed to mimic the nutrient-deficient conditions within biofilms by forcing media to enter the culture area through a narrow, torturous channel. The microfluidic channel was thin enough (0.97 μm) to prevent the motility of 1-μm-wide E. coli cells, enabling visualization of individual cells. The bacteria cultured in the device contained either a simple Plux-driven quorum sensing receiver (Chapters 3 and 5) or a LacI- and TetR-driven genetic toggle switch (Chapter 4). Under the culture conditions, the quorum sensing reporter signal was detected even without addition of the signaling molecule (Chapter 3). The genetic toggle switch was stable when the system began in the high-LacI expression state, but after 5 days of culture, >5% of high-TetR expression cells began to consistently express the high-LacI state (Chapter 4). This system was also employed to track lineages of cells using real-time microscopy, which successfully characterized the inheritance of aberrant, enlarged cell phenotypes under stress (Chapter 5). Another microfluidic device, a droplet bioreactor, was also developed to culture small numbers of cells in an aqueous bubble suspended in oil (Chapter 6). Quorum sensing receiver cellswere cultured in this device, demonstrating that it is well suited for testing the effects of compounds on biofilms within water-in-oil droplets. / Ph. D.

This dissertation is concerned with the potential multistability of protein concentrations in the cell that can arise in biochemical networks. That is, situations where one, or a family of, proteins may sit at one of two or more different steady state concentrations in otherwise identical cells, and in spite of them being in the same environment. Models of multisite protein phosphorylation have shown that this mechanism is able to exhibit unlimited multistability. Nevertheless, these models have not considered enzyme docking, the binding of the enzymes to one or more substrate docking sites, which are separate from the motif that is chemically modified. Enzyme docking is, however, increasingly being recognised as a method to achieve specificity in protein phosphorylation and dephosphorylation cycles. Most models in the literature for these systems are deterministic i.e. based on Ordinary Differential Equations, despite the fact that these are accurate only in the limit of large molecule numbers. For small molecule numbers, a discrete probabilistic, stochastic, approach is more suitable. However, when compared to the tools available in the deterministic framework, the tools available for stochastic analysis offer inadequate visualisation and intuition. We firstly try to bridge that gap, by developing three tools: a) a discrete `nullclines' construct applicable to stochastic systems - an analogue to the ODE nullcines, b) a stochastic tool based on a Weakly Chained Diagonally Dominant M-matrix formulation of the Chemical Master Equation and c) an algorithm that is able to construct non-reversible Markov chains with desired stationary probability distributions. We subsequently prove that, for multisite protein phosphorylation and similar models, in the deterministic domain, enzyme docking and the consequent substrate enzyme-sequestration must inevitably limit the extent of multistability, ultimately to one steady state. In contrast, bimodality can be obtained in the stochastic domain even in situations where bistability is not possible for large molecule numbers. We finally extend our results to cases where we have an autophosphorylating kinase, as for example is the case with $Ca^{2+}$/calmodulin-dependent protein kinase II (CaMKII), a key enzyme in synaptic plasticity.