Dynamic Compartmentalization of Persistent UPEC in the Superficial Bladder Epithelium

Urinary tract infections (UTIs) are typically caused by bacteria that colonize different regions of the urinary tract, mainly the bladder and the kidney. Approximately 25% of women that suffer from UTIs experience a recurrent infection within 6 months of the initial bout, making UTIs a serious economic burden resulting in more than 10 million hospital visits and $3.5 billion in healthcare costs in the United States alone. Type-1 fimbriated Uropathogenic E. coli (UPEC) is the major causative agent of UTIs, accounting for almost 90 % of bacterial UTIs. The unique ability of UPEC to bind and invade the superficial bladder epithelium allows the bacteria to persist inside epithelial niches and survive antibiotic treatment. Persistent, intracellular UPEC are retained in the bladder epithelium for long periods, making them a source of recurrent UTIs. Hence, the ability of UPEC to persist in the bladder is a matter of major health and economic concern, making studies exploring the underlying mechanism of UPEC persistence highly relevant.

In my thesis, I will describe how intracellular Uropathogenic E.coli (UPEC) evade host defense mechanisms in the superficial bladder epithelium. I will also describe some of the unique traits of persistent UPEC and explore strategies to induce their clearance from the bladder. I have discovered that the UPEC virulence factor Alpha-hemolysin (HlyA) plays a key role in the survival and persistence of UPEC in the superficial bladder epithelium. In-vitro and in-vivo studies comparing intracellular survival of wild type (WT) and hemolysin deficient UPEC suggested that HlyA is vital for UPEC persistence in the superficial bladder epithelium. Further in-vitro studies revealed that hemolysin helped UPEC persist intracellularly by evading the bacterial expulsion actions of the bladder cells and remarkably, this virulence factor also helped bacteria avoid t degradation in lysosomes.

To elucidate the mechanistic basis for how hemolysin promotes UPEC persistence in the urothelium, we initially focused on how hemolysin facilitates the evasion of UPEC expulsion from bladder cells. We found that upon entry, UPEC were encased in “exocytic vesicles” but as a result of HlyA expression these bacteria escaped these vesicles and entered the cytosol. Consequently, these bacteria were able to avoid expulsion by the cellular export machinery.

Since bacteria found in the cytosol of host cells are typically recognized by the cellular autophagy pathway and transported to the lysosomes where they are degraded, we explored why this was not the case here. We observed that although cytosolic HlyA expressing UPEC were recognized and encased by the autophagy system and transported to lysosomes, the bacteria appeared to avoid degradation in these normally degradative compartments. A closer examination of the bacteria containing lysosomes revealed that they lacked V-ATPase. V-ATPase is a well-known proton pump essential for the acidification of mammalian intracellular degradative compartments, allowing for the proper functioning of degradative proteases. The absence of V-ATPase appeared to be due to hemolysin mediated alteration of the bladder cell F-actin network. From these studies, it is clear that UPEC hemolysin facilitates UPEC persistence in the superficial bladder epithelium by helping bacteria avoid expulsion by the exocytic machinery of the cell and at the same time enabling the bacteria avoid degradation when the bacteria are shuttled into the lysosomes.

Interestingly even though UPEC appear to avoid elimination from the bladder cell their ability to multiple in bladder cells seem limited.. Indeed, our in-vitro and in-vivo experiments reveal that UPEC survive in superficial bladder epithelium for extended periods of time without a significantly change in CFU numbers. Indeed, we observed these bacteria appeared quiescent in nature. This observation was supported by the observation that UPEC genetically unable to enter a quiescence phase exhibited limited ability to persist in bladder cells in vitro and in vivo, in the mouse bladder.

The studies elucidated in this thesis reveal how UPEC toxin, Alpha-hemolysin plays a significant role in promoting UPEC persistence via the modulation of the vesicular compartmentalization of UPEC at two different stages of the infection in the superficial bladder epithelium. These results highlight the importance of UPEC Alpha-hemolysin as an essential determinant of UPEC persistence in the urinary bladder.

Efficient Computation of Electromagnetic Waves in Hydrocarbon Exploration Using the Improved Numerical Mode Matching (NMM) Method

In this study, we developed and improved the numerical mode matching (NMM) method which has previously been shown to be a fast and robust semi-analytical solver to investigate the propagation of electromagnetic (EM) waves in an isotropic layered medium. The applicable models, such as cylindrical waveguide, optical fiber, and borehole with earth geological formation, are generally modeled as an axisymmetric structure which is an orthogonal-plano-cylindrically layered (OPCL) medium consisting of materials stratified planarly and layered concentrically in the orthogonal directions.

In this report, several important improvements have been made to extend applications of this efficient solver to the anisotropic OCPL medium. The formulas for anisotropic media with three different diagonal elements in the cylindrical coordinate system are deduced to expand its application to more general materials. The perfectly matched layer (PML) is incorporated along the radial direction as an absorbing boundary condition (ABC) to make the NMM method more accurate and efficient for wave diffusion problems in unbounded media and applicable to scattering problems with lossless media. We manipulate the weak form of Maxwell's equations and impose the correct boundary conditions at the cylindrical axis to solve the singularity problem which is ignored by all previous researchers. The spectral element method (SEM) is introduced to more efficiently compute the eigenmodes of higher accuracy with less unknowns, achieving a faster mode matching procedure between different horizontal layers. We also prove the relationship of the field between opposite mode indices for different types of excitations, which can reduce the computational time by half. The formulas for computing EM fields excited by an electric or magnetic dipole located at any position with an arbitrary orientation are deduced. And the excitation are generalized to line and surface current sources which can extend the application of NMM to the simulations of controlled source electromagnetic techniques. Numerical simulations have demonstrated the efficiency and accuracy of this method.

Finally, the improved numerical mode matching (NMM) method is introduced to efficiently compute the electromagnetic response of the induction tool from orthogonal transverse hydraulic fractures in open or cased boreholes in hydrocarbon exploration. The hydraulic fracture is modeled as a slim circular disk which is symmetric with respect to the borehole axis and filled with electrically conductive or magnetic proppant. The NMM solver is first validated by comparing the normalized secondary field with experimental measurements and a commercial software. Then we analyze quantitatively the induction response sensitivity of the fracture with different parameters, such as length, conductivity and permeability of the filled proppant, to evaluate the effectiveness of the induction logging tool for fracture detection and mapping. Casings with different thicknesses, conductivities and permeabilities are modeled together with the fractures in boreholes to investigate their effects for fracture detection. It reveals that the normalized secondary field will not be weakened at low frequencies, ensuring the induction tool is still applicable for fracture detection, though the attenuation of electromagnetic field through the casing is significant. A hybrid approach combining the NMM method and BCGS-FFT solver based integral equation has been proposed to efficiently simulate the open or cased borehole with tilted fractures which is a non-axisymmetric model.

Sensor Planning for Bayesian Nonparametric Target Modeling

Bayesian nonparametric models, such as the Gaussian process and the Dirichlet process, have been extensively applied for target kinematics modeling in various applications including environmental monitoring, traffic planning, endangered species tracking, dynamic scene analysis, autonomous robot navigation, and human motion modeling. As shown by these successful applications, Bayesian nonparametric models are able to adjust their complexities adaptively from data as necessary, and are resistant to overfitting or underfitting. However, most existing works assume that the sensor measurements used to learn the Bayesian nonparametric target kinematics models are obtained a priori or that the target kinematics can be measured by the sensor at any given time throughout the task. Little work has been done for controlling the sensor with bounded field of view to obtain measurements of mobile targets that are most informative for reducing the uncertainty of the Bayesian nonparametric models. To present the systematic sensor planning approach to leaning Bayesian nonparametric models, the Gaussian process target kinematics model is introduced at first, which is capable of describing time-invariant spatial phenomena, such as ocean currents, temperature distributions and wind velocity fields. The Dirichlet process-Gaussian process target kinematics model is subsequently discussed for modeling mixture of mobile targets, such as pedestrian motion patterns.

Novel information theoretic functions are developed for these introduced Bayesian nonparametric target kinematics models to represent the expected utility of measurements as a function of sensor control inputs and random environmental variables. A Gaussian process expected Kullback Leibler divergence is developed as the expectation of the KL divergence between the current (prior) and posterior Gaussian process target kinematics models with respect to the future measurements. Then, this approach is extended to develop a new information value function that can be used to estimate target kinematics described by a Dirichlet process-Gaussian process mixture model. A theorem is proposed that shows the novel information theoretic functions are bounded. Based on this theorem, efficient estimators of the new information theoretic functions are designed, which are proved to be unbiased with the variance of the resultant approximation error decreasing linearly as the number of samples increases. Computational complexities for optimizing the novel information theoretic functions under sensor dynamics constraints are studied, and are proved to be NP-hard. A cumulative lower bound is then proposed to reduce the computational complexity to polynomial time.

Three sensor planning algorithms are developed according to the assumptions on the target kinematics and the sensor dynamics. For problems where the control space of the sensor is discrete, a greedy algorithm is proposed. The efficiency of the greedy algorithm is demonstrated by a numerical experiment with data of ocean currents obtained by moored buoys. A sweep line algorithm is developed for applications where the sensor control space is continuous and unconstrained. Synthetic simulations as well as physical experiments with ground robots and a surveillance camera are conducted to evaluate the performance of the sweep line algorithm. Moreover, a lexicographic algorithm is designed based on the cumulative lower bound of the novel information theoretic functions, for the scenario where the sensor dynamics are constrained. Numerical experiments with real data collected from indoor pedestrians by a commercial pan-tilt camera are performed to examine the lexicographic algorithm. Results from both the numerical simulations and the physical experiments show that the three sensor planning algorithms proposed in this dissertation based on the novel information theoretic functions are superior at learning the target kinematics with

little or no prior knowledge