The Hippo-YAP/TAZ signaling pathway plays a critical role in tissue homeostasis, tumorigenesis, and degeneration disorders. The regulation of YAP/TAZ levels is controlled by a complex regulatory network, where several feedback loops have been identified. However, it remains elusive how these feedback loops contain the YAP/TAZ levels and maintain the system in a healthy physiological state or trap the system into pathological conditions. Here, a mathematical model was developed to represent the YAP/TAZ regulatory network. Through theoretical analyses, three distinct states that designate the three physiological and pathological outcomes were found. The transition from the physiological state to the two pathological states is mechanistically controlled by coupled bidirectional bistable switches, which are robust to parametric variation and stochastic fluctuations at the molecular level. This work provides a mechanistic understanding of the regulation and dysregulation of YAP/TAZ levels in tissue state transitions.

This project begins with an overview of the female reproductive tract microenvironment. It outlines the microenvironment of the vaginal, cervical, and endometrial epithelium and the interactions with immune cells and hormone cycles. The review also outlines the models currently used to study the female reproductive tract. The second chapter of the thesis is a study of the effects of pathogenic and commensal bacteria P. micra, F. magna, and F. nucleatum on cervical epithelial cells. This study analyzes cytotoxic effects after 24 hour infection of these bacteria. This was assessed through crystal violet staining, conventional pcr of cDNA synthesized from extracted cervical RNA, and LDH analysis. There is also an attempted biofilm assay. It was concluded that bacteria P. micra, F. magna and F. nucleatum have cytotoxic potential. This was not expected as F. magna is largely understood to be a commensal bacteria in the vaginal microbiome.

Gene circuit engineering facilitates the discovery and understanding of fundamental biology and has been widely used in various biological applications. In synthetic biology, gene circuits are often constructed by two main strategies: either monocistronic or polycistronic constructions. The Latter architecture can be commonly found in prokaryotes, eukaryotes, and viruses and has been largely applied in gene circuit engineering. In this work, the effect of adjacent genes and noncoding regions are systematically investigated through the construction of batteries of gene circuits in diverse scenarios. Data-driven analysis yields a protein expression metric that strongly correlates with the features of adjacent transcriptional regions (ATRs). This novel mathematical tool helps the guide for circuit construction and has the implication for the design of synthetic ATRs to tune gene expression, illustrating its potential to facilitate engineering complex gene networks. The ability to tune RNA dynamics is greatly needed for biotech applications, including therapeutics and diagnostics. Diverse methods have been developed to tune gene expression through transcriptional or translational manipulation. Control of RNA stability/degradation is often overlooked and can be the lightweight alternative to regulate protein yields. To further extend the utility of engineered ATRs to regulate gene expression, a library of RNA modules named degradation-tuning RNAs (dtRNAs) are designed with the ability to form specific 5’ secondary structures prior to RBS. These modules can modulate transcript stability while having a minimal interference on translation initiation. Optimization of their functional structural features enables gene expression level to be tuned over a wide dynamic range. These engineered dtRNAs are capable of regulating gene circuit dynamics as well as noncoding RNA levels and can be further expanded into cell-free system for gene expression control in vitro. Finally, integrating dtRNA with synthetic toehold sensor enables improved paper-based viral diagnostics, illustrating the potential of using synthetic dtRNAs for biomedical applications.

Glioblastoma Multiforme (GBM) is a grade IV astrocytoma and the most aggressive form of cancer that begins within the brain. The two-year average survival rate of GBM in the United States of America is 25%, and it has a higher incidence in individuals within the ages of 45 - 60 years. GBM Tumor formation can either begin as normal brain cells or develop from an existing low-grade astrocytoma and are housed by the perivascular niche in the brain microenvironment. This niche allows for the persistence of a population of cells known as glioma stem cells (GSC) by supplying optimum growth conditions that build chemoresistance and cause recurrence of the tumor within two to five years of treatment. It has therefore become imperative to understand the role of the perivascular niche on GSCs through in vitro modelling in order to improve the efficiency of therapeutic treatment and increase the survival rate of patients with GBM.

In this study, a unique three dimensional (3D) microfluidic platform that permitted the study of intercellular interactions between three different cell types in the perivascular niche of the brain was developed and utilized for the first time. Specifically, human endothelial cells were embedded in a fibrin matrix and introduced into the vascular layer of the microfluidic platform.

After spontaneous formation of a vascular layer, Normal Human Astrocytes and Patient derived GSC were embedded in a Matrigel® matrix and incorporated in the stroma and tumor regions of the microfluidic device respectively.

Using the established platform, migration, proliferation and stemness of GSCs studies were conducted. The findings obtained indicate that astrocytes in the perivascular niche significantly increase the migratory and proliferative properties of GSCs in the tumor microenvironment, consistent with previous in vivo findings.

The novel GBM tumor microenvironment developed herein, could be utilized for further

in-depth cellular and molecular level studies to dissect the influence of individual factors within the tumor niche on GSCs biology, and could serve as a model for developing targeted therapies.

The human transcriptional regulatory machine utilizes hundreds of transcription factors which bind to specific genic sites resulting in either activation or repression of targeted genes. Networks comprised of nodes and edges can be constructed to model the relationships of regulators and their targets. Within these biological networks small enriched structural patterns containing at least three nodes can be identified as potential building blocks from which a network is organized. A first iteration computational pipeline was designed to generate a disease specific gene regulatory network for motif detection using established computational tools. The first goal was to identify motifs that can express themselves in a state that results in differential patient survival in one of the 32 different cancer types studied. This study identified issues for detecting strongly correlated motifs that also effect patient survival, yielding preliminary results for possible driving cancer etiology. Second, a comparison was performed for the topology of network motifs across multiple different data types to identify possible divergence from a conserved enrichment pattern in network perturbing diseases. The topology of enriched motifs across all the datasets converged upon a single conserved pattern reported in a previous study which did not appear to diverge dependent upon the type of disease. This report highlights possible methods to improve detection of disease driving motifs that can aid in identifying possible treatment targets in cancer. Finally, networks where only minimally perturbed, suggesting that regulatory programs were run from evolved circuits into a cancer context.

Malignant Pleural Mesothelioma is a type of lung cancer usually discovered at an advanced stage at which point there is no cure. Six primary MPM cell lines were used to conduct in vitro research to make conclusions about specific gene mutations associated with Mesothelioma. DNA exome sequencing, a time efficient and inexpensive technique, was used for identifying specific DNA mutations. Computational analysis of exome sequencing data was used to make conclusions about copy number variation among common MPM genes. Results show a CDKN2A gene heterozygous deletion in Meso24 cell line. This data is validated by a previous CRISPR-Cas9 outgrowth screen for Meso24 where the knocked-out gene caused increased Meso24 growth.

Malignant Pleural Mesothelioma (MPM) is an aggressive deadly tumor that has few therapeutic options. Immunotherapies have shown great potential in alleviating MPM patient symptoms. Using patient data from the Cancer Genome Atlas (TCGA) we sought to identify mutations, regulators, and immune factors driving immune cell migration. We explored computational methods to define regulatory causal flows in order to make biological predictions. These predictions were verified by cross-referencing peer-reviewed articles. A disease-relevant inference model was developed to examine the chemokine IL-18’s effect on natural killer cell (NK cell) migration.

The purpose of this project was to characterize the mucin layer in patients with eosinophilic esophagitis (EoE). EoE is a chronic disease that is characterized by eosinophilic inflammation in the esophagus. The current diagnosis and standard of care for patients with EoE is less than ideal. Diagnosis is highly invasive as it requires histological confirmation of eosinophilic inflammation in the esophagus, the patient must undergo an upper endoscopy to obtain the tissue sample. The histology as determined by the pathologist is subjective not quantitative which causes significant error in diagnosis. The current treatment methods are dietary therapy or corticosteroids, which require significant cost and time. The pathology of EoE is largely unknown, though it is known to involve allergic inflammatory and type-2 cytokine-mediated responses. Past studies have determined the genetic expression of mucins to be varied in the esophagi of EoE patients using RNA sequencing techniques. The varied expression of mucins in the esophagi of EoE patients has not been validated at the protein level. This study sought to better define mucin protein expression, specifically that of MUC1, MUC4, and MUC7, in the esophagi of EoE patients (n=4) and control patients (n=3). This was accomplished using histological staining. The tissue samples were stained for eosinophil peroxidase (EPX) in order to visualize the eosinophils, which are a pathological marker of EoE. The results of this study showed a qualitative increase in the protein expression of MUC4 in patients with EoE, indicating that MUC4 may play a protective role in the body’s defense against EoE. MUC1 and MUC7 staining showed no pattern. This study defined the conditions necessary for precise staining of esophageal tissues with the MUC4 8G7 antibody. The orientation of the tissue samples on the slides and the small sample size created significant difficulty in analysis and inhibited quantitative analysis. Future studies with tissue orientation standardization and greater sample size are needed to confirm the findings of this study. If verified, the increase of MUC4 protein expression in patients with EoE has implications for EoE diagnostics and therapeutics.

The WNT signaling pathway plays numerous roles in development and maintenance of adult homeostasis. In concordance with it’s numerous roles, dysfunction of WNT signaling leads to a variety of human diseases ranging from developmental disorders to cancer. WNT signaling is composed of a family of 19 WNT soluble secreted glycoproteins, which are evolutionarily conserved across all phyla of the animal kingdom. WNT ligands interact most commonly with a family of receptors known as frizzled (FZ) receptors, composed of 10 independent genes. Specific interactions between WNT proteins and FZ receptors are not well characterized and are known to be promiscuous, Traditionally canonical WNT signaling is described as a binary system in which WNT signaling is either off or on. In the ‘off’ state, in the absence of a WNT ligand, cytoplasmic β-catenin is continuously degraded by the action of the APC/Axin/GSK-3β destruction complex. In the ‘on’ state, when WNT binds to its Frizzled (Fz) receptor and LRP coreceptor, this protein destruction complex is disrupted, allowing β-catenin to translocate into the nucleus where it interacts with the DNA-bound T cell factor/lymphoid factor (TCF/LEF) family of proteins to regulate target gene expression. However in a variety of systems in development and disease canonical WNT signaling acts in a gradient fashion, suggesting more complex regulation of β-catenin transcriptional activity. As such, the traditional ‘binary’ view of WNT signaling does not clearly explain how this graded signal is transmitted intracellularly to control concentration-dependent changes in gene expression and cell identity. I have developed an in vitro human pluripotent stem cell (hPSC)-based model that recapitulates the same in vivo developmental effects of the WNT signaling gradient on the anterior-posterior (A/P) patterning of the neural tube observed during early development. Using RNA-seq and ChIP-seq I have characterized β-catenin binding at different levels of WNT signaling and identified different classes of β-catenin peaks that bind cis-regulatory elements to influence neural cell fate. This work expands the traditional binary view of canonical WNT signaling and illuminates WNT/β-catenin activity in other developmental and diseased contexts.