Three studies were conducted to achieve the following respective objectives: 1) to determine the cellular mechanism by which growth hormone (GH) stimulates skeletal muscle growth; 2) to identify the signaling pathways that mediate the different effects of insulin-like growth factor I (IGF-I) on skeletal muscle growth; and 3) to determine the role of a functionally unknown gene named SH3 and cysteine rich domain 3 (STAC3) in myogenesis. In the first study, the myogenic precursor cells, satellite cells, were isolated from cattle and allowed to proliferate as myoblasts or induced to fuse into myotubes in culture. GH increased protein synthesis without affecting protein degradation in myotubes; GH had no effect on proliferation of myoblasts; GH had no effect on IGF-I mRNA expression in either myoblasts or myotubes. These data suggest that GH stimulates skeletal muscle growth in cattle in part through stimulation of protein synthesis and that this stimulation is not mediated through increased IGF-I mRNA expression in the muscle. In the second study, the signaling pathways mediating the effects of IGF-I on proliferation of bovine myoblasts and protein synthesis and degradation in bovine myotubes were identified by adding to the culture medium rapamycin, LY294002, and PD98059, which are specific inhibitors of the signaling molecules mTOR, AKT, and ERK, respectively. The effectiveness of these inhibitors was confirmed by Western blotting. Proliferation of bovine myoblasts was stimulated by IGF-I, and this stimulation was partially blocked by PD98059 and completely blocked by rapamycin or LY294002. Protein degradation in myotubes was inhibited by IGF-I and this inhibition was completely relieved by LY294002, but not by rapamycin or PD98059. Protein synthesis in myotubes was increased by IGF-I, and this increase was completely blocked by rapamycin, LY294002, or PD98059. These data demonstrate that IGF-I stimulates proliferation of bovine myoblasts and protein synthesis in bovine myotubes through both the PI3K/AKT and the MAPK signaling pathways and that IGF-I inhibits protein degradation in bovine myotubes through the PI3K/AKT pathway only. In the third study, the potential roles of STAC3 in myoblast proliferation, differentiation, and fusion were investigated. Overexpression of STAC3 inhibited differentiation of C2C12 cells (a murine myoblast cell line) and fusion of these cells into myotubes, whereas knockdown of STAC3 had the opposite effects. Either STAC3 overexpression or STAC3 knockdown had no effect on proliferation of C2C12 cells. Myoblasts from STAC3-deficient mouse embryos had a greater ability to fuse into myotubes than control myoblasts; the former cells also expressed more mRNAs for the myogenic regulators MyoD and myogenin and the adult myosin heavy chain protein MyHC1 than the latter. These results suggest that STAC3 inhibits myoblast differentiation and fusion. / Ph. D.

Automated analysis of networks of interactions between proteins has become pervasive in molecular biology. Each node in such a network represents a protein and each edge an interaction between two proteins. Nearly every publication that uses network analysis includes a visualization of a graph in which the nodes and edges are laid out in two dimensions. Several systems implement multiple types of graph layout algorithms and make them easily accessible to scientists. Despite the existence of these systems, interdisciplinary research teams in computational biology face several challenges in sharing computed networks and interpreting them. This thesis presents two systemsGraphSpace and GraphCrowdthat together enhance network-based collaboration. GraphSpace users can automatically and rapidly share richly- annotated networks, irrespective of the algorithms or software used to generate them. A user may search for networks that contain a specific node or edge, or a collection of nodes and edges. Users can manually modify a layout, save it, and share it with other users. Users can create private groups, invite other users to join groups, and share networks with group members. Upon publication, researchers may make networks public and provide a URL in the paper. GraphCrowd addresses the challenging posed by automated layout algorithms, which incorporate almost no knowledge of the biological information underlying the networks. These algorithms compel researchers to use their knowledge and intuition to modify the node and edge positions manually to bring out salient features. GraphCrowd focuses on signaling networks, which connect proteins that represent a cells response to external signals. Treating network layout as a design problem, GraphCrowd explores the feasibility of leveraging human computation via crowdsourcing to create simplified and meaningful visualizations. GraphCrowd provides a streamlined interface that enables crowd workers to easily manipulate networks to create layouts that follow a specific set of guidelines. GraphCrowd also implements an interface to allow a user (e.g., an expert or a crowd worker) to evaluate how well a layout conforms to the guidelines. We use GraphCrowd to address two research questions: (i) Can we harness the power of crowdsourcing to create simplified, biologically meaningful visualizations of signaling networks?(ii) Can crowd workers rate layouts similarly to how an expert with domain knowledge would rate them? We design two systematic experiments that enable us to answer both questions in the affirmative. This thesis establishes crowdsourcing as a powerful methodology for laying out complex signaling networks. Moreover, by developing appropriate domain-specific guidelines for crowd workers, GraphCrowd can be generalized to a variety of applications. / Master of Science

In eukaryotes, distinct nutrient signals are integrated in order to produce robust cellular responses to fluctuations in the environment. This process of signal integration is attributed to the crosstalk between nutrient specific signaling pathways, as well as the large degree of overlap between their regulatory targets. In the budding yeast Saccharomyces cerevisiae, these distinct pathways have been well characterized. However, the significant overlap between these pathways confounds the interpretation of the overall regulatory logic in terms of nutrient-dependent cell state determination. Here, we propose a literature-curated molecular mechanism of the integrated nutrient signaling pathway in budding yeast, focussing on carbon and nitrogen signaling. We build a computational model of this pathway to reconcile the available experimental data with our proposed molecular mechanism. We evaluate the robustness of the model fit to data with respect to the variations in the values of kinetic parameters used to calibrate the model. Finally, we use the model to make novel, experimentally testable predictions of transcription factor activities in mutant strains undergoing complex nutrient shifts. We also propose a novel framework, called BoolODE for utilizing published Boolean models to generate synthetic datasets used to benchmark the performance of algorithms performing gene regulatory network inference from single cell RNA sequencing data. / Doctor of Philosophy / An important problem in biology is how organisms sense and adapt to ever changing environments. A good example of an environmental cue that affects animal behavior is the availability of food; scarcity of food forces animals to search for food-rich habitats, or go into hibernation. At the level of single cells, a range of behaviors are observed depending on the amount of food, or nutrients present in the environment. Moreover, different types of nutrients are important for different biological functions in single cells, and each different nutrient type will have to be available in the right quantities to support cellular growth. At the subcellular level, intricate molecular machineries exist which sense the amounts of each nutrient type, and interpret this information in order to make a decision on how best to respond. This interpretation and integration of nutrient information is a complex, poorly understood process even in a simple unicellular organism like the budding yeast. In order to understand this process, termed nutrient signaling, we propose a mathematical model of how yeasts respond to nutrient availability in the environment. Our model advances the state of knowledge by presenting the first comprehensive mathematical model of the nutrient signaling machinery, accounting for a variety of experimental observations from the last three decades of yeast nutrient signaling. We use our model to make predictions on how yeasts might behave when supplied with different combinations of nutrients, which can be verified by experiments. Finally, the cellular machinery that helps yeasts respond to nutrient availability in the environment is very similar to the machinery in cancer cells that causes them to grow rapidly. Our proposed model can serve as a stepping stone towards the construction of a model of cancer's responses to its nutritional environment.

Signaling pathways are widely studied in systems biology. Several databases catalog our knowledge of these pathways, including the proteins and interactions that comprise them. However, high-quality curation of this information is slow and painstaking. As a result, many interactions still lack annotation concerning the pathways they participate in. A natural question that arises is whether or not it is possible to automatically leverage existing annotations to identify new interactions for inclusion in a given pathway. Here, we present RegLinker, an algorithm that achieves this purpose by computing multiple short paths from pathway receptors to transcription factors (TFs) within a background interaction network. The key idea underlying RegLinker is the use of regular-language constraints to control the number of non-pathway edges present in the computed paths. We systematically evaluate RegLinker and alternative approaches against a comprehensive set of 15 signaling pathways and demonstrate that RegLinker exhibits superior recovery of withheld pathway proteins and interactions. These results show the promise of our approach for prioritizing candidates for experimental study and the broader potential of automated analysis to attenuate difficulties of traditional manual inquiry. / Master of Science / Cells in the human body are constantly receiving signals that inform their response to a variety of conditions. These signals serve as cues to a cell, allowing it to make informed decisions that impact cellular processes such as movement, growth, and death. Cells employ proteins and the interactions between them to achieve these capabilities. Signals manifest as molecules that interact with proteins bound to membrane of a cell. When this happens, a cascade of interactions between the proteins inside the cell will be set off. Ultimately, this cascade activate or inhibit the cell’s production of new proteins, constituting a response to the signal received. The proteins and interactions involved in such a cascade together form what is known as a signaling pathway. Experiments have uncovered the interactions that are present in many signaling pathways, and researchers have carefully cataloged this information in publicly available databases. However, high-quality curation is slow and painstaking, and many known interactions have not been annotated as belonging to any pathway. A natural question that arises is whether or not it is possible to leverage existing annotations to automatically determine which new interactions to include in a given pathway. In this thesis, we present an efficient algorithm, RegLinker, for this purpose. We evaluate this method and alternative approaches on a comprehensive set of 15 signaling pathways and demonstrate that RegLinker is better at recovering interactions withheld from these pathways. In particular, we show RegLinker’s superior ability to identify interactions that utilize proteins that were not previously considered part of a pathway. These results underscore the promise of our approach for prioritizing candidates for experimental study and the broader potential of automated analysis to attenuate difficulties of traditional manual inquiry.

INTRODUCTION: Porphyromonas gingivalis (P.g), a gram-negative anaerobe, is the major bacterium in the red complex (Socransky et al. 1998) and responsible for the onset and progression of severe periodontal disease. P. gingivalis is currently considered the ‘keystone’ pathogen of periodontal disease. It can produce several virulence factors, such as cysteine proteinases (gingipains), lipopolysaccharide (LPS), capsule and fimbriae. The LPS plays an important role in periodontal disease by inducing inflammation via stimulation of some cytokines such as TNF-ɑ. TNF-ɑ can activate expression of early response genes in macrophages, including Tumor Necrosis Factor-?-Induced Protein 1 (TNFAIP1). However, the role of TNFAIP1 in LPS-induced inflammation is largely unknown. OBJECTIVE: 1. Identification of TNFAIP1 biological functions in response to LPS/TNF-ɑ; 2. Identification of the TNFAIP1 mediated signaling pathway; 3. Determination of factors involved in the TNFAIP-dependent signaling pathway; 4. Analysis of TNFAIP1 promoter activity. MATERIALS AND METHODS: Mouse RAW cells, human THP-1 cells or MC3T3 cells were cultured in RPMI or ɑ-MEM media with 10% FBS at 37°C in 5% CO2. For DNA construction of TNFAIP1 cDNA or its promoter, DNAs were generated by polymerase chain reaction (PCR) with specific primers and templates. The cloned DNA sequences were confirmed by sequencing. Experiments to identify the biological function of TNFAIP1 and its promoter activity, utilized ELISA, DNA recovery, western blot, protein array, and promoter assay. RESULTS: 1. LPS-induced the activation of p-MARK or p-PI3K (but not p-JAK), the production of TNF-ɑ, NFĸB or TNFAIP1 was confirmed by ELISA and western blot analysis; 2. Transfection of TNFAIP1 cDNA for 1-10 hours stimulated TNF-ɑ production in macrophage cells but not after longer exposure; 3. Caspase 1 and 3 were induced by TNFAIP1 after transfection of TNFAIP1 for 20 hours; 4. Overexpression of TNFAIP1 induced apoptotic proteins, such as Bcl-x, Caspase 3, Catalase, Claspin, Cytochromic, HO-1/HMOX1/HSP32, MCL-1, P27/Kip1, or SMAC/Diablo; 5. TNFAIP1 promoter DNA was cloned into pGL3 basic plasmid DNA to determine promoter activity. TNFAIP1 promoter activity was tested via its potential protein-protein interaction using luciferase gene expression. With a MAPK inhibitor, TNFAIP1 promoter activity was increased. In contrast, with an ATK inhibitor, TNFAIP1 promoter activity was reduced. CONCLUSIONS: 1. TNFAIP1 is an important factor of the LPS/TNF-ɑ-dependent pathway; 2. MAPK or PI3K functions as an upstream factor of TNFAIP1, and LITAF is downstream factor of TNFAIP1-mediated signaling pathway in response to LPS; 3. Transfection of TNFAIP1 cDNA stimulated TNF-ɑ production for 1-10 hours exposure but reduced it for 10 - 20 hours exposure; 4. Overexpression of TNFAIP1 can increase expression of apoptotic proteins, Bcl-x, Caspase 3, Catalase, Claspin, Cytochromic, HO-1/HMOX1/HSP32, MCL-1, P27/Kip1, or SMAC/Diablo; 5. AKT and MAPK may act as transcriptional regulators of TNFAIP1 gene by binding to the promoter region. AKT upregulates TNFAIP1 gene expression and MAPK downregulates TNFAIP1 gene expression.

Yes / Background: Many urothelial carcinomas (UC) contain activating PIK3CA mutations. In telomerase-immortalized normal urothelial cells (TERT-NHUC), ectopic expression of mutant PIK3CA induces PI3K pathway activation, cell proliferation and cell migration. However, it is not clear whether advanced UC tumors are PIK3CA-dependent and whether PI3K pathway inhibition is a good therapeutic option in such cases. Methods: We used retrovirus-mediated delivery of shRNA to knock down mutant PIK3CA in UC cell lines and assessed effects on pathway activation, cell proliferation, migration and tumorigenicity. The effect of the class I PI3K inhibitor GDC-0941 was assessed in a panel of UC cell lines with a range of known molecular alterations in the PI3K pathway. Results: Specific knockdown of PIK3CA inhibited proliferation, migration, anchorage-independent growth and in vivo tumor growth of cells with PIK3CA mutations. Sensitivity to GDC-0941 was dependent on hotspot PIK3CA mutation status. Cells with rare PIK3CA mutations and co-occurring TSC1 or PTEN mutations were less sensitive. Furthermore, downstream PI3K pathway alterations in TSC1 or PTEN or co-occurring AKT1 and RAS gene mutations were associated with GDC-0941 resistance. Conclusions: Mutant PIK3CA is a potent oncogenic driver in many UC cell lines and may represent a valuable therapeutic target in advanced bladder cancer.

In Saccharomyces cerevisiae, retrograde signaling is utilized as a pathway of communication from the mitochondria to the nucleus, regulating nuclear gene expression and allowing the cell to adapt to mitochondrial dysfunction. A key target of this pathway is CIT2, which encodes a peroxisomal citrate synthase essential for metabolic adaptation. This study aimed to investigate the complex composition of the retrograde initiating protein, Rtg2p. Through co-immunoprecipitation and size exclusion chromatography, Rtg2p was found to form a high molecular weight complex that contained multiple copies of Rtg2p. Previously generated mutations in the carboxyl terminus of Rtg2p shown to negatively impact CIT2 transcriptional upregulation, demonstrated reduced Rtg2p-Rtg2p self-association indicating the critical role of these interactions in retrograde signaling. These findings highlight the importance of protein interactions in maintaining the function of the Rtg2p complex, essential for effective cellular adaptation.

The cornea, which is the outermost part of the anterior segment of the eye, is composed of an outer stratified epithelium, an inner endothelial monolayer, and a collagen-rich, avascular stroma. The corneal endothelium and stroma are derived from neural crest cells (NCCs), while the corneal epithelium develops from surface ectoderm (SE). Our lab has developed a mutant mouse model lacking expression of activating protein 2β (AP-2β), a transcription factor critical in corneal development, in NCC-derived tissues utilizing the Wnt1Cre transgene. In this mutant mouse model, we have observed an absent endothelium, a vascularized stroma, and a non-stratified epithelium. The lack of proper corneal epithelial stratification is interesting to note as AP-2β expression is unaltered in the SE-derived corneal epithelium. A possible mechanism for the observed lack of stratification may be due to altered Wnt/β-catenin/bone morphological protein 4 (BMP4) signalling between the corneal stroma and the epithelium. Thus, the purpose of this thesis was to investigate changes in Wnt/β-catenin/BMP4 signaling in the absence of stromal AP-2β expression and determine whether the lack of corneal epithelial stratification can be rescued. Immunohistochemical staining of corneal sections revealed that compared to controls, AP-2β NCC KO mutant mice experienced elevated Wnt/β-catenin signaling and reduced BMP4 signaling at later timepoints. Due to the decrease in BMP4 signaling, we hypothesized that administration of exogenous BMP4 delivered via subconjunctival injections would increase BMP4 downstream signaling and trigger corneal epithelial stratification in mutant mice. Haematoxylin and eosin staining of BMP4 treated mice revealed a change in corneal epithelial stratification in control mice compared to untreated control mice. However, no change in corneal epithelial stratification was observed between untreated and BMP4 treated mutant eyes. Ultimately, these results indicate that AP-2β expression in NCC-derived tissues are critical for corneal epithelial stratification. / Thesis / Master of Science (MSc) / Limbal stem cell deficiency is a corneal disorder caused by the death or dysfunction of limbal epithelial stem cells that reside in the limbal epithelium. Due to the importance of these stem cells in corneal health and maintenance, patients suffering from this condition are at risk for corneal ulceration, neovascularization, scarring, and ultimately, corneal blindness. Our lab has developed a mutant mouse model that displays a similar phenotype to patients suffering from limbal stem cell deficiency. In this thesis, we explored the importance of cell signaling in corneal development and identified changes to signaling in our mutant mouse model. Furthermore, we investigated whether a potential treatment could rescue the phenotype observed in our mutant mouse model, allowing them to return to a normal phenotype. Results from this thesis allowed us to gain a better insight into the pathology of limbal stem cell deficiency, which can help guide future treatments, procedures, and therapies.

Skeletal muscle is the most abundant muscle in the body and performs important bodily functions such as movement, body temperature regulation, joint stabilization, etc. It requires calcium ions (Ca2+) for proper function, growth, development, and repair. Regulated Ca2+ signaling is crucial for muscle health and perturbation of Ca2+ signaling can, therefore, lead to a multitude of muscle pathophysiologies, one of which is atrophy. Skeletal muscle atrophy results from loss of proteins leading to loss of muscle mass and, unfortunately, there are no effective pharmacological therapies presently available for it. The only truly effective treatment includes exercise and proper diet. Physical activity is not a feasible option for ailing and aging populations who have the most occurrence of skeletal muscle atrophy. Thus, it is imperative to explore various molecular mechanisms which can initiate and contribute to skeletal muscle atrophy in order to elucidate possible pharmacological interventions. That is where this dissertation comes into place. The potassium (K+) channel, ERG1A, induces atrophy in the skeletal muscle of mice when ectopically expressed. Indeed, the human homolog of this atrophy-inducing K+ channel increases basal cytosolic Ca2+ concentration in cultured mouse skeletal muscle cells, C2C12. Here, we sought to discover the sources of the increased cytosolic Ca2+. To that end, we explored the effect of HERG1A overexpression on multiple important calcium signaling pathways. We discovered that HERG1A affects various Ca2+ signaling mechanisms in skeletal muscle cells. We show that HERG1A enhances the very abundant extracellular Ca2+ entry mechanism of SOCE (store operated calcium entry) to increase cytosolic Ca2+ levels. We also show that HERG1A also increases RyR1 (ryanodine receptor 1) signaling along with ECCE (excitation coupled calcium entry) in skeletal muscle cells. Most interestingly, we connected all these HERG1A-modulated pathways by showing that HERG1A modulates the global Ca2+ homeostasis regulator, Calsequestrin1 (CSQ1) both at the level of transcription and translation. This suggests that HERG1A is a global Ca2+ homeostasis regulator itself. We speculate that HERG1A is affecting the various Ca2+ signaling mechanisms in cells via its regulation of the levels of CSQ1 and thereby modulating the availability of cytosolic Ca2+ in the cells. This dissertation thus summarizes the vastness of HERG1A regulation of Ca2+ homeostasis in skeletal muscle cells. Furthermore, this dissertation also shows how HERG1A affects various mechanisms in skeletal muscle cells which could also have roles in apoptosis and cancer. Most importantly, HERG1A in skeletal muscle cells has been shown to have a real and significant impact on the functioning of multiple cellular signaling pathways and not the levels of the members of such pathways which reveals for the first time a mechanistic control of the intracellular pathways in skeletal muscle cells by this voltage gated K+ channel.

Typescript (photocopy). / Digitized by Kansas Correctional Industries