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.

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.

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.

Typescript (photocopy). / Digitized by Kansas Correctional Industries

Die Entwicklung von Fernmetastasen ist die Haupttodesursache bei Tumorerkrankten und der entscheidende klinisch relevante Schritt während der Tumorprogression. Die Seed and Soil Theorie von Stephen Paget besagt, dass verschiedene Tumorzellen spezifische Zielorgane während der Metatasierung bevorzugen. Während das häufigste Target der kolorektalen Karzinome die Leber ist, hat der triple-negative molekulare Subtyp von Brustkrebs die Neigung, in das Gehirn zu metastasieren. Interessanterweise spielen sowohl deregulierte EGFR (Epithelial growth factor receptor) als auch WNT Signalwege in diesen beiden Entitäten eine entscheidende Rolle. Das Ziel der Arbeit ist, die Rolle der beiden Signalwege in soliden Tumorzelllinien in Bezug auf die Tumorprogression und Kolonisation zu untersuchen. Im Rahmen der molekularen Charakterisierung der Zelllinien zeigten sich die Mammakarzinomzelllinie 410.4 und die kolorektale Tumorzelllinie CMT-93 als passende Modellsysteme für unsere Fragestellung. Anschließend wurden der EGFR und der WNT Signalweg in diesen Zellen im Sinne von gain of function und loss of function moduliert und die Auswirkungen auf Aspekte der Tumorprogression analysiert. In CMT-93 Zellen wurde ein EGFR Knockdown etabliert. Während der Knockdown keinen Einfluss auf die Proliferation hat, vermindert er die Invasion der Zellen. Somit konnte dem effizienten Knockdown eine funktionelle Wirksamkeit zugeschrieben werden. Eine EGFR Überexpression konnte sowohl in 410.4 als auch in CMT-93 Zellen etabliert werden. Die Analyse der jeweiligen Signalkaskadenweiterleitung ergab zwar Änderungen und somit eine funktionelle Relevanz, dies blieb jedoch ohne Auswirkungen auf das Invasionspotential der Zelllinien. Ein Knockdown von β-Catenin konnte in 410.4 zwar etabliert werden, blieb jedoch ohne funktionelle Auswirkungen. Eine stabile Überexpression von β-Catenin war nicht erfolgreich, da dies offenbar mit der Viabilität der Zellen interferierte. Die Relevanz des β-Catenin-abhängigen WNT Signalwegs in den beiden gewählten Zelllinien konnte somit nicht abschließend geklärt werden. Des Weiteren wurde die Bedeutung des nicht-kanonischen WNT Signalwegs via ROR2 und WNT11 untersucht. Dabei ergab sich, dass die Überexpression von WNT11 und ROR2 in 410.4 Zellen deren Invasion durch einen RHOA-abhängigen Mechnismus steigert und einen Einfluss auf den PI3K Signalweg hat. Es ist anzunehmen, dass WNT11 als downstream Target über ROR2 induziert wird und über einen positiven Feedback-Loop via ROR2 eine autokrine Stimulation ausübt.

Chronic exposure to arsenic-contaminated drinking water is correlated with obstructive lung disease (i.e. chronic obstructive pulmonary disease (COPD), bronchiectasis), reduced lung function and other respiratory effects (e.g. chronic cough, chest sounds). Researchers have associated arsenic exposure with reduced airway immunity. The airway epithelial innate immune system protects underlying tissue from inhaled particulates and pathogens through a variety of mechanisms. Such defects in innate immunity are associated with chronic bacterial infections and development of obstructive airway diseases, including COPD and bronchiectasis. We hypothesize that arsenic exposure may lead to recurrent lung infection and eventual obstructive lung disease by compromising mechanisms essential in airway innate immunity. In the work presented herein we evaluated the effects of arsenic on airway epithelial barrier properties, wound repair capacity, and signaling pathways essential in innate immunity. We previously published that acute (24 hr) arsenic (0.4-3.9 μM as Naarsenite) slowed wound repair in a human bronchial epithelial cell line (16HBE14o-). In the first study we hypothesized arsenic may be affecting wound repair by altering Ca²⁺ signaling that is important in multiple aspects of wound repair, including cell migration. We found wound-induced Ca²⁺ signaling was largely mediated by paracrine ATP in 16HBE14o- cells, and acute (24 hr) arsenic (0.8, 3.9 μM) exposure reduced ATPmediated Ca²⁺ signaling. We identified functional reductions in the ATP receptors P2Y₂ and P2X₄ following arsenic exposure. Both of these receptors are essential in airway innate immunity (e.g. mucociliary clearance). In the second study we found similar reductions in wound repair capacity and ATP-mediated Ca²⁺ signaling in 16HBE14o cells using a chronic (4-5 week) low-dose (0.13, 0.33 μM) arsenic exposure representative of U.S. drinking water standards. Further, wound-induced Ca²⁺ signaling was reduced in primary cultured tracheal cells derived from mice fed arsenic-free or arsenic-supplemented (50 ppb; 1μM=75 ppb) water for four weeks prior to experimentation. In the last study we demonstrated that the structure and function of the airway epithelial barrier was altered by a five-day exposure of arsenic (0.8, 3.9 μM). We conclude that arsenic at environmentally relevant levels compromises key functions in airway epithelial innate immunity that may underlie development of lung disease.

Magistrantūros studijų baigiamasis darbas, 57 puslapiai, 5 paveikslai, 5 lentelės, 38 literatūros šaltiniai, 3 priedai, lietuvių kalba. RAKTINIAI ŽODŽIAI – dividendai, finansinis signalizavimas, signalinis efektas, akcijų rinka. Tyrimo objektas – dividendų politikos formavimas finansinio signalizavimo aspektu. Darbo tikslas – suformavus dividendų signaliniam efektui akcijų rinkoje nustatyti metodiką, įvertinti šio efekto stiprumą Lietuvos akcijų rinkoje. Uždaviniai: • Paaiškinti ir pagrįsti dividendų svarbą rinkos dalyviams. • Pateikti ir palyginti pagrindines dividendų teorijas finansinio signalizavimo aspektu. • Sukurti dividendų signalinio efekto akcijų rinkoje tyrimo metodiką. • Ištirti ryšį tarp dividendų išmokų ir Lietuvos akcinių bendrovių finansinės būklės bei nustatyti akcijų kainos ir dividendų išmokų priklausomybę. Tyrimo metodai – literatūros analizė ir sintezė bei palyginimo metodas, matematinės statistikos funkcijos, dispersinė, regresinė analizė, koreliacija ir grafinė analizė. Tyrimų laikotarpis – 2000-2008 m. Tyrimo rezultatai: • pirmoje darbo dalyje atlikta dividendų teorijų analizė finansinio signalizavimo aspektu; • antroje dalyje atlikus dividendų signalinio efekto empirinių tyrimų ir taikytų metodikų analizę sukurta metodika, pagal kurią tiriamas dividendų signalinis efektas Lietuvos akcijų rinkoje; • trečioje darbo dalyje ištirtas dividendų signalinis efektas Lietuvos akcijų rinkoje; • atliktas empirinis tyrimas parodė, jog kaikurios Lietuvos įmonės... [toliau žr. visą tekstą] / Master final work, consist of 57 pages, 5 figures, 5 tables, 38 references, 3 appendix, writen in Lithuanian language. KEY WORDS – dividend, financial signaling, signaling effect, stock market.. The object of research – formation of dividend poicy by the financial signaling aspect. The research aim – to develop the methodology for determination of signaling effect in stock market, estimate of this effect strengthness in the Lithuanian stock market. The objectives: • Explane and base the importance of dividends to market participants. • To represent and compare the main theorys by the dividends signaling aspect. • to create the methodology for determination of signaling effect in stock market. • To research the relation between dividend payments and financial situation of Lithuanian joint stock companies also dependence on stock price and dividend payments.. Research methods – literary analysis and synthesis and comparison method, mathematical statistics function of variance, regression analysis, correlation and graphical analysis. Research period – 2000-2008. Resaerch results: • in the first part of the research was done the dividend theory anglysis by the financial signaling aspect; • in the second part was developed the methodology based on which was researched the dividend signaling effect of Lithuanian stock market after the anglysis of empirical research and applied anglysis of methodologies; • in the third part of the research was investigated the signaling effect... [to full text]