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Thesis (Ph. D.)--University of Rhode Island, 2006. / Typescript. Includes bibliographical references (leaves 136-153).

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To date, most genome-scale approaches designed to explore kinase pathways have been targeted towards substrate identification for individual kinases but provide little functional information and only a limited view of the interplay of kinases and their targets in key biological processes. I attempted to tackle the complexity of kinase networks using an unbiased integrated global analysis in budding yeast. I used functional genomics screens to study the yeast kinome using combinatorial genetic perturbations. I first assessed the effects of gene overexpression on the fitness of non-essential kinase deletion mutants to generate a comprehensive view of Synthetic Dosage Lethal (SDL) interactions involving yeast kinases. These data were complemented by assessing genome-wide Synthetic Lethal (SL) interactions for kinases that gave SDL interactions. By measuring >600,000 potential interactions between kinase-gene pairs, I produced a meta-network of ~1300 dosage lethal interactions and 7500 negative and positive genetic interactions. I reasoned that by combining two complementary genetic datasets for kinases, I could: 1) characterize the unexpected phenotypic outcomes that result from the interplay of gain-of-function and loss-of-function phenotypes; 2) better comprehend the complexity of kinase signaling networks and; 3) predict the function of novel genes that arise from the combined genetic network and a gold standard list of known kinase-substrate pairs in the literature. The SDL network alone was enriched for pathways known to be regulated by cognate kinases including phosphoproteins, and kinase targets and kinases that yielded informative SDL interactions were largely those with cell polarity roles. Condition-specific screens and analysis of kinase double mutants suggested that the apparent resistance of many kinases to genetic perturbation cannot be solely attributed to kinase redundancy but most likely reflects the requirement for many kinases in certain activating conditions. Next, I created the first systematic gold standard for kinase-substrate pairs and generated the first kinase interaction database, specifically curated for experiments pertaining to kinase-substrate relationships, in order to analyze the SDL network for identification of kinase targets. Also, using a novel approach that combines the gold standard and the integrated SDL-genetic interaction meta-network, I found that the integrated network is more functionally informative than either SGA or SDL networks alone. Additional integration of known kinase-substrate relationships extracted from the biochemical literature into this network was key to the identification of recurring motifs that enable accurate prediction of single mutant phenotypes. I have also identified ~2000 triplet regulatory network motifs, unraveling novel pathways regulated by kinases. I have tested several motifs using phenotypic and biochemical assays and have identified a novel gene involved in the regulation of cell wall integrity pathway, and found a new regulatory mechanism involving the mitotic exit network machinery. My study provides a general framework for predicting phenotypic outcomes from different combinations of genetic mutations, but also delineates the complexity of signaling pathways involving phosphorylation. The identified network motifs belie the simplistic notion of linear kinase cascades, and support a complex network model where multi-dimensional signaling waves dictate a phenotypic outcome. My data suggest that unraveling the complexity of network biology demands an unbiased global analysis using an integrated set of functional genomics approaches with a high quality gold standard.

To date, most genome-scale approaches designed to explore kinase pathways have been targeted towards substrate identification for individual kinases but provide little functional information and only a limited view of the interplay of kinases and their targets in key biological processes. I attempted to tackle the complexity of kinase networks using an unbiased integrated global analysis in budding yeast. I used functional genomics screens to study the yeast kinome using combinatorial genetic perturbations. I first assessed the effects of gene overexpression on the fitness of non-essential kinase deletion mutants to generate a comprehensive view of Synthetic Dosage Lethal (SDL) interactions involving yeast kinases. These data were complemented by assessing genome-wide Synthetic Lethal (SL) interactions for kinases that gave SDL interactions. By measuring >600,000 potential interactions between kinase-gene pairs, I produced a meta-network of ~1300 dosage lethal interactions and 7500 negative and positive genetic interactions. I reasoned that by combining two complementary genetic datasets for kinases, I could: 1) characterize the unexpected phenotypic outcomes that result from the interplay of gain-of-function and loss-of-function phenotypes; 2) better comprehend the complexity of kinase signaling networks and; 3) predict the function of novel genes that arise from the combined genetic network and a gold standard list of known kinase-substrate pairs in the literature. The SDL network alone was enriched for pathways known to be regulated by cognate kinases including phosphoproteins, and kinase targets and kinases that yielded informative SDL interactions were largely those with cell polarity roles. Condition-specific screens and analysis of kinase double mutants suggested that the apparent resistance of many kinases to genetic perturbation cannot be solely attributed to kinase redundancy but most likely reflects the requirement for many kinases in certain activating conditions. Next, I created the first systematic gold standard for kinase-substrate pairs and generated the first kinase interaction database, specifically curated for experiments pertaining to kinase-substrate relationships, in order to analyze the SDL network for identification of kinase targets. Also, using a novel approach that combines the gold standard and the integrated SDL-genetic interaction meta-network, I found that the integrated network is more functionally informative than either SGA or SDL networks alone. Additional integration of known kinase-substrate relationships extracted from the biochemical literature into this network was key to the identification of recurring motifs that enable accurate prediction of single mutant phenotypes. I have also identified ~2000 triplet regulatory network motifs, unraveling novel pathways regulated by kinases. I have tested several motifs using phenotypic and biochemical assays and have identified a novel gene involved in the regulation of cell wall integrity pathway, and found a new regulatory mechanism involving the mitotic exit network machinery. My study provides a general framework for predicting phenotypic outcomes from different combinations of genetic mutations, but also delineates the complexity of signaling pathways involving phosphorylation. The identified network motifs belie the simplistic notion of linear kinase cascades, and support a complex network model where multi-dimensional signaling waves dictate a phenotypic outcome. My data suggest that unraveling the complexity of network biology demands an unbiased global analysis using an integrated set of functional genomics approaches with a high quality gold standard.

<p>Diseases caused by smooth muscle dysfunction such as hypertension and asthma are major public health concerns, a better understanding of the signaling pathways that regulate smooth muscle contraction could identify new drug targets. The opposing effects of two enzymes; calcium/calmodulin regulated myosin light chain kinase (MLCK) and smooth muscle myosin phosphatase (SMPP-1M) determine the amount of force generated by smooth muscle. The calcium-independent signaling mediated by myosin phosphatase is regulated by several kinases which include zipper interacting protein kinase (ZIPK). Our laboratory has shown that ZIPK is able to phosphorylate and inhibit SMPP-1M which results in increased smooth muscle contraction. Additional studies demonstrated that ZIPK is also regulated by phosphorylation. The goal of this study is to identify kinases in the context of smooth muscle that regulate ZIPK and to define the events required for ZIPK activation. </p><p>A proteomic approach which employed ATP-affinity chromatography coupled with mass spectrometry isolated discreet kinase activities towards ZIPK, these activities were attributed to integrin-linked kinase (ILK) and Rho kinase 1 (ROCK1). ILK phosphorylates ZIPK at Thr180 while ROCK1 phosphorylates ZIPK at Thr265 and Thr299. </p><p>Additionally the ATP-affinity media used for kinase enrichment in the proteomic screen was used as a tool to measure ZIPK activation. Pre-incubating ZIPK with ROCK before the assay resulted in increased binding which suggests phosphorylation of ZIPK by ROCK is activating. Increasing the substrate concentration in the assay resulted in increased ZIPK binding, this result was only observed when the assay was performed with the full-length protein. Phosphorylation of residues in the kinase domain along with substrate binding relieves inhibition and results in kinase activation. </p><p>Finally fluorescence microscopy along with targeted mutations of ZIPK was used to determine the mechanism of cellular transport. This was done to address the difference in cellular localization between human and murine cells. The localization of human ZIPK is dictated by nuclear localization sequence 2 (NLS2) and the phosphorylation state of Thr299; the mechanism is not shared by the murine form of ZIPK. </p><p>Completion of this work has provided additional information about the signaling interactions that take place in smooth muscle; the results suggest that ZIPK is a convergence point for multiple signaling pathways that lead to SMPP-1 inhibition and subsequently smooth muscle contraction. This study also contributes significantly to our knowledge of the molecular dynamics that lead to active full length ZIPK. Future research that employs animal modeling as a tool to investigate ZIPK will be informed by the experiments that address the cellular localization of ZIPK.</p> / Dissertation

Circadian rhythms of behavior have been well characterized in organisms including mammals, plants, insects, fungi, and photosynthetic bacteria. Cyanobacteria, such as the unicellular Synechococcus elongatus PCC 7942, display near 24-h circadian rhythms of gene expression. These rhythms persist in the absence of external cues, can be reset by the same stimuli to which they entrain, and are relatively insensitive to changes in ambient temperature within their physiological range. Key components have been identified as belonging to the central oscillator that comprises the timekeeping units, output pathways that relay temporal information to clock-controlled processes, and input pathways that synchronize the oscillator with local time. The emerging model of the cyanobacterial clock depicts the internal timekeeping elements KaiA, KaiB, and KaiC interacting with one another to form a large, multimeric complex that assembles and disassembles over the course of a day. Information is sent into and out of the oscillator via signal transduction pathways that include proteins involved in bacterial twocomponent systems. The research presented in this dissertation explores the regulatory mechanisms that exist at each level of the clock system. New components were identified that interact with an important protein in the input pathway; these new players are involved in clock-associated phenomena, such as resetting the internal oscillation to external stimuli and maintaining proper circadian periodicity, as well as the process of cell division. The model formerly associated with the temporal, transcriptional regulation of the kai genes was redefined to reflect the unique properties of the prokaryotic oscillator. The differential output of the clock was examined by studying the circadian regulation of the psbA gene family. Overall, these data provide insight into the complex molecular events that occur to create a circadian timing circuit in S. elongatus.

Thesis (Ph. D.)--University of Hong Kong, 2001. / Includes bibliographical references (leaves 148-170).

Thesis (M.S.)--Central Connecticut State University, 2004. / Thesis advisor: Cheryl Watson. " ... in partial fulfillment of the requirements for the degree of Master of Science in Biology." Includes bibliographical references (leaves 43-47). Also available via the World Wide Web.

Thesis (Ph. D.) in Biochemistry and Molecular Biology--University of Maine, 2001. / Includes vita. Includes bibliographical references (leaves 91-103).