This is a systems biology approach involving modeling to approach the significant biomedical question of the mechanisms by light inputs adjust the phase of the mammalian circadian clock. The circadian clock is a critical component of all living organisms and is critical for the maintenance of temporal synchrony of the organism with the environment and rhythmic orchestration of processes within the organism. Disruption of circadian clock function results in disrupted sleep/wake cycles and has been associated with cardiorespiratory dysfunction and cancer, gastrointestinal disorders, depression and altered. The molecular mechanism by which mammalian circadian clocks are entrained to light-dark cycles is a highly significant problem. A full understanding of this function is significant. The approaches to be developed address a fundamental unmet need in understanding the mechanisms by which light activates intracellular signaling that leads to transcriptional consequences which modulate cellular function in mammalian cells. Our objective is to link light-initiated signaling to gene expression in the response of retino-hypothalamic (RHT) light stimulation in auto-synchronized suprachiasmatic nucleus (SCN) circadian cells. The SCN is the master clock, coordinating numerous biological rhythms throughout the body. Inputs reflecting environmental and internal status are transmitted to SCN cell receptors that interact with the clock through complex signaling pathways, ultimately allowing it to control rhythmic physiological functions. Light signaling through RHT activation is the best characterized of all inputs into the circadian clock function. The circadian response to light signaling has been found to be circadian phase-related. The robustness of these effects in the context of synchronous SCN cellular behavior, in conjunction with the wealth of relevant information on RHT signaling from the literature, provides an advantageous environment for our objective. Our experimental strategy uses a factorial design approach to genome-wide expression profiling combined with pharmacological signaling inhibition. We will employ transcriptional regulatory network analysis by integrating gene expression data with promoter informatics. These results will be integrated with existing literature and used to derive signaling pathways. We will then experimentally validate the model structure at the various levels of interaction. The result will be an experimentally verified network of the gene expression effects of light signaling in SCN mediated by interactions between signaling proteins and ultimately transcription factors - making novel and directly validated links between the extensively studied fields of signaling and gene expression, and doing so in a physiologically relevant model system.
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