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COMPUTATIONAL MODELING OF THE MAMMALIAN CENTRAL CIRCADIAN CLOCK: THE INTERCELLULAR SIGNALING ROLE OF GABA NEUROTRANSMITTER

Abstract
The mammalian central circadian clock in the brain's suprachiasmatic nucleus (SCN) contains ~20,000 networked pacemaker neurons and astrocytes. They synchronize their actions to generate coherent 24-h rhythms and can be entrained by external cues to regulate physiological and behavioral activities (e.g., sleep-wake cycles and metabolic processes). While the gamma-aminobutyric acid (GABA) neurotransmitter is the most abundant signaling agent for the SCN oscillators' intercellular communication, its properties involving with chloride dynamics and roles in cell-to-cell synchronization or light-induced entrainment remain unclear. The primary purpose of this dissertation was to investigate SCN GABA's roles via computational modeling to establish a multiscale connection between cellular heterogeneities (clock-gene/electrical/intracellular activities) at the single-cell level and complex GABAergic and other peptidergic network heterogeneities at the SCN population level. The GABAergic system's influence on the behavior of the SCN system was investigated by developing various multicellular models that replicate (1) the circadian network activity of the SCN's neuronal-astrocytic oscillators, (2) the dynamics of synaptic and extra-synaptic GABA receptors, and (3) pharmacological modulation targeting GABAergic pathways for enhanced re-entrainment. The model predictions revealed (1) the impact of astrocytes on modulating neuronal activity for the circadian timekeeping system depending upon their inherent period distinction, complex cell-to-cell signaling interactions, and degree of astrocytic connections, (2) the distinct effects of GABA signaling and GABAA receptor expression, as well as the critical interplay between synaptic and extra-synaptic GABAA on cell-to-cell coordination and circadian outputs, (3) Optimal dosing strategies for drugs affecting the GABAergic system that could be appropriately designed to promote re-entrainment and reduce circadian phase misalignment caused by long-distance travel or irregular shift-work schedules. Taken together, the dissertation has advanced mathematical modeling of coupled biological oscillators in complex networks and significantly expanded an understanding of GABA neurotransmitter and its associated roles in the SCN circadian timekeeping system. Remarkably, the in silico SCN model has provided novel insights into the potential chronotherapeutic optimization via GABAergic system manipulation. The computational suggestions could serve as a guideline for the targeted prevention and strategic treatment of circadian rhythm disruptions, which cause health problems such as jet lag, sleep-wake disorders, mental illness, and metabolic syndrome.
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campusfive
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dissertation
Date
2022-05-13
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