Circadian Clock Study Through Frequency-Encoded Entrainment Stimulations

Circadian clocks are intrinsic, time-tracking systems that enable organisms to maintain their physiological state and their synchrony with the 24-hour rotation of the Earth, by partitioning behavioural and metabolic processes according to time of day within each tissue. They are entrained to the external environment by light/dark cycles and by food timing, which act as clock synchronizers. Emerging evidence suggests that circadian regulation is intimately linked to metabolic homeostasis and that dysregulation of circadian rhythms can contribute to disease. Conversely, metabolic signals also feed back into the circadian system, modulating circadian gene expression and behaviour. Conventional experimental approach of circadian clock in vitro studies is based on single-pulse stimulation of only one metabolite or hormone, while in vivo peripheral tissues are exposed to periodic oscillating stimuli of a large number of metabolites and hormones, whose variations are in most cases interconnected, as for example glucose and insulin. Moreover, only one or few clock genes are generally considered, while it is known that a large number of genes, thus biological processes, are under circadian regulation. Therefore, this Ph.D. research work is aimed at the development of technologies and data analysis tools to investigate the entrainment of peripheral mammalian circadian clock to frequency-encoded metabolic stimuli, which well mimic physiological oscillations at which peripheral tissues are exposed in vivo. Technologies, and, more specifically, microtechnologies have been developed to investigate the effects of periodic metabolic entrainment, showing that in murine fibroblasts oscillatory periodic metabolic stimulations entrain the expression of Per2, one of the core genes of the circadian molecular mechanism. Moreover, it has been proven that only by metabolic oscillations it is possible to completely reset the phase of cell-autonomous clocks. In order to develop a physiological and pathological in vitro model, achieving a high spatio-temporal control of cell culture microenvironment, frequency-encoded perturbations have been automated in a newly designed microfluidic platform for circadian applications. Finally, to broaden the description of genes expressed with a circadian temporal pattern, a new data analysis method has been proposed and characterized, that allows to identify circadian genes in whole transcriptome data, to group genes based on the phase of their expression, to visualize transcriptome data at a glance and clearly identifying modifications at the transcriptome level from one biological condition to another one