Data-driven models of circadian output regulation in mammals

• Applicant: Dr. Bharath Ananthasubramaniam
• Subject Area: Bioinformatics and Theoretical Biology ; Cognitive, Systems and Behavioural Neurobiology
• Term: from 2020 to 2024
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 444137814

The circadian clock regulates most processes in mammalian physiology in a time of day-dependent manner. The clock system is a network with the master clock in the brain and peripheral clocks in other tissues, such as liver and skeletal muscles. A gene-regulatory core-clock network generates oscillations in single cells. Most of the research thus far has focused on understanding this core-clock mechanism (Nobel Prize 2017). The outputs of the clock received empirical and theoretical attention only recently. Interestingly, the molecular, hormonal and neuronal outputs of the clock also act as links within the clock network, but these links are poorly understood. I address this gap by identifying the regulatory links in the circadian clock network using a combination of data-analysis, modeling and theory.Glucocorticoid hormones (GCs) are a key link in the circadian network between the master SCN clock and the peripheral clocks. They also play an important role in metabolism and are a regularly used drug. My first objective is to quantify the effect of GCs on the peripheral core-clock and clock controlled genes in key metabolic tissues and thus to infer the mechanisms of co-regulation by the master and peripheral clocks. I will achieve this goal by (i) cataloging target gene expression patterns driven by ultradian and circadian GC rhythms using simple mathematical models, (ii) searching for such expression patterns using custom-build tools in transcriptomic datasets under different genotypes, (iii) inferring co-regulation of target gene expression by both GC action and the clock from genome-wide datasets using machine learning, and (iv) incorporating the effects of GC action into established core-clock models.The master clock not only synchronizes the circadian network, but controls circadian patterns of rest and activity of the organism via neuronal firing. However, organisms exhibit complex patterns of rest-activity including ultradian rhythms, such as sleep stages. My second objective is to quantify to what extent behavioral activity at different timescales is controlled by the master clock and whether there is feedback from behavior to the clock. This has implications for health as it concerns how exercise might interact with the clock. I will achieve this goal by constructing a novel predictive model relating neuronal firing and behavioral activity using in-vivo recordings. By means of the model, I want to (i) classify activity into behavioral states within a probabilistic framework, (ii) quantify how much of behavior is predicted by neuronal firing alone, (iii) measure the effect of behavior itself on neuronal firing, and finally (iv) test whether these insights change under different environmental light conditions. Thus, the study of hormonal regulation and neuronal output will help advance our understanding of how the clock integrates with other physiological processes.

• DFG Programme: Research Grants