This Faculty Early Career Development project will determine the underlying mechanisms that regulate the integration of environmental signals into the circadian clock. Organisms have widely-adapted a highly conserved process to anticipate our 24-hr planetary cycles, termed circadian rhythms, making them a fundamental “rule of life” on planet Earth. Circadian rhythms are controlled by a molecular “clock” that tunes organismal physiology to time a wide variety of cellular functions. Understanding how this clock times physiology is vital as the dysregulation of circadian rhythms can impact a wide array of critical biological functions in most organisms. Though the clock mechanism was presumed to be buffered against changes in an organism’s environment, contemporary research shows that environmental fluctuations can alter circadian regulation at the cellular level through as yet unknown mechanisms and the goals of this research are to identify how environmental signals are incorporated into the circadian timing of a cell. This project will also use the circadian clock to educate future scientists at the college and pre-school levels in the scientific method. As the creation of experimental and computational biological data has surpassed the education of biological researchers in data analytics, the principal investigator will implement a biological data analytics program at the undergraduate level to develop an understanding of how data analytics can solve biological problems. These undergraduate researchers will then work with the Rensselaer Science Ambassadors to reach out to local preschools to teach young children about the scientific method using the growth and tracking of sunflower movements as a model of the circadian clock in an effort to increase STEM interest in underserved communities.

The specific objectives of this project are to use computational and molecular approaches to identify and validate the mechanisms by which environmental signals are integrated into the circadian programing of cellular physiology. The molecular clock that drives circadian rhythms has been long believed to be buffered from environmental insult, theoretically acting as a fixed switch that turns a specific set of genes on during the day and off again at night. Contrary to this theory, recent data has shown there is flexibility in circadian regulation, demonstrating that environmental signals can be transduced into the clock’s control of transcript and protein levels. However, there is no mechanistic comprehension of how systemic integration of environmental signals into circadian molecular programing occurs. The data that the investigators have gathered on transcripts and proteins over circadian time from the model organism Neurospora crassa, along with the computational algorithms that they have built to analyze this data, suggest potential mechanisms for the integration of environmental signals into the circadian clock. Therefore, the scientific goals of this proposal are to utilize novel computational approaches to predict specific points at which environmental signals are integrated into circadian transcriptional and translational programming. The investigators will then use this exquisitely tractable circadian model organism to biochemically validate these predictions. This research will contribute to the understanding of how environmental signals are integrated into circadian regulation, which will serve as a model for signal integration in other cellular regulatory systems. This project will also develop novel computational tools with which to study many types of oscillations across research systems. This award was co-funded by the Cellular Dynamics and Function and Systems and Synthetic Biology clusters of the Division of Molecular and Cellular Biosciences.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

National Science Foundation (NSF)
Division of Molecular and Cellular Biosciences (MCB)
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Steve Clouse
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Rensselaer Polytechnic Institute
United States
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