The role of spatiotemporal organization and dynamics of clock complexes in circadian regulation

Epigenetic control of circadian clocks by environmental signals

Circadian clocks have evolved to enable organisms to respond to daily environmental changes. Maintaining a robust circadian rhythm under various perturbations and stresses is essential for the fitness of an organism. In the core circadian oscillator conserved in eukaryotes (from fungi to mammals), a negative feedback loop based on both transcription and translation drives circadian rhythms. The expression of circadian clock genes depends both on the binding of transcription activators at the promoter and on the chromatin state of the clock genes, and epigenetic modifications of chromatin are crucial for transcriptional regulation of circadian clock genes. Herein we review current knowledge of epigenetic regulation of circadian clock mechanisms and discuss how environmental cues can control clock gene expression by affecting chromatin states.

Streamlined single-molecule RNA-FISH of core clock mRNAs in clock neurons in whole mount Drosophila brains

Circadian clocks are ∼24-h timekeepers that control rhythms in almost all aspects of our behavior and physiology. While it is well known that subcellular localization of core clock proteins plays a critical role in circadian regulation, very little is known about the spatiotemporal organization of core clock mRNAs and its role in generating ∼24-h circadian rhythms. Here we describe a streamlined single molecule Fluorescence In Situ Hybridization (smFISH) protocol and a fully automated analysis pipeline to precisely quantify the number and subcellular location of mRNAs of Clock, a core circadian transcription factor, in individual clock neurons in whole mount Drosophila adult brains. Specifically, we used ∼48 fluorescent oligonucleotide probes that can bind to an individual Clock mRNA molecule, which can then be detected as a diffraction-limited spot. Further, we developed a machine learning-based approach for 3-D cell segmentation, based on a pretrained encoder-decoder convolutional neural network, to automatically identify the cytoplasm and nuclei of clock neurons. We combined our segmentation model with a spot counting algorithm to detect Clock mRNA spots in individual clock neurons. Our results demonstrate that the number of Clock mRNA molecules cycle in large ventral lateral clock neurons (lLNvs) with peak levels at ZT4 (4 h after lights are turned on) with ∼80 molecules/neuron and trough levels at ZT16 with ∼30 molecules/neuron. Our streamlined smFISH protocol and deep learning-based analysis pipeline can be employed to quantify the number and subcellular location of any mRNA in individual clock neurons in Drosophila brains. Further, this method can open mechanistic and functional studies into how spatiotemporal localization of clock mRNAs affect circadian rhythms.