A Neural Network Underlying Circadian Entrainment and Photoperiodic Adjustment of Sleep and Activity in Drosophila.

Abstract

A sensitivity of the circadian clock to light/dark cycles ensures that biological rhythms maintain optimal phase relationships with the external day. In animals, the circadian clock neuron network (CCNN) driving sleep/activity rhythms receives light input from multiple photoreceptors, but how these photoreceptors modulate CCNN components is not well understood. Here we show that the Hofbauer-Buchner eyelets differentially modulate two classes of ventral lateral neurons (LNvs) within the Drosophila CCNN. The eyelets antagonize Cryptochrome (CRY)- and compound-eye-based photoreception in the large LNvs while synergizing CRY-mediated photoreception in the small LNvs. Furthermore, we show that the large LNvs interact with subsets of "evening cells" to adjust the timing of the evening peak of activity in a day length-dependent manner. Our work identifies a peptidergic connection between the large LNvs and a group of evening cells that is critical for the seasonal adjustment of circadian rhythms. In animals, circadian clocks have evolved to orchestrate the timing of behavior and metabolism. Consistent timing requires the entrainment these clocks to the solar day, a process that is critical for an organism's health. Light cycles are the most important external cue for the entrainment of circadian clocks, and the circadian system uses multiple photoreceptors to link timekeeping to the light/dark cycle. How light information from these photorecptors is integrated into the circadian clock neuron network to support entrainment is not understood. Our results establish that input from the HB eyelets differentially impacts the physiology of neuronal subgroups. This input pathway, together with input from the compound eyes, precisely times the activity of flies under long summer days. Our results provide a mechanistic model of light transduction and integration into the circadian system, identifying new and unexpected network motifs within the circadian clock neuron network.