Developing and characterizing sleep-based network homeostasis in a diurnal rodent model for Familial Natural Short Sleep - Abstract: Despite the importance of sleep for brain health, some people have a recently recognized condition called Familial Natural Short Sleep (FNSS) where individuals sleep 4-5 hours per night but without health deficit. Several human mutations causing FNSS have been identified and introduced in mouse genomes, but we do not understand how this mutation enables less sleep need. However, while in humans the mutations result in 20-30% reduction of sleep at night, the same mutations in nocturnal mice had subtle (~6%) or no effects in the amount of sleep, especially in the light phase when mice are predominantly sleeping. Given that FNSS genes such as Dec2 are circadian clock modulators, an FNSS mutation in a diurnal model may better recapitulate the human FNSS phenotype and can better model human sleep and circadian interactions. Here we propose to develop a diurnal FNSS model to study the impact of sleep on homeostasis of neural network function, using state-of-the-art behavioral and electrophysiologic methods. The fact that the grass rats share diurnality with humans can render them a particularly powerful system for the study of sleep and circadian health. We expect that since our grass rat model shares diurnal circadian drives with humans, our findings will offer substantial new strengths in modeling human FNSS. Leveraging the recently available grass rat genome and CRISPR, we have generated multiple genome-edited lines of grass rats and are in the process of developing a line carrying the Dec2-P384R mutation. To measure sleep action on neural networks, the Watson lab has developed multiple metrics based on multiple, single-unit electrophysiologic recordings. First, we published that spike rates and spike rate variance drop over sleep, and preliminary data suggest that excitatory-inhibitory balance, burst firing, and synchrony are also modulated by sleep/wake and circadian rhythms. These measures are defined as “electrophysiologic background state” (EBS) and can be represent a novel but research-informed approach to quantifying overall network status. To understand FNSS and normal sleep effects on the brain, it will be key to establish how sleep in the Dec2-P384R mutation modulates these EBS metrics. Our central hypothesis is that faster homeostatic attenuation of EBS measures per unit time in sleep enables/underlies healthy brain function despite the shorter sleep duration in FNSS. Aim 1 of this study: Determine the impact of FNSS Dec2-P384R mutation in circadian behavior and sleep state occupancy in this new mutation in diurnal grass rats. Aim 2: Measure differential effects of sleep and wake on mutant versus FNSS using neural network functional recordings. This will create a new research model encapsulating more human-like relationships between sleep and circadian rhythms. Aim 2 will already establish novel understanding of sleep action on neural networks. In the future, these animals can enable study many aspects of modern life including but not limited to 1) chronic sleep deprivation, 2) irregular light schedule for shiftwork-like models, 3) chronic stress and other mood disorders.
