Single-cell transcriptomics and analysis for new molecular regulators of sleep
Ontology highlight
ABSTRACT:
ORGANISM(S): Mus musculus
PROVIDER: GSE137665 | GEO | 2022/08/24
REPOSITORIES: GEO
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Project description:Every day, we sleep for a third of the day. Sleep is important for cognition, brain waste clearance, metabolism, and immune responses. Homeostatic regulation of sleep is maintained by progressively rising sleep need during wakefulness, which then dissipates during sleep. The molecular mechanisms governing sleep are largely unknown. Here, we used a combination of single-cell RNA sequencing and cell-type specific proteomics to interrogate the molecular and functional underpinnings of sleep. Different cell-types in the brain regions show similar transcriptional response to sleep need whereas sleep deprivation changes overall expression indicative of altered antigen processing, synaptic transmission and cellular metabolism in brainstem, cortex and hypothalamus, respectively. Increased sleep need enhances expression of transcription factor Sox2, Mafb, and Zic1 in brainstem; Hlf, Cebpb and Sox9 in cortex, and Atf3, Fosb and Mef2c in hypothalamus. Results from cell-type proteome analysis suggest that sleep deprivation changes abundance of proteins in cortical neurons indicative of altered synaptic vesicle cycles and glucose metabolism whereas in astrocytes it alters the abundance of proteins associated with fatty acid degradation. Similarly, phosphoproteomics of each cell type demonstrates large shifts in site-specific protein phosphorylation in neurons and astrocytes of sleep deprived mice. Our results indicate that sleep deprivation regulates transcriptional, translational and post-translational responses in a cell-specific manner and advances our understanding of the cellular and molecular mechanisms that govern sleep-wake homeostasis in mammals.
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Project description:Why we sleep is still one of the most perplexing mysteries in biology. Strong evidence, however, indicates that sleep is necessary for normal brain function and that the need to sleep is a tightly regulated process. Surprisingly molecular mechanisms that determine the need to sleep are incompletely described. Moreover, very little is known about transcriptional changes that specifically accompany the accumulation and discharge of sleep need. In this study we present an integrated 2 cross-laboratory analysis of the effects of sleep deprivation (SD) in gene expression in the mouse cortex. We also evaluate changes in gene expression genome-wide following various lengths of subsequent recovery sleep. (RS). We demonstrate that changes in gene expression specifically linked to SD or RS, and not to technical factors (e.g. the assay used), requires a novel analysis methodology not previously utilized in the field of sleep research. Cortical samples from mice were analyzed, from groups that were sleep deprived, sleep deprived and allowed to recover for 1, 2, 3, or 6 hours, and circadian control animals that were not sleep deprived. The experimental protocol began at lights on (ZT0) with 13 mice: 1 sacrificed, 4 control mice left undisturbed, and 8 mice kept awake with gentle brushing when attempting to sleep. After 5 hours of sleep deprivation the mice were randomly assigned to recovery sleep or continued sleep deprivation, and at fixed intervals the mice were sacrificed, dissected and the left cortex retained. The experimental protocol was repeated 7 times, one animal per timepoint per experimental day, so that 7 independent experiments are represented for each timepoint. All animals were acclimated to the brushing and tapping on cages used during sleep deprivationfor 6 days, and dissections and tissue collection were performed by a single experimenter.
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Project description:Why we sleep is still one of the most perplexing mysteries in biology. Strong evidence, however, indicates that sleep is necessary for normal brain function and that the need to sleep is a tightly regulated process. Surprisingly molecular mechanisms that determine the need to sleep are incompletely described. Moreover, very little is known about transcriptional changes that specifically accompany the accumulation and discharge of sleep need. In this study we present an integrated 2 cross-laboratory analysis of the effects of sleep deprivation (SD) in gene expression in the mouse cortex. We also evaluate changes in gene expression genome-wide following various lengths of subsequent recovery sleep. (RS). We demonstrate that changes in gene expression specifically linked to SD or RS, and not to technical factors (e.g. the assay used), requires a novel analysis methodology not previously utilized in the field of sleep research.
2016-09-07 | GSE78215 | GEO
Project description:To gain insight into the molecular changes of sleep need, this study addresses gene expression changes in a subpopulation of neurons selectively activated by sleep deprivation. Whole brain expression analyses after 6h sleep deprivation clearly indicate that Homer1a is the best index of sleep need, consistently in all mouse strains analyzed. Transgenic mice expressing a FLAG-tagged poly(A)-binding protein (PABP) under the control of Homer1a promoter were generated. Because PABP binds the poly(A) tails of mRNA, affinity purification of FLAG-tagged PABP proteins from whole brain lysates, is expected to co-precipitate all mRNAs from neurons expressing Homer1a. Three other activity-induced genes (Ptgs2, Jph3, and Nptx2) were identified by this technique to be over-expressed after sleep loss. All four genes play a role in recovery from glutamate-induced neuronal hyperactivity. The consistent activation of Homer1a suggests a role for sleep in intracellular calcium homeostasis for protecting and recovering from the neuronal activation imposed by wakefulness. Keywords: sleep deprivation, neuronal subpopulation transcriptome
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Project description:These studies address temporal changes in gene expression during spontaneous sleep and extended wakefulness in the mouse cerebral cortex, a neuronal target for processes that control sleep; and the hypothalamus, an important site of sleep regulatory processes. We determined these changes by comparing expression in sleeping animals sacrificed at different times during the lights on period, to that in animals sleep deprived and sacrificed at the same diurnal time. Experiment Overall Design: Experiments were performed on male mice (C57/BL6), 10 weeks of age ±1 week. Animals were housed in a light/dark cycle of 12 hrs, in a pathogen free, temperature- and humidity-controlled room (22°C and 45-55%, respectively) with water available ad libitum. Food was accessible for 12 hrs only during the active period. Animals were subjected to 14 days of acclimatization during which a nighttime feeding pattern was established. This was done to avoid differential food intake between mice that were subsequently sleep deprived during the lights on period and those allowed to sleep. Mice were sacrificed following 3, 6, 9 and 12 hrs of total sleep deprivation (n=5 at each time point). Deprivation was initiated at lights-on, and performed through gentle handling. Sleeping animals, which were left undisturbed, were sacrificed at the same diurnal time points as sleep deprived mice (n=5 at each time point). An additional control group of mice were sacrificed at time zero, i.e., at the time of lights-on (n=5). All mice were behaviorally monitored using the AccuScan infrared monitoring system that detects movement when the mouse crosses electronic beams (Columbus Instruments). Mice were sacrificed by cervical dislocation. Brain sectioning was performed according to the mouse brain atlas of Franklin and Paxinos . The primary and secondary motor areas (M1 and M2) of the cerebral cortex and broadly defined regions and zones of the hypothalamus were sampled. RNA was isolated with Trizol (Invitrogen) and further purified using RNeasy columns (Qiagen) as per the manufacturer's instructions.
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Project description:This dataset constitutes the first snRNA-Seq study of gene expression following sleep deprivation in wildtype mice with paralell bulk-RNA-seq data. In addition it contains RNA-seq analysis of the effect of recovery sleep following sleep deprivation
2023-04-17 | GSE211088 | GEO
Project description:This a model from the article:
Sleep deprivation in a quantitative physiologically based model of the ascending
arousal system.
Phillips AJ, Robinson PA. J Theor Biol
2008 Dec 21;255(4):413-23 18805427
,
Abstract:
A physiologically based quantitative model of the human ascending arousal system
is used to study sleep deprivation after being calibrated on a small set of
experimentally based criteria. The model includes the sleep-wake switch of
mutual inhibition between nuclei which use monoaminergic neuromodulators, and
the ventrolateral preoptic area. The system is driven by the circadian rhythm
and sleep homeostasis. We use a small number of experimentally derived criteria
to calibrate the model for sleep deprivation, then investigate model predictions
for other experiments, demonstrating the scope of application. Calibration gives
an improved parameter set, in which the form of the homeostatic drive is better
constrained, and its weighting relative to the circadian drive is increased.
Within the newly constrained parameter ranges, the model predicts repayment of
sleep debt consistent with experiment in both quantity and distribution,
asymptoting to a maximum repayment for very long deprivations. Recovery is found
to depend on circadian phase, and the model predicts that it is most efficient
to recover during normal sleeping phases of the circadian cycle, in terms of the
amount of recovery sleep required. The form of the homeostatic drive suggests
that periods of wake during recovery from sleep deprivation are phases of
relative recovery, in the sense that the homeostatic drive continues to converge
toward baseline levels. This undermines the concept of sleep debt, and is in
agreement with experimentally restricted recovery protocols. Finally, we compare
our model to the two-process model, and demonstrate the power of physiologically
based modeling by correctly predicting sleep latency times following deprivation
from experimental data.
This model was taken from the CellML repository
and automatically converted to SBML.
The original model was:
Phillips AJ, Robinson PA. (2008) - version=1.0
The original CellML model was created by:
Catherine Lloyd
c.lloyd@auckland.ac.nz
The University of Auckland
This model originates from BioModels Database: A Database of Annotated Published Models (http://www.ebi.ac.uk/biomodels/). It is copyright (c) 2005-2011 The BioModels.net Team.
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To cite BioModels Database, please use: Li C, Donizelli M, Rodriguez N, Dharuri H, Endler L, Chelliah V, Li L, He E, Henry A, Stefan MI, Snoep JL, Hucka M, Le Novère N, Laibe C (2010) BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. BMC Syst Biol., 4:92.
2005-01-01 | MODEL1006230115 | BioModels