bioRxiv ScienceSearch

bioRxiv · 10.1101/2021.02.04.429717

The molecular clockwork of the suprachiasmatic nucleus is sufficient to co-ordinate phasing and stabilisation of sleep-wake cycles and enhance memory deficits in a clockless mouse

Abstract

The timing and quality of sleep-wake cycles are regulated by interacting circadian and homeostatic mechanisms. Although the suprachiasmatic nucleus (SCN) is the principal circadian clock, local clocks are active across the brain and the respective sleep-regulatory roles of SCN and extra-SCN clocks are unclear. To determine the specific contribution(s) of the SCN, we used virally mediated genetic complementation, expressing Cryptochrome1 (Cry1) to restore circadian molecular competence to the SCN of globally clockless Cry1/Cry2-null mice. Under free-running conditions, the rest/activity behaviour of Cry1/Cry2-null controls which received EGFP (SCNCon) was arrhythmic, whereas Cry1-complemented mice (SCNCry1) had circadian behaviour comparable to that of Cry1,2-competent wild-types (WT). In SCNCon mice, sleep-wakefulness, assessed by electroencephalography/electromyography, also lacked circadian organisation. In SCNCry1 mice, however, it was comparable to WT, with consolidated vigilance states (wake, REM and NREM sleep) and rhythms in NREMS delta power and expression of REMS within total sleep. Wakefulness in SCNCon mice was more fragmented than in WT, with more wake-NREMS-wake transitions. This disruption was corrected in SCNCry1 mice. Following sleep deprivation, all mice showed an initial homeostatic increase in NREMS delta power. The SCNCon mice, however, had reduced, non-consolidated NREMS during the inactive phase of the recovery period. In contrast, the dynamics of homeostatic responses in the SCNCry1 mice were equivalent to WT. Finally, SCNCon mice exhibited poor sleep-dependent memory but this was corrected in SCNCry1mice. Therefore, the SCN clock is sufficient for circadian control of sleep-wake, facilitating initiation and maintenance of wake, promoting sleep consolidation, homeostatic dynamics, and sleep-dependent memory. Significance statementThe circadian timing system regulates sleep-wake cycles. The hypothalamic suprachiasmatic nucleus (SCN) is the principal circadian clock, but local clocks are also active across the brain and the respective roles of SCN and local clocks in regulating sleep are unclear. To determine, explicitly, the contribution of the SCN, we used virally mediated genetic complementation to restore SCN molecular circadian functions in otherwise genetically clockless mice. This initiated circadian activity-rest cycles, accompanied by circadian sleep-wake cycles, circadian patterning to the intensity of NREM sleep and circadian control of REM sleep as a proportion of total sleep. Consolidation of sleep-wake established normal dynamics of sleep homeostasis and enhanced sleep-dependent memory. Thus, the SCN is the principal and sufficient circadian regulator of sleep-wake.

Source connections

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Maywood, E. S., Chesham, J. E., Winsky-Sommerer, R., Hastings, M. H.. 2021-02-05. The molecular clockwork of the suprachiasmatic nucleus is sufficient to co-ordinate phasing and stabilisation of sleep-wake cycles and enhance memory deficits in a clockless mouse. https://doi.org/10.1101/2021.02.04.429717

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

The Unreasonable Effectiveness of Cell Types in Describing Neuronal Physiological Features

Single-cell RNA sequencing (scRNA-seq) captures detailed gene expression profiles at scale, while patch-clamp recordings measure intrinsic neuronal electrophysiological properties. Modeling the relations between these two modalities remains a challenge. Here, we compare how well electrophysiological features can be predicted by traditional transcriptomic cell type classification, representations derived from a foundational model (scGPT) pretrained on large-scale scRNA-seq datasets, ion channel-coding genes, and highly variable genes. Using paired transcriptomic and electrophysiological patch-sequencing data from 495 human neurons from neurosurgical tissue, we find that cluster-level cell type representations consistently outperform highly variable gene selection, ion channel gene selection, and context-enriched scGPT embeddings. Notably, performance varies across model architectures and initializations, and the best results are obtained by combining the outputs of separate cell type and scGPT-based models. Together, these findings suggest that traditional discrete cellular classification is highly effective in predicting physiological features. For maximum performance it can be complemented by pretrained transformer models.

neuroscience

A nonlinear inhibition pathway underlying cortical responses to tuned holographic optogenetic perturbations

Optogenetics enables causal manipulation of cortical activity. Perturbation responses can be counterintuitive due to network interactions, making theory essential for predicting them. Existing approaches often rely on linear approximations, which fail for many biologically relevant perturbations. Here we develop a nonlinear theory of responses to holographic perturbations in cell-type-specific recurrent networks with structured connectivity. We fit a nonlinear model to mouse V1 data, which shows cotuned-ensemble suppression: perturbing spatially clustered neurons with similar preferred orientations yields markedly stronger short-range suppression than perturbing untuned ensembles. We show that cotuned-ensemble suppression arises from a feature-tuned, nonlinear inhibition pathway implicating somatostatin-positive (SST) interneurons. The theory predicts that cotuned ensembles suppress parvalbumin-positive (PV) neurons but facilitate SST neurons, and links the degree of cotuned-ensemble suppression or facilitation to the variance of the SST response. This framework identifies mechanisms by which nonlinear inhibition sculpts cortical dynamics and establishes a predictive basis for targeted optogenetic interventions.

neuroscience

Proteomic signatures of APOE ε4 across human tissues and cell types in Alzheimers disease

The apolipoprotein E {varepsilon}4 (APOE {varepsilon}4) allele is the strongest genetic risk factor for late-onset Alzheimers disease (AD). However, the underlying molecular mechanisms remain unclear. This study included 1691 participants from the Religious Orders Study and Rush Memory and Aging Project (ROSMAP), 1226 participants from the Accelerating Medicines Partnership - Alzheimers Disease (AMP-AD) Diverse Cohorts Study, and 735 participants from the Alzheimers Disease Neuroimaging Initiative (ADNI). To characterise APOE {varepsilon}4 molecular effects, we analysed proteomic data from plasma, cerebrospinal fluid (CSF), and induced pluripotent stem cell (iPSC)-derived astrocytes and neurons, as well as transcriptomic and proteomic data from multiple brain regions. The association of APOE {varepsilon}4 with AD neuropathology was also examined. APOE {varepsilon}4 carriers shared a plasma proteomic signature enriched for immune processes, irrespective of AD diagnosis. A machine learning classifier trained on this signature discriminated APOE {varepsilon}4 carriers from non-carriers in an independent cohort using CSF proteomics. APOE {varepsilon}4 carriage was associated with higher Braak stages and Consortium to Establish a Registry for Alzheimers Disease (CERAD) score. However, only limited APOE {varepsilon}4-associated transcriptomic and proteomic changes were observed in bulk brain tissue, with poor cross-layer concordance. Proteomic analyses of iPSC-derived astrocytes and neurons further revealed cell-type-specific APOE {varepsilon}4-associated changes. APOE {varepsilon}4 is associated with a consistent proteomic signature across plasma and CSF. Its molecular effects in the brain differ across cell types, brain regions and molecular layers. These findings support the need for cell-type-resolved multi-omic studies to elucidate how APOE {varepsilon}4 confers AD risk.

neuroscience