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Bojarskaite L, Bjørnstad DM, Pettersen KH, Cunen C, Hermansen GH, Åbjørsbråten KS, Chambers AR, Sprengel R, Vervaeke K, Tang W, Enger R, Nagelhus EA. Astrocytic Ca 2+ signaling is reduced during sleep and is involved in the regulation of slow wave sleep. Nat Commun 2020; 11:3240. [PMID: 32632168 PMCID: PMC7338360 DOI: 10.1038/s41467-020-17062-2] [Citation(s) in RCA: 103] [Impact Index Per Article: 25.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2019] [Accepted: 06/09/2020] [Indexed: 12/31/2022] Open
Abstract
Astrocytic Ca2+ signaling has been intensively studied in health and disease but has not been quantified during natural sleep. Here, we employ an activity-based algorithm to assess astrocytic Ca2+ signals in the neocortex of awake and naturally sleeping mice while monitoring neuronal Ca2+ activity, brain rhythms and behavior. We show that astrocytic Ca2+ signals exhibit distinct features across the sleep-wake cycle and are reduced during sleep compared to wakefulness. Moreover, an increase in astrocytic Ca2+ signaling precedes transitions from slow wave sleep to wakefulness, with a peak upon awakening exceeding the levels during whisking and locomotion. Finally, genetic ablation of an important astrocytic Ca2+ signaling pathway impairs slow wave sleep and results in an increased number of microarousals, abnormal brain rhythms, and an increased frequency of slow wave sleep state transitions and sleep spindles. Our findings demonstrate an essential role for astrocytic Ca2+ signaling in regulating slow wave sleep.
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Affiliation(s)
- Laura Bojarskaite
- Letten Centre and GliaLab, Division of Physiology, Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, 0317, Oslo, Norway
| | - Daniel M Bjørnstad
- Letten Centre and GliaLab, Division of Physiology, Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, 0317, Oslo, Norway
| | - Klas H Pettersen
- Letten Centre and GliaLab, Division of Physiology, Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, 0317, Oslo, Norway
| | - Céline Cunen
- Statistics and Data Science group, Department of Mathematics, Faculty of Mathematics and Natural Sciences, University of Oslo, 0316, Oslo, Norway
| | - Gudmund Horn Hermansen
- Statistics and Data Science group, Department of Mathematics, Faculty of Mathematics and Natural Sciences, University of Oslo, 0316, Oslo, Norway
| | - Knut Sindre Åbjørsbråten
- Letten Centre and GliaLab, Division of Physiology, Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, 0317, Oslo, Norway
| | - Anna R Chambers
- Lab for Neural Computation, Division of Physiology, Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, 0317, Oslo, Norway
| | - Rolf Sprengel
- Research Group of the Max Planck Institute for Medical Research, Institute for Anatomy and Cell Biology, Heidelberg University, 69120, Heidelberg, Germany
| | - Koen Vervaeke
- Lab for Neural Computation, Division of Physiology, Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, 0317, Oslo, Norway
| | - Wannan Tang
- Letten Centre and GliaLab, Division of Physiology, Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, 0317, Oslo, Norway.,Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway
| | - Rune Enger
- Letten Centre and GliaLab, Division of Physiology, Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, 0317, Oslo, Norway. .,Division of Anatomy, Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, 0317, Oslo, Norway. .,Department of Neurology, Oslo University Hospital, Rikshospitalet, 0027, Oslo, Norway.
| | - Erlend A Nagelhus
- Letten Centre and GliaLab, Division of Physiology, Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, 0317, Oslo, Norway.,Department of Neurology, Oslo University Hospital, Rikshospitalet, 0027, Oslo, Norway
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Miyazaki T, Kanda T, Tsujino N, Ishii R, Nakatsuka D, Kizuka M, Kasagi Y, Hino H, Yanagisawa M. Dynamics of Cortical Local Connectivity during Sleep-Wake States and the Homeostatic Process. Cereb Cortex 2020; 30:3977-3990. [PMID: 32037455 DOI: 10.1093/cercor/bhaa012] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2019] [Revised: 12/11/2019] [Accepted: 01/09/2020] [Indexed: 02/06/2023] Open
Abstract
Sleep exerts modulatory effects on the cerebral cortex. Whether sleep modulates local connectivity in the cortex or only individual neural activity, however, is poorly understood. Here we investigated functional connectivity, that is, covarying activity between neurons, during spontaneous sleep-wake states and during and after sleep deprivation using calcium imaging of identified excitatory/inhibitory neurons in the motor cortex. Functional connectivity was estimated with a statistical learning approach glasso and quantified by "the probability of establishing connectivity (sparse/dense)" and "the strength of the established connectivity (weak/strong)." Local cortical connectivity was sparse in non-rapid eye movement (NREM) sleep and dense in REM sleep, which was similar in both excitatory and inhibitory neurons. The overall mean strength of the connectivity did not differ largely across spontaneous sleep-wake states. Sleep deprivation induced strong excitatory/inhibitory and dense inhibitory, but not excitatory, connectivity. Subsequent NREM sleep after sleep deprivation exhibited weak excitatory/inhibitory, sparse excitatory, and dense inhibitory connectivity. These findings indicate that sleep-wake states modulate local cortical connectivity, and the modulation is large and compensatory for stability of local circuits during the homeostatic control of sleep, which contributes to plastic changes in neural information flow.
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Affiliation(s)
- Takehiro Miyazaki
- International Institute for Integrative Sleep Medicine, University of Tsukuba, Ibaraki 305-8575, Japan
| | - Takeshi Kanda
- International Institute for Integrative Sleep Medicine, University of Tsukuba, Ibaraki 305-8575, Japan
| | - Natsuko Tsujino
- International Institute for Integrative Sleep Medicine, University of Tsukuba, Ibaraki 305-8575, Japan
| | - Ryo Ishii
- International Institute for Integrative Sleep Medicine, University of Tsukuba, Ibaraki 305-8575, Japan
| | - Daiki Nakatsuka
- International Institute for Integrative Sleep Medicine, University of Tsukuba, Ibaraki 305-8575, Japan
| | - Mariko Kizuka
- International Institute for Integrative Sleep Medicine, University of Tsukuba, Ibaraki 305-8575, Japan
| | - Yasuhiro Kasagi
- International Institute for Integrative Sleep Medicine, University of Tsukuba, Ibaraki 305-8575, Japan
| | - Hideitsu Hino
- Department of Statistical Modeling, The Institute of Statistical Mathematics, Tokyo 190-8562, Japan
| | - Masashi Yanagisawa
- International Institute for Integrative Sleep Medicine, University of Tsukuba, Ibaraki 305-8575, Japan.,Department of Molecular Genetics, University of Texas Southwestern Medical Center, Dallas, TX 75390-9050, USA.,Life Science Center for Survival Dynamics (TARA), University of Tsukuba, Ibaraki 305-8575, Japan.,R&D Center for Frontiers of Mirai in Policy and Technology (F-MIRAI), University of Tsukuba, Ibaraki 305-8575, Japan
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Cooper JM, Halter KA, Prosser RA. Circadian rhythm and sleep-wake systems share the dynamic extracellular synaptic milieu. Neurobiol Sleep Circadian Rhythms 2018; 5:15-36. [PMID: 31236509 PMCID: PMC6584685 DOI: 10.1016/j.nbscr.2018.04.001] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2017] [Revised: 03/06/2018] [Accepted: 04/10/2018] [Indexed: 01/23/2023] Open
Abstract
The mammalian circadian and sleep-wake systems are closely aligned through their coordinated regulation of daily activity patterns. Although they differ in their anatomical organization and physiological processes, they utilize overlapping regulatory mechanisms that include an assortment of proteins and molecules interacting within the extracellular space. These extracellular factors include proteases that interact with soluble proteins, membrane-attached receptors and the extracellular matrix; and cell adhesion molecules that can form complex scaffolds connecting adjacent neurons, astrocytes and their respective intracellular cytoskeletal elements. Astrocytes also participate in the dynamic regulation of both systems through modulating neuronal appositions, the extracellular space and/or through release of gliotransmitters that can further contribute to the extracellular signaling processes. Together, these extracellular elements create a system that integrates rapid neurotransmitter signaling across longer time scales and thereby adjust neuronal signaling to reflect the daily fluctuations fundamental to both systems. Here we review what is known about these extracellular processes, focusing specifically on areas of overlap between the two systems. We also highlight questions that still need to be addressed. Although we know many of the extracellular players, far more research is needed to understand the mechanisms through which they modulate the circadian and sleep-wake systems.
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Key Words
- ADAM, A disintegrin and metalloproteinase
- AMPAR, AMPA receptor
- Astrocytes
- BDNF, brain-derived neurotrophic factor
- BMAL1, Brain and muscle Arnt-like-1 protein
- Bmal1, Brain and muscle Arnt-like-1 gene
- CAM, cell adhesion molecules
- CRY, cryptochrome protein
- Cell adhesion molecules
- Circadian rhythms
- Cry, cryptochrome gene
- DD, dark-dark
- ECM, extracellular matrix
- ECS, extracellular space
- EEG, electroencephalogram
- Endo N, endoneuraminidase N
- Extracellular proteases
- GFAP, glial fibrillary acidic protein
- IL, interleukin
- Ig, immunoglobulin
- LC, locus coeruleus
- LD, light-dark
- LH, lateral hypothalamus
- LRP-1, low density lipoprotein receptor-related protein 1
- LTP, long-term potentiation
- MMP, matrix metalloproteinases
- NCAM, neural cell adhesion molecule protein
- NMDAR, NMDA receptor
- NO, nitric oxide
- NST, nucleus of the solitary tract
- Ncam, neural cell adhesion molecule gene
- Nrl, neuroligin gene
- Nrx, neurexin gene
- P2, purine type 2 receptor
- PAI-1, plasminogen activator inhibitor-1
- PER, period protein
- PPT, peduculopontine tegmental nucleus
- PSA, polysialic acid
- Per, period gene
- REMS, rapid eye movement sleep
- RSD, REM sleep disruption
- SCN, suprachiasmatic nucleus
- SWS, slow wave sleep
- Sleep-wake system
- Suprachiasmatic nucleus
- TNF, tumor necrosis factor
- TTFL, transcriptional-translational negative feedback loop
- VIP, vasoactive intestinal polypeptide
- VLPO, ventrolateral preoptic
- VP, vasopressin
- VTA, ventral tegmental area
- dNlg4, drosophila neuroligin-4 gene
- nNOS, neuronal nitric oxide synthase gene
- nNOS, neuronal nitric oxide synthase protein
- tPA, tissue-type plasminogen activator
- uPA, urokinase-type plasminogen activator
- uPAR, uPA receptor
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