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Krutoshinskaya Y, Coulehan K, Pushchinska G, Spiegel R. The Reciprocal Relationship between Sleep and Epilepsy. J Pers Med 2024; 14:118. [PMID: 38276240 PMCID: PMC10817641 DOI: 10.3390/jpm14010118] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Revised: 01/08/2024] [Accepted: 01/17/2024] [Indexed: 01/27/2024] Open
Abstract
The relationship between sleep and epilepsy is bidirectional. Certain epilepsy syndromes predominantly or exclusively manifest during sleep, with seizures frequently originating from non-rapid eye movement (NREM) sleep. Interictal epileptiform discharges observed on electroencephalograms are most likely to be activated during the deep NREM sleep stage known as N3. Conversely, epileptiform discharges, anti-seizure medications (ASMs), as well as other anti-seizure therapies can exert detrimental effects on sleep architecture. Moreover, the co-occurrence of sleep disorders has the potential to exacerbate seizure control. Understating the relationship between sleep and epilepsy is crucial for healthcare providers. Addressing and managing sleep-related problems in individuals with epilepsy can potentially contribute to improved seizure control and overall well-being. At the same time, improving seizure control can improve sleep quality and quantity, thus further improving the health of individuals with epilepsy.
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Affiliation(s)
- Yana Krutoshinskaya
- Department of Neurology, Renaissance School of Medicine at Stony Brook University, Stony Brook, NY 11794, USA; (K.C.); (G.P.); (R.S.)
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Jha PK, Valekunja UK, Ray S, Nollet M, Reddy AB. Single-cell transcriptomics and cell-specific proteomics reveals molecular signatures of sleep. Commun Biol 2022; 5:846. [PMID: 35986171 PMCID: PMC9391396 DOI: 10.1038/s42003-022-03800-3] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Accepted: 08/03/2022] [Indexed: 12/03/2022] Open
Abstract
Every day, we sleep for a third of the day. Sleep is important for cognition, brain waste clearance, metabolism, and immune responses. 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 underpinnings of sleep. Different cell types in three important brain regions for sleep (brainstem, cortex, and hypothalamus) exhibited diverse transcriptional responses to sleep need. Sleep restriction modulates astrocyte-neuron crosstalk and sleep need enhances expression of specific sets of transcription factors in different brain regions. In cortex, we also interrogated the proteome of two major cell types: astrocytes and neurons. Sleep deprivation differentially alters the expression of proteins in astrocytes and neurons. Similarly, phosphoproteomics revealed large shifts in cell-type-specific protein phosphorylation. Our results indicate that sleep need regulates transcriptional, translational, and post-translational responses in a cell-specific manner.
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Affiliation(s)
- Pawan K Jha
- Department of Systems Pharmacology & Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Utham K Valekunja
- Department of Systems Pharmacology & Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Sandipan Ray
- Department of Systems Pharmacology & Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Biotechnology, Indian Institute of Technology Hyderabad, Kandi, Sangareddy, 502285, Telangana, India
| | - Mathieu Nollet
- Department of Systems Pharmacology & Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Imperial College London, South Kensington Campus, London, SW7 2AZ, UK
| | - Akhilesh B Reddy
- Department of Systems Pharmacology & Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.
- Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.
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Archer SN, Schmidt C, Vandewalle G, Dijk DJ. Phenotyping of PER3 variants reveals widespread effects on circadian preference, sleep regulation, and health. Sleep Med Rev 2018; 40:109-126. [PMID: 29248294 DOI: 10.1016/j.smrv.2017.10.008] [Citation(s) in RCA: 69] [Impact Index Per Article: 9.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2017] [Revised: 10/16/2017] [Accepted: 10/30/2017] [Indexed: 12/29/2022]
Abstract
Period3 (Per3) is one of the most robustly rhythmic genes in humans and animals. It plays a significant role in temporal organisation in peripheral tissues. The effects of PER3 variants on many phenotypes have been investigated in targeted and genome-wide studies. PER3 variants, especially the human variable number tandem repeat (VNTR), associate with diurnal preference, mental disorders, non-visual responses to light, brain and cognitive responses to sleep loss/circadian misalignment. Introducing the VNTR into mice alters responses to sleep loss and expression of sleep homeostasis-related genes. Several studies were limited in size and some findings were not replicated. Nevertheless, the data indicate a significant contribution of PER3 to sleep and circadian phenotypes and diseases, which may be connected by common pathways. Thus, PER3-dependent altered light sensitivity could relate to high retinal PER3 expression and may contribute to altered brain response to light, diurnal preference and seasonal mood. Altered cognitive responses during sleep loss/circadian misalignment and changes to slow wave sleep may relate to changes in wake/activity-dependent patterns of hypothalamic gene expression involved in sleep homeostasis and neural network plasticity. Comprehensive characterisation of effects of clock gene variants may provide new insights into the role of circadian processes in health and disease.
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Affiliation(s)
- Simon N Archer
- Sleep Research Centre, Faculty of Health and Medical Sciences, University of Surrey, Guildford GU2 7XP, UK.
| | - Christina Schmidt
- GIGA-Research, Cyclotron Research Centre-In Vivo Imaging Unit, University of Liège, Belgium; Psychology and Neuroscience of Cognition Research Unit (PsyNCog), Faculty of Psychology and Educational Sciences, University of Liège, Belgium
| | - Gilles Vandewalle
- GIGA-Research, Cyclotron Research Centre-In Vivo Imaging Unit, University of Liège, Belgium
| | - Derk-Jan Dijk
- Sleep Research Centre, Faculty of Health and Medical Sciences, University of Surrey, Guildford GU2 7XP, UK
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Khan AM, Grant AH, Martinez A, Burns GAPC, Thatcher BS, Anekonda VT, Thompson BW, Roberts ZS, Moralejo DH, Blevins JE. Mapping Molecular Datasets Back to the Brain Regions They are Extracted from: Remembering the Native Countries of Hypothalamic Expatriates and Refugees. ADVANCES IN NEUROBIOLOGY 2018; 21:101-193. [PMID: 30334222 PMCID: PMC6310046 DOI: 10.1007/978-3-319-94593-4_6] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
This article focuses on approaches to link transcriptomic, proteomic, and peptidomic datasets mined from brain tissue to the original locations within the brain that they are derived from using digital atlas mapping techniques. We use, as an example, the transcriptomic, proteomic and peptidomic analyses conducted in the mammalian hypothalamus. Following a brief historical overview, we highlight studies that have mined biochemical and molecular information from the hypothalamus and then lay out a strategy for how these data can be linked spatially to the mapped locations in a canonical brain atlas where the data come from, thereby allowing researchers to integrate these data with other datasets across multiple scales. A key methodology that enables atlas-based mapping of extracted datasets-laser-capture microdissection-is discussed in detail, with a view of how this technology is a bridge between systems biology and systems neuroscience.
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Affiliation(s)
- Arshad M Khan
- UTEP Systems Neuroscience Laboratory, University of Texas at El Paso, El Paso, TX, USA.
- Department of Biological Sciences, University of Texas at El Paso, El Paso, TX, USA.
- Border Biomedical Research Center, University of Texas at El Paso, El Paso, TX, USA.
| | - Alice H Grant
- UTEP Systems Neuroscience Laboratory, University of Texas at El Paso, El Paso, TX, USA
- Department of Biological Sciences, University of Texas at El Paso, El Paso, TX, USA
- Graduate Program in Pathobiology, University of Texas at El Paso, El Paso, TX, USA
| | - Anais Martinez
- UTEP Systems Neuroscience Laboratory, University of Texas at El Paso, El Paso, TX, USA
- Department of Biological Sciences, University of Texas at El Paso, El Paso, TX, USA
- Graduate Program in Pathobiology, University of Texas at El Paso, El Paso, TX, USA
| | - Gully A P C Burns
- Information Sciences Institute, Viterbi School of Engineering, University of Southern California, Marina del Rey, CA, USA
| | - Brendan S Thatcher
- VA Puget Sound Health Care System, Office of Research and Development Medical Research Service, Department of Veterans Affairs Medical Center, Seattle, WA, USA
| | - Vishwanath T Anekonda
- VA Puget Sound Health Care System, Office of Research and Development Medical Research Service, Department of Veterans Affairs Medical Center, Seattle, WA, USA
| | - Benjamin W Thompson
- VA Puget Sound Health Care System, Office of Research and Development Medical Research Service, Department of Veterans Affairs Medical Center, Seattle, WA, USA
| | - Zachary S Roberts
- VA Puget Sound Health Care System, Office of Research and Development Medical Research Service, Department of Veterans Affairs Medical Center, Seattle, WA, USA
| | - Daniel H Moralejo
- Division of Neonatology, Department of Pediatrics, University of Washington School of Medicine, Seattle, WA, USA
| | - James E Blevins
- VA Puget Sound Health Care System, Office of Research and Development Medical Research Service, Department of Veterans Affairs Medical Center, Seattle, WA, USA
- Division of Metabolism, Endocrinology, and Nutrition, Department of Medicine, University of Washington School of Medicine, Seattle, WA, USA
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Nikonova EV, Gilliland JDA, Tanis KQ, Podtelezhnikov AA, Rigby AM, Galante RJ, Finney EM, Stone DJ, Renger JJ, Pack AI, Winrow CJ. Transcriptional Profiling of Cholinergic Neurons From Basal Forebrain Identifies Changes in Expression of Genes Between Sleep and Wake. Sleep 2017; 40:3608773. [PMID: 28419375 PMCID: PMC6075396 DOI: 10.1093/sleep/zsx059] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
Study objective To assess differences in gene expression in cholinergic basal forebrain cells between sleeping and sleep-deprived mice sacrificed at the same time of day. Methods Tg(ChAT-eGFP)86Gsat mice expressing enhanced green fluorescent protein (eGFP) under control of the choline acetyltransferase (Chat) promoter were utilized to guide laser capture of cholinergic cells in basal forebrain. Messenger RNA expression levels in these cells were profiled using microarrays. Gene expression in eGFP(+) neurons was compared (1) to that in eGFP(-) neurons and to adjacent white matter, (2) between 7:00 am (lights on) and 7:00 pm (lights off), (3) between sleep-deprived and sleeping animals at 0, 3, 6, and 9 hours from lights on. Results There was a marked enrichment of ChAT and other markers of cholinergic neurons in eGFP(+) cells. Comparison of gene expression in these eGFP(+) neurons between 7:00 am and 7:00 pm revealed expected differences in the expression of clock genes (Arntl2, Per1, Per2, Dbp, Nr1d1) as well as mGluR3. Comparison of expression between spontaneous sleep and sleep-deprived groups sacrificed at the same time of day revealed a number of transcripts (n = 55) that had higher expression in sleep deprivation compared to sleep. Genes upregulated in sleep deprivation predominantly were from the protein folding pathway (25 transcripts, including chaperones). Among 42 transcripts upregulated in sleep was the cold-inducible RNA-binding protein. Conclusions Cholinergic cell signatures were characterized. Whether the identified genes are changing as a consequence of differences in behavioral state or as part of the molecular regulatory mechanism remains to be determined.
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Affiliation(s)
- Elena V Nikonova
- Genetics and Pharmacogenomics, Merck Research Laboratories, Merck & Co., Inc., West Point, PA
| | - Jason DA Gilliland
- Center for Sleep and Circadian Neurobiology, University of Pennsylvania, Philadelphia, PA
| | - Keith Q Tanis
- Genetics and Pharmacogenomics, Merck Research Laboratories, Merck & Co., Inc., West Point, PA
| | - Alexei A Podtelezhnikov
- Genetics and Pharmacogenomics, Merck Research Laboratories, Merck & Co., Inc., West Point, PA
| | - Alison M Rigby
- Department of Neuroscience, Merck & Co., Inc., West Point, PA
| | - Raymond J Galante
- Center for Sleep and Circadian Neurobiology, University of Pennsylvania, Philadelphia, PA
| | - Eva M Finney
- Genetics and Pharmacogenomics, Merck Research Laboratories, Merck & Co., Inc., West Point, PA
| | - David J Stone
- Genetics and Pharmacogenomics, Merck Research Laboratories, Merck & Co., Inc., West Point, PA
| | - John J Renger
- Department of Neuroscience, Merck & Co., Inc., West Point, PA
| | - Allan I Pack
- Center for Sleep and Circadian Neurobiology, University of Pennsylvania, Philadelphia, PA
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7
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Bakken TE, Miller JA, Ding SL, Sunkin SM, Smith KA, Ng L, Szafer A, Dalley RA, Royall JJ, Lemon T, Shapouri S, Aiona K, Arnold J, Bennett JL, Bertagnolli D, Bickley K, Boe A, Brouner K, Butler S, Byrnes E, Caldejon S, Carey A, Cate S, Chapin M, Chen J, Dee N, Desta T, Dolbeare TA, Dotson N, Ebbert A, Fulfs E, Gee G, Gilbert TL, Goldy J, Gourley L, Gregor B, Gu G, Hall J, Haradon Z, Haynor DR, Hejazinia N, Hoerder-Suabedissen A, Howard R, Jochim J, Kinnunen M, Kriedberg A, Kuan CL, Lau C, Lee CK, Lee F, Luong L, Mastan N, May R, Melchor J, Mosqueda N, Mott E, Ngo K, Nyhus J, Oldre A, Olson E, Parente J, Parker PD, Parry S, Pendergraft J, Potekhina L, Reding M, Riley ZL, Roberts T, Rogers B, Roll K, Rosen D, Sandman D, Sarreal M, Shapovalova N, Shi S, Sjoquist N, Sodt AJ, Townsend R, Velasquez L, Wagley U, Wakeman WB, White C, Bennett C, Wu J, Young R, Youngstrom BL, Wohnoutka P, Gibbs RA, Rogers J, Hohmann JG, Hawrylycz MJ, Hevner RF, Molnár Z, Phillips JW, Dang C, Jones AR, Amaral DG, Bernard A, Lein ES. A comprehensive transcriptional map of primate brain development. Nature 2016; 535:367-75. [PMID: 27409810 PMCID: PMC5325728 DOI: 10.1038/nature18637] [Citation(s) in RCA: 266] [Impact Index Per Article: 29.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2015] [Accepted: 06/10/2016] [Indexed: 12/20/2022]
Abstract
The transcriptional underpinnings of brain development remain poorly understood, particularly in humans and closely related non-human primates. We describe a high-resolution transcriptional atlas of rhesus monkey (Macaca mulatta) brain development that combines dense temporal sampling of prenatal and postnatal periods with fine anatomical division of cortical and subcortical regions associated with human neuropsychiatric disease. Gene expression changes more rapidly before birth, both in progenitor cells and maturing neurons. Cortical layers and areas acquire adult-like molecular profiles surprisingly late in postnatal development. Disparate cell populations exhibit distinct developmental timing of gene expression, but also unexpected synchrony of processes underlying neural circuit construction including cell projection and adhesion. Candidate risk genes for neurodevelopmental disorders including primary microcephaly, autism spectrum disorder, intellectual disability, and schizophrenia show disease-specific spatiotemporal enrichment within developing neocortex. Human developmental expression trajectories are more similar to monkey than rodent, although approximately 9% of genes show human-specific regulation with evidence for prolonged maturation or neoteny compared to monkey.
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Affiliation(s)
- Trygve E. Bakken
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Jeremy A. Miller
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Song-Lin Ding
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Susan M. Sunkin
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | | | - Lydia Ng
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Aaron Szafer
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Rachel A. Dalley
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Joshua J. Royall
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Tracy Lemon
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Sheila Shapouri
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Kaylynn Aiona
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - James Arnold
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Jeffrey L. Bennett
- Department of Psychiatry and Behavioral Science, California National Primate Research Center, The M.I.N.D. Institute, University of California, Davis, Sacramento, CA 95817, USA
| | | | | | - Andrew Boe
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Krissy Brouner
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Stephanie Butler
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Emi Byrnes
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Shiella Caldejon
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Anita Carey
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Shelby Cate
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Mike Chapin
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Jefferey Chen
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Nick Dee
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Tsega Desta
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Tim A. Dolbeare
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Nadia Dotson
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Amanda Ebbert
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Erich Fulfs
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Garrett Gee
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Terri L. Gilbert
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Jeff Goldy
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Lindsey Gourley
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Ben Gregor
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Guangyu Gu
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Jon Hall
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Zeb Haradon
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - David R. Haynor
- Department of Radiology, University of Washington, Seattle, Washington 98195, USA
| | - Nika Hejazinia
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Anna Hoerder-Suabedissen
- Department of Physiology, Anatomy and Genetics, University of Oxford, South Parks Road Oxford OX1 3QX, UK
| | - Robert Howard
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Jay Jochim
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Marty Kinnunen
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Ali Kriedberg
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Chihchau L. Kuan
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Christopher Lau
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Chang-Kyu Lee
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Felix Lee
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Lon Luong
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Naveed Mastan
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Ryan May
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Jose Melchor
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Nerick Mosqueda
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Erika Mott
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Kiet Ngo
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Julie Nyhus
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Aaron Oldre
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Eric Olson
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Jody Parente
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | | | - Sheana Parry
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | | | - Lydia Potekhina
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Melissa Reding
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Zackery L. Riley
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Tyson Roberts
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Brandon Rogers
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Kate Roll
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - David Rosen
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - David Sandman
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Melaine Sarreal
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | | | - Shu Shi
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Nathan Sjoquist
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Andy J. Sodt
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Robbie Townsend
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | | | - Udi Wagley
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Wayne B. Wakeman
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Cassandra White
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Crissa Bennett
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Jennifer Wu
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Rob Young
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | | | - Paul Wohnoutka
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Richard A. Gibbs
- Human Genome Sequencing Center and Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas 77030, USA
| | - Jeffrey Rogers
- Human Genome Sequencing Center and Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas 77030, USA
| | - John G. Hohmann
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | | | - Robert F. Hevner
- Center for Integrative Brain Research, Seattle Children’s Research Institute, Seattle, Washington 98101, USA
| | - Zoltán Molnár
- Department of Physiology, Anatomy and Genetics, University of Oxford, South Parks Road Oxford OX1 3QX, UK
| | - John W. Phillips
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Chinh Dang
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Allan R. Jones
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - David G. Amaral
- Department of Psychiatry and Behavioral Science, California National Primate Research Center, The M.I.N.D. Institute, University of California, Davis, Sacramento, CA 95817, USA
| | - Amy Bernard
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
| | - Ed S. Lein
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
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8
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Sleepiness phenomics: Modeling individual differences in subjective sleepiness profiles. Int J Psychophysiol 2014; 93:150-61. [DOI: 10.1016/j.ijpsycho.2013.03.021] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2012] [Revised: 03/26/2013] [Accepted: 03/28/2013] [Indexed: 01/08/2023]
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Miller RA, Winrow CJ, Spellman DS, Song Q, Reiss DR, Conway JP, Taylor RR, Coleman PJ, Hendrickson RC, Renger JJ. Quantitative proteomics in laser capture microdissected sleep nuclei from rat brain. J Neurogenet 2014; 28:136-45. [PMID: 24579665 PMCID: PMC4075250 DOI: 10.3109/01677063.2014.883389] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
The combination of stable isotope labeling of amino acids in mammals (SILAM) and laser capture microdissection (LCM) for selective proteomic analysis of the targeted tissues holds tremendous potential for refined characterization of proteome changes within complex tissues such as the brain. The authors have applied this approach to measure changes in relative protein abundance in ventral tegmental area (VTA) of the rat brain that correlate to pharmacological perturbations. Enriched 13C615N2-lysine was introduced in vivo via diet. These animals were sacrificed during the middle of the 12-hour light period to extract isotopically “heavy” proteins, which were then used as a reference for extracts from dosed, unlabeled rats. Animals were administered an orexin peptide (Ox-B), an orexin receptor antagonist (ORA), or a mixture of both (Ox-B + ORA). All samples were obtained at same phase of the sleep cycle. Labeled-pair identification and differential quantitation provided protein identification and expression ratio data. Five proteins were found to exhibit decreased relative abundance after administration of an ORA, including α-synuclein and rat myelin basic protein. Conversely, six proteins showed increased relative abundance upon antagonist treatment, including 2’,3’-cyclic nucleotide 3’-phosphodiesterase.
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Affiliation(s)
- Ronald A Miller
- Department of Proteomics, Molecular Profiling and Research Informatics, Merck Research Laboratories , West Point, Pennsylvania , USA
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10
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Abstract
Previous studies of differential gene expression in sleep and wake pooled transcripts from all brain cells and showed that several genes expressed at higher levels during sleep are involved in the synthesis/maintenance of membranes in general and of myelin in particular, a surprising finding given the reported slow turnover of many myelin components. Other studies showed that oligodendrocyte precursor cells (OPCs) are responsible for the formation of new myelin in both the injured and the normal adult brain, and that glutamate released from neurons, via neuron-OPC synapses, can inhibit OPC proliferation and affect their differentiation into myelin-forming oligodendrocytes. Because glutamatergic transmission is higher in wake than in sleep, we asked whether sleep and wake can affect oligodendrocytes and OPCs. Using the translating ribosome affinity purification technology combined with microarray analysis in mice, we obtained a genome-wide profiling of oligodendrocytes after sleep, spontaneous wake, and forced wake (acute sleep deprivation). We found that hundreds of transcripts being translated in oligodendrocytes are differentially expressed in sleep and wake: genes involved in phospholipid synthesis and myelination or promoting OPC proliferation are transcribed preferentially during sleep, while genes implicated in apoptosis, cellular stress response, and OPC differentiation are enriched in wake. We then confirmed through BrdU and other experiments that OPC proliferation doubles during sleep and positively correlates with time spent in REM sleep, whereas OPC differentiation is higher during wake. Thus, OPC proliferation and differentiation are not perfectly matched at any given circadian time but preferentially occur during sleep and wake, respectively.
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11
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Regression of atherosclerosis is characterized by broad changes in the plaque macrophage transcriptome. PLoS One 2012; 7:e39790. [PMID: 22761902 PMCID: PMC3384622 DOI: 10.1371/journal.pone.0039790] [Citation(s) in RCA: 89] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2012] [Accepted: 05/29/2012] [Indexed: 01/19/2023] Open
Abstract
We have developed a mouse model of atherosclerotic plaque regression in which an atherosclerotic aortic arch from a hyperlipidemic donor is transplanted into a normolipidemic recipient, resulting in rapid elimination of cholesterol and monocyte-derived macrophage cells (CD68+) from transplanted vessel walls. To gain a comprehensive view of the differences in gene expression patterns in macrophages associated with regressing compared with progressing atherosclerotic plaque, we compared mRNA expression patterns in CD68+ macrophages extracted from plaque in aortic aches transplanted into normolipidemic or into hyperlipidemic recipients. In CD68+ cells from regressing plaque we observed that genes associated with the contractile apparatus responsible for cellular movement (e.g. actin and myosin) were up-regulated whereas genes related to cell adhesion (e.g. cadherins, vinculin) were down-regulated. In addition, CD68+ cells from regressing plaque were characterized by enhanced expression of genes associated with an anti-inflammatory M2 macrophage phenotype, including arginase I, CD163 and the C-lectin receptor. Our analysis suggests that in regressing plaque CD68+ cells preferentially express genes that reduce cellular adhesion, enhance cellular motility, and overall act to suppress inflammation.
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Bernard A, Lubbers LS, Tanis KQ, Luo R, Podtelezhnikov AA, Finney EM, McWhorter MME, Serikawa K, Lemon T, Morgan R, Copeland C, Smith K, Cullen V, Davis-Turak J, Lee CK, Sunkin SM, Loboda AP, Levine DM, Stone DJ, Hawrylycz MJ, Roberts CJ, Jones AR, Geschwind DH, Lein ES. Transcriptional architecture of the primate neocortex. Neuron 2012; 73:1083-99. [PMID: 22445337 DOI: 10.1016/j.neuron.2012.03.002] [Citation(s) in RCA: 178] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/01/2012] [Indexed: 01/03/2023]
Abstract
Genome-wide transcriptional profiling was used to characterize the molecular underpinnings of neocortical organization in rhesus macaque, including cortical areal specialization and laminar cell-type diversity. Microarray analysis of individual cortical layers across sensorimotor and association cortices identified robust and specific molecular signatures for individual cortical layers and areas, prominently involving genes associated with specialized neuronal function. Overall, transcriptome-based relationships were related to spatial proximity, being strongest between neighboring cortical areas and between proximal layers. Primary visual cortex (V1) displayed the most distinctive gene expression compared to other cortical regions in rhesus and human, both in the specialized layer 4 as well as other layers. Laminar patterns were more similar between macaque and human compared to mouse, as was the unique V1 profile that was not observed in mouse. These data provide a unique resource detailing neocortical transcription patterns in a nonhuman primate with great similarity in gene expression to human.
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Affiliation(s)
- Amy Bernard
- Allen Institute for Brain Science, Seattle, WA 98103, USA
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Atkins N, Miller CM, Owens JR, Turek FW. Non-laser capture microscopy approach for the microdissection of discrete mouse brain regions for total RNA isolation and downstream next-generation sequencing and gene expression profiling. J Vis Exp 2011:3125. [PMID: 22104983 DOI: 10.3791/3125] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/31/2022] Open
Abstract
As technological platforms, approaches such as next-generation sequencing, microarray, and qRT-PCR have great promise for expanding our understanding of the breadth of molecular regulation. Newer approaches such as high-resolution RNA sequencing (RNA-Seq)(1) provides new and expansive information about tissue- or state-specific expression such as relative transcript levels, alternative splicing, and micro RNAs(2-4). Prospects for employing the RNA-Seq method in comparative whole transcriptome profiling(5) within discrete tissues or between phenotypically distinct groups of individuals affords new avenues for elucidating molecular mechanisms involved in both normal and abnormal physiological states. Recently, whole transcriptome profiling has been performed on human brain tissue, identifying gene expression differences associated with disease progression(6). However, the use of next-generation sequencing has yet to be more widely integrated into mammalian studies. Gene expression studies in mouse models have reported distinct profiles within various brain nuclei using laser capture microscopy (LCM) for sample excision(7,8). While LCM affords sample collection with single-cell and discrete brain region precision, the relatively low total RNA yields from the LCM approach can be prohibitive to RNA-Seq and other profiling approaches in mouse brain tissues and may require sub-optimal sample amplification steps. Here, a protocol is presented for microdissection and total RNA extraction from discrete mouse brain regions. Set-diameter tissue corers are used to isolate 13 tissues from 750-μm serial coronal sections of an individual mouse brain. Tissue micropunch samples are immediately frozen and archived. Total RNA is obtained from the samples using magnetic bead-enabled total RNA isolation technology. Resulting RNA samples have adequate yield and quality for use in downstream expression profiling. This microdissection strategy provides a viable option to existing sample collection strategies for obtaining total RNA from discrete brain regions, opening possibilities for new gene expression discoveries.
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Affiliation(s)
- Norman Atkins
- Center for Sleep and Circadian Biology, Northwestern University
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14
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Thompson CL, Wisor JP, Lee CK, Pathak SD, Gerashchenko D, Smith KA, Fischer SR, Kuan CL, Sunkin SM, Ng LL, Lau C, Hawrylycz M, Jones AR, Kilduff TS, Lein ES. Molecular and anatomical signatures of sleep deprivation in the mouse brain. Front Neurosci 2010; 4:165. [PMID: 21088695 PMCID: PMC2981377 DOI: 10.3389/fnins.2010.00165] [Citation(s) in RCA: 80] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2010] [Accepted: 08/23/2010] [Indexed: 11/13/2022] Open
Abstract
Sleep deprivation (SD) leads to a suite of cognitive and behavioral impairments, and yet the molecular consequences of SD in the brain are poorly understood. Using a systematic immediate-early gene (IEG) mapping to detect neuronal activation, the consequences of SD were mapped primarily to forebrain regions. SD was found to both induce and suppress IEG expression (and thus neuronal activity) in subregions of neocortex, striatum, and other brain regions. Laser microdissection and cDNA microarrays were used to identify the molecular consequences of SD in seven brain regions. In situ hybridization (ISH) for 222 genes selected from the microarray data and other sources confirmed that robust molecular changes were largely restricted to the forebrain. Analysis of the ISH data for 222 genes (publicly accessible at http://sleep.alleninstitute.org) provided a molecular and anatomic signature of the effects of SD on the brain. The suprachiasmatic nucleus (SCN) and the neocortex exhibited differential regulation of the same genes, such that in the SCN genes exhibited time-of-day effects while in the neocortex, genes exhibited only SD and waking (W) effects. In the neocortex, SD activated gene expression in areal-, layer-, and cell type-specific manner. In the forebrain, SD preferentially activated excitatory neurons, as demonstrated by double-labeling, except for striatum which consists primarily of inhibitory neurons. These data provide a characterization of the anatomical and cell type-specific signatures of SD on neuronal activity and gene expression that may account for the associated cognitive and behavioral effects.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | - Lydia L. Ng
- Allen Institute for Brain ScienceSeattle, WA, USA
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Dijk DJ, Archer SN. PERIOD3, circadian phenotypes, and sleep homeostasis. Sleep Med Rev 2010; 14:151-60. [PMID: 19716732 DOI: 10.1016/j.smrv.2009.07.002] [Citation(s) in RCA: 161] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2009] [Revised: 07/06/2009] [Accepted: 07/06/2009] [Indexed: 01/22/2023]
Abstract
Circadian rhythmicity and sleep homeostasis contribute to sleep phenotypes and sleep-wake disorders, some of the genetic determinants of which are emerging. Approximately 10% of the population are homozygous for the 5-repeat allele (PER3(5/5)) of a variable number tandem repeat polymorphism in the clock gene PERIOD3 (PER3). We review recent data on the effects of this polymorphism on sleep-wake regulation. PER3(5/5) are more likely to show morning preference, whereas homozygosity for the four-repeat allele (PER3(4/4)) associates with evening preferences. The association between sleep timing and the circadian rhythms of melatonin and PER3 RNA in leukocytes is stronger in PER3(5/5) than in PER3(4/4). EEG alpha activity in REM sleep, theta/alpha activity during wakefulness and slow wave activity in NREM sleep are elevated in PER3(5/5). PER3(5/5) show a greater cognitive decline, and a greater reduction in fMRI-assessed brain responses to an executive task, in response to total sleep deprivation. These effects are most pronounced during the late circadian night/early morning hours, i.e., approximately 0-4h after the crest of the melatonin rhythm. We interpret the effects of the PER3 polymorphism within the context of a conceptual model in which higher homeostatic sleep pressure in PER3(5/5) through feedback onto the circadian pacemaker modulates the amplitude of diurnal variation in performance. These findings highlight the interrelatedness of circadian rhythmicity and sleep homeostasis.
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Affiliation(s)
- Derk-Jan Dijk
- Surrey Sleep Research Centre, Faculty of Health and Medical Sciences, University of Surrey, Guildford, GU2 7XP, UK.
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Winrow CJ, Tanis KQ, Reiss DR, Rigby AM, Uslaner JM, Uebele VN, Doran SM, Fox SV, Garson SL, Gotter AL, Levine DM, Roecker AJ, Coleman PJ, Koblan KS, Renger JJ. Orexin receptor antagonism prevents transcriptional and behavioral plasticity resulting from stimulant exposure. Neuropharmacology 2010; 58:185-94. [DOI: 10.1016/j.neuropharm.2009.07.008] [Citation(s) in RCA: 59] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2009] [Revised: 07/02/2009] [Accepted: 07/03/2009] [Indexed: 12/20/2022]
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