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Otomo K, Omura T, Nozawa Y, Edwards SJ, Sato Y, Saito Y, Yagishita S, Uchida H, Watakabe Y, Naitou K, Yanai R, Sahara N, Takagi S, Katayama R, Iwata Y, Shiokawa T, Hayakawa Y, Otsuka K, Watanabe-Takano H, Haneda Y, Fukuhara S, Fujiwara M, Nii T, Meno C, Takeshita N, Yashiro K, Rosales Rocabado JM, Kaku M, Yamada T, Oishi Y, Koike H, Cheng Y, Sekine K, Koga JI, Sugiyama K, Kimura K, Karube F, Kim H, Manabe I, Nemoto T, Tainaka K, Hamada A, Brismar H, Susaki EA. descSPIM: an affordable and easy-to-build light-sheet microscope optimized for tissue clearing techniques. Nat Commun 2024; 15:4941. [PMID: 38866781 PMCID: PMC11169475 DOI: 10.1038/s41467-024-49131-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2023] [Accepted: 05/24/2024] [Indexed: 06/14/2024] Open
Abstract
Despite widespread adoption of tissue clearing techniques in recent years, poor access to suitable light-sheet fluorescence microscopes remains a major obstacle for biomedical end-users. Here, we present descSPIM (desktop-equipped SPIM for cleared specimens), a low-cost ($20,000-50,000), low-expertise (one-day installation by a non-expert), yet practical do-it-yourself light-sheet microscope as a solution for this bottleneck. Even the most fundamental configuration of descSPIM enables multi-color imaging of whole mouse brains and a cancer cell line-derived xenograft tumor mass for the visualization of neurocircuitry, assessment of drug distribution, and pathological examination by false-colored hematoxylin and eosin staining in a three-dimensional manner. Academically open-sourced ( https://github.com/dbsb-juntendo/descSPIM ), descSPIM allows routine three-dimensional imaging of cleared samples in minutes. Thus, the dissemination of descSPIM will accelerate biomedical discoveries driven by tissue clearing technologies.
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Affiliation(s)
- Kohei Otomo
- Department of Biochemistry and Systems Biomedicine, Juntendo University Graduate School of Medicine, Tokyo, Japan
- Biochemistry II, Juntendo University School of Medicine, Tokyo, Japan
- Nakatani Biomedical Spatialomics Hub, Juntendo University Graduate School of Medicine, Tokyo, Japan
- Division of Biophotonics, National Institute for Physiological Sciences, National Institutes of Natural Sciences, Okazaki, Japan
- Biophotonics Research Group, Exploratory Research Center on Life and Living Systems, National Institutes of Natural Sciences, Okazaki, Japan
| | - Takaki Omura
- Department of Biochemistry and Systems Biomedicine, Juntendo University Graduate School of Medicine, Tokyo, Japan
- Nakatani Biomedical Spatialomics Hub, Juntendo University Graduate School of Medicine, Tokyo, Japan
- Department of Neurosurgery, University of Tokyo, Tokyo, Japan
- Department of Neurosurgery and Neuro-Oncology, National Cancer Center Hospital, Tokyo, Japan
| | - Yuki Nozawa
- Biochemistry II, Juntendo University School of Medicine, Tokyo, Japan
| | - Steven J Edwards
- Science for Life Laboratory, Department of Applied Physics, KTH Royal Institute of Technology, Stockholm, Sweden
| | - Yukihiko Sato
- Department of Biochemistry and Systems Biomedicine, Juntendo University Graduate School of Medicine, Tokyo, Japan
- Nakatani Biomedical Spatialomics Hub, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Yuri Saito
- Department of Biochemistry and Systems Biomedicine, Juntendo University Graduate School of Medicine, Tokyo, Japan
- Nakatani Biomedical Spatialomics Hub, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Shigehiro Yagishita
- Department of Pharmacology and Therapeutics, Fundamental Innovative Oncology Core, National Cancer Center Research Institute, Tokyo, Japan
- Division of Molecular Pharmacology, National Cancer Center Research Institute, Tokyo, Japan
| | - Hitoshi Uchida
- Department of System Pathology for Neurological Disorders, Brain Research Institute, Niigata University, Niigata, Japan
| | - Yuki Watakabe
- Division of Biophotonics, National Institute for Physiological Sciences, National Institutes of Natural Sciences, Okazaki, Japan
- Biophotonics Research Group, Exploratory Research Center on Life and Living Systems, National Institutes of Natural Sciences, Okazaki, Japan
| | - Kiyotada Naitou
- Department of Basic Veterinary Science, Joint Faculty of Veterinary Medicine, Kagoshima University, Kagoshima, Japan
| | - Rin Yanai
- Advanced Neuroimaging Center, Institute for Quantum Medical Sciences, National Institutes for Quantum Science and Technology, Chiba, Japan
| | - Naruhiko Sahara
- Advanced Neuroimaging Center, Institute for Quantum Medical Sciences, National Institutes for Quantum Science and Technology, Chiba, Japan
| | - Satoshi Takagi
- Division of Experimental Chemotherapy, Cancer Chemotherapy Center, Japanese Foundation for Cancer Research, Tokyo, Japan
| | - Ryohei Katayama
- Division of Experimental Chemotherapy, Cancer Chemotherapy Center, Japanese Foundation for Cancer Research, Tokyo, Japan
| | - Yusuke Iwata
- Department of Gastroenterology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Toshiro Shiokawa
- Department of Gastroenterology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Yoku Hayakawa
- Department of Gastroenterology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Kensuke Otsuka
- Biology and Environmental Chemistry Division, Sustainable System Research Laboratory, Central Research Institute of Electric Power Industry, Chiba, Japan
| | - Haruko Watanabe-Takano
- Department of Molecular Pathophysiology, Institute for Advanced Medical Sciences, Nippon Medical School, Tokyo, Japan
| | - Yuka Haneda
- Department of Molecular Pathophysiology, Institute for Advanced Medical Sciences, Nippon Medical School, Tokyo, Japan
| | - Shigetomo Fukuhara
- Department of Molecular Pathophysiology, Institute for Advanced Medical Sciences, Nippon Medical School, Tokyo, Japan
| | - Miku Fujiwara
- Department of Developmental Biology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Takenobu Nii
- Department of Developmental Biology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Chikara Meno
- Department of Developmental Biology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Naoki Takeshita
- Anatomy and Developmental Biology, Kyoto Prefectural University of Medicine, Kyoto, Japan
- Department of Pediatrics, Kyoto Prefectural University of Medicine, Kyoto, Japan
| | - Kenta Yashiro
- Anatomy and Developmental Biology, Kyoto Prefectural University of Medicine, Kyoto, Japan
| | - Juan Marcelo Rosales Rocabado
- Division of Bio-prosthodontics, Faculty of Dentistry & Graduate School of Medical and Dental Sciences, Niigata University, Niigata, Japan
| | - Masaru Kaku
- Division of Bio-prosthodontics, Faculty of Dentistry & Graduate School of Medical and Dental Sciences, Niigata University, Niigata, Japan
| | - Tatsuya Yamada
- Department of Biochemistry, University of Nebraska-Lincoln, Lincoln, USA
| | - Yumiko Oishi
- Department of Meidical Biochemistry, Tokyo Medical and Dental University, Tokyo, Japan
| | - Hiroyuki Koike
- Department of Meidical Biochemistry, Tokyo Medical and Dental University, Tokyo, Japan
| | - Yinglan Cheng
- Department of Meidical Biochemistry, Tokyo Medical and Dental University, Tokyo, Japan
| | - Keisuke Sekine
- Laboratory of Cancer Cell Systems, National Cancer Center Research Institute, Tokyo, Japan
| | - Jun-Ichiro Koga
- The Second Department of Internal Medicine, University of Occupational and Environmental Health, Kitakyushu, Japan
| | - Kaori Sugiyama
- Institute for Advanced Research of Biosystem Dynamics, Research Institute for Science and Engineering, Waseda University, Tokyo, Japan
| | - Kenichi Kimura
- Life Science Center for Survival Dynamics, Tsukuba Advanced Research Alliance (TARA), University of Tsukuba, Tsukuba, Japan
| | - Fuyuki Karube
- Lab of Histology and Cytology, Graduate School of Medicine, Hokkaido University, Sapporo, Japan
| | - Hyeree Kim
- Department of Systems Medicine, Graduate School of Medicine, Chiba University, Chiba, Japan
| | - Ichiro Manabe
- Department of Systems Medicine, Graduate School of Medicine, Chiba University, Chiba, Japan
| | - Tomomi Nemoto
- Division of Biophotonics, National Institute for Physiological Sciences, National Institutes of Natural Sciences, Okazaki, Japan
- Biophotonics Research Group, Exploratory Research Center on Life and Living Systems, National Institutes of Natural Sciences, Okazaki, Japan
| | - Kazuki Tainaka
- Department of System Pathology for Neurological Disorders, Brain Research Institute, Niigata University, Niigata, Japan
| | - Akinobu Hamada
- Department of Pharmacology and Therapeutics, Fundamental Innovative Oncology Core, National Cancer Center Research Institute, Tokyo, Japan
- Division of Molecular Pharmacology, National Cancer Center Research Institute, Tokyo, Japan
| | - Hjalmar Brismar
- Science for Life Laboratory, Department of Applied Physics, KTH Royal Institute of Technology, Stockholm, Sweden
| | - Etsuo A Susaki
- Department of Biochemistry and Systems Biomedicine, Juntendo University Graduate School of Medicine, Tokyo, Japan.
- Biochemistry II, Juntendo University School of Medicine, Tokyo, Japan.
- Nakatani Biomedical Spatialomics Hub, Juntendo University Graduate School of Medicine, Tokyo, Japan.
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Johnson MC, Zweig JA, Zhang Y, Ryabinin AE. Effects of social housing on alcohol intake in mice depend on the non-social environment. Front Behav Neurosci 2024; 18:1380031. [PMID: 38817806 PMCID: PMC11137225 DOI: 10.3389/fnbeh.2024.1380031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Accepted: 05/01/2024] [Indexed: 06/01/2024] Open
Abstract
Background Excessive alcohol consumption leads to serious health problems. Mechanisms regulating the consumption of alcohol are insufficiently understood. Previous preclinical studies suggested that non-social environmental and social environmental complexities can regulate alcohol consumption in opposite directions. However, previous studies did not include all conditions and/or did not include female rodents. Therefore, in this study, we examined the effects of social versus single housing in standard versus non-standard housing conditions in male and female mice. Methods Adult C57BL/6 J mice were housed in either standard shoebox cages or in automated Herdsman 2 (HM2) cages and exposed to a two-bottle choice procedure with 3% or 6% ethanol versus water for 5 days. The HM2 cages use radiotracking devices to measure the fluid consumption of individual mice in an undisturbed and automated manner. In both housing conditions, mice were housed either at one or at four per cage. Results In standard cages, group housing of animals decreased alcohol consumption and water consumption. In HM2 cages, group housing significantly increased ethanol preference and decreased water intake. There were no significant differences in these effects between male and female animals. These observations were similar for 3 and 6% ethanol solutions but were more pronounced for the latter. The effects of social environment on ethanol preference in HM2 cages were accompanied by an increase in the number of approaches to the ethanol solution and a decrease in the number of approaches to water. The differences in ethanol intake could not be explained by differences in locomotor or exploratory activity as socially housed mice showed fewer non-consummatory visits to the ethanol solutions than single-housed animals. In addition, we observed that significant changes in behaviors measuring the approach to the fluid were not always accompanied by significant changes in fluid consumption, and vice versa, suggesting that it is important to assess both measures of motivation to consume alcohol. Conclusion Our results indicate that the direction of the effects of social environment on alcohol intake in mice depends on the non-social housing environment. Understanding mechanisms by which social and non-social housing conditions modulate alcohol intake could suggest approaches to counteract environmental factors enhancing hazardous alcohol consumption.
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Affiliation(s)
| | | | | | - Andrey E. Ryabinin
- Department of Behavioral Neuroscience, School of Medicine, Oregon Health and Science University, Portland, OR, United States
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Ardinger CE, Chen Y, Kimbrough A, Grahame NJ, Lapish CC. Sex Differences in Neural Networks Recruited by Frontloaded Binge Alcohol Drinking. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.08.579387. [PMID: 38370732 PMCID: PMC10871329 DOI: 10.1101/2024.02.08.579387] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/20/2024]
Abstract
Frontloading is an alcohol drinking pattern where intake is skewed toward the onset of access. The goal of the current study was to identify brain regions involved in frontloading. Whole brain imaging was performed in 63 C57Bl/6J (32 female and 31 male) mice that underwent 8 days of binge drinking using the drinking-in-the-dark (DID) model. On days 1-7, three hours into the dark cycle, mice received 20% (v/v) alcohol or water for two hours. Intake was measured in 1-minute bins using volumetric sippers, which facilitated analyses of drinking patterns. On day 8 mice were perfused 80 minutes into the DID session and brains were extracted. Brains were then processed to stain for Fos protein using iDISCO+. Following light sheet imaging, ClearMap2.1 was used to register brains to the Allen Brain Atlas and detect Fos+ cells. For brain network analyses, day 8 drinking patterns were used to characterize mice as frontloaders or non-frontloaders using a recently developed change-point analysis. Based on this analysis the groups were female frontloaders (n = 20), female non-frontloaders (n = 2), male frontloaders (n = 13) and male non-frontloaders (n = 8). There were no differences in total alcohol intake in animals that frontloaded versus those that did not. Only two female mice were characterized as non-frontloaders, thus preventing brain network analysis of this group. Functional correlation matrices were calculated for each group from log10 Fos values. Euclidean distances were calculated from these R values and hierarchical clustering was used to determine modules (highly connected groups of brain regions). In males, alcohol access decreased modularity (3 modules in both frontloaders and non-frontloaders) as compared to water drinkers (7 modules). In females, an opposite effect was observed. Alcohol access (9 modules for frontloaders) increased modularity as compared to water drinkers (5 modules). These results suggest sex differences in how alcohol consumption reorganizes the functional architecture of neural networks. Next, key brain regions in each network were identified. Connector hubs, which primarily facilitate communication between modules, and provincial hubs, which facilitate communication within modules, were of specific interest for their important and differing roles. In males, 4 connector hubs and 17 provincial hubs were uniquely identified in frontloaders (i.e., were brain regions that did not have this status in male non-frontloaders or water drinkers). These represented a group of hindbrain regions (e.g., locus coeruleus and the pontine gray) functionally connected to striatal/cortical regions (e.g., cortical amygdalar area) by the paraventricular nucleus of the thalamus. In females, 16 connector and 17 provincial hubs were uniquely identified which were distributed across 8 of the 9 modules in the female frontloader alcohol drinker network. Only one brain region (the nucleus raphe pontis) was a connector hub in both sexes, suggesting that frontloading in males and females may be driven by different brain regions. In conclusion, alcohol consumption led to fewer, but more densely connected, groups of brain regions in males but not females, and recruited different hub brain regions between the sexes. These results suggest that alcohol frontloading leads to a reduction in network efficiency in male mice.
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Affiliation(s)
- Cherish E Ardinger
- Addiction Neuroscience, Department of Psychology and Indiana Alcohol Research Center, Indiana University - Purdue University Indianapolis, Indianapolis, IN
| | - Yueyi Chen
- Department of Basic Medical Sciences, College of Veterinary Medicine, Purdue University, West Lafayette, IN
| | - Adam Kimbrough
- Department of Basic Medical Sciences, College of Veterinary Medicine, Purdue University, West Lafayette, IN
- Weldon School of Biomedical Engineering, College of Engineering, Purdue University, West Lafayette, IN
- Purdue Institute of Inflammation, Immunology, and Infectious Disease, Purdue University, West Lafayette, IN
| | - Nicholas J Grahame
- Addiction Neuroscience, Department of Psychology and Indiana Alcohol Research Center, Indiana University - Purdue University Indianapolis, Indianapolis, IN
| | - Christopher C Lapish
- Addiction Neuroscience, Department of Psychology and Indiana Alcohol Research Center, Indiana University - Purdue University Indianapolis, Indianapolis, IN
- Stark Neuroscience Research Institute, Indiana University - Purdue University Indianapolis, Indianapolis, IN
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Xie Y, Brynildsen JK, Windisch K, Blendy JA. Neural Network Connectivity Following Opioid Dependence is Altered by a Common Genetic Variant in the µ-Opioid Receptor, OPRM1 A118G. J Neurosci 2024; 44:e1492232023. [PMID: 38124015 PMCID: PMC10866092 DOI: 10.1523/jneurosci.1492-23.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Revised: 11/24/2023] [Accepted: 11/29/2023] [Indexed: 12/23/2023] Open
Abstract
Opioid use disorder is a chronic, relapsing disease associated with persistent changes in brain plasticity. A common single nucleotide polymorphism (SNP) in the µ-opioid receptor gene, OPRM1 A118G, is associated with altered vulnerability to opioid addiction. Reconfiguration of neuronal connectivity may explain dependence risk in individuals with this SNP. Mice with the equivalent Oprm1 variant, A112G, demonstrate sex-specific alterations in the rewarding properties of morphine and heroin. To determine whether this SNP influences network-level changes in neuronal activity, we compared FOS expression in male and female mice that were opioid-naive or opioid-dependent. Network analyses identified significant differences between the AA and GG Oprm1 genotypes. Based on several graph theory metrics, including small-world analysis and degree centrality, we show that GG females in the opioid-dependent state exhibit distinct patterns of connectivity compared to other groups of the same genotype. Using a network control theory approach, we identified key cortical brain regions that drive the transition between opioid-naive and opioid-dependent brain states; however, these regions are less influential in GG females leading to sixfold higher average minimum energy needed to transition from the acute to the dependent state. In addition, we found that the opioid-dependent brain state is significantly less stable in GG females compared to other groups. Collectively, our findings demonstrate sex- and genotype-specific modifications in local, mesoscale, and global properties of functional brain networks following opioid exposure and provide a framework for identifying genotype differences in specific brain regions that play a role in opioid dependence.
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Affiliation(s)
- Yihan Xie
- Department of Systems Pharmacology and Translational Therapeutics and Perelman School of Medicine, University of Pennsylvania, Philadelphia 19104, Pennsylvania
| | - Julia K Brynildsen
- Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia 19104, Pennsylvania
| | - Kyle Windisch
- Department of Systems Pharmacology and Translational Therapeutics and Perelman School of Medicine, University of Pennsylvania, Philadelphia 19104, Pennsylvania
| | - Julie A Blendy
- Department of Systems Pharmacology and Translational Therapeutics and Perelman School of Medicine, University of Pennsylvania, Philadelphia 19104, Pennsylvania
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Lipp HP, Krackow S, Turkes E, Benner S, Endo T, Russig H. IntelliCage: the development and perspectives of a mouse- and user-friendly automated behavioral test system. Front Behav Neurosci 2024; 17:1270538. [PMID: 38235003 PMCID: PMC10793385 DOI: 10.3389/fnbeh.2023.1270538] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Accepted: 10/18/2023] [Indexed: 01/19/2024] Open
Abstract
IntelliCage for mice is a rodent home-cage equipped with four corner structures harboring symmetrical double panels for operant conditioning at each of the two sides, either by reward (access to water) or by aversion (non-painful stimuli: air-puffs, LED lights). Corner visits, nose-pokes and actual licks at bottle-nipples are recorded individually using subcutaneously implanted transponders for RFID identification of up to 16 adult mice housed in the same home-cage. This allows for recording individual in-cage activity of mice and applying reward/punishment operant conditioning schemes in corners using workflows designed on a versatile graphic user interface. IntelliCage development had four roots: (i) dissatisfaction with standard approaches for analyzing mouse behavior, including standardization and reproducibility issues, (ii) response to handling and housing animal welfare issues, (iii) the increasing number of mouse models had produced a high work burden on classic manual behavioral phenotyping of single mice. and (iv), studies of transponder-chipped mice in outdoor settings revealed clear genetic behavioral differences in mouse models corresponding to those observed by classic testing in the laboratory. The latter observations were important for the development of home-cage testing in social groups, because they contradicted the traditional belief that animals must be tested under social isolation to prevent disturbance by other group members. The use of IntelliCages reduced indeed the amount of classic testing remarkably, while its flexibility was proved in a wide range of applications worldwide including transcontinental parallel testing. Essentially, two lines of testing emerged: sophisticated analysis of spontaneous behavior in the IntelliCage for screening of new genetic models, and hypothesis testing in many fields of behavioral neuroscience. Upcoming developments of the IntelliCage aim at improved stimulus presentation in the learning corners and videotracking of social interactions within the IntelliCage. Its main advantages are (i) that mice live in social context and are not stressfully handled for experiments, (ii) that studies are not restricted in time and can run in absence of humans, (iii) that it increases reproducibility of behavioral phenotyping worldwide, and (iv) that the industrial standardization of the cage permits retrospective data analysis with new statistical tools even after many years.
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Affiliation(s)
- Hans-Peter Lipp
- Faculty of Medicine, Institute of Evolutionary Medicine, University of Zürich, Zürich, Switzerland
| | - Sven Krackow
- Institute of Pathology and Molecular Pathology, University Hospital Zürich, Zürich, Switzerland
| | - Emir Turkes
- Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Seico Benner
- Center for Health and Environmental Risk Research, National Institute for Environmental Studies, Ibaraki, Japan
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Shah P, Kaneria A, Fleming G, Williams CRO, Sullivan RM, Lemon CH, Smiley J, Saito M, Wilson DA. Homeostatic NREM sleep and salience network function in adult mice exposed to ethanol during development. Front Neurosci 2023; 17:1267542. [PMID: 38033546 PMCID: PMC10682725 DOI: 10.3389/fnins.2023.1267542] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Accepted: 10/30/2023] [Indexed: 12/02/2023] Open
Abstract
Developmental exposure to ethanol is a leading cause of cognitive, emotional and behavioral problems, with fetal alcohol spectrum disorder (FASD) affecting more than 1:100 children. Recently, comorbid sleep deficits have been highlighted in these disorders, with sleep repair a potential therapeutic target. Animal models of FASD have shown non-REM (NREM) sleep fragmentation and slow-wave oscillation impairments that predict cognitive performance. Here we use a mouse model of perinatal ethanol exposure to explore whether reduced sleep pressure may contribute to impaired NREM sleep, and compare the function of a brain network reported to be impacted by insomnia-the Salience network-in developmental ethanol-exposed mice with sleep-deprived, saline controls. Mice were exposed to ethanol or saline on postnatal day 7 (P7) and allowed to mature to adulthood for testing. At P90, telemetered cortical recordings were made for assessment of NREM sleep in home cage before and after 4 h of sleep deprivation to assess basal NREM sleep and homeostatic NREM sleep response. To assess Salience network functional connectivity, mice were exposed to the 4 h sleep deprivation period or left alone, then immediately sacrificed for immunohistochemical analysis of c-Fos expression. The results show that developmental ethanol severely impairs both normal rebound NREM sleep and sleep deprivation induced increases in slow-wave activity, consistent with reduced sleep pressure. Furthermore, the Salience network connectome in rested, ethanol-exposed mice was most similar to that of sleep-deprived, saline control mice, suggesting a sleep deprivation-like state of Salience network function after developmental ethanol even without sleep deprivation.
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Affiliation(s)
- Prachi Shah
- Emotional Brain Institute, Nathan Kline Institute for Psychiatric Research, Orangeburg, NY,United States
| | - Aayush Kaneria
- Emotional Brain Institute, Nathan Kline Institute for Psychiatric Research, Orangeburg, NY,United States
| | - Gloria Fleming
- Emotional Brain Institute, Nathan Kline Institute for Psychiatric Research, Orangeburg, NY,United States
| | - Colin R. O. Williams
- Emotional Brain Institute, Nathan Kline Institute for Psychiatric Research, Orangeburg, NY,United States
| | - Regina M. Sullivan
- Emotional Brain Institute, Nathan Kline Institute for Psychiatric Research, Orangeburg, NY,United States
- School of Biological Sciences, University of Oklahoma, Norman, OK, United States
- Department of Child and Adolescent Psychiatry, NYU School of Medicine, New York, NY, United States
| | - Christian H. Lemon
- School of Biological Sciences, University of Oklahoma, Norman, OK, United States
| | - John Smiley
- Division of Neurochemistry, Nathan Kline Institute for Psychiatric Research, Orangeburg, NY,United States
- Department of Psychiatry, New York University Medical Center, New York, NY,United States
| | - Mariko Saito
- Division of Neurochemistry, Nathan Kline Institute for Psychiatric Research, Orangeburg, NY,United States
- Department of Psychiatry, New York University Medical Center, New York, NY,United States
| | - Donald A. Wilson
- Emotional Brain Institute, Nathan Kline Institute for Psychiatric Research, Orangeburg, NY,United States
- School of Biological Sciences, University of Oklahoma, Norman, OK, United States
- Department of Child and Adolescent Psychiatry, NYU School of Medicine, New York, NY, United States
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7
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Frycz BA, Nowicka K, Konopka A, Hoener MC, Bulska E, Kaczmarek L, Stefaniuk M. Activation of trace amine-associated receptor 1 (TAAR1) transiently reduces alcohol drinking in socially housed mice. Addict Biol 2023; 28:e13285. [PMID: 37369127 DOI: 10.1111/adb.13285] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Revised: 04/18/2023] [Accepted: 04/20/2023] [Indexed: 06/29/2023]
Abstract
Alcohol dependence is characterized by the abnormal release of dopamine in the brain reward-related areas. Trace amine-associated receptor 1 (TAAR1) is a G protein-coupled receptor that negatively regulates dopamine neurotransmission and thus is a promising target in the treatment of drug addiction. However, the role of TAAR1 in the regulation of alcohol abuse remains understudied. Here, we assessed the effect of TAAR1 activation on alcohol drinking behaviours of C57Bl/6J female mice housed in IntelliCages. The animals were administered with either vehicle or TAAR1 full selective agonist, RO5256390, and tested for alcohol consumption, alcohol preference and motivation for alcohol seeking. We found that mice with the highest preference for alcohol (high drinkers) in the RO5256390 group consumed less alcohol and had lower alcohol preference in comparison with high drinkers in the vehicle group, during 20 h of free alcohol access (FAA). We also found decreased alcohol consumption and alcohol preference comparing all animals in the RO5256390 to all animals in the vehicle group, during 20 h of FAA performed after the abstinence. These effects of RO5256390 lasted for the first 24 h after administration that roughly corresponded to the compound level in the brain, measured by mass spectrometry. Finally, we found that administration of RO5256390 may attenuate motivation for alcohol seeking. Taken together, our findings reveal that activation of TAAR1 may transiently reduce alcohol drinking; thus, TAAR1 is a promising target for the treatment of alcohol abuse and relapse.
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Affiliation(s)
- Bartosz Adam Frycz
- Laboratory of Neurobiology, BRAINCITY, Nencki Institute of Experimental Biology, Polish Academy of Sciences, Warsaw, Poland
- Laboratory of Cell Biophysics, Nencki Institute of Experimental Biology, Polish Academy of Sciences, Warsaw, Poland
| | - Klaudia Nowicka
- Laboratory of Neurobiology, BRAINCITY, Nencki Institute of Experimental Biology, Polish Academy of Sciences, Warsaw, Poland
| | - Anna Konopka
- Faculty of Chemistry, Biological, and Chemical Research Centre, University of Warsaw, Warsaw, Poland
| | - Marius Christian Hoener
- Neuroscience and Rare Diseases Discovery and Translational Area, pRED, Roche Innovation Center Basel, F. Hoffmann-La Roche, Basel, Switzerland
| | - Ewa Bulska
- Faculty of Chemistry, Biological, and Chemical Research Centre, University of Warsaw, Warsaw, Poland
| | - Leszek Kaczmarek
- Laboratory of Neurobiology, BRAINCITY, Nencki Institute of Experimental Biology, Polish Academy of Sciences, Warsaw, Poland
| | - Marzena Stefaniuk
- Laboratory of Neurobiology, BRAINCITY, Nencki Institute of Experimental Biology, Polish Academy of Sciences, Warsaw, Poland
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