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Rego M, Houston DW, Fan M, Murray KD, Trimmer JS. Open-source antibodies as a path to enhanced research reproducibility and transparency. N Biotechnol 2025; 87:121-129. [PMID: 40252918 DOI: 10.1016/j.nbt.2025.04.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2024] [Revised: 03/05/2025] [Accepted: 04/06/2025] [Indexed: 04/21/2025]
Abstract
Antibodies are important tools with diverse uses in biomedical research. However, open access to reliable sources of well-characterized antibodies with unambiguous molecular identities remains an obstacle to research transparency and reproducibility. We propose here a community shift towards open-source antibodies, analogous to open-source computer software. The tenets of such antibodies are that 1) they are available to researchers in a ready to use form, 2) the renewable source of the antibody (e.g., hybridoma cells or plasmid) is also widely available ensuring reproducible and cost-effective access to the same antibody, and 3) the antibody sequence is publicly available. With these criteria met, the antibody can be widely used with the transparent assurance associated with a molecularly defined reagent, and the code can be edited to generate antibody variants to meet researchers' specific needs. We (the UC Davis/NIH NeuroMab Facility, the Development Studies Hybridoma Bank, and Addgene) have established a consortium to provide open-source access to a large collection of well characterized antibodies. As open-source software has benefitted both users and developers, we suggest open-source antibodies will have a similar positive impact on antibody based biomedical research. We encourage funding agencies to support initiatives to expand access to open-source antibody resources, and researchers to both utilize and to contribute to them, with a goal of enabling more reliable and cost-effective pursuit of research.
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Affiliation(s)
| | - Douglas W Houston
- Developmental Studies Hybridoma Bank, Department of Biology, University of Iowa, Iowa City, IA, United States
| | | | - Karl D Murray
- UC Davis/NIH NeuroMab Facility, Department of Physiology and Membrane Biology, University of California School of Medicine, Davis, CA, United States
| | - James S Trimmer
- UC Davis/NIH NeuroMab Facility, Department of Physiology and Membrane Biology, University of California School of Medicine, Davis, CA, United States.
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2
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Le TT, Choi SH, Im GH, Lee C, Lee D, Schulman J, Cho H, Uludağ K, Kim S. Whole-brain BOLD responses to graded hypoxic challenges at 7 T, 9.4 T, and 15.2 T: Implications for ultrahigh-field functional and dynamic susceptibility contrast MRI. Magn Reson Med 2025; 94:262-277. [PMID: 39963739 PMCID: PMC12021331 DOI: 10.1002/mrm.30459] [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: 10/01/2024] [Revised: 01/15/2025] [Accepted: 01/17/2025] [Indexed: 04/26/2025]
Abstract
PURPOSE Blood oxygen-level dependent (BOLD) functional MRI signals depend on changes in deoxyhemoglobin content, which is associated with baseline cerebral blood volume (CBV) and blood oxygen saturation change. To accurately interpret activation-induced BOLD responses and quantify perfusion values by BOLD dynamic susceptibility contrast (BOLD-DSC) with transient hypoxia, it is critical to assess ΔR 2 * $$ {\mathrm{R}}_2^{\ast } $$ values in tissue and blood across varying levels of hypoxia and magnetic field strengths (B0). METHODS Whole-brain BOLD responses were examined using 5-s graded hypoxic challenges with 10%, 5%, and 0% O2 at ultrahigh field strengths of 7 T, 9.4 T, and 15.2 T. Both tissue and blood responses were analyzed for BOLD-DSC quantification. RESULTS Substantial heterogeneity in hypoxia-induced ΔR 2 * $$ {\mathrm{R}}_2^{\ast } $$ was observed among regions under different hypoxic doses and B0. Nonlinear ΔR 2 * $$ {\mathrm{R}}_2^{\ast } $$ responses with increasing field strength were observed, depending on hypoxic levels: 10% O2 condition exhibited pronounced supralinear trends, whereas 0% and 5% O2 conditions showed nearly linear dependencies. Blood arterial and venous∆ R 2 * $$ \Delta {\mathrm{R}}_2^{\ast } $$ responses showed a similar dependence as tissue. However, at 15.2 T, the venous signal saturated under 5% and 0% O2 conditions. Quantitative CBV values obtained from BOLD-DSC data showed dependency on susceptibility effects, and higher B0 and hypoxic severity resulted in slightly higher CBV, indicating that caution is needed when comparing quantitative CBV values derived from different experimental protocols. Normalizing regional CBV values to those of white matter effectively reduced the impact of varying susceptibility contrasts. CONCLUSIONS Our investigations provide biophysical insights into the BOLD contrast mechanism at ultrahigh fields, and address quantification issues in susceptibility-based CBV measurements.
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Affiliation(s)
- Thuy Thi Le
- Center for Neuroscience Imaging ResearchInstitute for Basic ScienceSuwonRepublic of Korea
- Department of Biomedical EngineeringSungkyunkwan UniversitySuwonRepublic of Korea
- Department of Intelligent Precision Healthcare ConvergenceSungkyunkwan UniversitySuwonRepublic of Korea
| | - Sang Han Choi
- Center for Neuroscience Imaging ResearchInstitute for Basic ScienceSuwonRepublic of Korea
| | - Geun Ho Im
- Center for Neuroscience Imaging ResearchInstitute for Basic ScienceSuwonRepublic of Korea
| | - Chanhee Lee
- Center for Neuroscience Imaging ResearchInstitute for Basic ScienceSuwonRepublic of Korea
| | - Dongkyu Lee
- Brain Tech CenterKorea Brain Research InstituteDaeguRepublic of Korea
- Department of Biomedical EngineeringUlsan National Institute of Science and TechnologyUlsanRepublic of Korea
| | - Jacob Schulman
- Department of Medical BiophysicsUniversity of TorontoTorontoOntarioCanada
- Krembil Brain InstituteUniversity Health NetworkTorontoOntarioCanada
| | - HyungJoon Cho
- Department of Biomedical EngineeringUlsan National Institute of Science and TechnologyUlsanRepublic of Korea
| | - Kamil Uludağ
- Center for Neuroscience Imaging ResearchInstitute for Basic ScienceSuwonRepublic of Korea
- Department of Biomedical EngineeringSungkyunkwan UniversitySuwonRepublic of Korea
- Department of Medical BiophysicsUniversity of TorontoTorontoOntarioCanada
- Krembil Brain InstituteUniversity Health NetworkTorontoOntarioCanada
- Physical SciencesSunnybrook Research InstituteTorontoOntarioCanada
| | - Seong‐Gi Kim
- Center for Neuroscience Imaging ResearchInstitute for Basic ScienceSuwonRepublic of Korea
- Department of Biomedical EngineeringSungkyunkwan UniversitySuwonRepublic of Korea
- Department of Intelligent Precision Healthcare ConvergenceSungkyunkwan UniversitySuwonRepublic of Korea
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3
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Payet JM, Baratta MV, Christianson JP, Lowry CA, Hale MW. Modulation of dorsal raphe nucleus connectivity and serotonergic signalling to the insular cortex in the prosocial effects of chronic fluoxetine. Neuropharmacology 2025; 272:110406. [PMID: 40081797 DOI: 10.1016/j.neuropharm.2025.110406] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2024] [Revised: 01/22/2025] [Accepted: 03/09/2025] [Indexed: 03/16/2025]
Abstract
Long-term exposure to fluoxetine and other selective serotonin reuptake inhibitors alters social and anxiety-related behaviours, including social withdrawal, which is a symptom of several neuropsychiatric disorders. Adaptive changes in serotonergic neurotransmission likely mediate this delayed effect, although the exact mechanisms are still unclear. Here we investigated the functional circuitry underlying the biphasic effects of fluoxetine on social approach-avoidance behaviour and explored the place of serotonergic dorsal raphe nucleus (DR) ensembles in this network, using c-Fos-immunoreactivity as a correlate of activity. Graph theory-based network analysis revealed changes in patterns of functional connectivity and identified neuronal populations in the insular cortex (IC) and serotonergic populations in the DR as central targets to the prosocial effects of chronic fluoxetine. To determine the role of serotonergic projections to the IC, a retrograde tracer was micro-injected in the IC prior to fluoxetine treatment and social behaviour testing. Chronic fluoxetine increased c-Fos immunoreactivity in insula-projecting neurons of the rostral, ventral part of the DR (DRV). Using a virally delivered Tet-Off platform for temporally-controlled marking of neuronal activation, we observed that chronic fluoxetine may affect social behaviour by influencing independent but interconnected populations of serotonergic DR ensembles. These findings suggest that sustained fluoxetine exposure causes adaptive changes in functional connectivity due to altered serotonergic neurotransmission in DR projection targets, and the increased serotonergic signalling to the IC likely mediates some of the therapeutic effects of fluoxetine on social behaviour.
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Affiliation(s)
- Jennyfer M Payet
- School of Psychology and Public Health, La Trobe University, Melbourne, VIC, 3086, Australia
| | - Michael V Baratta
- Department of Psychology and Neuroscience, Center for Neuroscience, University of Colorado Boulder, Boulder, CO 80301, USA
| | - John P Christianson
- Department of Psychology and Neuroscience, Boston College, Chestnut Hill, MA, 02467, USA
| | - Christopher A Lowry
- Department of Integrative Physiology, Center for Neuroscience, and Center for Microbial Exploration, University of Colorado Boulder, Boulder, CO 80309, USA
| | - Matthew W Hale
- School of Psychology and Public Health, La Trobe University, Melbourne, VIC, 3086, Australia.
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4
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Fulton SL, Bendl J, Di Salvo G, Fullard JF, Al-Kachak A, Lepack AE, Stewart AF, Singh S, Poller WF, Bastle RM, Hauberg ME, Fakira AK, Patel V, Chen M, Durand-de Cuttoli R, Gameiro-Ros I, Cathomas F, Ramakrishnan A, Gleason K, Shen L, Tamminga CA, Milosevic A, Russo SJ, Swirski FK, Slesinger PA, Abdus-Saboor I, Blitzer RD, Roussos P, Maze I. Major-depressive-disorder-associated dysregulation of ZBTB7A in orbitofrontal cortex promotes astrocyte-mediated stress susceptibility. Neuron 2025:S0896-6273(25)00394-0. [PMID: 40516534 DOI: 10.1016/j.neuron.2025.05.023] [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: 05/11/2023] [Revised: 03/25/2025] [Accepted: 05/20/2025] [Indexed: 06/16/2025]
Abstract
Heightened activity in the orbitofrontal cortex (OFC), a brain region that contributes to motivation, emotion, and reward-related decision-making, is a key clinical feature of major depressive disorder (MDD). However, the cellular and molecular substrates underlying this dysfunction remain unclear. Here, we performed cell-type-specific profiling of human OFC and unexpectedly mapped MDD-linked epigenomic features (including genetic risk variants) to non-neuronal cells, revealing significant glial dysregulation in this region. Characterization of MDD-specific chromatin loci further identified ZBTB7A-a transcriptional regulator of astrocyte reactivity-as an important mediator of MDD-related alterations. In rodent models, we found that Zbtb7a induction in astrocytes is both necessary and sufficient to drive stress-mediated behavioral deficits, cell-type-specific transcriptional/epigenomic signatures, and aberrant OFC astrocyte-neuronal communication in male mice-an established MDD risk factor. These findings thus highlight essential roles for astrocytes in OFC-mediated stress susceptibility and identify ZBTB7A as a critical and therapeutically relevant regulator of MDD-related OFC dysfunction.
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Affiliation(s)
- Sasha L Fulton
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Zuckerman Institute of Mind, Brain, and Behavior, Columbia University, New York, NY, USA
| | - Jaroslav Bendl
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Giuseppina Di Salvo
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - John F Fullard
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Amni Al-Kachak
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ashley E Lepack
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Andrew F Stewart
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Sumnima Singh
- Department of Cardiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Cardiovascular Research Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Wolfram F Poller
- Department of Cardiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Cardiovascular Research Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ryan M Bastle
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Mads E Hauberg
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Amanda K Fakira
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Vishwendra Patel
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Min Chen
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Romain Durand-de Cuttoli
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Isabel Gameiro-Ros
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Flurin Cathomas
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Aarthi Ramakrishnan
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Kelly Gleason
- Department of Psychiatry, UT Southwestern Medical Center, Dallas, TX, USA
| | - Li Shen
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Carol A Tamminga
- Department of Psychiatry, UT Southwestern Medical Center, Dallas, TX, USA
| | - Ana Milosevic
- Laboratory of Developmental Genetics, Rockefeller University, New York, NY, USA
| | - Scott J Russo
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Filip K Swirski
- Department of Cardiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Cardiovascular Research Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Paul A Slesinger
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ishmail Abdus-Saboor
- Zuckerman Institute of Mind, Brain, and Behavior, Columbia University, New York, NY, USA
| | - Robert D Blitzer
- Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Panos Roussos
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Center for Precision Medicine and Translational Therapeutics, James J. Peters VA Medical Center, Bronx, New York, NY, USA; Mental Illness Research Education and Clinical Center, James J. Peters VA Medical Center, Bronx, New York, NY, USA
| | - Ian Maze
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Howard Hughes Medical Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
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5
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Sznajder ŁJ, Khan M, Ciesiołka A, Tadross M, Nutter CA, Taylor K, Pearson CE, Lewis MH, Hines RM, Swanson MS, Sobczak K, Yuen RKC. Autism-related traits in myotonic dystrophy type 1 model mice are due to MBNL sequestration and RNA mis-splicing of autism-risk genes. Nat Neurosci 2025; 28:1199-1212. [PMID: 40259070 DOI: 10.1038/s41593-025-01943-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Accepted: 03/14/2025] [Indexed: 04/23/2025]
Abstract
Genome-wide enrichment of gene-specific tandem repeat expansions has been linked to autism spectrum disorder. One such mutation is the CTG tandem repeat expansion in the 3' untranslated region of the DMPK gene, which is known to cause myotonic muscular dystrophy type 1. Although there is a clear clinical association between autism and myotonic dystrophy, the molecular basis for this connection remains unknown. Here, we report that sequestration of MBNL splicing factors by mutant DMPK RNAs with expanded CUG repeats alters the RNA splicing patterns of autism-risk genes during brain development, particularly a class of autism-relevant microexons. We demonstrate that both DMPK-CTG expansion and Mbnl null mouse models recapitulate autism-relevant mis-splicing profiles, along with social behavioral deficits and altered responses to novelty. These findings support our model that myotonic dystrophy-associated autism arises from developmental mis-splicing of autism-risk genes.
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Affiliation(s)
- Łukasz J Sznajder
- Department of Chemistry and Biochemistry, University of Nevada, Las Vegas, NV, USA.
- Department of Molecular Genetics and Microbiology, Center for NeuroGenetics and the Genetics Institute, University of Florida, College of Medicine, Gainesville, FL, USA.
| | - Mahreen Khan
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
- Genetics and Genome Biology, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Adam Ciesiołka
- Department of Gene Expression, Institute of Molecular Biology and Biotechnology, Adam Mickiewicz University, Poznań, Poland
| | - Mariam Tadross
- Department of Molecular Genetics and Microbiology, Center for NeuroGenetics and the Genetics Institute, University of Florida, College of Medicine, Gainesville, FL, USA
- Department of Psychiatry, McKnight Brain Institute, University of Florida, College of Medicine, Gainesville, FL, USA
| | - Curtis A Nutter
- Department of Molecular Genetics and Microbiology, Center for NeuroGenetics and the Genetics Institute, University of Florida, College of Medicine, Gainesville, FL, USA
| | - Katarzyna Taylor
- Department of Gene Expression, Institute of Molecular Biology and Biotechnology, Adam Mickiewicz University, Poznań, Poland
| | - Christopher E Pearson
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
- Genetics and Genome Biology, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Mark H Lewis
- Department of Psychiatry, McKnight Brain Institute, University of Florida, College of Medicine, Gainesville, FL, USA
| | - Rochelle M Hines
- Department of Psychology, University of Nevada, Las Vegas, NV, USA
| | - Maurice S Swanson
- Department of Molecular Genetics and Microbiology, Center for NeuroGenetics and the Genetics Institute, University of Florida, College of Medicine, Gainesville, FL, USA
| | - Krzysztof Sobczak
- Department of Gene Expression, Institute of Molecular Biology and Biotechnology, Adam Mickiewicz University, Poznań, Poland
| | - Ryan K C Yuen
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
- Genetics and Genome Biology, The Hospital for Sick Children, Toronto, Ontario, Canada
- Centre for Applied Genomics, The Hospital for Sick Children, Toronto, Ontario, Canada
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6
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Junaid M, Lee EJ, Lim SB. Single-cell and spatial omics: exploring hypothalamic heterogeneity. Neural Regen Res 2025; 20:1525-1540. [PMID: 38993130 PMCID: PMC11688568 DOI: 10.4103/nrr.nrr-d-24-00231] [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: 02/26/2024] [Revised: 05/06/2024] [Accepted: 06/03/2024] [Indexed: 07/13/2024] Open
Abstract
Elucidating the complex dynamic cellular organization in the hypothalamus is critical for understanding its role in coordinating fundamental body functions. Over the past decade, single-cell and spatial omics technologies have significantly evolved, overcoming initial technical challenges in capturing and analyzing individual cells. These high-throughput omics technologies now offer a remarkable opportunity to comprehend the complex spatiotemporal patterns of transcriptional diversity and cell-type characteristics across the entire hypothalamus. Current single-cell and single-nucleus RNA sequencing methods comprehensively quantify gene expression by exploring distinct phenotypes across various subregions of the hypothalamus. However, single-cell/single-nucleus RNA sequencing requires isolating the cell/nuclei from the tissue, potentially resulting in the loss of spatial information concerning neuronal networks. Spatial transcriptomics methods, by bypassing the cell dissociation, can elucidate the intricate spatial organization of neural networks through their imaging and sequencing technologies. In this review, we highlight the applicative value of single-cell and spatial transcriptomics in exploring the complex molecular-genetic diversity of hypothalamic cell types, driven by recent high-throughput achievements.
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Affiliation(s)
- Muhammad Junaid
- Department of Biochemistry & Molecular Biology, Ajou University School of Medicine, Suwon, South Korea
- Department of Biomedical Sciences, Graduate School of Ajou University, Suwon, South Korea
| | - Eun Jeong Lee
- Department of Biomedical Sciences, Graduate School of Ajou University, Suwon, South Korea
- Department of Brain Science, Ajou University School of Medicine, Suwon, South Korea
| | - Su Bin Lim
- Department of Biochemistry & Molecular Biology, Ajou University School of Medicine, Suwon, South Korea
- Department of Biomedical Sciences, Graduate School of Ajou University, Suwon, South Korea
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7
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Ben-Simon Y, Hooper M, Narayan S, Daigle TL, Dwivedi D, Way SW, Oster A, Stafford DA, Mich JK, Taormina MJ, Martinez RA, Opitz-Araya X, Roth JR, Alexander JR, Allen S, Amster A, Arbuckle J, Ayala A, Baker PM, Bakken TE, Barcelli T, Barta S, Bendrick J, Bertagnolli D, Bielstein C, Bishwakarma P, Bowlus J, Boyer G, Brouner K, Casian B, Casper T, Chakka AB, Chakrabarty R, Chance RK, Chavan S, Clark M, Colbert K, Collman F, Daniel S, Departee M, DiValentin P, Donadio N, Dotson N, Egdorf T, Fliss T, Gabitto M, Garcia J, Gary A, Gasperini M, Gloe J, Goldy J, Gore BB, Graybuck L, Greisman N, Haeseleer F, Halterman C, Haradon Z, Hastings SD, Helback O, Ho W, Hockemeyer D, Huang C, Huff S, Hunker A, Johansen N, Jones D, Juneau Z, Kalmbach B, Kannan M, Khem S, Kussick E, Kutsal R, Larsen R, Lee C, Lee AY, Leibly M, Lenz GH, Li S, Liang E, Lusk N, Madigan Z, Malloy J, Malone J, McCue R, Melchor J, Mollenkopf T, Moosman S, Morin E, Newman D, Ng L, Ngo K, Omstead V, Otto S, Oyama A, Pena N, Pham T, Phillips E, Pom CA, Potekhina L, Ransford S, et alBen-Simon Y, Hooper M, Narayan S, Daigle TL, Dwivedi D, Way SW, Oster A, Stafford DA, Mich JK, Taormina MJ, Martinez RA, Opitz-Araya X, Roth JR, Alexander JR, Allen S, Amster A, Arbuckle J, Ayala A, Baker PM, Bakken TE, Barcelli T, Barta S, Bendrick J, Bertagnolli D, Bielstein C, Bishwakarma P, Bowlus J, Boyer G, Brouner K, Casian B, Casper T, Chakka AB, Chakrabarty R, Chance RK, Chavan S, Clark M, Colbert K, Collman F, Daniel S, Departee M, DiValentin P, Donadio N, Dotson N, Egdorf T, Fliss T, Gabitto M, Garcia J, Gary A, Gasperini M, Gloe J, Goldy J, Gore BB, Graybuck L, Greisman N, Haeseleer F, Halterman C, Haradon Z, Hastings SD, Helback O, Ho W, Hockemeyer D, Huang C, Huff S, Hunker A, Johansen N, Jones D, Juneau Z, Kalmbach B, Kannan M, Khem S, Kussick E, Kutsal R, Larsen R, Lee C, Lee AY, Leibly M, Lenz GH, Li S, Liang E, Lusk N, Madigan Z, Malloy J, Malone J, McCue R, Melchor J, Mollenkopf T, Moosman S, Morin E, Newman D, Ng L, Ngo K, Omstead V, Otto S, Oyama A, Pena N, Pham T, Phillips E, Pom CA, Potekhina L, Ransford S, Ray PL, Rette D, Reynoldson C, Rimorin C, Rocha D, Ruiz A, Sanchez REA, Sawyer L, Sedeno-Cortes A, Sevigny JP, Shapovalova N, Shepard N, Shulga L, Sigler AR, Siverts L, Soliman S, Somasundaram S, Staats B, Stewart K, Szelenyi E, Tieu M, Trader C, Tran A, van Velthoven CTJ, Walker M, Wang Y, Weed N, Wirthlin M, Wood T, Wynalda B, Yao Z, Zhou T, Ariza J, Dee N, Reding M, Ronellenfitch K, Mufti S, Sunkin SM, Smith KA, Esposito L, Waters J, Thyagarajan B, Yao S, Lein ES, Zeng H, Levi BP, Ngai J, Ting JT, Tasic B. A suite of enhancer AAVs and transgenic mouse lines for genetic access to cortical cell types. Cell 2025; 188:3045-3064.e23. [PMID: 40403729 DOI: 10.1016/j.cell.2025.05.002] [Show More Authors] [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: 09/25/2024] [Revised: 03/25/2025] [Accepted: 05/01/2025] [Indexed: 05/24/2025]
Abstract
The mammalian cortex is comprised of cells classified into types according to shared properties. Defining the contribution of each cell type to the processes guided by the cortex is essential for understanding its function in health and disease. We use transcriptomic and epigenomic cortical cell-type taxonomies from mouse and human to define marker genes and putative enhancers and create a large toolkit of transgenic lines and enhancer adeno-associated viruses (AAVs) for selective targeting of cortical cell populations. We report creation and evaluation of fifteen transgenic driver lines, two reporter lines, and >1,000 different enhancer AAV vectors covering most subclasses of cortical cells. The tools reported here have been made publicly available, and along with the scaled process of tool creation, evaluation, and modification, they will enable diverse experimental strategies toward understanding mammalian cortex and brain function.
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Affiliation(s)
- Yoav Ben-Simon
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Marcus Hooper
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | | | - Tanya L Daigle
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | | | - Sharon W Way
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Aaron Oster
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | | | - John K Mich
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | | | | | | | - Jada R Roth
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | | | - Shona Allen
- University of California, Berkeley, Berkeley, CA 94720, USA
| | - Adam Amster
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Joel Arbuckle
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Angela Ayala
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Pamela M Baker
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | | | - Tyler Barcelli
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Stuard Barta
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | | | | | | | | | - Jessica Bowlus
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | | | - Krissy Brouner
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Brittny Casian
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Tamara Casper
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Anish B Chakka
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | | | | | - Sakshi Chavan
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Michael Clark
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Kaity Colbert
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | | | - Scott Daniel
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | | | | | | | | | - Tom Egdorf
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Tim Fliss
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | | | - Jazmin Garcia
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Amanda Gary
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | | | - Jessica Gloe
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Jeff Goldy
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Bryan B Gore
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Lucas Graybuck
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Noah Greisman
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | | | | | - Zeb Haradon
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | | | - Olivia Helback
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Windy Ho
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | | | - Cindy Huang
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Sydney Huff
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Avery Hunker
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | | | - Danielle Jones
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Zoe Juneau
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Brian Kalmbach
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Madhav Kannan
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Shannon Khem
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Emily Kussick
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Rana Kutsal
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Rachael Larsen
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Changkyu Lee
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Angus Y Lee
- University of California, Berkeley, Berkeley, CA 94720, USA
| | - Madison Leibly
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Garreck H Lenz
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Su Li
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | | | - Nicholas Lusk
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | | | - Jessica Malloy
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Jocelin Malone
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Rachel McCue
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Jose Melchor
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | | | - Skyler Moosman
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Elyse Morin
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Dakota Newman
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Lydia Ng
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Kiet Ngo
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | | | - Sven Otto
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Alana Oyama
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Nick Pena
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | | | | | | | | | - Shea Ransford
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Patrick L Ray
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Dean Rette
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | | | | | - Dana Rocha
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Augustin Ruiz
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | | | - Lane Sawyer
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | | | | | | | - Noah Shepard
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | | | - Ana R Sigler
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | | | - Sherif Soliman
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | | | - Brian Staats
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Kaiya Stewart
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Eric Szelenyi
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Michael Tieu
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Cameron Trader
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Alex Tran
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | | | - Miranda Walker
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Yimin Wang
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Natalie Weed
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | | | - Toren Wood
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Brooke Wynalda
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Zizhen Yao
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Thomas Zhou
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Jeanelle Ariza
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Nick Dee
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Melissa Reding
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | | | - Shoaib Mufti
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Susan M Sunkin
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | | | - Luke Esposito
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Jack Waters
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | | | - Shenqin Yao
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Ed S Lein
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Hongkui Zeng
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Boaz P Levi
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - John Ngai
- University of California, Berkeley, Berkeley, CA 94720, USA
| | | | - Bosiljka Tasic
- Allen Institute for Brain Science, Seattle, WA 98109, USA.
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8
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Karolczak EO, Li C, Alcantara IC, Cohen IM, Gao C, Xiao C, Goldschmidt AI, Pinkus CA, Li J, Li MM, Esquejo RM, Fortin JP, Bence KK, Reitman ML, Krashes MJ. Uncovering the role of Gpr45 in obesity regulation. Mol Metab 2025; 98:102174. [PMID: 40449730 DOI: 10.1016/j.molmet.2025.102174] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/25/2025] [Revised: 05/12/2025] [Accepted: 05/23/2025] [Indexed: 06/03/2025] Open
Abstract
OBJECTIVES G protein-coupled receptors (GPCRs) are the most druggable targets in biology due to their cell-type specificity, ligand binding, and cell surface accessibility. Underscoring this, agonists for GPCRs have recently revolutionized the treatment of diabetes and obesity. The rampant success of these compounds has invigorated interest in identifying additional GPCRs that modulate appetite and body weight homeostasis. One such potential therapeutic target is G-protein couped receptor 45 (Gpr45), an orphan GPCR expressed both centrally and peripherally. We aimed to explore the role of Gpr45 as well as neurons expressing Gpr45 in energy balance. METHODS Three novel transgenic mouse models were engineered to investigate the functional contribution of Gpr45 to body weight and appetite regulation: 1) a global Gpr45 knockout, 2) a conditional floxed Gpr45 allele, and 3) a Gpr45-CreERT2 knock-in. Metabolic profiling was performed in global Gpr45 knockout animals including body weight, food intake, body mass, energy expenditure, and body temperature measurements. Animals harboring a conditional floxed Gpr45 allele were bred to mice expressing Cre-recombinase in excitatory neurons labeled via Vesicular glutamate transporter 2 (Vglut2), inhibitory cells expressing Vesicular GABA transporter (Vgat), or neurons marked by the transcription factor Single-minded 1 (Sim1) and monitored for body weight and food consumption. Additionally, floxed Gpr45 mice were bilaterally injected with AAV-Cre targeting the paraventricular nucleus of the hypothalamus (PVH) and body weight and food intake were evaluated. The Gpr45-CreERT2 knock-in model was used to express chronic and acute actuators to the PVH to assess the role of PVHGpr45 neurons in energy homeostasis. RESULTS Global Gpr45 disruption caused marked weight gain, increased food intake and fat mass, but no detectable alterations in core temperature or energy output. Selective deletion of Gpr45 from Sim1+ or excitatory Vglut2+ but not inhibitory Vgat+, neurons produced obesity and hyperphagia. Targeted deletion of Gpr45 from the PVH phenocopies these metabolic changes suggesting a major site of action of Gpr45 signaling is glutamatergic neurons residing in the PVH. Tetanus toxin light chain (TeNT) was used to permanently silence PVHGpr45 neuronal activity in Gpr45-CreER mice leading to rapid weight accumulation and escalated food intake. These experiments highlight the critical role of both Gpr45 signaling and neural network activity in the regulation of body weight and appetite. A mutated version of the bacterial sodium channel, NaChBac, was used to constitutively activate PVHGpr45 neuronal activity in Gpr45-CreER mice with limited to no effect on body weight and food consumption, implicating redundant circuitry acting in concert to bias weight loss protection. Acute chemogenetic stimulation of PVHGpr45 neurons durably suppressed food intake regardless of caloric need state or food palatability demonstrating the capacity of these cells to curb appetite. CONCLUSIONS Gpr45 is a putative therapeutic candidate that could be targeted to combat obesity and overeating.
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Affiliation(s)
- Eva O Karolczak
- Diabetes, Endocrinology, and Obesity Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Chia Li
- Diabetes, Endocrinology, and Obesity Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Ivan C Alcantara
- Diabetes, Endocrinology, and Obesity Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, USA; NIH-Brown University Graduate Program in Neuroscience, Bethesda, MD, USA
| | - Isabel M Cohen
- Diabetes, Endocrinology, and Obesity Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Claire Gao
- Diabetes, Endocrinology, and Obesity Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Cuiying Xiao
- Diabetes, Endocrinology, and Obesity Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Abigail I Goldschmidt
- Diabetes, Endocrinology, and Obesity Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, USA
| | | | - Junjie Li
- Internal Medicine Research Unit, Pfizer Inc., Cambridge MA, USA
| | - Monica M Li
- Internal Medicine Research Unit, Pfizer Inc., Cambridge MA, USA
| | - Ryan M Esquejo
- Internal Medicine Research Unit, Pfizer Inc., Cambridge MA, USA
| | | | - Kendra K Bence
- Internal Medicine Research Unit, Pfizer Inc., Cambridge MA, USA
| | - Marc L Reitman
- Diabetes, Endocrinology, and Obesity Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Michael J Krashes
- Diabetes, Endocrinology, and Obesity Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, USA.
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9
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Li Y, Torok J, Zhang S, Ding J, Wang N, Lau C, Kulkarni S, Anand C, Tran J, Cheng M, Lo C, Lu B, Sun Y, Damoiseaux R, Yang X, Raj A, Peng C. Key Connectomes and Synaptic-Compartment-Specific Risk Genes Drive Pathological α-Synuclein Spreading. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2025:e2413052. [PMID: 40433888 DOI: 10.1002/advs.202413052] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/16/2024] [Revised: 04/03/2025] [Indexed: 05/29/2025]
Abstract
Previous studies have suggested that pathological α-synuclein (α-Syn) mainly transmits along the neuronal network, but several key questions remain unanswered: 1) How many and which connections in the connectome are necessary for predicting the progression of pathological α-Syn? 2) How to identify risk genes that affect pathology spreading functioning at presynaptic or postsynaptic regions, and are these genes enriched in different cell types? Here, these questions are addressed with novel mathematical models. Strikingly, the spreading of pathological α-Syn is predominantly determined by the key subnetworks composed of only 2% of the strongest connections in the connectome. Genes associated with the selective vulnerability of brain regions to pathological α-Syn transmission are further analyzed to distinguish those functioning at presynaptic versus postsynaptic regions. Those risk genes are significantly enriched in microglial cells of presynaptic regions and neurons of postsynaptic regions. Gene regulatory network analyses are then conducted to identify "key drivers" of genes responsible for selective vulnerability and overlapping with Parkinson's disease risk genes. By identifying and discriminating between key gene mediators of transmission operating at presynaptic and postsynaptic regions, this study has demonstrated for the first time that these are functionally distinct processes.
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Affiliation(s)
- Yuanxi Li
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Institute for Cognitive Neurodynamics, East China University of Science and Technology, Shanghai, 200237, China
- School of Mathematics, East China University of Science and Technology, Shanghai, 200237, China
| | - Justin Torok
- Department of Radiology, University of California, San Francisco, San Francisco, CA, 94117, USA
| | - Shujing Zhang
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Jessica Ding
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Interdepartmental Program of Molecular, Cellular and Integrative Physiology, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Ning Wang
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Courtney Lau
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Shruti Kulkarni
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Chaitali Anand
- Department of Radiology, University of California, San Francisco, San Francisco, CA, 94117, USA
| | - Julie Tran
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Michael Cheng
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Claire Lo
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Binbin Lu
- Smith College, Northampton, MA, 01063, USA
| | - Yanzi Sun
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Robert Damoiseaux
- Molecular Screening Shared Resource (MSSR), California NanoSystems Institute, University of California, Los Angeles, CA, 90095, USA
| | - Xia Yang
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Interdepartmental Program of Molecular, Cellular and Integrative Physiology, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Institute for Quantitative and Computational Biosciences, University of California, Los Angeles, CA, 90095, USA
- Molecular Biology Institute, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Brain Research Institute, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Ashish Raj
- Department of Radiology, University of California, San Francisco, San Francisco, CA, 94117, USA
| | - Chao Peng
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Molecular Biology Institute, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Brain Research Institute, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Mary S. Easton Center for Alzheimer's Research, University of California, Los Angeles, Los Angeles, CA, 90095, USA
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10
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Guyoton M, Matteucci G, Foucher CG, Getz MP, Gjorgjieva J, El-Boustani S. Cortical circuits for cross-modal generalization. Nat Commun 2025; 16:4230. [PMID: 40419471 DOI: 10.1038/s41467-025-59342-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2024] [Accepted: 04/18/2025] [Indexed: 05/28/2025] Open
Abstract
Adapting goal-directed behaviors to changing sensory conditions is a fundamental aspect of intelligence. The brain uses abstract representations of the environment to generalize learned associations across sensory modalities. The circuit organization that mediates such cross-modal generalizations remains, however, unknown. Here, we demonstrate that mice can bidirectionally generalize sensorimotor task rules between touch and vision by using abstract representations of peri-personal space within the cortex. Using large-scale mapping in the dorsal cortex at single-cell resolution, we discovered multimodal neurons with congruent spatial representations within multiple associative areas of the dorsal and ventral streams. Optogenetic sensory substitution and systematic silencing of these associative areas revealed that a single area in the dorsal stream is necessary and sufficient for cross-modal generalization. Our results identify and comprehensively describe a cortical circuit organization that underlies an essential cognitive function, providing a structural and functional basis for abstract reasoning in the mammalian brain.
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Affiliation(s)
- Maëlle Guyoton
- Department of Basic Neurosciences, Faculty of Medicine, University of Geneva, 1 Rue Michel-Servet, 1206, Geneva, Switzerland
| | - Giulio Matteucci
- Department of Basic Neurosciences, Faculty of Medicine, University of Geneva, 1 Rue Michel-Servet, 1206, Geneva, Switzerland
| | - Charlie G Foucher
- Department of Basic Neurosciences, Faculty of Medicine, University of Geneva, 1 Rue Michel-Servet, 1206, Geneva, Switzerland
| | - Matthew P Getz
- School of Life Sciences, Technical University of Munich, Maximus-von-Imhof-Forum 3, 85354, Freising, Germany
| | - Julijana Gjorgjieva
- School of Life Sciences, Technical University of Munich, Maximus-von-Imhof-Forum 3, 85354, Freising, Germany
| | - Sami El-Boustani
- Department of Basic Neurosciences, Faculty of Medicine, University of Geneva, 1 Rue Michel-Servet, 1206, Geneva, Switzerland.
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11
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Zhu Z, Jiang T, Jia X, Wang X, Ren M. Whole-brain long-range connectivity of glutamatergic, GABAergic, parvalbumin-expressing and somatostatin-expressing neurons in mouse somatosensory cortex. Neurosci Res 2025; 217:104912. [PMID: 40436113 DOI: 10.1016/j.neures.2025.104912] [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: 02/09/2025] [Revised: 05/17/2025] [Accepted: 05/23/2025] [Indexed: 06/02/2025]
Abstract
Understanding the composition of cortical circuits at the whole-brain scale is crucial. However, the specific ways in which particular neuronal types in the primary somatosensory cortex (SSp) establish connections with upstream and downstream brain regions remain unclear. In this study, we used whole-brain imaging technology with submicron resolution to systematically reveal the long-range connectivity patterns of glutamatergic, GABAergic, parvalbumin-expressing (PV+), and somatostatin-expressing (SOM+) neurons in the SSp. Our results show that while glutamatergic, GABAergic, PV+ , and SOM+ neurons receive similar upstream afferent, specific thalamic subregions showed numerically stronger afferent to GABAergic, PV+ , and SOM+ neurons compared to glutamatergic neurons. Additionally, glutamatergic neurons exhibit a more complex collateral projection pattern in subcortical axonal pathways compared to PV+ neurons. These findings elucidate the long-range connectivity patterns of specific neuronal types in the SSp, offering new insights into the cell-type-specific mechanisms of sensory information processing.
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Affiliation(s)
- Zhaoxin Zhu
- State Key Laboratory of Digital Medical Engineering, Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, Sanya, Hainan, 572025, China
| | - Tao Jiang
- HUST-Suzhou Institute for Brainsmatics, JITRI, Suzhou 215125, China
| | - Xueyan Jia
- HUST-Suzhou Institute for Brainsmatics, JITRI, Suzhou 215125, China
| | - Xiaojun Wang
- State Key Laboratory of Digital Medical Engineering, Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, Sanya, Hainan, 572025, China
| | - Miao Ren
- State Key Laboratory of Digital Medical Engineering, Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, Sanya, Hainan, 572025, China.
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12
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Martín-Pérez A, Villa M, Rosa Olmeda G, Sancho J, Vazquez G, Urbanos G, Martinez de Ternero A, Chavarrías M, Jimenez-Roldan L, Perez-Nuñez A, Lagares A, Juarez E, Sanz C. SLIMBRAIN database: A multimodal image database of in vivo human brains for tumour detection. Sci Data 2025; 12:836. [PMID: 40399336 PMCID: PMC12095585 DOI: 10.1038/s41597-025-04993-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2024] [Accepted: 04/11/2025] [Indexed: 05/23/2025] Open
Abstract
Hyperspectral imaging (HSI) and machine learning (ML) have been employed in the medical field for classifying highly infiltrative brain tumours. Although existing HSI databases of in vivo human brains are available, they present two main deficiencies. First, the amount of labelled data are scarce, and second, 3D-tissue information is unavailable. To address both issues, we present the SLIMBRAIN database, a multimodal image database of in vivo human brains that provides HS brain tissue data within the 400-1000 nm spectra, as well as RGB, depth and multiview images. Two HS cameras, two depth cameras and different RGB sensors were used to capture images and videos from 193 patients. All the data in the SLIMBRAIN database can be used in a variety of ways, for example, to train ML models with more than 1 million HS pixels available and labelled by neurosurgeons, to reconstruct 3D scenes or to visualize RGB brain images with different pathologies, offering unprecedented flexibility for both the medical and engineering communities.
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Affiliation(s)
- Alberto Martín-Pérez
- Research Center on Software Technologies and Multimedia Systems, Universidad Politécnica de Madrid (UPM), Madrid, 28031, Spain.
| | - Manuel Villa
- Research Center on Software Technologies and Multimedia Systems, Universidad Politécnica de Madrid (UPM), Madrid, 28031, Spain
| | - Gonzalo Rosa Olmeda
- Research Center on Software Technologies and Multimedia Systems, Universidad Politécnica de Madrid (UPM), Madrid, 28031, Spain
| | - Jaime Sancho
- Research Center on Software Technologies and Multimedia Systems, Universidad Politécnica de Madrid (UPM), Madrid, 28031, Spain
| | - Guillermo Vazquez
- Research Center on Software Technologies and Multimedia Systems, Universidad Politécnica de Madrid (UPM), Madrid, 28031, Spain
| | - Gemma Urbanos
- Research Center on Software Technologies and Multimedia Systems, Universidad Politécnica de Madrid (UPM), Madrid, 28031, Spain
- Neurosurgery Department, Hospital Universitario 12 de Octubre, Medicine Faculty, Universidad Complutense de Madrid (UCM), Instituto de Investigación Sanitaria Hospital 12 de Octubre (imas12), Madrid, 28041, Spain
| | - Alejandro Martinez de Ternero
- Research Center on Software Technologies and Multimedia Systems, Universidad Politécnica de Madrid (UPM), Madrid, 28031, Spain
| | - Miguel Chavarrías
- Research Center on Software Technologies and Multimedia Systems, Universidad Politécnica de Madrid (UPM), Madrid, 28031, Spain
| | - Luis Jimenez-Roldan
- Neurosurgery Department, Hospital Universitario 12 de Octubre, Medicine Faculty, Universidad Complutense de Madrid (UCM), Instituto de Investigación Sanitaria Hospital 12 de Octubre (imas12), Madrid, 28041, Spain
| | - Angel Perez-Nuñez
- Neurosurgery Department, Hospital Universitario 12 de Octubre, Medicine Faculty, Universidad Complutense de Madrid (UCM), Instituto de Investigación Sanitaria Hospital 12 de Octubre (imas12), Madrid, 28041, Spain
| | - Alfonso Lagares
- Neurosurgery Department, Hospital Universitario 12 de Octubre, Medicine Faculty, Universidad Complutense de Madrid (UCM), Instituto de Investigación Sanitaria Hospital 12 de Octubre (imas12), Madrid, 28041, Spain.
| | - Eduardo Juarez
- Research Center on Software Technologies and Multimedia Systems, Universidad Politécnica de Madrid (UPM), Madrid, 28031, Spain.
| | - César Sanz
- Research Center on Software Technologies and Multimedia Systems, Universidad Politécnica de Madrid (UPM), Madrid, 28031, Spain
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13
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Chen M, Cheng R, He J, Chen J, Zhang J. SMOPCA: spatially aware dimension reduction integrating multi-omics improves the efficiency of spatial domain detection. Genome Biol 2025; 26:135. [PMID: 40399936 PMCID: PMC12096709 DOI: 10.1186/s13059-025-03576-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2024] [Accepted: 04/12/2025] [Indexed: 05/23/2025] Open
Abstract
Technological advances have enabled us to profile multiple omics layers with spatial information, significantly enhancing spatial domain detection and advancing a variety of biomedical research fields. Despite these advancements, there is a notable lack of effective methods for modeling spatial multi-omics data. We introduce SMOPCA, a Spatial Multi-Omics Principal Component Analysis method designed to perform joint dimension reduction on multimodal data while preserving spatial dependencies. Extensive experiments reveal that SMOPCA outperforms existing single-modal and multimodal dimension reduction and clustering methods, across both single-cell and spatial multi-omics datasets derived from diverse technologies and tissue structures.
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Affiliation(s)
- Mo Chen
- National Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, Jiangsu, China
- School of Artificial Intelligence, Nanjing University, Nanjing, Jiangsu, China
| | - Ruihua Cheng
- Big Data Statistics Research Center, Tianjin University of Finance and Economics, Tianjin, China
| | - Jianuo He
- National Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, Jiangsu, China
- School of Artificial Intelligence, Nanjing University, Nanjing, Jiangsu, China
| | - Jun Chen
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA.
| | - Jie Zhang
- National Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, Jiangsu, China.
- School of Artificial Intelligence, Nanjing University, Nanjing, Jiangsu, China.
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14
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Sahota A, Paulose Nadappuram B, Kwan Z, Lesept F, Howden JH, Claxton S, Kittler JT, Devine MJ, Edel JB, Ivanov AP. Spatial and Temporal Single-Cell Profiling of RNA Compartmentalization in Neurons with Nanotweezers. ACS NANO 2025; 19:18522-18533. [PMID: 40326740 PMCID: PMC12096465 DOI: 10.1021/acsnano.5c02056] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/04/2025] [Revised: 04/22/2025] [Accepted: 04/24/2025] [Indexed: 05/07/2025]
Abstract
Emerging techniques for mapping mRNAs within the subcellular compartments of live cells hold great promise for advancing our understanding of the spatial distribution of transcripts and enabling the study of single-cell dynamics in health and disease. This is particularly critical for polarized cells, such as neurons, where mRNA compartmentalization is essential for regulating gene expression, and defects in these localization mechanisms are linked to numerous neurological disorders. However, many subcellular analysis techniques require a compromise between subcellular precision, live-cell measurements, and nondestructive access to single cells in their native microenvironment. To overcome these challenges, we employ a single-cell technology that we have recently developed, the nanotweezer, which features a nanoscale footprint (∼100 nm), avoids cytoplasmic fluid aspiration, and enables rapid RNA isolation from living cells with minimal invasiveness. Using this tool, we investigate single-cell mRNA compartmentalization in the soma and dendrites of hippocampal neurons at different stages of neuronal development. By combining precise targeting with sequential sampling, we track changes in mRNA abundance at dendritic spine regions of the same neuron, both before and after stimulation. This minimally invasive approach enables time-resolved, subcellular gene expression profiling of the same single cell. This could provide critical insights into polarized cells and advance our understanding of biological processes and complex diseases.
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Affiliation(s)
- Annie Sahota
- Department
of Chemistry, Imperial College London, Molecular
Science Research Hub, LondonW12 0BZ, United
Kingdom
| | - Binoy Paulose Nadappuram
- Department
of Chemistry, Imperial College London, Molecular
Science Research Hub, LondonW12 0BZ, United
Kingdom
- Department
of Pure and Applied Chemistry, University
of Strathclyde, GlasgowG1 1BX, United
Kingdom
| | - Zoe Kwan
- Department
of Chemistry, Imperial College London, Molecular
Science Research Hub, LondonW12 0BZ, United
Kingdom
| | - Flavie Lesept
- Department
of Neuroscience, Physiology and Pharmacology, University College London, Gower Street, LondonWC1E 6BT, United
Kingdom.
| | - Jack H. Howden
- Department
of Neuroscience, Physiology and Pharmacology, University College London, Gower Street, LondonWC1E 6BT, United
Kingdom.
| | - Suzanne Claxton
- Kinases
and Brain Development Lab, The Francis Crick
Institute, 1 Midland Road, LondonNW1 1AT, United Kingdom
| | - Josef T. Kittler
- Department
of Neuroscience, Physiology and Pharmacology, University College London, Gower Street, LondonWC1E 6BT, United
Kingdom.
| | - Michael J. Devine
- Mitochondrial
Neurobiology Lab, The Francis Crick Institute, 1 Midland Road, LondonNW1 1AT, United Kingdom
- Department
of Clinical and Movement Neurosciences, UCL Queen Square Institute
of Neurology, University College London, LondonWC1N 3BG, United Kingdom
| | - Joshua B. Edel
- Department
of Chemistry, Imperial College London, Molecular
Science Research Hub, LondonW12 0BZ, United
Kingdom
| | - Aleksandar P. Ivanov
- Department
of Chemistry, Imperial College London, Molecular
Science Research Hub, LondonW12 0BZ, United
Kingdom
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15
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Mori T, Zhou M, Kunugitani K, Akatsuka T, Yoshida Y, Kouyama-Suzuki E, Kobayashi S, Shirai Y, Tabuchi K. The Competitive Loss of Cerebellar Granule and Purkinje Cells Driven by X-Linked Mosaicism in a Female Mouse Model of CASK-Related Disorders. Cells 2025; 14:735. [PMID: 40422238 DOI: 10.3390/cells14100735] [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: 02/13/2025] [Revised: 05/10/2025] [Accepted: 05/15/2025] [Indexed: 05/28/2025] Open
Abstract
CASK-related disorders are a form of female-restricted intellectual disabilities associated with cerebellar and pontine hypoplasia. The CASK gene is regulated by X-chromosome inactivation, which results in a mosaic distribution of CASK-expressing and CASK-deficient neurons in the female brain. This mosaic distribution is believed to play a key role in the pathophysiology of X-linked neurological disorders; however, the detailed brain structure has not been extensively characterized. In this study, we used CASK heterozygous knockout (CASK-hKO) mice combined with X-linked GFP reporter mice to investigate motor abilities and the distribution of CASK-expressing cells in the brains of female CASK-hKO mice. The CASK-hKO mice exhibited motor deficits and cerebellar hypoplasia similar to those observed in patients with CASK-related disorders. Interestingly, although half of the cerebellar granule cells were CASK-negative during early postnatal development, almost all Purkinje cells and cerebellar granule cells were CASK-positive in adulthood, suggesting that CASK expression may determine the survival of cerebellar granule cells during postnatal development. We also analyzed CASK-hypomorphic mice, which express 50% less CASK than wild-type mice, and compared hemizygous males and heterozygous females. The CASK-hypomorphic heterozygous females displayed a thinner cerebellar cortex and a higher probability of CASK-positive granule cells in CASK-hKO females, suggesting that the survival of cerebellar granule cells is regulated by a combination of cell-autonomous and cell-competitive mechanisms between CASK-expressing and CASK-deficient cells, which are generated by X-chromosome inactivation. These findings provide new insights into the relationship between the mosaic distribution of cells established by X-chromosome inactivation and the pathophysiology of CASK-related disorders.
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Affiliation(s)
- Takuma Mori
- Department of Molecular and Cellular Physiology, Shinshu University School of Medicine, Matsumoto 390-8621, Japan
- Department of Neuroinnovation, Institute for Biomedical Sciences, Interdisciplinary Cluster for Cutting Edge Research, Shinshu University, Matsumoto 390-8621, Japan
| | - Mengyun Zhou
- Department of Molecular and Cellular Physiology, Shinshu University School of Medicine, Matsumoto 390-8621, Japan
| | - Ken Kunugitani
- Department of Molecular and Cellular Physiology, Shinshu University School of Medicine, Matsumoto 390-8621, Japan
| | - Taichi Akatsuka
- Department of Molecular and Cellular Physiology, Shinshu University School of Medicine, Matsumoto 390-8621, Japan
| | - Yukina Yoshida
- Department of Molecular and Cellular Physiology, Shinshu University School of Medicine, Matsumoto 390-8621, Japan
| | - Emi Kouyama-Suzuki
- Department of Molecular and Cellular Physiology, Shinshu University School of Medicine, Matsumoto 390-8621, Japan
| | - Shin Kobayashi
- Cellular and Molecular Biotechnology Research Institute, National Institute of Advanced Industrial Science and Technology, Tokyo 135-0064, Japan
| | - Yoshinori Shirai
- Department of Molecular and Cellular Physiology, Shinshu University School of Medicine, Matsumoto 390-8621, Japan
| | - Katsuhiko Tabuchi
- Department of Molecular and Cellular Physiology, Shinshu University School of Medicine, Matsumoto 390-8621, Japan
- Department of Neuroinnovation, Institute for Biomedical Sciences, Interdisciplinary Cluster for Cutting Edge Research, Shinshu University, Matsumoto 390-8621, Japan
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16
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Rodríguez-Rodríguez A, Uribe RM, Cote-Vélez A, Joseph-Bravo P, Charli JL. Hypothalamic Median Eminence Thyrotropin-Releasing Hormone-Degrading Ectoenzyme Activity Is Dispensable for Basal Thyroid Axis Activity in Lean Rodents. Cells 2025; 14:725. [PMID: 40422228 DOI: 10.3390/cells14100725] [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: 02/13/2025] [Revised: 04/17/2025] [Accepted: 04/25/2025] [Indexed: 05/28/2025] Open
Abstract
The amplitude of the phasic output of thyrotropin-releasing hormone (TRH) into the hypothalamus-pituitary portal capillaries is likely controlled by the TRH-degrading ectoenzyme (TRH-DE) expressed on the surface of median eminence (ME) β2-tanycytes. To extend this hypothesis, we performed experiments on adult rodents reared in standard conditions. TRH-DE was close to the putative sites of TRH release in the male rat external layer of the ME. In global Trhde knockout mice, basal hypothalamus-pituitary-thyroid (HPT) axis parameters were not altered but we detected an increased vimentin (a tanycyte marker) positive coverage of the portal vessels. We then overexpressed TRH-DE or a dominant negative isoform by microinjection of adeno-associated virus 1 (AAV1) vectors into the third ventricle of adult male rats. Two weeks after microinjection, cold-stress-induced serum TSH concentration was decreased if ME TRH-DE activity had been enhanced. However, the long-term modification of TRH-DE activity in the ME had only a small impact on basal serum TSH concentration but increased Trhr expression in the anterior pituitary of animals transduced with AAV1-TRH-DE. Thus, long-term modifications of ME TRH-DE activity lead to limited changes in serum TSH concentration in adult rodents reared in standard conditions, possibly because of adaptations of TRH communication in the ME and/or anterior pituitary.
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Affiliation(s)
- Adair Rodríguez-Rodríguez
- Departamento de Genética del Desarrollo y Fisiología Molecular, Instituto de Biotecnología, Universidad Nacional Autónoma de México (UNAM), Avenida Universidad 2001, Cuernavaca 62210, Mexico
| | - Rosa María Uribe
- Departamento de Genética del Desarrollo y Fisiología Molecular, Instituto de Biotecnología, Universidad Nacional Autónoma de México (UNAM), Avenida Universidad 2001, Cuernavaca 62210, Mexico
| | - Antonieta Cote-Vélez
- Departamento de Genética del Desarrollo y Fisiología Molecular, Instituto de Biotecnología, Universidad Nacional Autónoma de México (UNAM), Avenida Universidad 2001, Cuernavaca 62210, Mexico
| | - Patricia Joseph-Bravo
- Departamento de Genética del Desarrollo y Fisiología Molecular, Instituto de Biotecnología, Universidad Nacional Autónoma de México (UNAM), Avenida Universidad 2001, Cuernavaca 62210, Mexico
| | - Jean-Louis Charli
- Departamento de Genética del Desarrollo y Fisiología Molecular, Instituto de Biotecnología, Universidad Nacional Autónoma de México (UNAM), Avenida Universidad 2001, Cuernavaca 62210, Mexico
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17
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Gao T, Liu X, Liu S, Liu F, Zhou Y, Wang S, Zeng N, Bao Y, Wang Y, Lu L. Antianxiety effects of dexmedetomidine: systematic review and meta-analysis. Eur Arch Psychiatry Clin Neurosci 2025:10.1007/s00406-025-02017-9. [PMID: 40372453 DOI: 10.1007/s00406-025-02017-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/04/2025] [Accepted: 04/12/2025] [Indexed: 05/16/2025]
Abstract
BACKGROUND Despite numerous studies of the anxiolytic effects of dexmedetomidine compared with those of other drugs or saline, the results have been inconsistent. Here we report a systematic review and meta-analysis to comprehensively evaluate the evidence of the anxiolytic effects of dexmedetomidine. METHODS This research has been registered in the International Prospective Register of Systematic Reviews. The PubMed, Embase, Cochrane Library, Web of Science, and ClinicalTrials.gov database were searched for clinical trials that compared the anxiolytic effects of dexmedetomidine with those of a control group with valid anxiety scores from inception to December 29, 2024. RESULTS Overall, this systematic review and meta-analysis included 25 clinical studies with 2159 participants who underwent surgery. The primary outcome revealed that patients who were treated with dexmedetomidine had significantly lower anxiety scores than others did overall (MD = - 1.73, 95% CI = [ - 2.33, - 1.13], p < 0.00001, I2 = 86.5%). Dexmedetomidine was found to be more effective than benzodiazepines in relieving anxiety (MD = - 1.34, 95% CI = [ - 2.08, - 0.60], p = 0.0004, I2 = 83.3%). The secondary outcomes revealed no significant differences in satisfaction, pain level, sedation scores or the risk of postoperative nausea and vomiting between patients who were treated with dexmedetomidine and controls. However, the occurrence of bradycardia was more common in the dexmedetomidine groups. CONCLUSIONS Overall, this meta-analysis provided evidence of the potential of dexmedetomidine for relieving anxiety among patients who undergo surgery, with superior antianxiety effects compared with those of benzodiazepines.
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Affiliation(s)
- Teng Gao
- Institute of Mental Health, National Clinical Research Center for Mental Disorders, Key Laboratory of Mental Health and Peking University Sixth Hospital, Peking University, Huayuan Bei Road, Beijing, 100191, China
| | - Xiaoxing Liu
- Institute of Mental Health, National Clinical Research Center for Mental Disorders, Key Laboratory of Mental Health and Peking University Sixth Hospital, Peking University, Huayuan Bei Road, Beijing, 100191, China
- Peking-Tsinghua Center for Life Sciences and PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, 100191, China
| | - Siyu Liu
- Institute of Mental Health, National Clinical Research Center for Mental Disorders, Key Laboratory of Mental Health and Peking University Sixth Hospital, Peking University, Huayuan Bei Road, Beijing, 100191, China
| | - Fanglin Liu
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, Beijing, 100191, China
- Department of Neurobiology, School of Basic Medical Sciences, Peking University Health Science Center, Beijing, 100191, China
| | - Yuchen Zhou
- Department of Anaesthesiology and Surgical Critical Care Medicine, Beijing Shijitan Hospital, Capital Medical University, No.10, Tieyi Road, Beijing, 100038, China
| | - Shaoheng Wang
- Department of Anaesthesiology, Peking University First Hospital, Beijing, China
| | - Na Zeng
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, Beijing, 100191, China
- Department of Neurobiology, School of Basic Medical Sciences, Peking University Health Science Center, Beijing, 100191, China
| | - Yanping Bao
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, Beijing, 100191, China
- Department of Neurobiology, School of Basic Medical Sciences, Peking University Health Science Center, Beijing, 100191, China
| | - Yuefu Wang
- Department of Anaesthesiology and Surgical Critical Care Medicine, Beijing Shijitan Hospital, Capital Medical University, No.10, Tieyi Road, Beijing, 100038, China.
| | - Lin Lu
- Institute of Mental Health, National Clinical Research Center for Mental Disorders, Key Laboratory of Mental Health and Peking University Sixth Hospital, Peking University, Huayuan Bei Road, Beijing, 100191, China.
- Peking-Tsinghua Center for Life Sciences and PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, 100191, China.
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, Beijing, 100191, China.
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18
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Inada K, Hagihara M, Kihara M, Abe T, Miyamichi K. A transgenic mouse line for rabies virus-mediated trans-synaptic tracing in the postnatal developing brain. PLoS One 2025; 20:e0323629. [PMID: 40354365 PMCID: PMC12068592 DOI: 10.1371/journal.pone.0323629] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2025] [Accepted: 04/10/2025] [Indexed: 05/14/2025] Open
Abstract
Neural circuits are composed of numerous neurons that perform diverse functions. Understanding the mechanisms of neural processing requires elucidating the connections among individual neurons. Rabies virus (RV)-mediated trans-synaptic tracing enables the visualization of direct presynaptic neurons of a defined neural population, facilitating the precise mapping of neural circuits across various brain regions. This method relies on RV mutants that require the expression of the TVA receptor and rabies glycoprotein to infect and spread to presynaptic neurons. Traditionally, adeno-associated virus (AAV) has been used to express these proteins. However, because AAV requires several weeks to achieve sufficient gene expression, it is challenging to use this approach for studying neural connections during postnatal development. To address this limitation, we generated a transgenic mouse line, termed Ai162-nCTG, which expresses nuclear-localized mCherry, the TVA receptor, and rabies glycoprotein in a Cre-dependent manner. As a proof-of-principle, we crossed the Ai162-nCTG line with the vasopressin-Cre line. In the paraventricular hypothalamic nucleus, where a major cluster of vasopressin neurons exists, mCherry expression was highly specific to vasopressin neurons, although not all vasopressin neurons co-expressed mCherry. We injected RV into the paraventricular hypothalamic nucleus and compared the labeling patterns with those of the conventional AAV-based approach. Although both methods labeled input cells in similar brain regions, the AAV-based approach was superior in terms of labeling efficiency. We also demonstrated that the Ai162-nCTG-based method enables rabies virus-mediated trans-synaptic tracing in mice at postnatal day 7 and 30. The distribution of presynaptic neurons was largely similar in the juvenile and adult stages, suggesting that paraventricular vasopressin neurons do not significantly change their presynaptic inputs during post-weaning development. Taken together, these findings suggest that the Ai162-nCTG line can be used for rabies virus-mediated trans-synaptic tracing when AAV administration is challenging. We also acknowledge and discuss the technical constraints associated with this mouse line.
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Affiliation(s)
- Kengo Inada
- Laboratory for Comparative Connectomics, RIKEN Center for Biosystems Dynamics Research, Kobe, Hyogo, Japan
| | - Mitsue Hagihara
- Laboratory for Comparative Connectomics, RIKEN Center for Biosystems Dynamics Research, Kobe, Hyogo, Japan
| | - Miho Kihara
- Laboratory for Animal Resources and Genetic Engineering, RIKEN Center for Biosystems Dynamics Research, Kobe, Hyogo, Japan
| | - Takaya Abe
- Laboratory for Animal Resources and Genetic Engineering, RIKEN Center for Biosystems Dynamics Research, Kobe, Hyogo, Japan
| | - Kazunari Miyamichi
- Laboratory for Comparative Connectomics, RIKEN Center for Biosystems Dynamics Research, Kobe, Hyogo, Japan
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19
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Lungu R, Fernandes FF, Pires Monteiro S, Outeiro TF, Shemesh N. Neural and vascular contributions to sensory impairments in a human alpha-synuclein transgenic mouse model of Parkinson's disease. J Cereb Blood Flow Metab 2025:271678X251338952. [PMID: 40334688 PMCID: PMC12058711 DOI: 10.1177/0271678x251338952] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/15/2024] [Revised: 03/06/2025] [Accepted: 04/14/2025] [Indexed: 05/09/2025]
Abstract
Parkinson's disease (PD) is a complex progressive neurodegenerative disorder involving hallmarks such as α -Synuclein (α Syn) aggregation and dopaminergic dysfunction that affect brain-wide neural activity. Although movement disorders are prominent in PD, sensory impairments also occur relatively early on, mainly in olfactory and, to a lesser extent visual systems. While these deficits have been described mainly at the behavioral and molecular levels, the underlying network-level activity remains poorly understood. Here, we harnessed a human α Syn transgenic mouse model of PD with in vivo functional MRI (fMRI) to map evoked activity in the visual and olfactory pathways, along with pseudo-Continuous Arterial Spin Labeling (pCASL) and c-FOS measurements to disentangle vascular from neuronal effects. Upon stimulation with either odors or flickering lights, we found significant decreases in fMRI responses along both olfactory and visual pathways, in multiple cortical and subcortical sensory areas. Average Cerebral Blood Flow rates were decreased by ∼10% in the α Syn group, while c-FOS levels were reduced by over 50%, suggesting a strong neural driver for the dysfunction, along with more modest vascular contributions. Our study provides insight into brain-level activity in an α Syn-based model, and suggests a novel target for biomarking via quantification of simple sensory evoked responses.
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Affiliation(s)
- Ruxanda Lungu
- Champalimaud Research, Champalimaud Foundation, Lisbon, Portugal
| | | | - Sara Pires Monteiro
- Champalimaud Research, Champalimaud Foundation, Lisbon, Portugal
- Institute for Systems and Robotics - Lisboa and Department of Bioengineering, Instituto Superior Técnico – Universidade de Lisboa, Lisbon, Portugal
| | - Tiago F Outeiro
- Department of Experimental Neurodegeneration, University Medical Center Göttingen, Center for Biostructural Imaging of Neurodegeneration, Göttingen, Germany
- Max Planck Institute for Multidisciplinary Sciences, Göttingen, Germany
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle Upon Tyne, UK
- Scientific Employee with an Honorary Contract at German Center for Neurodegenerative Diseases (DZNE), Göttingen, Germany
| | - Noam Shemesh
- Champalimaud Research, Champalimaud Foundation, Lisbon, Portugal
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20
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Catto F, Kirschenbaum D, Economides AE, Reuss AM, Trevisan C, Caredio D, Dadgar-Kiani E, Mirzet D, Frick L, Weber-Stadlbauer U, Litvinov S, Koumoutsakos P, Lee JH, Aguzzi A. Quantitative 3D histochemistry reveals region-specific amyloid-β reduction by the antidiabetic drug netoglitazone. PLoS One 2025; 20:e0309489. [PMID: 40327707 PMCID: PMC12054868 DOI: 10.1371/journal.pone.0309489] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2024] [Accepted: 03/29/2025] [Indexed: 05/08/2025] Open
Abstract
A hallmark of Alzheimer's disease (AD) is the extracellular aggregation of toxic amyloid-beta (Aβ) peptides in form of plaques. Here, we identify netoglitazone, an antidiabetic compound previously tested in humans, as an Aβ aggregation antagonist. Netoglitazone improved cognition and reduced microglia activity in a mouse model of AD. Using quantitative whole-brain three-dimensional histology (Q3D), we precisely identified brain regions where netoglitazone reduced the number and size of Aβ plaques. We demonstrate the utility of Q3D in preclinical drug evaluation for AD by providing a high-resolution brain-wide view of drug efficacy. Applying Q3D has the potential to improve pre-clinical drug evaluation by providing information that can help identify mechanisms leading to brain region-specific drug efficacy.
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Affiliation(s)
- Francesca Catto
- Institute of Neuropathology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
- IMAI MedTech GmbH, Zurich, Switzerland
| | - Daniel Kirschenbaum
- Institute of Neuropathology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Athena E. Economides
- Institute of Neuropathology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Anna Maria Reuss
- Institute of Neuropathology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Chiara Trevisan
- Institute of Neuropathology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Davide Caredio
- Institute of Neuropathology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Ehsan Dadgar-Kiani
- Institute of Veterinary Pharmacology and Toxicology, University of Zurich, Zürich, Switzerland
- Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Delic Mirzet
- Institute of Neuropathology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Lukas Frick
- Institute of Neuropathology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Ulrike Weber-Stadlbauer
- Institute of Veterinary Pharmacology and Toxicology, University of Zurich, Zürich, Switzerland
- Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Sergey Litvinov
- Computational Science and Engineering Laboratory, School of Engineering and Applied Sciences, Harvard University, Cambridge, United States of America
| | - Petros Koumoutsakos
- Computational Science and Engineering Laboratory, School of Engineering and Applied Sciences, Harvard University, Cambridge, United States of America
| | - Jin Hyung Lee
- Department of Neurology and Neurological Sciences, Stanford University, California, United States of America
- Department of Bioengineering, Stanford University, Stanford, California, United States of America
- Department of Electrical Engineering, Stanford University, Stanford, California, United States of America
- Department of Neurosurgery, Stanford University, Stanford, California, United States of America
| | - Adriano Aguzzi
- Institute of Neuropathology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
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21
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Bhardwaj D, Youssef I, Imphean D, Holmes SK, Krishnan V, Estill-Terpack SJ, Diamond M, Chopra R, Bailey RM, Shah BR. Nitrous oxide enhances MR-guided focused ultrasound delivery of gene therapy to the murine hippocampus. Gene Ther 2025:10.1038/s41434-025-00530-z. [PMID: 40328971 DOI: 10.1038/s41434-025-00530-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2024] [Revised: 03/04/2025] [Accepted: 03/25/2025] [Indexed: 05/08/2025]
Abstract
Transcranial Magnetic Resonance Guided Focused Ultrasound can oscillate intravenously delivered microbubbles and transiently open the blood brain barrier (BBB) in a targeted brain region. However, high microbubble doses or Focused ultrasound pressures (FUS) leads to injury. So, we administered nitrous oxide (N2O), an anesthetic gas to determine reduced need of FUS pressure and microbubble dose for opening BBB. Swiss Webster mice were treated with N2O or medical air (MA) at varying FUS pressures, while the microbubble dose was kept constant and the vice-versa. Consequently, BBB opening was quantified by acoustic emissions and enhancement rate on T1-weighted MR. To compare the effect of N2O on gene delivery, following BBB opening with either MA or N2O, a viral vector expressing GFP was subsequently delivered. Additionally, Immunohistochemical studies quantified viral transfection efficacy and assessed acute cell injury. We observed that N2O significantly potentiates acoustic emissions and enhancement rate on post-contrast MRI images, compared to MA at all measured pressures (0.39, 0.45, 0.67 MPa). Furthermore, N2O reduces the microbubble dose to 0.02μl/kg and FUS pressures to 0.28 and 0.39 MPa for BBB disruption and enhanced viral gene delivery, respectively. Hence, N2O potentiates microbubble oscillations, allowing reduced microbubble dose and FUS pressures and improved viral gene delivery.
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Affiliation(s)
- Deepshikha Bhardwaj
- Transcranial Focused Ultrasound Lab, UTSW Medical Center, Dallas, TX, USA
- Neuroradiology and Neuro-intervention Section, Department of Radiology, UTSW Medical Center, Dallas, TX, USA
| | - Ibrahim Youssef
- Transcranial Focused Ultrasound Lab, UTSW Medical Center, Dallas, TX, USA
- Neuroradiology and Neuro-intervention Section, Department of Radiology, UTSW Medical Center, Dallas, TX, USA
- Department of Chemistry, Faculty of Science, Mansoura University, Dakahlia, Egypt
| | - Darren Imphean
- Transcranial Focused Ultrasound Lab, UTSW Medical Center, Dallas, TX, USA
- Neuroradiology and Neuro-intervention Section, Department of Radiology, UTSW Medical Center, Dallas, TX, USA
| | - Sydni K Holmes
- Center for Alzheimer's and Neurodegenerative Diseases, UTSW Medical Center, Dallas, TX, USA
| | - Venugopal Krishnan
- Transcranial Focused Ultrasound Lab, UTSW Medical Center, Dallas, TX, USA
- Neuroradiology and Neuro-intervention Section, Department of Radiology, UTSW Medical Center, Dallas, TX, USA
| | | | - Marc Diamond
- Center for Alzheimer's and Neurodegenerative Diseases, UTSW Medical Center, Dallas, TX, USA
- Department of Neurology, UTSW Medical Center, Dallas, TX, USA
| | - Rajiv Chopra
- Transcranial Focused Ultrasound Lab, UTSW Medical Center, Dallas, TX, USA
- Neuroradiology and Neuro-intervention Section, Department of Radiology, UTSW Medical Center, Dallas, TX, USA
- Advanced Imaging Research Center, UTSW Medical Center, Dallas, TX, USA
| | - Rachel M Bailey
- Center for Alzheimer's and Neurodegenerative Diseases, UTSW Medical Center, Dallas, TX, USA
- Department of Pediatrics, UTSW Medical Center, Dallas, TX, USA
| | - Bhavya R Shah
- Transcranial Focused Ultrasound Lab, UTSW Medical Center, Dallas, TX, USA.
- Neuroradiology and Neuro-intervention Section, Department of Radiology, UTSW Medical Center, Dallas, TX, USA.
- Center for Alzheimer's and Neurodegenerative Diseases, UTSW Medical Center, Dallas, TX, USA.
- Advanced Imaging Research Center, UTSW Medical Center, Dallas, TX, USA.
- Department of Neurological Surgery, UTSW Medical Center, Dallas, TX, USA.
- O'Donnell Brain Institute, UTSW Medical Center, Dallas, TX, USA.
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22
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Qneibi M, Bdir S, Bdair M, Aldwaik SA, Heeh M, Sandouka D, Idais T. Exploring the role of AMPA receptor auxiliary proteins in synaptic functions and diseases. FEBS J 2025; 292:2433-2478. [PMID: 39394632 DOI: 10.1111/febs.17287] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2024] [Revised: 08/21/2024] [Accepted: 09/20/2024] [Indexed: 10/13/2024]
Abstract
α-Amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) ionotropic glutamate receptors (AMPARs) mediate rapid excitatory synaptic transmission in the mammalian brain, primarily driven by the neurotransmitter glutamate. The modulation of AMPAR activity, particularly calcium-permeable AMPARs (CP-AMPARs), is crucially influenced by various auxiliary subunits. These subunits are integral membrane proteins that bind to the receptor's core and modify its functional properties, including ion channel kinetics and receptor trafficking. This review comprehensively catalogs all known AMPAR auxiliary proteins, providing vital insights into the biochemical mechanisms governing synaptic modulation and the specific impact of CP-AMPARs compared to their calcium-impermeable AMPA receptor (CI-AMPARs). Understanding the complex interplay between AMPARs and their auxiliary subunits in different brain regions is essential for elucidating their roles in cognitive functions such as learning and memory. Importantly, alterations in these auxiliary proteins' expression, function or interactions have been implicated in various neurological disorders. Aberrant signaling through CP-AMPARs, in particular, is associated with severe synaptic dysfunctions across neurodevelopmental, neurodegenerative and psychiatric conditions. Targeting the distinct properties of AMPAR-auxiliary subunit complexes, especially those involving CP-AMPARs, could disclose new therapeutic strategies, potentially allowing for more precise interventions in treating complex neuronal disorders.
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Affiliation(s)
- Mohammad Qneibi
- Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, An-Najah National University, Nablus, Palestine
| | - Sosana Bdir
- Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, An-Najah National University, Nablus, Palestine
| | - Mohammad Bdair
- Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, An-Najah National University, Nablus, Palestine
| | - Samia Ammar Aldwaik
- Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, An-Najah National University, Nablus, Palestine
| | | | - Dana Sandouka
- Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, An-Najah National University, Nablus, Palestine
| | - Tala Idais
- Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, An-Najah National University, Nablus, Palestine
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23
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Zhu S, Huszar IN, Cottaar M, Daubney G, Eichert N, Hanayik T, Khrapitchev AA, Mars RB, Mollink J, Sallet J, Scott C, Smart A, Jbabdi S, Miller KL, Howard AFD. Imaging the structural connectome with hybrid MRI-microscopy tractography. Med Image Anal 2025; 102:103498. [PMID: 40086183 DOI: 10.1016/j.media.2025.103498] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2024] [Revised: 01/20/2025] [Accepted: 02/05/2025] [Indexed: 03/16/2025]
Abstract
Mapping how neurons are structurally wired into whole-brain networks can be challenging, particularly in larger brains where 3D microscopy is not available. Multi-modal datasets combining MRI and microscopy provide a solution, where high resolution but 2D microscopy can be complemented by whole-brain but lowresolution MRI. However, there lacks unified approaches to integrate and jointly analyse these multi-modal data in an insightful way. To address this gap, we introduce a data-fusion method for hybrid MRI-microscopy fibre orientation and connectome reconstruction. Specifically, we complement precise "in-plane" orientations from microscopy with "through-plane" information from MRI to construct 3D hybrid fibre orientations at resolutions far exceeding that of MRI whilst preserving microscopy's myelin specificity, resulting in superior fibre tracking. Our method is openly available, can be deployed on standard 2D microscopy, including different microscopy contrasts, and is species agnostic, facilitating neuroanatomical investigation in both animal models and human brains.
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Affiliation(s)
- Silei Zhu
- Wellcome Centre for Integrative Neuroimaging, FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom.
| | - Istvan N Huszar
- Wellcome Centre for Integrative Neuroimaging, FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Michiel Cottaar
- Wellcome Centre for Integrative Neuroimaging, FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Greg Daubney
- Wellcome Centre for Integrative Neuroimaging, Experimental Psychology, Medical Sciences Division, University of Oxford, Oxford, United Kingdom
| | - Nicole Eichert
- Wellcome Centre for Integrative Neuroimaging, FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Taylor Hanayik
- Wellcome Centre for Integrative Neuroimaging, FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | | | - Rogier B Mars
- Wellcome Centre for Integrative Neuroimaging, FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom; Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, the Netherlands
| | - Jeroen Mollink
- Wellcome Centre for Integrative Neuroimaging, Experimental Psychology, Medical Sciences Division, University of Oxford, Oxford, United Kingdom
| | - Jerome Sallet
- Wellcome Centre for Integrative Neuroimaging, Experimental Psychology, Medical Sciences Division, University of Oxford, Oxford, United Kingdom; INSERM U1208, Stem Cell and Brain Research Institute, University Lyon, Bron, France
| | - Connor Scott
- Division of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Adele Smart
- Wellcome Centre for Integrative Neuroimaging, FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom; Division of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Saad Jbabdi
- Wellcome Centre for Integrative Neuroimaging, FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Karla L Miller
- Wellcome Centre for Integrative Neuroimaging, FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Amy F D Howard
- Wellcome Centre for Integrative Neuroimaging, FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom; Department of Bioengineering, Imperial College London, London, United Kingdom
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24
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Hanchate NK. Single-cell genomics meets systems neuroscience: Insights from mapping the brain circuitry of stress. J Neuroendocrinol 2025; 37:e70005. [PMID: 39956535 PMCID: PMC12045673 DOI: 10.1111/jne.70005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/08/2024] [Revised: 12/26/2024] [Accepted: 02/03/2025] [Indexed: 02/18/2025]
Abstract
Responses to external and internal dangers is essential for survival and homeostatic regulation. Hypothalamic corticotropin-releasing hormone neurons (CRHNs) play a pivotal role in regulating neuroendocrine responses to fear and stress. In recent years, the application of neurogenetic tools, such as fiber photometry, chemogenetics and optogenetics, have provided new insights into the dynamic neuronal responses of CRHNs during stressful events, offering new perspectives into their functional significance in mediating neurobehavioural responses to stress. Transsynaptic viral tracers have facilitated the comprehensive mapping of neuronal inputs to CRHNs. Furthermore, the development and application of innovative single-cell genomic tools combined with viral tracing have begun to pave the way for a deeper understanding of the transcriptional profiles of neural circuit components, enabling molecular-anatomical circuit mapping. Here, I will discuss how these systems neuroscience approaches and novel single-cell genomic methods are advancing the molecular and functional mapping of stress neurocircuits, their associated challenges and future directions.
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Affiliation(s)
- Naresh K. Hanchate
- Genetics & Genomic Medicine DepartmentUCL Great Ormond Street Institute of Child Health, University College LondonLondonUK
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25
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Hui T, Zhou J, Yao M, Xie Y, Zeng H. Advances in Spatial Omics Technologies. SMALL METHODS 2025; 9:e2401171. [PMID: 40099571 DOI: 10.1002/smtd.202401171] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/29/2024] [Revised: 03/03/2025] [Indexed: 03/20/2025]
Abstract
Rapidly developing spatial omics technologies provide us with new approaches to deeply understanding the diversity and functions of cell types within organisms. Unlike traditional approaches, spatial omics technologies enable researchers to dissect the complex relationships between tissue structure and function at the cellular or even subcellular level. The application of spatial omics technologies provides new perspectives on key biological processes such as nervous system development, organ development, and tumor microenvironment. This review focuses on the advancements and strategies of spatial omics technologies, summarizes their applications in biomedical research, and highlights the power of spatial omics technologies in advancing the understanding of life sciences related to development and disease.
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Affiliation(s)
- Tianxiao Hui
- State Key Laboratory of Gene Function and Modulation Research, College of Future Technology, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, 100871, China
| | - Jian Zhou
- Peking-Tsinghua Center for Life Sciences, Tsinghua University, Beijing, 100084, China
| | - Muchen Yao
- College of Biological Sciences, China Agricultural University, Beijing, 100193, China
| | - Yige Xie
- School of Nursing, Peking University, Beijing, 100871, China
| | - Hu Zeng
- State Key Laboratory of Gene Function and Modulation Research, College of Future Technology, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, 100871, China
- Beijing Advanced Center of RNA Biology (BEACON), Peking University, Beijing, 100871, China
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26
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Luo B, Teng F, Tang G, Cen W, Liu X, Chen J, Qu C, Liu X, Liu X, Jiang W, Huang H, Feng Y, Zhang X, Jian M, Li M, Xi F, Li G, Liao S, Chen A, Yu W, Xu X, Zhang J. StereoMM: a graph fusion model for integrating spatial transcriptomic data and pathological images. Brief Bioinform 2025; 26:bbaf210. [PMID: 40407386 PMCID: PMC12100622 DOI: 10.1093/bib/bbaf210] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2024] [Revised: 03/27/2025] [Accepted: 04/10/2025] [Indexed: 05/26/2025] Open
Abstract
Spatial omics technologies, generating high-throughput and multimodal data, have necessitated the development of advanced data integration methods to facilitate comprehensive biological and clinical treatment discoveries. Based on the cross-attention concept, we developed an AI learning based toolchain called StereoMM, a graph based fusion model that can incorporate omics data such as gene expression, histological images, and spatial location. StereoMM uses an attention module for omics data interaction and a graph autoencoder to integrate spatial positions and omics data in a self-supervised manner. Applying StereoMM across various cancer types and platforms has demonstrated its robust capability. StereoMM outperforms competitors in identifying spatial regions reflecting tumour progression and shows promise in classifying colorectal cancer patients into deficient mismatch repair and proficient mismatch repair groups. The comprehensive inter-modal integration and efficiency of StereoMM enable researchers to construct spatial views of integrated multimodal features efficiently, advancing thorough tissue and patient characterization.
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Affiliation(s)
- Bingying Luo
- BGI Research, Chongqing, No. 313, Jinyue road, Jiulongpo District, Chongqing 401329, China
- BGI Research, Shenzhen, No. 9, Yunhua Road, Yantian District, Shenzhen 518083, China
| | - Fei Teng
- BGI Research, Chongqing, No. 313, Jinyue road, Jiulongpo District, Chongqing 401329, China
- BGI Research, Shenzhen, No. 9, Yunhua Road, Yantian District, Shenzhen 518083, China
| | - Guo Tang
- BGI Research, Chongqing, No. 313, Jinyue road, Jiulongpo District, Chongqing 401329, China
| | - Weixuan Cen
- BGI Research, Shenzhen, No. 9, Yunhua Road, Yantian District, Shenzhen 518083, China
| | - Xing Liu
- BGI Research, Chongqing, No. 313, Jinyue road, Jiulongpo District, Chongqing 401329, China
- BGI Research, Shenzhen, No. 9, Yunhua Road, Yantian District, Shenzhen 518083, China
| | - Jinmiao Chen
- Center for Computational Biology and Program in Cancer and Stem Cell Biology, Duke-NUS Medical School, 8 College Road, Singapore 169857, Singapore
| | - Chi Qu
- BGI Research, Chongqing, No. 313, Jinyue road, Jiulongpo District, Chongqing 401329, China
| | - Xuanzhu Liu
- BGI Research, Chongqing, No. 313, Jinyue road, Jiulongpo District, Chongqing 401329, China
- BGI Research, Shenzhen, No. 9, Yunhua Road, Yantian District, Shenzhen 518083, China
| | - Xin Liu
- BGI Research, Chongqing, No. 313, Jinyue road, Jiulongpo District, Chongqing 401329, China
| | - Wenyan Jiang
- BGI Research, Chongqing, No. 313, Jinyue road, Jiulongpo District, Chongqing 401329, China
| | - Huaqiang Huang
- BGI Research, Chongqing, No. 313, Jinyue road, Jiulongpo District, Chongqing 401329, China
| | - Yu Feng
- State Key Laboratory of Genome and Multi-omics Technologies, BGI Research, No. 9, Yunhua Road, Yantian District, Shenzhen 518083, China
- BGI Collaborative Center for Future Medicine, Shanxi Medical University, No. 1258, Xinjiannan Road, Yingze District, Taiyuan 030001, China
| | - Xue Zhang
- BGI Research, Chongqing, No. 313, Jinyue road, Jiulongpo District, Chongqing 401329, China
| | - Min Jian
- BGI Research, Shenzhen, No. 9, Yunhua Road, Yantian District, Shenzhen 518083, China
| | - Mei Li
- BGI Research, Shenzhen, No. 9, Yunhua Road, Yantian District, Shenzhen 518083, China
| | - Feng Xi
- BGI Research, Chongqing, No. 313, Jinyue road, Jiulongpo District, Chongqing 401329, China
| | - Guibo Li
- BGI Research, Chongqing, No. 313, Jinyue road, Jiulongpo District, Chongqing 401329, China
- BGI Research, Shenzhen, No. 9, Yunhua Road, Yantian District, Shenzhen 518083, China
| | - Sha Liao
- BGI Research, Shenzhen, No. 9, Yunhua Road, Yantian District, Shenzhen 518083, China
| | - Ao Chen
- BGI Research, Chongqing, No. 313, Jinyue road, Jiulongpo District, Chongqing 401329, China
- BGI Research, Shenzhen, No. 9, Yunhua Road, Yantian District, Shenzhen 518083, China
| | - Weimiao Yu
- School of Biological Science, Nanyang Technological University, 60 Nanyang Drive, Singapore 637551, Singapore
| | - Xun Xu
- BGI Research, Chongqing, No. 313, Jinyue road, Jiulongpo District, Chongqing 401329, China
- BGI Research, Shenzhen, No. 9, Yunhua Road, Yantian District, Shenzhen 518083, China
- BGI Research, Hangzhou, No. 203, Zhenzhong Road, Xihu District, Hangzhou 310030, China
| | - Jiajun Zhang
- BGI Research, Chongqing, No. 313, Jinyue road, Jiulongpo District, Chongqing 401329, China
- BGI Research, Shenzhen, No. 9, Yunhua Road, Yantian District, Shenzhen 518083, China
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27
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Raddatz MC, Newson CM, Stott M, Campbell C, Bobeck EN. GPR171 is necessary for normal physiological functions and mood-related behaviors in males, but not females. Behav Brain Res 2025; 490:115618. [PMID: 40318809 DOI: 10.1016/j.bbr.2025.115618] [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: 12/19/2024] [Revised: 04/22/2025] [Accepted: 04/30/2025] [Indexed: 05/07/2025]
Abstract
GPR171 is a recently deorphanized G protein-coupled receptor that has been implicated in feeding, mood regulation, and pain. However, the role of this receptor in other physiological functions and in female mice is largely unexplored. Using a novel genetic GPR171 knockout mouse model, we examined general physiological behaviors and mood-related behaviors in both sexes. In male GPR171 knockout mice, we observed increased feeding, reduced water intake, heightened ataxia, and decreased anxiety-like behaviors. Male GPR171 knockout mice showed greater depressive-like behaviors compared to female knockout mice, but this did not correspond to a change in cFos activity in the basolateral amygdala. No significant changes were detected in female GPR171 knockout mice in other behaviors measured. These findings corroborate previous studies linking GPR171 to feeding and mood regulation in males, but highlight notable sex differences that were previously unknown. These sex differences indicate that future studies should focus on elucidating the behavioral effects of GPR171 in females to provide a more comprehensive understanding of its physiological roles.
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Affiliation(s)
- Megan C Raddatz
- Department of Biology, Utah State University, Logan, UT, United States; Interdisciplinary Neuroscience Program, Utah State University, Logan, UT, United States
| | - Callie M Newson
- Department of Biology, Utah State University, Logan, UT, United States; Interdisciplinary Neuroscience Program, Utah State University, Logan, UT, United States
| | - Mitchel Stott
- Department of Biology, Utah State University, Logan, UT, United States
| | - Colton Campbell
- Department of Biology, Utah State University, Logan, UT, United States
| | - Erin N Bobeck
- Department of Biology, Utah State University, Logan, UT, United States; Interdisciplinary Neuroscience Program, Utah State University, Logan, UT, United States.
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28
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Inácio AR, Lam KC, Zhao Y, Pereira F, Gerfen CR, Lee S. Brain-wide presynaptic networks of functionally distinct cortical neurons. Nature 2025; 641:162-172. [PMID: 40011781 PMCID: PMC12043506 DOI: 10.1038/s41586-025-08631-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Accepted: 01/10/2025] [Indexed: 02/28/2025]
Abstract
Revealing the connectivity of functionally identified individual neurons is necessary to understand how activity patterns emerge and support behaviour. Yet the brain-wide presynaptic wiring rules that lay the foundation for the functional selectivity of individual neurons remain largely unexplored. Cortical neurons, even in primary sensory cortex, are heterogeneous in their selectivity, not only to sensory stimuli but also to multiple aspects of behaviour. Here, to investigate presynaptic connectivity rules underlying the selectivity of pyramidal neurons to behavioural state1-10 in primary somatosensory cortex (S1), we used two-photon calcium imaging, neuropharmacology, single-cell-based monosynaptic input tracing and optogenetics. We show that behavioural state-dependent activity patterns are stable over time. These are minimally affected by direct neuromodulatory inputs and are driven primarily by glutamatergic inputs. Analysis of brain-wide presynaptic networks of individual neurons with distinct behavioural state-dependent activity profiles revealed that although behavioural state-related and behavioural state-unrelated neurons shared a similar pattern of local inputs within S1, their long-range glutamatergic inputs differed. Individual cortical neurons, irrespective of their functional properties, received converging inputs from the main S1-projecting areas. Yet neurons that tracked behavioural state received a smaller proportion of motor cortical inputs and a larger proportion of thalamic inputs. Optogenetic suppression of thalamic inputs reduced behavioural state-dependent activity in S1, but this activity was not externally driven. Our results reveal distinct long-range glutamatergic inputs as a substrate for preconfigured network dynamics associated with behavioural state.
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Affiliation(s)
- Ana R Inácio
- Unit on Functional Neural Circuits, Systems Neurodevelopment Laboratory, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA.
| | - Ka Chun Lam
- Machine Learning Core, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA
| | - Yuan Zhao
- Machine Learning Core, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA
| | - Francisco Pereira
- Machine Learning Core, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA
| | - Charles R Gerfen
- Section on Neuroanatomy, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA
| | - Soohyun Lee
- Unit on Functional Neural Circuits, Systems Neurodevelopment Laboratory, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA.
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29
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Müller‐Bötticher N, Tiesmeyer S, Eils R, Ishaque N. Sainsc: A Computational Tool for Segmentation-Free Analysis of In Situ Capture Data. SMALL METHODS 2025; 9:e2401123. [PMID: 39533496 PMCID: PMC12103232 DOI: 10.1002/smtd.202401123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/22/2024] [Revised: 09/23/2024] [Indexed: 11/16/2024]
Abstract
Spatially resolved transcriptomics (SRT) has become the method of choice for characterising the complexity of biomedical tissue samples. Until recently, scientists were restricted to SRT methods that can profile a limited set of target genes at high spatial resolution or transcriptome-wide but at a low spatial resolution. Through recent developments, there are now methods that offer both subcellular spatial resolution and full transcriptome coverage. However, utilising these new methods' high spatial resolution and gene resolution remains elusive due to several factors, including low detection efficiency and high computational costs. Here, we present Sainsc (Segmentation-free analysis of in situ capture data), which combines a cell-segmentation-free approach with efficient data processing of transcriptome-wide nanometre-resolution spatial data. Sainsc can generate cell-type maps with accurate cell-type assignment at the nanometre scale, together with corresponding maps of the assignment scores that facilitate interpretation of the local confidence of cell-type assignment. We demonstrate its utility and accuracy for different tissues and technologies. Compared to other methods, Sainsc requires lower computational resources and has scalable performance, enabling interactive data exploration. Sainsc is compatible with common data analysis frameworks and is available as open-source software in multiple programming languages.
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Affiliation(s)
- Niklas Müller‐Bötticher
- Center of Digital HealthBerlin Institute of Health at Charité – Universitätsmedizin BerlinCharitéplatz 110117BerlinGermany
- Department of Mathematics and Computer ScienceFreie Universität BerlinArnimallee 1414195BerlinGermany
| | - Sebastian Tiesmeyer
- Center of Digital HealthBerlin Institute of Health at Charité – Universitätsmedizin BerlinCharitéplatz 110117BerlinGermany
- Department of Mathematics and Computer ScienceFreie Universität BerlinArnimallee 1414195BerlinGermany
| | - Roland Eils
- Center of Digital HealthBerlin Institute of Health at Charité – Universitätsmedizin BerlinCharitéplatz 110117BerlinGermany
- Department of Mathematics and Computer ScienceFreie Universität BerlinArnimallee 1414195BerlinGermany
- Health Data Science UnitHeidelberg University Hospital and BioQuantUniversity of HeidelbergIm Neuenheimer Feld 26769120HeidelbergGermany
| | - Naveed Ishaque
- Center of Digital HealthBerlin Institute of Health at Charité – Universitätsmedizin BerlinCharitéplatz 110117BerlinGermany
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30
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Sun Y, Liu D, Liang Y, Yang X, Liu X, Zhao B, Liang Z, Zhang Y, Zhang L. High-Throughput Proteoform Imaging for Revealing Spatial-Resolved Changes in Brain Tissues Associated with Alzheimer's Disease. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2025; 12:e2416722. [PMID: 40071752 PMCID: PMC12061265 DOI: 10.1002/advs.202416722] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/13/2024] [Revised: 02/04/2025] [Indexed: 05/10/2025]
Abstract
Spatially resolved characterization of proteoforms has substantial potential to significantly advance the understanding of physiological and disease mechanisms. However, challenges remain regarding throughput and coverage. A robust method is developed for high-throughput proteoform imaging (HTPi) by combining matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI MSI) and region-specific top-down proteomic analysis. MALDI MSI enables the imaging of proteoforms on tissue sections at a rate of 7 h cm-2 (100-µm spatial resolution), and the identification sensitivity of the proteoforms is improved by narrow-bore monolithic columns with low adsorption, yielding 366 annotated proteoform images from the mouse brain. The obtained proteoform images reveals differential expression of individual proteoforms across the brain regions, and distinct spatial distribution patterns of various proteoforms generated from a single gene. Given its ability to visualize proteoform, HTPi is further applied to explore spatial pathological changes associated with Alzheimer's disease (AD) in 5 × FAD mice. 158 annotated proteoform images are obtained in hippocampal regions at 50-µm spatial resolution, illuminating 14 differential proteoforms in the subiculum region and highlighting their significant associations with amyloid-β pathology in AD. The results highlight the power of HTPi in unraveling the intricate molecular landscape of brain tissues and its potential in elucidating disease mechanisms.
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Affiliation(s)
- Yue Sun
- State Key Laboratory of Medical ProteomicsNational Chromatographic R. & A. CenterCAS Key Laboratory of Separation Science for Analytical ChemistryDalian Institute of Chemical PhysicsChinese Academy of Sciences457 Zhongshan RoadDalian116023China
- University of Chinese Academy of SciencesBeijing100049China
| | - Dan Liu
- State Key Laboratory of Medical ProteomicsNational Chromatographic R. & A. CenterCAS Key Laboratory of Separation Science for Analytical ChemistryDalian Institute of Chemical PhysicsChinese Academy of Sciences457 Zhongshan RoadDalian116023China
| | - Yu Liang
- State Key Laboratory of Medical ProteomicsNational Chromatographic R. & A. CenterCAS Key Laboratory of Separation Science for Analytical ChemistryDalian Institute of Chemical PhysicsChinese Academy of Sciences457 Zhongshan RoadDalian116023China
| | - Xue Yang
- State Key Laboratory of Medical ProteomicsNational Chromatographic R. & A. CenterCAS Key Laboratory of Separation Science for Analytical ChemistryDalian Institute of Chemical PhysicsChinese Academy of Sciences457 Zhongshan RoadDalian116023China
- University of Chinese Academy of SciencesBeijing100049China
| | - Xinxin Liu
- State Key Laboratory of Medical ProteomicsNational Chromatographic R. & A. CenterCAS Key Laboratory of Separation Science for Analytical ChemistryDalian Institute of Chemical PhysicsChinese Academy of Sciences457 Zhongshan RoadDalian116023China
| | - Baofeng Zhao
- State Key Laboratory of Medical ProteomicsNational Chromatographic R. & A. CenterCAS Key Laboratory of Separation Science for Analytical ChemistryDalian Institute of Chemical PhysicsChinese Academy of Sciences457 Zhongshan RoadDalian116023China
| | - Zhen Liang
- State Key Laboratory of Medical ProteomicsNational Chromatographic R. & A. CenterCAS Key Laboratory of Separation Science for Analytical ChemistryDalian Institute of Chemical PhysicsChinese Academy of Sciences457 Zhongshan RoadDalian116023China
| | - Yukui Zhang
- State Key Laboratory of Medical ProteomicsNational Chromatographic R. & A. CenterCAS Key Laboratory of Separation Science for Analytical ChemistryDalian Institute of Chemical PhysicsChinese Academy of Sciences457 Zhongshan RoadDalian116023China
| | - Lihua Zhang
- State Key Laboratory of Medical ProteomicsNational Chromatographic R. & A. CenterCAS Key Laboratory of Separation Science for Analytical ChemistryDalian Institute of Chemical PhysicsChinese Academy of Sciences457 Zhongshan RoadDalian116023China
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31
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Bueno D, Schäfer MK, Wang S, Schmeisser MJ, Methner A. NECAB family of neuronal calcium-binding proteins in health and disease. Neural Regen Res 2025; 20:1236-1243. [PMID: 38934399 PMCID: PMC11624857 DOI: 10.4103/nrr.nrr-d-24-00094] [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: 01/23/2024] [Revised: 04/18/2024] [Accepted: 05/29/2024] [Indexed: 06/28/2024] Open
Abstract
The N-terminal EF-hand calcium-binding proteins 1-3 (NECAB1-3) constitute a family of predominantly neuronal proteins characterized by the presence of at least one EF-hand calcium-binding domain and a functionally less well characterized C-terminal antibiotic biosynthesis monooxygenase domain. All three family members were initially discovered due to their interactions with other proteins. NECAB1 associates with synaptotagmin-1, a critical neuronal protein involved in membrane trafficking and synaptic vesicle exocytosis. NECAB2 interacts with predominantly striatal G-protein-coupled receptors, while NECAB3 partners with amyloid-β A4 precursor protein-binding family A members 2 and 3, key regulators of amyloid-β production. This demonstrates the capacity of the family for interactions with various classes of proteins. NECAB proteins exhibit distinct subcellular localizations: NECAB1 is found in the nucleus and cytosol, NECAB2 resides in endosomes and the plasma membrane, and NECAB3 is present in the endoplasmic reticulum and Golgi apparatus. The antibiotic biosynthesis monooxygenase domain, an evolutionarily ancient component, is akin to atypical heme oxygenases in prokaryotes but is not well-characterized in vertebrates. Prokaryotic antibiotic biosynthesis monooxygenase domains typically form dimers, suggesting that calcium-mediated conformational changes in NECAB proteins may induce antibiotic biosynthesis monooxygenase domain dimerization, potentially activating some enzymatic properties. However, the substrate for this enzymatic activity remains uncertain. Alternatively, calcium-mediated conformational changes might influence protein interactions or the subcellular localization of NECAB proteins by controlling the availability of protein-protein interaction domains situated between the EF hands and the antibiotic biosynthesis monooxygenase domain. This review summarizes what is known about genomic organization, tissue expression, intracellular localization, interaction partners, and the physiological and pathophysiological role of the NECAB family.
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Affiliation(s)
- Diones Bueno
- Institute for Molecular Medicine, University Medical Center of the Johannes Gutenberg-University, Mainz, Germany
| | - Michael K.E. Schäfer
- Department of Anesthesiology, University Medical Center of the Johannes Gutenberg-University, Mainz, Germany
| | - Sudena Wang
- Department of Anesthesiology, University Medical Center of the Johannes Gutenberg-University, Mainz, Germany
| | - Michael J. Schmeisser
- Institute of Anatomy, University Medical Center of the Johannes Gutenberg-University, Mainz, Germany
| | - Axel Methner
- Institute for Molecular Medicine, University Medical Center of the Johannes Gutenberg-University, Mainz, Germany
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Humbel M, Tanner C, Girona Alarcón M, Schulz G, Weitkamp T, Scheel M, Kurtcuoglu V, Müller B, Rodgers G. Synchrotron Radiation-Based Tomography of an Entire Mouse Brain with Sub-Micron Voxels: Augmenting Interactive Brain Atlases with Terabyte Data. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2025:e2416879. [PMID: 40298880 DOI: 10.1002/advs.202416879] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/14/2024] [Revised: 03/07/2025] [Indexed: 04/30/2025]
Abstract
Synchrotron radiation-based X-ray microtomography is uniquely suited for post-mortem 3D visualization of organs such as the mouse brain. Tomographic imaging of the entire mouse brain with isotropic cellular resolution requires an extended field-of-view and produces datasets of multiple terabytes in size. These data must be reconstructed, analyzed, and made accessible to domain experts who may have limited image processing knowledge. Extended-field X-ray microtomography is presented with0.65 μ m $0.65 \,\umu \mathrm{m}$ voxel size covering an entire mouse brain. The 4495 projections from 8 × 8 offset acquisitions are stitched to reconstruct a volume of 150003 voxels. The microtomography volume was non-rigidly registered to the Allen Mouse Brain Common Coordinate Framework v3 based on a combination of image intensity and landmark pairs. The data were block-wise transformed and stored in a public repository with a hierarchical format for navigation and overlay with anatomical annotations in online viewers such as Neuroglancer or siibra-explorer. This study demonstrates X-ray imaging and data processing for a full mouse brain, augmenting current atlases by improving resolution in the third dimension by an order of magnitude. The 3.3-teravoxel dataset is publicly available and easily accessible for domain experts via browser-based viewers.
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Affiliation(s)
- Mattia Humbel
- Biomaterials Science Center, Department of Biomedical Engineering, University of Basel, Hegenheimermattweg 167B/C, Allschwil, 4123, Switzerland
| | - Christine Tanner
- Biomaterials Science Center, Department of Biomedical Engineering, University of Basel, Hegenheimermattweg 167B/C, Allschwil, 4123, Switzerland
- Core Facility Micro- and Nanotomography, Department of Biomedical Engineering, University of Basel, Hegenheimermattweg 167B/C, Allschwil, 4123, Switzerland
| | - Marta Girona Alarcón
- The Interface Group, Institute of Physiology, University of Zurich, Winterthurerstrasse 190, Zurich, 8057, Switzerland
| | - Georg Schulz
- Biomaterials Science Center, Department of Biomedical Engineering, University of Basel, Hegenheimermattweg 167B/C, Allschwil, 4123, Switzerland
- Core Facility Micro- and Nanotomography, Department of Biomedical Engineering, University of Basel, Hegenheimermattweg 167B/C, Allschwil, 4123, Switzerland
| | - Timm Weitkamp
- Synchrotron SOLEIL, L'Orme des Merisiers, Saint-Aubin, 91190, France
| | - Mario Scheel
- Synchrotron SOLEIL, L'Orme des Merisiers, Saint-Aubin, 91190, France
| | - Vartan Kurtcuoglu
- The Interface Group, Institute of Physiology, University of Zurich, Winterthurerstrasse 190, Zurich, 8057, Switzerland
| | - Bert Müller
- Biomaterials Science Center, Department of Biomedical Engineering, University of Basel, Hegenheimermattweg 167B/C, Allschwil, 4123, Switzerland
- Biomaterials Science Center, Department of Clinical Research, University Hospital Basel, Spitalstrasse 8/12, Basel, 4031, Switzerland
| | - Griffin Rodgers
- Biomaterials Science Center, Department of Biomedical Engineering, University of Basel, Hegenheimermattweg 167B/C, Allschwil, 4123, Switzerland
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Fadel L, Hipskind E, Pedersen SE, Romero J, Ortiz C, Shin E, Samee MAH, Pautler RG. Modeling functional connectivity with learning and memory in a mouse model of Alzheimer's disease. FRONTIERS IN NEUROIMAGING 2025; 4:1558759. [PMID: 40353249 PMCID: PMC12062036 DOI: 10.3389/fnimg.2025.1558759] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/10/2025] [Accepted: 04/04/2025] [Indexed: 05/14/2025]
Abstract
Introduction Functional connectivity (FC) is a metric of how different brain regions interact with each other. Although there have been some studies correlating learning and memory with FC, there have not yet been, to date, studies that use machine learning (ML) to explain how FC changes can be used to explain behavior not only in healthy mice, but also in mouse models of Alzheimer's Disease (AD). Here, we investigated changes in FC and their relationship to learning and memory in a mouse model of AD across disease progression. Methods We assessed the APP/PS1 mouse model of AD and wild-type controls at 3-, 6-, and 10-months of age. Using resting state functional magnetic resonance imaging (rs-fMRI) in awake, unanesthetized mice, we assessed FC between 30 brain regions. ML models were then used to define interactions between neuroimaging readouts with learning and memory performance. Results In the APP/PS1 mice, we identified a pattern of hyperconnectivity across all three time points, with 47 hyperconnected regions at 3 months, 46 at 6 months, and 84 at 10 months. Notably, FC changes were also observed in the Default Mode Network, exhibiting a loss of hyperconnectivity over time. Modeling revealed functional connections that support learning and memory performance differ between the 6- and 10-month groups. Discussion These ML models show potential for early disease detection by identifying connectivity patterns associated with cognitive decline. Additionally, ML may provide a means to begin to understand how FC translates into learning and memory performance.
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Affiliation(s)
- Lindsay Fadel
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, United States
| | - Elizabeth Hipskind
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, United States
| | - Steen E. Pedersen
- Department of Integrative Physiology, Baylor College of Medicine, Houston, TX, United States
| | - Jonathan Romero
- Small Animal Imaging Facility, Texas Children's Hospital, Houston, TX, United States
| | - Caitlyn Ortiz
- Department of Integrative Physiology, Baylor College of Medicine, Houston, TX, United States
- Small Animal Imaging Facility, Texas Children's Hospital, Houston, TX, United States
| | - Eric Shin
- Department of Integrative Physiology, Baylor College of Medicine, Houston, TX, United States
| | - Md Abul Hassan Samee
- Department of Integrative Physiology, Baylor College of Medicine, Houston, TX, United States
| | - Robia G. Pautler
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, United States
- Department of Integrative Physiology, Baylor College of Medicine, Houston, TX, United States
- Small Animal Imaging Facility, Texas Children's Hospital, Houston, TX, United States
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Zhang M, Yang L, Mi X, Hu G, Lu Y, Wang C, Yang J, Sun X, Niu M, Li X, Wang S, Zhang J, Yu H, Wang Y, Yu M, Li N, Zhou Y. GHS-R1a signaling drives anxiety-related behavior by shaping excitability of ventromedial hypothalamic neurons. Nat Commun 2025; 16:3858. [PMID: 40274845 PMCID: PMC12022087 DOI: 10.1038/s41467-025-59116-3] [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: 11/29/2023] [Accepted: 04/10/2025] [Indexed: 04/26/2025] Open
Abstract
The neural substrates of anxiety are poorly understood, which hinders treatment of anxiety disorders. Here we found, αCaMKII+ neurons in the ventral medial hypothalamic nucleus (VMH) responded to stressors with increased activity in male mice, both under physiological conditions and after repeated restraint stress. Activation of VMH αCaMKII+ neurons were necessary and sufficient to ameliorate stress-induced anxiety. The peripheral metabolic hormone ghrelin and receptor GHS-R1a play a complex role in emotion regulation; however, the mechanism is uncertain. A delayed increase in GHS-R1a expression in VMH αCaMKII+ neurons coincided with the development of stress-induced enhancement of anxiety-related behavior. GHS-R1a expression in VMH αCaMKII+ neurons promoted anxiety-related behavior, whereas GHS-R1a knockdown had the opposite effect. GHS-R1a upregulation inhibited the excitability of VMH αCaMKII+ neurons. We conclude that GHSR1a signaling drives stress-induced anxiety by shaping the activity of VMH αCaMKII+ neurons. GHS-R1a may be a therapeutic target for treating anxiety disorders such as post-traumatic stress disorder.
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Affiliation(s)
- Meng Zhang
- School of Life Sciences and Health, University of Health and Rehabilitation Sciences, Qingdao, Shandong, 266113, China
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, Qingdao University, Qingdao, Shandong, 266071, China
- Institute of Brain Sciences and Related Disorders, Qingdao University, Qingdao, Shandong, 266071, China
- College of Agriculture and Bioengineering, Heze University, Heze, Shandong, 274000, China
| | - Liu Yang
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, Qingdao University, Qingdao, Shandong, 266071, China
- Institute of Brain Sciences and Related Disorders, Qingdao University, Qingdao, Shandong, 266071, China
| | - Xue Mi
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, Qingdao University, Qingdao, Shandong, 266071, China
- Institute of Brain Sciences and Related Disorders, Qingdao University, Qingdao, Shandong, 266071, China
| | - Gonghui Hu
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, Qingdao University, Qingdao, Shandong, 266071, China
- Institute of Brain Sciences and Related Disorders, Qingdao University, Qingdao, Shandong, 266071, China
| | - Yingchang Lu
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, Qingdao University, Qingdao, Shandong, 266071, China
- Institute of Brain Sciences and Related Disorders, Qingdao University, Qingdao, Shandong, 266071, China
| | - Chen Wang
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, Qingdao University, Qingdao, Shandong, 266071, China
- Institute of Brain Sciences and Related Disorders, Qingdao University, Qingdao, Shandong, 266071, China
| | - Jie Yang
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, Qingdao University, Qingdao, Shandong, 266071, China
- Institute of Brain Sciences and Related Disorders, Qingdao University, Qingdao, Shandong, 266071, China
- Dongying No.1 Middle School, Dongying, Shandong, 257000, China
| | - Xiaomin Sun
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, Qingdao University, Qingdao, Shandong, 266071, China
- Institute of Brain Sciences and Related Disorders, Qingdao University, Qingdao, Shandong, 266071, China
- Qingdao West Coast New Area No. 9 Senior High School, Qingdao, Shandong, 266500, China
| | - Minglu Niu
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, Qingdao University, Qingdao, Shandong, 266071, China
- Institute of Brain Sciences and Related Disorders, Qingdao University, Qingdao, Shandong, 266071, China
- Qingdao Endocrine diabetes Hospital, Qingdao, Shandong, 266000, China
| | - Xianchao Li
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, Qingdao University, Qingdao, Shandong, 266071, China
- Institute of Brain Sciences and Related Disorders, Qingdao University, Qingdao, Shandong, 266071, China
| | - Sihan Wang
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, Qingdao University, Qingdao, Shandong, 266071, China
- Institute of Brain Sciences and Related Disorders, Qingdao University, Qingdao, Shandong, 266071, China
| | - Jingsai Zhang
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, Qingdao University, Qingdao, Shandong, 266071, China
- Institute of Brain Sciences and Related Disorders, Qingdao University, Qingdao, Shandong, 266071, China
| | - Hanbing Yu
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, Qingdao University, Qingdao, Shandong, 266071, China
- Institute of Brain Sciences and Related Disorders, Qingdao University, Qingdao, Shandong, 266071, China
| | - Yuyang Wang
- Department of Rehabilitation Medicine, Affiliated Hospital of Qingdao University, Qingdao, Shandong, 266000, China
| | - Ming Yu
- School of Life Sciences and Health, University of Health and Rehabilitation Sciences, Qingdao, Shandong, 266113, China
| | - Nan Li
- School of Life Sciences and Health, University of Health and Rehabilitation Sciences, Qingdao, Shandong, 266113, China
| | - Yu Zhou
- School of Life Sciences and Health, University of Health and Rehabilitation Sciences, Qingdao, Shandong, 266113, China.
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, Qingdao University, Qingdao, Shandong, 266071, China.
- Institute of Brain Sciences and Related Disorders, Qingdao University, Qingdao, Shandong, 266071, China.
- Department of Rehabilitation Medicine, Affiliated Hospital of Qingdao University, Qingdao, Shandong, 266000, China.
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Liu F, Ren S, Li J, Lv H, Jiang F, Bin Yu. SGTB: A graph representation learning model combining transformer and BERT for optimizing gene expression analysis in spatial transcriptomics data. Comput Biol Chem 2025; 118:108482. [PMID: 40306096 DOI: 10.1016/j.compbiolchem.2025.108482] [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: 03/09/2025] [Revised: 04/05/2025] [Accepted: 04/17/2025] [Indexed: 05/02/2025]
Abstract
In recent years, spatial transcriptomics (ST) has emerged as an innovative technology that enables the simultaneous acquisition of gene expression information and its spatial distribution at the single-cell or regional level, providing deeper insights into cellular interactions and tissue organization, this technology provides a more holistic view of tissue organization and intercellular dynamics. However, existing methods still face certain limitations in data representation capabilities, making it challenging to fully capture complex spatial dependencies and global features. To address this, this paper proposes an innovative spatial multi-scale graph convolutional network (SGTB) based on large language models, integrating graph convolutional networks (GCN), Transformer, and BERT language models to optimize the representation of spatial transcriptomics data. The Graph Convolutional Network (GCN) employs a multi-layer architecture to extract features from gene expression matrices. Through iterative aggregation of neighborhood information, it captures spatial dependencies among cells and gene co-expression patterns, thereby constructing hierarchical cell embeddings. Subsequently, the model integrates an attention mechanism to assign weights to critical features and leverages Transformer layers to model global relationships, refining the ability of learned representations to reflect variations in spatial patterns. Finally, the model incorporates the BERT language model, mapping cell embeddings into textual inputs to exploit its deep semantic representation capabilities for high-dimensional feature extraction. These features are then fused with the embeddings generated by the Transformer, further optimizing feature learning for spatial transcriptomics data. This approach holds significant application value in improving the accuracy of tasks such as cell type classification and gene regulatory network construction, providing a novel computational framework for deep mining of spatial multi-scale biological data.
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Affiliation(s)
- Farong Liu
- College of Mathematics and Physics, Qingdao University of Science and Technology, Qingdao 266061, China; School of Data Science, Qingdao University of Science and Technology, Qingdao 266061, China
| | - Sheng Ren
- School of Data Science, Qingdao University of Science and Technology, Qingdao 266061, China; Artificial Intelligence and Biomedical Big Data Research Center, Qingdao University of Science and Technology, Qingdao 266061, China
| | - Jie Li
- School of Data Science, Qingdao University of Science and Technology, Qingdao 266061, China; Artificial Intelligence and Biomedical Big Data Research Center, Qingdao University of Science and Technology, Qingdao 266061, China
| | - Haoyang Lv
- School of Data Science, Qingdao University of Science and Technology, Qingdao 266061, China; Artificial Intelligence and Biomedical Big Data Research Center, Qingdao University of Science and Technology, Qingdao 266061, China
| | - Fenghui Jiang
- Editorial Office of Journal of Qingdao University of Science and Technology (Natural Science Edition), Qingdao University of Science and Technology, Qingdao 266061, China.
| | - Bin Yu
- School of Data Science, Qingdao University of Science and Technology, Qingdao 266061, China; Artificial Intelligence and Biomedical Big Data Research Center, Qingdao University of Science and Technology, Qingdao 266061, China.
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Gandin V, Kim J, Yang LZ, Lian Y, Kawase T, Hu A, Rokicki K, Fleishman G, Tillberg P, Castrejon AA, Stringer C, Preibisch S, Liu ZJ. Deep-tissue transcriptomics and subcellular imaging at high spatial resolution. Science 2025; 388:eadq2084. [PMID: 39977545 PMCID: PMC12005972 DOI: 10.1126/science.adq2084] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2024] [Revised: 11/11/2024] [Accepted: 02/07/2025] [Indexed: 02/22/2025]
Abstract
Limited color channels in fluorescence microscopy have long constrained spatial analysis in biological specimens. We introduce cycle hybridization chain reaction (cycleHCR), a method that integrates multicycle DNA barcoding with HCR to overcome this limitation. cycleHCR enables highly multiplexed imaging of RNA and proteins using a unified barcode system. Whole-embryo transcriptomics imaging achieved precise three-dimensional gene expression and cell fate mapping across a specimen depth of ~310 μm. When combined with expansion microscopy, cycleHCR revealed an intricate network of 10 subcellular structures in mouse embryonic fibroblasts. In mouse hippocampal slices, multiplex RNA and protein imaging uncovered complex gene expression gradients and cell-type-specific nuclear structural variations. cycleHCR provides a quantitative framework for elucidating spatial regulation in deep tissue contexts for research and has potential diagnostic applications.
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Affiliation(s)
- Valentina Gandin
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Jun Kim
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Liang-Zhong Yang
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Yumin Lian
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Takashi Kawase
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Amy Hu
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Konrad Rokicki
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Greg Fleishman
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Paul Tillberg
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | | | - Carsen Stringer
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Stephan Preibisch
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Zhe J. Liu
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
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Soto F, Lin CI, Jo A, Chou SY, Harding EG, Ruzycki PA, Seabold GK, Petralia RS, Kerschensteiner D. Molecular mechanism establishing the OFF pathway in vision. Nat Commun 2025; 16:3708. [PMID: 40251167 PMCID: PMC12008213 DOI: 10.1038/s41467-025-59046-0] [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: 09/17/2024] [Accepted: 04/07/2025] [Indexed: 04/20/2025] Open
Abstract
Parallel ON and OFF (positive- and negative-contrast) pathways fundamental to vision arise at the complex synapse of cone photoreceptors. Cone pedicles form spatially segregated functionally opposite connections with ON and OFF bipolar cells. Here, we discover that mammalian cones express LRFN2, a cell-adhesion molecule, which localizes to the pedicle base. LRFN2 stabilizes basal contacts between cone pedicles and OFF bipolar cell dendrites to guide pathway-specific partner choices, encompassing multiple cell types. In addition, LRFN2 trans-synaptically organizes glutamate receptor clusters, determining the contrast preferences of the OFF pathway. ON and OFF pathways converge in the inner retina to regulate bipolar cell outputs. We analyze LRFN2's contributions to ON-OFF interactions, pathway asymmetries, and neural and behavioral responses to approaching predators. Our results reveal that LRFN2 controls the formation of the OFF pathway in vision, supports parallel processing in a single synapse, and shapes contrast coding and the detection of visual threats.
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Affiliation(s)
- Florentina Soto
- Department of Ophthalmology and Visual Sciences, Washington University School of Medicine, St. Louis, MO, USA.
| | - Chin-I Lin
- Department of Ophthalmology and Visual Sciences, Washington University School of Medicine, St. Louis, MO, USA
- Graduate Program in Neuroscience, Division of Biological & Biomedical Sciences, Washington University School of Medicine, St. Louis, MO, USA
| | - Andrew Jo
- Department of Ophthalmology and Visual Sciences, Washington University School of Medicine, St. Louis, MO, USA
| | - Ssu-Yu Chou
- Department of Ophthalmology and Visual Sciences, Washington University School of Medicine, St. Louis, MO, USA
| | - Ellen G Harding
- Department of Ophthalmology and Visual Sciences, Washington University School of Medicine, St. Louis, MO, USA
| | - Philip A Ruzycki
- Department of Ophthalmology and Visual Sciences, Washington University School of Medicine, St. Louis, MO, USA
| | - Gail K Seabold
- Laboratory of Neurochemistry, National Institute on Deafness and Other Communication Disorders, National Institutes of Health, Bethesda, MD, USA
| | - Ronald S Petralia
- Laboratory of Neurochemistry, National Institute on Deafness and Other Communication Disorders, National Institutes of Health, Bethesda, MD, USA
- Advanced Imaging Core, National Institute on Deafness and Other Communication Disorders, National Institutes of Health, Bethesda, MD, USA
| | - Daniel Kerschensteiner
- Department of Ophthalmology and Visual Sciences, Washington University School of Medicine, St. Louis, MO, USA.
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO, USA.
- Department of Biomedical Engineering, Washington University School of Medicine, St. Louis, MO, USA.
- Bright Center for Human Vision, Washington University School of Medicine, St. Louis, MO, USA.
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Ruiz-Amezcua P, Ibáñez-Barranco N, Reigada D, Novillo I, Soto A, Barreda-Manso MA, Muñoz-Galdeano T, Maza RM, Esteban FJ, Nieto-Díaz M. Reanalysis of Published Histological Data Can Help to Characterize Neuronal Death After Spinal Cord Injury. Int J Mol Sci 2025; 26:3749. [PMID: 40332342 PMCID: PMC12028015 DOI: 10.3390/ijms26083749] [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: 03/07/2025] [Revised: 04/06/2025] [Accepted: 04/08/2025] [Indexed: 05/08/2025] Open
Abstract
Neuronal death is a central event in spinal cord injury (SCI) pathophysiology. Despite its importance, we have a fragmentary vision of the process. In our opinion, the research community has accumulated enough information to provide a more detailed, integrated vision of neuronal death after SCI. This work embeds this vision by creating an open repository to store and share data and results from their analysis. We have employed this repository to upload raw images of spinal cord sections from a mouse model of contusive SCI and used this information to compare manual-, threshold-, and neural network-based neuron identifications and to explore neuronal death at the injury penumbra 21 days after injury and the effects of the anti-apoptotic drug ucf-101. Results indicate that, whereas the three identification methods assayed yield coherent estimates of the total number of neurons per section, neural network (NN) outperforms the other two methods. Combining NN identification and image registration has allowed us to characterize neuron distribution among Rexed laminae in the mice T11, revealing spatial patterns in the neuronal death that follows injury and in their survival following ucf-101 treatment.
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Affiliation(s)
- Pablo Ruiz-Amezcua
- Molecular Neuroprotection Group, National Hospital for Paraplegics (SESCAM), Instituto de Investigación Sanitaria de Castilla-La Mancha, 45071 Toledo, Spain; (P.R.-A.); (N.I.-B.); (D.R.); (I.N.); (A.S.); (M.A.B.-M.); (T.M.-G.)
- Department of Experimental Biology, University of Jaén, 23071 Jaén, Spain
| | - Nadia Ibáñez-Barranco
- Molecular Neuroprotection Group, National Hospital for Paraplegics (SESCAM), Instituto de Investigación Sanitaria de Castilla-La Mancha, 45071 Toledo, Spain; (P.R.-A.); (N.I.-B.); (D.R.); (I.N.); (A.S.); (M.A.B.-M.); (T.M.-G.)
- Global Services Learning Associate Human Pharma Regions in Boehringer Ingelheim, 08174 Barcelona, Spain
| | - David Reigada
- Molecular Neuroprotection Group, National Hospital for Paraplegics (SESCAM), Instituto de Investigación Sanitaria de Castilla-La Mancha, 45071 Toledo, Spain; (P.R.-A.); (N.I.-B.); (D.R.); (I.N.); (A.S.); (M.A.B.-M.); (T.M.-G.)
| | - Irene Novillo
- Molecular Neuroprotection Group, National Hospital for Paraplegics (SESCAM), Instituto de Investigación Sanitaria de Castilla-La Mancha, 45071 Toledo, Spain; (P.R.-A.); (N.I.-B.); (D.R.); (I.N.); (A.S.); (M.A.B.-M.); (T.M.-G.)
| | - Altea Soto
- Molecular Neuroprotection Group, National Hospital for Paraplegics (SESCAM), Instituto de Investigación Sanitaria de Castilla-La Mancha, 45071 Toledo, Spain; (P.R.-A.); (N.I.-B.); (D.R.); (I.N.); (A.S.); (M.A.B.-M.); (T.M.-G.)
| | - María Asunción Barreda-Manso
- Molecular Neuroprotection Group, National Hospital for Paraplegics (SESCAM), Instituto de Investigación Sanitaria de Castilla-La Mancha, 45071 Toledo, Spain; (P.R.-A.); (N.I.-B.); (D.R.); (I.N.); (A.S.); (M.A.B.-M.); (T.M.-G.)
- Functional Exploration and Neuromodulation of Nervous System Investigation Group, National Hospital for Paraplegics (SESCAM), Fundación del Hospital Nacional de Parapléjicos para la Investigación y la Integración, Instituto de Investigación Sanitaria de Castilla-La Mancha, 45071 Toledo, Spain
| | - Teresa Muñoz-Galdeano
- Molecular Neuroprotection Group, National Hospital for Paraplegics (SESCAM), Instituto de Investigación Sanitaria de Castilla-La Mancha, 45071 Toledo, Spain; (P.R.-A.); (N.I.-B.); (D.R.); (I.N.); (A.S.); (M.A.B.-M.); (T.M.-G.)
| | - Rodrigo M. Maza
- Molecular Neuroprotection Group, National Hospital for Paraplegics (SESCAM), Instituto de Investigación Sanitaria de Castilla-La Mancha, 45071 Toledo, Spain; (P.R.-A.); (N.I.-B.); (D.R.); (I.N.); (A.S.); (M.A.B.-M.); (T.M.-G.)
| | | | - Manuel Nieto-Díaz
- Molecular Neuroprotection Group, National Hospital for Paraplegics (SESCAM), Instituto de Investigación Sanitaria de Castilla-La Mancha, 45071 Toledo, Spain; (P.R.-A.); (N.I.-B.); (D.R.); (I.N.); (A.S.); (M.A.B.-M.); (T.M.-G.)
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39
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Relota XJ, Ford A, Savier EL. Behavioral Modulation and Molecular Definition of Wide-Field Vertical Cells in the Mouse Superior Colliculus. J Neurosci 2025; 45:e1816242025. [PMID: 40032526 PMCID: PMC12005361 DOI: 10.1523/jneurosci.1816-24.2025] [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: 09/23/2024] [Revised: 02/10/2025] [Accepted: 02/12/2025] [Indexed: 03/05/2025] Open
Abstract
Visual information can have different meanings across species, and the same visual stimulus can drive appetitive or aversive behavior. The superior colliculus (SC), a visual center located in the midbrain has been involved in driving such behaviors. Within this structure, the wide-field vertical cells (WFV) are a conserved morphological cell type that is present in species ranging from reptiles to cats (Basso et al., 2021). Here, we report our investigation of the connectivity of the WFV, their visual responses, and how these responses are modulated by locomotion in male and female laboratory mice. We also address the molecular definition of these cells and attempt to reconcile recent findings acquired by RNA sequencing of single cells in the SC with the Ntsr1-Cre GN209 transgenic mouse line which was previously used to investigate WFV. We use viral strategies to reveal WFV inputs and outputs and confirm their unique response properties using in vivo two-photon imaging. Among the stimuli tested, WFV prefer looming stimuli, a small moving spot, and upward-moving visual stimuli. We find that only visual responses driven by a looming stimulus show a significant modulation by locomotion. We identify several inputs to the WFV as potential candidates for this modulation. These results suggest that WFV integrate information across multiple brain regions and are subject to behavioral modulation. Taken together, our results pave the way to elucidate the role of these neurons in visual behavior and allow us to interrogate the definition of cell types in the light of new molecular definitions.
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Affiliation(s)
- Xena J Relota
- Molecular and Integrative Physiology Department, University of Michigan, Ann Arbor, Michigan 48109
| | - Alexander Ford
- Neuroscience Graduate Program, University of Michigan, Ann Arbor, Michigan 48109
| | - Elise L Savier
- Molecular and Integrative Physiology Department, University of Michigan, Ann Arbor, Michigan 48109
- Ophthalmology and Visual Science Department, University of Michigan, Ann Arbor, Michigan 48109
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40
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Braden K, Castro DC. The role of dorsal raphe nucleus neuropeptides in reward and aversion. Front Behav Neurosci 2025; 19:1553470. [PMID: 40270681 PMCID: PMC12014661 DOI: 10.3389/fnbeh.2025.1553470] [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: 12/30/2024] [Accepted: 03/13/2025] [Indexed: 04/25/2025] Open
Abstract
The dorsal raphe nucleus is a critical node for affective and motivated circuits in the brain. Though typically known as a serotonergic hub, the dorsal raphe nucleus is also highly enriched in a variety of neuropeptides. Recent advances in biotechnology and behavioral modeling have led to a resurgence in neuropeptide research, allowing investigators to target unique peptide systems with unprecedented clarity. Here, we review and discuss multiple neuropeptide systems in dorsal raphe and consider how their activity may contribute to reward and aversion. While this is not an exhaustive review, this short overview will highlight the many opportunities available to refine our understanding of multiple dorsal raphe neuropeptides. By more thoroughly studying dorsal raphe neuropeptides, we will reveal novel pathways to design more effective therapeutics and tailor treatments for millions of patients.
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Affiliation(s)
- Kathryn Braden
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, Saint Louis, MO, United States
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41
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Wu S, Huang H, Wang S, Chen G, Zhou C, Yang D. Neural heterogeneity enhances reliable neural information processing: Local sensitivity and globally input-slaved transient dynamics. SCIENCE ADVANCES 2025; 11:eadr3903. [PMID: 40173217 PMCID: PMC11963962 DOI: 10.1126/sciadv.adr3903] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/30/2024] [Accepted: 02/26/2025] [Indexed: 04/04/2025]
Abstract
Cortical neuronal activity varies over time and across repeated trials, yet consistently represents stimulus features. The dynamical mechanism underlying this reliable representation and computation remains elusive. This study uncovers a mechanism for reliable neural information processing, leveraging a biologically plausible network model incorporating neural heterogeneity. First, we investigate neuronal timescale diversity, revealing that it disrupts intrinsic coherent spatiotemporal patterns, induces firing rate heterogeneity, enhances local responsive sensitivity, and aligns network activity closely with input. The system exhibits globally input-slaved transient dynamics, essential for reliable neural information processing. Other neural heterogeneities, such as nonuniform input connections, spike threshold heterogeneity, and network in-degree heterogeneity, play similar roles, highlighting the importance of neural heterogeneity in shaping consistent stimulus representation. This mechanism offers a potentially general framework for understanding neural heterogeneity in reliable computation and informs the design of reservoir computing models endowed with liquid wave reservoirs for neuromorphic computing.
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Affiliation(s)
- Shengdun Wu
- Research Centre for Frontier Fundamental Studies, Zhejiang Lab, Hangzhou 311100, China
| | - Haiping Huang
- PMI Lab, School of Physics, Sun Yat-sen University, Guangzhou 510275, China
| | - Shengjun Wang
- Department of Physics, Shaanxi Normal University, Xi’an 710119, China
| | - Guozhang Chen
- National Key Laboratory for Multimedia Information Processing, School of Computer Science, Peking University, Beijing, China
| | - Changsong Zhou
- Department of Physics, Hong Kong Baptist University, Kowloon Tong, Hong Kong, China
| | - Dongping Yang
- Research Centre for Frontier Fundamental Studies, Zhejiang Lab, Hangzhou 311100, China
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42
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Sun Y, Yu N, Zhang J, Yang B. Advances in Microfluidic Single-Cell RNA Sequencing and Spatial Transcriptomics. MICROMACHINES 2025; 16:426. [PMID: 40283301 PMCID: PMC12029715 DOI: 10.3390/mi16040426] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/25/2024] [Revised: 11/22/2024] [Accepted: 11/25/2024] [Indexed: 04/29/2025]
Abstract
The development of micro- and nano-fabrication technologies has greatly advanced single-cell and spatial omics technologies. With the advantages of integration and compartmentalization, microfluidic chips are capable of generating high-throughput parallel reaction systems for single-cell screening and analysis. As omics technologies improve, microfluidic chips can now integrate promising transcriptomics technologies, providing new insights from molecular characterization for tissue gene expression profiles and further revealing the static and even dynamic processes of tissues in homeostasis and disease. Here, we survey the current landscape of microfluidic methods in the field of single-cell and spatial multi-omics, as well as assessing their relative advantages and limitations. We highlight how microfluidics has been adapted and improved to provide new insights into multi-omics over the past decade. Last, we emphasize the contributions of microfluidic-based omics methods in development, neuroscience, and disease mechanisms, as well as further revealing some perspectives for technological advances in translational and clinical medicine.
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Affiliation(s)
- Yueqiu Sun
- State Key Laboratory of Supramolecular Structure and Materials, College of Chemistry, Jilin University, Changchun 130000, China
- Joint Laboratory of Opto-Functional Theranostics in Medicine and Chemistry, The First Hospital of Jilin University, Jilin University, Changchun 130000, China
| | - Nianzuo Yu
- State Key Laboratory of Supramolecular Structure and Materials, College of Chemistry, Jilin University, Changchun 130000, China
- Joint Laboratory of Opto-Functional Theranostics in Medicine and Chemistry, The First Hospital of Jilin University, Jilin University, Changchun 130000, China
| | - Junhu Zhang
- State Key Laboratory of Supramolecular Structure and Materials, College of Chemistry, Jilin University, Changchun 130000, China
- Joint Laboratory of Opto-Functional Theranostics in Medicine and Chemistry, The First Hospital of Jilin University, Jilin University, Changchun 130000, China
| | - Bai Yang
- State Key Laboratory of Supramolecular Structure and Materials, College of Chemistry, Jilin University, Changchun 130000, China
- Joint Laboratory of Opto-Functional Theranostics in Medicine and Chemistry, The First Hospital of Jilin University, Jilin University, Changchun 130000, China
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43
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Poquérusse J, Whitford W, Taylor J, Gregersen N, Love DR, Tsang B, Drake KM, Snell RG, Lehnert K, Jacobsen JC. Germline mosaicism in TCF20-associated neurodevelopmental disorders: a case study and literature review. J Hum Genet 2025; 70:215-222. [PMID: 40011607 PMCID: PMC11882450 DOI: 10.1038/s10038-025-01323-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2024] [Revised: 02/05/2025] [Accepted: 02/06/2025] [Indexed: 02/28/2025]
Abstract
Autosomal dominant variants in transcription factor 20 (TCF20) can result in TCF20-associated neurodevelopmental disorder (TAND), a condition characterized by developmental delay and intellectual disability, autism, dysmorphisms, dystonia, and variable other neurological features. To date, a total of 91 individuals with TAND have been reported; ~67% of cases arose de novo, while ~10% were inherited, and, intriguingly, ~8% were either confirmed or suspected to have arisen via germline mosaicism. Here, we describe two siblings with a developmental condition characterized by intellectual disability, autism, a circadian rhythm sleep disorder, and attention deficit hyperactivity disorder (ADHD) caused by a novel heterozygous single nucleotide deletion in the TCF20 gene, NM_001378418.1:c.4737del; NP_001365347.1:p.Lys1579Asnfs*36 (GRCh38/hg38). The variant was not detected in DNA extracted from peripheral blood in either parent by Sanger sequencing of PCR-generated amplicons, or by deep sequencing of PCR amplicons using MiSeq and MinION. However, droplet digital PCR (ddPCR) of DNA derived from early morning urine detected the variation in 3.2% of the father's urothelial cells, confirming germline mosaicism. This report is only the second to confirm with physical evidence TCF20 germline mosaicism and discusses germline mosaicism as a likely under-detected mode of inheritance in neurodevelopmental conditions.
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Affiliation(s)
- Jessie Poquérusse
- School of Biological Sciences, The University of Auckland, Auckland, New Zealand
- Centre for Brain Research, The University of Auckland, Auckland, New Zealand
| | - Whitney Whitford
- School of Biological Sciences, The University of Auckland, Auckland, New Zealand
- Centre for Brain Research, The University of Auckland, Auckland, New Zealand
| | - Juliet Taylor
- Genetic Health Service New Zealand, Auckland City Hospital, Auckland, New Zealand
| | - Nerine Gregersen
- Genetic Health Service New Zealand, Auckland City Hospital, Auckland, New Zealand
| | - Donald R Love
- Diagnostic Genetics, LabPLUS, Auckland City Hospital, Auckland, New Zealand
- Genetic Pathology, Sidra Medicine, Doha, Qatar
| | - Bobby Tsang
- Pediatrics and Newborn Services, Waitakere Hospital, Auckland, New Zealand
| | - Kylie M Drake
- Canterbury Health Laboratories, Christchurch, New Zealand
| | - Russell G Snell
- School of Biological Sciences, The University of Auckland, Auckland, New Zealand
- Centre for Brain Research, The University of Auckland, Auckland, New Zealand
| | - Klaus Lehnert
- School of Biological Sciences, The University of Auckland, Auckland, New Zealand
- Centre for Brain Research, The University of Auckland, Auckland, New Zealand
| | - Jessie C Jacobsen
- School of Biological Sciences, The University of Auckland, Auckland, New Zealand.
- Centre for Brain Research, The University of Auckland, Auckland, New Zealand.
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44
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Li L, Guo Y, Jing W, Tang X, Zeng J, Hou Z, Song Y, He A, Li H, Zhu L, Lu Y, Li X. Cell-Type Specific Circuits in the Mammillary Body for Place and Object Recognition Memory. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2025; 12:e2409397. [PMID: 39928529 PMCID: PMC11967786 DOI: 10.1002/advs.202409397] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/08/2024] [Revised: 01/16/2025] [Indexed: 02/12/2025]
Abstract
Mammillary body (MB) is traditionally viewed as a structural node of an anatomic circuit for emotion and memory. However, little is known about its molecular and cellular organizations. Here, a discovery that MB contains four subtypes of neurons that occupy different spatial subregions is reported. Of these, two subtypes of neurons are tagged by parvalbumin (PV) and dopamine receptor-D2 (Drd2) markers. PV neurons are spontaneously active, whereas Drd2 neurons are inactive at rest and generate rebound bursts. These two distinct electrophysiological properties are encoded by Kcnn4 and Cacna1h. PV and Drd2 neurons generate two distinct cell-type specific circuits by receiving inputs from two discrete subiculum neuronal classes. Gain- and loss-of-function studies on these cortical-subcortical circuits demonstrate their differential roles for place and object recognition memory. This finding provides a comprehensive molecular and structural atlas of MB neurons at single-cell resolution and reveals that MB contains molecularly, structurally, and functionally dissociable streams within its serial architecture.
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Affiliation(s)
- Lanfang Li
- Wuhan Center of Brain ScienceHuazhong University of Science and TechnologyWuhan430030China
- Innovation Center of Brain Medical SciencesMinistry of Education of the People's Republic of ChinaWuhan430030China
- Department of PathophysiologySchool of Basic Medicine and Tongji Medical CollegeHuazhong University of Science and TechnologyWuhan430030China
| | - Yiqing Guo
- Wuhan Center of Brain ScienceHuazhong University of Science and TechnologyWuhan430030China
- Innovation Center of Brain Medical SciencesMinistry of Education of the People's Republic of ChinaWuhan430030China
- Department of PathophysiologySchool of Basic Medicine and Tongji Medical CollegeHuazhong University of Science and TechnologyWuhan430030China
| | - Wei Jing
- Wuhan Center of Brain ScienceHuazhong University of Science and TechnologyWuhan430030China
- Innovation Center of Brain Medical SciencesMinistry of Education of the People's Republic of ChinaWuhan430030China
- Department of AnatomySchool of Basic Medicine and Tongji Medical CollegeHuazhong University of Science and TechnologyWuhan430030China
| | - Xiaomei Tang
- Wuhan Center of Brain ScienceHuazhong University of Science and TechnologyWuhan430030China
- Innovation Center of Brain Medical SciencesMinistry of Education of the People's Republic of ChinaWuhan430030China
- Department of PathophysiologySchool of Basic Medicine and Tongji Medical CollegeHuazhong University of Science and TechnologyWuhan430030China
| | - Jinyu Zeng
- Wuhan Center of Brain ScienceHuazhong University of Science and TechnologyWuhan430030China
- Innovation Center of Brain Medical SciencesMinistry of Education of the People's Republic of ChinaWuhan430030China
- Department of PathophysiologySchool of Basic Medicine and Tongji Medical CollegeHuazhong University of Science and TechnologyWuhan430030China
| | - Zhenye Hou
- Wuhan Center of Brain ScienceHuazhong University of Science and TechnologyWuhan430030China
- Innovation Center of Brain Medical SciencesMinistry of Education of the People's Republic of ChinaWuhan430030China
- Department of PathophysiologySchool of Basic Medicine and Tongji Medical CollegeHuazhong University of Science and TechnologyWuhan430030China
| | - Yige Song
- Wuhan Center of Brain ScienceHuazhong University of Science and TechnologyWuhan430030China
- Innovation Center of Brain Medical SciencesMinistry of Education of the People's Republic of ChinaWuhan430030China
- Department of PathophysiologySchool of Basic Medicine and Tongji Medical CollegeHuazhong University of Science and TechnologyWuhan430030China
| | - Aodi He
- Wuhan Center of Brain ScienceHuazhong University of Science and TechnologyWuhan430030China
- Innovation Center of Brain Medical SciencesMinistry of Education of the People's Republic of ChinaWuhan430030China
- Department of AnatomySchool of Basic Medicine and Tongji Medical CollegeHuazhong University of Science and TechnologyWuhan430030China
| | - Hao Li
- Wuhan Center of Brain ScienceHuazhong University of Science and TechnologyWuhan430030China
- Innovation Center of Brain Medical SciencesMinistry of Education of the People's Republic of ChinaWuhan430030China
- Department of PathophysiologySchool of Basic Medicine and Tongji Medical CollegeHuazhong University of Science and TechnologyWuhan430030China
| | - Ling‐Qiang Zhu
- Wuhan Center of Brain ScienceHuazhong University of Science and TechnologyWuhan430030China
- Innovation Center of Brain Medical SciencesMinistry of Education of the People's Republic of ChinaWuhan430030China
- Department of PathophysiologySchool of Basic Medicine and Tongji Medical CollegeHuazhong University of Science and TechnologyWuhan430030China
| | - Youming Lu
- Wuhan Center of Brain ScienceHuazhong University of Science and TechnologyWuhan430030China
- Innovation Center of Brain Medical SciencesMinistry of Education of the People's Republic of ChinaWuhan430030China
- Department of PhysiologySchool of Basic Medicine and Tongji Medical CollegeHuazhong University of Science and TechnologyWuhan4030030China
| | - Xinyan Li
- Wuhan Center of Brain ScienceHuazhong University of Science and TechnologyWuhan430030China
- Innovation Center of Brain Medical SciencesMinistry of Education of the People's Republic of ChinaWuhan430030China
- Department of AnatomySchool of Basic Medicine and Tongji Medical CollegeHuazhong University of Science and TechnologyWuhan430030China
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45
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Yang J, Zheng Z, Jiao Y, Yu K, Bhatara S, Yang X, Natarajan S, Zhang J, Pan Q, Easton J, Yan KK, Peng J, Liu K, Yu J. Spotiphy enables single-cell spatial whole transcriptomics across an entire section. Nat Methods 2025; 22:724-736. [PMID: 40074951 PMCID: PMC11978521 DOI: 10.1038/s41592-025-02622-5] [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: 03/13/2024] [Accepted: 01/29/2025] [Indexed: 03/14/2025]
Abstract
Spatial transcriptomics (ST) has advanced our understanding of tissue regionalization by enabling the visualization of gene expression within whole-tissue sections, but current approaches remain plagued by the challenge of achieving single-cell resolution without sacrificing whole-genome coverage. Here we present Spotiphy (spot imager with pseudo-single-cell-resolution histology), a computational toolkit that transforms sequencing-based ST data into single-cell-resolved whole-transcriptome images. Spotiphy delivers the most precise cellular proportions in extensive benchmarking evaluations. Spotiphy-derived inferred single-cell profiles reveal astrocyte and disease-associated microglia regional specifications in Alzheimer's disease and healthy mouse brains. Spotiphy identifies multiple spatial domains and alterations in tumor-tumor microenvironment interactions in human breast ST data. Spotiphy bridges the information gap and enables visualization of cell localization and transcriptomic profiles throughout entire sections, offering highly informative outputs and an innovative spatial analysis pipeline for exploring complex biological systems.
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Affiliation(s)
- Jiyuan Yang
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Ziqian Zheng
- Department of Industrial & Systems Engineering, University of Wisconsin-Madison, Madison, WI, USA
| | - Yun Jiao
- Department of Structural Biology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Kaiwen Yu
- Center of Proteomics and Metabolomics, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Sheetal Bhatara
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Xu Yang
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Sivaraman Natarajan
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Jiahui Zhang
- Department of Industrial & Systems Engineering, University of Wisconsin-Madison, Madison, WI, USA
| | - Qingfei Pan
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - John Easton
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Koon-Kiu Yan
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Junmin Peng
- Department of Structural Biology, St. Jude Children's Research Hospital, Memphis, TN, USA.
| | - Kaibo Liu
- Department of Industrial & Systems Engineering, University of Wisconsin-Madison, Madison, WI, USA.
| | - Jiyang Yu
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN, USA.
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46
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Li Y, Dang X, Chen R, Teng Z, Wang J, Li S, Yue Y, Mitchell BL, Zeng Y, Yao YG, Li M, Liu Z, Yuan Y, Li T, Zhang Z, Luo XJ. Cross-ancestry genome-wide association study and systems-level integrative analyses implicate new risk genes and therapeutic targets for depression. Nat Hum Behav 2025; 9:806-823. [PMID: 39994458 DOI: 10.1038/s41562-024-02073-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2024] [Accepted: 10/23/2024] [Indexed: 02/26/2025]
Abstract
Deciphering the genetic architecture of depression is pivotal for characterizing the associated pathophysiological processes and development of new therapeutics. Here we conducted a cross-ancestry genome-wide meta-analysis on depression (416,437 cases and 1,308,758 controls) and identified 287 risk loci, of which 49 are new. Variant-level fine mapping prioritized potential causal variants and functional genomic analysis identified variants that regulate the binding of transcription factors. We validated that 80% of the identified functional variants are regulatory variants, and expression quantitative trait loci analysis uncovered the potential target genes regulated by the prioritized risk variants. Gene-level analysis, including transcriptome and proteome-wide association studies, colocalization and Mendelian randomization-based analyses, prioritized potential causal genes and drug targets. Gene prioritization analyses highlighted likely causal genes, including TMEM106B, CTNND1, AREL1 and so on. Pathway analysis indicated significant enrichment of depression risk genes in synapse-related pathways. Finally, knockdown of Tmem106b in mice resulted in depression-like behaviours, supporting the involvement of Tmem106b in depression. Our study identified new risk loci, likely causal variants and genes for depression, providing important insights into the genetic architecture of depression and potential therapeutic targets.
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Affiliation(s)
- Yifan Li
- Department of Psychiatry and Psychosomatics, Zhongda Hospital, School of Medicine, Advanced Institute for Life and Health, Jiangsu Provincial Key Laboratory of Brain Science and Medicine, Southeast University, Nanjing, China
| | - Xinglun Dang
- Department of Psychiatry and Psychosomatics, Zhongda Hospital, School of Medicine, Advanced Institute for Life and Health, Jiangsu Provincial Key Laboratory of Brain Science and Medicine, Southeast University, Nanjing, China
| | - Rui Chen
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Zhaowei Teng
- Key Laboratory of Neurological and Psychiatric Disease Research of Yunnan Province, The Second Affiliated Hospital of Kunming Medical University, Yunnan Provincial Department of Education Gut Microbiota Transplantation Engineering Research Center, Kunming, China
| | - Junyang Wang
- Department of Human Anatomy, School of Basic Medical Sciences, Zhengzhou University, Zhengzhou, China
| | - Shiwu Li
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Yingying Yue
- Department of Psychiatry and Psychosomatics, Zhongda Hospital, School of Medicine, Advanced Institute for Life and Health, Jiangsu Provincial Key Laboratory of Brain Science and Medicine, Southeast University, Nanjing, China
| | - Brittany L Mitchell
- Mental Health and Neuroscience Program, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Yong Zeng
- Key Laboratory of Neurological and Psychiatric Disease Research of Yunnan Province, The Second Affiliated Hospital of Kunming Medical University, Yunnan Provincial Department of Education Gut Microbiota Transplantation Engineering Research Center, Kunming, China
| | - Yong-Gang Yao
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Ming Li
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Zhongchun Liu
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, China
- Taikang Center for Life and Medical Sciences, Wuhan University, Wuhan, China
| | - Yonggui Yuan
- Department of Psychiatry and Psychosomatics, Zhongda Hospital, School of Medicine, Advanced Institute for Life and Health, Jiangsu Provincial Key Laboratory of Brain Science and Medicine, Southeast University, Nanjing, China.
| | - Tao Li
- Affiliated Mental Health Center, Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, China.
| | - Zhijun Zhang
- Department of Psychiatry and Psychosomatics, Zhongda Hospital, School of Medicine, Advanced Institute for Life and Health, Jiangsu Provincial Key Laboratory of Brain Science and Medicine, Southeast University, Nanjing, China.
- Department of Mental Health and Public Health, Faculty of Life and Health Sciences, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
| | - Xiong-Jian Luo
- Department of Psychiatry and Psychosomatics, Zhongda Hospital, School of Medicine, Advanced Institute for Life and Health, Jiangsu Provincial Key Laboratory of Brain Science and Medicine, Southeast University, Nanjing, China.
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47
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Tagore S, Caprio L, Amin AD, Bestak K, Luthria K, D'Souza E, Barrera I, Melms JC, Wu S, Abuzaid S, Wang Y, Jakubikova V, Koch P, Brodtman DZ, Bawa B, Deshmukh SK, Ebel L, Ibarra-Arellano MA, Jaiswal A, Gurjao C, Biermann J, Shaikh N, Ramaradj P, Georgis Y, Lagos GG, Ehrlich MI, Ho P, Walsh ZH, Rogava M, Politis MG, Biswas D, Cottarelli A, Rizvi N, Shu CA, Herzberg B, Anandasabapathy N, Sledge G, Zorn E, Canoll P, Bruce JN, Rizvi NA, Taylor AM, Saqi A, Hibshoosh H, Schwartz GK, Henick BS, Chen F, Schapiro D, Shah P, Izar B. Single-cell and spatial genomic landscape of non-small cell lung cancer brain metastases. Nat Med 2025; 31:1351-1363. [PMID: 40016452 DOI: 10.1038/s41591-025-03530-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2023] [Accepted: 01/19/2025] [Indexed: 03/01/2025]
Abstract
Brain metastases frequently develop in patients with non-small cell lung cancer (NSCLC) and are a common cause of cancer-related deaths, yet our understanding of the underlying human biology is limited. Here we performed multimodal single-nucleus RNA and T cell receptor, single-cell spatial and whole-genome sequencing of brain metastases and primary tumors of patients with treatment-naive NSCLC. Chromosomal instability (CIN) is a distinguishing genomic feature of brain metastases compared with primary tumors, which we validated through integrated analysis of molecular profiling and clinical data in 4,869 independent patients, and a new cohort of 12,275 patients with NSCLC. Unbiased analyses revealed transcriptional neural-like programs that strongly enriched in cancer cells from brain metastases, including a recurring, CINhigh cell subpopulation that preexists in primary tumors but strongly enriched in brain metastases, which was also recovered in matched single-cell spatial transcriptomics. Using multiplexed immunofluorescence in an independent cohort of treatment-naive pairs of primary tumors and brain metastases from the same patients with NSCLC, we validated genomic and tumor-microenvironmental findings and identified a cancer cell population characterized by neural features strongly enriched in brain metastases. This comprehensive analysis provides insights into human NSCLC brain metastasis biology and serves as an important resource for additional discovery.
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Affiliation(s)
- Somnath Tagore
- Division of Hematology/Oncology, Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY, USA
- Department of Systems Biology, Program for Mathematical Genomics, Columbia University, New York, NY, USA
- Vagelos College of Physicians and Surgeons, Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY, USA
| | - Lindsay Caprio
- Division of Hematology/Oncology, Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY, USA
- Vagelos College of Physicians and Surgeons, Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY, USA
- Columbia Center for Translational Immunology, Columbia University Irving Medical Center, New York, NY, USA
| | - Amit Dipak Amin
- Division of Hematology/Oncology, Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY, USA
- Vagelos College of Physicians and Surgeons, Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY, USA
- Columbia Center for Translational Immunology, Columbia University Irving Medical Center, New York, NY, USA
| | - Kresimir Bestak
- Institute for Computational Biomedicine, Faculty of Medicine, University Hospital Heidelberg and Heidelberg University, Heidelberg, Germany
| | - Karan Luthria
- Division of Hematology/Oncology, Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY, USA
- Vagelos College of Physicians and Surgeons, Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY, USA
- Columbia Center for Translational Immunology, Columbia University Irving Medical Center, New York, NY, USA
| | - Edridge D'Souza
- Division of Hematology/Oncology, Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY, USA
- Vagelos College of Physicians and Surgeons, Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY, USA
- Columbia Center for Translational Immunology, Columbia University Irving Medical Center, New York, NY, USA
| | - Irving Barrera
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, USA
| | - Johannes C Melms
- Division of Hematology/Oncology, Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY, USA
- Vagelos College of Physicians and Surgeons, Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY, USA
- Columbia Center for Translational Immunology, Columbia University Irving Medical Center, New York, NY, USA
| | - Sharon Wu
- Caris Life Sciences, Phoenix, AZ, USA
| | - Sinan Abuzaid
- Division of Hematology/Oncology, Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY, USA
- Vagelos College of Physicians and Surgeons, Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY, USA
| | - Yiping Wang
- Division of Hematology/Oncology, Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY, USA
- Department of Systems Biology, Program for Mathematical Genomics, Columbia University, New York, NY, USA
- Vagelos College of Physicians and Surgeons, Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY, USA
- Columbia Center for Translational Immunology, Columbia University Irving Medical Center, New York, NY, USA
| | - Viktoria Jakubikova
- Division of Hematology/Oncology, Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY, USA
- Vagelos College of Physicians and Surgeons, Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY, USA
| | - Peter Koch
- Division of Hematology/Oncology, Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY, USA
- Vagelos College of Physicians and Surgeons, Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY, USA
| | - D Zack Brodtman
- Division of Hematology/Oncology, Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY, USA
- Vagelos College of Physicians and Surgeons, Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY, USA
| | - Banpreet Bawa
- Division of Hematology/Oncology, Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY, USA
- Vagelos College of Physicians and Surgeons, Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY, USA
| | | | - Leon Ebel
- Division of Hematology/Oncology, Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY, USA
- Vagelos College of Physicians and Surgeons, Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY, USA
- Columbia Center for Translational Immunology, Columbia University Irving Medical Center, New York, NY, USA
| | - Miguel A Ibarra-Arellano
- Institute for Computational Biomedicine, Faculty of Medicine, University Hospital Heidelberg and Heidelberg University, Heidelberg, Germany
| | - Abhinav Jaiswal
- Department of Dermatology, Immunology and Microbial Pathogenesis Program, Weill Cornell Medicine, New York, NY, USA
| | - Carino Gurjao
- Division of Hematology/Oncology, Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY, USA
- Department of Systems Biology, Program for Mathematical Genomics, Columbia University, New York, NY, USA
- Vagelos College of Physicians and Surgeons, Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY, USA
- Columbia Center for Translational Immunology, Columbia University Irving Medical Center, New York, NY, USA
| | - Jana Biermann
- Division of Hematology/Oncology, Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY, USA
- Department of Systems Biology, Program for Mathematical Genomics, Columbia University, New York, NY, USA
- Vagelos College of Physicians and Surgeons, Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY, USA
- Columbia Center for Translational Immunology, Columbia University Irving Medical Center, New York, NY, USA
| | - Neha Shaikh
- Division of Hematology/Oncology, Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY, USA
- Vagelos College of Physicians and Surgeons, Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY, USA
| | - Priyanka Ramaradj
- Division of Hematology/Oncology, Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY, USA
- Vagelos College of Physicians and Surgeons, Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY, USA
| | - Yohanna Georgis
- Vagelos College of Physicians and Surgeons, Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY, USA
- Department of Pathology and Cell Biology, Columbia University Irving Medical Center, New York, NY, USA
| | - Galina G Lagos
- Lifespan Cancer Institute, The Warren Alpert Medical School of Brown University, Providence, RI, USA
| | - Matthew I Ehrlich
- Division of Hematology/Oncology, Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY, USA
| | - Patricia Ho
- Division of Hematology/Oncology, Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY, USA
- Vagelos College of Physicians and Surgeons, Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY, USA
- Columbia Center for Translational Immunology, Columbia University Irving Medical Center, New York, NY, USA
| | - Zachary H Walsh
- Division of Hematology/Oncology, Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY, USA
- Vagelos College of Physicians and Surgeons, Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY, USA
- Columbia Center for Translational Immunology, Columbia University Irving Medical Center, New York, NY, USA
| | - Meri Rogava
- Division of Hematology/Oncology, Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY, USA
- Vagelos College of Physicians and Surgeons, Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY, USA
- Columbia Center for Translational Immunology, Columbia University Irving Medical Center, New York, NY, USA
| | - Michelle Garlin Politis
- Department of Pathology and Cell Biology, Columbia University Irving Medical Center, New York, NY, USA
| | - Devanik Biswas
- Vagelos College of Physicians and Surgeons, Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY, USA
| | - Azzurra Cottarelli
- Division of Hematology/Oncology, Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY, USA
| | - Nikhil Rizvi
- Division of Hematology/Oncology, Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY, USA
| | - Catherine A Shu
- Division of Hematology/Oncology, Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY, USA
- Vagelos College of Physicians and Surgeons, Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY, USA
| | - Benjamin Herzberg
- Division of Hematology/Oncology, Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY, USA
- Vagelos College of Physicians and Surgeons, Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY, USA
| | - Niroshana Anandasabapathy
- Department of Dermatology, Immunology and Microbial Pathogenesis Program, Weill Cornell Medicine, New York, NY, USA
| | | | - Emmanuel Zorn
- Columbia Center for Translational Immunology, Columbia University Irving Medical Center, New York, NY, USA
| | - Peter Canoll
- Department of Pathology and Cell Biology, Columbia University Irving Medical Center, New York, NY, USA
| | - Jeffrey N Bruce
- Department of Neurological Surgery, New York Presbyterian/Columbia University Irving Medical Center, New York, NY, USA
| | - Naiyer A Rizvi
- Division of Hematology/Oncology, Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY, USA
- Vagelos College of Physicians and Surgeons, Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY, USA
- Synthekine Inc., Menlo Park, CA, USA
| | - Alison M Taylor
- Vagelos College of Physicians and Surgeons, Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY, USA
- Department of Pathology and Cell Biology, Columbia University Irving Medical Center, New York, NY, USA
| | - Anjali Saqi
- Vagelos College of Physicians and Surgeons, Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY, USA
- Department of Pathology and Cell Biology, Columbia University Irving Medical Center, New York, NY, USA
| | - Hanina Hibshoosh
- Vagelos College of Physicians and Surgeons, Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY, USA
- Department of Pathology and Cell Biology, Columbia University Irving Medical Center, New York, NY, USA
| | - Gary K Schwartz
- Division of Hematology/Oncology, Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY, USA
- Vagelos College of Physicians and Surgeons, Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY, USA
| | - Brian S Henick
- Division of Hematology/Oncology, Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY, USA
- Vagelos College of Physicians and Surgeons, Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY, USA
| | - Fei Chen
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, USA
| | - Denis Schapiro
- Institute for Computational Biomedicine, Faculty of Medicine, University Hospital Heidelberg and Heidelberg University, Heidelberg, Germany
- Institute of Pathology, University Hospital Heidelberg, Heidelberg, Germany
- Translational Spatial Profiling Center (TPSC), Heidelberg, Germany
| | - Parin Shah
- Division of Hematology/Oncology, Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY, USA
- Vagelos College of Physicians and Surgeons, Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY, USA
| | - Benjamin Izar
- Division of Hematology/Oncology, Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY, USA.
- Department of Systems Biology, Program for Mathematical Genomics, Columbia University, New York, NY, USA.
- Vagelos College of Physicians and Surgeons, Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY, USA.
- Columbia Center for Translational Immunology, Columbia University Irving Medical Center, New York, NY, USA.
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48
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Zhu M, Peng J, Wang M, Lin S, Zhang H, Zhou Y, Dai X, Zhao H, Yu YQ, Shen L, Li XM, Chen J. Transcriptomic and spatial GABAergic neuron subtypes in zona incerta mediate distinct innate behaviors. Nat Commun 2025; 16:3107. [PMID: 40169544 PMCID: PMC11961626 DOI: 10.1038/s41467-025-57896-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2024] [Accepted: 03/03/2025] [Indexed: 04/03/2025] Open
Abstract
Understanding the anatomical connection and behaviors of transcriptomic neuron subtypes is critical to delineating cell type-specific functions in the brain. Here we integrated single-nucleus transcriptomic sequencing, in vivo circuit mapping, optogenetic and chemogenetic approaches to dissect the molecular identity and function of heterogeneous GABAergic neuron populations in the zona incerta (ZI) in mice, a region involved in modulating various behaviors. By microdissecting ZI for transcriptomic and spatial gene expression analyses, our results revealed two non-overlapping Ecel1- and Pde11a-expressing GABAergic neurons with dominant expression in the rostral and medial zona incerta (ZIrEcel1 and ZImPde11a), respectively. The GABAergic projection from ZIrEcel1 to periaqueductal gray mediates self-grooming, while the GABAergic projection from ZImPde11a to the oral part of pontine reticular formation promotes transition from sleep to wakefulness. Together, our results revealed the molecular markers, spatial organization and specific neuronal circuits of two discrete GABAergic projection neuron populations in segregated subregions of the ZI that mediate distinct innate behaviors, advancing our understanding of the functional organization of the brain.
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Affiliation(s)
- Mengyue Zhu
- Department of Neurobiology, Departments of Neurosurgery and Neurology of the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310058, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, MOE Frontier Science Center for Brain Research and Brain-machine Integration, School of Brain Science and Brain Medicine, Zhejiang University, Hangzhou, 310058, China
| | - Jieqiao Peng
- Department of Neurobiology, Departments of Neurosurgery and Neurology of the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310058, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, MOE Frontier Science Center for Brain Research and Brain-machine Integration, School of Brain Science and Brain Medicine, Zhejiang University, Hangzhou, 310058, China
| | - Mi Wang
- Department of Neurobiology, Departments of Neurosurgery and Neurology of the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310058, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, MOE Frontier Science Center for Brain Research and Brain-machine Integration, School of Brain Science and Brain Medicine, Zhejiang University, Hangzhou, 310058, China
| | - Shan Lin
- Department of Neurobiology, Departments of Neurosurgery and Neurology of the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310058, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, MOE Frontier Science Center for Brain Research and Brain-machine Integration, School of Brain Science and Brain Medicine, Zhejiang University, Hangzhou, 310058, China
| | - Huiying Zhang
- The MOE Key Laboratory of Biosystems Homeostasis & Protection and Zhejiang Provincial Key Laboratory for Cancer Molecular Cell Biology, Life Sciences Institute, Zhejiang University, Hangzhou, 310058, China
| | - Yu Zhou
- Department of Neurobiology, Departments of Neurosurgery and Neurology of the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310058, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, MOE Frontier Science Center for Brain Research and Brain-machine Integration, School of Brain Science and Brain Medicine, Zhejiang University, Hangzhou, 310058, China
| | - Xinyue Dai
- Department of Neurobiology, Departments of Neurosurgery and Neurology of the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310058, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, MOE Frontier Science Center for Brain Research and Brain-machine Integration, School of Brain Science and Brain Medicine, Zhejiang University, Hangzhou, 310058, China
| | - Huiying Zhao
- Department of Neurobiology, Departments of Neurosurgery and Neurology of the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310058, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, MOE Frontier Science Center for Brain Research and Brain-machine Integration, School of Brain Science and Brain Medicine, Zhejiang University, Hangzhou, 310058, China
| | - Yan-Qin Yu
- Department of Neurobiology, Departments of Neurosurgery and Neurology of the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310058, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, MOE Frontier Science Center for Brain Research and Brain-machine Integration, School of Brain Science and Brain Medicine, Zhejiang University, Hangzhou, 310058, China
- Nanhu Brain-computer Interface Institute, Hangzhou, 311100, China
| | - Li Shen
- The MOE Key Laboratory of Biosystems Homeostasis & Protection and Zhejiang Provincial Key Laboratory for Cancer Molecular Cell Biology, Life Sciences Institute, Zhejiang University, Hangzhou, 310058, China
| | - Xiao-Ming Li
- Department of Neurobiology, Departments of Neurosurgery and Neurology of the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310058, China.
- NHC and CAMS Key Laboratory of Medical Neurobiology, MOE Frontier Science Center for Brain Research and Brain-machine Integration, School of Brain Science and Brain Medicine, Zhejiang University, Hangzhou, 310058, China.
- Nanhu Brain-computer Interface Institute, Hangzhou, 311100, China.
- Center for Brain Science and Brain-Inspired Intelligence, Research Units for Emotion and Emotion Disorders, Chinese Academy of Medical Sciences, Hangzhou, China.
- Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence, Guangzhou, 311305, China.
| | - Jiadong Chen
- Department of Neurobiology, Departments of Neurosurgery and Neurology of the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310058, China.
- NHC and CAMS Key Laboratory of Medical Neurobiology, MOE Frontier Science Center for Brain Research and Brain-machine Integration, School of Brain Science and Brain Medicine, Zhejiang University, Hangzhou, 310058, China.
- Nanhu Brain-computer Interface Institute, Hangzhou, 311100, China.
- Key Laboratory of Precise Treatment and Clinical Translational Research of Neurological Diseases, Hangzhou, 310009, Zhejiang, China.
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49
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Reautschnig P, Fruhner C, Wahn N, Wiegand CP, Kragness S, Yung JF, Hofacker DT, Fisk J, Eidelman M, Waffenschmidt N, Feige M, Pfeiffer LS, Schulz AE, Füll Y, Levanon EY, Mandel G, Stafforst T. Precise in vivo RNA base editing with a wobble-enhanced circular CLUSTER guide RNA. Nat Biotechnol 2025; 43:545-557. [PMID: 38997581 PMCID: PMC11994451 DOI: 10.1038/s41587-024-02313-0] [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: 07/15/2023] [Accepted: 05/17/2024] [Indexed: 07/14/2024]
Abstract
Recruiting the endogenous editing enzyme adenosine deaminase acting on RNA (ADAR) with tailored guide RNAs for adenosine-to-inosine (A-to-I) RNA base editing is promising for safely manipulating genetic information at the RNA level. However, the precision and efficiency of editing are often compromised by bystander off-target editing. Here, we find that in 5'-UAN triplets, which dominate bystander editing, G•U wobble base pairs effectively mitigate off-target events while maintaining high on-target efficiency. This strategy is universally applicable to existing A-to-I RNA base-editing systems and complements other suppression methods such as G•A mismatches and uridine (U) depletion. Combining wobble base pairing with a circularized format of the CLUSTER approach achieves highly precise and efficient editing (up to 87%) of a disease-relevant mutation in the Mecp2 transcript in cell culture. Virus-mediated delivery of the guide RNA alone realizes functional MeCP2 protein restoration in the central nervous system of a murine Rett syndrome model with editing yields of up to 19% and excellent bystander control in vivo.
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Affiliation(s)
- Philipp Reautschnig
- Interfaculty Institute of Biochemistry, Faculty of Science, University of Tübingen, Tübingen, Germany
| | - Carolin Fruhner
- Interfaculty Institute of Biochemistry, Faculty of Science, University of Tübingen, Tübingen, Germany
| | - Nicolai Wahn
- Interfaculty Institute of Biochemistry, Faculty of Science, University of Tübingen, Tübingen, Germany
| | - Charlotte P Wiegand
- Interfaculty Institute of Biochemistry, Faculty of Science, University of Tübingen, Tübingen, Germany
| | - Sabrina Kragness
- Vollum Institute, Oregon Health and Science University, Portland, OR, USA
| | - John F Yung
- Vollum Institute, Oregon Health and Science University, Portland, OR, USA
| | - Daniel T Hofacker
- Interfaculty Institute of Biochemistry, Faculty of Science, University of Tübingen, Tübingen, Germany
| | - Jenna Fisk
- Vollum Institute, Oregon Health and Science University, Portland, OR, USA
| | - Michelle Eidelman
- Mina and Everard Goodman Faculty of Life Sciences, Bar-Ilan University, Ramat Gan, Israel
- The Institute of Nanotechnology and Advanced Materials, Bar-Ilan University, Ramat Gan, Israel
| | - Nils Waffenschmidt
- Interfaculty Institute of Biochemistry, Faculty of Science, University of Tübingen, Tübingen, Germany
| | - Maximilian Feige
- Interfaculty Institute of Biochemistry, Faculty of Science, University of Tübingen, Tübingen, Germany
| | - Laura S Pfeiffer
- Interfaculty Institute of Biochemistry, Faculty of Science, University of Tübingen, Tübingen, Germany
| | - Annika E Schulz
- Interfaculty Institute of Biochemistry, Faculty of Science, University of Tübingen, Tübingen, Germany
| | - Yvonne Füll
- Interfaculty Institute of Biochemistry, Faculty of Science, University of Tübingen, Tübingen, Germany
| | - Erez Y Levanon
- Mina and Everard Goodman Faculty of Life Sciences, Bar-Ilan University, Ramat Gan, Israel
- The Institute of Nanotechnology and Advanced Materials, Bar-Ilan University, Ramat Gan, Israel
| | - Gail Mandel
- Vollum Institute, Oregon Health and Science University, Portland, OR, USA
| | - Thorsten Stafforst
- Interfaculty Institute of Biochemistry, Faculty of Science, University of Tübingen, Tübingen, Germany.
- Gene and RNA Therapy Center (GRTC), Faculty of Medicine, University of Tübingen, Tübingen, Germany.
- iFIT Cluster of Excellence (EXC2180) Image-Guided and Functionally Instructed Tumor Therapies, University of Tübingen, Tübingen, Germany.
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50
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Erdogan CS, Yavuz Y, Ozgun HB, Bilgin VA, Agus S, Kalkan UF, Yilmaz B. Fam163a knockdown and mitochondrial stress in the arcuate nucleus of hypothalamus reduce AgRP neuron activity and differentially regulate mitochondrial dynamics in mice. Acta Physiol (Oxf) 2025; 241:e70020. [PMID: 40071489 PMCID: PMC11897941 DOI: 10.1111/apha.70020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2024] [Revised: 01/21/2025] [Accepted: 02/21/2025] [Indexed: 03/15/2025]
Abstract
AIM Mitochondria play key roles in neuronal activity, particularly in modulating agouti-related protein (AgRP) and proopiomelanocortin (POMC) neurons in the arcuate nucleus of the hypothalamus (ARC), which regulates food intake. FAM163A, a newly identified protein, is suggested to be part of the mitochondrial proteome, though its functions remain largely unknown. This study aimed to investigate the effects of Fam163a knockdown and mitochondrial dysfunction on food intake, AgRP neuron activity, and mitochondrial function in the hypothalamus. METHODS Male C57BL/6 and AgRP-Cre mice received intracranial injections of either Fam163a shRNA, rotenone, or appropriate controls. Behavioral assessments included food intake, locomotor activity, and anxiety-like behaviors. qRT-PCR was used to quantify the expression of the genes related to food intake, mitochondrial biogenesis, dynamics, and oxidative stress. Blood glucose, serum insulin, and leptin levels were measured. Electrophysiological patch-clamp recordings were used to assess the AgRP neuronal activity. RESULTS Fam163a knockdown in the ARC increased the cumulative food intake in short term (first 7 days) without altering the 25-day food intake and significantly increased the Pomc mRNA expression. Fam163a silencing significantly reduced leptin levels. Both Fam163a knockdown and rotenone significantly reduced the firing frequency of AgRP neurons. Neither Fam163a silencing nor rotenone altered locomotor or anxiety-like behaviors. Fam163a knockdown and rotenone differentially altered the expression of mitochondrial biogenesis-, mitophagy-, fusion-, and oxidative stress-related genes. CONCLUSION Hypothalamic FAM163A may play a role in modulating AgRP neuronal activity through regulating mitochondrial biogenesis, dynamics, and redox state. These findings provide insights into the role of FAM163A and mitochondrial stress in the central regulation of metabolism.
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Affiliation(s)
| | - Yavuz Yavuz
- Department of PhysiologyFaculty of Medicine, Yeditepe UniversityIstanbulTurkey
- Department of Neuroscience and PharmacologyThe University of Iowa Carver College of MedicineIowa CityUSA
| | - Huseyin Bugra Ozgun
- Department of PhysiologyFaculty of Medicine, Yeditepe UniversityIstanbulTurkey
| | - Volkan Adem Bilgin
- Department of PhysiologyFaculty of Medicine, Yeditepe UniversityIstanbulTurkey
| | - Sami Agus
- Department of PhysiologyFaculty of Medicine, Yeditepe UniversityIstanbulTurkey
- Department of PhysiologyAugusta UniversityAugustaGeorgiaUSA
| | - Ugur Faruk Kalkan
- Department of PhysiologyFaculty of Medicine, Yeditepe UniversityIstanbulTurkey
| | - Bayram Yilmaz
- Department of PhysiologyFaculty of Medicine, Yeditepe UniversityIstanbulTurkey
- Department of Physiology, Faculty of MedicineDokuz Eylül UniversityIzmirTurkey
- Izmir Biomedicine and Genome CenterIzmirTurkey
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