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Thompson JR, Nelson ED, Tippani M, Ramnauth AD, Divecha HR, Miller RA, Eagles NJ, Pattie EA, Kwon SH, Bach SV, Kaipa UM, Yao J, Hou C, Kleinman JE, Collado-Torres L, Han S, Maynard KR, Hyde TM, Martinowich K, Page SC, Hicks SC. An integrated single-nucleus and spatial transcriptomics atlas reveals the molecular landscape of the human hippocampus. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.26.590643. [PMID: 38712198 PMCID: PMC11071618 DOI: 10.1101/2024.04.26.590643] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2024]
Abstract
The hippocampus contains many unique cell types, which serve the structure's specialized functions, including learning, memory and cognition. These cells have distinct spatial organization, morphology, physiology, and connectivity, highlighting the importance of transcriptome-wide profiling strategies that retain cytoarchitectural organization. Here, we generated spatially-resolved transcriptomics (SRT) and single-nucleus RNA-sequencing (snRNA-seq) data from adjacent tissue sections of the anterior human hippocampus in ten adult neurotypical donors to define molecular profiles for hippocampal cell types and spatial domains. Using non-negative matrix factorization (NMF) and label transfer, we integrated these data by defining gene expression patterns within the snRNA-seq data and inferring their expression in the SRT data. We identified NMF patterns that captured transcriptional variation across neuronal cell types and indicated that the response of excitatory and inhibitory postsynaptic specializations were prioritized in different SRT spatial domains. We used the NMF and label transfer approach to leverage existing rodent datasets, identifying patterns of activity-dependent transcription and subpopulations of dentate gyrus granule cells in our SRT dataset that may be predisposed to participate in learning and memory ensembles. Finally, we characterized the spatial organization of NMF patterns corresponding to non-cornu ammonis pyramidal neurons and identified snRNA-seq clusters mapping to distinct regions of the retrohippocampus, to three subiculum layers, and to a population of presubiculum neurons. To make this comprehensive molecular atlas accessible to the scientific community, both raw and processed data are freely available, including through interactive web applications.
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Affiliation(s)
- Jacqueline R. Thompson
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Erik D. Nelson
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
- Cellular and Molecular Medicine Graduate Program, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Madhavi Tippani
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
| | - Anthony D. Ramnauth
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
- Solomon H. Snyder Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Heena R. Divecha
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
| | - Ryan A. Miller
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
| | - Nicholas J. Eagles
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
| | - Elizabeth A. Pattie
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
| | - Sang Ho Kwon
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
- Solomon H. Snyder Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore, MD, USA
- Biochemistry, Cellular, and Molecular Biology Graduate Program, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Svitlana V. Bach
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Uma M. Kaipa
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
| | - Jianing Yao
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Christine Hou
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Joel E. Kleinman
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Leonardo Collado-Torres
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
| | - Shizhong Han
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, MD, USA
- Department of Genetic Medicine, Johns Hopkins School of Medicine, MD, USA
| | - Kristen R. Maynard
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
- Solomon H. Snyder Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore, MD, USA
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Thomas M. Hyde
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, MD, USA
- Department of Neurology, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Keri Martinowich
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
- Solomon H. Snyder Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore, MD, USA
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, MD, USA
- Department of Genetic Medicine, Johns Hopkins School of Medicine, MD, USA
- Johns Hopkins Kavli Neuroscience Discovery Institute, Baltimore, MD, USA
| | - Stephanie C. Page
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Stephanie C. Hicks
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
- Center for Computational Biology, Johns Hopkins University, Baltimore, MD, USA
- Malone Center for Engineering in Healthcare, Johns Hopkins University, Baltimore, MD, USA
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Steyn C, Mishi R, Fillmore S, Verhoog MB, More J, Rohlwink UK, Melvill R, Butler J, Enslin JMN, Jacobs M, Sauka-Spengler T, Greco M, Quiñones S, Dulla CG, Raimondo JV, Figaji A, Hockman D. A temporal cortex cell atlas highlights gene expression dynamics during human brain maturation. Nat Genet 2024; 56:2718-2730. [PMID: 39567748 PMCID: PMC11631765 DOI: 10.1038/s41588-024-01990-6] [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: 09/22/2023] [Accepted: 10/15/2024] [Indexed: 11/22/2024]
Abstract
The human brain undergoes protracted postnatal maturation, guided by dynamic changes in gene expression. Most studies exploring these processes have used bulk tissue analyses, which mask cell-type-specific gene expression dynamics. Here, using single-nucleus RNA sequencing on temporal lobe tissue, including samples of African ancestry, we build a joint pediatric and adult atlas of 75 cell subtypes, which we verify with spatial transcriptomics. We explore the differences between pediatric and adult cell subtypes, revealing the genes and pathways that change during brain maturation. Our results highlight excitatory neuron subtypes, including the LTK and FREM subtypes, that show elevated expression of genes associated with cognition and synaptic plasticity in pediatric tissue. The resources we present here improve our understanding of the brain during its development and contribute to global efforts to build an inclusive brain cell map.
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Affiliation(s)
- Christina Steyn
- Division of Cell Biology, Department of Human Biology, University of Cape Town, Cape Town, South Africa
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Ruvimbo Mishi
- Division of Cell Biology, Department of Human Biology, University of Cape Town, Cape Town, South Africa
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Stephanie Fillmore
- Division of Cell Biology, Department of Human Biology, University of Cape Town, Cape Town, South Africa
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Matthijs B Verhoog
- Division of Cell Biology, Department of Human Biology, University of Cape Town, Cape Town, South Africa
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Jessica More
- Division of Cell Biology, Department of Human Biology, University of Cape Town, Cape Town, South Africa
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Ursula K Rohlwink
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
- Division of Neurosurgery, Department of Surgery, University of Cape Town, Cape Town, South Africa
| | - Roger Melvill
- Division of Neurosurgery, Department of Surgery, University of Cape Town, Cape Town, South Africa
| | - James Butler
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
- Division of Neurology, Department of Medicine, University of Cape Town, Cape Town, South Africa
| | - Johannes M N Enslin
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
- Division of Neurosurgery, Department of Surgery, University of Cape Town, Cape Town, South Africa
| | - Muazzam Jacobs
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
- Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa
- Division of Immunology, Department of Pathology University of Cape Town, Cape Town, South Africa
- National Health Laboratory Service, Cape Town, South Africa
| | - Tatjana Sauka-Spengler
- Radcliffe Department of Medicine, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
- Stowers Institute for Medical Research, Kansas City, MO, USA
| | - Maria Greco
- Single Cell Facility, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - Sadi Quiñones
- Department of Neuroscience, Graduate School of Biomedical Sciences, Tufts University School of Medicine, Boston, MA, USA
- Graduate School of Biomedical Science, Tufts University School of Medicine, Boston, MA, USA
| | - Chris G Dulla
- Department of Neuroscience, Graduate School of Biomedical Sciences, Tufts University School of Medicine, Boston, MA, USA
| | - Joseph V Raimondo
- Division of Cell Biology, Department of Human Biology, University of Cape Town, Cape Town, South Africa
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
- Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa
| | - Anthony Figaji
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
- Division of Neurosurgery, Department of Surgery, University of Cape Town, Cape Town, South Africa
| | - Dorit Hockman
- Division of Cell Biology, Department of Human Biology, University of Cape Town, Cape Town, South Africa.
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa.
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Eagles NJ, Bach SV, Tippani M, Ravichandran P, Du Y, Miller RA, Hyde TM, Page SC, Martinowich K, Collado-Torres L. Integrating gene expression and imaging data across Visium capture areas with visiumStitched. BMC Genomics 2024; 25:1077. [PMID: 39533203 PMCID: PMC11559125 DOI: 10.1186/s12864-024-10991-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2024] [Accepted: 11/04/2024] [Indexed: 11/16/2024] Open
Abstract
BACKGROUND Visium is a widely-used spatially-resolved transcriptomics assay available from 10x Genomics. Standard Visium capture areas (6.5mm by 6.5mm) limit the survey of larger tissue structures, but combining overlapping images and associated gene expression data allow for more complex study designs. Current software can handle nested or partial image overlaps, but is designed for merging up to two capture areas, and cannot account for some technical scenarios related to capture area alignment. RESULTS We generated Visium data from a postmortem human tissue sample such that two capture areas were partially overlapping and a third one was adjacent. We developed the R/Bioconductor package visiumStitched, which facilitates stitching the images together with Fiji (ImageJ), and constructing SpatialExperiment R objects with the stitched images and gene expression data. visiumStitched constructs an artificial hexagonal array grid which allows seamless downstream analyses such as spatially-aware clustering without discarding data from overlapping spots. Data stitched with visiumStitched can then be interactively visualized with spatialLIBD. CONCLUSIONS visiumStitched provides a simple, but flexible framework to handle various multi-capture area study design scenarios. Specifically, it resolves a data processing step without disrupting analysis workflows and without discarding data from overlapping spots. visiumStitched relies on affine transformations by Fiji, which have limitations and are less accurate when aligning against an atlas or other situations. visiumStitched provides an easy-to-use solution which expands possibilities for designing multi-capture area study designs.
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Affiliation(s)
- Nicholas J Eagles
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, 21205, Baltimore, USA
| | - Svitlana V Bach
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, 21205, Baltimore, USA
| | - Madhavi Tippani
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, 21205, Baltimore, USA
| | - Prashanthi Ravichandran
- Department of Biomedical Engineering, Johns Hopkins School of Medicine, 21218, Baltimore, USA
| | - Yufeng Du
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, 21205, Baltimore, USA
| | - Ryan A Miller
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, 21205, Baltimore, USA
| | - Thomas M Hyde
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, 21205, Baltimore, USA
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, 21205, Baltimore, USA
- Department of Neurology, Johns Hopkins School of Medicine, 21205, Baltimore, USA
| | - Stephanie C Page
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, 21205, Baltimore, USA
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, 21205, Baltimore, USA
| | - Keri Martinowich
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, 21205, Baltimore, USA
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, 21205, Baltimore, USA
- Department of Neurology, Johns Hopkins School of Medicine, 21205, Baltimore, USA
- The Solomon H. Snyder Department of Neuroscience, Johns Hopkins School of Medicine, 21205, Baltimore, USA
- Johns Hopkins Kavli Neuroscience Discovery Institute, Johns Hopkins University, 21218, Baltimore, USA
| | - Leonardo Collado-Torres
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, 21205, Baltimore, USA.
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, 21205, Baltimore, USA.
- Center for Computational Biology, Johns Hopkins University, 21205, Baltimore, USA.
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Eagles NJ, Bach SV, Tippani M, Ravichandran P, Du Y, Miller RA, Hyde TM, Page SC, Martinowich K, Collado-Torres L. Integrating gene expression and imaging data across Visium capture areas with visiumStitched. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.08.08.607222. [PMID: 39149358 PMCID: PMC11326277 DOI: 10.1101/2024.08.08.607222] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/17/2024]
Abstract
Background Visium is a widely-used spatially-resolved transcriptomics assay available from 10x Genomics. Standard Visium capture areas (6.5mm by 6.5mm) limit the survey of larger tissue structures, but combining overlapping images and associated gene expression data allow for more complex study designs. Current software can handle nested or partial image overlaps, but is designed for merging up to two capture areas, and cannot account for some technical scenarios related to capture area alignment. Results We generated Visium data from a postmortem human tissue sample such that two capture areas were partially overlapping and a third one was adjacent. We developed the R/Bioconductor package visiumStitched, which facilitates stitching the images together with Fiji (ImageJ), and constructing SpatialExperiment R objects with the stitched images and gene expression data. visiumStitched constructs an artificial hexagonal array grid which allows seamless downstream analyses such as spatially-aware clustering without discarding data from overlapping spots. Data stitched with visiumStitched can then be interactively visualized with spatialLIBD. Conclusions visiumStitched provides a simple, but flexible framework to handle various multi-capture area study design scenarios. Specifically, it resolves a data processing step without disrupting analysis workflows and without discarding data from overlapping spots. visiumStiched relies on affine transformations by Fiji, which have limitations and are less accurate when aligning against an atlas or other situations. visiumStiched provides an easy-to-use solution which expands possibilities for designing multi-capture area study designs.
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Affiliation(s)
- Nicholas J. Eagles
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, 21205 Baltimore, USA
| | - Svitlana V. Bach
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, 21205 Baltimore, USA
| | - Madhavi Tippani
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, 21205 Baltimore, USA
| | - Prashanthi Ravichandran
- Department of Biomedical Engineering, Johns Hopkins School of Medicine, 21218, Baltimore, USA
| | - Yufeng Du
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, 21205 Baltimore, USA
| | - Ryan A. Miller
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, 21205 Baltimore, USA
| | - Thomas M. Hyde
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, 21205 Baltimore, USA
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, 21205, Baltimore, USA
- Department of Neurology, Johns Hopkins School of Medicine, 21205, Baltimore, USA
| | - Stephanie C. Page
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, 21205 Baltimore, USA
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, 21205, Baltimore, USA
| | - Keri Martinowich
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, 21205 Baltimore, USA
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, 21205, Baltimore, USA
- Department of Neurology, Johns Hopkins School of Medicine, 21205, Baltimore, USA
- The Solomon H. Snyder Department of Neuroscience, Johns Hopkins School of Medicine, 21205, Baltimore, USA
- Johns Hopkins Kavli Neuroscience Discovery Institute, Johns Hopkins University, 21218, Baltimore, USA
| | - Leonardo Collado-Torres
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, 21205 Baltimore, USA
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, 21205, Baltimore, USA
- Center for Computational Biology, Johns Hopkins University, 21205, Baltimore, USA
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Huuki-Myers LA, Spangler A, Eagles NJ, Montgomery KD, Kwon SH, Guo B, Grant-Peters M, Divecha HR, Tippani M, Sriworarat C, Nguyen AB, Ravichandran P, Tran MN, Seyedian A, Hyde TM, Kleinman JE, Battle A, Page SC, Ryten M, Hicks SC, Martinowich K, Collado-Torres L, Maynard KR. A data-driven single-cell and spatial transcriptomic map of the human prefrontal cortex. Science 2024; 384:eadh1938. [PMID: 38781370 PMCID: PMC11398705 DOI: 10.1126/science.adh1938] [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: 02/17/2023] [Accepted: 12/06/2023] [Indexed: 05/25/2024]
Abstract
The molecular organization of the human neocortex historically has been studied in the context of its histological layers. However, emerging spatial transcriptomic technologies have enabled unbiased identification of transcriptionally defined spatial domains that move beyond classic cytoarchitecture. We used the Visium spatial gene expression platform to generate a data-driven molecular neuroanatomical atlas across the anterior-posterior axis of the human dorsolateral prefrontal cortex. Integration with paired single-nucleus RNA-sequencing data revealed distinct cell type compositions and cell-cell interactions across spatial domains. Using PsychENCODE and publicly available data, we mapped the enrichment of cell types and genes associated with neuropsychiatric disorders to discrete spatial domains.
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Affiliation(s)
- Louise A Huuki-Myers
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD 21205, USA
| | - Abby Spangler
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD 21205, USA
| | - Nicholas J Eagles
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD 21205, USA
| | - Kelsey D Montgomery
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD 21205, USA
| | - Sang Ho Kwon
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD 21205, USA
- The Solomon H. Snyder Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA
| | - Boyi Guo
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
| | - Melissa Grant-Peters
- Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, University College London, London WC1N 1EH, UK
- Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD 20815, USA
| | - Heena R Divecha
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD 21205, USA
| | - Madhavi Tippani
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD 21205, USA
| | - Chaichontat Sriworarat
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD 21205, USA
- The Solomon H. Snyder Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA
| | - Annie B Nguyen
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD 21205, USA
| | - Prashanthi Ravichandran
- Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, MD 21218, USA
| | - Matthew N Tran
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD 21205, USA
| | - Arta Seyedian
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD 21205, USA
| | - Thomas M Hyde
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD 21205, USA
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA
- Department of Neurology, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA
| | - Joel E Kleinman
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD 21205, USA
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA
| | - Alexis Battle
- Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, MD 21218, USA
- Department of Computer Science, Johns Hopkins University, Baltimore, MD 21218, USA
- Department of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA
- Malone Center for Engineering in Healthcare, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Stephanie C Page
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD 21205, USA
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA
| | - Mina Ryten
- Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, University College London, London WC1N 1EH, UK
- Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD 20815, USA
- NIHR Great Ormond Street Hospital Biomedical Research Centre, University College London, London WC1N 1EH, UK
| | - Stephanie C Hicks
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
- Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, MD 21218, USA
- Malone Center for Engineering in Healthcare, Johns Hopkins University, Baltimore, MD 21218, USA
- Center for Computational Biology, Johns Hopkins University, Baltimore, MD 21205, USA
| | - Keri Martinowich
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD 21205, USA
- The Solomon H. Snyder Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA
- Johns Hopkins Kavli Neuroscience Discovery Institute, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Leonardo Collado-Torres
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD 21205, USA
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
- Center for Computational Biology, Johns Hopkins University, Baltimore, MD 21205, USA
| | - Kristen R Maynard
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD 21205, USA
- The Solomon H. Snyder Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA
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Ramnauth AD, Tippani M, Divecha HR, Papariello AR, Miller RA, Nelson ED, Pattie EA, Kleinman JE, Maynard KR, Collado-Torres L, Hyde TM, Martinowich K, Hicks SC, Page SC. Spatiotemporal analysis of gene expression in the human dentate gyrus reveals age-associated changes in cellular maturation and neuroinflammation. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.11.20.567883. [PMID: 38045413 PMCID: PMC10690172 DOI: 10.1101/2023.11.20.567883] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/05/2023]
Abstract
The dentate gyrus of the hippocampus is important for many cognitive functions, including learning, memory, and mood. Here, we investigated age-associated changes in transcriptome-wide spatial gene expression in the human dentate gyrus across the lifespan. Genes associated with neurogenesis and the extracellular matrix were enriched in infants, while gene markers of inhibitory neurons and cell proliferation showed increases and decreases in post-infancy, respectively. While we did not find evidence for neural proliferation post-infancy, we did identify molecular signatures supporting protracted maturation of granule cells. We also identified a wide-spread hippocampal aging signature and an age-associated increase in genes related to neuroinflammation. Our findings suggest major changes to the putative neurogenic niche after infancy and identify molecular foci of brain aging in glial and neuropil enriched tissue.
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Paveliev M, Egorchev AA, Musin F, Lipachev N, Melnikova A, Gimadutdinov RM, Kashipov AR, Molotkov D, Chickrin DE, Aganov AV. Perineuronal Net Microscopy: From Brain Pathology to Artificial Intelligence. Int J Mol Sci 2024; 25:4227. [PMID: 38673819 PMCID: PMC11049984 DOI: 10.3390/ijms25084227] [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: 02/02/2024] [Revised: 03/31/2024] [Accepted: 04/05/2024] [Indexed: 04/28/2024] Open
Abstract
Perineuronal nets (PNN) are a special highly structured type of extracellular matrix encapsulating synapses on large populations of CNS neurons. PNN undergo structural changes in schizophrenia, epilepsy, Alzheimer's disease, stroke, post-traumatic conditions, and some other brain disorders. The functional role of the PNN microstructure in brain pathologies has remained largely unstudied until recently. Here, we review recent research implicating PNN microstructural changes in schizophrenia and other disorders. We further concentrate on high-resolution studies of the PNN mesh units surrounding synaptic boutons to elucidate fine structural details behind the mutual functional regulation between the ECM and the synaptic terminal. We also review some updates regarding PNN as a potential pharmacological target. Artificial intelligence (AI)-based methods are now arriving as a new tool that may have the potential to grasp the brain's complexity through a wide range of organization levels-from synaptic molecular events to large scale tissue rearrangements and the whole-brain connectome function. This scope matches exactly the complex role of PNN in brain physiology and pathology processes, and the first AI-assisted PNN microscopy studies have been reported. To that end, we report here on a machine learning-assisted tool for PNN mesh contour tracing.
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Affiliation(s)
- Mikhail Paveliev
- Neuroscience Center, University of Helsinki, Haartmaninkatu 8, 00290 Helsinki, Finland
| | - Anton A. Egorchev
- Institute of Computational Mathematics and Information Technologies, Kazan Federal University, Kremlyovskaya 35, Kazan 420008, Tatarstan, Russia; (A.A.E.); (F.M.); (R.M.G.)
| | - Foat Musin
- Institute of Computational Mathematics and Information Technologies, Kazan Federal University, Kremlyovskaya 35, Kazan 420008, Tatarstan, Russia; (A.A.E.); (F.M.); (R.M.G.)
| | - Nikita Lipachev
- Institute of Physics, Kazan Federal University, Kremlyovskaya 16a, Kazan 420008, Tatarstan, Russia; (N.L.); (A.V.A.)
| | - Anastasiia Melnikova
- Institute of Fundamental Medicine and Biology, Kazan Federal University, Karl Marx 74, Kazan 420015, Tatarstan, Russia;
| | - Rustem M. Gimadutdinov
- Institute of Computational Mathematics and Information Technologies, Kazan Federal University, Kremlyovskaya 35, Kazan 420008, Tatarstan, Russia; (A.A.E.); (F.M.); (R.M.G.)
| | - Aidar R. Kashipov
- Institute of Artificial Intelligence, Robotics and Systems Engineering, Kazan Federal University, Kremlyovskaya 18, Kazan 420008, Tatarstan, Russia; (A.R.K.); (D.E.C.)
| | - Dmitry Molotkov
- Biomedicum Imaging Unit, University of Helsinki, Haartmaninkatu 8, 00014 Helsinki, Finland;
| | - Dmitry E. Chickrin
- Institute of Artificial Intelligence, Robotics and Systems Engineering, Kazan Federal University, Kremlyovskaya 18, Kazan 420008, Tatarstan, Russia; (A.R.K.); (D.E.C.)
| | - Albert V. Aganov
- Institute of Physics, Kazan Federal University, Kremlyovskaya 16a, Kazan 420008, Tatarstan, Russia; (N.L.); (A.V.A.)
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Weber LM, Divecha HR, Tran MN, Kwon SH, Spangler A, Montgomery KD, Tippani M, Bharadwaj R, Kleinman JE, Page SC, Hyde TM, Collado-Torres L, Maynard KR, Martinowich K, Hicks SC. The gene expression landscape of the human locus coeruleus revealed by single-nucleus and spatially-resolved transcriptomics. eLife 2024; 12:RP84628. [PMID: 38266073 PMCID: PMC10945708 DOI: 10.7554/elife.84628] [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] [Indexed: 01/26/2024] Open
Abstract
Norepinephrine (NE) neurons in the locus coeruleus (LC) make long-range projections throughout the central nervous system, playing critical roles in arousal and mood, as well as various components of cognition including attention, learning, and memory. The LC-NE system is also implicated in multiple neurological and neuropsychiatric disorders. Importantly, LC-NE neurons are highly sensitive to degeneration in both Alzheimer's and Parkinson's disease. Despite the clinical importance of the brain region and the prominent role of LC-NE neurons in a variety of brain and behavioral functions, a detailed molecular characterization of the LC is lacking. Here, we used a combination of spatially-resolved transcriptomics and single-nucleus RNA-sequencing to characterize the molecular landscape of the LC region and the transcriptomic profile of LC-NE neurons in the human brain. We provide a freely accessible resource of these data in web-accessible and downloadable formats.
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Affiliation(s)
- Lukas M Weber
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public HealthBaltimoreUnited States
| | - Heena R Divecha
- Lieber Institute for Brain Development, Johns Hopkins Medical CampusBaltimoreUnited States
| | - Matthew N Tran
- Lieber Institute for Brain Development, Johns Hopkins Medical CampusBaltimoreUnited States
| | - Sang Ho Kwon
- Lieber Institute for Brain Development, Johns Hopkins Medical CampusBaltimoreUnited States
- Department of Neuroscience, Johns Hopkins School of MedicineBaltimoreUnited States
| | - Abby Spangler
- Lieber Institute for Brain Development, Johns Hopkins Medical CampusBaltimoreUnited States
| | - Kelsey D Montgomery
- Lieber Institute for Brain Development, Johns Hopkins Medical CampusBaltimoreUnited States
| | - Madhavi Tippani
- Lieber Institute for Brain Development, Johns Hopkins Medical CampusBaltimoreUnited States
| | - Rahul Bharadwaj
- Lieber Institute for Brain Development, Johns Hopkins Medical CampusBaltimoreUnited States
| | - Joel E Kleinman
- Lieber Institute for Brain Development, Johns Hopkins Medical CampusBaltimoreUnited States
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of MedicineBaltimoreUnited States
| | - Stephanie C Page
- Lieber Institute for Brain Development, Johns Hopkins Medical CampusBaltimoreUnited States
| | - Thomas M Hyde
- Lieber Institute for Brain Development, Johns Hopkins Medical CampusBaltimoreUnited States
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of MedicineBaltimoreUnited States
- Department of Neurology, Johns Hopkins School of MedicineBaltimoreUnited States
| | | | - Kristen R Maynard
- Lieber Institute for Brain Development, Johns Hopkins Medical CampusBaltimoreUnited States
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of MedicineBaltimoreUnited States
| | - Keri Martinowich
- Lieber Institute for Brain Development, Johns Hopkins Medical CampusBaltimoreUnited States
- Department of Neuroscience, Johns Hopkins School of MedicineBaltimoreUnited States
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of MedicineBaltimoreUnited States
- The Kavli Neuroscience Discovery Institute, Johns Hopkins UniversityBaltimoreUnited States
| | - Stephanie C Hicks
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public HealthBaltimoreUnited States
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