1
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Fröhlich AS, Gerstner N, Gagliardi M, Ködel M, Yusupov N, Matosin N, Czamara D, Sauer S, Roeh S, Murek V, Chatzinakos C, Daskalakis NP, Knauer-Arloth J, Ziller MJ, Binder EB. Single-nucleus transcriptomic profiling of human orbitofrontal cortex reveals convergent effects of aging and psychiatric disease. Nat Neurosci 2024; 27:2021-2032. [PMID: 39227716 PMCID: PMC11452345 DOI: 10.1038/s41593-024-01742-z] [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: 07/13/2023] [Accepted: 07/30/2024] [Indexed: 09/05/2024]
Abstract
Aging is a complex biological process and represents the largest risk factor for neurodegenerative disorders. The risk for neurodegenerative disorders is also increased in individuals with psychiatric disorders. Here, we characterized age-related transcriptomic changes in the brain by profiling ~800,000 nuclei from the orbitofrontal cortex from 87 individuals with and without psychiatric diagnoses and replicated findings in an independent cohort with 32 individuals. Aging affects all cell types, with LAMP5+LHX6+ interneurons, a cell-type abundant in primates, by far the most affected. Disrupted synaptic transmission emerged as a convergently affected pathway in aged tissue. Age-related transcriptomic changes overlapped with changes observed in Alzheimer's disease across multiple cell types. We find evidence for accelerated transcriptomic aging in individuals with psychiatric disorders and demonstrate a converging signature of aging and psychopathology across multiple cell types. Our findings shed light on cell-type-specific effects and biological pathways underlying age-related changes and their convergence with effects driven by psychiatric diagnosis.
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Affiliation(s)
- Anna S Fröhlich
- Department of Genes and Environment, Max Planck Institute of Psychiatry, Munich, Germany.
- International Max Planck Research School for Translational Psychiatry, Munich, Germany.
| | - Nathalie Gerstner
- Department of Genes and Environment, Max Planck Institute of Psychiatry, Munich, Germany
- International Max Planck Research School for Translational Psychiatry, Munich, Germany
- Institute of Computational Biology, Helmholtz Zentrum München, Neuherberg, Germany
| | - Miriam Gagliardi
- Department of Psychiatry, University of Münster, Münster, Germany
| | - Maik Ködel
- Department of Genes and Environment, Max Planck Institute of Psychiatry, Munich, Germany
| | - Natan Yusupov
- Department of Genes and Environment, Max Planck Institute of Psychiatry, Munich, Germany
- International Max Planck Research School for Translational Psychiatry, Munich, Germany
| | - Natalie Matosin
- School of Medical Sciences, Faculty of Medicine and Health, University of Sydney, Camperdown, New South Wales, Australia
- Charles Perkins Centre, University of Sydney, Camperdown, New South Wales, Australia
| | - Darina Czamara
- Department of Genes and Environment, Max Planck Institute of Psychiatry, Munich, Germany
| | - Susann Sauer
- Department of Genes and Environment, Max Planck Institute of Psychiatry, Munich, Germany
| | - Simone Roeh
- Department of Genes and Environment, Max Planck Institute of Psychiatry, Munich, Germany
| | - Vanessa Murek
- Department of Psychiatry, University of Münster, Münster, Germany
| | - Chris Chatzinakos
- Department of Psychiatry, McLean Hospital, Harvard Medical School, Belmont, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Psychiatry and Behavioral Sciences, Institute for Genomics in Health, SUNY Downstate Health Sciences University, Brooklyn, NY, USA
| | - Nikolaos P Daskalakis
- Department of Psychiatry, McLean Hospital, Harvard Medical School, Belmont, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Janine Knauer-Arloth
- Department of Genes and Environment, Max Planck Institute of Psychiatry, Munich, Germany
- Institute of Computational Biology, Helmholtz Zentrum München, Neuherberg, Germany
| | - Michael J Ziller
- Department of Psychiatry, University of Münster, Münster, Germany
| | - Elisabeth B Binder
- Department of Genes and Environment, Max Planck Institute of Psychiatry, Munich, Germany.
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, USA.
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2
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Wu X, Yang X, Dai Y, Zhao Z, Zhu J, Guo H, Yang R. Single-cell sequencing to multi-omics: technologies and applications. Biomark Res 2024; 12:110. [PMID: 39334490 PMCID: PMC11438019 DOI: 10.1186/s40364-024-00643-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2024] [Accepted: 08/17/2024] [Indexed: 09/30/2024] Open
Abstract
Cells, as the fundamental units of life, contain multidimensional spatiotemporal information. Single-cell RNA sequencing (scRNA-seq) is revolutionizing biomedical science by analyzing cellular state and intercellular heterogeneity. Undoubtedly, single-cell transcriptomics has emerged as one of the most vibrant research fields today. With the optimization and innovation of single-cell sequencing technologies, the intricate multidimensional details concealed within cells are gradually unveiled. The combination of scRNA-seq and other multi-omics is at the forefront of the single-cell field. This involves simultaneously measuring various omics data within individual cells, expanding our understanding across a broader spectrum of dimensions. Single-cell multi-omics precisely captures the multidimensional aspects of single-cell transcriptomes, immune repertoire, spatial information, temporal information, epitopes, and other omics in diverse spatiotemporal contexts. In addition to depicting the cell atlas of normal or diseased tissues, it also provides a cornerstone for studying cell differentiation and development patterns, disease heterogeneity, drug resistance mechanisms, and treatment strategies. Herein, we review traditional single-cell sequencing technologies and outline the latest advancements in single-cell multi-omics. We summarize the current status and challenges of applying single-cell multi-omics technologies to biological research and clinical applications. Finally, we discuss the limitations and challenges of single-cell multi-omics and potential strategies to address them.
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Affiliation(s)
- Xiangyu Wu
- Department of Urology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, 321 Zhongshan Road, Nanjing, 210008, Jiangsu, China
| | - Xin Yang
- Department of Urology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, 321 Zhongshan Road, Nanjing, 210008, Jiangsu, China
| | - Yunhan Dai
- Medical School, Nanjing University, Nanjing, China
| | - Zihan Zhao
- Department of Urology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, 321 Zhongshan Road, Nanjing, 210008, Jiangsu, China
| | - Junmeng Zhu
- Department of Oncology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Hongqian Guo
- Department of Urology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, 321 Zhongshan Road, Nanjing, 210008, Jiangsu, China.
| | - Rong Yang
- Department of Urology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, 321 Zhongshan Road, Nanjing, 210008, Jiangsu, China.
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3
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Ben-Simon Y, Hooper M, Narayan S, Daigle T, Dwivedi D, Way SW, Oster A, Stafford DA, Mich JK, Taormina MJ, Martinez RA, Opitz-Araya X, Roth JR, Allen S, Ayala A, Bakken TE, Barcelli T, Barta S, Bendrick J, Bertagnolli D, Bowlus J, Boyer G, Brouner K, Casian B, Casper T, Chakka AB, Chakrabarty R, Chance RK, Chavan S, Departee M, Donadio N, Dotson N, Egdorf T, Gabitto M, Garcia J, Gary A, Gasperini M, Goldy J, Gore BB, Graybuck L, Greisman N, Haeseleer F, Halterman C, Helback O, Hockemeyer D, Huang C, Huff S, Hunker A, Johansen N, Juneau Z, Kalmbach B, Khem S, Kussick E, Kutsal R, Larsen R, Lee C, Lee AY, Leibly M, Lenz GH, Liang E, Lusk N, Malone J, Mollenkopf T, Morin E, Newman D, Ng L, Ngo K, Omstead V, Oyama A, Pham T, Pom CA, Potekhina L, Ransford S, Rette D, Rimorin C, Rocha D, Ruiz A, Sanchez REA, Sedeno-Cortes A, Sevigny JP, Shapovalova N, Shulga L, Sigler AR, Siverts LA, Somasundaram S, Stewart K, Szelenyi E, Tieu M, Trader C, van Velthoven CTJ, Walker M, 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 J, Tasic B. A suite of enhancer AAVs and transgenic mouse lines for genetic access to cortical cell types. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.10.597244. [PMID: 38915722 PMCID: PMC11195086 DOI: 10.1101/2024.06.10.597244] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/26/2024]
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 used transcriptomic and epigenomic cortical cell type taxonomies from mouse and human to define marker genes and putative enhancers and created a large toolkit of transgenic lines and enhancer AAVs for selective targeting of cortical cell populations. We report evaluation of fifteen new transgenic driver lines, two new reporter lines, and >800 different enhancer AAVs covering most subclasses of cortical cells. The tools reported here as well as the scaled process of tool creation and modification enable diverse experimental strategies towards understanding mammalian cortex and brain function.
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4
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Stöber MC, Chamorro González R, Brückner L, Conrad T, Wittstruck N, Szymansky A, Eggert A, Schulte JH, Koche RP, Henssen AG, Schwarz RF, Haase K. Intercellular extrachromosomal DNA copy-number heterogeneity drives neuroblastoma cell state diversity. Cell Rep 2024; 43:114711. [PMID: 39255063 DOI: 10.1016/j.celrep.2024.114711] [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: 08/10/2023] [Revised: 05/20/2024] [Accepted: 08/20/2024] [Indexed: 09/12/2024] Open
Abstract
Neuroblastoma exhibits significant inter- and intra-tumor genetic heterogeneity and varying clinical outcomes. Extrachromosomal DNAs (ecDNAs) may drive this heterogeneity by independently segregating during cell division, leading to rapid oncogene amplification. While ecDNA-mediated oncogene amplification is linked to poor prognosis in various cancers, the effects of ecDNA copy-number heterogeneity on intermediate phenotypes are poorly understood. Here, we leverage DNA and RNA sequencing from the same single cells in cell lines and neuroblastoma patients to investigate these effects. By analyzing ecDNA amplicon structures, we reveal extensive intercellular ecDNA copy-number heterogeneity. We also provide direct evidence of how this heterogeneity influences the expression of cargo genes, including MYCN and its downstream targets, and the overall transcriptional state of neuroblastoma cells. Our findings highlight the role of ecDNA copy number in promoting rapid adaptability of cellular states within tumors, underscoring the need for ecDNA-specific treatment strategies to address tumor formation and adaptation.
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Affiliation(s)
- Maja C Stöber
- Berlin Institute for Medical Systems Biology at the Max Delbrück Center for Molecular Medicine in the Helmholtz Association, 10115 Berlin, Germany; Institute of Pathology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, 10117 Berlin, Germany; Humboldt-Universität zu Berlin, Faculty of Life Science, 10099 Berlin, Germany
| | - Rocío Chamorro González
- Department of Pediatric Oncology/Hematology, Charité - Universitätsmedizin, 13353 Berlin, Germany
| | - Lotte Brückner
- Department of Pediatric Oncology/Hematology, Charité - Universitätsmedizin, 13353 Berlin, Germany
| | - Thomas Conrad
- Berlin Institute for Medical Systems Biology at the Max Delbrück Center for Molecular Medicine in the Helmholtz Association, 10115 Berlin, Germany; Berlin Institute of Health, 10178 Berlin, Germany
| | - Nadine Wittstruck
- Berlin Institute for Medical Systems Biology at the Max Delbrück Center for Molecular Medicine in the Helmholtz Association, 10115 Berlin, Germany; Department of Pediatric Oncology/Hematology, Charité - Universitätsmedizin, 13353 Berlin, Germany
| | - Annabell Szymansky
- Department of Pediatric Oncology/Hematology, Charité - Universitätsmedizin, 13353 Berlin, Germany
| | - Angelika Eggert
- Department of Pediatric Oncology/Hematology, Charité - Universitätsmedizin, 13353 Berlin, Germany; German Cancer Consortium (DKTK), partner site Berlin, and German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Johannes H Schulte
- Department of Pediatric Oncology/Hematology, Charité - Universitätsmedizin, 13353 Berlin, Germany; German Cancer Consortium (DKTK), partner site Berlin, and German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Richard P Koche
- Center for Epigenetics Research, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
| | - Anton G Henssen
- Berlin Institute for Medical Systems Biology at the Max Delbrück Center for Molecular Medicine in the Helmholtz Association, 10115 Berlin, Germany; Department of Pediatric Oncology/Hematology, Charité - Universitätsmedizin, 13353 Berlin, Germany; German Cancer Consortium (DKTK), partner site Berlin, and German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany; Berlin Institute of Health, 10178 Berlin, Germany; Experimental and Clinical Research Center (ECRC) of the MDC and Charité Berlin, 13125 Berlin, Germany.
| | - Roland F Schwarz
- Institute for Computational Cancer Biology (ICCB), Center for Integrated Oncology (CIO), Cancer Research Center Cologne Essen (CCCE), Faculty of Medicine and University Hospital Cologne, University of Cologne, 50937 Cologne, Germany; BIFOLD - Berlin Institute for the Foundations of Learning and Data, 10587 Berlin, Germany; Berlin Institute for Medical Systems Biology at the Max Delbrück Center for Molecular Medicine in the Helmholtz Association, 10115 Berlin, Germany.
| | - Kerstin Haase
- Department of Pediatric Oncology/Hematology, Charité - Universitätsmedizin, 13353 Berlin, Germany; German Cancer Consortium (DKTK), partner site Berlin, and German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany.
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5
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Patiño M, Rossa MA, Lagos WN, Patne NS, Callaway EM. Transcriptomic cell-type specificity of local cortical circuits. Neuron 2024:S0896-6273(24)00651-2. [PMID: 39353431 DOI: 10.1016/j.neuron.2024.09.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2024] [Revised: 07/02/2024] [Accepted: 09/04/2024] [Indexed: 10/04/2024]
Abstract
Complex neocortical functions rely on networks of diverse excitatory and inhibitory neurons. While local connectivity rules between major neuronal subclasses have been established, the specificity of connections at the level of transcriptomic subtypes remains unclear. We introduce single transcriptome assisted rabies tracing (START), a method combining monosynaptic rabies tracing and single-nuclei RNA sequencing to identify transcriptomic cell types, providing inputs to defined neuron populations. We employ START to transcriptomically characterize inhibitory neurons providing monosynaptic input to 5 different layer-specific excitatory cortical neuron populations in mouse primary visual cortex (V1). At the subclass level, we observe results consistent with findings from prior studies that resolve neuronal subclasses using antibody staining, transgenic mouse lines, and morphological reconstruction. With improved neuronal subtype granularity achieved with START, we demonstrate transcriptomic subtype specificity of inhibitory inputs to various excitatory neuron subclasses. These results establish local connectivity rules at the resolution of transcriptomic inhibitory cell types.
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Affiliation(s)
- Maribel Patiño
- Systems Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA; Medical Scientist Training Program, University of California, San Diego, La Jolla, CA, USA
| | - Marley A Rossa
- Systems Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA; Neurosciences Graduate Program, University of California, San Diego, La Jolla, CA, USA
| | - Willian Nuñez Lagos
- Systems Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Neelakshi S Patne
- Systems Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA; Neuroscience Graduate Program, Boston University, Boston, MA, USA
| | - Edward M Callaway
- Systems Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA.
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6
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Trevisan AJ, Han K, Chapman P, Kulkarni AS, Hinton JM, Ramirez C, Klein I, Gatto G, Gabitto MI, Menon V, Bikoff JB. The transcriptomic landscape of spinal V1 interneurons reveals a role for En1 in specific elements of motor output. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.09.18.613279. [PMID: 39345580 PMCID: PMC11429899 DOI: 10.1101/2024.09.18.613279] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/01/2024]
Abstract
Neural circuits in the spinal cord are composed of diverse sets of interneurons that play crucial roles in shaping motor output. Despite progress in revealing the cellular architecture of the spinal cord, the extent of cell type heterogeneity within interneuron populations remains unclear. Here, we present a single-nucleus transcriptomic atlas of spinal V1 interneurons across postnatal development. We find that the core molecular taxonomy distinguishing neonatal V1 interneurons perdures into adulthood, suggesting conservation of function across development. Moreover, we identify a key role for En1, a transcription factor that marks the V1 population, in specifying one unique subset of V1Pou6f2 interneurons. Loss of En1 selectively disrupts the frequency of rhythmic locomotor output but does not disrupt flexion/extension limb movement. Beyond serving as a molecular resource for this neuronal population, our study highlights how deep neuronal profiling provides an entry point for functional studies of specialized cell types in motor output.
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Affiliation(s)
- Alexandra J. Trevisan
- Department of Developmental Neurobiology, St. Jude Children’s Research Hospital, Memphis, TN, 38105, USA
| | - Katie Han
- Department of Developmental Neurobiology, St. Jude Children’s Research Hospital, Memphis, TN, 38105, USA
| | - Phillip Chapman
- Department of Developmental Neurobiology, St. Jude Children’s Research Hospital, Memphis, TN, 38105, USA
| | - Anand S. Kulkarni
- Department of Developmental Neurobiology, St. Jude Children’s Research Hospital, Memphis, TN, 38105, USA
| | - Jennifer M. Hinton
- Department of Developmental Neurobiology, St. Jude Children’s Research Hospital, Memphis, TN, 38105, USA
| | - Cody Ramirez
- Department of Developmental Neurobiology, St. Jude Children’s Research Hospital, Memphis, TN, 38105, USA
| | - Ines Klein
- Department of Neurology, University Hospital of Cologne, Cologne, 50937, Germany
| | - Graziana Gatto
- Department of Neurology, University Hospital of Cologne, Cologne, 50937, Germany
| | - Mariano I. Gabitto
- Allen Institute for Brain Science, Seattle, WA, 98109, USA
- Department of Statistics, University of Washington, Seattle, WA, 98109, USA
| | - Vilas Menon
- Department of Neurology, Center for Translational and Computational Neuroimmunology, Columbia University, New York, NY, 10033, USA
| | - Jay B. Bikoff
- Department of Developmental Neurobiology, St. Jude Children’s Research Hospital, Memphis, TN, 38105, USA
- Lead Contact
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Zhang C, Gou X, Lai G, Li K, Zhu X, Liu N, Kuang Y, Ren K, Xie Y, Xu Y, Zhong X, Xie B. Single-nucleus sequencing unveils heterogeneity in renal cell carcinomas microenvironment: Insights into pathogenic origins and treatment-responsive cellular subgroups. Cancer Lett 2024; 604:217259. [PMID: 39278398 DOI: 10.1016/j.canlet.2024.217259] [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: 06/17/2024] [Revised: 08/20/2024] [Accepted: 09/06/2024] [Indexed: 09/18/2024]
Abstract
BACKGROUND Different individuals with renal cell carcinoma (RCC) exhibit substantial heterogeneity in histomorphology, genetic alterations in the proteome, immune cell infiltration patterns, and clinical behavior. OBJECTIVES This study aims to use single-nucleus sequencing on ten samples (four normal, three clear cell renal cell carcinoma (ccRCC), and three chromophobe renal cell carcinoma (chRCC)) to uncover pathogenic origins and prognostic characteristics in patients with RCC. METHODS By using two algorithms, inferCNV and k-means, the study explores malignant cells and compares them with the normal group to reveal their origins. Furthermore, we explore the pathogenic factors at the gene level through Summary-data-based Mendelian Randomization and co-localization methods. Based on the relevant malignant markers, a total of 212 machine-learning combinations were compared to develop a prognostic signature with high precision and stability. Finally, the study correlates with clinical data to investigate which cell subtypes may impact patients' prognosis. RESULTS & CONCLUSION Two main origin tumor cells were identified: Proximal tubule cell B and Intercalated cell type A, which were highly differentiated in epithelial cells, and three gene loci were determined as potential pathogenic genes. The best malignant signature among the 212 prognostic models demonstrated high predictive power in ccRCC: (AUC: 0.920 (1-year), 0.920 (3-year) and 0.930 (5-year) in the training dataset; 0.756 (1-year), 0.828 (3-year), and 0.832 (5-year) in the testing dataset. In addition, we confirmed that LYVE1+ tissue-resident macrophage and TOX+ CD8 significantly impact the prognosis of ccRCC patients, while monocytes play a crucial role in the prognosis of chRCC patients.
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Affiliation(s)
- Cong Zhang
- Department of Epidemiology and Health Statistics, School of Public Health, Chongqing Medical University, Yixue Road, Chongqing, 400016, China
| | - Xin Gou
- Department of Urology, The First Affiliated Hospital of Chongqing Medical University, No. 1 Youyi Road, Yuzhong District, Chongqing, 400016, China
| | - Guichuan Lai
- Department of Epidemiology and Health Statistics, School of Public Health, Chongqing Medical University, Yixue Road, Chongqing, 400016, China
| | - Kangjie Li
- Department of Epidemiology and Health Statistics, School of Public Health, Chongqing Medical University, Yixue Road, Chongqing, 400016, China
| | - Xin Zhu
- Department of Urology, The First Affiliated Hospital of Chongqing Medical University, No. 1 Youyi Road, Yuzhong District, Chongqing, 400016, China
| | - Nian Liu
- Department of Urology, The First Affiliated Hospital of Chongqing Medical University, No. 1 Youyi Road, Yuzhong District, Chongqing, 400016, China
| | - Youlin Kuang
- Department of Urology, The First Affiliated Hospital of Chongqing Medical University, No. 1 Youyi Road, Yuzhong District, Chongqing, 400016, China
| | - Ke Ren
- Department of Urology, The First Affiliated Hospital of Chongqing Medical University, No. 1 Youyi Road, Yuzhong District, Chongqing, 400016, China
| | - Yongpeng Xie
- Department of Urology, The First Affiliated Hospital of Chongqing Medical University, No. 1 Youyi Road, Yuzhong District, Chongqing, 400016, China
| | - Yungang Xu
- Department of Cell Biology and Genetics, School of Basic Medical Sciences, Xi'an Jiaotong University Health Science Center, Xi'an, 710061, China
| | - Xiaoni Zhong
- Department of Epidemiology and Health Statistics, School of Public Health, Chongqing Medical University, Yixue Road, Chongqing, 400016, China.
| | - Biao Xie
- Department of Epidemiology and Health Statistics, School of Public Health, Chongqing Medical University, Yixue Road, Chongqing, 400016, China.
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8
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Tenorio Berrío R, Dubois M. Single-cell transcriptomics reveals heterogeneity in plant responses to the environment: a focus on biotic and abiotic interactions. JOURNAL OF EXPERIMENTAL BOTANY 2024; 75:5188-5203. [PMID: 38466621 DOI: 10.1093/jxb/erae107] [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: 11/30/2023] [Accepted: 03/08/2024] [Indexed: 03/13/2024]
Abstract
Biotic and abiotic environmental cues are major factors influencing plant growth and productivity. Interactions with biotic (e.g. symbionts and pathogens) and abiotic (e.g. changes in temperature, water, or nutrient availability) factors trigger signaling and downstream transcriptome adjustments in plants. While bulk RNA-sequencing technologies have traditionally been used to profile these transcriptional changes, tissue homogenization may mask heterogeneity of responses resulting from the cellular complexity of organs. Thus, whether different cell types respond equally to environmental fluctuations, or whether subsets of the responses are cell-type specific, are long-lasting questions in plant biology. The recent breakthrough of single-cell transcriptomics in plant research offers an unprecedented view of cellular responses under changing environmental conditions. In this review, we discuss the contribution of single-cell transcriptomics to the understanding of cell-type-specific plant responses to biotic and abiotic environmental interactions. Besides major biological findings, we present some technical challenges coupled to single-cell studies of plant-environment interactions, proposing possible solutions and exciting paths for future research.
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Affiliation(s)
- Rubén Tenorio Berrío
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Ghent, Belgium
- VIB Center for Plant Systems Biology, Ghent, Belgium
| | - Marieke Dubois
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Ghent, Belgium
- VIB Center for Plant Systems Biology, Ghent, Belgium
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9
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Liu C, Hong T, Zhao C, Xue T, Wang S, Ren Z. Single-nucleus transcriptomics and chromatin accessibility analysis of musk gland development in Chinese forest musk deer (Moschus berezovskii). Integr Zool 2024; 19:955-974. [PMID: 38644525 DOI: 10.1111/1749-4877.12823] [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: 07/10/2023] [Revised: 12/28/2023] [Accepted: 02/15/2024] [Indexed: 04/23/2024]
Abstract
Musk secreted by male forest musk deer (Moschus berezovskii) musk glands is an invaluable component of medicine and perfume. Musk secretion depends on musk gland maturation; however, the mechanism of its development remains elusive. Herein, using single cell multiome ATAC + gene expression coupled with several bioinformatic analyses, a dynamic transcriptional cell atlas of musk gland development was revealed, and key genes and transcription factors affecting its development were determined. Twelve cell types, including two different types of acinar cells (Clusters 0 and 10) were identified. Single-nucleus RNA and single-nucleus ATAC sequencing analyses revealed that seven core target genes associated with musk secretion (Hsd17b2, Acacb, Lss, Vapa, Aldh16a1, Aldh7a1, and Sqle) were regulated by 12 core transcription factors (FOXO1, CUX2, RORA, RUNX1, KLF6, MGA, NFIC, FOXO3, ETV5, NR3C1, HSF4, and MITF) during the development of Cluster 0 acinar cells. Kyoto Encyclopedia of Genes and Genomes enrichment showed significant changes in the pathways associated with musk secretion during acinar cell development. Gene set variation analysis also revealed that certain pathways associated with musk secretion were enriched in 6-year-old acinar cells. A gene co-expression network was constructed during acinar cell development to provide a precise understanding of the connections between transcription factors, genes, and pathways. Finally, intercellular communication analysis showed that intercellular communication is involved in musk gland development. This study provides crucial insights into the changes and key factors underlying musk gland development, which serve as valuable resources for studying musk secretion mechanisms and promoting the protection of this endangered species.
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Affiliation(s)
- Chenmiao Liu
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, China
| | - Tingting Hong
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, China
| | - Chengcheng Zhao
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, China
| | - Tao Xue
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, China
| | - Shuhui Wang
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, China
| | - Zhanjun Ren
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, China
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10
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Liu C, Hong T, Yu L, Chen Y, Dong X, Ren Z. Single-nucleus multiomics unravels the genetic mechanisms underlying musk secretion in Chinese forest musk deer (Moschus berezovskii). Int J Biol Macromol 2024; 279:135050. [PMID: 39214228 DOI: 10.1016/j.ijbiomac.2024.135050] [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: 12/21/2023] [Revised: 08/13/2024] [Accepted: 08/22/2024] [Indexed: 09/04/2024]
Abstract
Musk secreted by the musk glands in male forest musk deer (FMD; Moschus berezovskii) is highly valued for its pharmaceutical and perfumery applications. However, the regulatory mechanisms underlying musk secretion are not well understood. This study aimed to investigate the genes and transcription factors involved in musk secretion across different periods and ages. We analyzed the musk glands of adult male FMD during the non-secretory and secretory periods, as well as juvenile and adult male FMD during the secretory period, using single-cell multiome ATAC+gene expression technique. Our analysis identified 13 cell types, including acinar cells of Types 1 and 2. Chromatin accessibility analysis and gene expression data confirmed that the genes Map3k2, Hsd17b12, and Jun are critical for musk secretion. Additionally, EHF, NR4A2, and FOXO1 proteins play crucial regulatory roles. Weighted gene co-expression network analysis (WGCNA) highlighted the importance of GnRH signaling pathway in musk secretion. Gene set enrichment analysis (GSEA) showed that the steroid hormone biosynthesis pathway is notably enriched in acinar cells. Furthermore, intercellular communication appears to influence both the initiation and maintenance of musk secretion. These findings provide valuable insights into the molecular pathways of musk secretion in FMD, offering potential avenues for increasing musk production and developing treatment for inflammation and tumors.
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Affiliation(s)
- Chenmiao Liu
- College of Animal Science and Technology, Northwest A&F University, Yangling 712100, Shaanxi, China
| | - Tingting Hong
- College of Animal Science and Technology, Northwest A&F University, Yangling 712100, Shaanxi, China
| | - Lin Yu
- College of Animal Science and Technology, Northwest A&F University, Yangling 712100, Shaanxi, China
| | - Yuan Chen
- College of Animal Science and Technology, Northwest A&F University, Yangling 712100, Shaanxi, China
| | - Xianggui Dong
- College of Animal Science and Technology, Northwest A&F University, Yangling 712100, Shaanxi, China.
| | - Zhanjun Ren
- College of Animal Science and Technology, Northwest A&F University, Yangling 712100, Shaanxi, China.
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11
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Saraswathy VM, Zhou L, Mokalled MH. Single-cell analysis of innate spinal cord regeneration identifies intersecting modes of neuronal repair. Nat Commun 2024; 15:6808. [PMID: 39147780 PMCID: PMC11327264 DOI: 10.1038/s41467-024-50628-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: 11/23/2023] [Accepted: 07/11/2024] [Indexed: 08/17/2024] Open
Abstract
Adult zebrafish have an innate ability to recover from severe spinal cord injury. Here, we report a comprehensive single nuclear RNA sequencing atlas that spans 6 weeks of regeneration. We identify cooperative roles for adult neurogenesis and neuronal plasticity during spinal cord repair. Neurogenesis of glutamatergic and GABAergic neurons restores the excitatory/inhibitory balance after injury. In addition, a transient population of injury-responsive neurons (iNeurons) show elevated plasticity 1 week post-injury. We found iNeurons are injury-surviving neurons that acquire a neuroblast-like gene expression signature after injury. CRISPR/Cas9 mutagenesis showed iNeurons are required for functional recovery and employ vesicular trafficking as an essential mechanism that underlies neuronal plasticity. This study provides a comprehensive resource of the cells and mechanisms that direct spinal cord regeneration and establishes zebrafish as a model of plasticity-driven neural repair.
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Affiliation(s)
- Vishnu Muraleedharan Saraswathy
- Department of Developmental Biology, Washington University School of Medicine, St. Louis, MO, USA
- Center of Regenerative Medicine, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
| | - Lili Zhou
- Department of Developmental Biology, Washington University School of Medicine, St. Louis, MO, USA
- Center of Regenerative Medicine, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
| | - Mayssa H Mokalled
- Department of Developmental Biology, Washington University School of Medicine, St. Louis, MO, USA.
- Center of Regenerative Medicine, Washington University School of Medicine, St. Louis, MO, USA.
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA.
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12
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Rastogi M, Bartolucci M, Nanni M, Aloisio M, Vozzi D, Petretto A, Contestabile A, Cancedda L. Integrative multi-omic analysis reveals conserved cell-projection deficits in human Down syndrome brains. Neuron 2024; 112:2503-2523.e10. [PMID: 38810652 DOI: 10.1016/j.neuron.2024.05.002] [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: 01/02/2023] [Revised: 03/17/2024] [Accepted: 05/01/2024] [Indexed: 05/31/2024]
Abstract
Down syndrome (DS) is the most common genetic cause of cognitive disability. However, it is largely unclear how triplication of a small gene subset may impinge on diverse aspects of DS brain physiopathology. Here, we took a multi-omic approach and simultaneously analyzed by RNA-seq and proteomics the expression signatures of two diverse regions of human postmortem DS brains. We found that the overexpression of triplicated genes triggered global expression dysregulation, differentially affecting transcripts, miRNAs, and proteins involved in both known and novel biological candidate pathways. Among the latter, we observed an alteration in RNA splicing, specifically modulating the expression of genes involved in cytoskeleton and axonal dynamics in DS brains. Accordingly, we found an alteration in axonal polarization in neurons from DS human iPSCs and mice. Thus, our study provides an integrated multilayer expression database capable of identifying new potential targets to aid in designing future clinical interventions for DS.
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Affiliation(s)
- Mohit Rastogi
- Brain Development and Disease Laboratory, Istituto Italiano di Tecnologia, Genova 16163, Italy
| | - Martina Bartolucci
- Core Facilities - Clinical Proteomics and Metabolomics, IRCCS Istituto Giannina Gaslini, Genova 16147, Italy
| | - Marina Nanni
- Brain Development and Disease Laboratory, Istituto Italiano di Tecnologia, Genova 16163, Italy
| | | | - Diego Vozzi
- Central RNA Laboratory, Istituto Italiano di Tecnologia, Genova 16152, Italy
| | - Andrea Petretto
- Core Facilities - Clinical Proteomics and Metabolomics, IRCCS Istituto Giannina Gaslini, Genova 16147, Italy
| | - Andrea Contestabile
- Brain Development and Disease Laboratory, Istituto Italiano di Tecnologia, Genova 16163, Italy.
| | - Laura Cancedda
- Brain Development and Disease Laboratory, Istituto Italiano di Tecnologia, Genova 16163, Italy; Dulbecco Telethon Institute, Rome 00185, Italy.
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13
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Yan Y, Zhu S, Jia M, Chen X, Qi W, Gu F, Valencak TG, Liu JX, Sun HZ. Advances in single-cell transcriptomics in animal research. J Anim Sci Biotechnol 2024; 15:102. [PMID: 39090689 PMCID: PMC11295521 DOI: 10.1186/s40104-024-01063-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2024] [Accepted: 06/12/2024] [Indexed: 08/04/2024] Open
Abstract
Understanding biological mechanisms is fundamental for improving animal production and health to meet the growing demand for high-quality protein. As an emerging biotechnology, single-cell transcriptomics has been gradually applied in diverse aspects of animal research, offering an effective method to study the gene expression of high-throughput single cells of different tissues/organs in animals. In an unprecedented manner, researchers have identified cell types/subtypes and their marker genes, inferred cellular fate trajectories, and revealed cell‒cell interactions in animals using single-cell transcriptomics. In this paper, we introduce the development of single-cell technology and review the processes, advancements, and applications of single-cell transcriptomics in animal research. We summarize recent efforts using single-cell transcriptomics to obtain a more profound understanding of animal nutrition and health, reproductive performance, genetics, and disease models in different livestock species. Moreover, the practical experience accumulated based on a large number of cases is highlighted to provide a reference for determining key factors (e.g., sample size, cell clustering, and cell type annotation) in single-cell transcriptomics analysis. We also discuss the limitations and outlook of single-cell transcriptomics in the current stage. This paper describes the comprehensive progress of single-cell transcriptomics in animal research, offering novel insights and sustainable advancements in agricultural productivity and animal health.
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Affiliation(s)
- Yunan Yan
- Institute of Dairy Science, Ministry of Education Key Laboratory of Molecular Animal Nutrition, College of Animal Sciences, Zhejiang University, Hangzhou, 310058, China
| | - Senlin Zhu
- Institute of Dairy Science, Ministry of Education Key Laboratory of Molecular Animal Nutrition, College of Animal Sciences, Zhejiang University, Hangzhou, 310058, China
| | - Minghui Jia
- Institute of Dairy Science, Ministry of Education Key Laboratory of Molecular Animal Nutrition, College of Animal Sciences, Zhejiang University, Hangzhou, 310058, China
| | - Xinyi Chen
- Institute of Dairy Science, Ministry of Education Key Laboratory of Molecular Animal Nutrition, College of Animal Sciences, Zhejiang University, Hangzhou, 310058, China
| | - Wenlingli Qi
- Institute of Dairy Science, Ministry of Education Key Laboratory of Molecular Animal Nutrition, College of Animal Sciences, Zhejiang University, Hangzhou, 310058, China
| | - Fengfei Gu
- Institute of Dairy Science, Ministry of Education Key Laboratory of Molecular Animal Nutrition, College of Animal Sciences, Zhejiang University, Hangzhou, 310058, China
- Key Laboratory of Dairy Cow Genetic Improvement and Milk Quality Research of Zhejiang Province, Zhejiang University, Hangzhou, 310058, China
| | - Teresa G Valencak
- Institute of Dairy Science, Ministry of Education Key Laboratory of Molecular Animal Nutrition, College of Animal Sciences, Zhejiang University, Hangzhou, 310058, China
- Agency for Health and Food Safety Austria, 1220, Vienna, Austria
| | - Jian-Xin Liu
- Institute of Dairy Science, Ministry of Education Key Laboratory of Molecular Animal Nutrition, College of Animal Sciences, Zhejiang University, Hangzhou, 310058, China
| | - Hui-Zeng Sun
- Institute of Dairy Science, Ministry of Education Key Laboratory of Molecular Animal Nutrition, College of Animal Sciences, Zhejiang University, Hangzhou, 310058, China.
- Key Laboratory of Dairy Cow Genetic Improvement and Milk Quality Research of Zhejiang Province, Zhejiang University, Hangzhou, 310058, China.
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14
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Huang Y, Wang M, Ni H, Zhang J, Li A, Hu B, Junqueira Alves C, Wahane S, Rios de Anda M, Ho L, Li Y, Kang S, Neff R, Kostic A, Buxbaum JD, Crary JF, Brennand KJ, Zhang B, Zou H, Friedel RH. Regulation of cell distancing in peri-plaque glial nets by Plexin-B1 affects glial activation and amyloid compaction in Alzheimer's disease. Nat Neurosci 2024; 27:1489-1504. [PMID: 38802590 PMCID: PMC11346591 DOI: 10.1038/s41593-024-01664-w] [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: 10/13/2021] [Accepted: 04/22/2024] [Indexed: 05/29/2024]
Abstract
Communication between glial cells has a profound impact on the pathophysiology of Alzheimer's disease (AD). We reveal here that reactive astrocytes control cell distancing in peri-plaque glial nets, which restricts microglial access to amyloid deposits. This process is governed by guidance receptor Plexin-B1 (PLXNB1), a network hub gene in individuals with late-onset AD that is upregulated in plaque-associated astrocytes. Plexin-B1 deletion in a mouse AD model led to reduced number of reactive astrocytes and microglia in peri-plaque glial nets, but higher coverage of plaques by glial processes, along with transcriptional changes signifying reduced neuroinflammation. Additionally, a reduced footprint of glial nets was associated with overall lower plaque burden, a shift toward dense-core-type plaques and reduced neuritic dystrophy. Altogether, our study demonstrates that Plexin-B1 regulates peri-plaque glial net activation in AD. Relaxing glial spacing by targeting guidance receptors may present an alternative strategy to increase plaque compaction and reduce neuroinflammation in AD.
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Affiliation(s)
- Yong Huang
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Mount Sinai Center for Transformative Disease Modeling, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Minghui Wang
- Department of Genetics and Genomic Sciences, Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Mount Sinai Center for Transformative Disease Modeling, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Haofei Ni
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- School of Medicine, Tongji University, Shanghai, China
| | - Jinglong Zhang
- Department of Genetics and Genomic Sciences, Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Mount Sinai Center for Transformative Disease Modeling, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Aiqun Li
- Department of Genetics and Genomic Sciences, Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Mount Sinai Center for Transformative Disease Modeling, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Bin Hu
- Department of Genetics and Genomic Sciences, Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Mount Sinai Center for Transformative Disease Modeling, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Chrystian Junqueira Alves
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Shalaka Wahane
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Mitzy Rios de Anda
- Seaver Autism Center, Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Lap Ho
- Department of Genetics and Genomic Sciences, Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Mount Sinai Center for Transformative Disease Modeling, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Yuhuan Li
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Orthopedics, the Second Affiliated Hospital of Xi'an Jiaotong University, Xi'An, China
| | - Sangjo Kang
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ryan Neff
- Department of Genetics and Genomic Sciences, Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Mount Sinai Center for Transformative Disease Modeling, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ana Kostic
- Seaver Autism Center, Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Joseph D Buxbaum
- Seaver Autism Center, Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - John F Crary
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Pathology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Artificial Intelligence and Human Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Mount Sinai Neuropathology Brain Bank & Research Core, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Ronald M. Loeb Center for Alzheimer's Disease, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Kristen J Brennand
- Departments of Psychiatry and Genetics, Wu Tsai Institute, Yale University School of Medicine, New Haven, CT, USA
| | - Bin Zhang
- Department of Genetics and Genomic Sciences, Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Mount Sinai Center for Transformative Disease Modeling, 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.
| | - Hongyan Zou
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Department of Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
| | - Roland H Friedel
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Department of Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
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15
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Schwalbe DC, Stornetta DS, Abraham-Fan RJ, Souza GMPR, Jalil M, Crook ME, Campbell JN, Abbott SBG. Molecular Organization of Autonomic, Respiratory, and Spinally-Projecting Neurons in the Mouse Ventrolateral Medulla. J Neurosci 2024; 44:e2211232024. [PMID: 38918066 PMCID: PMC11293450 DOI: 10.1523/jneurosci.2211-23.2024] [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: 11/28/2023] [Revised: 06/05/2024] [Accepted: 06/11/2024] [Indexed: 06/27/2024] Open
Abstract
The ventrolateral medulla (VLM) is a crucial region in the brain for visceral and somatic control, serving as a significant source of synaptic input to the spinal cord. Experimental studies have shown that gene expression in individual VLM neurons is predictive of their function. However, the molecular and cellular organization of the VLM has remained uncertain. This study aimed to create a comprehensive dataset of VLM cells using single-cell RNA sequencing in male and female mice. The dataset was enriched with targeted sequencing of spinally-projecting and adrenergic/noradrenergic VLM neurons. Based on differentially expressed genes, the resulting dataset of 114,805 VLM cells identifies 23 subtypes of neurons, excluding those in the inferior olive, and five subtypes of astrocytes. Spinally-projecting neurons were found to be abundant in seven subtypes of neurons, which were validated through in situ hybridization. These subtypes included adrenergic/noradrenergic neurons, serotonergic neurons, and neurons expressing gene markers associated with premotor neurons in the ventromedial medulla. Further analysis of adrenergic/noradrenergic neurons and serotonergic neurons identified nine and six subtypes, respectively, within each class of monoaminergic neurons. Marker genes that identify the neural network responsible for breathing were concentrated in two subtypes of neurons, delineated from each other by markers for excitatory and inhibitory neurons. These datasets are available for public download and for analysis with a user-friendly interface. Collectively, this study provides a fine-scale molecular identification of cells in the VLM, forming the foundation for a better understanding of the VLM's role in vital functions and motor control.
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Affiliation(s)
- Dana C Schwalbe
- Departments of Biology, University of Virginia, Charlottesville, Virginia 22904
| | | | | | | | - Maira Jalil
- Departments of Biology, University of Virginia, Charlottesville, Virginia 22904
| | - Maisie E Crook
- Departments of Biology, University of Virginia, Charlottesville, Virginia 22904
| | - John N Campbell
- Departments of Biology, University of Virginia, Charlottesville, Virginia 22904
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16
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Gliko O, Mallory M, Dalley R, Gala R, Gornet J, Zeng H, Sorensen SA, Sümbül U. High-throughput analysis of dendrite and axonal arbors reveals transcriptomic correlates of neuroanatomy. Nat Commun 2024; 15:6337. [PMID: 39068160 PMCID: PMC11283452 DOI: 10.1038/s41467-024-50728-9] [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: 12/01/2023] [Accepted: 07/16/2024] [Indexed: 07/30/2024] Open
Abstract
Neuronal anatomy is central to the organization and function of brain cell types. However, anatomical variability within apparently homogeneous populations of cells can obscure such insights. Here, we report large-scale automation of neuronal morphology reconstruction and analysis on a dataset of 813 inhibitory neurons characterized using the Patch-seq method, which enables measurement of multiple properties from individual neurons, including local morphology and transcriptional signature. We demonstrate that these automated reconstructions can be used in the same manner as manual reconstructions to understand the relationship between some, but not all, cellular properties used to define cell types. We uncover gene expression correlates of laminar innervation on multiple transcriptomically defined neuronal subclasses and types. In particular, our results reveal correlates of the variability in Layer 1 (L1) axonal innervation in a transcriptomically defined subpopulation of Martinotti cells in the adult mouse neocortex.
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Affiliation(s)
| | | | | | | | - James Gornet
- California Institute of Technology, Pasadena, CA, USA
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17
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Sorek G, Haim Y, Chalifa-Caspi V, Lazarescu O, Ziv-Agam M, Hagemann T, Nono Nankam PA, Blüher M, Liberty IF, Dukhno O, Kukeev I, Yeger-Lotem E, Rudich A, Levin L. sNucConv: A bulk RNA-seq deconvolution method trained on single-nucleus RNA-seq data to estimate cell-type composition of human adipose tissues. iScience 2024; 27:110368. [PMID: 39071890 PMCID: PMC11277759 DOI: 10.1016/j.isci.2024.110368] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2023] [Revised: 02/27/2024] [Accepted: 06/21/2024] [Indexed: 07/30/2024] Open
Abstract
Deconvolution algorithms mostly rely on single-cell RNA-sequencing (scRNA-seq) data applied onto bulk RNA-sequencing (bulk RNA-seq) to estimate tissues' cell-type composition, with performance accuracy validated on deposited databases. Adipose tissues' cellular composition is highly variable, and adipocytes can only be captured by single-nucleus RNA-sequencing (snRNA-seq). Here we report the development of sNucConv, a Scaden deep-learning-based deconvolution tool, trained using 5 hSAT and 7 hVAT snRNA-seq-based data corrected by (i) snRNA-seq/bulk RNA-seq highly correlated genes and (ii) individual cell-type regression models. Applying sNucConv on our bulk RNA-seq data resulted in cell-type proportion estimation of 15 and 13 cell types, with accuracy of R = 0.93 (range: 0.76-0.97) and R = 0.95 (range: 0.92-0.98) for hVAT and hSAT, respectively. This performance level was further validated on an independent set of samples (5 hSAT; 5 hVAT). The resulting model was depot specific, reflecting depot differences in gene expression patterns. Jointly, sNucConv provides proof-of-concept for producing validated deconvolution models for tissues un-amenable to scRNA-seq.
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Affiliation(s)
- Gil Sorek
- Bioinformatics Core Facility, llse Katz Institute for Nanoscale Science and Technology, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Yulia Haim
- Department of Clinical Biochemistry and Pharmacology, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Vered Chalifa-Caspi
- Bioinformatics Core Facility, llse Katz Institute for Nanoscale Science and Technology, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Or Lazarescu
- Department of Clinical Biochemistry and Pharmacology, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Maya Ziv-Agam
- Department of Clinical Biochemistry and Pharmacology, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Tobias Hagemann
- Helmholtz Institute for Metabolic, Obesity and Vascular Research (HI-MAG) of the Helmholtz Zentrum München at the University of Leipzig and University Hospital Leipzig, Leipzig, Germany
| | - Pamela Arielle Nono Nankam
- Helmholtz Institute for Metabolic, Obesity and Vascular Research (HI-MAG) of the Helmholtz Zentrum München at the University of Leipzig and University Hospital Leipzig, Leipzig, Germany
| | - Matthias Blüher
- Helmholtz Institute for Metabolic, Obesity and Vascular Research (HI-MAG) of the Helmholtz Zentrum München at the University of Leipzig and University Hospital Leipzig, Leipzig, Germany
| | - Idit F. Liberty
- Soroka University Medical Center, and the Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Oleg Dukhno
- Soroka University Medical Center, and the Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Ivan Kukeev
- Soroka University Medical Center, and the Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Esti Yeger-Lotem
- Department of Clinical Biochemistry and Pharmacology, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Assaf Rudich
- Department of Clinical Biochemistry and Pharmacology, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Liron Levin
- Bioinformatics Core Facility, llse Katz Institute for Nanoscale Science and Technology, Ben-Gurion University of the Negev, Beer-Sheva, Israel
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18
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Webster AN, Becker JJ, Li C, Schwalbe DC, Kerspern D, Karolczak EO, Godschall EN, Belmont-Rausch DM, Pers TH, Lutas A, Habib N, Güler AD, Krashes MJ, Campbell JN. Molecular Connectomics Reveals a Glucagon-Like Peptide 1 Sensitive Neural Circuit for Satiety. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.10.31.564990. [PMID: 37961449 PMCID: PMC10635031 DOI: 10.1101/2023.10.31.564990] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Liraglutide and other agonists of the glucagon-like peptide 1 receptor (GLP-1RAs) are effective weight loss drugs, but how they suppress appetite remains unclear. One potential mechanism is by activating neurons which inhibit hunger-promoting Agouti-related peptide (AgRP) neurons of the arcuate hypothalamus (Arc). To identify these afferents, we developed a method combining rabies-based connectomics with single-nuclei transcriptomics. Applying this method to AgRP neurons predicted at least 21 afferent subtypes in the mouse mediobasal and paraventricular hypothalamus. Among these are Trh+ Arc neurons, inhibitory neurons which express the Glp1r gene and are activated by the GLP-1RA liraglutide. Activating Trh+ Arc neurons inhibits AgRP neurons and feeding in an AgRP neuron-dependent manner. Silencing Trh+ Arc neurons causes over-eating and weight gain and attenuates liraglutide's effect on body weight. Our results demonstrate a widely applicable method for molecular connectomics, comprehensively identify local inputs to AgRP neurons, and reveal a circuit through which GLP-1RAs suppress appetite.
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Affiliation(s)
- Addison N. Webster
- Neuroscience Graduate Program, University of Virginia, Charlottesville, VA, U.S.A
| | - Jordan J. Becker
- Section on Motivational Processes Underlying Appetite, Diabetes, Endocrinology, & Obesity Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD, U.S.A
| | - Chia Li
- Section on Motivational Processes Underlying Appetite, Diabetes, Endocrinology, & Obesity Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD, U.S.A
| | - Dana C. Schwalbe
- Department of Biology, University of Virginia, Charlottesville, VA, U.S.A
| | - Damien Kerspern
- Section on Motivational Processes Underlying Appetite, Diabetes, Endocrinology, & Obesity Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD, U.S.A
| | - Eva O. Karolczak
- Section on Motivational Processes Underlying Appetite, Diabetes, Endocrinology, & Obesity Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD, U.S.A
| | | | | | - Tune H. Pers
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
| | - Andrew Lutas
- Section on Motivational Processes Underlying Appetite, Diabetes, Endocrinology, & Obesity Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD, U.S.A
| | - Naomi Habib
- Center for Brain Sciences, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Ali D. Güler
- Department of Biology, University of Virginia, Charlottesville, VA, U.S.A
| | - Michael J. Krashes
- Section on Motivational Processes Underlying Appetite, Diabetes, Endocrinology, & Obesity Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD, U.S.A
| | - John N. Campbell
- Neuroscience Graduate Program, University of Virginia, Charlottesville, VA, U.S.A
- Department of Biology, University of Virginia, Charlottesville, VA, U.S.A
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19
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DeCasien AR, Chiou KL, Testard C, Mercer A, Negrón-Del Valle JE, Bauman Surratt SE, González O, Stock MK, Ruiz-Lambides AV, Martínez MI, Antón SC, Walker CS, Sallet J, Wilson MA, Brent LJN, Montague MJ, Sherwood CC, Platt ML, Higham JP, Snyder-Mackler N. Evolutionary and biomedical implications of sex differences in the primate brain transcriptome. CELL GENOMICS 2024; 4:100589. [PMID: 38942023 PMCID: PMC11293591 DOI: 10.1016/j.xgen.2024.100589] [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: 06/15/2023] [Revised: 12/28/2023] [Accepted: 05/31/2024] [Indexed: 06/30/2024]
Abstract
Humans exhibit sex differences in the prevalence of many neurodevelopmental disorders and neurodegenerative diseases. Here, we generated one of the largest multi-brain-region bulk transcriptional datasets for the rhesus macaque and characterized sex-biased gene expression patterns to investigate the translatability of this species for sex-biased neurological conditions. We identify patterns similar to those in humans, which are associated with overlapping regulatory mechanisms, biological processes, and genes implicated in sex-biased human disorders, including autism. We also show that sex-biased genes exhibit greater genetic variance for expression and more tissue-specific expression patterns, which may facilitate rapid evolution of sex-biased genes. Our findings provide insights into the biological mechanisms underlying sex-biased disease and support the rhesus macaque model for the translational study of these conditions.
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Affiliation(s)
- Alex R DeCasien
- Department of Anthropology, New York University, New York, NY, USA; New York Consortium in Evolutionary Primatology, New York, NY, USA; Section on Developmental Neurogenomics, National Institute of Mental Health, Bethesda, MD, USA.
| | - Kenneth L Chiou
- Center for Evolution and Medicine, Arizona State University, Tempe, AZ, USA; School of Life Sciences, Arizona State University, Tempe, AZ, USA; Department of Psychology, University of Washington, Seattle, WA, USA; Nathan Shock Center of Excellence in the Basic Biology of Aging, University of Washington, Seattle, WA, USA.
| | - Camille Testard
- Department of Neuroscience, University of Pennsylvania, Philadelphia, PA, USA
| | - Arianne Mercer
- Department of Psychology, University of Washington, Seattle, WA, USA
| | | | | | - Olga González
- Southwest National Primate Research Center, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - Michala K Stock
- Department of Sociology and Anthropology, Metropolitan State University of Denver, Denver, CO, USA
| | | | - Melween I Martínez
- Caribbean Primate Research Center, University of Puerto Rico, San Juan, PR, USA
| | - Susan C Antón
- Department of Anthropology, New York University, New York, NY, USA; New York Consortium in Evolutionary Primatology, New York, NY, USA
| | - Christopher S Walker
- Department of Molecular Biomedical Sciences, College of Veterinary Medicine, North Carolina State University, Raleigh, NC, USA
| | - Jérôme Sallet
- Stem Cell and Brain Research Institute, Université Lyon, Lyon, France
| | - Melissa A Wilson
- Center for Evolution and Medicine, Arizona State University, Tempe, AZ, USA; School of Life Sciences, Arizona State University, Tempe, AZ, USA; Biodesign Center for Mechanisms of Evolution, Arizona State University, Tempe, AZ, USA
| | - Lauren J N Brent
- Centre for Research in Animal Behavior, University of Exeter, Exeter, UK
| | - Michael J Montague
- Department of Neuroscience, University of Pennsylvania, Philadelphia, PA, USA
| | - Chet C Sherwood
- Department of Anthropology, The George Washington University, Washington, DC, USA
| | - Michael L Platt
- Department of Neuroscience, University of Pennsylvania, Philadelphia, PA, USA; Department of Psychology, University of Pennsylvania, Philadelphia, PA, USA; Department of Marketing, University of Pennsylvania, Philadelphia, PA, USA
| | - James P Higham
- Department of Anthropology, New York University, New York, NY, USA; New York Consortium in Evolutionary Primatology, New York, NY, USA.
| | - Noah Snyder-Mackler
- Center for Evolution and Medicine, Arizona State University, Tempe, AZ, USA; School of Life Sciences, Arizona State University, Tempe, AZ, USA; Department of Psychology, University of Washington, Seattle, WA, USA; Nathan Shock Center of Excellence in the Basic Biology of Aging, University of Washington, Seattle, WA, USA; ASU-Banner Neurodegenerative Disease Research Center, Arizona State University, Tempe, AZ, USA.
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20
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Liharska L, Charney A. Transcriptomics : Approaches to Quantifying Gene Expression and Their Application to Studying the Human Brain. Curr Top Behav Neurosci 2024. [PMID: 38972894 DOI: 10.1007/7854_2024_466] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/09/2024]
Abstract
To date, the field of transcriptomics has been characterized by rapid methods development and technological advancement, with new technologies continuously rendering older ones obsolete.This chapter traces the evolution of approaches to quantifying gene expression and provides an overall view of the current state of the field of transcriptomics, its applications to the study of the human brain, and its place in the broader emerging multiomics landscape.
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Affiliation(s)
- Lora Liharska
- Icahn School of Medicine at Mount Sinai, New York, NY, USA.
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21
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Liao Z, Zhang Q, Ren N, Zhao H, Zheng X. Progress in mitochondrial and omics studies in Alzheimer's disease research: from molecular mechanisms to therapeutic interventions. Front Immunol 2024; 15:1418939. [PMID: 39040111 PMCID: PMC11260616 DOI: 10.3389/fimmu.2024.1418939] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2024] [Accepted: 06/21/2024] [Indexed: 07/24/2024] Open
Abstract
Alzheimer's disease (Alzheimer's disease, AD) is a progressive neurological disorder characterized by memory loss and cognitive impairment. It is characterized by the formation of tau protein neurofibrillary tangles and β-amyloid plaques. Recent studies have found that mitochondria in neuronal cells of AD patients exhibit various dysfunctions, including reduced numbers, ultrastructural changes, reduced enzyme activity, and abnormal kinetics. These abnormal mitochondria not only lead to the loss of normal neuronal cell function, but are also a major driver of AD progression. In this review, we will focus on the advances of mitochondria and their multi-omics in AD research, with particular emphasis on how mitochondrial dysfunction in AD drives disease progression. At the same time, we will focus on summarizing how mitochondrial genomics technologies have revealed specific details of these dysfunctions and how therapeutic strategies targeting mitochondria may provide new directions for future AD treatments. By delving into the key mechanisms of mitochondria in AD related to energy metabolism, altered kinetics, regulation of cell death, and dysregulation of calcium-ion homeostasis, and how mitochondrial multi-omics technologies can be utilized to provide us with a better understanding of these processes. In the future, mitochondria-centered therapeutic strategies will be a key idea in the treatment of AD.
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Affiliation(s)
- Zuning Liao
- Department of Neurology, Fourth People’s Hospital of Jinan, Jinan, China
| | - Qiying Zhang
- Department of Internal Medicine, Jinan Municipal Government Hospital, Jinan, China
| | - Na Ren
- Pharmacy Department, Jinan Municipal People’s Government Organs Outpatient Department, Jinan, China
| | - Haiyan Zhao
- Department of Pharmacy, Qihe County People’s Hospital, Dezhou, China
| | - Xueyan Zheng
- Department of Pharmacy, Jinan Second People’s Hospital, Jinan, China
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22
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Zhu Y, Zhang Y, He S, Yi S, Feng H, Xia X, Fang X, Gong X, Zhao P. Integrating single-nucleus RNA sequencing and spatial transcriptomics to elucidate a specialized subpopulation of astrocytes, microglia and vascular cells in brains of mouse model of lipopolysaccharide-induced sepsis-associated encephalopathy. J Neuroinflammation 2024; 21:169. [PMID: 38961424 PMCID: PMC11223438 DOI: 10.1186/s12974-024-03161-0] [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: 02/22/2024] [Accepted: 06/26/2024] [Indexed: 07/05/2024] Open
Abstract
BACKGROUND Understanding the mechanism behind sepsis-associated encephalopathy (SAE) remains a formidable task. This study endeavors to shed light on the complex cellular and molecular alterations that occur in the brains of a mouse model with SAE, ultimately unraveling the underlying mechanisms of this condition. METHODS We established a murine model using intraperitoneal injection of lipopolysaccharide (LPS) in wild type and Anxa1-/- mice and collected brain tissues for analysis at 0-hour, 12-hour, 24-hour, and 72-hour post-injection. Utilizing advanced techniques such as single-nucleus RNA sequencing (snRNA-seq) and Stereo-seq, we conducted a comprehensive characterization of the cellular responses and molecular patterns within the brain. RESULTS Our study uncovered notable temporal differences in the response to LPS challenge between Anxa1-/- (annexin A1 knockout) and wild type mice, specifically at the 12-hour and 24-hour time points following injection. We observed a significant increase in the proportion of Astro-2 and Micro-2 cells in these mice. These cells exhibited a colocalization pattern with the vascular subtype Vas-1, forming a distinct region known as V1A2M2, where Astro-2 and Micro-2 cells surrounded Vas-1. Moreover, through further analysis, we discovered significant upregulation of ligands and receptors such as Timp1-Cd63, Timp1-Itgb1, Timp1-Lrp1, as well as Ccl2-Ackr1 and Cxcl2-Ackr1 within this region. In addition, we observed a notable increase in the expression of Cd14-Itgb1, Cd14-Tlr2, and Cd14-C3ar1 in regions enriched with Micro-2 cells. Additionally, Cxcl10-Sdc4 showed broad upregulation in brain regions containing both Micro-2 and Astro-2 cells. Notably, upon LPS challenge, there was an observed increase in Anxa1 expression in the mouse brain. Furthermore, our study revealed a noteworthy increase in mortality rates following Anxa1 knockdown. However, we did not observe substantial differences in the types, numbers, or distribution of other brain cells between Anxa1-/- and wildtype mice over time. Nevertheless, when comparing the 24-hour post LPS injection time point, we observed a significant decrease in the proportion and distribution of Micro-2 and Astro-2 cells in the vicinity of blood vessels in Anxa1-/- mice. Additionally, we noted reduced expression levels of several ligand-receptor pairs including Cd14-Tlr2, Cd14-C3ar1, Cd14-Itgb1, Cxcl10-Sdc4, Ccl2-Ackr1, and Cxcl2-Ackr1. CONCLUSIONS By combining snRNA-seq and Stereo-seq techniques, our study successfully identified a distinctive cellular colocalization, referred to as a special pathological niche, comprising Astro-2, Micro-2, and Vas-1 cells. Furthermore, we observed an upregulation of ligand-receptor pairs within this niche. These findings suggest a potential association between this cellular arrangement and the underlying mechanisms contributing to SAE or the increased mortality observed in Anxa1 knockdown mice.
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Grants
- 2021A1515012429 Natural Science Foundation of Guangdong Province, China
- 211102114530659 Shaoguan Municipal Science and Technology Program, China
- 20221807 Shaoguan Engineering Research Center for Research and Development of Molecular and Cellular Technology in Rapid Diagnosis of Infectious Diseases and Cancer Program, China
- KEYANSHEN (2023) 01 Research Fund for Joint Laboratory for Digital and Precise Detection of Clinical Pathogens, Yuebei People's Hospital Affiliated to Shantou University Medical College, China
- RS202001 Research Project for Outstanding Scholar of Yuebei People's Hospital, Shantou University Medical College, China
- Research Fund for Joint Laboratory for Digital and Precise Detection of Clinical Pathogens, Yuebei People’s Hospital Affiliated to Shantou University Medical College, China
- Research Project for Outstanding Scholar of Yuebei People’s Hospital, Shantou University Medical College, China
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Affiliation(s)
- Yanyan Zhu
- Department of Laboratory Medicine, Yuebei People's Hospital, Shantou University Medical College, No 133, Huimin Road South, Wujiang District, Shaoguan, 512025, China
- Laboratory for Diagnosis of Clinical Microbiology and Infection, Yuebei People's Hospital, Shantou University Medical College, Shaoguan, 512025, China
- Research Center for Interdisciplinary & High-quality Innovative Development in Laboratory Medicine, Shaoguan, 512025, China
- Shaoguan Municipal Quality Control Center for Laboratory Medicine, Yuebei People's Hospital, Shantou University Medical College, Shaoguan, 512025, China
- Shaoguan Municipal Quality Control Center for Surveillance of Bacterial Resistance, Shaoguan, 512025, China
- Shaoguan Engineering Research Center for Research and Development of Molecular and Cellular Technology in Rapid Diagnosis of Infectious Diseases and Cancer, Shaoguan, 512025, China
| | - Yin Zhang
- BGI-Shenzhen, Shenzhen, 518083, China
| | - Sheng He
- Department of Laboratory Medicine, Yuebei People's Hospital, Shantou University Medical College, No 133, Huimin Road South, Wujiang District, Shaoguan, 512025, China
- Laboratory for Diagnosis of Clinical Microbiology and Infection, Yuebei People's Hospital, Shantou University Medical College, Shaoguan, 512025, China
- Research Center for Interdisciplinary & High-quality Innovative Development in Laboratory Medicine, Shaoguan, 512025, China
- Shaoguan Municipal Quality Control Center for Laboratory Medicine, Yuebei People's Hospital, Shantou University Medical College, Shaoguan, 512025, China
- Shaoguan Municipal Quality Control Center for Surveillance of Bacterial Resistance, Shaoguan, 512025, China
- Shaoguan Engineering Research Center for Research and Development of Molecular and Cellular Technology in Rapid Diagnosis of Infectious Diseases and Cancer, Shaoguan, 512025, China
| | - Sanjun Yi
- Department of Laboratory Medicine, Yuebei People's Hospital, Shantou University Medical College, No 133, Huimin Road South, Wujiang District, Shaoguan, 512025, China
- Laboratory for Diagnosis of Clinical Microbiology and Infection, Yuebei People's Hospital, Shantou University Medical College, Shaoguan, 512025, China
- Research Center for Interdisciplinary & High-quality Innovative Development in Laboratory Medicine, Shaoguan, 512025, China
- Shaoguan Municipal Quality Control Center for Laboratory Medicine, Yuebei People's Hospital, Shantou University Medical College, Shaoguan, 512025, China
- Shaoguan Municipal Quality Control Center for Surveillance of Bacterial Resistance, Shaoguan, 512025, China
- Shaoguan Engineering Research Center for Research and Development of Molecular and Cellular Technology in Rapid Diagnosis of Infectious Diseases and Cancer, Shaoguan, 512025, China
| | - Hao Feng
- Jiaxing University Master Degree Cultivation Base, Zhejiang Chinese Medical University, Jiaxing, 314001, China
| | - Xianzhu Xia
- Department of Laboratory Medicine, Yuebei People's Hospital, Shantou University Medical College, No 133, Huimin Road South, Wujiang District, Shaoguan, 512025, China
- Laboratory for Diagnosis of Clinical Microbiology and Infection, Yuebei People's Hospital, Shantou University Medical College, Shaoguan, 512025, China
- Research Center for Interdisciplinary & High-quality Innovative Development in Laboratory Medicine, Shaoguan, 512025, China
| | | | - Xiaoqian Gong
- Yuebei People's Hospital, Shantou University Medical College, Shaoguan, 512025, China.
| | - Pingsen Zhao
- Department of Laboratory Medicine, Yuebei People's Hospital, Shantou University Medical College, No 133, Huimin Road South, Wujiang District, Shaoguan, 512025, China.
- Laboratory for Diagnosis of Clinical Microbiology and Infection, Yuebei People's Hospital, Shantou University Medical College, Shaoguan, 512025, China.
- Research Center for Interdisciplinary & High-quality Innovative Development in Laboratory Medicine, Shaoguan, 512025, China.
- Shaoguan Municipal Quality Control Center for Laboratory Medicine, Yuebei People's Hospital, Shantou University Medical College, Shaoguan, 512025, China.
- Shaoguan Municipal Quality Control Center for Surveillance of Bacterial Resistance, Shaoguan, 512025, China.
- Shaoguan Engineering Research Center for Research and Development of Molecular and Cellular Technology in Rapid Diagnosis of Infectious Diseases and Cancer, Shaoguan, 512025, China.
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23
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Rhaman MS, Ali M, Ye W, Li B. Opportunities and Challenges in Advancing Plant Research with Single-cell Omics. GENOMICS, PROTEOMICS & BIOINFORMATICS 2024; 22:qzae026. [PMID: 38996445 PMCID: PMC11423859 DOI: 10.1093/gpbjnl/qzae026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/12/2023] [Revised: 01/12/2024] [Accepted: 01/15/2024] [Indexed: 07/14/2024]
Abstract
Plants possess diverse cell types and intricate regulatory mechanisms to adapt to the ever-changing environment of nature. Various strategies have been employed to study cell types and their developmental progressions, including single-cell sequencing methods which provide high-dimensional catalogs to address biological concerns. In recent years, single-cell sequencing technologies in transcriptomics, epigenomics, proteomics, metabolomics, and spatial transcriptomics have been increasingly used in plant science to reveal intricate biological relationships at the single-cell level. However, the application of single-cell technologies to plants is more limited due to the challenges posed by cell structure. This review outlines the advancements in single-cell omics technologies, their implications in plant systems, future research applications, and the challenges of single-cell omics in plant systems.
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Affiliation(s)
- Mohammad Saidur Rhaman
- Peking University Institute of Advanced Agricultural Sciences, Shandong Laboratory of Advanced Agricultural Sciences in Weifang, Weifang 261325, China
| | - Muhammad Ali
- Peking University Institute of Advanced Agricultural Sciences, Shandong Laboratory of Advanced Agricultural Sciences in Weifang, Weifang 261325, China
| | - Wenxiu Ye
- Peking University Institute of Advanced Agricultural Sciences, Shandong Laboratory of Advanced Agricultural Sciences in Weifang, Weifang 261325, China
| | - Bosheng Li
- Peking University Institute of Advanced Agricultural Sciences, Shandong Laboratory of Advanced Agricultural Sciences in Weifang, Weifang 261325, China
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24
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Baum ML, Wilton DK, Fox RG, Carey A, Hsu YHH, Hu R, Jäntti HJ, Fahey JB, Muthukumar AK, Salla N, Crotty W, Scott-Hewitt N, Bien E, Sabatini DA, Lanser TB, Frouin A, Gergits F, Håvik B, Gialeli C, Nacu E, Lage K, Blom AM, Eggan K, McCarroll SA, Johnson MB, Stevens B. CSMD1 regulates brain complement activity and circuit development. Brain Behav Immun 2024; 119:317-332. [PMID: 38552925 DOI: 10.1016/j.bbi.2024.03.041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Revised: 02/29/2024] [Accepted: 03/26/2024] [Indexed: 04/16/2024] Open
Abstract
Complement proteins facilitate synaptic elimination during neurodevelopmental pruning, but neural complement regulation is not well understood. CUB and Sushi Multiple Domains 1 (CSMD1) can regulate complement activity in vitro, is expressed in the brain, and is associated with increased schizophrenia risk. Beyond this, little is known about CSMD1 including whether it regulates complement activity in the brain or otherwise plays a role in neurodevelopment. We used biochemical, immunohistochemical, and proteomic techniques to examine the regional, cellular, and subcellular distribution as well as protein interactions of CSMD1 in the brain. To evaluate whether CSMD1 is involved in complement-mediated synapse elimination, we examined Csmd1-knockout mice and CSMD1-knockout human stem cell-derived neurons. We interrogated synapse and circuit development of the mouse visual thalamus, a process that involves complement pathway activity. We also quantified complement deposition on synapses in mouse visual thalamus and on cultured human neurons. Finally, we assessed uptake of synaptosomes by cultured microglia. We found that CSMD1 is present at synapses and interacts with complement proteins in the brain. Mice lacking Csmd1 displayed increased levels of complement component C3, an increased colocalization of C3 with presynaptic terminals, fewer retinogeniculate synapses, and aberrant segregation of eye-specific retinal inputs to the visual thalamus during the critical period of complement-dependent refinement of this circuit. Loss of CSMD1 in vivo enhanced synaptosome engulfment by microglia in vitro, and this effect was dependent on activity of the microglial complement receptor, CR3. Finally, human stem cell-derived neurons lacking CSMD1 were more vulnerable to complement deposition. These data suggest that CSMD1 can function as a regulator of complement-mediated synapse elimination in the brain during development.
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Affiliation(s)
- Matthew L Baum
- Department of Neurology, F.M. Kirby Neurobiology Center, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; MD-PhD Program of Harvard & MIT, Harvard Medical School, Boston, MA 02115, USA
| | - Daniel K Wilton
- Department of Neurology, F.M. Kirby Neurobiology Center, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Rachel G Fox
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Alanna Carey
- Department of Neurology, F.M. Kirby Neurobiology Center, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Yu-Han H Hsu
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Ruilong Hu
- Department of Neurology, F.M. Kirby Neurobiology Center, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Henna J Jäntti
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Jaclyn B Fahey
- Department of Neurology, F.M. Kirby Neurobiology Center, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Allie K Muthukumar
- Department of Neurology, F.M. Kirby Neurobiology Center, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Nikkita Salla
- Department of Neurology, F.M. Kirby Neurobiology Center, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - William Crotty
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Stem Cell and Regenerative Biology and Harvard Stem Cell Institute, Harvard University, Cambridge, MA 02138, USA
| | - Nicole Scott-Hewitt
- Department of Neurology, F.M. Kirby Neurobiology Center, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Elizabeth Bien
- Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - David A Sabatini
- Department of Neurology, F.M. Kirby Neurobiology Center, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Toby B Lanser
- Department of Neurology, F.M. Kirby Neurobiology Center, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Arnaud Frouin
- Department of Neurology, F.M. Kirby Neurobiology Center, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Frederick Gergits
- Department of Neurology, F.M. Kirby Neurobiology Center, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | | | - Chrysostomi Gialeli
- Division of Medical Protein Chemistry, Department of Translational Medicine, Lund University, S-214 28 Malmö, Sweden; Cardiovascular Research - Translational Studies Research Group, Department of Clinical Sciences, Lund University, S-214 28 Malmö, Sweden
| | - Eugene Nacu
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Kasper Lage
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Anna M Blom
- Division of Medical Protein Chemistry, Department of Translational Medicine, Lund University, S-214 28 Malmö, Sweden
| | - Kevin Eggan
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Stem Cell and Regenerative Biology and Harvard Stem Cell Institute, Harvard University, Cambridge, MA 02138, USA
| | - Steven A McCarroll
- Department of Genetics, Harvard Medical School, Boston, MA 02115, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Matthew B Johnson
- Department of Neurology, F.M. Kirby Neurobiology Center, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
| | - Beth Stevens
- Department of Neurology, F.M. Kirby Neurobiology Center, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Howard Hughes Medical Institute, USA.
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25
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Kuo A, Hansen KD, Hicks SC. Quantification and statistical modeling of droplet-based single-nucleus RNA-sequencing data. Biostatistics 2024; 25:801-817. [PMID: 37257175 PMCID: PMC11247185 DOI: 10.1093/biostatistics/kxad010] [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: 05/20/2022] [Revised: 03/22/2023] [Accepted: 04/19/2023] [Indexed: 06/02/2023] Open
Abstract
In complex tissues containing cells that are difficult to dissociate, single-nucleus RNA-sequencing (snRNA-seq) has become the preferred experimental technology over single-cell RNA-sequencing (scRNA-seq) to measure gene expression. To accurately model these data in downstream analyses, previous work has shown that droplet-based scRNA-seq data are not zero-inflated, but whether droplet-based snRNA-seq data follow the same probability distributions has not been systematically evaluated. Using pseudonegative control data from nuclei in mouse cortex sequenced with the 10x Genomics Chromium system and mouse kidney sequenced with the DropSeq system, we found that droplet-based snRNA-seq data follow a negative binomial distribution, suggesting that parametric statistical models applied to scRNA-seq are transferable to snRNA-seq. Furthermore, we found that the quantification choices in adapting quantification mapping strategies from scRNA-seq to snRNA-seq can play a significant role in downstream analyses and biological interpretation. In particular, reference transcriptomes that do not include intronic regions result in significantly smaller library sizes and incongruous cell type classifications. We also confirmed the presence of a gene length bias in snRNA-seq data, which we show is present in both exonic and intronic reads, and investigate potential causes for the bias.
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Affiliation(s)
- Albert Kuo
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, 615 N Wolfe St, Baltimore, MD 21205, USA
| | - Kasper D Hansen
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, 615 N Wolfe St, Baltimore, MD 21205, USA
- Department of Genetic Medicine, Johns Hopkins School of Medicine, 733 N Broadway, Baltimore, MD 21205, USA
| | - Stephanie C Hicks
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, 615 N Wolfe St, Baltimore, MD 21205, USA
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26
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Hatai D, Levenson MT, Rehan VK, Allard P. Inter- and trans-generational impacts of environmental exposures on the germline resolved at the single-cell level. CURRENT OPINION IN TOXICOLOGY 2024; 38:100465. [PMID: 38586548 PMCID: PMC10993723 DOI: 10.1016/j.cotox.2024.100465] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/09/2024]
Abstract
Reproduction is a remarkably intricate process involving the interaction of multiple cell types and organ systems unfolding over long periods of time and that culminates with the production of gametes. The initiation of germ cell development takes place during embryogenesis but only completes decades later in humans. The complexity inherent to reproduction and its study has long hampered our ability to decipher how environmental agents disrupt this process. Single-cell approaches provide an opportunity for a deeper understanding of the action of toxicants on germline function and analyze how the response to their exposure is differentially distributed across tissues and cell types. In addition to single-cell RNA sequencing, other single-cell or nucleus level approaches such as ATAC-sequencing and multi-omics have expanded the strategies that can be implemented in reproductive toxicological studies to include epigenomic and the nuclear transcriptomic data. Here we will discuss the current state of single-cell technologies and how they can best be utilized to advance reproductive toxicological studies. We will then discuss case studies in two model organisms (Caenorhabditis elegans and mouse) studying different environmental exposures (alcohol and e-cigarettes respectively) to highlight the value of single-cell and single-nucleus approaches for reproductive biology and reproductive toxicology.
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Affiliation(s)
- Dylan Hatai
- UCLA Molecular Toxicology Interdepartmental Program, University of California Los Angeles, Los Angeles, CA, USA
| | - Max T. Levenson
- UCLA Molecular Toxicology Interdepartmental Program, University of California Los Angeles, Los Angeles, CA, USA
| | - Virender K. Rehan
- UCLA Molecular Toxicology Interdepartmental Program, University of California Los Angeles, Los Angeles, CA, USA
- Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Patrick Allard
- UCLA Molecular Toxicology Interdepartmental Program, University of California Los Angeles, Los Angeles, CA, USA
- Institute for Society and Genetics, University of California, Los Angeles, Los Angeles, CA, USA
- Molecular Biology Institute, University of California, Los Angeles, Los Angeles, CA, USA
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27
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Liu W, Li Q. Single-cell transcriptomics dissecting the development and evolution of nervous system in insects. CURRENT OPINION IN INSECT SCIENCE 2024; 63:101201. [PMID: 38608931 DOI: 10.1016/j.cois.2024.101201] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/31/2024] [Revised: 04/07/2024] [Accepted: 04/08/2024] [Indexed: 04/14/2024]
Abstract
Insects can display a vast repertoire of complex and adaptive behaviors crucial for survival and reproduction. Yet, how the neural circuits underlying insect behaviors are assembled throughout development and remodeled during evolution remains largely obscure. The advent of single-cell transcriptomics has opened new paths to illuminate these historically intractable questions. Insect behavior is governed by its brain, whose functional complexity is realized through operations across multiple levels, from the molecular and cellular to the circuit and organ. Single-cell transcriptomics enables dissecting brain functions across all these levels and allows tracking regulatory dynamics throughout development and under perturbation. In this review, we mainly focus on the achievements of single-cell transcriptomics in dissecting the molecular and cellular architectures of nervous systems in representative insects, then discuss its applications in tracking the developmental trajectory and functional evolution of insect brains.
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Affiliation(s)
- Weiwei Liu
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China; Yunnan Key Laboratory of Biodiversity Information, Kunming, China.
| | - Qiye Li
- BGI Research, Shenzhen 518083, China; BGI Research, Wuhan 430074, China; College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China.
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28
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Benjamin K, Bhandari A, Kepple JD, Qi R, Shang Z, Xing Y, An Y, Zhang N, Hou Y, Crockford TL, McCallion O, Issa F, Hester J, Tillmann U, Harrington HA, Bull KR. Multiscale topology classifies cells in subcellular spatial transcriptomics. Nature 2024; 630:943-949. [PMID: 38898271 PMCID: PMC11208150 DOI: 10.1038/s41586-024-07563-1] [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: 03/06/2023] [Accepted: 05/14/2024] [Indexed: 06/21/2024]
Abstract
Spatial transcriptomics measures in situ gene expression at millions of locations within a tissue1, hitherto with some trade-off between transcriptome depth, spatial resolution and sample size2. Although integration of image-based segmentation has enabled impactful work in this context, it is limited by imaging quality and tissue heterogeneity. By contrast, recent array-based technologies offer the ability to measure the entire transcriptome at subcellular resolution across large samples3-6. Presently, there exist no approaches for cell type identification that directly leverage this information to annotate individual cells. Here we propose a multiscale approach to automatically classify cell types at this subcellular level, using both transcriptomic information and spatial context. We showcase this on both targeted and whole-transcriptome spatial platforms, improving cell classification and morphology for human kidney tissue and pinpointing individual sparsely distributed renal mouse immune cells without reliance on image data. By integrating these predictions into a topological pipeline based on multiparameter persistent homology7-9, we identify cell spatial relationships characteristic of a mouse model of lupus nephritis, which we validate experimentally by immunofluorescence. The proposed framework readily generalizes to new platforms, providing a comprehensive pipeline bridging different levels of biological organization from genes through to tissues.
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Affiliation(s)
| | - Aneesha Bhandari
- Centre for Human Genetics, University of Oxford, Oxford, UK
- Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Jessica D Kepple
- Centre for Human Genetics, University of Oxford, Oxford, UK
- Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Rui Qi
- Centre for Human Genetics, University of Oxford, Oxford, UK
- Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Chinese Academy of Medical Sciences Oxford Institute, University of Oxford, Oxford, UK
| | - Zhouchun Shang
- BGI Research, Riga, Latvia
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Yanan Xing
- BGI Research, Riga, Latvia
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | | | | | | | - Tanya L Crockford
- Centre for Human Genetics, University of Oxford, Oxford, UK
- Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Oliver McCallion
- Translational Research Immunology Group, Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK
| | - Fadi Issa
- Translational Research Immunology Group, Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK
| | - Joanna Hester
- Translational Research Immunology Group, Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK
| | - Ulrike Tillmann
- Mathematical Institute, University of Oxford, Oxford, UK
- Isaac Newton Institute for Mathematical Sciences, University of Cambridge, Cambridge, UK
| | - Heather A Harrington
- Mathematical Institute, University of Oxford, Oxford, UK.
- Centre for Human Genetics, University of Oxford, Oxford, UK.
- Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany.
- Centre for Systems Biology, Dresden, Dresden, Germany.
- Faculty of Mathematics, Technische Universität Dresden, Dresden, Germany.
| | - Katherine R Bull
- Centre for Human Genetics, University of Oxford, Oxford, UK.
- Nuffield Department of Medicine, University of Oxford, Oxford, UK.
- Chinese Academy of Medical Sciences Oxford Institute, University of Oxford, Oxford, UK.
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29
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Kumari P, Kaur M, Dindhoria K, Ashford B, Amarasinghe SL, Thind AS. Advances in long-read single-cell transcriptomics. Hum Genet 2024:10.1007/s00439-024-02678-x. [PMID: 38787419 DOI: 10.1007/s00439-024-02678-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Accepted: 05/07/2024] [Indexed: 05/25/2024]
Abstract
Long-read single-cell transcriptomics (scRNA-Seq) is revolutionizing the way we profile heterogeneity in disease. Traditional short-read scRNA-Seq methods are limited in their ability to provide complete transcript coverage, resolve isoforms, and identify novel transcripts. The scRNA-Seq protocols developed for long-read sequencing platforms overcome these limitations by enabling the characterization of full-length transcripts. Long-read scRNA-Seq techniques initially suffered from comparatively poor accuracy compared to short read scRNA-Seq. However, with improvements in accuracy, accessibility, and cost efficiency, long-reads are gaining popularity in the field of scRNA-Seq. This review details the advances in long-read scRNA-Seq, with an emphasis on library preparation protocols and downstream bioinformatics analysis tools.
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Affiliation(s)
- Pallawi Kumari
- Institute of Microbial Technology, Council of Scientific and Industrial Research, Chandigarh, India
| | - Manmeet Kaur
- Institute of Microbial Technology, Council of Scientific and Industrial Research, Chandigarh, India
| | - Kiran Dindhoria
- Institute of Microbial Technology, Council of Scientific and Industrial Research, Chandigarh, India
| | - Bruce Ashford
- Illawarra Shoalhaven Local Health District (ISLHD), NSW Health, Wollongong, NSW, Australia
| | - Shanika L Amarasinghe
- Monash Biomedical Discovery Institute, Monash University, Clayton, VIC, 3800, Australia
- Walter and Eliza Hall Institute of Medical Research, 1G, Royal Parade, Parkville, VIC, 3025, Australia
| | - Amarinder Singh Thind
- Illawarra Shoalhaven Local Health District (ISLHD), NSW Health, Wollongong, NSW, Australia.
- The School of Chemistry and Molecular Bioscience (SCMB), University of Wollongong, Loftus St, Wollongong, NSW, 2500, Australia.
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30
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Huang S, Shi W, Li S, Fan Q, Yang C, Cao J, Wu L. Advanced sequencing-based high-throughput and long-read single-cell transcriptome analysis. LAB ON A CHIP 2024; 24:2601-2621. [PMID: 38669201 DOI: 10.1039/d4lc00105b] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/28/2024]
Abstract
Cells are the fundamental building blocks of living systems, exhibiting significant heterogeneity. The transcriptome connects the cellular genotype and phenotype, and profiling single-cell transcriptomes is critical for uncovering distinct cell types, states, and the interplay between cells in development, health, and disease. Nevertheless, single-cell transcriptome analysis faces daunting challenges due to the low abundance and diverse nature of RNAs in individual cells, as well as their heterogeneous expression. The advent and continuous advancements of next-generation sequencing (NGS) and third-generation sequencing (TGS) technologies have solved these problems and facilitated the high-throughput, sensitive, full-length, and rapid profiling of single-cell RNAs. In this review, we provide a broad introduction to current methodologies for single-cell transcriptome sequencing. First, state-of-the-art advancements in high-throughput and full-length single-cell RNA sequencing (scRNA-seq) platforms using NGS are reviewed. Next, TGS-based long-read scRNA-seq methods are summarized. Finally, a brief conclusion and perspectives for comprehensive single-cell transcriptome analysis are discussed.
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Affiliation(s)
- Shanqing Huang
- Discipline of Intelligent Instrument and Equipment, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, China
| | - Weixiong Shi
- Discipline of Intelligent Instrument and Equipment, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, China
| | - Shiyu Li
- Discipline of Intelligent Instrument and Equipment, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, China
| | - Qian Fan
- Institute of Molecular Medicine, Shanghai Key Laboratory for Nucleic Acid Chemistry and Nanomedicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, China.
| | - Chaoyong Yang
- Institute of Molecular Medicine, Shanghai Key Laboratory for Nucleic Acid Chemistry and Nanomedicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, China.
- Discipline of Intelligent Instrument and Equipment, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, China
| | - Jiao Cao
- Institute of Molecular Medicine, Shanghai Key Laboratory for Nucleic Acid Chemistry and Nanomedicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, China.
| | - Lingling Wu
- Institute of Molecular Medicine, Shanghai Key Laboratory for Nucleic Acid Chemistry and Nanomedicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, China.
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31
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Renaut S, Saavedra Armero V, Boudreau DK, Gaudreault N, Desmeules P, Thériault S, Mathieu P, Joubert P, Bossé Y. Single-cell and single-nucleus RNA-sequencing from paired normal-adenocarcinoma lung samples provide both common and discordant biological insights. PLoS Genet 2024; 20:e1011301. [PMID: 38814983 PMCID: PMC11166281 DOI: 10.1371/journal.pgen.1011301] [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: 12/13/2023] [Revised: 06/11/2024] [Accepted: 05/13/2024] [Indexed: 06/01/2024] Open
Abstract
Whether single-cell RNA-sequencing (scRNA-seq) captures the same biological information as single-nucleus RNA-sequencing (snRNA-seq) remains uncertain and likely to be context-dependent. Herein, a head-to-head comparison was performed in matched normal-adenocarcinoma human lung samples to assess biological insights derived from scRNA-seq versus snRNA-seq and better understand the cellular transition that occurs from normal to tumoral tissue. Here, the transcriptome of 160,621 cells/nuclei was obtained. In non-tumor lung, cell type proportions varied widely between scRNA-seq and snRNA-seq with a predominance of immune cells in the former (81.5%) and epithelial cells (69.9%) in the later. Similar results were observed in adenocarcinomas, in addition to an overall increase in cell type heterogeneity and a greater prevalence of copy number variants in cells of epithelial origin, which suggests malignant assignment. The cell type transition that occurs from normal lung tissue to adenocarcinoma was not always concordant whether cells or nuclei were examined. As expected, large differential expression of the whole-cell and nuclear transcriptome was observed, but cell-type specific changes of paired normal and tumor lung samples revealed a set of common genes in the cells and nuclei involved in cancer-related pathways. In addition, we showed that the ligand-receptor interactome landscape of lung adenocarcinoma was largely different whether cells or nuclei were evaluated. Immune cell depletion in fresh specimens partly mitigated the difference in cell type composition observed between cells and nuclei. However, the extra manipulations affected cell viability and amplified the transcriptional signatures associated with stress responses. In conclusion, research applications focussing on mapping the immune landscape of lung adenocarcinoma benefit from scRNA-seq in fresh samples, whereas snRNA-seq of frozen samples provide a low-cost alternative to profile more epithelial and cancer cells, and yield cell type proportions that more closely match tissue content.
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Affiliation(s)
- Sébastien Renaut
- Institut universitaire de cardiologie et de pneumologie de Québec–Université Laval, Quebec City, Canada
| | - Victoria Saavedra Armero
- Institut universitaire de cardiologie et de pneumologie de Québec–Université Laval, Quebec City, Canada
| | - Dominique K. Boudreau
- Institut universitaire de cardiologie et de pneumologie de Québec–Université Laval, Quebec City, Canada
| | - Nathalie Gaudreault
- Institut universitaire de cardiologie et de pneumologie de Québec–Université Laval, Quebec City, Canada
| | - Patrice Desmeules
- Institut universitaire de cardiologie et de pneumologie de Québec–Université Laval, Quebec City, Canada
| | - Sébastien Thériault
- Institut universitaire de cardiologie et de pneumologie de Québec–Université Laval, Quebec City, Canada
| | - Patrick Mathieu
- Institut universitaire de cardiologie et de pneumologie de Québec–Université Laval, Quebec City, Canada
| | - Philippe Joubert
- Institut universitaire de cardiologie et de pneumologie de Québec–Université Laval, Quebec City, Canada
| | - Yohan Bossé
- Institut universitaire de cardiologie et de pneumologie de Québec–Université Laval, Quebec City, Canada
- Department of Molecular Medicine, Université Laval, Quebec City, Canada
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32
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Xie G, Toledo MP, Hu X, Yong HJ, Sanchez PS, Liu C, Naji A, Irianto J, Wang YJ. NKX2-2 based nuclei sorting on frozen human archival pancreas enables the enrichment of islet endocrine populations for single-nucleus RNA sequencing. BMC Genomics 2024; 25:427. [PMID: 38689254 PMCID: PMC11059690 DOI: 10.1186/s12864-024-10335-w] [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: 01/03/2024] [Accepted: 04/22/2024] [Indexed: 05/02/2024] Open
Abstract
BACKGROUND Current approaches to profile the single-cell transcriptomics of human pancreatic endocrine cells almost exclusively rely on freshly isolated islets. However, human islets are limited in availability. Furthermore, the extensive processing steps during islet isolation and subsequent single cell dissolution might alter gene expressions. In this work, we report the development of a single-nucleus RNA sequencing (snRNA-seq) approach with targeted islet cell enrichment for endocrine-population focused transcriptomic profiling using frozen archival pancreatic tissues without islet isolation. RESULTS We cross-compared five nuclei isolation protocols and selected the citric acid method as the best strategy to isolate nuclei with high RNA integrity and low cytoplasmic contamination from frozen archival human pancreata. We innovated fluorescence-activated nuclei sorting based on the positive signal of NKX2-2 antibody to enrich nuclei of the endocrine population from the entire nuclei pool of the pancreas. Our sample preparation procedure generated high-quality single-nucleus gene-expression libraries while preserving the endocrine population diversity. In comparison with single-cell RNA sequencing (scRNA-seq) library generated with live cells from freshly isolated human islets, the snRNA-seq library displayed comparable endocrine cellular composition and cell type signature gene expression. However, between these two types of libraries, differential enrichments of transcripts belonging to different functional classes could be observed. CONCLUSIONS Our work fills a technological gap and helps to unleash frozen archival pancreatic tissues for molecular profiling targeting the endocrine population. This study opens doors to retrospective mappings of endocrine cell dynamics in pancreatic tissues of complex histopathology. We expect that our protocol is applicable to enrich nuclei for transcriptomics studies from various populations in different types of frozen archival tissues.
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Affiliation(s)
- Gengqiang Xie
- Department of Biomedical Sciences, College of Medicine, Florida State University, 1115 West Call Street, Tallahassee, FL, 32306, USA
| | - Maria Pilar Toledo
- Department of Biomedical Sciences, College of Medicine, Florida State University, 1115 West Call Street, Tallahassee, FL, 32306, USA
| | - Xue Hu
- Department of Biomedical Sciences, College of Medicine, Florida State University, 1115 West Call Street, Tallahassee, FL, 32306, USA
| | - Hyo Jeong Yong
- Department of Biomedical Sciences, College of Medicine, Florida State University, 1115 West Call Street, Tallahassee, FL, 32306, USA
| | - Pamela Sandoval Sanchez
- Department of Biomedical Sciences, College of Medicine, Florida State University, 1115 West Call Street, Tallahassee, FL, 32306, USA
| | - Chengyang Liu
- Department of Surgery, Hospital of the University of Pennsylvania, Philadelphia, PA, USA
| | - Ali Naji
- Department of Surgery, Hospital of the University of Pennsylvania, Philadelphia, PA, USA
| | - Jerome Irianto
- Department of Biomedical Sciences, College of Medicine, Florida State University, 1115 West Call Street, Tallahassee, FL, 32306, USA
| | - Yue J Wang
- Department of Biomedical Sciences, College of Medicine, Florida State University, 1115 West Call Street, Tallahassee, FL, 32306, USA.
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33
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Yaghmaeian Salmani B, Lahti L, Gillberg L, Jacobsen JK, Mantas I, Svenningsson P, Perlmann T. Transcriptomic atlas of midbrain dopamine neurons uncovers differential vulnerability in a Parkinsonism lesion model. eLife 2024; 12:RP89482. [PMID: 38587883 PMCID: PMC11001297 DOI: 10.7554/elife.89482] [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: 04/09/2024] Open
Abstract
Midbrain dopamine (mDA) neurons comprise diverse cells with unique innervation targets and functions. This is illustrated by the selective sensitivity of mDA neurons of the substantia nigra compacta (SNc) in patients with Parkinson's disease, while those in the ventral tegmental area (VTA) are relatively spared. Here, we used single nuclei RNA sequencing (snRNA-seq) of approximately 70,000 mouse midbrain cells to build a high-resolution atlas of mouse mDA neuron diversity at the molecular level. The results showed that differences between mDA neuron groups could best be understood as a continuum without sharp differences between subtypes. Thus, we assigned mDA neurons to several 'territories' and 'neighborhoods' within a shifting gene expression landscape where boundaries are gradual rather than discrete. Based on the enriched gene expression patterns of these territories and neighborhoods, we were able to localize them in the adult mouse midbrain. Moreover, because the underlying mechanisms for the variable sensitivities of diverse mDA neurons to pathological insults are not well understood, we analyzed surviving neurons after partial 6-hydroxydopamine (6-OHDA) lesions to unravel gene expression patterns that correlate with mDA neuron vulnerability and resilience. Together, this atlas provides a basis for further studies on the neurophysiological role of mDA neurons in health and disease.
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Affiliation(s)
| | - Laura Lahti
- Department of Cell and Molecular Biology, Karolinska InstitutetStockholmSweden
| | - Linda Gillberg
- Department of Cell and Molecular Biology, Karolinska InstitutetStockholmSweden
| | - Jesper Kjaer Jacobsen
- Department of Cell and Molecular Biology, Karolinska InstitutetStockholmSweden
- Department of Neurology, Karolinska University HospitalStockholmSweden
| | - Ioannis Mantas
- Department of Clinical Neuroscience, Karolinska InstitutetStockholmSweden
| | - Per Svenningsson
- Department of Clinical Neuroscience, Karolinska InstitutetStockholmSweden
| | - Thomas Perlmann
- Department of Cell and Molecular Biology, Karolinska InstitutetStockholmSweden
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34
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Fiorini MR, Dilliott AA, Thomas RA, Farhan SMK. Transcriptomics of Human Brain Tissue in Parkinson's Disease: a Comparison of Bulk and Single-cell RNA Sequencing. Mol Neurobiol 2024:10.1007/s12035-024-04124-5. [PMID: 38578357 DOI: 10.1007/s12035-024-04124-5] [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: 10/11/2023] [Accepted: 03/12/2024] [Indexed: 04/06/2024]
Abstract
Parkinson's disease (PD) is a chronic and progressive neurodegenerative disease leading to motor dysfunction and, in some cases, dementia. Transcriptome analysis is one promising approach for characterizing PD and other neurodegenerative disorders by informing how specific disease events influence gene expression and contribute to pathogenesis. With the emergence of single-cell and single-nucleus RNA sequencing (scnRNA-seq) technologies, the transcriptional landscape of neurodegenerative diseases can now be described at the cellular level. As the application of scnRNA-seq is becoming routine, it calls to question how results at a single-cell resolution compare to those obtained from RNA sequencing of whole tissues (bulk RNA-seq), whether the findings are compatible, and how the assays are complimentary for unraveling the elusive transcriptional changes that drive neurodegenerative disease. Herein, we review the studies that have leveraged RNA-seq technologies to investigate PD. Through the integration of bulk and scnRNA-seq findings from human, post-mortem brain tissue, we use the PD literature as a case study to evaluate the compatibility of the results generated from each assay and demonstrate the complementarity of the sequencing technologies. Finally, through the lens of the PD transcriptomic literature, we evaluate the current feasibility of bulk and scnRNA-seq technologies to illustrate the necessity of both technologies for achieving a comprehensive insight into the mechanism by which gene expression promotes neurodegenerative disease. We conclude that the continued application of both assays will provide the greatest insight into neurodegenerative disease pathology, providing both cell-specific and whole-tissue level information.
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Affiliation(s)
- Michael R Fiorini
- The Montreal Neurological Institute-Hospital, Montreal, QC, Canada
- Department of Human Genetics, McGill University, Montreal, QC, Canada
| | - Allison A Dilliott
- The Montreal Neurological Institute-Hospital, Montreal, QC, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
| | - Rhalena A Thomas
- The Montreal Neurological Institute-Hospital, Montreal, QC, Canada.
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada.
| | - Sali M K Farhan
- The Montreal Neurological Institute-Hospital, Montreal, QC, Canada.
- Department of Human Genetics, McGill University, Montreal, QC, Canada.
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada.
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35
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Magrath JW, Goldberg IN, Truong DD, Hartono AB, Sampath SS, Jackson CE, Ghosh A, Cardin DL, Zhang H, Ludwig JA, Lee SB. Enzalutamide induces cytotoxicity in desmoplastic small round cell tumor independent of the androgen receptor. Commun Biol 2024; 7:411. [PMID: 38575753 PMCID: PMC10995187 DOI: 10.1038/s42003-024-06003-0] [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: 11/02/2023] [Accepted: 03/01/2024] [Indexed: 04/06/2024] Open
Abstract
Desmoplastic Small Round Cell Tumor (DSRCT) is a rare, pediatric cancer caused by the EWSR1::WT1 fusion protein. DSRCT predominantly occurs in males, which comprise 80-90% of the patient population. While the reason for this male predominance remains unknown, one hypothesis is that the androgen receptor (AR) plays a critical role in DSRCT and elevated testosterone levels in males help drive tumor growth. Here, we demonstrate that AR is highly expressed in DSRCT relative to other fusion-driven sarcomas and that the AR antagonists enzalutamide and flutamide reduce DSRCT growth. However, despite these findings, which suggest an important role for AR in DSRCT, we show that DSRCT cell lines form xenografts in female mice at the same rate as male mice and AR depletion does not significantly alter DSRCT growth in vitro. Further, we find that AR antagonists reduce DSRCT growth in cells depleted of AR, establishing an AR-independent mechanism of action. These findings suggest that AR dependence is not the reason for male predominance in DSRCT and that AR-targeted therapies may provide therapeutic benefit primarily through an AR-independent mechanism that requires further elucidation.
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Affiliation(s)
- Justin W Magrath
- Department of Pathology and Laboratory Medicine, Tulane University School of Medicine, 1430 Tulane Ave, New Orleans, LA, USA
| | - Ilon N Goldberg
- Department of Pathology and Laboratory Medicine, Tulane University School of Medicine, 1430 Tulane Ave, New Orleans, LA, USA
| | - Danh D Truong
- Sarcoma Medical Oncology Department, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Alifiani B Hartono
- Department of Pathology and Laboratory Medicine, Tulane University School of Medicine, 1430 Tulane Ave, New Orleans, LA, USA
| | - Shruthi Sanjitha Sampath
- Department of Pathology and Laboratory Medicine, Tulane University School of Medicine, 1430 Tulane Ave, New Orleans, LA, USA
| | - Chandler E Jackson
- Department of Pathology and Laboratory Medicine, Tulane University School of Medicine, 1430 Tulane Ave, New Orleans, LA, USA
| | - Anushka Ghosh
- Department of Pathology and Laboratory Medicine, Tulane University School of Medicine, 1430 Tulane Ave, New Orleans, LA, USA
| | - Derrick L Cardin
- Department of Pathology and Laboratory Medicine, Tulane University School of Medicine, 1430 Tulane Ave, New Orleans, LA, USA
| | - Haitao Zhang
- Department of Pathology and Laboratory Medicine, Tulane University School of Medicine, 1430 Tulane Ave, New Orleans, LA, USA
| | - Joseph A Ludwig
- Sarcoma Medical Oncology Department, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Sean B Lee
- Department of Pathology and Laboratory Medicine, Tulane University School of Medicine, 1430 Tulane Ave, New Orleans, LA, USA.
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36
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Chamberlin JT, Lee Y, Marth GT, Quinlan AR. Differences in molecular sampling and data processing explain variation among single-cell and single-nucleus RNA-seq experiments. Genome Res 2024; 34:179-188. [PMID: 38355308 PMCID: PMC10984380 DOI: 10.1101/gr.278253.123] [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: 07/07/2023] [Accepted: 02/01/2024] [Indexed: 02/16/2024]
Abstract
A mechanistic understanding of the biological and technical factors that impact transcript measurements is essential to designing and analyzing single-cell and single-nucleus RNA sequencing experiments. Nuclei contain the same pre-mRNA population as cells, but they contain a small subset of the mRNAs. Nonetheless, early studies argued that single-nucleus analysis yielded results comparable to cellular samples if pre-mRNA measurements were included. However, typical workflows do not distinguish between pre-mRNA and mRNA when estimating gene expression, and variation in their relative abundances across cell types has received limited attention. These gaps are especially important given that incorporating pre-mRNA has become commonplace for both assays, despite known gene length bias in pre-mRNA capture. Here, we reanalyze public data sets from mouse and human to describe the mechanisms and contrasting effects of mRNA and pre-mRNA sampling on gene expression and marker gene selection in single-cell and single-nucleus RNA-seq. We show that pre-mRNA levels vary considerably among cell types, which mediates the degree of gene length bias and limits the generalizability of a recently published normalization method intended to correct for this bias. As an alternative, we repurpose an existing post hoc gene length-based correction method from conventional RNA-seq gene set enrichment analysis. Finally, we show that inclusion of pre-mRNA in bioinformatic processing can impart a larger effect than assay choice itself, which is pivotal to the effective reuse of existing data. These analyses advance our understanding of the sources of variation in single-cell and single-nucleus RNA-seq experiments and provide useful guidance for future studies.
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Affiliation(s)
- John T Chamberlin
- Department of Biomedical Informatics, University of Utah, Salt Lake City, Utah 84108, USA
| | - Younghee Lee
- Department of Biomedical Informatics, University of Utah, Salt Lake City, Utah 84108, USA
- Seoul National University, College of Veterinary Medicine, Seoul, 08826, South Korea
| | - Gabor T Marth
- Department of Human Genetics, Utah Center for Genetic Discovery, University of Utah, Salt Lake City, Utah 84112, USA
| | - Aaron R Quinlan
- Department of Biomedical Informatics, University of Utah, Salt Lake City, Utah 84108, USA;
- Department of Human Genetics, Utah Center for Genetic Discovery, University of Utah, Salt Lake City, Utah 84112, USA
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37
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Qiu R, Petit C, Thom CS. Nuclear Isolation from Cryopreserved In Vitro Derived Blood Cells. J Vis Exp 2024:10.3791/66490. [PMID: 38558008 PMCID: PMC11190953 DOI: 10.3791/66490] [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] [Indexed: 04/04/2024] Open
Abstract
Induced pluripotent stem cell (iPSC)-based models are excellent platforms to understand blood development, and iPSC-derived blood cells have translational utility as clinical testing reagents and transfusable cell therapeutics. The advent and expansion of multiomics analysis, including but not limited to single nucleus RNA sequencing (snRNAseq) and Assay for Transposase-Accessible Chromatin sequencing (snATACseq), offers the potential to revolutionize our understanding of cell development. This includes developmental biology using in vitro hematopoietic models. However, it can be technically challenging to isolate intact nuclei from cultured or primary cells. Different cell types often require tailored nuclear preparations depending on cellular rigidity and content. These technical difficulties can limit data quality and act as a barrier to investigators interested in pursuing multiomics studies. Specimen cryopreservation is often necessary due to limitations with cell collection and/or processing, and frozen samples can present additional technical challenges for intact nuclear isolation. In this manuscript, we provide a detailed method to isolate high-quality nuclei from iPSC-derived cells at different stages of in vitro hematopoietic development for use in single-nucleus multiomics workflows. We have focused the method development on the isolation of nuclei from iPSC-derived adherent stromal/endothelial cells and non-adherent hematopoietic progenitor cells, as these represent very different cell types with regard to structural and cellular identity. The described troubleshooting steps limited nuclear clumping and debris, allowing the recovery of nuclei in sufficient quantity and quality for downstream analyses. Similar methods may be adapted to isolate nuclei from other cryopreserved cell types.
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Affiliation(s)
- Rong Qiu
- Division of Neonatology, Children's Hospital of Philadelphia
| | - Chayanne Petit
- Division of Neonatology, Children's Hospital of Philadelphia
| | - Christopher S Thom
- Division of Neonatology, Children's Hospital of Philadelphia; Department of Pediatrics, University of Pennsylvania Perelman School of Medicine;
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38
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Kashima Y, Reteng P, Haga Y, Yamagishi J, Suzuki Y. Single-cell analytical technologies: uncovering the mechanisms behind variations in immune responses. FEBS J 2024; 291:819-831. [PMID: 36082537 DOI: 10.1111/febs.16622] [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: 06/10/2022] [Revised: 08/25/2022] [Accepted: 09/08/2022] [Indexed: 11/30/2022]
Abstract
The immune landscape varies among individuals. It determines the immune response and results in surprisingly diverse symptoms, even in response to similar external stimuli. However, the detailed mechanisms underlying such diverse immune responses have remained mostly elusive. The utilization of recently developed single-cell multimodal analysis platforms has started to answer this question. Emerging studies have elucidated several molecular networks that may explain diversity with respect to age or other factors. An elaborate interplay between inherent physical conditions and environmental conditions has been demonstrated. Furthermore, the importance of modifications by the epigenome resulting in transcriptome variation among individuals is gradually being revealed. Accordingly, epigenomes and transcriptomes are direct indicators of the medical history and dynamic interactions with environmental factors. Coronavirus disease 2019 (COVID-19) has recently become one of the most remarkable examples of the necessity of in-depth analyses of diverse responses with respect to various factors to improve treatment in severe cases and to prevent viral transmission from asymptomatic carriers. In fact, determining why some patients develop serious symptoms is still a pressing issue. Here, we review the current "state of the art" in single-cell analytical technologies and their broad applications to healthy individuals and representative diseases, including COVID-19.
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Affiliation(s)
- Yukie Kashima
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa, Japan
| | - Patrick Reteng
- Division of Collaboration and Education, International Institute for Zoonosis Control, Hokkaido University, Sapporo, Japan
| | - Yasuhiko Haga
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa, Japan
| | - Junya Yamagishi
- Division of Collaboration and Education, International Institute for Zoonosis Control, Hokkaido University, Sapporo, Japan
| | - Yutaka Suzuki
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa, Japan
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39
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Andresen AMS, Taylor RS, Grimholt U, Daniels RR, Sun J, Dobie R, Henderson NC, Martin SAM, Macqueen DJ, Fosse JH. Mapping the cellular landscape of Atlantic salmon head kidney by single cell and single nucleus transcriptomics. FISH & SHELLFISH IMMUNOLOGY 2024; 146:109357. [PMID: 38181891 DOI: 10.1016/j.fsi.2024.109357] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Revised: 12/19/2023] [Accepted: 12/21/2023] [Indexed: 01/07/2024]
Abstract
Single-cell transcriptomics is the current gold standard for global gene expression profiling, not only in mammals and model species, but also in non-model fish species. This is a rapidly expanding field, creating a deeper understanding of tissue heterogeneity and the distinct functions of individual cells, making it possible to explore the complexities of immunology and gene expression on a highly resolved level. In this study, we compared two single cell transcriptomic approaches to investigate cellular heterogeneity within the head kidney of healthy farmed Atlantic salmon (Salmo salar). We compared 14,149 cell transcriptomes assayed by single cell RNA-seq (scRNA-seq) with 18,067 nuclei transcriptomes captured by single nucleus RNA-Seq (snRNA-seq). Both approaches detected eight major cell populations in common: granulocytes, heamatopoietic stem cells, erythrocytes, mononuclear phagocytes, thrombocytes, B cells, NK-like cells, and T cells. Four additional cell types, endothelial, epithelial, interrenal, and mesenchymal cells, were detected in the snRNA-seq dataset, but appeared to be lost during preparation of the single cell suspension submitted for scRNA-seq library generation. We identified additional heterogeneity and subpopulations within the B cells, T cells, and endothelial cells, and revealed developmental trajectories of heamatopoietic stem cells into differentiated granulocyte and mononuclear phagocyte populations. Gene expression profiles of B cell subtypes revealed distinct IgM and IgT-skewed resting B cell lineages and provided insights into the regulation of B cell lymphopoiesis. The analysis revealed eleven T cell sub-populations, displaying a level of T cell heterogeneity in salmon head kidney comparable to that observed in mammals, including distinct subsets of cd4/cd8-negative T cells, such as tcrγ positive, progenitor-like, and cytotoxic cells. Although snRNA-seq and scRNA-seq were both useful to resolve cell type-specific expression in the Atlantic salmon head kidney, the snRNA-seq pipeline was overall more robust in identifying several cell types and subpopulations. While scRNA-seq displayed higher levels of ribosomal and mitochondrial genes, snRNA-seq captured more transcription factor genes. However, only scRNA-seq-generated data was useful for cell trajectory inference within the myeloid lineage. In conclusion, this study systematically outlines the relative merits of scRNA-seq and snRNA-seq in Atlantic salmon, enhances understanding of teleost immune cell lineages, and provides a comprehensive list of markers for identifying major cell populations in the head kidney with significant immune relevance.
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Affiliation(s)
| | - Richard S Taylor
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh, United Kingdom
| | | | - Rose Ruiz Daniels
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh, United Kingdom
| | - Jianxuan Sun
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh, United Kingdom
| | - Ross Dobie
- Centre for Inflammation Research, The Queen's Medical Research Institute, Edinburgh BioQuarter, University of Edinburgh, Edinburgh, United Kingdom
| | - Neil C Henderson
- Centre for Inflammation Research, The Queen's Medical Research Institute, Edinburgh BioQuarter, University of Edinburgh, Edinburgh, United Kingdom; MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom
| | - Samuel A M Martin
- Scottish Fish Immunology Research Centre, School of Biological Sciences, University of Aberdeen, Aberdeen, United Kingdom
| | - Daniel J Macqueen
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh, United Kingdom.
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40
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Khodosevich K, Dragicevic K, Howes O. Drug targeting in psychiatric disorders - how to overcome the loss in translation? Nat Rev Drug Discov 2024; 23:218-231. [PMID: 38114612 DOI: 10.1038/s41573-023-00847-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/03/2023] [Indexed: 12/21/2023]
Abstract
In spite of major efforts and investment in development of psychiatric drugs, many clinical trials have failed in recent decades, and clinicians still prescribe drugs that were discovered many years ago. Although multiple reasons have been discussed for the drug development deadlock, we focus here on one of the major possible biological reasons: differences between the characteristics of drug targets in preclinical models and the corresponding targets in patients. Importantly, based on technological advances in single-cell analysis, we propose here a framework for the use of available and newly emerging knowledge from single-cell and spatial omics studies to evaluate and potentially improve the translational predictivity of preclinical models before commencing preclinical and, in particular, clinical studies. We believe that these recommendations will improve preclinical models and the ability to assess drugs in clinical trials, reducing failure rates in expensive late-stage trials and ultimately benefitting psychiatric drug discovery and development.
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Affiliation(s)
- Konstantin Khodosevich
- Biotech Research and Innovation Centre, Faculty of Health, University of Copenhagen, Copenhagen, Denmark.
| | - Katarina Dragicevic
- Biotech Research and Innovation Centre, Faculty of Health, University of Copenhagen, Copenhagen, Denmark
| | - Oliver Howes
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
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41
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Ali M, Yang T, He H, Zhang Y. Plant biotechnology research with single-cell transcriptome: recent advancements and prospects. PLANT CELL REPORTS 2024; 43:75. [PMID: 38381195 DOI: 10.1007/s00299-024-03168-0] [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: 09/12/2023] [Accepted: 02/05/2024] [Indexed: 02/22/2024]
Abstract
KEY MESSAGE Single-cell transcriptomic techniques have emerged as powerful tools in plant biology, offering high-resolution insights into gene expression at the individual cell level. This review highlights the rapid expansion of single-cell technologies in plants, their potential in understanding plant development, and their role in advancing plant biotechnology research. Single-cell techniques have emerged as powerful tools to enhance our understanding of biological systems, providing high-resolution transcriptomic analysis at the single-cell level. In plant biology, the adoption of single-cell transcriptomics has seen rapid expansion of available technologies and applications. This review article focuses on the latest advancements in the field of single-cell transcriptomic in plants and discusses the potential role of these approaches in plant development and expediting plant biotechnology research in the near future. Furthermore, inherent challenges and limitations of single-cell technology are critically examined to overcome them and enhance our knowledge and understanding.
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Affiliation(s)
- Muhammad Ali
- School of Agriculture, Sun Yat-Sen University, Shenzhen, 518107, China
- Peking University-Institute of Advanced Agricultural Sciences, Weifang, China
| | - Tianxia Yang
- School of Agriculture, Sun Yat-Sen University, Shenzhen, 518107, China
- State Key Laboratory of Maize Bio-breeding, National Maize Improvement Center, Frontiers Science Center for Molecular Design Breeding (MOE), China Agricultural University, Beijing, China
| | - Hai He
- School of Agriculture, Sun Yat-Sen University, Shenzhen, 518107, China
| | - Yu Zhang
- School of Agriculture, Sun Yat-Sen University, Shenzhen, 518107, China.
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42
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Liao K, Xiang Y, Huang F, Huang M, Xu W, Lin Y, Liao P, Wang Z, Yang L, Tian X, Chen D, Wang Z, Liu S, Zhuang Z. Spatial and single-nucleus transcriptomics decoding the molecular landscape and cellular organization of avian optic tectum. iScience 2024; 27:109009. [PMID: 38333704 PMCID: PMC10850779 DOI: 10.1016/j.isci.2024.109009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2023] [Revised: 12/19/2023] [Accepted: 01/22/2024] [Indexed: 02/10/2024] Open
Abstract
The avian optic tectum (OT) has been studied for its diverse functions, yet a comprehensive molecular landscape at the cellular level has been lacking. In this study, we applied spatial transcriptome sequencing and single-nucleus RNA sequencing (snRNA-seq) to explore the cellular organization and molecular characteristics of the avian OT from two species: Columba livia and Taeniopygia guttata. We identified precise layer structures and provided comprehensive layer-specific signatures of avian OT. Furthermore, we elucidated diverse functions in different layers, with the stratum griseum periventriculare (SGP) potentially playing a key role in advanced functions of OT, like fear response and associative learning. We characterized detailed neuronal subtypes and identified a population of FOXG1+ excitatory neurons, resembling those found in the mouse neocortex, potentially involved in neocortex-related functions and expansion of avian OT. These findings could contribute to our understanding of the architecture of OT, shedding light on visual perception and multifunctional association.
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Affiliation(s)
- Kuo Liao
- School of Biology and Biological Engineering, South China University of Technology, Guangzhou 510006, China
- BGI Research, Hangzhou 310030, China
| | - Ya Xiang
- BGI Research, Hangzhou 310030, China
- College of Life Sciences, Northwest University, Xi’an 710069, China
| | - Fubaoqian Huang
- School of Biology and Biological Engineering, South China University of Technology, Guangzhou 510006, China
- BGI Research, Hangzhou 310030, China
| | - Maolin Huang
- School of Life Sciences, Zhengzhou University, Zhengzhou 450001, China
| | - Wenbo Xu
- School of Life Sciences, Zhengzhou University, Zhengzhou 450001, China
| | - Youning Lin
- BGI Research, Hangzhou 310030, China
- BGI Research, Shenzhen 518083, China
| | - Pingfang Liao
- BGI Research, Hangzhou 310030, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Zishi Wang
- School of Life Sciences, Zhengzhou University, Zhengzhou 450001, China
| | - Lin Yang
- School of Life Sciences, Zhengzhou University, Zhengzhou 450001, China
| | - Xinmao Tian
- School of Life Sciences, Zhengzhou University, Zhengzhou 450001, China
| | - Duoyuan Chen
- BGI Research, Hangzhou 310030, China
- BGI Research, Shenzhen 518083, China
| | - Zhenlong Wang
- School of Life Sciences, Zhengzhou University, Zhengzhou 450001, China
| | - Shiping Liu
- BGI Research, Hangzhou 310030, China
- BGI Research, Shenzhen 518083, China
| | - Zhenkun Zhuang
- BGI Research, Hangzhou 310030, China
- BGI Research, Shenzhen 518083, China
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43
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Mariën V, Arckens L, Van Houcke J. Preparation of High-Viability Single-Cell Suspensions from African Turquoise Killifish Brain Tissue. Cold Spring Harb Protoc 2024; 2024:107829. [PMID: 36931736 DOI: 10.1101/pdb.prot107829] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/19/2023]
Abstract
Studying the brain at the single-cell level has become increasingly popular in recent years. This, however, remains challenging, especially in emerging model organisms. To carry out single-cell sequencing, the preparation of a high-viability single-cell suspension is critical. In this protocol, we describe how to prepare a high-viability single-cell suspension starting from brain tissue of the African turquoise killifish (Nothobranchius furzeri). The protocol consists of dissection, enzymatic and mechanical dissociation of the brain tissue, and debris removal. The protocol described here has been successfully used for 10× Genomics single-cell sequencing of the telencephalon of adult killifish, which requires a cell viability of at least 70%. In addition to single-cell sequencing experiments, the single-cell suspension generated can be used for other applications, including cell culture and flow cytometry.
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Affiliation(s)
- Valerie Mariën
- Neuroplasticity and Neuroproteomics Research Group, Animal Physiology and Neurobiology Section, Department of Biology, KU Leuven, 3000 Leuven, Belgium
| | - Lutgarde Arckens
- Neuroplasticity and Neuroproteomics Research Group, Animal Physiology and Neurobiology Section, Department of Biology, KU Leuven, 3000 Leuven, Belgium
| | - Jolien Van Houcke
- Neuroplasticity and Neuroproteomics Research Group, Animal Physiology and Neurobiology Section, Department of Biology, KU Leuven, 3000 Leuven, Belgium
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44
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Yang S, Liu C, Jiang M, Liu X, Geng L, Zhang Y, Sun S, Wang K, Yin J, Ma S, Wang S, Belmonte JCI, Zhang W, Qu J, Liu GH. A single-nucleus transcriptomic atlas of primate liver aging uncovers the pro-senescence role of SREBP2 in hepatocytes. Protein Cell 2024; 15:98-120. [PMID: 37378670 PMCID: PMC10833472 DOI: 10.1093/procel/pwad039] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2023] [Accepted: 05/19/2023] [Indexed: 06/29/2023] Open
Abstract
Aging increases the risk of liver diseases and systemic susceptibility to aging-related diseases. However, cell type-specific changes and the underlying mechanism of liver aging in higher vertebrates remain incompletely characterized. Here, we constructed the first single-nucleus transcriptomic landscape of primate liver aging, in which we resolved cell type-specific gene expression fluctuation in hepatocytes across three liver zonations and detected aberrant cell-cell interactions between hepatocytes and niche cells. Upon in-depth dissection of this rich dataset, we identified impaired lipid metabolism and upregulation of chronic inflammation-related genes prominently associated with declined liver functions during aging. In particular, hyperactivated sterol regulatory element-binding protein (SREBP) signaling was a hallmark of the aged liver, and consequently, forced activation of SREBP2 in human primary hepatocytes recapitulated in vivo aging phenotypes, manifesting as impaired detoxification and accelerated cellular senescence. This study expands our knowledge of primate liver aging and informs the development of diagnostics and therapeutic interventions for liver aging and associated diseases.
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Affiliation(s)
- Shanshan Yang
- Advanced Innovation Center for Human Brain Protection and National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing 100053, China
- Aging Translational Medicine Center, International Center for Aging and Cancer, Beijing Municipal Geriatric Medical Research Center, Xuanwu Hospital, Capital Medical University, Beijing 100053, China
- Xuanwu Hospital Capital Medical University, Beijing 100053, China
| | - Chengyu Liu
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Mengmeng Jiang
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing 100101, China
| | - Xiaoqian Liu
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing 100101, China
| | - Lingling Geng
- Advanced Innovation Center for Human Brain Protection and National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing 100053, China
- Aging Translational Medicine Center, International Center for Aging and Cancer, Beijing Municipal Geriatric Medical Research Center, Xuanwu Hospital, Capital Medical University, Beijing 100053, China
| | - Yiyuan Zhang
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing 100101, China
| | - Shuhui Sun
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing 100101, China
| | - Kang Wang
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jian Yin
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Shuai Ma
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing 100101, China
| | - Si Wang
- Advanced Innovation Center for Human Brain Protection and National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing 100053, China
- Aging Translational Medicine Center, International Center for Aging and Cancer, Beijing Municipal Geriatric Medical Research Center, Xuanwu Hospital, Capital Medical University, Beijing 100053, China
| | | | - Weiqi Zhang
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing 100101, China
- Aging Biomarker Consortium, Beijing 100101, China
| | - Jing Qu
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing 100101, China
- Aging Biomarker Consortium, Beijing 100101, China
| | - Guang-Hui Liu
- Advanced Innovation Center for Human Brain Protection and National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing 100053, China
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
- Aging Translational Medicine Center, International Center for Aging and Cancer, Beijing Municipal Geriatric Medical Research Center, Xuanwu Hospital, Capital Medical University, Beijing 100053, China
- Xuanwu Hospital Capital Medical University, Beijing 100053, China
- University of Chinese Academy of Sciences, Beijing 100049, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing 100101, China
- Aging Biomarker Consortium, Beijing 100101, China
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45
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Zhang Y, Petukhov V, Biederstedt E, Que R, Zhang K, Kharchenko PV. Gene panel selection for targeted spatial transcriptomics. Genome Biol 2024; 25:35. [PMID: 38273415 PMCID: PMC10811939 DOI: 10.1186/s13059-024-03174-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Accepted: 01/12/2024] [Indexed: 01/27/2024] Open
Abstract
Targeted spatial transcriptomics hold particular promise in analyzing complex tissues. Most such methods, however, measure only a limited panel of transcripts, which need to be selected in advance to inform on the cell types or processes being studied. A limitation of existing gene selection methods is their reliance on scRNA-seq data, ignoring platform effects between technologies. Here we describe gpsFISH, a computational method performing gene selection through optimizing detection of known cell types. By modeling and adjusting for platform effects, gpsFISH outperforms other methods. Furthermore, gpsFISH can incorporate cell type hierarchies and custom gene preferences to accommodate diverse design requirements.
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Affiliation(s)
- Yida Zhang
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Department of Neurobiology, Duke University, Durham, NC, USA
| | - Viktor Petukhov
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Evan Biederstedt
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Richard Que
- Department of Bioengineering, University of California San Diego, La Jolla, CA, USA
| | - Kun Zhang
- Department of Bioengineering, University of California San Diego, La Jolla, CA, USA
- San Diego Institute of Science, Altos Labs, San Diego, CA, USA
| | - Peter V Kharchenko
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
- San Diego Institute of Science, Altos Labs, San Diego, CA, USA.
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46
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Ghasemi DR, Okonechnikov K, Rademacher A, Tirier S, Maass KK, Schumacher H, Joshi P, Gold MP, Sundheimer J, Statz B, Rifaioglu AS, Bauer K, Schumacher S, Bortolomeazzi M, Giangaspero F, Ernst KJ, Clifford SC, Saez-Rodriguez J, Jones DTW, Kawauchi D, Fraenkel E, Mallm JP, Rippe K, Korshunov A, Pfister SM, Pajtler KW. Compartments in medulloblastoma with extensive nodularity are connected through differentiation along the granular precursor lineage. Nat Commun 2024; 15:269. [PMID: 38191550 PMCID: PMC10774372 DOI: 10.1038/s41467-023-44117-x] [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: 01/04/2023] [Accepted: 11/30/2023] [Indexed: 01/10/2024] Open
Abstract
Medulloblastomas with extensive nodularity are cerebellar tumors characterized by two distinct compartments and variable disease progression. The mechanisms governing the balance between proliferation and differentiation in MBEN remain poorly understood. Here, we employ a multi-modal single cell transcriptome analysis to dissect this process. In the internodular compartment, we identify proliferating cerebellar granular neuronal precursor-like malignant cells, along with stromal, vascular, and immune cells. In contrast, the nodular compartment comprises postmitotic, neuronally differentiated malignant cells. Both compartments are connected through an intermediate cell stage resembling actively migrating CGNPs. Notably, we also discover astrocytic-like malignant cells, found in proximity to migrating and differentiated cells at the transition zone between the two compartments. Our study sheds light on the spatial tissue organization and its link to the developmental trajectory, resulting in a more benign tumor phenotype. This integrative approach holds promise to explore intercompartmental interactions in other cancers with varying histology.
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Affiliation(s)
- David R Ghasemi
- Hopp-Children's Cancer Center Heidelberg (KiTZ), Heidelberg, Germany
- Division of Pediatric Neuro-oncology, German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
- Department of Pediatric Oncology, Hematology, and Immunology, Heidelberg University Hospital, Heidelberg, Germany
| | - Konstantin Okonechnikov
- Hopp-Children's Cancer Center Heidelberg (KiTZ), Heidelberg, Germany
- Division of Pediatric Neuro-oncology, German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Anne Rademacher
- Division of Chromatin Networks, German Cancer Research Center (DKFZ) and Bioquant, Heidelberg, Germany
| | - Stephan Tirier
- Division of Chromatin Networks, German Cancer Research Center (DKFZ) and Bioquant, Heidelberg, Germany
- Resolve BioSciences GmbH, Monheim am Rhein, Germany
| | - Kendra K Maass
- Hopp-Children's Cancer Center Heidelberg (KiTZ), Heidelberg, Germany
- Division of Pediatric Neuro-oncology, German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
- Department of Pediatric Oncology, Hematology, and Immunology, Heidelberg University Hospital, Heidelberg, Germany
| | - Hanna Schumacher
- Heidelberg University, Faculty of Medicine, and Heidelberg University Hospital, Institute for Computational Biomedicine, Bioquant, Heidelberg, Germany
| | - Piyush Joshi
- Hopp-Children's Cancer Center Heidelberg (KiTZ), Heidelberg, Germany
- Division of Pediatric Neuro-oncology, German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Maxwell P Gold
- Department of Biological Engineering, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA
| | - Julia Sundheimer
- Hopp-Children's Cancer Center Heidelberg (KiTZ), Heidelberg, Germany
- Division of Pediatric Neuro-oncology, German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
- Faculty of Biosciences, Heidelberg University, Heidelberg, Germany
| | - Britta Statz
- Hopp-Children's Cancer Center Heidelberg (KiTZ), Heidelberg, Germany
- Division of Pediatric Neuro-oncology, German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Ahmet S Rifaioglu
- Heidelberg University, Faculty of Medicine, and Heidelberg University Hospital, Institute for Computational Biomedicine, Bioquant, Heidelberg, Germany
- Department of Electrical and Electronics Engineering, İskenderun Technical University, Hatay, Turkey
| | - Katharina Bauer
- Single-cell Open Lab, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Sabrina Schumacher
- Division of Chromatin Networks, German Cancer Research Center (DKFZ) and Bioquant, Heidelberg, Germany
| | | | - Felice Giangaspero
- Department of Radiological, Oncological and Anatomo-Pathological Sciences, Sapienza University of Rome, Rome, Italy
- Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Neuromed, Pozzilli, Italy
| | - Kati J Ernst
- Hopp-Children's Cancer Center Heidelberg (KiTZ), Heidelberg, Germany
- Division of Pediatric Glioma Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Steven C Clifford
- Wolfson Childhood Cancer Research Centre, Translational and Clinical Research Institute, Newcastle University Centre for Cancer, Newcastle upon Tyne, UK
| | - Julio Saez-Rodriguez
- Heidelberg University, Faculty of Medicine, and Heidelberg University Hospital, Institute for Computational Biomedicine, Bioquant, Heidelberg, Germany
| | - David T W Jones
- Hopp-Children's Cancer Center Heidelberg (KiTZ), Heidelberg, Germany
- Division of Pediatric Glioma Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Daisuke Kawauchi
- Department of Biochemistry and Cellular Biology, National Center of Neurology and Psychiatry (NCNP), Tokyo, Japan
| | - Ernest Fraenkel
- Department of Biological Engineering, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA
- Edythe Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Jan-Philipp Mallm
- Single-cell Open Lab, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Karsten Rippe
- Division of Chromatin Networks, German Cancer Research Center (DKFZ) and Bioquant, Heidelberg, Germany
| | - Andrey Korshunov
- Hopp-Children's Cancer Center Heidelberg (KiTZ), Heidelberg, Germany.
- Department of Neuropathology, Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany.
- Clinical Cooperation Unit Neuropathology, German Cancer Research Center (DKFZ), German Consortium for Translational Cancer Research (DKTK), Heidelberg, Germany.
| | - Stefan M Pfister
- Hopp-Children's Cancer Center Heidelberg (KiTZ), Heidelberg, Germany.
- Division of Pediatric Neuro-oncology, German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany.
- Department of Pediatric Oncology, Hematology, and Immunology, Heidelberg University Hospital, Heidelberg, Germany.
| | - Kristian W Pajtler
- Hopp-Children's Cancer Center Heidelberg (KiTZ), Heidelberg, Germany.
- Division of Pediatric Neuro-oncology, German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany.
- Department of Pediatric Oncology, Hematology, and Immunology, Heidelberg University Hospital, Heidelberg, Germany.
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47
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Han Y, Huang C, Pan Y, Gu X. Single Cell Sequencing Technology and Its Application in Alzheimer's Disease. J Alzheimers Dis 2024; 97:1033-1050. [PMID: 38217599 DOI: 10.3233/jad-230861] [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] [Indexed: 01/15/2024]
Abstract
Alzheimer's disease (AD) involves degeneration of cells in the brain. Due to insidious onset and slow progression, AD is often not diagnosed until it gets progressed to a more severe stage. The diagnosis and treatment of AD has been a challenge. In recent years, high-throughput sequencing technologies have exhibited advantages in exploring the pathogenesis of diseases. However, the types of cells of the central nervous system are complex and traditional bulk sequencing cannot reflect their heterogeneity. Single-cell sequencing technology enables study at the individual cell level and has an irreplaceable advantage in the study of complex diseases. In recent years, this field has expanded rapidly and several types of single-cell sequencing technologies have emerged, including transcriptomics, epigenomics, genomics and proteomics. This review article provides an overview of these single-cell sequencing technologies and their application in AD.
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Affiliation(s)
- Yuru Han
- Shanghai Key Laboratory of Molecular Imaging, Zhoupu Hospital, Shanghai University of Medicine and Health Sciences, Shanghai, China
- School of Pharmacy, Shanghai University of Medicine & Health Sciences, Shanghai, China
- School of Health Sciences and Engineering, University of Shanghai for Science and Technology, Shanghai, China
| | - Congying Huang
- Shanghai Key Laboratory of Molecular Imaging, Zhoupu Hospital, Shanghai University of Medicine and Health Sciences, Shanghai, China
- School of Pharmacy, Shanghai University of Medicine & Health Sciences, Shanghai, China
- School of Health Sciences and Engineering, University of Shanghai for Science and Technology, Shanghai, China
| | - Yuhui Pan
- Center for Disease Control and Prevention of Harbin, Harbin, China
| | - Xuefeng Gu
- Shanghai Key Laboratory of Molecular Imaging, Zhoupu Hospital, Shanghai University of Medicine and Health Sciences, Shanghai, China
- School of Pharmacy, Shanghai University of Medicine & Health Sciences, Shanghai, China
- School of Health Sciences and Engineering, University of Shanghai for Science and Technology, Shanghai, China
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48
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Wei N, Lee C, Duan L, Galdos FX, Samad T, Raissadati A, Goodyer WR, Wu SM. Cardiac Development at a Single-Cell Resolution. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2024; 1441:253-268. [PMID: 38884716 DOI: 10.1007/978-3-031-44087-8_14] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2024]
Abstract
Mammalian cardiac development is a complex, multistage process. Though traditional lineage tracing studies have characterized the broad trajectories of cardiac progenitors, the advent and rapid optimization of single-cell RNA sequencing methods have yielded an ever-expanding toolkit for characterizing heterogeneous cell populations in the developing heart. Importantly, they have allowed for a robust profiling of the spatiotemporal transcriptomic landscape of the human and mouse heart, revealing the diversity of cardiac cells-myocyte and non-myocyte-over the course of development. These studies have yielded insights into novel cardiac progenitor populations, chamber-specific developmental signatures, the gene regulatory networks governing cardiac development, and, thus, the etiologies of congenital heart diseases. Furthermore, single-cell RNA sequencing has allowed for the exquisite characterization of distinct cardiac populations such as the hard-to-capture cardiac conduction system and the intracardiac immune population. Therefore, single-cell profiling has also resulted in new insights into the regulation of cardiac regeneration and injury repair. Single-cell multiomics approaches combining transcriptomics, genomics, and epigenomics may uncover an even more comprehensive atlas of human cardiac biology. Single-cell analyses of the developing and adult mammalian heart offer an unprecedented look into the fundamental mechanisms of cardiac development and the complex diseases that may arise from it.
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Affiliation(s)
- Nicholas Wei
- Stanford University, Cardiovascular Institute, Stanford, CA, USA
| | - Carissa Lee
- Stanford University, Cardiovascular Institute, Stanford, CA, USA
| | - Lauren Duan
- Stanford University, Cardiovascular Institute, Stanford, CA, USA
| | | | - Tahmina Samad
- Stanford University, Cardiovascular Institute, Stanford, CA, USA
| | | | | | - Sean M Wu
- Stanford University, Cardiovascular Institute, Stanford, CA, USA.
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49
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Zheng J, Song W, Zhou Y, Li X, Wang M, Zhang C. Cross-species single-cell landscape of vertebrate pineal gland. J Pineal Res 2024; 76:e12927. [PMID: 38018267 DOI: 10.1111/jpi.12927] [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: 05/16/2023] [Revised: 11/04/2023] [Accepted: 11/15/2023] [Indexed: 11/30/2023]
Abstract
The pineal gland has evolved from a photoreceptive organ in fish to a neuroendocrine organ in mammals. This study integrated multiple daytime single-cell RNA-seq datasets from the pineal glands of zebrafish, rats, and monkeys, providing a detailed examination of the evolutionary transition at single-cell resolution. We identified key factors responsible for the anatomical and functional transformation of the pineal gland. We retrieved and integrated daytime single-cell transcriptomic datasets from the pineal glands of zebrafish, rats, and monkeys, resulting in a total of 22 431 cells after rigorous quality filtering. Comparative analysis was then conducted to elucidate the evolution of pineal cells, their photosensitivity, their role in melatonin production, and the signaling processes within the glands of these species. Our analysis identified distinct cellular compositions of the pineal gland in zebrafish, rats, and monkeys. Zebrafish photoreceptors exhibited comprehensive phototransduction gene expression, while specific genes, including transducin (Gngt1, Gnb3, and Gngt2) and phosducin (Pdc), were consistently present in mammalian pinealocytes. We found transcriptional similarities between the pineal gland and retina, underscoring shared evolutionary and functional pathways. Zebrafish displayed unique light-responsive circadian gene activity compared to rats and monkeys. Key ligand-receptor interactions were identified, especially involving MDK and PTN, influencing melatonin synthesis across species. Furthermore, we observed species-specific GPCR (G protein-coupled receptors) expressions related to melatonin synthesis and their alignment with retinal expressions. Our findings also highlighted specific transcription factors (TFs) and regulatory networks associated with pineal gland evolution and function. Our study provides a detailed analysis of the pineal gland's evolution from fish to mammals. We identified key transcriptional changes and controls that highlight the gland's functional diversity. Notably, we found significant ligand-receptor interactions influencing melatonin synthesis and demonstrated parallels between pineal and retinal expressions. These insights enhance our understanding of the pineal gland's role in phototransduction, melatonin production, and circadian rhythms in vertebrates.
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Affiliation(s)
- Jihong Zheng
- Fundamental Research Center, Shanghai Yangzhi Rehabilitation Hospital (Shanghai Sunshine Rehabilitation Center), School of Life Sciences and Technology, Tongji University, Shanghai, China
| | - Wenqi Song
- Fundamental Research Center, Shanghai Yangzhi Rehabilitation Hospital (Shanghai Sunshine Rehabilitation Center), School of Life Sciences and Technology, Tongji University, Shanghai, China
| | - Yihang Zhou
- Fundamental Research Center, Shanghai Yangzhi Rehabilitation Hospital (Shanghai Sunshine Rehabilitation Center), School of Life Sciences and Technology, Tongji University, Shanghai, China
| | - Xuan Li
- Fundamental Research Center, Shanghai Yangzhi Rehabilitation Hospital (Shanghai Sunshine Rehabilitation Center), School of Life Sciences and Technology, Tongji University, Shanghai, China
| | - Meng Wang
- Songjiang Research Institute, Songjiang District Central Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Chao Zhang
- Fundamental Research Center, Shanghai Yangzhi Rehabilitation Hospital (Shanghai Sunshine Rehabilitation Center), School of Life Sciences and Technology, Tongji University, Shanghai, China
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50
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Imrie G, Gray MB, Raghuraman V, Farhy-Tselnicker I. Gene Expression at the Tripartite Synapse: Bridging the Gap Between Neurons and Astrocytes. ADVANCES IN NEUROBIOLOGY 2024; 39:95-136. [PMID: 39190073 DOI: 10.1007/978-3-031-64839-7_5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/28/2024]
Abstract
Astrocytes, a major class of glial cells, are an important element at the synapse where they engage in bidirectional crosstalk with neurons to regulate numerous aspects of neurotransmission, circuit function, and behavior. Mutations in synapse-related genes expressed in both neurons and astrocytes are central factors in a vast number of neurological disorders, making the proteins that they encode prominent targets for therapeutic intervention. Yet, while the roles of many of these synaptic proteins in neurons are well established, the functions of the same proteins in astrocytes are largely unknown. This gap in knowledge must be addressed to refine therapeutic approaches. In this chapter, we integrate multiomic meta-analysis and a comprehensive overview of current literature to show that astrocytes express an astounding number of genes that overlap with the neuronal and synaptic transcriptomes. Further, we highlight recent reports that characterize the expression patterns and potential novel roles of these genes in astrocytes in both physiological and pathological conditions, underscoring the importance of considering both cell types when investigating the function and regulation of synaptic proteins.
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Affiliation(s)
- Gillian Imrie
- Department of Biology, Texas A&M University, College Station, TX, USA
| | - Madison B Gray
- Department of Biology, Texas A&M University, College Station, TX, USA
| | - Vishnuvasan Raghuraman
- Department of Biology, Texas A&M University, College Station, TX, USA
- Department of Computer Science and Engineering, Texas A&M University, College Station, TX, USA
| | - Isabella Farhy-Tselnicker
- Department of Biology, Texas A&M University, College Station, TX, USA.
- Texas A&M Institute for Neuroscience (TAMIN), Texas A&M University, College Station, TX, USA.
- Center for Biological Clocks Research, Texas A&M University, College Station, TX, USA.
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