1
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Fu Z, Jiang S, Sun Y, Zheng S, Zong L, Li P. Cut&tag: a powerful epigenetic tool for chromatin profiling. Epigenetics 2024; 19:2293411. [PMID: 38105608 PMCID: PMC10730171 DOI: 10.1080/15592294.2023.2293411] [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: 09/07/2023] [Accepted: 12/05/2023] [Indexed: 12/19/2023] Open
Abstract
Analysis of transcription factors and chromatin modifications at the genome-wide level provides insights into gene regulatory processes, such as transcription, cell differentiation and cellular response. Chromatin immunoprecipitation is the most popular and powerful approach for mapping chromatin, and other enzyme-tethering techniques have recently become available for living cells. Among these, Cleavage Under Targets and Tagmentation (CUT&Tag) is a relatively novel chromatin profiling method that has rapidly gained popularity in the field of epigenetics since 2019. It has also been widely adapted to map chromatin modifications and TFs in different species, illustrating the association of these chromatin epitopes with various physiological and pathological processes. Scalable single-cell CUT&Tag can be combined with distinct platforms to distinguish cellular identity, epigenetic features and even spatial chromatin profiling. In addition, CUT&Tag has been developed as a strategy for joint profiling of the epigenome, transcriptome or proteome on the same sample. In this review, we will mainly consolidate the applications of CUT&Tag and its derivatives on different platforms, give a detailed explanation of the pros and cons of this technique as well as the potential development trends and applications in the future.
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Affiliation(s)
- Zhijun Fu
- BGI Tech Solutions Co, Ltd. BGI-Shenzhen, Shenzhen, China
| | - Sanjie Jiang
- BGI Tech Solutions Co, Ltd. BGI-Shenzhen, Shenzhen, China
| | - Yiwen Sun
- BGI Tech Solutions Co, Ltd. BGI-Shenzhen, Shenzhen, China
| | - Shanqiao Zheng
- BGI Tech Solutions Co, Ltd. BGI-Shenzhen, Shenzhen, China
| | - Liang Zong
- BGI Tech Solutions Co, Ltd. BGI-Wuhan, Wuhan, China
| | - Peipei Li
- BGI Tech Solutions Co, Ltd. BGI-Shenzhen, Shenzhen, China
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2
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Trapnell C. Revealing gene function with statistical inference at single-cell resolution. Nat Rev Genet 2024; 25:623-638. [PMID: 38951690 DOI: 10.1038/s41576-024-00750-w] [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: 05/21/2024] [Indexed: 07/03/2024]
Abstract
Single-cell and spatial molecular profiling assays have shown large gains in sensitivity, resolution and throughput. Applying these technologies to specimens from human and model organisms promises to comprehensively catalogue cell types, reveal their lineage origins in development and discern their contributions to disease pathogenesis. Moreover, rapidly dropping costs have made well-controlled perturbation experiments and cohort studies widely accessible, illuminating mechanisms that give rise to phenotypes at the scale of the cell, the tissue and the whole organism. Interpreting the coming flood of single-cell data, much of which will be spatially resolved, will place a tremendous burden on existing computational pipelines. However, statistical concepts, models, tools and algorithms can be repurposed to solve problems now arising in genetic and molecular biology studies of development and disease. Here, I review how the questions that recent technological innovations promise to answer can be addressed by the major classes of statistical tools.
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Affiliation(s)
- Cole Trapnell
- Department of Genome Sciences, University of Washington, Seattle, WA, USA.
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA.
- Allen Discovery Center for Cell Lineage Tracing, Seattle, WA, USA.
- Seattle Hub for Synthetic Biology, Seattle, WA, USA.
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3
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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 DOI: 10.1038/s41467-024-50628-y] [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: 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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4
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Han X, Maharjan S, Chen J, Zhao Y, Qi Y, White LE, Johnson GA, Wang N. High-resolution diffusion magnetic resonance imaging and spatial-transcriptomic in developing mouse brain. Neuroimage 2024; 297:120734. [PMID: 39032791 DOI: 10.1016/j.neuroimage.2024.120734] [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: 01/04/2024] [Revised: 07/06/2024] [Accepted: 07/11/2024] [Indexed: 07/23/2024] Open
Abstract
Brain development is a highly complex process regulated by numerous genes at the molecular and cellular levels. Brain tissue exhibits serial microstructural changes during the development process. High-resolution diffusion magnetic resonance imaging (dMRI) affords a unique opportunity to probe these changes in the developing brain non-destructively. In this study, we acquired multi-shell dMRI datasets at 32 µm isotropic resolution to investigate the tissue microstructure alterations, which we believe to be the highest spatial resolution dMRI datasets obtained for postnatal mouse brains. We adapted the Allen Developing Mouse Brain Atlas (ADMBA) to integrate quantitative MRI metrics and spatial transcriptomics. Diffusion tensor imaging (DTI), diffusion kurtosis imaging (DKI), and neurite orientation dispersion and density imaging (NODDI) metrics were used to quantify brain development at different postnatal days. We demonstrated that the differential evolutions of fiber orientation distributions contribute to the distinct development patterns in white matter (WM) and gray matter (GM). Furthermore, the genes enriched in the nervous system that regulate brain structure and function were expressed in spatial correlation with age-matched dMRI. This study is the first one providing high-resolution dMRI, including DTI, DKI, and NODDI models, to trace mouse brain microstructural changes in WM and GM during postnatal development. This study also highlighted the genotype-phenotype correlation of spatial transcriptomics and dMRI, which may improve our understanding of brain microstructure changes at the molecular level.
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Affiliation(s)
- Xinyue Han
- Department of Radiology and Imaging Sciences, Indiana University, Indianapolis, IN, USA; Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Surendra Maharjan
- Department of Radiology and Imaging Sciences, Indiana University, Indianapolis, IN, USA
| | - Jie Chen
- Department of Radiology and Imaging Sciences, Indiana University, Indianapolis, IN, USA
| | - Yi Zhao
- Department of Biostatistics and Health Data Science, Indiana University, Indianapolis, IN, USA
| | - Yi Qi
- Center for In Vivo Microscopy, Department of Radiology, Duke University, Durham, NC, USA
| | - Leonard E White
- Department of Neurology, Duke University Medical Center, Durham, NC, USA
| | - G Allan Johnson
- Center for In Vivo Microscopy, Department of Radiology, Duke University, Durham, NC, USA; Department of Biomedical Engineering, Duke University, Durham, NC, USA
| | - Nian Wang
- Department of Radiology and Imaging Sciences, Indiana University, Indianapolis, IN, USA; Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, TX, USA; Stark Neurosciences Research Institute, Indiana University, Indianapolis, IN, USA.
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5
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Yoshikawa T, Yanagita M. Single-Cell Analysis Provides New Insights into the Roles of Tertiary Lymphoid Structures and Immune Cell Infiltration in Kidney Injury and Chronic Kidney Disease. THE AMERICAN JOURNAL OF PATHOLOGY 2024:S0002-9440(24)00275-X. [PMID: 39097168 DOI: 10.1016/j.ajpath.2024.07.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/10/2024] [Revised: 06/27/2024] [Accepted: 07/02/2024] [Indexed: 08/05/2024]
Abstract
Chronic kidney disease (CKD) is a global health concern with high morbidity and mortality. Acute kidney injury (AKI) is a pivotal risk factor for the progression of CKD, and the rate of AKI-to-CKD progression increases with aging. Intrarenal inflammation is a fundamental mechanism underlying AKI-to-CKD progression. Tertiary lymphoid structures (TLSs), ectopic lymphoid aggregates formed in nonlymphoid organs, develop in aged injured kidneys, but not in young kidneys, with prolonged inflammation and maladaptive repair, which potentially exacerbates AKI-to-CKD progression in aged individuals. Dysregulated immune responses are involved in the pathogenesis of various kidney diseases, such as IgA nephropathy, lupus nephritis, and diabetic kidney diseases, thereby deteriorating kidney function. TLSs also develop in several kidney diseases, including transplanted kidneys and renal cell carcinoma. However, the precise immunologic mechanisms driving AKI-to-CKD progression and development of these kidney diseases remain unclear, which hinders the development of novel therapeutic approaches. This review aims to describe recent findings from single-cell analysis of cellular heterogeneity and complex interactions among immune and renal parenchymal cells, which potentially contribute to the pathogenesis of AKI-to-CKD progression and other kidney diseases, highlighting the mechanisms of formation and pathogenic roles of TLSs in aged injured kidneys.
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Affiliation(s)
- Takahisa Yoshikawa
- Department of Nephrology, Graduate School of Medicine, Kyoto, Japan; Department of Urology, Graduate School of Medicine, Kyoto, Japan; Department of Diagnostic Pathology, Graduate School of Medicine, Kyoto, Japan
| | - Motoko Yanagita
- Department of Nephrology, Graduate School of Medicine, Kyoto, Japan; Department of Urology, Graduate School of Medicine, Kyoto, Japan; Department of Diagnostic Pathology, Graduate School of Medicine, Kyoto, Japan; Institute for the Advanced Study of Human Biology, Kyoto University, Kyoto, Japan.
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6
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Eastburn DJ, White KS, Jayne ND, Camiolo S, Montis G, Ha S, Watson KG, Yeakley JM, McComb J, Seligmann B. High-throughput gene expression analysis with TempO-LINC sensitively resolves complex brain, lung and kidney heterogeneity at single-cell resolution. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.08.03.606484. [PMID: 39149288 PMCID: PMC11326174 DOI: 10.1101/2024.08.03.606484] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 08/17/2024]
Abstract
We report the development and performance of a novel genomics platform, TempO-LINC, for conducting high-throughput transcriptomic analysis on single cells and nuclei. TempO-LINC works by adding cell-identifying molecular barcodes onto highly selective and high-sensitivity gene expression probes within fixed cells, without having to first generate cDNA. Using an instrument-free combinatorial-indexing approach, all probes within the same fixed cell receive an identical barcode, enabling the reconstruction of single-cell gene expression profiles across as few as several hundred cells and up to 100,000+ cells per run. The TempO-LINC approach is easily scalable based on the number of barcodes and rounds of barcoding performed; however, for the experiments reported in this study, the assay utilized over 5.3 million unique barcodes. TempO-LINC has a robust protocol for fixing and banking cells and displays high-sensitivity gene detection from multiple diverse sample types. We show that TempO-LINC has an observed multiplet rate of less than 1.1% and a cell capture rate of ∼50%. Although the assay can accurately profile the whole transcriptome (19,683 human or 21,400 mouse genes), it can be targeted to measure only actionable/informative genes and molecular pathways of interest - thereby reducing sequencing requirements. In this study, we applied TempO-LINC to profile the transcriptomes of 89,722 cells across multiple sample types, including nuclei from mouse lung, kidney and brain tissues. The data demonstrated the ability to identify and annotate at least 50 unique cell populations and positively correlate expression of cell type-specific molecular markers within them. TempO-LINC is a robust new single-cell technology that is ideal for large-scale applications/studies across thousands of samples with high data quality.
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7
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Pepin AS, Schneider R. Emerging toolkits for decoding the co-occurrence of modified histones and chromatin proteins. EMBO Rep 2024; 25:3202-3220. [PMID: 39095610 PMCID: PMC11316037 DOI: 10.1038/s44319-024-00199-2] [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: 02/28/2024] [Revised: 05/10/2024] [Accepted: 06/10/2024] [Indexed: 08/04/2024] Open
Abstract
In eukaryotes, DNA is packaged into chromatin with the help of highly conserved histone proteins. Together with DNA-binding proteins, posttranslational modifications (PTMs) on these histones play crucial roles in regulating genome function, cell fate determination, inheritance of acquired traits, cellular states, and diseases. While most studies have focused on individual DNA-binding proteins, chromatin proteins, or histone PTMs in bulk cell populations, such chromatin features co-occur and potentially act cooperatively to accomplish specific functions in a given cell. This review discusses state-of-the-art techniques for the simultaneous profiling of multiple chromatin features in low-input samples and single cells, focusing on histone PTMs, DNA-binding, and chromatin proteins. We cover the origins of the currently available toolkits, compare and contrast their characteristic features, and discuss challenges and perspectives for future applications. Studying the co-occurrence of histone PTMs, DNA-binding proteins, and chromatin proteins in single cells will be central for a better understanding of the biological relevance of combinatorial chromatin features, their impact on genomic output, and cellular heterogeneity.
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Affiliation(s)
- Anne-Sophie Pepin
- Institute of Functional Epigenetics (IFE), Helmholtz Zentrum München, Neuherberg, Germany
| | - Robert Schneider
- Institute of Functional Epigenetics (IFE), Helmholtz Zentrum München, Neuherberg, Germany.
- Faculty of Biology, Ludwig-Maximilians-Universität München, Planegg-Martinsried, Germany.
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8
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Zhou T, Zhang R, Jia D, Doty RT, Munday AD, Gao D, Xin L, Abkowitz JL, Duan Z, Ma J. GAGE-seq concurrently profiles multiscale 3D genome organization and gene expression in single cells. Nat Genet 2024; 56:1701-1711. [PMID: 38744973 PMCID: PMC11323187 DOI: 10.1038/s41588-024-01745-3] [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: 07/21/2023] [Accepted: 04/05/2024] [Indexed: 05/16/2024]
Abstract
The organization of mammalian genomes features a complex, multiscale three-dimensional (3D) architecture, whose functional significance remains elusive because of limited single-cell technologies that can concurrently profile genome organization and transcriptional activities. Here, we introduce genome architecture and gene expression by sequencing (GAGE-seq), a scalable, robust single-cell co-assay measuring 3D genome structure and transcriptome simultaneously within the same cell. Applied to mouse brain cortex and human bone marrow CD34+ cells, GAGE-seq characterized the intricate relationships between 3D genome and gene expression, showing that multiscale 3D genome features inform cell-type-specific gene expression and link regulatory elements to target genes. Integration with spatial transcriptomic data revealed in situ 3D genome variations in mouse cortex. Observations in human hematopoiesis unveiled discordant changes between 3D genome organization and gene expression, underscoring a complex, temporal interplay at the single-cell level. GAGE-seq provides a powerful, cost-effective approach for exploring genome structure and gene expression relationships at the single-cell level across diverse biological contexts.
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Affiliation(s)
- Tianming Zhou
- Ray and Stephanie Lane Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Ruochi Zhang
- Ray and Stephanie Lane Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA
- Eric and Wendy Schmidt Center, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Deyong Jia
- Department of Urology, University of Washington, Seattle, WA, USA
| | - Raymond T Doty
- Division of Hematology and Oncology, Department of Medicine/Fred Hutch Cancer Center, University of Washington, Seattle, WA, USA
| | - Adam D Munday
- Division of Hematology and Oncology, Department of Medicine/Fred Hutch Cancer Center, University of Washington, Seattle, WA, USA
| | - Daniel Gao
- Institute for Stem Cell and Regenerative Medicine, University of Washington, Seattle, WA, USA
- Department of Chemistry, Pomona College, Claremont, CA, USA
| | - Li Xin
- Department of Urology, University of Washington, Seattle, WA, USA
- Institute for Stem Cell and Regenerative Medicine, University of Washington, Seattle, WA, USA
| | - Janis L Abkowitz
- Division of Hematology and Oncology, Department of Medicine/Fred Hutch Cancer Center, University of Washington, Seattle, WA, USA
- Institute for Stem Cell and Regenerative Medicine, University of Washington, Seattle, WA, USA
| | - Zhijun Duan
- Division of Hematology and Oncology, Department of Medicine/Fred Hutch Cancer Center, University of Washington, Seattle, WA, USA.
- Institute for Stem Cell and Regenerative Medicine, University of Washington, Seattle, WA, USA.
| | - Jian Ma
- Ray and Stephanie Lane Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA.
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9
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Zhang D, Rubio Rodríguez-Kirby LA, Lin Y, Song M, Wang L, Wang L, Kanatani S, Jimenez-Beristain T, Dang Y, Zhong M, Kukanja P, Wang S, Chen XL, Gao F, Wang D, Xu H, Lou X, Liu Y, Chen J, Sestan N, Uhlén P, Kriegstein A, Zhao H, Castelo-Branco G, Fan R. Spatial dynamics of mammalian brain development and neuroinflammation by multimodal tri-omics mapping. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.28.605493. [PMID: 39091821 PMCID: PMC11291146 DOI: 10.1101/2024.07.28.605493] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 08/04/2024]
Abstract
The ability to spatially map multiple layers of the omics information over different time points allows for exploring the mechanisms driving brain development, differentiation, arealization, and alterations in disease. Herein we developed and applied spatial tri-omic sequencing technologies, DBiT ARP-seq (spatial ATAC-RNA-Protein-seq) and DBiT CTRP-seq (spatial CUT&Tag-RNA-Protein-seq) together with multiplexed immunofluorescence imaging (CODEX) to map spatial dynamic remodeling in brain development and neuroinflammation. A spatiotemporal tri-omic atlas of the mouse brain was obtained at different stages from postnatal day P0 to P21, and compared to the regions of interest in the human developing brains. Specifically, in the cortical area, we discovered temporal persistence and spatial spreading of chromatin accessibility for the layer-defining transcription factors. In corpus callosum, we observed dynamic chromatin priming of myelin genes across the subregions. Together, it suggests a role for layer specific projection neurons to coordinate axonogenesis and myelination. We further mapped the brain of a lysolecithin (LPC) neuroinflammation mouse model and observed common molecular programs in development and neuroinflammation. Microglia, exhibiting both conserved and distinct programs for inflammation and resolution, are transiently activated not only at the core of the LPC lesion, but also at distal locations presumably through neuronal circuitry. Thus, this work unveiled common and differential mechanisms in brain development and neuroinflammation, resulting in a valuable data resource to investigate brain development, function and disease.
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Affiliation(s)
- Di Zhang
- Department of Biomedical Engineering, Yale University, New Haven, CT 06520, USA
- These authors contributed equally
| | - Leslie A Rubio Rodríguez-Kirby
- Laboratory of Molecular Neurobiology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
- These authors contributed equally
| | - Yingxin Lin
- Department of Biostatistics, Yale School of Public Health, New Haven, CT 06510, USA
| | - Mengyi Song
- The Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California San Francisco; San Francisco, CA 94143, USA
- Department of Neurology, University of California San Francisco; San Francisco, CA 94143, USA
| | - Li Wang
- The Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California San Francisco; San Francisco, CA 94143, USA
- Department of Neurology, University of California San Francisco; San Francisco, CA 94143, USA
| | - Lijun Wang
- Department of Biostatistics, Yale School of Public Health, New Haven, CT 06510, USA
| | - Shigeaki Kanatani
- Laboratory of Molecular Neurobiology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
| | - Tony Jimenez-Beristain
- Laboratory of Molecular Neurobiology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
| | - Yonglong Dang
- Laboratory of Molecular Neurobiology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
| | - Mei Zhong
- Yale Stem Cell Center and Department of Cell Biology, Yale University School of Medicine, New Haven, CT 06520, USA
| | - Petra Kukanja
- Laboratory of Molecular Neurobiology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
| | - Shaohui Wang
- The Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California San Francisco; San Francisco, CA 94143, USA
- Department of Neurology, University of California San Francisco; San Francisco, CA 94143, USA
| | - Xinyi Lisa Chen
- Department of Biostatistics, Yale School of Public Health, New Haven, CT 06510, USA
| | - Fu Gao
- Department of Biomedical Engineering, Yale University, New Haven, CT 06520, USA
- Department of Pathology, Yale University School of Medicine, New Haven, CT, USA
| | - Dejiang Wang
- Department of Pathology, Yale University School of Medicine, New Haven, CT, USA
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA
| | - Hang Xu
- Binformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore
| | - Xing Lou
- Department of Biomedical Engineering, Yale University, New Haven, CT 06520, USA
| | - Yang Liu
- Department of Pathology, Yale University School of Medicine, New Haven, CT, USA
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA
| | - Jinmiao Chen
- Institute of Molecular and Cell Biology (IMCB), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore
- Binformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore
| | - Nenad Sestan
- Department of Neuroscience, Yale School of Medicine, Yale University, New Haven, CT, USA
| | - Per Uhlén
- Laboratory of Molecular Neurobiology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
| | - Arnold Kriegstein
- The Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California San Francisco; San Francisco, CA 94143, USA
- Department of Neurology, University of California San Francisco; San Francisco, CA 94143, USA
| | - Hongyu Zhao
- Department of Biostatistics, Yale School of Public Health, New Haven, CT 06510, USA
- Program of Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA
| | - Gonçalo Castelo-Branco
- Laboratory of Molecular Neurobiology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
| | - Rong Fan
- Department of Biomedical Engineering, Yale University, New Haven, CT 06520, USA
- Yale Stem Cell Center and Yale Cancer Center, Yale School of Medicine, New Haven, CT 06520, USA
- Department of Pathology, Yale University School of Medicine, New Haven, CT, USA
- Human and Translational Immunology Program, Yale School of Medicine, New Haven, CT 06520, USA
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10
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Metzner E, Southard KM, Norman TM. Multiome Perturb-seq unlocks scalable discovery of integrated perturbation effects on the transcriptome and epigenome. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.26.605307. [PMID: 39091800 PMCID: PMC11291144 DOI: 10.1101/2024.07.26.605307] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 08/04/2024]
Abstract
Single-cell CRISPR screens link genetic perturbations to transcriptional states, but high-throughput methods connecting these induced changes to their regulatory foundations are limited. Here we introduce Multiome Perturb-seq, extending single-cell CRISPR screens to simultaneously measure perturbation-induced changes in gene expression and chromatin accessibility. We apply Multiome Perturb-seq in a CRISPRi screen of 13 chromatin remodelers in human RPE-1 cells, achieving efficient assignment of sgRNA identities to single nuclei via an improved method for capturing barcode transcripts from nuclear RNA. We organize expression and accessibility measurements into coherent programs describing the integrated effects of perturbations on cell state, finding that ARID1A and SUZ12 knockdowns induce programs enriched for developmental features. Pseudotime analysis of perturbations connects accessibility changes to changes in gene expression, highlighting the value of multimodal profiling. Overall, our method provides a scalable and simply implemented system to dissect the regulatory logic underpinning cell state.
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Affiliation(s)
- Eli Metzner
- Computational and Systems Biology Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Tri-Institutional Training Program in Computational Biology and Medicine, New York, NY, USA
| | - Kaden M. Southard
- Computational and Systems Biology Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Thomas M. Norman
- Computational and Systems Biology Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
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11
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Pertseva M, Follonier O, Scarcella D, Reddy ST. TCR clustering by contrastive learning on antigen specificity. Brief Bioinform 2024; 25:bbae375. [PMID: 39129361 PMCID: PMC11317525 DOI: 10.1093/bib/bbae375] [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: 04/03/2024] [Revised: 07/09/2024] [Accepted: 07/25/2024] [Indexed: 08/13/2024] Open
Abstract
Effective clustering of T-cell receptor (TCR) sequences could be used to predict their antigen-specificities. TCRs with highly dissimilar sequences can bind to the same antigen, thus making their clustering into a common antigen group a central challenge. Here, we develop TouCAN, a method that relies on contrastive learning and pretrained protein language models to perform TCR sequence clustering and antigen-specificity predictions. Following training, TouCAN demonstrates the ability to cluster highly dissimilar TCRs into common antigen groups. Additionally, TouCAN demonstrates TCR clustering performance and antigen-specificity predictions comparable to other leading methods in the field.
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Affiliation(s)
- Margarita Pertseva
- Department of Biosystems Science and Engineering, ETH Zurich, Schanzenstrasse 44, 4056 Basel, Switzerland
- Life Science Zurich Graduate School, ETH Zurich and University of Zurich, Winterthurerstrasse 190, 8057 Zurich, Switzerland
| | - Oceane Follonier
- Department of Biosystems Science and Engineering, ETH Zurich, Schanzenstrasse 44, 4056 Basel, Switzerland
| | - Daniele Scarcella
- Department of Biosystems Science and Engineering, ETH Zurich, Schanzenstrasse 44, 4056 Basel, Switzerland
| | - Sai T Reddy
- Department of Biosystems Science and Engineering, ETH Zurich, Schanzenstrasse 44, 4056 Basel, Switzerland
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12
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Baltar J, Miranda RM, Cabral M, Rebelo S, Grahammer F, Huber TB, Reguenga C, Monteiro FA. Neph1 is required for neurite branching and is negatively regulated by the PRRXL1 homeodomain factor in the developing spinal cord dorsal horn. Neural Dev 2024; 19:13. [PMID: 39049046 PMCID: PMC11271021 DOI: 10.1186/s13064-024-00190-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2024] [Accepted: 07/05/2024] [Indexed: 07/27/2024] Open
Abstract
The cell-adhesion molecule NEPH1 is required for maintaining the structural integrity and function of the glomerulus in the kidneys. In the nervous system of Drosophila and C. elegans, it is involved in synaptogenesis and axon branching, which are essential for establishing functional circuits. In the mammalian nervous system, the expression regulation and function of Neph1 has barely been explored. In this study, we provide a spatiotemporal characterization of Neph1 expression in mouse dorsal root ganglia (DRGs) and spinal cord. After the neurogenic phase, Neph1 is broadly expressed in the DRGs and in their putative targets at the dorsal horn of the spinal cord, comprising both GABAergic and glutamatergic neurons. Interestingly, we found that PRRXL1, a homeodomain transcription factor that is required for proper establishment of the DRG-spinal cord circuit, prevents a premature expression of Neph1 in the superficial laminae of the dorsal spinal cord at E14.5, but has no regulatory effect on the DRGs or on either structure at E16.5. By chromatin immunoprecipitation analysis of the dorsal spinal cord, we identified four PRRXL1-bound regions within the Neph1 introns, suggesting that PRRXL1 directly regulates Neph1 transcription. We also showed that Neph1 is required for branching, especially at distal neurites. Together, our work showed that Prrxl1 prevents the early expression of Neph1 in the superficial dorsal horn, suggesting that Neph1 might function as a downstream effector gene for proper assembly of the DRG-spinal nociceptive circuit.
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Affiliation(s)
- João Baltar
- Unidade de Biologia Experimental, Departamento de Biomedicina, FMUP - Faculdade de Medicina da Universidade do Porto, Porto, Portugal
- Pain Neurobiology, IBMC - Instituto de Biologia Celular e Molecular, Porto, Portugal
- i3S - Instituto de Investigação e Inovação em Saúde, Universidade do Porto, Porto, Portugal
| | - Rafael Mendes Miranda
- Unidade de Biologia Experimental, Departamento de Biomedicina, FMUP - Faculdade de Medicina da Universidade do Porto, Porto, Portugal
- Pain Neurobiology, IBMC - Instituto de Biologia Celular e Molecular, Porto, Portugal
- i3S - Instituto de Investigação e Inovação em Saúde, Universidade do Porto, Porto, Portugal
| | - Maria Cabral
- Unidade de Biologia Experimental, Departamento de Biomedicina, FMUP - Faculdade de Medicina da Universidade do Porto, Porto, Portugal
- Pain Neurobiology, IBMC - Instituto de Biologia Celular e Molecular, Porto, Portugal
- i3S - Instituto de Investigação e Inovação em Saúde, Universidade do Porto, Porto, Portugal
| | - Sandra Rebelo
- Unidade de Biologia Experimental, Departamento de Biomedicina, FMUP - Faculdade de Medicina da Universidade do Porto, Porto, Portugal
- Pain Neurobiology, IBMC - Instituto de Biologia Celular e Molecular, Porto, Portugal
- i3S - Instituto de Investigação e Inovação em Saúde, Universidade do Porto, Porto, Portugal
- Departamento de Patologia Clínica, Centro Hospitalar Universitário São João, Porto, Portugal
| | - Florian Grahammer
- III. Department of Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Hamburg Center for Kidney Health (HCKH), University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Tobias B Huber
- III. Department of Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Hamburg Center for Kidney Health (HCKH), University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Carlos Reguenga
- Unidade de Biologia Experimental, Departamento de Biomedicina, FMUP - Faculdade de Medicina da Universidade do Porto, Porto, Portugal
- Pain Neurobiology, IBMC - Instituto de Biologia Celular e Molecular, Porto, Portugal
- i3S - Instituto de Investigação e Inovação em Saúde, Universidade do Porto, Porto, Portugal
| | - Filipe Almeida Monteiro
- Unidade de Biologia Experimental, Departamento de Biomedicina, FMUP - Faculdade de Medicina da Universidade do Porto, Porto, Portugal.
- Pain Neurobiology, IBMC - Instituto de Biologia Celular e Molecular, Porto, Portugal.
- i3S - Instituto de Investigação e Inovação em Saúde, Universidade do Porto, Porto, Portugal.
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13
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Sun F, Li H, Sun D, Fu S, Gu L, Shao X, Wang Q, Dong X, Duan B, Xing F, Wu J, Xiao M, Zhao F, Han JDJ, Liu Q, Fan X, Li C, Wang C, Shi T. Single-cell omics: experimental workflow, data analyses and applications. SCIENCE CHINA. LIFE SCIENCES 2024:10.1007/s11427-023-2561-0. [PMID: 39060615 DOI: 10.1007/s11427-023-2561-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Accepted: 04/18/2024] [Indexed: 07/28/2024]
Abstract
Cells are the fundamental units of biological systems and exhibit unique development trajectories and molecular features. Our exploration of how the genomes orchestrate the formation and maintenance of each cell, and control the cellular phenotypes of various organismsis, is both captivating and intricate. Since the inception of the first single-cell RNA technology, technologies related to single-cell sequencing have experienced rapid advancements in recent years. These technologies have expanded horizontally to include single-cell genome, epigenome, proteome, and metabolome, while vertically, they have progressed to integrate multiple omics data and incorporate additional information such as spatial scRNA-seq and CRISPR screening. Single-cell omics represent a groundbreaking advancement in the biomedical field, offering profound insights into the understanding of complex diseases, including cancers. Here, we comprehensively summarize recent advances in single-cell omics technologies, with a specific focus on the methodology section. This overview aims to guide researchers in selecting appropriate methods for single-cell sequencing and related data analysis.
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Affiliation(s)
- Fengying Sun
- Department of Clinical Laboratory, the Affiliated Wuhu Hospital of East China Normal University (The Second People's Hospital of Wuhu City), Wuhu, 241000, China
| | - Haoyan Li
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China
| | - Dongqing Sun
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University), Ministry of Education, Orthopaedic Department, Tongji Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China
- Frontier Science Center for Stem Cells, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China
| | - Shaliu Fu
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University), Ministry of Education, Orthopaedic Department, Tongji Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China
- Translational Medical Center for Stem Cell Therapy and Institute for Regenerative Medicine, Shanghai East Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China
- Research Institute of Intelligent Computing, Zhejiang Lab, Hangzhou, 311121, China
- Shanghai Research Institute for Intelligent Autonomous Systems, Shanghai, 201210, China
| | - Lei Gu
- Center for Single-cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Xin Shao
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China
- National Key Laboratory of Chinese Medicine Modernization, Innovation Center of Yangtze River Delta, Zhejiang University, Jiaxing, 314103, China
| | - Qinqin Wang
- Center for Single-cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Xin Dong
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University), Ministry of Education, Orthopaedic Department, Tongji Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China
- Frontier Science Center for Stem Cells, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China
| | - Bin Duan
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University), Ministry of Education, Orthopaedic Department, Tongji Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China
- Translational Medical Center for Stem Cell Therapy and Institute for Regenerative Medicine, Shanghai East Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China
- Research Institute of Intelligent Computing, Zhejiang Lab, Hangzhou, 311121, China
- Shanghai Research Institute for Intelligent Autonomous Systems, Shanghai, 201210, China
| | - Feiyang Xing
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University), Ministry of Education, Orthopaedic Department, Tongji Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China
- Frontier Science Center for Stem Cells, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China
| | - Jun Wu
- Center for Bioinformatics and Computational Biology, Shanghai Key Laboratory of Regulatory Biology, the Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, 200241, China
| | - Minmin Xiao
- Department of Clinical Laboratory, the Affiliated Wuhu Hospital of East China Normal University (The Second People's Hospital of Wuhu City), Wuhu, 241000, China.
| | - Fangqing Zhao
- Beijing Institutes of Life Science, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Jing-Dong J Han
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Center for Quantitative Biology (CQB), Peking University, Beijing, 100871, China.
| | - Qi Liu
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University), Ministry of Education, Orthopaedic Department, Tongji Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China.
- Translational Medical Center for Stem Cell Therapy and Institute for Regenerative Medicine, Shanghai East Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China.
- Research Institute of Intelligent Computing, Zhejiang Lab, Hangzhou, 311121, China.
- Shanghai Research Institute for Intelligent Autonomous Systems, Shanghai, 201210, China.
| | - Xiaohui Fan
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China.
- National Key Laboratory of Chinese Medicine Modernization, Innovation Center of Yangtze River Delta, Zhejiang University, Jiaxing, 314103, China.
- Zhejiang Key Laboratory of Precision Diagnosis and Therapy for Major Gynecological Diseases, Women's Hospital, Zhejiang University School of Medicine, Hangzhou, 310006, China.
| | - Chen Li
- Center for Single-cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
| | - Chenfei Wang
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University), Ministry of Education, Orthopaedic Department, Tongji Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China.
- Frontier Science Center for Stem Cells, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China.
| | - Tieliu Shi
- Department of Clinical Laboratory, the Affiliated Wuhu Hospital of East China Normal University (The Second People's Hospital of Wuhu City), Wuhu, 241000, China.
- Center for Bioinformatics and Computational Biology, Shanghai Key Laboratory of Regulatory Biology, the Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, 200241, China.
- Key Laboratory of Advanced Theory and Application in Statistics and Data Science-MOE, School of Statistics, East China Normal University, Shanghai, 200062, China.
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14
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Shin SW, Mudvari P, Thaploo S, Wheeler MA, Douek DC, Quintana FJ, Boritz EA, Abate AR, Clark IC. FIND-seq: high-throughput nucleic acid cytometry for rare single-cell transcriptomics. Nat Protoc 2024:10.1038/s41596-024-01021-y. [PMID: 39039320 DOI: 10.1038/s41596-024-01021-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2023] [Accepted: 05/09/2024] [Indexed: 07/24/2024]
Abstract
Rare cells have an important role in development and disease, and methods for isolating and studying cell subsets are therefore an essential part of biology research. Such methods traditionally rely on labeled antibodies targeted to cell surface proteins, but large public databases and sophisticated computational approaches increasingly define cell subsets on the basis of genomic, epigenomic and transcriptomic sequencing data. Methods for isolating cells on the basis of nucleic acid sequences powerfully complement these approaches by providing experimental access to cell subsets discovered in cell atlases, as well as those that cannot be otherwise isolated, including cells infected with pathogens, with specific DNA mutations or with unique transcriptional or splicing signatures. We recently developed a nucleic acid cytometry platform called 'focused interrogation of cells by nucleic acid detection and sequencing' (FIND-seq), capable of isolating rare cells on the basis of RNA or DNA markers, followed by bulk or single-cell transcriptomic analysis. This platform has previously been used to characterize the splicing-dependent activation of the transcription factor XBP1 in astrocytes and HIV persistence in memory CD4 T cells from people on long-term antiretroviral therapy. Here, we outline the molecular and microfluidic steps involved in performing FIND-seq, including protocol updates that allow detection and whole transcriptome sequencing of rare HIV-infected cells that harbor genetically intact virus genomes. FIND-seq requires knowledge of microfluidics, optics and molecular biology. We expect that FIND-seq, and this comprehensive protocol, will enable mechanistic studies of rare HIV+ cells, as well as other cell subsets that were previously difficult to recover and sequence.
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Affiliation(s)
- Seung Won Shin
- Department of Bioengineering, College of Engineering, California Institute for Quantitative Biosciences (QB3), University of California Berkeley, Berkeley, CA, USA
| | - Prakriti Mudvari
- Virus Persistence and Dynamics Section, Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Shravan Thaploo
- Ann Romney Center for Neurologic Diseases, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Michael A Wheeler
- Ann Romney Center for Neurologic Diseases, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Daniel C Douek
- Human Immunology Section, Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Francisco J Quintana
- Ann Romney Center for Neurologic Diseases, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Eli A Boritz
- Virus Persistence and Dynamics Section, Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Adam R Abate
- Department of Bioengineering and Therapeutic Sciences, School of Pharmacy, University of California San Francisco, San Francisco, CA, USA
| | - Iain C Clark
- Department of Bioengineering, College of Engineering, California Institute for Quantitative Biosciences (QB3), University of California Berkeley, Berkeley, CA, USA.
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15
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Tiwari V, Prajapati B, Asare Y, Damkou A, Ji H, Liu L, Naser N, Gouna G, Leszczyńska KB, Mieczkowski J, Dichgans M, Wang Q, Kawaguchi R, Shi Z, Swarup V, Geschwind DH, Prinz M, Gokce O, Simons M. Innate immune training restores pro-reparative myeloid functions to promote remyelination in the aged central nervous system. Immunity 2024:S1074-7613(24)00348-0. [PMID: 39053462 DOI: 10.1016/j.immuni.2024.07.001] [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: 04/26/2023] [Revised: 11/21/2023] [Accepted: 07/01/2024] [Indexed: 07/27/2024]
Abstract
The reduced ability of the central nervous system to regenerate with increasing age limits functional recovery following demyelinating injury. Previous work has shown that myelin debris can overwhelm the metabolic capacity of microglia, thereby impeding tissue regeneration in aging, but the underlying mechanisms are unknown. In a model of demyelination, we found that a substantial number of genes that were not effectively activated in aged myeloid cells displayed epigenetic modifications associated with restricted chromatin accessibility. Ablation of two class I histone deacetylases in microglia was sufficient to restore the capacity of aged mice to remyelinate lesioned tissue. We used Bacillus Calmette-Guerin (BCG), a live-attenuated vaccine, to train the innate immune system and detected epigenetic reprogramming of brain-resident myeloid cells and functional restoration of myelin debris clearance and lesion recovery. Our results provide insight into aging-associated decline in myeloid function and how this decay can be prevented by innate immune reprogramming.
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Affiliation(s)
- Vini Tiwari
- Institute of Neuronal Cell Biology, Technical University Munich, 81377 Munich, Germany; German Center for Neurodegenerative Diseases (DZNE), 81377 Munich, Germany
| | - Bharat Prajapati
- Institute of Biomedicine, Sahlgrenska Academy, University of Gothenburg, 41390 Gothenburg, Sweden
| | - Yaw Asare
- Institute for Stroke and Dementia Research, University Hospital of Munich, LMU Munich, 81377 Munich, Germany
| | - Alkmini Damkou
- Institute of Neuronal Cell Biology, Technical University Munich, 81377 Munich, Germany; German Center for Neurodegenerative Diseases (DZNE), 81377 Munich, Germany
| | - Hao Ji
- Institute for Stroke and Dementia Research, University Hospital of Munich, LMU Munich, 81377 Munich, Germany
| | - Lu Liu
- German Center for Neurodegenerative Diseases (DZNE), 81377 Munich, Germany; Institute for Stroke and Dementia Research, University Hospital of Munich, LMU Munich, 81377 Munich, Germany
| | - Nawraa Naser
- Institute for Stroke and Dementia Research, University Hospital of Munich, LMU Munich, 81377 Munich, Germany
| | - Garyfallia Gouna
- Institute of Neuronal Cell Biology, Technical University Munich, 81377 Munich, Germany; German Center for Neurodegenerative Diseases (DZNE), 81377 Munich, Germany
| | - Katarzyna B Leszczyńska
- Laboratory of Molecular Neurobiology, Nencki Institute of Experimental Biology of the Polish Academy of Sciences, 02093 Warsaw, Poland
| | - Jakub Mieczkowski
- Laboratory of Molecular Neurobiology, Nencki Institute of Experimental Biology of the Polish Academy of Sciences, 02093 Warsaw, Poland; 3P-Medicine Laboratory, Medical University of Gdańsk, 80211 Gdańsk, Poland
| | - Martin Dichgans
- German Center for Neurodegenerative Diseases (DZNE), 81377 Munich, Germany; Munich Cluster of Systems Neurology (SyNergy), 81377 Munich, Germany; Institute for Stroke and Dementia Research, University Hospital of Munich, LMU Munich, 81377 Munich, Germany
| | - Qing Wang
- Departments of Neurology and Human Genetics, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Riki Kawaguchi
- Departments of Neurology and Human Genetics, University of California, Los Angeles, Los Angeles, CA 90095, USA; Psychiatry, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Zechuan Shi
- Department of Neurobiology and Behavior, University of California, Irvine, CA, USA
| | - Vivek Swarup
- Department of Neurobiology and Behavior, University of California, Irvine, CA, USA
| | - Daniel H Geschwind
- Departments of Neurology and Human Genetics, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Marco Prinz
- Institute of Neuropathology, Faculty of Medicine, University of Freiburg, 79085 Freiburg, Germany; Signalling Research Centres BIOSS and CIBSS, University of Freiburg, 79104 Freiburg, Germany
| | - Ozgun Gokce
- Munich Cluster of Systems Neurology (SyNergy), 81377 Munich, Germany; Institute for Stroke and Dementia Research, University Hospital of Munich, LMU Munich, 81377 Munich, Germany; German Center for Neurodegenerative Diseases (DZNE), 53127 Bonn, Germany; Department of Neurodegenerative Diseases and Geriatric Psychiatry, University Hospital Bonn, 53127 Bonn, Germany
| | - Mikael Simons
- Institute of Neuronal Cell Biology, Technical University Munich, 81377 Munich, Germany; German Center for Neurodegenerative Diseases (DZNE), 81377 Munich, Germany; Munich Cluster of Systems Neurology (SyNergy), 81377 Munich, Germany; Institute for Stroke and Dementia Research, University Hospital of Munich, LMU Munich, 81377 Munich, Germany.
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16
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Dong C, Meng X, Zhang T, Guo Z, Liu Y, Wu P, Chen S, Zhou F, Ma Y, Xiong H, Shu S, He A. Single-cell EpiChem jointly measures drug-chromatin binding and multimodal epigenome. Nat Methods 2024:10.1038/s41592-024-02360-0. [PMID: 39025969 DOI: 10.1038/s41592-024-02360-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2023] [Accepted: 06/25/2024] [Indexed: 07/20/2024]
Abstract
Studies of molecular and cellular functions of small-molecule inhibitors in cancer treatment, eliciting effects by targeting genome and epigenome associated proteins, requires measurement of drug-target engagement in single-cell resolution. Here we present EpiChem for in situ single-cell joint mapping of small molecules and multimodal epigenomic landscape. We demonstrate single-cell co-assays of three small molecules together with histone modifications, chromatin accessibility or target proteins in human colorectal cancer (CRC) organoids. Integrated multimodal analysis reveals diverse drug interactions in the context of chromatin states within heterogeneous CRC organoids. We further reveal drug genomic binding dynamics and adaptive epigenome across cell types after small-molecule drug treatment in CRC organoids. This method provides a unique tool to exploit the mechanisms of cell type-specific drug actions.
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Affiliation(s)
- Chao Dong
- Institute of Molecular Medicine, National Biomedical Imaging Center, College of Future Technology, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China
| | - Xiaoxuan Meng
- Institute of Molecular Medicine, National Biomedical Imaging Center, College of Future Technology, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China
| | - Tong Zhang
- Institute of Molecular Medicine, National Biomedical Imaging Center, College of Future Technology, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China
| | - Zhifang Guo
- State Key Laboratory of Molecular Oncology, Beijing Key Laboratory of Carcinogenesis and Translational Research, Department of Lymphoma, Peking University Cancer Hospital & Institute, Beijing, China
- Peking University International Cancer Institute, Beijing, China
- Peking University-Yunnan Baiyao International Medical Research Center, Beijing, China
| | - Yaxi Liu
- Institute of Molecular Medicine, National Biomedical Imaging Center, College of Future Technology, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China
| | - Peihuang Wu
- State Key Laboratory of Molecular Oncology, Beijing Key Laboratory of Carcinogenesis and Translational Research, Department of Lymphoma, Peking University Cancer Hospital & Institute, Beijing, China
| | - Shiwei Chen
- Peking University International Cancer Institute, Beijing, China
- Peking University-Yunnan Baiyao International Medical Research Center, Beijing, China
| | - Fanqi Zhou
- State Key Laboratory of Medical Molecular Biology, Haihe laboratory of Cell Ecosystem, Key Laboratory of RNA and Hematopoietic Regulation, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, China
| | - Yanni Ma
- State Key Laboratory of Medical Molecular Biology, Haihe laboratory of Cell Ecosystem, Key Laboratory of RNA and Hematopoietic Regulation, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, China
| | - Haiqing Xiong
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China
- Tianjin Institutes of Health Science, Tianjin, China
| | - Shaokun Shu
- State Key Laboratory of Molecular Oncology, Beijing Key Laboratory of Carcinogenesis and Translational Research, Department of Lymphoma, Peking University Cancer Hospital & Institute, Beijing, China.
- Peking University International Cancer Institute, Beijing, China.
- Peking University-Yunnan Baiyao International Medical Research Center, Beijing, China.
| | - Aibin He
- Institute of Molecular Medicine, National Biomedical Imaging Center, College of Future Technology, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China.
- Key laboratory of Carcinogenesis and Translational Research of Ministry of Education of China, Peking University Cancer Hospital & Institute, Beijing, China.
- Peking University Chengdu Academy for Advanced Interdisciplinary Biotechnologies, Chengdu, China.
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17
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Wang Z, Li Z, Luan T, Cui G, Shu S, Liang Y, Zhang K, Xiao J, Yu W, Cui J, Li A, Peng G, Fang Y. A spatiotemporal molecular atlas of mouse spinal cord injury identifies a distinct astrocyte subpopulation and therapeutic potential of IGFBP2. Dev Cell 2024:S1534-5807(24)00394-0. [PMID: 39029468 DOI: 10.1016/j.devcel.2024.06.016] [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: 10/09/2023] [Revised: 03/26/2024] [Accepted: 06/20/2024] [Indexed: 07/21/2024]
Abstract
Spinal cord injury (SCI) triggers a cascade of intricate molecular and cellular changes that determine the outcome. In this study, we resolve the spatiotemporal organization of the injured mouse spinal cord and quantitatively assess in situ cell-cell communication following SCI. By analyzing existing single-cell RNA sequencing datasets alongside our spatial data, we delineate a subpopulation of Igfbp2-expressing astrocytes that migrate from the white matter (WM) to gray matter (GM) and become reactive upon SCI, termed Astro-GMii. Further, Igfbp2 upregulation promotes astrocyte migration, proliferation, and reactivity, and the secreted IGFBP2 protein fosters neurite outgrowth. Finally, we show that IGFBP2 significantly reduces neuronal loss and remarkably improves the functional recovery in a mouse model of SCI in vivo. Together, this study not only provides a comprehensive molecular atlas of SCI but also exemplifies how this rich resource can be applied to endow cells and genes with functional insight and therapeutic potential.
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Affiliation(s)
- Zeqing Wang
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai 201210, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Zhuxia Li
- Center for Cell Lineage and Development, CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, GIBH-CUHK Joint Research Laboratory on Stem Cell and Regenerative Medicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou 510530, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Tianle Luan
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai 201210, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Guizhong Cui
- Guangzhou National Laboratory, Guangzhou 510005, China
| | - Shunpan Shu
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai 201210, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yiyao Liang
- Key Laboratory of CNS Regeneration (Ministry of Education), Guangdong Key Laboratory of Non-human Primate Research, GHM Institute of CNS Regeneration, Jinan University, Guangzhou 510632, China
| | - Kai Zhang
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai 201210, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jingshu Xiao
- Guangzhou National Laboratory, Guangzhou 510005, China
| | - Wei Yu
- Key Laboratory of CNS Regeneration (Ministry of Education), Guangdong Key Laboratory of Non-human Primate Research, GHM Institute of CNS Regeneration, Jinan University, Guangzhou 510632, China
| | - Jihong Cui
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai 201210, China
| | - Ang Li
- Key Laboratory of CNS Regeneration (Ministry of Education), Guangdong Key Laboratory of Non-human Primate Research, GHM Institute of CNS Regeneration, Jinan University, Guangzhou 510632, China.
| | - Guangdun Peng
- Center for Cell Lineage and Development, CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, GIBH-CUHK Joint Research Laboratory on Stem Cell and Regenerative Medicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou 510530, China; University of Chinese Academy of Sciences, Beijing 100049, China.
| | - Yanshan Fang
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai 201210, China; University of Chinese Academy of Sciences, Beijing 100049, China.
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18
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Xie Z, Chai Y, Zhu Z, Shen Z, Guo Z, Zhao Z, Xiao L, Du Z, Ou G, Li W. Vacuolar H +-ATPase determines daughter cell fates through asymmetric segregation of the nucleosome remodeling and deacetylase complex. eLife 2024; 12:RP89032. [PMID: 38994733 PMCID: PMC11245309 DOI: 10.7554/elife.89032] [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: 07/13/2024] Open
Abstract
Asymmetric cell divisions (ACDs) generate two daughter cells with identical genetic information but distinct cell fates through epigenetic mechanisms. However, the process of partitioning different epigenetic information into daughter cells remains unclear. Here, we demonstrate that the nucleosome remodeling and deacetylase (NuRD) complex is asymmetrically segregated into the surviving daughter cell rather than the apoptotic one during ACDs in Caenorhabditis elegans. The absence of NuRD triggers apoptosis via the EGL-1-CED-9-CED-4-CED-3 pathway, while an ectopic gain of NuRD enables apoptotic daughter cells to survive. We identify the vacuolar H+-adenosine triphosphatase (V-ATPase) complex as a crucial regulator of NuRD's asymmetric segregation. V-ATPase interacts with NuRD and is asymmetrically segregated into the surviving daughter cell. Inhibition of V-ATPase disrupts cytosolic pH asymmetry and NuRD asymmetry. We suggest that asymmetric segregation of V-ATPase may cause distinct acidification levels in the two daughter cells, enabling asymmetric epigenetic inheritance that specifies their respective life-versus-death fates.
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Affiliation(s)
- Zhongyun Xie
- Tsinghua-Peking Center for Life Sciences, Beijing Frontier Research Center for Biological Structure, McGovern Institute for Brain Research, State Key Laboratory of Membrane Biology, School of Life Sciences and MOE Key Laboratory for Protein Science, Tsinghua UniversityBeijingChina
| | - Yongping Chai
- Tsinghua-Peking Center for Life Sciences, Beijing Frontier Research Center for Biological Structure, McGovern Institute for Brain Research, State Key Laboratory of Membrane Biology, School of Life Sciences and MOE Key Laboratory for Protein Science, Tsinghua UniversityBeijingChina
| | - Zhiwen Zhu
- Tsinghua-Peking Center for Life Sciences, Beijing Frontier Research Center for Biological Structure, McGovern Institute for Brain Research, State Key Laboratory of Membrane Biology, School of Life Sciences and MOE Key Laboratory for Protein Science, Tsinghua UniversityBeijingChina
| | - Zijie Shen
- Tsinghua-Peking Center for Life Sciences, Beijing Frontier Research Center for Biological Structure, McGovern Institute for Brain Research, State Key Laboratory of Membrane Biology, School of Life Sciences and MOE Key Laboratory for Protein Science, Tsinghua UniversityBeijingChina
| | - Zhengyang Guo
- Tsinghua-Peking Center for Life Sciences, Beijing Frontier Research Center for Biological Structure, McGovern Institute for Brain Research, State Key Laboratory of Membrane Biology, School of Life Sciences and MOE Key Laboratory for Protein Science, Tsinghua UniversityBeijingChina
| | - Zhiguang Zhao
- State Key Laboratory of Molecular Developmental Biology, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, University of Chinese Academy of SciencesBeijingChina
| | - Long Xiao
- State Key Laboratory of Molecular Developmental Biology, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, University of Chinese Academy of SciencesBeijingChina
| | - Zhuo Du
- State Key Laboratory of Molecular Developmental Biology, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, University of Chinese Academy of SciencesBeijingChina
| | - Guangshuo Ou
- Tsinghua-Peking Center for Life Sciences, Beijing Frontier Research Center for Biological Structure, McGovern Institute for Brain Research, State Key Laboratory of Membrane Biology, School of Life Sciences and MOE Key Laboratory for Protein Science, Tsinghua UniversityBeijingChina
| | - Wei Li
- School of Medicine, Tsinghua UniversityBeijingChina
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19
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Udugampolage NS, Frolova S, Taurino J, Pini A, Martelli F, Voellenkle C. Coding and Non-Coding Transcriptomic Landscape of Aortic Complications in Marfan Syndrome. Int J Mol Sci 2024; 25:7367. [PMID: 39000474 PMCID: PMC11242319 DOI: 10.3390/ijms25137367] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2024] [Revised: 06/21/2024] [Accepted: 06/27/2024] [Indexed: 07/16/2024] Open
Abstract
Marfan syndrome (MFS) is a rare congenital disorder of the connective tissue, leading to thoracic aortic aneurysms (TAA) and dissection, among other complications. Currently, the most efficient strategy to prevent life-threatening dissection is preventive surgery. Periodic imaging applying complex techniques is required to monitor TAA progression and to guide the timing of surgical intervention. Thus, there is an acute demand for non-invasive biomarkers for diagnosis and prognosis, as well as for innovative therapeutic targets of MFS. Unraveling the intricate pathomolecular mechanisms underlying the syndrome is vital to address these needs. High-throughput platforms are particularly well-suited for this purpose, as they enable the integration of different datasets, such as transcriptomic and epigenetic profiles. In this narrative review, we summarize relevant studies investigating changes in both the coding and non-coding transcriptome and epigenome in MFS-induced TAA. The collective findings highlight the implicated pathways, such as TGF-β signaling, extracellular matrix structure, inflammation, and mitochondrial dysfunction. Potential candidates as biomarkers, such as miR-200c, as well as therapeutic targets emerged, like Tfam, associated with mitochondrial respiration, or miR-632, stimulating endothelial-to-mesenchymal transition. While these discoveries are promising, rigorous and extensive validation in large patient cohorts is indispensable to confirm their clinical relevance and therapeutic potential.
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Affiliation(s)
| | - Svetlana Frolova
- Molecular Cardiology Laboratory, IRCCS Policlinico San Donato, 20097 Milan, Italy; (S.F.); (C.V.)
- Department of Biosciences, University of Milan, 20122 Milan, Italy
| | - Jacopo Taurino
- Cardiovascular-Genetic Center, IRCCS Policlinico San Donato, 20097 Milan, Italy; (N.S.U.); (J.T.); (A.P.)
| | - Alessandro Pini
- Cardiovascular-Genetic Center, IRCCS Policlinico San Donato, 20097 Milan, Italy; (N.S.U.); (J.T.); (A.P.)
| | - Fabio Martelli
- Molecular Cardiology Laboratory, IRCCS Policlinico San Donato, 20097 Milan, Italy; (S.F.); (C.V.)
| | - Christine Voellenkle
- Molecular Cardiology Laboratory, IRCCS Policlinico San Donato, 20097 Milan, Italy; (S.F.); (C.V.)
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20
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Ghimire S, Xue B, Li K, Gannon RM, Wohlford-Lenane CL, Thurman AL, Gong H, Necker GC, Zheng J, Meyerholz DK, Perlman S, McCray PB, Pezzulo AA. IL-13 decreases susceptibility to airway epithelial SARS-CoV-2 infection but increases disease severity in vivo. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.03.601941. [PMID: 39005257 PMCID: PMC11244965 DOI: 10.1101/2024.07.03.601941] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/16/2024]
Abstract
Treatments available to prevent progression of virus-induced lung diseases, including coronavirus disease 2019 (COVID-19) are of limited benefit once respiratory failure occurs. The efficacy of approved and emerging cytokine signaling-modulating antibodies is variable and is affected by disease course and patient-specific inflammation patterns. Therefore, understanding the role of inflammation on the viral infectious cycle is critical for effective use of cytokine-modulating agents. We investigated the role of the type 2 cytokine IL-13 on SARS-CoV-2 binding/entry, replication, and host response in primary HAE cells in vitro and in a model of mouse-adapted SARS-CoV-2 infection in vivo. IL-13 protected airway epithelial cells from SARS-CoV-2 infection in vitro by decreasing the abundance of ACE2-expressing ciliated cells rather than by neutralization in the airway surface liquid or by interferon-mediated antiviral effects. In contrast, IL-13 worsened disease severity in mice; the effects were mediated by eicosanoid signaling and were abolished in mice deficient in the phospholipase A2 enzyme PLA2G2D. We conclude that IL-13-induced inflammation differentially affects multiple steps of COVID-19 pathogenesis. IL-13-induced inflammation may be protective against initial SARS-CoV-2 airway epithelial infection; however, it enhances disease progression in vivo. Blockade of IL-13 and/or eicosanoid signaling may be protective against progression to severe respiratory virus-induced lung disease.
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Affiliation(s)
- Shreya Ghimire
- Department of Internal Medicine, Roy J. and Lucille A. Carver College of Medicine, University of Iowa, Iowa City, Iowa
| | - Biyun Xue
- Department of Internal Medicine, Roy J. and Lucille A. Carver College of Medicine, University of Iowa, Iowa City, Iowa
| | - Kun Li
- Stead Family Department of Pediatrics, Roy J. and Lucille A. Carver College of Medicine, University of Iowa, Iowa City, IA
| | - Ryan M. Gannon
- Department of Internal Medicine, Roy J. and Lucille A. Carver College of Medicine, University of Iowa, Iowa City, Iowa
| | - Christine L. Wohlford-Lenane
- Stead Family Department of Pediatrics, Roy J. and Lucille A. Carver College of Medicine, University of Iowa, Iowa City, IA
| | - Andrew L. Thurman
- Department of Internal Medicine, Roy J. and Lucille A. Carver College of Medicine, University of Iowa, Iowa City, Iowa
| | - Huiyu Gong
- Department of Internal Medicine, Roy J. and Lucille A. Carver College of Medicine, University of Iowa, Iowa City, Iowa
| | - Grace C. Necker
- Department of Internal Medicine, Roy J. and Lucille A. Carver College of Medicine, University of Iowa, Iowa City, Iowa
| | - Jian Zheng
- Department of Microbiology and Immunology, Roy J. and Lucille A. Carver College of Medicine, University of Iowa, Iowa City, Iowa
| | - David K. Meyerholz
- Department of Pathology, Roy J. and Lucille A. Carver College of Medicine, University of Iowa, Iowa City, Iowa
| | - Stanley Perlman
- Stead Family Department of Pediatrics, Roy J. and Lucille A. Carver College of Medicine, University of Iowa, Iowa City, IA
- Department of Microbiology and Immunology, Roy J. and Lucille A. Carver College of Medicine, University of Iowa, Iowa City, Iowa
| | - Paul B. McCray
- Stead Family Department of Pediatrics, Roy J. and Lucille A. Carver College of Medicine, University of Iowa, Iowa City, IA
- Department of Microbiology and Immunology, Roy J. and Lucille A. Carver College of Medicine, University of Iowa, Iowa City, Iowa
| | - Alejandro A. Pezzulo
- Department of Internal Medicine, Roy J. and Lucille A. Carver College of Medicine, University of Iowa, Iowa City, Iowa
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21
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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 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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22
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Wang J, Liang Y, Xu C, Gao J, Tong J, Shi L. The heterogeneity of erythroid cells: insight at the single-cell transcriptome level. Cell Tissue Res 2024:10.1007/s00441-024-03903-9. [PMID: 38953986 DOI: 10.1007/s00441-024-03903-9] [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: 12/11/2023] [Accepted: 06/19/2024] [Indexed: 07/04/2024]
Abstract
Erythroid cells, the most prevalent cell type in blood, are one of the earliest products and permeate through the entire process of hematopoietic development in the human body, the oxygen-transporting function of which is crucial for maintaining overall health and life support. Previous investigations into erythrocyte differentiation and development have primarily focused on population-level analyses, lacking the single-cell perspective essential for comprehending the intricate pathways of erythroid maturation, differentiation, and the encompassing cellular heterogeneity. The continuous optimization of single-cell transcriptome sequencing technology, or single-cell RNA sequencing (scRNA-seq), provides a powerful tool for life sciences research, which has a particular superiority in the identification of unprecedented cell subgroups, the analyzing of cellular heterogeneity, and the transcriptomic characteristics of individual cells. Over the past decade, remarkable strides have been taken in the realm of single-cell RNA sequencing technology, profoundly enhancing our understanding of erythroid cells. In this review, we systematically summarize the recent developments in single-cell transcriptome sequencing technology and emphasize their substantial impact on the study of erythroid cells, highlighting their contributions, including the exploration of functional heterogeneity within erythroid populations, the identification of novel erythrocyte subgroups, the tracking of different erythroid lineages, and the unveiling of mechanisms governing erythroid fate decisions. These findings not only invigorate erythroid cell research but also offer new perspectives on the management of diseases related to erythroid cells.
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Affiliation(s)
- Jingwei Wang
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China
| | - Yipeng Liang
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China
| | - Changlu Xu
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China
| | - Jie Gao
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China
| | - Jingyuan Tong
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China.
| | - Lihong Shi
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China.
- Tianjin Institutes of Health Science, Tianjin, 301600, China.
- CAMS Center for Stem Cell Medicine, PUMC Department of Stem Cell and Regenerative Medicine, Tianjin, 300020, China.
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23
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Skinnider MA, Gautier M, Teo AYY, Kathe C, Hutson TH, Laskaratos A, de Coucy A, Regazzi N, Aureli V, James ND, Schneider B, Sofroniew MV, Barraud Q, Bloch J, Anderson MA, Squair JW, Courtine G. Single-cell and spatial atlases of spinal cord injury in the Tabulae Paralytica. Nature 2024; 631:150-163. [PMID: 38898272 DOI: 10.1038/s41586-024-07504-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Accepted: 05/01/2024] [Indexed: 06/21/2024]
Abstract
Here, we introduce the Tabulae Paralytica-a compilation of four atlases of spinal cord injury (SCI) comprising a single-nucleus transcriptome atlas of half a million cells, a multiome atlas pairing transcriptomic and epigenomic measurements within the same nuclei, and two spatial transcriptomic atlases of the injured spinal cord spanning four spatial and temporal dimensions. We integrated these atlases into a common framework to dissect the molecular logic that governs the responses to injury within the spinal cord1. The Tabulae Paralytica uncovered new biological principles that dictate the consequences of SCI, including conserved and divergent neuronal responses to injury; the priming of specific neuronal subpopulations to upregulate circuit-reorganizing programs after injury; an inverse relationship between neuronal stress responses and the activation of circuit reorganization programs; the necessity of re-establishing a tripartite neuroprotective barrier between immune-privileged and extra-neural environments after SCI and a failure to form this barrier in old mice. We leveraged the Tabulae Paralytica to develop a rejuvenative gene therapy that re-established this tripartite barrier, and restored the natural recovery of walking after paralysis in old mice. The Tabulae Paralytica provides a window into the pathobiology of SCI, while establishing a framework for integrating multimodal, genome-scale measurements in four dimensions to study biology and medicine.
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Affiliation(s)
- Michael A Skinnider
- NeuroX Institute, School of Life Sciences, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland
- Defitech Center for Interventional Neurotherapies (.NeuroRestore), CHUV/UNIL/EPFL, Lausanne, Switzerland
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA
- Ludwig Institute for Cancer Research, Princeton University, Princeton, NJ, USA
| | - Matthieu Gautier
- NeuroX Institute, School of Life Sciences, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland
- Defitech Center for Interventional Neurotherapies (.NeuroRestore), CHUV/UNIL/EPFL, Lausanne, Switzerland
| | - Alan Yue Yang Teo
- NeuroX Institute, School of Life Sciences, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland
- Defitech Center for Interventional Neurotherapies (.NeuroRestore), CHUV/UNIL/EPFL, Lausanne, Switzerland
| | - Claudia Kathe
- NeuroX Institute, School of Life Sciences, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland
- Defitech Center for Interventional Neurotherapies (.NeuroRestore), CHUV/UNIL/EPFL, Lausanne, Switzerland
| | - Thomas H Hutson
- NeuroX Institute, School of Life Sciences, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland
- Defitech Center for Interventional Neurotherapies (.NeuroRestore), CHUV/UNIL/EPFL, Lausanne, Switzerland
- Wyss Center for Bio and Neuroengineering, Geneva, Switzerland
| | - Achilleas Laskaratos
- NeuroX Institute, School of Life Sciences, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland
- Defitech Center for Interventional Neurotherapies (.NeuroRestore), CHUV/UNIL/EPFL, Lausanne, Switzerland
| | - Alexandra de Coucy
- NeuroX Institute, School of Life Sciences, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland
- Defitech Center for Interventional Neurotherapies (.NeuroRestore), CHUV/UNIL/EPFL, Lausanne, Switzerland
| | - Nicola Regazzi
- NeuroX Institute, School of Life Sciences, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland
- Defitech Center for Interventional Neurotherapies (.NeuroRestore), CHUV/UNIL/EPFL, Lausanne, Switzerland
| | - Viviana Aureli
- NeuroX Institute, School of Life Sciences, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland
- Defitech Center for Interventional Neurotherapies (.NeuroRestore), CHUV/UNIL/EPFL, Lausanne, Switzerland
- Department of Neurosurgery, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- Department of Clinical Neuroscience, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Nicholas D James
- NeuroX Institute, School of Life Sciences, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland
- Defitech Center for Interventional Neurotherapies (.NeuroRestore), CHUV/UNIL/EPFL, Lausanne, Switzerland
| | - Bernard Schneider
- NeuroX Institute, School of Life Sciences, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland
- Bertarelli Platform for Gene Therapy, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland
| | - Michael V Sofroniew
- Department of Neurobiology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Quentin Barraud
- NeuroX Institute, School of Life Sciences, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland
- Defitech Center for Interventional Neurotherapies (.NeuroRestore), CHUV/UNIL/EPFL, Lausanne, Switzerland
| | - Jocelyne Bloch
- NeuroX Institute, School of Life Sciences, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland
- Defitech Center for Interventional Neurotherapies (.NeuroRestore), CHUV/UNIL/EPFL, Lausanne, Switzerland
- Department of Neurosurgery, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- Department of Clinical Neuroscience, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Mark A Anderson
- NeuroX Institute, School of Life Sciences, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland.
- Defitech Center for Interventional Neurotherapies (.NeuroRestore), CHUV/UNIL/EPFL, Lausanne, Switzerland.
- Wyss Center for Bio and Neuroengineering, Geneva, Switzerland.
- Department of Clinical Neuroscience, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.
| | - Jordan W Squair
- NeuroX Institute, School of Life Sciences, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland.
- Defitech Center for Interventional Neurotherapies (.NeuroRestore), CHUV/UNIL/EPFL, Lausanne, Switzerland.
- Department of Neurosurgery, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.
| | - Grégoire Courtine
- NeuroX Institute, School of Life Sciences, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland.
- Defitech Center for Interventional Neurotherapies (.NeuroRestore), CHUV/UNIL/EPFL, Lausanne, Switzerland.
- Department of Neurosurgery, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.
- Department of Clinical Neuroscience, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.
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24
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Zhou G, Li T, Du J, Wu M, Lin D, Pu W, Zhang J, Gu Z. Harnessing HetHydrogel: A Universal Platform to Dropletize Single-Cell Multiomics. SMALL METHODS 2024; 8:e2301631. [PMID: 38419597 DOI: 10.1002/smtd.202301631] [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: 11/25/2023] [Revised: 01/12/2024] [Indexed: 03/02/2024]
Abstract
A universal platform is developed for dropletizing single cell plate-based multiomic assays, consisting of three main pillars: a miniaturized open Heterogeneous Hydrogel reactor (abbreviated HetHydrogel) for multi-step biochemistry, its tunable permeability that allows Tn5 tagmentation, and single cell droplet barcoding. Through optimizing the HetHydrogel manufacturing procedure, the chemical composition, and cell permeation conditions, simultaneous high-throughput mitochondrial DNA genotyping and chromatin profiling at the single-cell level are demonstrated using a mixed-species experiment. This platform offers a powerful way to investigate the genotype-phenotype relationships of various mtDNA mutations in biological processes. The HetHydrogel platform is believed to have the potential to democratize droplet technologies, upgrading a whole range of plate-based single cell assays to high throughput format.
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Affiliation(s)
- Guoqiang Zhou
- Center for Mitochondrial Genetics and Health, Greater Bay Area Institute of Precision Medicine (Guangzhou), Fudan University, Guangzhou, 511458, China
| | - Ting Li
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Fudan University, Shanghai, 200438, China
| | - Jingjing Du
- Center for Mitochondrial Genetics and Health, Greater Bay Area Institute of Precision Medicine (Guangzhou), Fudan University, Guangzhou, 511458, China
| | - Mengying Wu
- Center for Mitochondrial Genetics and Health, Greater Bay Area Institute of Precision Medicine (Guangzhou), Fudan University, Guangzhou, 511458, China
| | - Deng Lin
- Center for Mitochondrial Genetics and Health, Greater Bay Area Institute of Precision Medicine (Guangzhou), Fudan University, Guangzhou, 511458, China
| | - Weilin Pu
- Center for Mitochondrial Genetics and Health, Greater Bay Area Institute of Precision Medicine (Guangzhou), Fudan University, Guangzhou, 511458, China
| | - Jingwei Zhang
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Fudan University, Shanghai, 200438, China
- Zhejiang Lab, Hangzhou, 310000, China
| | - Zhenglong Gu
- Center for Mitochondrial Genetics and Health, Greater Bay Area Institute of Precision Medicine (Guangzhou), Fudan University, Guangzhou, 511458, China
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25
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Bilous M, Hérault L, Gabriel AA, Teleman M, Gfeller D. Building and analyzing metacells in single-cell genomics data. Mol Syst Biol 2024; 20:744-766. [PMID: 38811801 PMCID: PMC11220014 DOI: 10.1038/s44320-024-00045-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2024] [Revised: 05/03/2024] [Accepted: 05/08/2024] [Indexed: 05/31/2024] Open
Abstract
The advent of high-throughput single-cell genomics technologies has fundamentally transformed biological sciences. Currently, millions of cells from complex biological tissues can be phenotypically profiled across multiple modalities. The scaling of computational methods to analyze and visualize such data is a constant challenge, and tools need to be regularly updated, if not redesigned, to cope with ever-growing numbers of cells. Over the last few years, metacells have been introduced to reduce the size and complexity of single-cell genomics data while preserving biologically relevant information and improving interpretability. Here, we review recent studies that capitalize on the concept of metacells-and the many variants in nomenclature that have been used. We further outline how and when metacells should (or should not) be used to analyze single-cell genomics data and what should be considered when analyzing such data at the metacell level. To facilitate the exploration of metacells, we provide a comprehensive tutorial on the construction and analysis of metacells from single-cell RNA-seq data ( https://github.com/GfellerLab/MetacellAnalysisTutorial ) as well as a fully integrated pipeline to rapidly build, visualize and evaluate metacells with different methods ( https://github.com/GfellerLab/MetacellAnalysisToolkit ).
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Affiliation(s)
- Mariia Bilous
- Department of Oncology, Ludwig Institute for Cancer Research Lausanne, University of Lausanne, 1011, Lausanne, Switzerland
- Agora Cancer Research Centre, 1011, Lausanne, Switzerland
- Swiss Cancer Center Leman (SCCL), Lausanne, Switzerland
- Swiss Institute of Bioinformatics (SIB), 1015, Lausanne, Switzerland
| | - Léonard Hérault
- Department of Oncology, Ludwig Institute for Cancer Research Lausanne, University of Lausanne, 1011, Lausanne, Switzerland
- Agora Cancer Research Centre, 1011, Lausanne, Switzerland
- Swiss Cancer Center Leman (SCCL), Lausanne, Switzerland
- Swiss Institute of Bioinformatics (SIB), 1015, Lausanne, Switzerland
| | - Aurélie Ag Gabriel
- Department of Oncology, Ludwig Institute for Cancer Research Lausanne, University of Lausanne, 1011, Lausanne, Switzerland
- Agora Cancer Research Centre, 1011, Lausanne, Switzerland
- Swiss Cancer Center Leman (SCCL), Lausanne, Switzerland
- Swiss Institute of Bioinformatics (SIB), 1015, Lausanne, Switzerland
| | - Matei Teleman
- Department of Oncology, Ludwig Institute for Cancer Research Lausanne, University of Lausanne, 1011, Lausanne, Switzerland
- Agora Cancer Research Centre, 1011, Lausanne, Switzerland
- Swiss Cancer Center Leman (SCCL), Lausanne, Switzerland
- Swiss Institute of Bioinformatics (SIB), 1015, Lausanne, Switzerland
| | - David Gfeller
- Department of Oncology, Ludwig Institute for Cancer Research Lausanne, University of Lausanne, 1011, Lausanne, Switzerland.
- Agora Cancer Research Centre, 1011, Lausanne, Switzerland.
- Swiss Cancer Center Leman (SCCL), Lausanne, Switzerland.
- Swiss Institute of Bioinformatics (SIB), 1015, Lausanne, Switzerland.
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26
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Sun K, Liu X, Xu R, Liu C, Meng A, Lan X. Mapping the chromatin accessibility landscape of zebrafish embryogenesis at single-cell resolution by SPATAC-seq. Nat Cell Biol 2024; 26:1187-1199. [PMID: 38977847 DOI: 10.1038/s41556-024-01449-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Accepted: 05/30/2024] [Indexed: 07/10/2024]
Abstract
Currently, the dynamic accessible elements that determine regulatory programs responsible for the unique identity and function of each cell type during zebrafish embryogenesis lack detailed study. Here we present SPATAC-seq: a split-pool ligation-based assay for transposase-accessible chromatin using sequencing. Using SPATAC-seq, we profiled chromatin accessibility in more than 800,000 individual nuclei across 20 developmental stages spanning the sphere stage to the early larval protruding mouth stage. Using this chromatin accessibility map, we identified 604 cell states and inferred their developmental relationships. We also identified 959,040 candidate cis-regulatory elements (cCREs) and delineated development-specific cCREs, as well as transcription factors defining diverse cell identities. Importantly, enhancer reporter assays confirmed that the majority of tested cCREs exhibited robust enhanced green fluorescent protein expression in restricted cell types or tissues. Finally, we explored gene regulatory programs that drive pigment and notochord cell differentiation. Our work provides a valuable open resource for exploring driver regulators of cell fate decisions in zebrafish embryogenesis.
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Affiliation(s)
- Keyong Sun
- School of Medicine, Tsinghua University, Beijing, China
- Peking University-Tsinghua University-National Institute of Biological Sciences Joint Graduate Program, Tsinghua University, Beijing, China
| | - Xin Liu
- School of Life Sciences, Tsinghua University, Beijing, China
- Tsinghua University-Peking University Center for Life Sciences, Beijing, China
| | - Runda Xu
- School of Medicine, Tsinghua University, Beijing, China
- Tsinghua University-Peking University Center for Life Sciences, Beijing, China
| | - Chang Liu
- School of Medicine, Tsinghua University, Beijing, China
| | - Anming Meng
- School of Life Sciences, Tsinghua University, Beijing, China.
- Tsinghua University-Peking University Center for Life Sciences, Beijing, China.
| | - Xun Lan
- School of Medicine, Tsinghua University, Beijing, China.
- Peking University-Tsinghua University-National Institute of Biological Sciences Joint Graduate Program, Tsinghua University, Beijing, China.
- Tsinghua University-Peking University Center for Life Sciences, Beijing, China.
- Ministry of Education Key Laboratory of Bioinformatics, Tsinghua University, Beijing, China.
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27
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Chen R, Nie P, Wang J, Wang GZ. Deciphering brain cellular and behavioral mechanisms: Insights from single-cell and spatial RNA sequencing. WILEY INTERDISCIPLINARY REVIEWS. RNA 2024; 15:e1865. [PMID: 38972934 DOI: 10.1002/wrna.1865] [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: 01/31/2024] [Revised: 05/05/2024] [Accepted: 05/14/2024] [Indexed: 07/09/2024]
Abstract
The brain is a complex computing system composed of a multitude of interacting neurons. The computational outputs of this system determine the behavior and perception of every individual. Each brain cell expresses thousands of genes that dictate the cell's function and physiological properties. Therefore, deciphering the molecular expression of each cell is of great significance for understanding its characteristics and role in brain function. Additionally, the positional information of each cell can provide crucial insights into their involvement in local brain circuits. In this review, we briefly overview the principles of single-cell RNA sequencing and spatial transcriptomics, the potential issues and challenges in their data processing, and their applications in brain research. We further outline several promising directions in neuroscience that could be integrated with single-cell RNA sequencing, including neurodevelopment, the identification of novel brain microstructures, cognition and behavior, neuronal cell positioning, molecules and cells related to advanced brain functions, sleep-wake cycles/circadian rhythms, and computational modeling of brain function. We believe that the deep integration of these directions with single-cell and spatial RNA sequencing can contribute significantly to understanding the roles of individual cells or cell types in these specific functions, thereby making important contributions to addressing critical questions in those fields. This article is categorized under: RNA Evolution and Genomics > Computational Analyses of RNA RNA in Disease and Development > RNA in Development RNA in Disease and Development > RNA in Disease.
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Affiliation(s)
- Renrui Chen
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Pengxing Nie
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Jing Wang
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Guang-Zhong Wang
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
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28
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Huang D, Jiao X, Huang S, Liu J, Si H, Qi D, Pei X, Lu D, Wang Y, Li Z. Analysis of the heterogeneity and complexity of murine extraorbital lacrimal gland via single-cell RNA sequencing. Ocul Surf 2024; 34:60-95. [PMID: 38945476 DOI: 10.1016/j.jtos.2024.06.005] [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: 08/26/2022] [Revised: 06/22/2024] [Accepted: 06/26/2024] [Indexed: 07/02/2024]
Abstract
PURPOSE The lacrimal gland is essential for maintaining ocular surface health and avoiding external damage by secreting an aqueous layer of the tear film. However, a healthy lacrimal gland's inventory of cell types and heterogeneity remains understudied. METHODS Here, 10X Genome-based single-cell RNA sequencing was used to generate an unbiased classification of cellular diversity in the extraorbital lacrimal gland (ELG) of C57BL/6J mice. From 43,850 high-quality cells, we produced an atlas of cell heterogeneity and defined cell types using classic marker genes. The possible functions of these cells were analyzed through bioinformatics analysis. Additionally, the CellChat was employed for a preliminary analysis of the cell-cell communication network in the ELG. RESULTS Over 37 subclasses of cells were identified, including seven types of glandular epithelial cells, three types of fibroblasts, ten types of myeloid-derived immune cells, at least eleven types of lymphoid-derived immune cells, and five types of vascular-associated cell subsets. The cell-cell communication network analysis revealed that fibroblasts and immune cells play a pivotal role in the dense intercellular communication network within the mouse ELG. CONCLUSIONS This study provides a comprehensive transcriptome atlas and related database of the mouse ELG.
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Affiliation(s)
- Duliurui Huang
- Department of Ophthalmology, Zhengzhou University People's Hospital, Henan Provincial People's Hospital, Zhengzhou, Henan, China
| | - Xinwei Jiao
- Henan Eye Institute, Henan Eye Hospital and Henan Key Laboratory of Ophthalmology and Visual Science, Henan Provincial People's Hospital, People's Hospital of Zhengzhou University, People's Hospital of Henan University, Zhengzhou, 450000, China
| | - Shenzhen Huang
- Henan Eye Institute, Henan Eye Hospital and Henan Key Laboratory of Ophthalmology and Visual Science, Henan Provincial People's Hospital, People's Hospital of Zhengzhou University, People's Hospital of Henan University, Zhengzhou, 450000, China
| | - Jiangman Liu
- Department of Ophthalmology, Zhengzhou University People's Hospital, Henan Provincial People's Hospital, Zhengzhou, Henan, China
| | - Hongli Si
- Department of Ophthalmology, Zhengzhou University People's Hospital, Henan Provincial People's Hospital, Zhengzhou, Henan, China
| | - Di Qi
- Henan Eye Institute, Henan Eye Hospital and Henan Key Laboratory of Ophthalmology and Visual Science, Henan Provincial People's Hospital, People's Hospital of Zhengzhou University, People's Hospital of Henan University, Zhengzhou, 450000, China
| | - Xiaoting Pei
- Henan Eye Institute, Henan Eye Hospital and Henan Key Laboratory of Ophthalmology and Visual Science, Henan Provincial People's Hospital, People's Hospital of Zhengzhou University, People's Hospital of Henan University, Zhengzhou, 450000, China
| | - Dingli Lu
- Henan Eye Institute, Henan Eye Hospital and Henan Key Laboratory of Ophthalmology and Visual Science, Henan Provincial People's Hospital, People's Hospital of Zhengzhou University, People's Hospital of Henan University, Zhengzhou, 450000, China
| | - Yimian Wang
- Division of Medicine, Faculty of Medical Sciences, University College London, Gower Street, London, WC1E 6BT, UK
| | - Zhijie Li
- Department of Ophthalmology, Zhengzhou University People's Hospital, Henan Provincial People's Hospital, Zhengzhou, Henan, China; Henan Eye Institute, Henan Eye Hospital and Henan Key Laboratory of Ophthalmology and Visual Science, Henan Provincial People's Hospital, People's Hospital of Zhengzhou University, People's Hospital of Henan University, Zhengzhou, 450000, China.
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29
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Korshoj LE, Kielian T. Bacterial single-cell RNA sequencing captures biofilm transcriptional heterogeneity and differential responses to immune pressure. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.28.601229. [PMID: 38979200 PMCID: PMC11230364 DOI: 10.1101/2024.06.28.601229] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/10/2024]
Abstract
Biofilm formation is an important mechanism of survival and persistence for many bacterial pathogens. These multicellular communities contain subpopulations of cells that display vast metabolic and transcriptional diversity along with high recalcitrance to antibiotics and host immune defenses. Investigating the complex heterogeneity within biofilm has been hindered by the lack of a sensitive and high-throughput method to assess stochastic transcriptional activity and regulation between bacterial subpopulations, which requires single-cell resolution. We have developed an optimized bacterial single-cell RNA sequencing method, BaSSSh-seq, to study Staphylococcus aureus diversity during biofilm growth and transcriptional adaptations following immune cell exposure. We validated the ability of BaSSSh-seq to capture extensive transcriptional heterogeneity during biofilm compared to planktonic growth. Application of new computational tools revealed transcriptional regulatory networks across the heterogeneous biofilm subpopulations and identification of gene sets that were associated with a trajectory from planktonic to biofilm growth. BaSSSh-seq also detected alterations in biofilm metabolism, stress response, and virulence that were tailored to distinct immune cell populations. This work provides an innovative platform to explore biofilm dynamics at single-cell resolution, unlocking the potential for identifying biofilm adaptations to environmental signals and immune pressure.
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30
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Ruska Y, Csibi A, Dorogházi B, Szilvásy-Szabó A, Mohácsik P, Környei Z, Dénes Á, Kádár A, Puskár Z, Hrabovszky E, Gereben B, Wittmann G, Fekete C. Topography of the GLP-1/GLP-1 receptor system in the spinal cord of male mice. Sci Rep 2024; 14:14403. [PMID: 38909126 PMCID: PMC11193760 DOI: 10.1038/s41598-024-65442-1] [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: 04/22/2024] [Accepted: 06/20/2024] [Indexed: 06/24/2024] Open
Abstract
Glucagon-like peptide-1 receptor (GLP-1R) agonists are now commonly used to treat type 2 diabetes and obesity. GLP-1R signaling in the spinal cord has been suggested to account for the mild tachycardia caused by GLP-1R agonists, and may also be involved in the therapeutic effects of these drugs. However, the neuroanatomy of the GLP-1/GLP-1R system in the spinal cord is still poorly understood. Here we applied in situ hybridization and immunohistochemistry to characterize this system, and its relation to cholinergic neurons. GLP-1R transcript and protein were expressed in neuronal cell bodies across the gray matter, in matching distribution patterns. GLP-1R-immunolabeling was also robust in dendrites and axons, especially in laminae II-III in the dorsal horn. Cerebrospinal fluid-contacting neurons expressed GLP-1R protein at exceedingly high levels. Only small subpopulations of cholinergic neurons expressed GLP-1R, including a subset of sympathetic preganglionic neurons at the rostral tip of the intermediolateral nucleus. GLP-1 axons innervated all regions where GLP-1R neurons were distributed, except laminae II-III. Scattered preproglucagon (Gcg) mRNA-expressing neurons were identified in the cervical and lumbar enlargements. The results will facilitate further studies on how GLP-1 regulates the sympathetic system and other autonomic and somatic functions via the spinal cord.
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Affiliation(s)
- Yvette Ruska
- Laboratory of Integrative Neuroendocrinology, HUN-REN Institute of Experimental Medicine, Szigony Street 43, Budapest, 1083, Hungary
| | - Andrea Csibi
- Laboratory of Integrative Neuroendocrinology, HUN-REN Institute of Experimental Medicine, Szigony Street 43, Budapest, 1083, Hungary
| | - Beáta Dorogházi
- Laboratory of Molecular Cell Metabolism, HUN-REN Institute of Experimental Medicine, Budapest, 1083, Hungary
| | - Anett Szilvásy-Szabó
- Laboratory of Integrative Neuroendocrinology, HUN-REN Institute of Experimental Medicine, Szigony Street 43, Budapest, 1083, Hungary
| | - Petra Mohácsik
- Laboratory of Molecular Cell Metabolism, HUN-REN Institute of Experimental Medicine, Budapest, 1083, Hungary
| | - Zsuzsanna Környei
- "Momentum" Laboratory of Neuroimmunology, HUN-REN Institute of Experimental Medicine, Budapest, 1083, Hungary
| | - Ádám Dénes
- "Momentum" Laboratory of Neuroimmunology, HUN-REN Institute of Experimental Medicine, Budapest, 1083, Hungary
| | - Andrea Kádár
- Laboratory of Integrative Neuroendocrinology, HUN-REN Institute of Experimental Medicine, Szigony Street 43, Budapest, 1083, Hungary
| | - Zita Puskár
- Department of Anatomy, Histology and Embryology, Semmelweis University, Budapest, 1094, Hungary
| | - Erik Hrabovszky
- Laboratory of Reproductive Neurobiology, HUN-REN Institute of Experimental Medicine, Budapest, 1083, Hungary
| | - Balázs Gereben
- Laboratory of Molecular Cell Metabolism, HUN-REN Institute of Experimental Medicine, Budapest, 1083, Hungary
| | - Gábor Wittmann
- Laboratory of Integrative Neuroendocrinology, HUN-REN Institute of Experimental Medicine, Szigony Street 43, Budapest, 1083, Hungary.
| | - Csaba Fekete
- Laboratory of Integrative Neuroendocrinology, HUN-REN Institute of Experimental Medicine, Szigony Street 43, Budapest, 1083, Hungary.
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31
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O'Toole SM, Keller GB. Sample collection protocol for single-cell RNA sequencing of functionally identified neuronal populations in vivo. STAR Protoc 2024; 5:103135. [PMID: 38875113 PMCID: PMC11225893 DOI: 10.1016/j.xpro.2024.103135] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2024] [Revised: 04/28/2024] [Accepted: 05/29/2024] [Indexed: 06/16/2024] Open
Abstract
Here, we present a sample collection protocol for single-cell RNA sequencing of functionally identified neuronal populations in vivo with a virally delivered activity-dependent labeling tool (CaMPARI2). We describe steps for photoconversion in mice during the onset of computationally relevant events in a virtual reality environment, followed by removal and dissociation of the photo-labeled tissue, and separation of differentially labeled groups with fluorescence-activated cell sorting (FACS). We then detail procedures for characterizing and examining functionally relevant groups using standard bioinformatic techniques. For complete details on the use and execution of this protocol, please refer to O'Toole et al.1.
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Affiliation(s)
- Sean M O'Toole
- Friedrich Miescher Institute for Biomedical Research, Maulbeerstrasse 66, 4058 Basel, Switzerland
| | - Georg B Keller
- Friedrich Miescher Institute for Biomedical Research, Maulbeerstrasse 66, 4058 Basel, Switzerland; Faculty of Natural Sciences, University of Basel, Basel, Switzerland.
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32
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Huang K, Xu Y, Feng T, Lan H, Ling F, Xiang H, Liu Q. The Advancement and Application of the Single-Cell Transcriptome in Biological and Medical Research. BIOLOGY 2024; 13:451. [PMID: 38927331 PMCID: PMC11200756 DOI: 10.3390/biology13060451] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/10/2024] [Revised: 06/11/2024] [Accepted: 06/17/2024] [Indexed: 06/28/2024]
Abstract
Single-cell RNA sequencing technology (scRNA-seq) has been steadily developing since its inception in 2009. Unlike bulk RNA-seq, scRNA-seq identifies the heterogeneity of tissue cells and reveals gene expression changes in individual cells at the microscopic level. Here, we review the development of scRNA-seq, which has gone through iterations of reverse transcription, in vitro transcription, smart-seq, drop-seq, 10 × Genomics, and spatial single-cell transcriptome technologies. The technology of 10 × Genomics has been widely applied in medicine and biology, producing rich research results. Furthermore, this review presents a summary of the analytical process for single-cell transcriptome data and its integration with other omics analyses, including genomes, epigenomes, proteomes, and metabolomics. The single-cell transcriptome has a wide range of applications in biology and medicine. This review analyzes the applications of scRNA-seq in cancer, stem cell research, developmental biology, microbiology, and other fields. In essence, scRNA-seq provides a means of elucidating gene expression patterns in single cells, thereby offering a valuable tool for scientific research. Nevertheless, the current single-cell transcriptome technology is still imperfect, and this review identifies its shortcomings and anticipates future developments. The objective of this review is to facilitate a deeper comprehension of scRNA-seq technology and its applications in biological and medical research, as well as to identify avenues for its future development in alignment with practical needs.
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Affiliation(s)
- Kongwei Huang
- Guangdong Provincial Key Laboratory of Animal Molecular Design and Precise Breeding, School of Life Science and Engineering, Foshan University, Foshan 528225, China
- School of Biology and Biological Engineering, South China University of Technology, Guangzhou 510641, China
| | - Yixue Xu
- Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, College of Animal Science and Technology, Guangxi University, Nanning 530005, China;
| | - Tong Feng
- Key Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular Imaging, Center for Artificial Biology, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Hong Lan
- Guangdong Provincial Key Laboratory of Animal Molecular Design and Precise Breeding, School of Life Science and Engineering, Foshan University, Foshan 528225, China
| | - Fei Ling
- School of Biology and Biological Engineering, South China University of Technology, Guangzhou 510641, China
| | - Hai Xiang
- Guangdong Provincial Key Laboratory of Animal Molecular Design and Precise Breeding, School of Life Science and Engineering, Foshan University, Foshan 528225, China
| | - Qingyou Liu
- Guangdong Provincial Key Laboratory of Animal Molecular Design and Precise Breeding, School of Life Science and Engineering, Foshan University, Foshan 528225, China
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33
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Li H, Humphreys BD. Protocol for multimodal profiling of human kidneys with simultaneous high-throughput ATAC and RNA expression with sequencing. STAR Protoc 2024; 5:103049. [PMID: 38900631 PMCID: PMC11239685 DOI: 10.1016/j.xpro.2024.103049] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2024] [Revised: 03/31/2024] [Accepted: 04/15/2024] [Indexed: 06/22/2024] Open
Abstract
Simultaneous high-throughput ATAC and RNA expression with sequencing (SHARE-seq) profiles transcriptomics and chromatin accessibility in the same cells at high throughput. Here, we present a protocol for multimodal profiling of human kidneys with SHARE-seq. We describe steps for processing fixed nuclei for SHARE-seq split-pool barcoding and library preparation. We also detail how to determine the optimal working concentration of Tn5 transposase for transposition and tagmentation. This protocol allows researchers to generate large-scale single-cell multiomics data at low reagent cost. For complete details on the use and execution of this protocol, please refer to Li et al.1.
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Affiliation(s)
- Haikuo Li
- Division of Nephrology, Department of Medicine, Washington University in St. Louis, St. Louis, MO 63105, USA.
| | - Benjamin D Humphreys
- Division of Nephrology, Department of Medicine, Washington University in St. Louis, St. Louis, MO 63105, USA; Department of Developmental Biology, Washington University in St. Louis, St. Louis, MO 63105, USA.
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34
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Gaisser KD, Skloss SN, Brettner LM, Paleologu L, Roco CM, Rosenberg AB, Hirano M, DePaolo RW, Seelig G, Kuchina A. High-throughput single-cell transcriptomics of bacteria using combinatorial barcoding. Nat Protoc 2024:10.1038/s41596-024-01007-w. [PMID: 38886529 DOI: 10.1038/s41596-024-01007-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Accepted: 04/09/2024] [Indexed: 06/20/2024]
Abstract
Microbial split-pool ligation transcriptomics (microSPLiT) is a high-throughput single-cell RNA sequencing method for bacteria. With four combinatorial barcoding rounds, microSPLiT can profile transcriptional states in hundreds of thousands of Gram-negative and Gram-positive bacteria in a single experiment without specialized equipment. As bacterial samples are fixed and permeabilized before barcoding, they can be collected and stored ahead of time. During the first barcoding round, the fixed and permeabilized bacteria are distributed into a 96-well plate, where their transcripts are reverse transcribed into cDNA and labeled with the first well-specific barcode inside the cells. The cells are mixed and redistributed two more times into new 96-well plates, where the second and third barcodes are appended to the cDNA via in-cell ligation reactions. Finally, the cells are mixed and divided into aliquot sub-libraries, which can be stored until future use or prepared for sequencing with the addition of a fourth barcode. It takes 4 days to generate sequencing-ready libraries, including 1 day for collection and overnight fixation of samples. The standard plate setup enables single-cell transcriptional profiling of up to 1 million bacterial cells and up to 96 samples in a single barcoding experiment, with the possibility of expansion by adding barcoding rounds. The protocol requires experience in basic molecular biology techniques, handling of bacterial samples and preparation of DNA libraries for next-generation sequencing. It can be performed by experienced undergraduate or graduate students. Data analysis requires access to computing resources, familiarity with Unix command line and basic experience with Python or R.
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Affiliation(s)
| | | | - Leandra M Brettner
- Biodesign Institute Center for Mechanisms of Evolution, Arizona State University, Tempe, AZ, USA
| | - Luana Paleologu
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | | | | | - Matthew Hirano
- Department of Electrical and Computer Engineering, University of Washington, Seattle, WA, USA
| | - R William DePaolo
- Center for Microbiome Sciences and Therapeutics, School of Medicine, University of Washington, Seattle, WA, USA
- Department of Medicine, Division of Gastroenterology, School of Medicine, University of Washington, Seattle, WA, USA
| | - Georg Seelig
- Department of Electrical and Computer Engineering, University of Washington, Seattle, WA, USA
- Molecular Engineering and Sciences Institute, University of Washington, Seattle, WA, USA
- Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, WA, USA
| | - Anna Kuchina
- Institute for Systems Biology, Seattle, WA, USA.
- Department of Electrical and Computer Engineering, University of Washington, Seattle, WA, USA.
- Molecular Engineering and Sciences Institute, University of Washington, Seattle, WA, USA.
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35
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Zhang J, Yang Z, Zhao Z, Zhang N. Structural and pharmacological insights into cordycepin for neoplasms and metabolic disorders. Front Pharmacol 2024; 15:1367820. [PMID: 38953102 PMCID: PMC11215060 DOI: 10.3389/fphar.2024.1367820] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2024] [Accepted: 05/31/2024] [Indexed: 07/03/2024] Open
Abstract
Cytotoxic adenosine analogues were among the earliest chemotherapeutic agents utilised in cancer treatment. Cordycepin, a natural derivative of adenosine discovered in the fungus Ophiocordyceps sinensis, directly inhibits tumours not only by impeding biosynthesis, inducing apoptosis or autophagy, regulating the cell cycle, and curtailing tumour invasion and metastasis but also modulates the immune response within the tumour microenvironment. Furthermore, extensive research highlights cordycepin's significant therapeutic potential in alleviating hyperlipidaemia and regulating glucose metabolism. This review comprehensively analyses the structure-activity relationship of cordycepin and its analogues, outlines its pharmacokinetic properties, and strategies to enhance its bioavailability. Delving into the molecular biology, it explores the pharmacological mechanisms of cordycepin in tumour suppression and metabolic disorder treatment, thereby underscoring its immense potential in drug development within these domains and laying the groundwork for innovative treatment strategies.
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Affiliation(s)
- Jinming Zhang
- Department of Gastroenterology, First Hospital of Jilin University, Jilin University, Changchun, China
| | - Ziling Yang
- Second Hospital of Jilin University, Jilin University, Changchun, China
| | - Zhuo Zhao
- Department of Gastroenterology, First Hospital of Jilin University, Jilin University, Changchun, China
| | - Nan Zhang
- Department of Gastroenterology, First Hospital of Jilin University, Jilin University, Changchun, China
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36
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Yin C, Hair SC, Byeon GW, Bromley P, Meuleman W, Seelig G. Iterative deep learning-design of human enhancers exploits condensed sequence grammar to achieve cell type-specificity. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.14.599076. [PMID: 38915713 PMCID: PMC11195158 DOI: 10.1101/2024.06.14.599076] [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
An important and largely unsolved problem in synthetic biology is how to target gene expression to specific cell types. Here, we apply iterative deep learning to design synthetic enhancers with strong differential activity between two human cell lines. We initially train models on published datasets of enhancer activity and chromatin accessibility and use them to guide the design of synthetic enhancers that maximize predicted specificity. We experimentally validate these sequences, use the measurements to re-optimize the predictor, and design a second generation of enhancers with improved specificity. Our design methods embed relevant transcription factor binding site (TFBS) motifs with higher frequencies than comparable endogenous enhancers while using a more selective motif vocabulary, and we show that enhancer activity is correlated with transcription factor expression at the single cell level. Finally, we characterize causal features of top enhancers via perturbation experiments and show enhancers as short as 50bp can maintain specificity.
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Affiliation(s)
- Christopher Yin
- Department of Electrical & Computer Engineering, University of Washington, Seattle, WA
| | | | - Gun Woo Byeon
- Department of Electrical & Computer Engineering, University of Washington, Seattle, WA
| | - Peter Bromley
- Altius Institute for Biomedical Sciences, Seattle, WA
| | - Wouter Meuleman
- Altius Institute for Biomedical Sciences, Seattle, WA
- Paul G. Allen School of Computer Science & Engineering, University of Washington, Seattle, WA
| | - Georg Seelig
- Department of Electrical & Computer Engineering, University of Washington, Seattle, WA
- Paul G. Allen School of Computer Science & Engineering, University of Washington, Seattle, WA
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37
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Rebboah E, Rezaie N, Williams BA, Weimer AK, Shi M, Yang X, Liang HY, Dionne LA, Reese F, Trout D, Jou J, Youngworth I, Reinholdt L, Morabito S, Snyder MP, Wold BJ, Mortazavi A. The ENCODE mouse postnatal developmental time course identifies regulatory programs of cell types and cell states. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.12.598567. [PMID: 38915583 PMCID: PMC11195270 DOI: 10.1101/2024.06.12.598567] [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
Postnatal genomic regulation significantly influences tissue and organ maturation but is under-studied relative to existing genomic catalogs of adult tissues or prenatal development in mouse. The ENCODE4 consortium generated the first comprehensive single-nucleus resource of postnatal regulatory events across a diverse set of mouse tissues. The collection spans seven postnatal time points, mirroring human development from childhood to adulthood, and encompasses five core tissues. We identified 30 cell types, further subdivided into 69 subtypes and cell states across adrenal gland, left cerebral cortex, hippocampus, heart, and gastrocnemius muscle. Our annotations cover both known and novel cell differentiation dynamics ranging from early hippocampal neurogenesis to a new sex-specific adrenal gland population during puberty. We used an ensemble Latent Dirichlet Allocation strategy with a curated vocabulary of 2,701 regulatory genes to identify regulatory "topics," each of which is a gene vector, linked to cell type differentiation, subtype specialization, and transitions between cell states. We find recurrent regulatory topics in tissue-resident macrophages, neural cell types, endothelial cells across multiple tissues, and cycling cells of the adrenal gland and heart. Cell-type-specific topics are enriched in transcription factors and microRNA host genes, while chromatin regulators dominate mitosis topics. Corresponding chromatin accessibility data reveal dynamic and sex-specific regulatory elements, with enriched motifs matching transcription factors in regulatory topics. Together, these analyses identify both tissue-specific and common regulatory programs in postnatal development across multiple tissues through the lens of the factors regulating transcription.
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Affiliation(s)
- Elisabeth Rebboah
- Developmental and Cell Biology, University of California Irvine, Irvine, USA
- Center for Complex Biological Systems, University of California Irvine, Irvine, USA
| | - Narges Rezaie
- Developmental and Cell Biology, University of California Irvine, Irvine, USA
- Center for Complex Biological Systems, University of California Irvine, Irvine, USA
| | - Brian A. Williams
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, USA
| | - Annika K. Weimer
- Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute of MIT and Harvard, Cambridge, USA
| | - Minyi Shi
- Department of Next Generation Sequencing and Microchemistry, Proteomics and Lipidomics, Genentech, San Francisco, USA
| | - Xinqiong Yang
- Department of Genetics, Stanford University School of Medicine, Palo Alto, USA
| | - Heidi Yahan Liang
- Developmental and Cell Biology, University of California Irvine, Irvine, USA
| | | | - Fairlie Reese
- Developmental and Cell Biology, University of California Irvine, Irvine, USA
| | - Diane Trout
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, USA
| | - Jennifer Jou
- Department of Genetics, Stanford University School of Medicine, Palo Alto, USA
| | - Ingrid Youngworth
- Department of Genetics, Stanford University School of Medicine, Palo Alto, USA
| | | | - Samuel Morabito
- Developmental and Cell Biology, University of California Irvine, Irvine, USA
- Center for Complex Biological Systems, University of California Irvine, Irvine, USA
| | - Michael P. Snyder
- Department of Genetics, Stanford University School of Medicine, Palo Alto, USA
| | - Barbara J. Wold
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, USA
| | - Ali Mortazavi
- Developmental and Cell Biology, University of California Irvine, Irvine, USA
- Center for Complex Biological Systems, University of California Irvine, Irvine, USA
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Liu HK, Hao HL, You H, Feng F, Qi XH, Huang XY, Hou B, Tian CG, Wang H, Yang HM, Wang J, Wu R, Fang H, Zhou JN, Zhang JG, Zhang ZX. A Cysteinyl-tRNA Synthetase Mutation Causes Novel Autosomal-Dominant Inheritance of a Parkinsonism/Spinocerebellar-Ataxia Complex. Neurosci Bull 2024:10.1007/s12264-024-01231-0. [PMID: 38869703 DOI: 10.1007/s12264-024-01231-0] [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: 08/19/2023] [Accepted: 12/22/2023] [Indexed: 06/14/2024] Open
Abstract
This study aimed to identify possible pathogenic genes in a 90-member family with a rare combination of multiple neurodegenerative disease phenotypes, which has not been depicted by the known neurodegenerative disease. We performed physical and neurological examinations with International Rating Scales to assess signs of ataxia, Parkinsonism, and cognitive function, as well as brain magnetic resonance imaging scans with seven sequences. We searched for co-segregations of abnormal repeat-expansion loci, pathogenic variants in known spinocerebellar ataxia-related genes, and novel rare mutations via whole-genome sequencing and linkage analysis. A rare co-segregating missense mutation in the CARS gene was validated by Sanger sequencing and the aminoacylation activity of mutant CARS was measured by spectrophotometric assay. This pedigree presented novel late-onset core characteristics including cerebellar ataxia, Parkinsonism, and pyramidal signs in all nine affected members. Brain magnetic resonance imaging showed cerebellar/pons atrophy, pontine-midline linear hyperintensity, decreased rCBF in the bilateral basal ganglia and cerebellar dentate nucleus, and hypo-intensities of the cerebellar dentate nuclei, basal ganglia, mesencephalic red nuclei, and substantia nigra, all of which suggested neurodegeneration. Whole-genome sequencing identified a novel pathogenic heterozygous mutation (E795V) in the CARS gene, meanwhile, exhibited none of the known repeat-expansions or point mutations in pathogenic genes. Remarkably, this CARS mutation causes a 20% decrease in aminoacylation activity to charge tRNACys with L-cysteine in protein synthesis compared with that of the wild type. All family members carrying a heterozygous mutation CARS (E795V) had the same clinical manifestations and neuropathological changes of Parkinsonism and spinocerebellar-ataxia. These findings identify novel pathogenesis of Parkinsonism-spinocerebellar ataxia and provide insights into its genetic architecture.
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Affiliation(s)
- Han-Kui Liu
- BGI Genomics and BGI Research, Shenzhen, 518083, China
- Hebei Industrial Technology Research Institute of Genomics in Maternal and Child Health, Clin Lab, BGI Genomics, Shijiazhuang, 050011, China
| | - Hong-Lin Hao
- Department of Neurology, Clinical Epidemiology Unit, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, 100730, China
| | - Hui You
- Department of Neurology, Clinical Epidemiology Unit, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, 100730, China
| | - Feng Feng
- Department of Neurology, Clinical Epidemiology Unit, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, 100730, China
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, 100730, China
| | - Xiu-Hong Qi
- Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230026, China
| | | | - Bo Hou
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, 100730, China
| | | | - Han Wang
- Department of Neurology, Clinical Epidemiology Unit, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, 100730, China
| | | | - Jian Wang
- BGI Genomics and BGI Research, Shenzhen, 518083, China
| | - Rui Wu
- Department of Pathology, Beijing Key Laboratory of Biomarker Research and Transformation for Neurodegenerative Diseases, Peking University Third Hospital, School of Basic Medical Sciences, Peking University Health Science Center, Beijing, 100191, China
| | - Hui Fang
- Anhui Provincial Children's Hospital, Children's Hospital of Fudan University, Hefei, 230051, China
| | - Jiang-Ning Zhou
- Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230026, China
- Institute of Brain Science, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022, China
| | - Jian-Guo Zhang
- BGI Genomics and BGI Research, Shenzhen, 518083, China.
- Hebei Industrial Technology Research Institute of Genomics in Maternal and Child Health, Clin Lab, BGI Genomics, Shijiazhuang, 050011, China.
| | - Zhen-Xin Zhang
- Department of Neurology, Clinical Epidemiology Unit, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, 100730, China.
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Shaw DK, Saraswathy VM, McAdow AR, Zhou L, Park D, Mote R, Johnson AN, Mokalled MH. Elevated phagocytic capacity directs innate spinal cord repair. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.11.598515. [PMID: 38915507 PMCID: PMC11195157 DOI: 10.1101/2024.06.11.598515] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/26/2024]
Abstract
Immune cells elicit a continuum of transcriptional and functional states after spinal cord injury (SCI). In mammals, inefficient debris clearance and chronic inflammation impede recovery and overshadow pro-regenerative immune functions. We found that, unlike mammals, zebrafish SCI elicits transient immune activation and efficient debris clearance, without causing chronic inflammation. Single-cell transcriptomics and inducible genetic ablation showed zebrafish macrophages are highly phagocytic and required for regeneration. Cross-species comparisons between zebrafish and mammalian macrophages identified transcription and immune response regulator ( tcim ) as a macrophage-enriched zebrafish gene. Genetic deletion of zebrafish tcim impairs phagocytosis and regeneration, causes aberrant and chronic immune activation, and can be rescued by transplanting wild-type immune precursors into tcim mutants. Conversely, genetic expression of human TCIM accelerates debris clearance and regeneration by reprogramming myeloid precursors into activated phagocytes. This study establishes a central requirement for elevated phagocytic capacity to achieve innate spinal cord repair.
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40
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Ma Y, Guo S, Chen Y, Peng Y, Su X, Jiang H, Lin X, Zhang J. Single-nucleus chromatin landscape dataset of mouse brain development and aging. Sci Data 2024; 11:616. [PMID: 38866804 PMCID: PMC11169343 DOI: 10.1038/s41597-024-03382-1] [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: 02/26/2024] [Accepted: 05/15/2024] [Indexed: 06/14/2024] Open
Abstract
The development and aging of the brain constitute a lifelong dynamic process, marked by structural and functional changes that entail highly coordinated cellular differentiation and epigenetic regulatory mechanisms. Chromatin accessibility serves as the foundational basis for genetic activity. However, the holistic and dynamic chromatin landscape that spans various brain regions throughout development and ageing remains predominantly unexplored. In this study, we employed single-nucleus ATAC-seq to generate comprehensive chromatin accessibility maps, incorporating data from 69,178 cells obtained from four distinct brain regions - namely, the olfactory bulb (OB), cerebellum (CB), prefrontal cortex (PFC), and hippocampus (HP) - across key developmental time points at 7 P, 3 M, 12 M, and 18 M. We delineated the distribution of cell types across different age stages and brain regions, providing insight into chromatin accessible regions and key transcription factors specific to different cell types. Our data contribute to understanding the epigenetic basis of the formation of different brain regions, providing a dynamic landscape and comprehensive resource for revealing gene regulatory programs during brain development and aging.
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Affiliation(s)
- Yuting Ma
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
- Hebei Industrial Technology Research Institute of Genomics in Maternal & Child Health, Clin Lab, BGI Genomics, Shijiazhuang, 050035, China
- BGI Genomics, Shenzhen, 518083, China
| | - Sicheng Guo
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
- Hebei Industrial Technology Research Institute of Genomics in Maternal & Child Health, Clin Lab, BGI Genomics, Shijiazhuang, 050035, China
- BGI Genomics, Shenzhen, 518083, China
| | - Yixi Chen
- BGI Research, Shenzhen, 518083, China
- School of Biology and Biological Engineering, South China University of Technology, Guangzhou, China
| | | | - Xi Su
- Hebei Industrial Technology Research Institute of Genomics in Maternal & Child Health, Clin Lab, BGI Genomics, Shijiazhuang, 050035, China
- BGI Genomics, Shenzhen, 518083, China
| | - Hui Jiang
- BGI Genomics, Shenzhen, 518083, China
| | - Xiumei Lin
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China.
- BGI Research, Shenzhen, 518083, China.
| | - Jianguo Zhang
- Hebei Industrial Technology Research Institute of Genomics in Maternal & Child Health, Clin Lab, BGI Genomics, Shijiazhuang, 050035, China.
- BGI Genomics, Shenzhen, 518083, China.
- BGI Research, Shenzhen, 518083, China.
- School of Public Health, Hebei Medical University, Shijiazhuang, 050017, China.
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41
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Hoedjes KM, Grath S, Posnien N, Ritchie MG, Schlötterer C, Abbott JK, Almudi I, Coronado-Zamora M, Durmaz Mitchell E, Flatt T, Fricke C, Glaser-Schmitt A, González J, Holman L, Kankare M, Lenhart B, Orengo DJ, Snook RR, Yılmaz VM, Yusuf L. From whole bodies to single cells: A guide to transcriptomic approaches for ecology and evolutionary biology. Mol Ecol 2024:e17382. [PMID: 38856653 DOI: 10.1111/mec.17382] [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: 12/07/2023] [Revised: 04/09/2024] [Accepted: 04/29/2024] [Indexed: 06/11/2024]
Abstract
RNA sequencing (RNAseq) methodology has experienced a burst of technological developments in the last decade, which has opened up opportunities for studying the mechanisms of adaptation to environmental factors at both the organismal and cellular level. Selecting the most suitable experimental approach for specific research questions and model systems can, however, be a challenge and researchers in ecology and evolution are commonly faced with the choice of whether to study gene expression variation in whole bodies, specific tissues, and/or single cells. A wide range of sometimes polarised opinions exists over which approach is best. Here, we highlight the advantages and disadvantages of each of these approaches to provide a guide to help researchers make informed decisions and maximise the power of their study. Using illustrative examples of various ecological and evolutionary research questions, we guide the readers through the different RNAseq approaches and help them identify the most suitable design for their own projects.
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Affiliation(s)
- Katja M Hoedjes
- Amsterdam Institute for Life and Environment, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Sonja Grath
- Division of Evolutionary Biology, LMU Munich, Planegg-Martinsried, Germany
| | - Nico Posnien
- Department of Developmental Biology, Göttingen Center for Molecular Biosciences (GZMB), University of Göttingen, Göttingen, Germany
| | - Michael G Ritchie
- Centre for Biological Diversity, University of St Andrews, St Andrews, UK
| | | | | | - Isabel Almudi
- Departament de Genètica, Microbiologia i Estadística, Universitat de Barcelona, Barcelona, Spain
- Institut de Recerca de la Biodiversitat (IRBio), Universitat de Barcelona, Barcelona, Spain
| | | | - Esra Durmaz Mitchell
- Department of Biology, University of Fribourg, Fribourg, Switzerland
- Functional Genomics and Metabolism Research Unit, Department of Biochemistry and Molecular Biology, University of Southern Denmark, Odense, Denmark
| | - Thomas Flatt
- Department of Biology, University of Fribourg, Fribourg, Switzerland
| | - Claudia Fricke
- Institute for Zoology/Animal Ecology, Martin-Luther-University Halle-Wittenberg, Halle (Saale), Germany
| | | | - Josefa González
- Institute of Evolutionary Biology, CSIC, UPF, Barcelona, Spain
| | - Luke Holman
- School of Applied Sciences, Edinburgh Napier University, Edinburgh, UK
| | - Maaria Kankare
- Department of Biological and Environmental Science, University of Jyväskylä, Jyväskylä, Finland
| | - Benedict Lenhart
- Department of Biology, University of Virginia, Charlottesville, Virginia, USA
| | - Dorcas J Orengo
- Departament de Genètica, Microbiologia i Estadística, Universitat de Barcelona, Barcelona, Spain
- Institut de Recerca de la Biodiversitat (IRBio), Universitat de Barcelona, Barcelona, Spain
| | - Rhonda R Snook
- Department of Zoology, Stockholm University, Stockholm, Sweden
| | - Vera M Yılmaz
- Division of Evolutionary Biology, LMU Munich, Planegg-Martinsried, Germany
| | - Leeban Yusuf
- Centre for Biological Diversity, University of St Andrews, St Andrews, UK
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42
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Brettner L, Geiler-Samerotte K. Single-cell heterogeneity in ribosome content and the consequences for the growth laws. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.19.590370. [PMID: 38895328 PMCID: PMC11185559 DOI: 10.1101/2024.04.19.590370] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/21/2024]
Abstract
Previous work has suggested that the ribosome content of a cell is optimized to maximize growth given the nutrient availability. The resulting correlation between ribosome number and growth rate appears to be independent of the rate limiting nutrient and has been reported in many organisms. The robustness and universality of this observation has given it the classification of a "growth law." These laws have had powerful impacts on many biological disciplines. They have fueled predictions about how organisms evolve to maximize reproduction, and informed models about how cells regulate growth. Due to methodological limitations, this growth law has rarely been studied at the level of individual cells. While populations of fast-growing cells tend to have more ribosomes than populations of slow-growing cells, it is unclear if individual cells tightly regulate their ribosome content to match their environment. Here, we use recent ground-breaking single-cell RNA sequencing techniques to study this growth law at the single-cell level in two different microbes, S. cerevisiae (a single-celled yeast and eukaryote) and B. subtilis (a bacterium and prokaryote). In both species, we find enormous variation in the ribosomal content of single cells that is not predictive of growth rate. Fast-growing populations include cells showing transcriptional signatures of slow growth and stress, as do cells with the highest ribosome content we survey. Broadening our focus to the levels of non-ribosomal transcripts reveals subpopulations of cells in unique transcriptional states suggestive of divergent growth strategies. These results suggest that single-cell ribosome levels are not finely tuned to match population growth rates or nutrient availability, at least not in a way that can be captured by a unifying law that applies to all cell types. Overall, this work encourages the expansion of these "laws" and other models that predict how growth rates are regulated or how they evolve to consider single-cell heterogeneity.
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Affiliation(s)
- Leandra Brettner
- Biodesign Institute Center for Mechanisms of Evolution, Arizona State University, Tempe, Arizona, USA
| | - Kerry Geiler-Samerotte
- Biodesign Institute Center for Mechanisms of Evolution, Arizona State University, Tempe, Arizona, USA
- School of Life Sciences, Arizona State University, Tempe, Arizona, USA
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43
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Lyu J, Chen C. Linearly Amplified Single-Stranded RNA-Derived Transcriptome Sequencing (LAST-seq). Bio Protoc 2024; 14:e4998. [PMID: 38873015 PMCID: PMC11166533 DOI: 10.21769/bioprotoc.4998] [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: 01/31/2024] [Accepted: 05/08/2024] [Indexed: 06/15/2024] Open
Abstract
Single-cell RNA sequencing (scRNA-seq) stands as a cutting-edge technology widely used in biological and biomedical research. Existing scRNA-seq methods rely on reverse transcription (RT) and second-strand synthesis (SSS) to convert RNA to cDNA before amplification. However, these methods often suffer from limited RT/SSS efficiency, which compromises the sensitivity of RNA detection. Here, we develop a new method, linearly amplified single-stranded RNA-derived transcriptome sequencing (LAST-seq), which directly amplifies the original single-stranded RNA without prior RT and SSS and offers high-sensitivity RNA detection and a low level of technical noise in single-cell transcriptome analysis. LAST-seq has been applied to quantify transcriptional bursting kinetics in human cells, advancing our understanding of chromatin organization's role in regulating gene expression. Key features • An RNase H/DNA polymerase-based strategy to attach the T7 promoter to single-stranded RNA. • T7 promoter mediated IVT on single stranded RNA template at single cell level.
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Affiliation(s)
- Jun Lyu
- Laboratory of Biochemistry and Molecular Biology, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Chongyi Chen
- Laboratory of Biochemistry and Molecular Biology, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
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44
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Sullivan DK, Pachter L. Flexible parsing, interpretation, and editing of technical sequences with splitcode. Bioinformatics 2024; 40:btae331. [PMID: 38876979 PMCID: PMC11193061 DOI: 10.1093/bioinformatics/btae331] [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: 12/12/2023] [Revised: 03/14/2024] [Accepted: 06/12/2024] [Indexed: 06/16/2024] Open
Abstract
MOTIVATION Next-generation sequencing libraries are constructed with numerous synthetic constructs such as sequencing adapters, barcodes, and unique molecular identifiers. Such sequences can be essential for interpreting results of sequencing assays, and when they contain information pertinent to an experiment, they must be processed and analyzed. RESULTS We present a tool called splitcode, that enables flexible and efficient parsing, interpreting, and editing of sequencing reads. This versatile tool facilitates simple, reproducible preprocessing of reads from libraries constructed for a large array of single-cell and bulk sequencing assays. AVAILABILITY AND IMPLEMENTATION The splitcode program is available at http://github.com/pachterlab/splitcode.
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Affiliation(s)
- Delaney K Sullivan
- UCLA-Caltech Medical Scientist Training Program, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, United States
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125, United States
| | - Lior Pachter
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125, United States
- Department of Computing and Mathematical Sciences, California Institute of Technology, Pasadena, CA 91125, United States
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45
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Gupta P, O’Neill H, Wolvetang E, Chatterjee A, Gupta I. Advances in single-cell long-read sequencing technologies. NAR Genom Bioinform 2024; 6:lqae047. [PMID: 38774511 PMCID: PMC11106032 DOI: 10.1093/nargab/lqae047] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Revised: 04/18/2024] [Accepted: 04/29/2024] [Indexed: 05/24/2024] Open
Abstract
With an increase in accuracy and throughput of long-read sequencing technologies, they are rapidly being assimilated into the single-cell sequencing pipelines. For transcriptome sequencing, these techniques provide RNA isoform-level information in addition to the gene expression profiles. Long-read sequencing technologies not only help in uncovering complex patterns of cell-type specific splicing, but also offer unprecedented insights into the origin of cellular complexity and thus potentially new avenues for drug development. Additionally, single-cell long-read DNA sequencing enables high-quality assemblies, structural variant detection, haplotype phasing, resolving high-complexity regions, and characterization of epigenetic modifications. Given that significant progress has primarily occurred in single-cell RNA isoform sequencing (scRiso-seq), this review will delve into these advancements in depth and highlight the practical considerations and operational challenges, particularly pertaining to downstream analysis. We also aim to offer a concise introduction to complementary technologies for single-cell sequencing of the genome, epigenome and epitranscriptome. We conclude by identifying certain key areas of innovation that may drive these technologies further and foster more widespread application in biomedical science.
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Affiliation(s)
- Pallavi Gupta
- University of Queensland – IIT Delhi Research Academy, Hauz Khas, New Delhi 110016, India
- Australian Institute of Bioengineering and Nanotechnology (AIBN), The University of Queensland, St Lucia, QLD 4072, Australia
- Department of Biochemical Engineering and Biotechnology, Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110016, India
| | - Hannah O’Neill
- Department of Pathology, Dunedin School of Medicine, University of Otago, 58 Hanover Street, Dunedin 9054, New Zealand
| | - Ernst J Wolvetang
- Australian Institute of Bioengineering and Nanotechnology (AIBN), The University of Queensland, St Lucia, QLD 4072, Australia
| | - Aniruddha Chatterjee
- Department of Pathology, Dunedin School of Medicine, University of Otago, 58 Hanover Street, Dunedin 9054, New Zealand
| | - Ishaan Gupta
- Department of Biochemical Engineering and Biotechnology, Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110016, India
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46
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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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47
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Hong CKY, Ramu A, Zhao S, Cohen BA. Effect of genomic and cellular environments on gene expression noise. Genome Biol 2024; 25:137. [PMID: 38790076 PMCID: PMC11127367 DOI: 10.1186/s13059-024-03277-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Accepted: 05/13/2024] [Indexed: 05/26/2024] Open
Abstract
BACKGROUND Individual cells from isogenic populations often display large cell-to-cell differences in gene expression. This "noise" in expression derives from several sources, including the genomic and cellular environment in which a gene resides. Large-scale maps of genomic environments have revealed the effects of epigenetic modifications and transcription factor occupancy on mean expression levels, but leveraging such maps to explain expression noise will require new methods to assay how expression noise changes at locations across the genome. RESULTS To address this gap, we present Single-cell Analysis of Reporter Gene Expression Noise and Transcriptome (SARGENT), a method that simultaneously measures the noisiness of reporter genes integrated throughout the genome and the global mRNA profiles of individual reporter-gene-containing cells. Using SARGENT, we perform the first comprehensive genome-wide survey of how genomic locations impact gene expression noise. We find that the mean and noise of expression correlate with different histone modifications. We quantify the intrinsic and extrinsic components of reporter gene noise and, using the associated mRNA profiles, assign the extrinsic component to differences between the CD24+ "stem-like" substate and the more "differentiated" substate. SARGENT also reveals the effects of transgene integrations on endogenous gene expression, which will help guide the search for "safe-harbor" loci. CONCLUSIONS Taken together, we show that SARGENT is a powerful tool to measure both the mean and noise of gene expression at locations across the genome and that the data generatd by SARGENT reveals important insights into the regulation of gene expression noise genome-wide.
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Affiliation(s)
- Clarice K Y Hong
- The Edison Family Center for Genome Sciences and Systems Biology, School of Medicine, Washington University in St. Louis, Saint Louis, MO, 63110, USA
- Department of Genetics, School of Medicine, Washington University in St. Louis, Saint Louis, MO, 63110, USA
| | - Avinash Ramu
- The Edison Family Center for Genome Sciences and Systems Biology, School of Medicine, Washington University in St. Louis, Saint Louis, MO, 63110, USA
- Department of Genetics, School of Medicine, Washington University in St. Louis, Saint Louis, MO, 63110, USA
| | - Siqi Zhao
- The Edison Family Center for Genome Sciences and Systems Biology, School of Medicine, Washington University in St. Louis, Saint Louis, MO, 63110, USA
- Department of Genetics, School of Medicine, Washington University in St. Louis, Saint Louis, MO, 63110, USA
| | - Barak A Cohen
- The Edison Family Center for Genome Sciences and Systems Biology, School of Medicine, Washington University in St. Louis, Saint Louis, MO, 63110, USA.
- Department of Genetics, School of Medicine, Washington University in St. Louis, Saint Louis, MO, 63110, USA.
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48
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Samanta P, Cooke SF, McNulty R, Hormoz S, Rosenthal A. ProBac-seq, a bacterial single-cell RNA sequencing methodology using droplet microfluidics and large oligonucleotide probe sets. Nat Protoc 2024:10.1038/s41596-024-01002-1. [PMID: 38769144 DOI: 10.1038/s41596-024-01002-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Accepted: 03/12/2024] [Indexed: 05/22/2024]
Abstract
Methods that measure the transcriptomic state of thousands of individual cells have transformed our understanding of cellular heterogeneity in eukaryotic cells since their introduction in the past decade. While simple and accessible protocols and commercial products are now available for the processing of mammalian cells, these existing technologies are incompatible with use in bacterial samples for several fundamental reasons including the absence of polyadenylation on bacterial messenger RNA, the instability of bacterial transcripts and the incompatibility of bacterial cell morphology with existing methodologies. Recently, we developed ProBac sequencing (ProBac-seq), a method that overcomes these technical difficulties and provides high-quality single-cell gene expression data from thousands of bacterial cells by using messenger RNA-specific probes. Here we provide details for designing large oligonucleotide probe sets for an organism of choice, amplifying probe sets to produce sufficient quantities for repeated experiments, adding unique molecular indexes and poly-A tails to produce finalized probes, in situ probe hybridization and single-cell encapsulation and library preparation. This protocol, from the probe amplification to the library preparation, requires ~7 d to complete. ProBac-seq offers several advantages over other methods by capturing only the desired target sequences and avoiding nondesired transcripts, such as highly abundant ribosomal RNA, thus enriching for signal that better informs on cellular state. The use of multiple probes per gene can detect meaningful single-cell signals from cells expressing transcripts to a lesser degree or those grown in minimal media and other environmentally relevant conditions in which cells are less active. ProBac-seq is also compatible with other organisms that can be profiled by in situ hybridization techniques.
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Affiliation(s)
- Prosenjit Samanta
- Department of Microbiology and Immunology, University of North Carolina, Chapel Hill, NC, USA
| | - Samuel F Cooke
- Department of Microbiology and Immunology, University of North Carolina, Chapel Hill, NC, USA
| | - Ryan McNulty
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA
| | - Sahand Hormoz
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA
- Department of Systems Biology, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Adam Rosenthal
- Department of Microbiology and Immunology, University of North Carolina, Chapel Hill, NC, USA.
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49
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Pacalin NM, Steinhart Z, Shi Q, Belk JA, Dorovskyi D, Kraft K, Parker KR, Shy BR, Marson A, Chang HY. Bidirectional epigenetic editing reveals hierarchies in gene regulation. Nat Biotechnol 2024:10.1038/s41587-024-02213-3. [PMID: 38760566 DOI: 10.1038/s41587-024-02213-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Accepted: 03/19/2024] [Indexed: 05/19/2024]
Abstract
CRISPR perturbation methods are limited in their ability to study non-coding elements and genetic interactions. In this study, we developed a system for bidirectional epigenetic editing, called CRISPRai, in which we apply activating (CRISPRa) and repressive (CRISPRi) perturbations to two loci simultaneously in the same cell. We developed CRISPRai Perturb-seq by coupling dual perturbation gRNA detection with single-cell RNA sequencing, enabling study of pooled perturbations in a mixed single-cell population. We applied this platform to study the genetic interaction between two hematopoietic lineage transcription factors, SPI1 and GATA1, and discovered novel characteristics of their co-regulation on downstream target genes, including differences in SPI1 and GATA1 occupancy at genes that are regulated through different modes. We also studied the regulatory landscape of IL2 (interleukin-2) in Jurkat T cells, primary T cells and chimeric antigen receptor (CAR) T cells and elucidated mechanisms of enhancer-mediated IL2 gene regulation. CRISPRai facilitates investigation of context-specific genetic interactions, provides new insights into gene regulation and will enable exploration of non-coding disease-associated variants.
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Affiliation(s)
- Naomi M Pacalin
- Center for Personal Dynamic Regulomes, Stanford University, Stanford, CA, USA
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Zachary Steinhart
- Gladstone-UCSF Institute of Genomic Immunology, San Francisco, CA, USA
| | - Quanming Shi
- Center for Personal Dynamic Regulomes, Stanford University, Stanford, CA, USA
| | - Julia A Belk
- Center for Personal Dynamic Regulomes, Stanford University, Stanford, CA, USA
| | - Dmytro Dorovskyi
- Gladstone-UCSF Institute of Genomic Immunology, San Francisco, CA, USA
- Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
- Department of Laboratory Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Katerina Kraft
- Center for Personal Dynamic Regulomes, Stanford University, Stanford, CA, USA
| | - Kevin R Parker
- Center for Personal Dynamic Regulomes, Stanford University, Stanford, CA, USA
- Program in Epithelial Biology, Stanford University School of Medicine, Stanford, CA, USA
- Cartography Biosciences, Inc., South San Francisco, CA, USA
| | - Brian R Shy
- Gladstone-UCSF Institute of Genomic Immunology, San Francisco, CA, USA
- Department of Laboratory Medicine, University of California, San Francisco, San Francisco, CA, USA
- UCSF Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA
| | - Alexander Marson
- Gladstone-UCSF Institute of Genomic Immunology, San Francisco, CA, USA
- Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
- UCSF Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA
- Parker Institute for Cancer Immunotherapy, San Francisco, CA, USA
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
- Department of Microbiology and Immunology, University of California, San Francisco, San Francisco, CA, USA
- Diabetes Center, University of California, San Francisco, San Francisco, CA, USA
- Innovative Genomics Institute, University of California, Berkeley, Berkeley, CA, USA
| | - Howard Y Chang
- Center for Personal Dynamic Regulomes, Stanford University, Stanford, CA, USA.
- Howard Hughes Medical Institute, Stanford University, Stanford, CA, USA.
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50
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Chen S, Liang B, Xu J. Unveiling heterogeneity in MSCs: exploring marker-based strategies for defining MSC subpopulations. J Transl Med 2024; 22:459. [PMID: 38750573 PMCID: PMC11094970 DOI: 10.1186/s12967-024-05294-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Accepted: 05/11/2024] [Indexed: 05/19/2024] Open
Abstract
Mesenchymal stem/stromal cells (MSCs) represent a heterogeneous cell population distributed throughout various tissues, demonstrating remarkable adaptability to microenvironmental cues and holding immense promise for disease treatment. However, the inherent diversity within MSCs often leads to variability in therapeutic outcomes, posing challenges for clinical applications. To address this heterogeneity, purification of MSC subpopulations through marker-based isolation has emerged as a promising approach to ensure consistent therapeutic efficacy. In this review, we discussed the reported markers of MSCs, encompassing those developed through candidate marker strategies and high-throughput approaches, with the aim of explore viable strategies for addressing the heterogeneity of MSCs and illuminate prospective research directions in this field.
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Affiliation(s)
- Si Chen
- Shenzhen University Medical School, Shenzhen University, Shenzhen, 518000, People's Republic of China
| | - Bowei Liang
- Shenzhen University Medical School, Shenzhen University, Shenzhen, 518000, People's Republic of China
| | - Jianyong Xu
- Shenzhen Key Laboratory of Reproductive Immunology for Peri-Implantation, Guangdong Engineering Technology Research Center of Reproductive Immunology for Peri-Implantation, Shenzhen Zhongshan Obstetrics & Gynecology Hospital (formerly Shenzhen Zhongshan Urology Hospital), Fuqiang Avenue 1001, Shenzhen, 518060, Guangdong, People's Republic of China.
- Guangdong Engineering Technology Research Center of Reproductive Immunology for Peri-Implantation, Shenzhen, 518000, People's Republic of China.
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