51
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Kobayashi T, Yamashita A, Tsumaki N, Watanabe H. Subpopulations of fibroblasts derived from human iPS cells. Commun Biol 2024; 7:736. [PMID: 38890483 PMCID: PMC11189496 DOI: 10.1038/s42003-024-06419-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Accepted: 06/06/2024] [Indexed: 06/20/2024] Open
Abstract
Organ fibrosis causes collagen fiber overgrowth and impairs organ function. Cardiac fibrosis after myocardial infarction impairs cardiac function significantly, pulmonary fibrosis reduces gas exchange efficiency, and liver fibrosis disturbs the natural function of the liver. Its development is associated with the differentiation of fibroblasts into myofibroblasts and increased collagen synthesis. Fibrosis has organ specificity, defined by the heterogeneity of fibroblasts. Although this heterogeneity is established during embryonic development, it has not been defined yet. Fibroblastic differentiation of induced pluripotent stem cells (iPSCs) recapitulates the process by which fibroblasts acquire diversity. Here, we differentiated iPSCs into cardiac, hepatic, and dermal fibroblasts and analyzed their properties using single-cell RNA sequencing. We observed characteristic subpopulations with different ratios in each organ-type fibroblast group, which contained both resting and distinct ACTA2+ myofibroblasts. These findings provide crucial information on the ontogeny-based heterogeneity of fibroblasts, leading to the development of therapeutic strategies to control fibrosis.
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Affiliation(s)
- Takashi Kobayashi
- Institute for Molecular Science of Medicine, Aichi Medical University, Aichi, Japan
| | - Akihiro Yamashita
- Department of Tissue Biochemistry, Graduate School of Medicine and Frontier Biosciences, Osaka University, Osaka, Japan
| | - Noriyuki Tsumaki
- Department of Tissue Biochemistry, Graduate School of Medicine and Frontier Biosciences, Osaka University, Osaka, Japan
| | - Hideto Watanabe
- Institute for Molecular Science of Medicine, Aichi Medical University, Aichi, Japan.
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52
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Wang HLV, Xiang JF, Yuan C, Veire AM, Gendron TF, Murray ME, Tansey MG, Hu J, Gearing M, Glass JD, Jin P, Corces VG, McEachin ZT. pTDP-43 levels correlate with cell type specific molecular alterations in the prefrontal cortex of C9orf72 ALS/FTD patients. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.01.12.523820. [PMID: 36711601 PMCID: PMC9882184 DOI: 10.1101/2023.01.12.523820] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
Abstract
Repeat expansions in the C9orf72 gene are the most common genetic cause of amyotrophic lateral sclerosis and familial frontotemporal dementia (ALS/FTD). To identify molecular defects that take place in the dorsolateral frontal cortex of patients with C9orf72 ALS/FTD, we compared healthy controls with C9orf72 ALS/FTD donor samples staged based on the levels of cortical phosphorylated TAR DNA binding protein (pTDP-43), a neuropathological hallmark of disease progression. We identified distinct molecular changes in different cell types that take place during FTD development. Loss of neurosurveillance microglia and activation of the complement cascade take place early, when pTDP-43 aggregates are absent or very low, and become more pronounced in late stages, suggesting an initial involvement of microglia in disease progression. Reduction of layer 2-3 cortical projection neurons with high expression of CUX2/LAMP5 also occurs early, and the reduction becomes more pronounced as pTDP-43 accumulates. Several unique features were observed only in samples with high levels of pTDP-43, including global alteration of chromatin accessibility in oligodendrocytes, microglia, and astrocytes; higher ratios of premature oligodendrocytes; increased levels of the noncoding RNA NEAT1 in astrocytes and neurons, and higher amount of phosphorylated ribosomal protein S6. Our findings reveal previously unknown progressive functional changes in major cell types found in the frontal cortex of C9orf72 ALS/FTD patients that shed light on the mechanisms underlying the pathology of this disease.
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Affiliation(s)
- Hsiao-Lin V. Wang
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA 30322
- Emory Center for Neurodegenerative Diseases, Emory University School of Medicine, Atlanta, GA 30322
| | - Jian-Feng Xiang
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA 30322
| | - Chenyang Yuan
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA 30322
- Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA, 30322, USA
| | - Austin M. Veire
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL 32224
| | | | | | - Malú G. Tansey
- Center for Translational Research in Neurodegenerative Disease, University of Florida, Gainesville, FL 32607
- Norman Fixel Institute for Neurological Diseases, University of Florida, Gainesville, FL 32607
| | - Jian Hu
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA 30322
- Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA, 30322, USA
| | - Marla Gearing
- Emory Center for Neurodegenerative Diseases, Emory University School of Medicine, Atlanta, GA 30322
- Department of Neurology, Emory University School of Medicine, Atlanta, GA 30322
- Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA 30322
| | - Jonathan D. Glass
- Emory Center for Neurodegenerative Diseases, Emory University School of Medicine, Atlanta, GA 30322
- Department of Neurology, Emory University School of Medicine, Atlanta, GA 30322
| | - Peng Jin
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA 30322
- Emory Center for Neurodegenerative Diseases, Emory University School of Medicine, Atlanta, GA 30322
| | - Victor G. Corces
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA 30322
- Emory Center for Neurodegenerative Diseases, Emory University School of Medicine, Atlanta, GA 30322
| | - Zachary T. McEachin
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA 30322
- Emory Center for Neurodegenerative Diseases, Emory University School of Medicine, Atlanta, GA 30322
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53
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Shang Z, Fan Y, Xi S, Zhang S, Shen W, Tao L, Xu C, Tan J, Fan M, Ma H, Lai Y, Sun D, Cheng H. Arenobufagin enhances T-cell anti-tumor immunity in colorectal cancer by modulating HSP90β accessibility. PHYTOMEDICINE : INTERNATIONAL JOURNAL OF PHYTOTHERAPY AND PHYTOPHARMACOLOGY 2024; 128:155497. [PMID: 38640855 DOI: 10.1016/j.phymed.2024.155497] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Revised: 02/01/2024] [Accepted: 02/26/2024] [Indexed: 04/21/2024]
Abstract
BACKGROUND Colorectal cancer (CRC) is a significant public health issue, ranking as one of the predominant cancer types globally in terms of incidence. Intriguingly, Arenobufagin (Are), a compound extracted from toad venom, has demonstrated the potential to inhibit tumor growth effectively. PURPOSE This study aimed to explore Are's molecular targets and unravel its antitumor mechanism in CRC. Specifically, we were interested in its impact on immune checkpoint modulation and correlations with HSP90β-STAT3-PD-L1 axis activity. METHODS We investigated the in vivo antitumor effects of Are by constructing a colorectalcancer subcutaneous xenograft mouse model. Subsequently, we employed single-cell multi-omics technology to study the potential mechanism by which Are inhibits CRC. Utilizing target-responsive accessibility profiling (TRAP) technology, we identified heatshock protein 90β (HSP90β) as the direct target of Are, and confirmed this through a microscale thermophoresis experiment (MST). Further downstream mechanisms were explored through techniques such as co-immunoprecipitation, Western blotting, qPCR, and immunofluorescence. Concurrently, we arrived at the same research conclusion at the organoid level by co-cultivating with immune cells. RESULTS We observed that Are inhibits PD-Ll expression in CRC tumor xenografts at low concentrations. Moreover, TRAP revealed that HSP90β's accessibility significantly decreased upon Are binding. We demonstrated a decrease in the activity of the HSP90β-STAT3-PD-Ll axis following low-concentration Are treatment in vivo. The PDO analysis showed improved enrichment of lymphocytes, particularly T cells, on the PDOs following Are treatment. CONCLUSION Contrary to previous research focusing on the direct cytotoxicity of Are towards tumor cells, our findings indicate that it can also inhibit tumor growth at lower concentrations through the modulation of immune checkpoints. This study unveils a novel anti-tumor mechanism of Are and stimulates contemplation on the dose-response relationship of natural products, which is beneficial for the clinical translational application of Are.
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Affiliation(s)
- Zhihao Shang
- Jiangsu Collaborative Innovation Center of Traditional Chinese Medicine Prevention and Treatment of Tumor, Nanjing University of Chinese Medicine, Nanjing, 210046, China; The First School of Clinical Medicine, Nanjing University of Chinese Medicine, Nanjing, 210046, China
| | - Yiping Fan
- Jiangsu Collaborative Innovation Center of Traditional Chinese Medicine Prevention and Treatment of Tumor, Nanjing University of Chinese Medicine, Nanjing, 210046, China; The First School of Clinical Medicine, Nanjing University of Chinese Medicine, Nanjing, 210046, China; Jiaxing Hospital of Traditional Chinese Medicine, Jiaxing 314000, China
| | - Songyang Xi
- Jiangsu Collaborative Innovation Center of Traditional Chinese Medicine Prevention and Treatment of Tumor, Nanjing University of Chinese Medicine, Nanjing, 210046, China; The First School of Clinical Medicine, Nanjing University of Chinese Medicine, Nanjing, 210046, China; Zhenjiang Hospital of Chinese Traditional and Western Medicine, Zhenjiang, 212000, China
| | - Shang Zhang
- Jiangsu Collaborative Innovation Center of Traditional Chinese Medicine Prevention and Treatment of Tumor, Nanjing University of Chinese Medicine, Nanjing, 210046, China; The First School of Clinical Medicine, Nanjing University of Chinese Medicine, Nanjing, 210046, China
| | - Weixing Shen
- Jiangsu Collaborative Innovation Center of Traditional Chinese Medicine Prevention and Treatment of Tumor, Nanjing University of Chinese Medicine, Nanjing, 210046, China; The First School of Clinical Medicine, Nanjing University of Chinese Medicine, Nanjing, 210046, China
| | - Lihuiping Tao
- Jiangsu Collaborative Innovation Center of Traditional Chinese Medicine Prevention and Treatment of Tumor, Nanjing University of Chinese Medicine, Nanjing, 210046, China; The First School of Clinical Medicine, Nanjing University of Chinese Medicine, Nanjing, 210046, China
| | - Changliang Xu
- Jiangsu Collaborative Innovation Center of Traditional Chinese Medicine Prevention and Treatment of Tumor, Nanjing University of Chinese Medicine, Nanjing, 210046, China; The First School of Clinical Medicine, Nanjing University of Chinese Medicine, Nanjing, 210046, China
| | - Jiani Tan
- Jiangsu Collaborative Innovation Center of Traditional Chinese Medicine Prevention and Treatment of Tumor, Nanjing University of Chinese Medicine, Nanjing, 210046, China; The First School of Clinical Medicine, Nanjing University of Chinese Medicine, Nanjing, 210046, China
| | - Minmin Fan
- Jiangsu Collaborative Innovation Center of Traditional Chinese Medicine Prevention and Treatment of Tumor, Nanjing University of Chinese Medicine, Nanjing, 210046, China; The First School of Clinical Medicine, Nanjing University of Chinese Medicine, Nanjing, 210046, China
| | - Hongyue Ma
- School of Pharmacy, Nanjing University of Chinese Medicine, Nanjing, 210046, China
| | - Yueyang Lai
- Jiangsu Collaborative Innovation Center of Traditional Chinese Medicine Prevention and Treatment of Tumor, Nanjing University of Chinese Medicine, Nanjing, 210046, China; The First School of Clinical Medicine, Nanjing University of Chinese Medicine, Nanjing, 210046, China.
| | - Dongdong Sun
- Jiangsu Collaborative Innovation Center of Traditional Chinese Medicine Prevention and Treatment of Tumor, Nanjing University of Chinese Medicine, Nanjing, 210046, China; School of Integrated Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, 210046, China.
| | - Haibo Cheng
- Jiangsu Collaborative Innovation Center of Traditional Chinese Medicine Prevention and Treatment of Tumor, Nanjing University of Chinese Medicine, Nanjing, 210046, China; The First School of Clinical Medicine, Nanjing University of Chinese Medicine, Nanjing, 210046, China.
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54
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Emani PS, Liu JJ, Clarke D, Jensen M, Warrell J, Gupta C, Meng R, Lee CY, Xu S, Dursun C, Lou S, Chen Y, Chu Z, Galeev T, Hwang A, Li Y, Ni P, Zhou X, Bakken TE, Bendl J, Bicks L, Chatterjee T, Cheng L, Cheng Y, Dai Y, Duan Z, Flaherty M, Fullard JF, Gancz M, Garrido-Martín D, Gaynor-Gillett S, Grundman J, Hawken N, Henry E, Hoffman GE, Huang A, Jiang Y, Jin T, Jorstad NL, Kawaguchi R, Khullar S, Liu J, Liu J, Liu S, Ma S, Margolis M, Mazariegos S, Moore J, Moran JR, Nguyen E, Phalke N, Pjanic M, Pratt H, Quintero D, Rajagopalan AS, Riesenmy TR, Shedd N, Shi M, Spector M, Terwilliger R, Travaglini KJ, Wamsley B, Wang G, Xia Y, Xiao S, Yang AC, Zheng S, Gandal MJ, Lee D, Lein ES, Roussos P, Sestan N, Weng Z, White KP, Won H, Girgenti MJ, Zhang J, Wang D, Geschwind D, Gerstein M. Single-cell genomics and regulatory networks for 388 human brains. Science 2024; 384:eadi5199. [PMID: 38781369 PMCID: PMC11365579 DOI: 10.1126/science.adi5199] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2023] [Accepted: 04/05/2024] [Indexed: 05/25/2024]
Abstract
Single-cell genomics is a powerful tool for studying heterogeneous tissues such as the brain. Yet little is understood about how genetic variants influence cell-level gene expression. Addressing this, we uniformly processed single-nuclei, multiomics datasets into a resource comprising >2.8 million nuclei from the prefrontal cortex across 388 individuals. For 28 cell types, we assessed population-level variation in expression and chromatin across gene families and drug targets. We identified >550,000 cell type-specific regulatory elements and >1.4 million single-cell expression quantitative trait loci, which we used to build cell-type regulatory and cell-to-cell communication networks. These networks manifest cellular changes in aging and neuropsychiatric disorders. We further constructed an integrative model accurately imputing single-cell expression and simulating perturbations; the model prioritized ~250 disease-risk genes and drug targets with associated cell types.
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Affiliation(s)
- Prashant S Emani
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Jason J Liu
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Declan Clarke
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Matthew Jensen
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Jonathan Warrell
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Chirag Gupta
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI 53706, USA
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Ran Meng
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Che Yu Lee
- Department of Computer Science, University of California, Irvine, CA 92697, USA
| | - Siwei Xu
- Department of Computer Science, University of California, Irvine, CA 92697, USA
| | - Cagatay Dursun
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Shaoke Lou
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Yuhang Chen
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Zhiyuan Chu
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
| | - Timur Galeev
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Ahyeon Hwang
- Department of Computer Science, University of California, Irvine, CA 92697, USA
- Mathematical, Computational and Systems Biology, University of California, Irvine, CA 92697, USA
| | - Yunyang Li
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
- Department of Computer Science, Yale University, New Haven, CT 06520, USA
| | - Pengyu Ni
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Xiao Zhou
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | | | - Jaroslav Bendl
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Lucy Bicks
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
| | - Tanima Chatterjee
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | | | - Yuyan Cheng
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
- Department of Ophthalmology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Yi Dai
- Department of Computer Science, University of California, Irvine, CA 92697, USA
| | - Ziheng Duan
- Department of Computer Science, University of California, Irvine, CA 92697, USA
| | | | - John F Fullard
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Michael Gancz
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Diego Garrido-Martín
- Department of Genetics, Microbiology and Statistics, Universitat de Barcelona, Barcelona 08028, Spain
| | - Sophia Gaynor-Gillett
- Tempus Labs, Chicago, IL 60654, USA
- Department of Biology, Cornell College, Mount Vernon, IA 52314, USA
| | - Jennifer Grundman
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
| | - Natalie Hawken
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
| | - Ella Henry
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Gabriel E Hoffman
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Mental Illness Research Education and Clinical Center, James J. Peters VA Medical Center, Bronx, NY 10468, USA
- Center for Precision Medicine and Translational Therapeutics, James J. Peters VA Medical Center, Bronx, NY 10468, USA
| | - Ao Huang
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
| | - Yunzhe Jiang
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Ting Jin
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI 53706, USA
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA
| | | | - Riki Kawaguchi
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
- Center for Autism Research and Treatment, Semel Institute, University of California, Los Angeles, CA 90095, USA
| | - Saniya Khullar
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI 53706, USA
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Jianyin Liu
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
| | - Junhao Liu
- Department of Computer Science, University of California, Irvine, CA 92697, USA
| | - Shuang Liu
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Shaojie Ma
- Department of Neuroscience, Yale University, New Haven, CT 06510, USA
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | | | - Samantha Mazariegos
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
| | - Jill Moore
- Department of Genomics and Computational Biology, UMass Chan Medical School, Worcester, MA 01605, USA
| | | | - Eric Nguyen
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Nishigandha Phalke
- Department of Genomics and Computational Biology, UMass Chan Medical School, Worcester, MA 01605, USA
| | - Milos Pjanic
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Henry Pratt
- Department of Genomics and Computational Biology, UMass Chan Medical School, Worcester, MA 01605, USA
| | - Diana Quintero
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
| | | | - Tiernon R Riesenmy
- Department of Statistics and Data Science, Yale University, New Haven, CT 06520, USA
| | - Nicole Shedd
- Department of Genomics and Computational Biology, UMass Chan Medical School, Worcester, MA 01605, USA
| | | | | | - Rosemarie Terwilliger
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06520, USA
| | | | - Brie Wamsley
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
| | - Gaoyuan Wang
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Yan Xia
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Shaohua Xiao
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
| | - Andrew C Yang
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Suchen Zheng
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Michael J Gandal
- Interdepartmental Program in Bioinformatics, University of California, Los Angeles, Los Angeles CA, 90095, USA
- Department of Psychiatry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Donghoon Lee
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Ed S Lein
- Allen Institute for Brain Science, Seattle, WA 98109, USA
- Department of Neurological Surgery, University of Washington, Seattle, WA 98195, USA
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA 98195, USA
| | - Panos Roussos
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Mental Illness Research Education and Clinical Center, James J. Peters VA Medical Center, Bronx, NY 10468, USA
- Center for Precision Medicine and Translational Therapeutics, James J. Peters VA Medical Center, Bronx, NY 10468, USA
| | - Nenad Sestan
- Department of Neuroscience, Yale University, New Haven, CT 06510, USA
| | - Zhiping Weng
- Department of Genomics and Computational Biology, UMass Chan Medical School, Worcester, MA 01605, USA
| | - Kevin P White
- Yong Loo Lin School of Medicine, National University of Singapore, 117597 Singapore
| | - Hyejung Won
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Matthew J Girgenti
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06520, USA
- Wu Tsai Institute, Yale University, New Haven, CT 06520, USA
- Clinical Neuroscience Division, National Center for Posttraumatic Stress Disorder, Veterans Affairs Connecticut Healthcare System, West Haven, CT 06516, USA
| | - Jing Zhang
- Department of Computer Science, University of California, Irvine, CA 92697, USA
| | - Daifeng Wang
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI 53706, USA
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA
- Department of Computer Sciences, University of Wisconsin-Madison, Madison, WI 53706, USA
| | - Daniel Geschwind
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
- Center for Autism Research and Treatment, Semel Institute, University of California, Los Angeles, CA 90095, USA
- Department of Psychiatry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Institute for Precision Health, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
| | - Mark Gerstein
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
- Department of Computer Science, Yale University, New Haven, CT 06520, USA
- Department of Statistics and Data Science, Yale University, New Haven, CT 06520, USA
- Department of Biomedical Informatics & Data Science, Yale University, New Haven, CT 06520, USA
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You M, Fu M, Shen Z, Feng Y, Zhang L, Zhu X, Zhuang Z, Mao Y, Hua W. HIF2A mediates lineage transition to aggressive phenotype of cancer-associated fibroblasts in lung cancer brain metastasis. Oncoimmunology 2024; 13:2356942. [PMID: 38778816 PMCID: PMC11110709 DOI: 10.1080/2162402x.2024.2356942] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2024] [Accepted: 05/13/2024] [Indexed: 05/25/2024] Open
Abstract
Brain metastasis is the most devasting form of lung cancer. Recent studies highlight significant differences in the tumor microenvironment (TME) between lung cancer brain metastasis (LCBM) and primary lung cancer, which contribute significantly to tumor progression and drug resistance. Cancer-associated fibroblasts (CAFs) are the major component of pro-tumor TME with high plasticity. However, the lineage composition and function of CAFs in LCBM remain elusive. By reanalyzing single-cell RNA sequencing (scRNA-seq) data (GSE131907) from lung cancer patients with different stages of metastasis comprising primary lesions and brain metastasis, we found that CAFs undergo distinctive lineage transition during LCBM under a hypoxic situation, which is directly driven by hypoxia-induced HIF-2α activation. Transited CAFs enhance angiogenesis through VEGF pathways, trigger metabolic reprogramming, and promote the growth of tumor cells. Bulk RNA sequencing data was utilized as validation cohorts. Multiplex immunohistochemistry (mIHC) assay was performed on four paired samples of brain metastasis and their primary lung cancer counterparts to validate the findings. Our study revealed a novel mechanism of lung cancer brain metastasis featuring HIF-2α-induced lineage transition and functional alteration of CAFs, which offers potential therapeutic targets.
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Affiliation(s)
- Muyuan You
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
- National Center for Neurological Disorders, Shanghai, China
- Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai, China
- Neurosurgical Institute of Fudan University, Shanghai, China
- Shanghai Clinical Medical Center of Neurosurgery, Shanghai, China
| | - Minjie Fu
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
- National Center for Neurological Disorders, Shanghai, China
- Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai, China
- Neurosurgical Institute of Fudan University, Shanghai, China
- Shanghai Clinical Medical Center of Neurosurgery, Shanghai, China
| | - Zhewei Shen
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
- National Center for Neurological Disorders, Shanghai, China
- Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai, China
- Neurosurgical Institute of Fudan University, Shanghai, China
- Shanghai Clinical Medical Center of Neurosurgery, Shanghai, China
| | - Yuan Feng
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
- National Center for Neurological Disorders, Shanghai, China
- Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai, China
- Neurosurgical Institute of Fudan University, Shanghai, China
- Shanghai Clinical Medical Center of Neurosurgery, Shanghai, China
| | - Licheng Zhang
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
- National Center for Neurological Disorders, Shanghai, China
- Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai, China
- Neurosurgical Institute of Fudan University, Shanghai, China
- Shanghai Clinical Medical Center of Neurosurgery, Shanghai, China
| | - Xianmin Zhu
- Shanghai Institute for Advanced Immunochemical Studies, ShanghaiTech University, Shanghai, China
| | - Zhengping Zhuang
- Neuro-Oncology Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Ying Mao
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
- National Center for Neurological Disorders, Shanghai, China
- Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai, China
- Neurosurgical Institute of Fudan University, Shanghai, China
- Shanghai Clinical Medical Center of Neurosurgery, Shanghai, China
| | - Wei Hua
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
- National Center for Neurological Disorders, Shanghai, China
- Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai, China
- Neurosurgical Institute of Fudan University, Shanghai, China
- Shanghai Clinical Medical Center of Neurosurgery, Shanghai, China
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Yang B, Yang J, Zhang K. A cuproptosis-related signature predicts prognosis and indicates cross-talk with immunocyte in ovarian cancer. Discov Oncol 2024; 15:141. [PMID: 38696071 PMCID: PMC11065839 DOI: 10.1007/s12672-024-00981-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Accepted: 04/11/2024] [Indexed: 05/05/2024] Open
Abstract
PURPOSE Cuproptosis, programmed cell death by intracellular copper-mediated lipoylated protein aggregation, is involved in various tumorigenesis and drug resistance abilities by mediating the tumor microenvironment. Previous studies have demonstrated that serum copper levels are higher in OC patients than in normal subjects. However, the exact relationship between cuproptosis and ovarian cancer progression remains to be further elucidated. METHODS The Cancer Genome Atlas (TCGA) and gene expression omnibus (GEO) datasets were utilized to establish a cuproptosis-related prognostic signature in ovarian cancer. Subsequently, the bulk RNA-seq analysis and single-cell RNA-seq analysis were used to identify the relationship between signature with immune cell infiltration, chemotherapy, and cuproptosis-related scoring (CuRS) system. Finally, the potential biological functional roles of target genes in cuproptosis were validated in vitro. RESULTS By using LASSO-Cox regression analysis to establish the cuproptosis-related prognostic model, our works demonstrated the accuracy and efficiency of our model in the TCGA (583 OC patients) and GEO (260 OC patients) OC cohorts, and the high-scoring groups showed worse survival outcomes. Notably, there were substantial differences between the high and low-risk groups in extensive respects, such as the activating transcription factors, cell pseudotime features, cell intercommunication patterns, immunocytes infiltration, chemotherapy response, and potential drug resistance. KIF26B was selected to construct a prognostic model from the identified 33 prognosis-related genes, and high expression of KIF26B predicted poorer prognosis in ovarian cancer. Ultimately, further in vitro experiments demonstrated that KIF26B participated in the proliferation and cisplatin resistance of OC cells. Knockdown of KIF26B increased the sensitivity of OC cells to elesclomol, a cuproptosis agonists. CONCLUSION This study constructed a new cuproptosis-related gene signature that has a good prognostic capacity in assessing the outcome of OC patients. This study enhances our understanding of cuproptosis associated with ovarian cancer aggressiveness, cross-talk with immunocytes, and serves as a novel chemotherapy strategy.
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Affiliation(s)
- Bikang Yang
- Department of Gynecologic Oncology, Hunan Cancer Hospital, The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, 283 Tongzipo Road, Yuelu District, Changsha, 410013, Hunan, People's Republic of China
| | - Juan Yang
- Department of Gynecologic Oncology, Hunan Cancer Hospital, The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, 283 Tongzipo Road, Yuelu District, Changsha, 410013, Hunan, People's Republic of China
| | - Keqiang Zhang
- Department of Gynecologic Oncology, Hunan Cancer Hospital, The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, 283 Tongzipo Road, Yuelu District, Changsha, 410013, Hunan, People's Republic of China.
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Wang Y, Zhu Z, Luo R, Chen W. Single-cell transcriptome analysis reveals heterogeneity of neutrophils in non-small cell lung cancer. J Gene Med 2024; 26:e3690. [PMID: 38735760 DOI: 10.1002/jgm.3690] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2023] [Revised: 03/23/2024] [Accepted: 04/07/2024] [Indexed: 05/14/2024] Open
Abstract
BACKGROUND Lung cancer stands out as a highly perilous malignant tumor with severe implications for human health. There has been a growing interest in neutrophils as a result of their role in promoting cancer in recent years. Thus, the present study aimed to investigate the heterogeneity of neutrophils in non-small cell lung cancer (NSCLC). METHODS Single-cell RNA sequencing of tumor-associated neutrophils (TANs) and polymorphonuclear neutrophils sourced from the Gene Expression Omnibus database was analyzed. Moreover, cell-cell communication, differentiation trajectories and transcription factor analyses were performed. RESULTS Neutrophils were found to be closely associated with macrophages. Four major types of TANs were identified: a transitional subcluster that migrated from blood to tumor microenvironment (TAN-0), an inflammatory subcluster (TAN-1), a subpopulation that displayed a distinctive transcriptional signature (TAN-2) and a final differentiation state that promoted tumor formation (TAN-3). Meanwhile, TAN-3 displayed a marked increase in glycolytic activity. Finally, transcription factors were analyzed to uncover distinct TAN cluster-specific regulons. CONCLUSIONS The discovery of the dynamic characteristics of TANs in the present study is anticipated to contribute to yielding a better understanding of the tumor microenvironment and advancing the treatment of NSCLC.
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Affiliation(s)
- Yunzhen Wang
- Department of Thoracic Surgery, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Ziyi Zhu
- Department of Thoracic Surgery, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Raojun Luo
- Department of Thoracic Surgery, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Wenwen Chen
- Nursing Department, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
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Cao S, Zhao X, Li Z, Yu R, Li Y, Zhou X, Yan W, Chen D, He C. Comprehensive integration of single-cell transcriptomic data illuminates the regulatory network architecture of plant cell fate specification. PLANT DIVERSITY 2024; 46:372-385. [PMID: 38798726 PMCID: PMC11119547 DOI: 10.1016/j.pld.2024.03.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/27/2024] [Accepted: 03/29/2024] [Indexed: 05/29/2024]
Abstract
Plant morphogenesis relies on precise gene expression programs at the proper time and position which is orchestrated by transcription factors (TFs) in intricate regulatory networks in a cell-type specific manner. Here we introduced a comprehensive single-cell transcriptomic atlas of Arabidopsis seedlings. This atlas is the result of meticulous integration of 63 previously published scRNA-seq datasets, addressing batch effects and conserving biological variance. This integration spans a broad spectrum of tissues, including both below- and above-ground parts. Utilizing a rigorous approach for cell type annotation, we identified 47 distinct cell types or states, largely expanding our current view of plant cell compositions. We systematically constructed cell-type specific gene regulatory networks and uncovered key regulators that act in a coordinated manner to control cell-type specific gene expression. Taken together, our study not only offers extensive plant cell atlas exploration that serves as a valuable resource, but also provides molecular insights into gene-regulatory programs that varies from different cell types.
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Affiliation(s)
- Shanni Cao
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing 210023, China
| | - Xue Zhao
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing 210023, China
| | - Zhuojin Li
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing 210023, China
| | - Ranran Yu
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing 210023, China
| | - Yuqi Li
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China
| | - Xinkai Zhou
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing 210023, China
| | - Wenhao Yan
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China
| | - Dijun Chen
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing 210023, China
| | - Chao He
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China
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Qiu X, He H, Zeng H, Tong X, Zhang C, Liu Y, Liao Z, Liu Q. Integrative transcriptome analysis identifies MYBL2 as a poor prognosis marker for osteosarcoma and a pan-cancer marker of immune infiltration. Genes Dis 2024; 11:101004. [PMID: 38292182 PMCID: PMC10825309 DOI: 10.1016/j.gendis.2023.04.035] [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: 11/30/2022] [Revised: 03/23/2023] [Accepted: 04/29/2023] [Indexed: 02/01/2024] Open
Abstract
MYBL2 (MYB proto-oncogene like 2) is an emerging prognostic marker for malignant tumors, and its potential role in osteosarcoma and its relationship with immune infiltration in pan-cancer is yet to be elucidated. We constructed a transcription factor activity profile of osteosarcoma using the single-cell regulatory network inference algorithm based on single-cell RNA sequencing data obtained from the Gene Expression Omnibus. Subsequently, we calculated the extent of MYBL2 activation in malignant proliferative osteoblasts. We also explored the association between MYBL2 and chemotherapy resistance in osteosarcoma. Furthermore, we systematically correlated MYBL2 with immunological signatures in the tumor microenvironment in pan-cancer, including immune cell infiltration, immune checkpoints, and tumor immunotherapy prognosis. Finally, we developed and validated a risk score (MRGS), derived an osteosarcoma risk score nomogram based on MRGS, and tested its ability to predict prognosis. MYBL2 and gene enrichment analyses in osteosarcoma and pan-cancer revealed that MYBL2 was positively correlated with cell proliferation and tumor immune pathways. MYBL2 expression positively correlated with SLC19A1 in pan-cancer and osteosarcoma cell lines. Pan-cancer immune infiltration analysis revealed that MYBL2 was correlated with myeloid-derived suppressor cells, Th2 cell infiltration, CD276, RELT gene expression, and tumor mutation burden. In summary, MYBL2 regulates proliferation, progression, and immune infiltration in osteosarcoma and pan-cancer. Therefore, we found that MYBL2 could be used as a potential marker for predicting the osteosarcoma prognosis. Patients with osteosarcoma and high MYBL2 expression are theoretically more sensitive to methotrexate. An osteosarcoma prognostic nomogram can provide new ideas in the search for osteosarcoma prognostic markers.
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Affiliation(s)
- Xinzhu Qiu
- Department of Orthopaedics, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Changsha, Hunan 410008, China
- Department of Sports Medicine, Research Center of Sports Medicine, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Hongbo He
- Department of Orthopaedics, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Changsha, Hunan 410008, China
| | - Hao Zeng
- Department of Orthopaedics, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Changsha, Hunan 410008, China
| | - Xiaopeng Tong
- Department of Orthopaedics, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Changsha, Hunan 410008, China
- Department of Sports Medicine, Research Center of Sports Medicine, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Can Zhang
- Department of Orthopaedics, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Changsha, Hunan 410008, China
| | - Yupeng Liu
- Department of Orthopaedics, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Changsha, Hunan 410008, China
| | - Zhan Liao
- Department of Orthopaedics, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Changsha, Hunan 410008, China
| | - Qing Liu
- Department of Orthopaedics, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Changsha, Hunan 410008, China
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Wang W, Zheng S, Shin SC, Yuan GC. Characterizing Spatially Continuous Variations in Tissue Microenvironment through Niche Trajectory Analysis. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.23.590827. [PMID: 38712255 PMCID: PMC11071437 DOI: 10.1101/2024.04.23.590827] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 05/08/2024]
Abstract
Recent technological developments have made it possible to map the spatial organization of a tissue at the single-cell resolution. However, computational methods for analyzing spatially continuous variations in tissue microenvironment are still lacking. Here we present ONTraC as a strategy that constructs niche trajectories using a graph neural network-based modeling framework. Our benchmark analysis shows that ONTraC performs more favorably than existing methods for reconstructing spatial trajectories. Applications of ONTraC to public spatial transcriptomics datasets successfully recapitulated the underlying anatomical structure, and further enabled detection of tissue microenvironment-dependent changes in gene regulatory networks and cell-cell interaction activities during embryonic development. Taken together, ONTraC provides a useful and generally applicable tool for the systematic characterization of the structural and functional organization of tissue microenvironments.
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Affiliation(s)
- Wen Wang
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Shiwei Zheng
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Sujung Crystal Shin
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Guo-Cheng Yuan
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
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Ammons DT, Hopkins LS, Cronise KE, Kurihara J, Regan DP, Dow S. Single-cell RNA sequencing reveals the cellular and molecular heterogeneity of treatment-naïve primary osteosarcoma in dogs. Commun Biol 2024; 7:496. [PMID: 38658617 PMCID: PMC11043452 DOI: 10.1038/s42003-024-06182-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2023] [Accepted: 04/10/2024] [Indexed: 04/26/2024] Open
Abstract
Osteosarcoma (OS) is a heterogeneous, aggressive malignancy of the bone that disproportionally affects children and adolescents. Therapeutic interventions for OS are limited, which is in part due to the complex tumor microenvironment (TME). As such, we used single-cell RNA sequencing (scRNA-seq) to describe the cellular and molecular composition of the TME in 6 treatment-naïve dogs with spontaneously occurring primary OS. Through analysis of 35,310 cells, we identified 41 transcriptomically distinct cell types including the characterization of follicular helper T cells, mature regulatory dendritic cells (mregDCs), and 8 tumor-associated macrophage (TAM) populations. Cell-cell interaction analysis predicted that mregDCs and TAMs play key roles in modulating T cell mediated immunity. Furthermore, we completed cross-species cell type gene signature homology analysis and found a high degree of similarity between human and canine OS. The data presented here act as a roadmap of canine OS which can be applied to advance translational immuno-oncology research.
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Affiliation(s)
- Dylan T Ammons
- Department of Microbiology, Immunology, and Pathology, College of Veterinary Medicine and Biomedical Sciences, Colorado State University, Fort Collins, CO, USA.
| | - Leone S Hopkins
- Flint Animal Cancer Center, Department of Clinical Sciences, College of Veterinary Medicine and Biomedical Sciences, Colorado State University, Fort Collins, CO, USA
| | - Kathryn E Cronise
- Department of Microbiology, Immunology, and Pathology, College of Veterinary Medicine and Biomedical Sciences, Colorado State University, Fort Collins, CO, USA
| | - Jade Kurihara
- Flint Animal Cancer Center, Department of Clinical Sciences, College of Veterinary Medicine and Biomedical Sciences, Colorado State University, Fort Collins, CO, USA
| | - Daniel P Regan
- Department of Microbiology, Immunology, and Pathology, College of Veterinary Medicine and Biomedical Sciences, Colorado State University, Fort Collins, CO, USA
- Flint Animal Cancer Center, Department of Clinical Sciences, College of Veterinary Medicine and Biomedical Sciences, Colorado State University, Fort Collins, CO, USA
| | - Steven Dow
- Department of Microbiology, Immunology, and Pathology, College of Veterinary Medicine and Biomedical Sciences, Colorado State University, Fort Collins, CO, USA.
- Flint Animal Cancer Center, Department of Clinical Sciences, College of Veterinary Medicine and Biomedical Sciences, Colorado State University, Fort Collins, CO, USA.
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Xu X, Qiu F, Yang M, Liu X, Tao S, Zheng B. Unveiling Atherosclerotic Plaque Heterogeneity and SPP1 +/VCAN + Macrophage Subtype Prognostic Significance Through Integrative Single-Cell and Bulk-Seq Analysis. J Inflamm Res 2024; 17:2399-2426. [PMID: 38681071 PMCID: PMC11055562 DOI: 10.2147/jir.s454505] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2024] [Accepted: 04/09/2024] [Indexed: 05/01/2024] Open
Abstract
Background Dysregulated macrophages are important causes of Atherosclerosis (AS) formation and increased plaque instability, but the heterogeneity of these plaques and the role of macrophage subtypes in plaque instability have yet to be clarified. Methods This study integrates single-cell and bulk-seq data to analyze atherosclerotic plaques. Unsupervised clustering was used to reveal distinct plaque subtypes, while survival analysis and gene set variation analysis (GSVA) methods helped in understanding their clinical outcomes. Enrichment of differential expression of macrophage genes (DEMGs) score and pseudo-trajectory analysis were utilized to explore the biological functions and differentiation stages of macrophage subtypes in AS progression. Additionally, CellChat and the BayesPrism deconvolution method were used to elucidate macrophage subtype interaction and their prognostic significance at single-cell resolution. Finally, the expression of biomarkers was validated in mouse experiments. Results Three distinct AS plaque subtypes were identified, with cluster 3 plaque subtype being particularly associated with higher immune infiltration and poorer prognosis. The DEMGs score exhibited a significant elevation in three macrophage subtypes (SPP1+/VCAN+ macrophages, IL1B+ macrophages, and FLT3LG+ macrophages), associated with cluster 3 plaque subtype and highlighted the prognostic significance of these subtypes. Activation trajectory of the macrophage subtypes is divided into three states (Pre-branch, Cell fate 1, and Cell fate 2), and Cell fate 2 (SPP1+/VCAN+ macrophages, IL1B+ macrophages, and FLT3LG+ macrophages dominant) exhibiting the highest DEMGs score, distinct interactions with other cell components, and relating to poorer prognosis of ischemic events. This study also uncovered a unique SPP1+/VCAN+ macrophage subtype, rare in quantity but significant in influencing AS progression. Machine learning algorithms identified 10 biomarkers crucial for AS diagnosis. The validation of these biomarkers was performed using Mendelian Randomization analysis and in vitro methods, supporting their relevance in AS pathology. Conclusion Our study provides a comprehensive view of AS plaque heterogeneity and the prognostic significance of macrophage subtypes in plaque instability.
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Affiliation(s)
- Xiang Xu
- School of Medicine, Yunnan University, Kunming City, Yunnan Province, People’s Republic of China
- Department of Cardiology, The Second Affiliated Hospital of Kunming Medical University, Kunming City, Yunnan Province, People’s Republic of China
| | - Fuling Qiu
- Department of Cardiology, The Second Affiliated Hospital of Kunming Medical University, Kunming City, Yunnan Province, People’s Republic of China
| | - Man Yang
- School of Medicine, Dali University, Dali City, Yunnan Province, People’s Republic of China
| | - Xiaoyong Liu
- Department of Cardiology, The Second Affiliated Hospital of Kunming Medical University, Kunming City, Yunnan Province, People’s Republic of China
| | - Siming Tao
- Department of Cardiology, The Affiliated Hospital of Yunnan University, Kunming City, Yunnan Province, People’s Republic of China
| | - Bingrong Zheng
- School of Medicine, Yunnan University, Kunming City, Yunnan Province, People’s Republic of China
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Quan P, Li X, Si Y, Sun L, Ding FF, Fan Y, Liu H, Wei C, Li R, Zhao X, Yang F, Yao L. Single cell analysis reveals the roles and regulatory mechanisms of type-I interferons in Parkinson's disease. Cell Commun Signal 2024; 22:212. [PMID: 38566100 PMCID: PMC10985960 DOI: 10.1186/s12964-024-01590-1] [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: 01/25/2024] [Accepted: 03/23/2024] [Indexed: 04/04/2024] Open
Abstract
The pathogenesis of Parkinson's disease (PD) is strongly associated with neuroinflammation, and type I interferons (IFN-I) play a crucial role in regulating immune and inflammatory responses. However, the specific features of IFN in different cell types and the underlying mechanisms of PD have yet to be fully described. In this study, we analyzed the GSE157783 dataset, which includes 39,024 single-cell RNA sequencing results for five PD patients and six healthy controls from the Gene Expression Omnibus database. After cell type annotation, we intersected differentially expressed genes in each cell subcluster with genes collected in The Interferome database to generate an IFN-I-stimulated gene set (ISGs). Based on this gene set, we used the R package AUCell to score each cell, representing the IFN-I activity. Additionally, we performed monocle trajectory analysis, and single-cell regulatory network inference and clustering (SCENIC) to uncover the underlying mechanisms. In silico gene perturbation and subsequent experiments confirm NFATc2 regulation of type I interferon response and neuroinflammation. Our analysis revealed that microglia, endothelial cells, and pericytes exhibited the highest activity of IFN-I. Furthermore, single-cell trajectory detection demonstrated that microglia in the midbrain of PD patients were in a pro-inflammatory activation state, which was validated in the 1-Methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced PD mouse model as well. We identified transcription factors NFATc2, which was significantly up-regulated and involved in the expression of ISGs and activation of microglia in PD. In the 1-Methyl-4-phenylpyridinium (MPP+)-induced BV2 cell model, the suppression of NFATc2 resulted in a reduction in IFN-β levels, impeding the phosphorylation of STAT1, and attenuating the activation of the NF-κB pathway. Furthermore, the downregulation of NFATc2 mitigated the detrimental effects on SH-SY5Y cells co-cultured in conditioned medium. Our study highlights the critical role of microglia in type I interferon responses in PD. Additionally, we identified transcription factors NFATc2 as key regulators of aberrant type I interferon responses and microglial pro-inflammatory activation in PD. These findings provide new insights into the pathogenesis of PD and may have implications for the development of novel therapeutic strategies.
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Affiliation(s)
- Pusheng Quan
- Department of Neurology, The First Affiliated Hospital, Harbin Medical University, Harbin, China
- Department of Neurology, The Affiliated Hospital of Inner Mongolia Medical University, Hohhot, China
| | - Xueying Li
- Department of Neurology, The First Affiliated Hospital, Harbin Medical University, Harbin, China
| | - Yao Si
- Department of Neurology, The First Affiliated Hospital, Harbin Medical University, Harbin, China
| | - Linlin Sun
- Department of Neurology, The First Affiliated Hospital, Harbin Medical University, Harbin, China
| | - Fei Fan Ding
- Department of Neurology, The First Affiliated Hospital, Harbin Medical University, Harbin, China
| | - Yuwei Fan
- Department of Neurology, The First Affiliated Hospital, Harbin Medical University, Harbin, China
| | - Han Liu
- Department of Neurology, The First Affiliated Hospital, Harbin Medical University, Harbin, China
| | - Chengqun Wei
- Department of General Practice, Heilongjiang Provincial Hospital, Harbin, China
| | - Ruihua Li
- Department of Neurology, The First Affiliated Hospital, Harbin Medical University, Harbin, China
| | - Xue Zhao
- Department of Neurology, The First Affiliated Hospital, Harbin Medical University, Harbin, China
| | - Fan Yang
- Department of Neurology, The First Affiliated Hospital, Harbin Medical University, Harbin, China.
| | - Lifen Yao
- Department of Neurology, The First Affiliated Hospital, Harbin Medical University, Harbin, China.
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Zou G, Huang Y, Zhang S, Ko KP, Kim B, Zhang J, Venkatesan V, Pizzi MP, Fan Y, Jun S, Niu N, Wang H, Song S, Ajani JA, Park JI. E-cadherin loss drives diffuse-type gastric tumorigenesis via EZH2-mediated reprogramming. J Exp Med 2024; 221:e20230561. [PMID: 38411616 PMCID: PMC10899090 DOI: 10.1084/jem.20230561] [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: 04/03/2023] [Revised: 09/27/2023] [Accepted: 01/29/2024] [Indexed: 02/28/2024] Open
Abstract
Diffuse-type gastric adenocarcinoma (DGAC) is a deadly cancer often diagnosed late and resistant to treatment. While hereditary DGAC is linked to CDH1 mutations, the role of CDH1/E-cadherin inactivation in sporadic DGAC tumorigenesis remains elusive. We discovered CDH1 inactivation in a subset of DGAC patient tumors. Analyzing single-cell transcriptomes in malignant ascites, we identified two DGAC subtypes: DGAC1 (CDH1 loss) and DGAC2 (lacking immune response). DGAC1 displayed distinct molecular signatures, activated DGAC-related pathways, and an abundance of exhausted T cells in ascites. Genetically engineered murine gastric organoids showed that Cdh1 knock-out (KO), KrasG12D, Trp53 KO (EKP) accelerates tumorigenesis with immune evasion compared with KrasG12D, Trp53 KO (KP). We also identified EZH2 as a key mediator promoting CDH1 loss-associated DGAC tumorigenesis. These findings highlight DGAC's molecular diversity and potential for personalized treatment in CDH1-inactivated patients.
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Affiliation(s)
- Gengyi Zou
- Division of Radiation Oncology, Department of Experimental Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Yuanjian Huang
- Division of Radiation Oncology, Department of Experimental Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
- Department of General Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Shengzhe Zhang
- Division of Radiation Oncology, Department of Experimental Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Kyung-Pil Ko
- Division of Radiation Oncology, Department of Experimental Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Bongjun Kim
- Division of Radiation Oncology, Department of Experimental Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Jie Zhang
- Division of Radiation Oncology, Department of Experimental Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Vishwa Venkatesan
- Division of Radiation Oncology, Department of Experimental Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Melissa P. Pizzi
- Department of GI Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Yibo Fan
- Department of GI Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Sohee Jun
- Division of Radiation Oncology, Department of Experimental Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Na Niu
- Department of Pathology, Yale School of Medicine, New Haven, CT, USA
| | - Huamin Wang
- Division of Pathology/Lab Medicine, Department of Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Shumei Song
- Department of GI Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Jaffer A. Ajani
- Department of GI Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Jae-Il Park
- Division of Radiation Oncology, Department of Experimental Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
- Graduate School of Biomedical Sciences, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
- Program in Genetics and Epigenetics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
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65
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Emani PS, Liu JJ, Clarke D, Jensen M, Warrell J, Gupta C, Meng R, Lee CY, Xu S, Dursun C, Lou S, Chen Y, Chu Z, Galeev T, Hwang A, Li Y, Ni P, Zhou X, Bakken TE, Bendl J, Bicks L, Chatterjee T, Cheng L, Cheng Y, Dai Y, Duan Z, Flaherty M, Fullard JF, Gancz M, Garrido-Martín D, Gaynor-Gillett S, Grundman J, Hawken N, Henry E, Hoffman GE, Huang A, Jiang Y, Jin T, Jorstad NL, Kawaguchi R, Khullar S, Liu J, Liu J, Liu S, Ma S, Margolis M, Mazariegos S, Moore J, Moran JR, Nguyen E, Phalke N, Pjanic M, Pratt H, Quintero D, Rajagopalan AS, Riesenmy TR, Shedd N, Shi M, Spector M, Terwilliger R, Travaglini KJ, Wamsley B, Wang G, Xia Y, Xiao S, Yang AC, Zheng S, Gandal MJ, Lee D, Lein ES, Roussos P, Sestan N, Weng Z, White KP, Won H, Girgenti MJ, Zhang J, Wang D, Geschwind D, Gerstein M. Single-cell genomics and regulatory networks for 388 human brains. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.18.585576. [PMID: 38562822 PMCID: PMC10983939 DOI: 10.1101/2024.03.18.585576] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
Single-cell genomics is a powerful tool for studying heterogeneous tissues such as the brain. Yet, little is understood about how genetic variants influence cell-level gene expression. Addressing this, we uniformly processed single-nuclei, multi-omics datasets into a resource comprising >2.8M nuclei from the prefrontal cortex across 388 individuals. For 28 cell types, we assessed population-level variation in expression and chromatin across gene families and drug targets. We identified >550K cell-type-specific regulatory elements and >1.4M single-cell expression-quantitative-trait loci, which we used to build cell-type regulatory and cell-to-cell communication networks. These networks manifest cellular changes in aging and neuropsychiatric disorders. We further constructed an integrative model accurately imputing single-cell expression and simulating perturbations; the model prioritized ~250 disease-risk genes and drug targets with associated cell types.
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Affiliation(s)
- Prashant S Emani
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Jason J Liu
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Declan Clarke
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Matthew Jensen
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Jonathan Warrell
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Chirag Gupta
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI, 53706, USA
- Waisman Center, University of Wisconsin-Madison, Madison, WI, 53705, USA
| | - Ran Meng
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Che Yu Lee
- Department of Computer Science, University of California, Irvine, CA, 92697, USA
| | - Siwei Xu
- Department of Computer Science, University of California, Irvine, CA, 92697, USA
| | - Cagatay Dursun
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Shaoke Lou
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Yuhang Chen
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Zhiyuan Chu
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
| | - Timur Galeev
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Ahyeon Hwang
- Department of Computer Science, University of California, Irvine, CA, 92697, USA
- Mathematical, Computational and Systems Biology, University of California, Irvine, CA, 92697, USA
| | - Yunyang Li
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
- Department of Computer Science, Yale University, New Haven, CT, 06520, USA
| | - Pengyu Ni
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Xiao Zhou
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | | | - Jaroslav Bendl
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Lucy Bicks
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
| | - Tanima Chatterjee
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | | | - Yuyan Cheng
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
- Department of Opthalmology, Perlman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Yi Dai
- Department of Computer Science, University of California, Irvine, CA, 92697, USA
| | - Ziheng Duan
- Department of Computer Science, University of California, Irvine, CA, 92697, USA
| | | | - John F Fullard
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Michael Gancz
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Diego Garrido-Martín
- Department of Genetics, Microbiology and Statistics, Universitat de Barcelona, Barcelona, 08028, Spain
| | - Sophia Gaynor-Gillett
- Tempus Labs, Inc., Chicago, IL, 60654, USA
- Department of Biology, Cornell College, Mount Vernon, IA, 52314, USA
| | - Jennifer Grundman
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
| | - Natalie Hawken
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
| | - Ella Henry
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Gabriel E Hoffman
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Mental Illness Research Education and Clinical Center, James J. Peters VA Medical Center, Bronx, NY, 10468, USA
- Center for Precision Medicine and Translational Therapeutics, James J. Peters VA Medical Center, Bronx, NY, 10468, USA
| | - Ao Huang
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
| | - Yunzhe Jiang
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Ting Jin
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI, 53706, USA
- Waisman Center, University of Wisconsin-Madison, Madison, WI, 53705, USA
| | | | - Riki Kawaguchi
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
- Center for Autism Research and Treatment, Semel Institute, University of California, Los Angeles, CA, 90095, USA
| | - Saniya Khullar
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI, 53706, USA
- Waisman Center, University of Wisconsin-Madison, Madison, WI, 53705, USA
| | - Jianyin Liu
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
| | - Junhao Liu
- Department of Computer Science, University of California, Irvine, CA, 92697, USA
| | - Shuang Liu
- Waisman Center, University of Wisconsin-Madison, Madison, WI, 53705, USA
| | - Shaojie Ma
- Department of Neuroscience, Yale University, New Haven, CT, 06510, USA
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Michael Margolis
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
| | - Samantha Mazariegos
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
| | - Jill Moore
- Department of Genomics and Computational Biology, UMass Chan Medical School, Worcester, MA, 01605, USA
| | | | - Eric Nguyen
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Nishigandha Phalke
- Department of Genomics and Computational Biology, UMass Chan Medical School, Worcester, MA, 01605, USA
| | - Milos Pjanic
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Henry Pratt
- Department of Genomics and Computational Biology, UMass Chan Medical School, Worcester, MA, 01605, USA
| | - Diana Quintero
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
| | | | - Tiernon R Riesenmy
- Department of Statistics & Data Science, Yale University, New Haven, CT, 06520, USA
| | - Nicole Shedd
- Department of Genomics and Computational Biology, UMass Chan Medical School, Worcester, MA, 01605, USA
| | - Manman Shi
- Tempus Labs, Inc., Chicago, IL, 60654, USA
| | | | - Rosemarie Terwilliger
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, 06520, USA
| | | | - Brie Wamsley
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
| | - Gaoyuan Wang
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Yan Xia
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Shaohua Xiao
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
| | - Andrew C Yang
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Suchen Zheng
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Michael J Gandal
- Interdepartmental Program in Bioinformatics, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Department of Psychiatry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Lifespan Brain Institute, The Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Donghoon Lee
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Ed S Lein
- Allen Institute for Brain Science, Seattle, WA, 98109, USA
- Department of Neurological Surgery, University of Washington, Seattle, WA, 98195, USA
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, 98195, USA
| | - Panos Roussos
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Mental Illness Research Education and Clinical Center, James J. Peters VA Medical Center, Bronx, NY, 10468, USA
- Center for Precision Medicine and Translational Therapeutics, James J. Peters VA Medical Center, Bronx, NY, 10468, USA
| | - Nenad Sestan
- Department of Neuroscience, Yale University, New Haven, CT, 06510, USA
| | - Zhiping Weng
- Department of Genomics and Computational Biology, UMass Chan Medical School, Worcester, MA, 01605, USA
| | - Kevin P White
- Yong Loo Lin School of Medicine, National University of Singapore, 117597, Singapore
| | - Hyejung Won
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Matthew J Girgenti
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, 06520, USA
- Wu Tsai Institute, Yale University, New Haven, CT, 06520, USA
- Clinical Neuroscience Division, National Center for Posttraumatic Stress Disorder, Veterans Affairs Connecticut Healthcare System, West Haven, CT, 06516, USA
| | - Jing Zhang
- Department of Computer Science, University of California, Irvine, CA, 92697, USA
| | - Daifeng Wang
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI, 53706, USA
- Waisman Center, University of Wisconsin-Madison, Madison, WI, 53705, USA
- Department of Computer Sciences, University of Wisconsin-Madison, Madison, WI, 53706, USA
| | - Daniel Geschwind
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
- Center for Autism Research and Treatment, Semel Institute, University of California, Los Angeles, CA, 90095, USA
- Department of Psychiatry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Institute for Precision Health, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
| | - Mark Gerstein
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
- Department of Computer Science, Yale University, New Haven, CT, 06520, USA
- Department of Statistics & Data Science, Yale University, New Haven, CT, 06520, USA
- Department of Biomedical Informatics & Data Science, Yale University, New Haven, CT, 06520, USA
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Tsagiopoulou M, Rashmi S, Aguilar-Fernandez S, Nieto J, Gut IG. Multi-organ single-cell transcriptomics of immune cells uncovered organ-specific gene expression and functions. Sci Data 2024; 11:316. [PMID: 38538617 PMCID: PMC10973478 DOI: 10.1038/s41597-024-03152-z] [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: 06/27/2023] [Accepted: 03/18/2024] [Indexed: 04/01/2024] Open
Abstract
Despite the wealth of publicly available single-cell datasets, our understanding of distinct resident immune cells and their unique features in diverse human organs remains limited. To address this, we compiled a meta-analysis dataset of 114,275 CD45+ immune cells sourced from 14 organs in healthy donors. While the transcriptome of immune cells remains relatively consistent across organs, our analysis has unveiled organ-specific gene expression differences (GTPX3 in kidney, DNTT and ACVR2B in thymus). These alterations are linked to different transcriptional factor activities and pathways including metabolism. TNF-α signaling through the NFkB pathway was found in several organs and immune compartments. The presence of distinct expression profiles for NFkB family genes and their target genes, including cytokines, underscores their pivotal role in cell positioning. Taken together, immune cells serve a dual role: safeguarding the organs and dynamically adjusting to the intricacies of the host organ environment, thereby actively contributing to its functionality and overall homeostasis.
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Affiliation(s)
| | - Sonal Rashmi
- Centro Nacional de Analisis Genomico (CNAG), Barcelona, Spain
| | | | - Juan Nieto
- Centro Nacional de Analisis Genomico (CNAG), Barcelona, Spain
| | - Ivo G Gut
- Centro Nacional de Analisis Genomico (CNAG), Barcelona, Spain.
- Universitat de Barcelona (UB), Barcelona, Spain.
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67
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Cao C, Wu R, Wang S, Zhuang L, Chen P, Li S, Zhu Q, Li H, Lin Y, Li M, Cao L, Chen J. Elucidating the changes in the heterogeneity and function of radiation-induced cardiac macrophages using single-cell RNA sequencing. Front Immunol 2024; 15:1363278. [PMID: 38601160 PMCID: PMC11004337 DOI: 10.3389/fimmu.2024.1363278] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2023] [Accepted: 03/08/2024] [Indexed: 04/12/2024] Open
Abstract
Purpose A mouse model of irradiation (IR)-induced heart injury was established to investigate the early changes in cardiac function after radiation and the role of cardiac macrophages in this process. Methods Cardiac function was evaluated by heart-to-tibia ratio, lung-to-heart ratio and echocardiography. Immunofluorescence staining and flow cytometry analysis were used to evaluate the changes of macrophages in the heart. Immune cells from heart tissues were sorted by magnetic beads for single-cell RNA sequencing, and the subsets of macrophages were identified and analyzed. Trajectory analysis was used to explore the differentiation relationship of each macrophage subset. The differentially expressed genes (DEGs) were compared, and the related enriched pathways were identified. Single-cell regulatory network inference and clustering (SCENIC) analysis was performed to identify the potential transcription factors (TFs) which participated in this process. Results Cardiac function temporarily decreased on Day 7 and returned to normal level on Day 35, accompanied by macrophages decreased and increased respectively. Then, we identified 7 clusters of macrophages by single-cell RNA sequencing and found two kinds of stage specific macrophages: senescence-associated macrophage (Cdkn1ahighC5ar1high) on Day 7 and interferon-associated macrophage (Ccr2highIsg15high) on Day 35. Moreover, we observed cardiac macrophages polarized over these two-time points based on M1/M2 and CCR2/major histocompatibility complex II (MHCII) expression. Finally, Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses suggested that macrophages on Day 7 were characterized by an inflammatory senescent phenotype with enhanced chemotaxis and inflammatory factors, while macrophages on Day 35 showed enhanced phagocytosis with reduced inflammation, which was associated with interferon-related pathways. SCENIC analysis showed AP-1 family members were associated with IR-induced macrophages changes. Conclusion We are the first study to characterize the diversity, features, and evolution of macrophages during the early stages in an IR-induced cardiac injury animal model.
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Affiliation(s)
- Chunxiang Cao
- Department of Radiation Oncology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai Key Laboratory of Proton-therapy, Shanghai, China
| | - Ran Wu
- Department of Radiation Oncology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai Key Laboratory of Proton-therapy, Shanghai, China
| | - Shubei Wang
- Department of Radiation Oncology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai Key Laboratory of Proton-therapy, Shanghai, China
| | - Lingfang Zhuang
- Department of Cardiovascular Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Peizhan Chen
- Clinical Research Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Shuyan Li
- Department of Radiation Oncology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai Key Laboratory of Proton-therapy, Shanghai, China
| | - Qian Zhu
- Department of Radiation Oncology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai Key Laboratory of Proton-therapy, Shanghai, China
| | - Huan Li
- Department of Radiation Oncology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai Key Laboratory of Proton-therapy, Shanghai, China
| | - Yingying Lin
- Department of Radiation Oncology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai Key Laboratory of Proton-therapy, Shanghai, China
| | - Min Li
- Department of Radiation Oncology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai Key Laboratory of Proton-therapy, Shanghai, China
| | - Lu Cao
- Department of Radiation Oncology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai Key Laboratory of Proton-therapy, Shanghai, China
| | - Jiayi Chen
- Department of Radiation Oncology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai Key Laboratory of Proton-therapy, Shanghai, China
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Dufour A, Kurylo C, Stöckl JB, Laloë D, Bailly Y, Manceau P, Martins F, Turhan AG, Ferchaud S, Pain B, Fröhlich T, Foissac S, Artus J, Acloque H. Cell specification and functional interactions in the pig blastocyst inferred from single-cell transcriptomics and uterine fluids proteomics. Genomics 2024; 116:110780. [PMID: 38211822 DOI: 10.1016/j.ygeno.2023.110780] [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: 06/29/2023] [Revised: 12/08/2023] [Accepted: 12/30/2023] [Indexed: 01/13/2024]
Abstract
The embryonic development of the pig comprises a long in utero pre- and peri-implantation development, which dramatically differs from mice and humans. During this peri-implantation period, a complex series of paracrine signals establishes an intimate dialogue between the embryo and the uterus. To better understand the biology of the pig blastocyst during this period, we generated a large dataset of single-cell RNAseq from early and hatched blastocysts, spheroid and ovoid conceptus and proteomic datasets from corresponding uterine fluids. Our results confirm the molecular specificity and functionality of the three main cell populations. We also discovered two previously unknown subpopulations of the trophectoderm, one characterised by the expression of LRP2, which could represent progenitor cells, and the other, expressing pro-apoptotic markers, which could correspond to the Rauber's layer. Our work provides new insights into the biology of these populations, their reciprocal functional interactions, and the molecular dialogue with the maternal uterine environment.
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Affiliation(s)
- Adrien Dufour
- Université Paris Saclay, INRAE, AgroParisTech, GABI, Domaine de Vilvert, 78350 Jouy en Josas, France
| | - Cyril Kurylo
- Université de Toulouse, INRAE, ENVT, GenPhySE, Chemin de Borde Rouge, 31326 Castanet-Tolosan, France
| | - Jan B Stöckl
- Ludwig-Maximilians-Universität München, Genzentrum, Feodor-Lynen-Str. 25, 81377 München, Germany
| | - Denis Laloë
- Université Paris Saclay, INRAE, AgroParisTech, GABI, Domaine de Vilvert, 78350 Jouy en Josas, France
| | - Yoann Bailly
- INRAE, GenESI, La Gouvanière, 86480 Rouillé, France
| | | | - Frédéric Martins
- Plateforme Genome et Transcriptome (GeT-Santé), GenoToul, Toulouse University, CNRS, INRAE, INSA, Toulouse, France; I2MC - Institut des Maladies Métaboliques et Cardiovasculaires, Inserm, Université de Toulouse, Université Paul Sabatier, Toulouse, France
| | - Ali G Turhan
- Université Paris Saclay, Inserm, UMRS1310, 7 rue Guy Moquet, 94800 Villejuif, France
| | | | - Bertrand Pain
- Université de Lyon, Inserm, INRAE, SBRI, 18 Av. du Doyen Jean Lépine, 69500 Bron, France
| | - Thomas Fröhlich
- Ludwig-Maximilians-Universität München, Genzentrum, Feodor-Lynen-Str. 25, 81377 München, Germany
| | - Sylvain Foissac
- Université de Toulouse, INRAE, ENVT, GenPhySE, Chemin de Borde Rouge, 31326 Castanet-Tolosan, France
| | - Jérôme Artus
- Université Paris Saclay, Inserm, UMRS1310, 7 rue Guy Moquet, 94800 Villejuif, France
| | - Hervé Acloque
- Université Paris Saclay, INRAE, AgroParisTech, GABI, Domaine de Vilvert, 78350 Jouy en Josas, France.
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Zhang F, Ge Q, Meng J, Chen J, Liang C, Zhang M. Characterizing CD8+ TEMRA Cells in CP/CPPS Patients: Insights from Targeted Single-Cell Transcriptomic and Functional Investigations. Immunotargets Ther 2024; 13:111-121. [PMID: 38435982 PMCID: PMC10906729 DOI: 10.2147/itt.s451199] [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: 11/22/2023] [Accepted: 02/17/2024] [Indexed: 03/05/2024] Open
Abstract
Background The specific involvement of the CD8+ T effector memory RA (TEMRA) subset in patients with chronic prostatitis/chronic pelvic pain syndrome (CP/CPPS) has largely not been explored in the literature. Methods Targeted single-cell RNA sequencing (scRNA-seq) profiles were generated from peripheral blood mononuclear cells (PBMCs) obtained from two CP/CPPS patients and two healthy controls (HCs) in our recent study. Pseudotime series algorithms were used to reveal the differentiation trajectory, CellChat analysis was used to explore the communication between individual cells, and the SCENIC program was used to identify potential transcription factors (TFs). Based on the cosine similarity, clusters of differentially expressed genes (DEGs) were considered to be further enriched in different pathways. To confirm the functional role of the critical clusters, flow cytometry was employed. Results The results revealed the molecular landscape of these clusters, with TEMRA cells exhibiting pronounced cytokine-mediated signaling pathway enrichment. Pseudotime trajectory analysis further mapped the evolution from naïve T cells to that of TEMRA cells, elucidating the developmental pathways involved in the immune context. A significant finding from CellChat analysis was the differential expression of ligands and receptors, with CD8+ TEMRA cells showing enhanced signaling, particularly in the CP/CPPS context, compared to HCs. Flow cytometry confirmed these results, revealing a heightened proinflammatory cytokine profile in patients with chronic prostatitis-like symptoms (CP-LS), suggesting that TEMRA cells play a significant role in disease pathogenesis. TF profiling across the T-cell clusters identified key regulators of cellular identity, identifying novel therapeutic targets. Elevated TNF signaling activity in CD8+ TEMRA cells underscored the involvement of these cells in disease mechanisms. Conclusion This study elucidates the pivotal role of the CD8+ TEMRA cell subset in CP/CPPS, which is characterized by increased TNF signaling and proinflammatory factor expression, highlighting potential biomarkers and opening new avenues for therapeutic intervention.
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Affiliation(s)
- Fei Zhang
- Department of Urology, The First Affiliated Hospital of Anhui Medical University; Institute of Urology, Anhui Medical University; Anhui Province Key Laboratory of Urological and Andrological Diseases Research and Medical Transformation, Anhui Medical University, Hefei, 230022, People's Republic of China
| | - Qintao Ge
- Department of Urology, The First Affiliated Hospital of Anhui Medical University; Institute of Urology, Anhui Medical University; Anhui Province Key Laboratory of Urological and Andrological Diseases Research and Medical Transformation, Anhui Medical University, Hefei, 230022, People's Republic of China
| | - Jialin Meng
- Department of Urology, The First Affiliated Hospital of Anhui Medical University; Institute of Urology, Anhui Medical University; Anhui Province Key Laboratory of Urological and Andrological Diseases Research and Medical Transformation, Anhui Medical University, Hefei, 230022, People's Republic of China
| | - Jia Chen
- Department of Urology, The First Affiliated Hospital of Anhui Medical University; Institute of Urology, Anhui Medical University; Anhui Province Key Laboratory of Urological and Andrological Diseases Research and Medical Transformation, Anhui Medical University, Hefei, 230022, People's Republic of China
| | - Chaozhao Liang
- Department of Urology, The First Affiliated Hospital of Anhui Medical University; Institute of Urology, Anhui Medical University; Anhui Province Key Laboratory of Urological and Andrological Diseases Research and Medical Transformation, Anhui Medical University, Hefei, 230022, People's Republic of China
| | - Meng Zhang
- Department of Urology, The First Affiliated Hospital of Anhui Medical University; Institute of Urology, Anhui Medical University; Anhui Province Key Laboratory of Urological and Andrological Diseases Research and Medical Transformation, Anhui Medical University, Hefei, 230022, People's Republic of China
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Massoni-Badosa R, Aguilar-Fernández S, Nieto JC, Soler-Vila P, Elosua-Bayes M, Marchese D, Kulis M, Vilas-Zornoza A, Bühler MM, Rashmi S, Alsinet C, Caratù G, Moutinho C, Ruiz S, Lorden P, Lunazzi G, Colomer D, Frigola G, Blevins W, Romero-Rivero L, Jiménez-Martínez V, Vidal A, Mateos-Jaimez J, Maiques-Diaz A, Ovejero S, Moreaux J, Palomino S, Gomez-Cabrero D, Agirre X, Weniger MA, King HW, Garner LC, Marini F, Cervera-Paz FJ, Baptista PM, Vilaseca I, Rosales C, Ruiz-Gaspà S, Talks B, Sidhpura K, Pascual-Reguant A, Hauser AE, Haniffa M, Prosper F, Küppers R, Gut IG, Campo E, Martin-Subero JI, Heyn H. An atlas of cells in the human tonsil. Immunity 2024; 57:379-399.e18. [PMID: 38301653 PMCID: PMC10869140 DOI: 10.1016/j.immuni.2024.01.006] [Citation(s) in RCA: 29] [Impact Index Per Article: 29.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Revised: 07/07/2023] [Accepted: 01/09/2024] [Indexed: 02/03/2024]
Abstract
Palatine tonsils are secondary lymphoid organs (SLOs) representing the first line of immunological defense against inhaled or ingested pathogens. We generated an atlas of the human tonsil composed of >556,000 cells profiled across five different data modalities, including single-cell transcriptome, epigenome, proteome, and immune repertoire sequencing, as well as spatial transcriptomics. This census identified 121 cell types and states, defined developmental trajectories, and enabled an understanding of the functional units of the tonsil. Exemplarily, we stratified myeloid slan-like subtypes, established a BCL6 enhancer as locally active in follicle-associated T and B cells, and identified SIX5 as putative transcriptional regulator of plasma cell maturation. Analyses of a validation cohort confirmed the presence, annotation, and markers of tonsillar cell types and provided evidence of age-related compositional shifts. We demonstrate the value of this resource by annotating cells from B cell-derived mantle cell lymphomas, linking transcriptional heterogeneity to normal B cell differentiation states of the human tonsil.
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Affiliation(s)
| | | | - Juan C Nieto
- Centro Nacional de Análisis Genómico (CNAG), Barcelona, Spain
| | - Paula Soler-Vila
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | | | | | - Marta Kulis
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Amaia Vilas-Zornoza
- Hemato-Oncology Program, Center for Applied Medical Research (CIMA), University of Navarra, IDISNA, Universidad de Navarra, Pamplona, Spain; Centro de Investigación Biomédica en Red Cáncer (CIBERONC), Madrid, Spain
| | - Marco Matteo Bühler
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Department of Pathology and Molecular Pathology, University Hospital Zurich, Zurich, Switzerland; Hematopathology Section, Pathology Department, Hospital Clinic, Barcelona, Spain
| | - Sonal Rashmi
- Centro Nacional de Análisis Genómico (CNAG), Barcelona, Spain
| | - Clara Alsinet
- Centro Nacional de Análisis Genómico (CNAG), Barcelona, Spain
| | - Ginevra Caratù
- Centro Nacional de Análisis Genómico (CNAG), Barcelona, Spain
| | - Catia Moutinho
- Centro Nacional de Análisis Genómico (CNAG), Barcelona, Spain
| | - Sara Ruiz
- Centro Nacional de Análisis Genómico (CNAG), Barcelona, Spain
| | - Patricia Lorden
- Centro Nacional de Análisis Genómico (CNAG), Barcelona, Spain
| | - Giulia Lunazzi
- Centro Nacional de Análisis Genómico (CNAG), Barcelona, Spain
| | - Dolors Colomer
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Centro de Investigación Biomédica en Red Cáncer (CIBERONC), Madrid, Spain; Hematopathology Section, Pathology Department, Hospital Clinic, Barcelona, Spain; Departament de Fonaments Clínics, Facultat de Medicina, Universitat de Barcelona, Barcelona, Spain
| | - Gerard Frigola
- Hematopathology Section, Pathology Department, Hospital Clinic, Barcelona, Spain
| | - Will Blevins
- Centro Nacional de Análisis Genómico (CNAG), Barcelona, Spain
| | - Lucia Romero-Rivero
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | | | - Anna Vidal
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Judith Mateos-Jaimez
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Alba Maiques-Diaz
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Sara Ovejero
- Department of Biological Hematology, CHU Montpellier, Montpellier, France; Institute of Human Genetics, UMR 9002 CNRS-UM, Montpellier, France
| | - Jérôme Moreaux
- Department of Biological Hematology, CHU Montpellier, Montpellier, France; Institute of Human Genetics, UMR 9002 CNRS-UM, Montpellier, France; Department of Clinical Hematology, CHU Montpellier, Montpellier, France
| | - Sara Palomino
- Translational Bioinformatics Unit (TransBio), Navarrabiomed, Navarra Health Department (CHN), Public University of Navarra (UPNA), Navarra Institute for Health Research (IdiSNA), Pamplona, Spain
| | - David Gomez-Cabrero
- Translational Bioinformatics Unit (TransBio), Navarrabiomed, Navarra Health Department (CHN), Public University of Navarra (UPNA), Navarra Institute for Health Research (IdiSNA), Pamplona, Spain; Bioscience Program, Biological and Environmental Sciences and Engineering Division (BESE), King Abdullah University of Science and Technology KAUST, Thuwal, Saudi Arabia
| | - Xabier Agirre
- Hemato-Oncology Program, Center for Applied Medical Research (CIMA), University of Navarra, IDISNA, Universidad de Navarra, Pamplona, Spain; Centro de Investigación Biomédica en Red Cáncer (CIBERONC), Madrid, Spain
| | - Marc A Weniger
- Institute of Cell Biology (Cancer Research), Medical Faculty, University of Duisburg-Essen, Essen, Germany
| | - Hamish W King
- Epigenetics and Development Division, Walter and Eliza Hall Institute, Parkville, Australia
| | - Lucy C Garner
- Translational Gastroenterology Unit, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Federico Marini
- Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany; Center for Thrombosis and Hemostasis (CTH), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | | | - Peter M Baptista
- Department of Otorhinolaryngology, University of Navarra, Pamplona, Spain
| | - Isabel Vilaseca
- Otorhinolaryngology Head-Neck Surgery Department, Hospital Clínic, IDIBAPS Universitat de Barcelona, Barcelona, Spain
| | - Cecilia Rosales
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Silvia Ruiz-Gaspà
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Benjamin Talks
- Biosciences Institute, Newcastle University, Newcastle Upon Tyne, UK; Department of Otolaryngology, Freeman Hospital, Newcastle Hospitals NHS Foundation Trust, Newcastle Upon Tyne, UK
| | - Keval Sidhpura
- Biosciences Institute, Newcastle University, Newcastle Upon Tyne, UK
| | - Anna Pascual-Reguant
- Department of Rheumatology and Clinical Immunology, Charité - Universitätsmedizin Berlin, Berlin, Germany; Immune Dynamics, Deutsches Rheuma-Forschungszentrum (DRFZ), Berlin, Germany
| | - Anja E Hauser
- Department of Rheumatology and Clinical Immunology, Charité - Universitätsmedizin Berlin, Berlin, Germany; Immune Dynamics, Deutsches Rheuma-Forschungszentrum (DRFZ), Berlin, Germany
| | - Muzlifah Haniffa
- Biosciences Institute, Newcastle University, Newcastle Upon Tyne, UK; Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, UK; Department of Dermatology and NIHR Newcastle Biomedical Research Centre, Newcastle Hospitals NHS Foundation Trust, Newcastle Upon Tyne, UK
| | - Felipe Prosper
- Hemato-Oncology Program, Center for Applied Medical Research (CIMA), University of Navarra, IDISNA, Universidad de Navarra, Pamplona, Spain; Centro de Investigación Biomédica en Red Cáncer (CIBERONC), Madrid, Spain; Departamento de Hematología, Clínica Universidad de Navarra, University of Navarra, Pamplona, Spain
| | - Ralf Küppers
- Institute of Cell Biology (Cancer Research), Medical Faculty, University of Duisburg-Essen, Essen, Germany
| | - Ivo Glynne Gut
- Centro Nacional de Análisis Genómico (CNAG), Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Elias Campo
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Centro de Investigación Biomédica en Red Cáncer (CIBERONC), Madrid, Spain; Hematopathology Section, Pathology Department, Hospital Clinic, Barcelona, Spain; Departament de Fonaments Clínics, Facultat de Medicina, Universitat de Barcelona, Barcelona, Spain
| | - José Ignacio Martin-Subero
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Departament de Fonaments Clínics, Facultat de Medicina, Universitat de Barcelona, Barcelona, Spain; Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain.
| | - Holger Heyn
- Centro Nacional de Análisis Genómico (CNAG), Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain.
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Han P, Zhang W, Wang D, Wu Y, Li X, Zhao S, Zhu M. Comparative transcriptome analysis of T lymphocyte subpopulations and identification of critical regulators defining porcine thymocyte identity. Front Immunol 2024; 15:1339787. [PMID: 38384475 PMCID: PMC10879363 DOI: 10.3389/fimmu.2024.1339787] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2023] [Accepted: 01/18/2024] [Indexed: 02/23/2024] Open
Abstract
Introduction The development and migration of T cells in the thymus and peripheral tissues are crucial for maintaining adaptive immunity in mammals. However, the regulatory mechanisms underlying T cell development and thymocyte identity formation in pigs remain largely underexplored. Method Here, by integrating bulk and single-cell RNA-sequencing data, we investigated regulatory signatures of porcine thymus and lymph node T cells. Results The comparison of T cell subpopulations derived from porcine thymus and lymph nodes revealed that their transcriptomic differences were influenced more by tissue origin than by T cell phenotypes, and that lymph node cells exhibited greater transcriptional diversity than thymocytes. Through weighted gene co-expression network analysis (WGCNA), we identified the key modules and candidate hub genes regulating the heterogeneity of T cell subpopulations. Further, we integrated the porcine thymocyte dataset with peripheral blood mononuclear cell (PBMC) dataset to systematically compare transcriptomic differences between T cell types from different tissues. Based on single-cell datasets, we further identified the key transcription factors (TFs) responsible for maintaining porcine thymocyte identity and unveiled that these TFs coordinately regulated the entire T cell development process. Finally, we performed GWAS of cell type-specific differentially expressed genes (DEGs) and 30 complex traits, and found that the DEGs in thymus-related and peripheral blood-related cell types, especially CD4_SP cluster and CD8-related cluster, were significantly associated with pig productive and reproductive traits. Discussion Our findings provide an insight into T cell development and lay a foundation for further exploring the porcine immune system and genetic mechanisms underlying complex traits in pigs.
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Affiliation(s)
- Pingping Han
- Key Lab of Agricultural Animal Genetics, Breeding, and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan, China
| | - Wei Zhang
- Key Lab of Agricultural Animal Genetics, Breeding, and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan, China
| | - Daoyuan Wang
- Key Lab of Agricultural Animal Genetics, Breeding, and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan, China
| | - Yalan Wu
- Key Lab of Agricultural Animal Genetics, Breeding, and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan, China
| | - Xinyun Li
- Key Lab of Agricultural Animal Genetics, Breeding, and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan, China
- The Cooperative Innovation Center for Sustainable Pig Production, Huazhong Agricultural University, Wuhan, China
| | - Shuhong Zhao
- Key Lab of Agricultural Animal Genetics, Breeding, and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan, China
- The Cooperative Innovation Center for Sustainable Pig Production, Huazhong Agricultural University, Wuhan, China
| | - Mengjin Zhu
- Key Lab of Agricultural Animal Genetics, Breeding, and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan, China
- The Cooperative Innovation Center for Sustainable Pig Production, Huazhong Agricultural University, Wuhan, China
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Dunaway LS, Luse MA, Nyshadham S, Bulut G, Alencar GF, Chavkin NW, Cortese-Krott M, Hirschi KK, Isakson BE. Obesogenic diet disrupts tissue-specific mitochondrial gene signatures in the artery and capillary endothelium. Physiol Genomics 2024; 56:113-127. [PMID: 37982169 PMCID: PMC11281809 DOI: 10.1152/physiolgenomics.00109.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2023] [Revised: 11/03/2023] [Accepted: 11/13/2023] [Indexed: 11/21/2023] Open
Abstract
Endothelial cells (ECs) adapt to the unique needs of their resident tissue and metabolic perturbations, such as obesity. We sought to understand how obesity affects EC metabolic phenotypes, specifically mitochondrial gene expression. We investigated the mesenteric and adipose endothelium because these vascular beds have distinct roles in lipid homeostasis. Initially, we performed bulk RNA sequencing on ECs from mouse adipose and mesenteric vasculatures after a normal chow (NC) diet or high-fat diet (HFD) and found higher mitochondrial gene expression in adipose ECs compared with mesenteric ECs in both NC and HFD mice. Next, we performed single-cell RNA sequencing and categorized ECs as arterial, capillary, venous, or lymphatic. We found mitochondrial genes to be enriched in adipose compared with mesentery under NC conditions in artery and capillary ECs. After HFD, these genes were decreased in adipose ECs, becoming like mesenteric ECs. Transcription factor analysis revealed that peroxisome proliferator-activated receptor-γ (PPAR-γ) had high specificity in NC adipose artery and capillary ECs. These findings were recapitulated in single-nuclei RNA-sequencing data from human visceral adipose. The sum of these findings suggests that mesenteric and adipose arterial ECs metabolize lipids differently, and the transcriptional phenotype of the vascular beds converges in obesity due to downregulation of PPAR-γ in adipose artery and capillary ECs.NEW & NOTEWORTHY Using bulk and single-cell RNA sequencing on endothelial cells from adipose and mesentery, we found that an obesogenic diet induces a reduction in adipose endothelial oxidative phosphorylation gene expression, resulting in a phenotypic convergence of mesenteric and adipose endothelial cells. Furthermore, we found evidence that PPAR-γ drives this phenotypic shift. Mining of human data sets segregated based on body mass index supported these findings. These data point to novel mechanisms by which obesity induces endothelial dysfunction.
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Affiliation(s)
- Luke S Dunaway
- Robert M. Berne Cardiovascular Research Center, University of Virginia School of Medicine, Charlottesville, Virginia, United States
| | - Melissa A Luse
- Robert M. Berne Cardiovascular Research Center, University of Virginia School of Medicine, Charlottesville, Virginia, United States
- Department of Molecular Physiology and Biological Physics, University of Virginia School of Medicine, Charlottesville, Virginia, United States
| | - Shruthi Nyshadham
- Robert M. Berne Cardiovascular Research Center, University of Virginia School of Medicine, Charlottesville, Virginia, United States
| | - Gamze Bulut
- Robert M. Berne Cardiovascular Research Center, University of Virginia School of Medicine, Charlottesville, Virginia, United States
| | - Gabriel F Alencar
- Department of Biochemistry and Molecular Genetics, University of Virginia School of Medicine, Charlottesville, Virginia, United States
| | - Nicholas W Chavkin
- Robert M. Berne Cardiovascular Research Center, University of Virginia School of Medicine, Charlottesville, Virginia, United States
- Department of Cell Biology, University of Virginia School of Medicine, Charlottesville, Virginia, United States
| | - Miriam Cortese-Krott
- Department of Cardiology, Pneumology and Angiology, Heinrich Heine University of Düsseldorf, Düsseldorf, Germany
| | - Karen K Hirschi
- Robert M. Berne Cardiovascular Research Center, University of Virginia School of Medicine, Charlottesville, Virginia, United States
- Department of Cell Biology, University of Virginia School of Medicine, Charlottesville, Virginia, United States
| | - Brant E Isakson
- Robert M. Berne Cardiovascular Research Center, University of Virginia School of Medicine, Charlottesville, Virginia, United States
- Department of Molecular Physiology and Biological Physics, University of Virginia School of Medicine, Charlottesville, Virginia, United States
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Yang X, Chen X, Wang W, Qu S, Lai B, Zhang J, Chen J, Han C, Tian Y, Xiao Y, Gao W, Wu Y. Transcriptional profile of human thymus reveals IGFBP5 is correlated with age-related thymic involution. Front Immunol 2024; 15:1322214. [PMID: 38318192 PMCID: PMC10839013 DOI: 10.3389/fimmu.2024.1322214] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Accepted: 01/03/2024] [Indexed: 02/07/2024] Open
Abstract
Thymus is the main immune organ which is responsible for the production of self-tolerant and functional T cells, but it shrinks rapidly with age after birth. Although studies have researched thymus development and involution in mouse, the critical regulators that arise with age in human thymus remain unclear. We collected public human single-cell transcriptomic sequencing (scRNA-seq) datasets containing 350,678 cells from 36 samples, integrated them as a cell atlas of human thymus. Clinical samples were collected and experiments were performed for validation. We found early thymocyte-specific signaling and regulons which played roles in thymocyte migration, proliferation, apoptosis and differentiation. Nevertheless, signaling patterns including number, strength and path completely changed during aging, Transcription factors (FOXC1, MXI1, KLF9, NFIL3) and their target gene, IGFBP5, were resolved and up-regulated in aging thymus and involved in promoting epithelial-mesenchymal transition (EMT), responding to steroid and adipogenesis process of thymic epithelial cell (TECs). Furthermore, we validated that IGFBP5 protein increased at TECs and Hassall's corpuscle in both human and mouse aging thymus and knockdown of IGFBP5 significantly increased the expression of proliferation-related genes in thymocytes. Collectively, we systematically explored cell-cell communications and regulons of early thymocytes as well as age-related differences in human thymus by using both bioinformatic and experimental verification, indicating IGFBP5 as a functional marker of thymic involution and providing new insights into the mechanisms of thymus involution.
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Affiliation(s)
- Xiaojing Yang
- College of Bioengineering, Chongqing University, Chongqing, China
| | - Xichan Chen
- Institute of Immunology People’s Liberation Army (PLA) & Department of Immunology, College of Basic Medicine, Army Medical University (Third Military Medical University), Chongqing, China
| | - Wei Wang
- Department of Cardiovascular Surgery, the Second Affiliated Hospital, Army Medical University, Chongqing, China
| | - Siming Qu
- Organ Transplantation Center, the First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China
| | - Binbin Lai
- Institute of Medical Technology, Peking University Health Science Center, Beijing, China
| | - Ji Zhang
- Institute of Immunology People’s Liberation Army (PLA) & Department of Immunology, College of Basic Medicine, Army Medical University (Third Military Medical University), Chongqing, China
| | - Jian Chen
- Institute of Immunology People’s Liberation Army (PLA) & Department of Immunology, College of Basic Medicine, Army Medical University (Third Military Medical University), Chongqing, China
| | - Chao Han
- Institute of Immunology People’s Liberation Army (PLA) & Department of Immunology, College of Basic Medicine, Army Medical University (Third Military Medical University), Chongqing, China
| | - Yi Tian
- Institute of Immunology People’s Liberation Army (PLA) & Department of Immunology, College of Basic Medicine, Army Medical University (Third Military Medical University), Chongqing, China
| | - Yingbin Xiao
- Department of Cardiovascular Surgery, the Second Affiliated Hospital, Army Medical University, Chongqing, China
| | - Weiwu Gao
- Institute of Immunology People’s Liberation Army (PLA) & Department of Immunology, College of Basic Medicine, Army Medical University (Third Military Medical University), Chongqing, China
| | - Yuzhang Wu
- College of Bioengineering, Chongqing University, Chongqing, China
- Institute of Immunology People’s Liberation Army (PLA) & Department of Immunology, College of Basic Medicine, Army Medical University (Third Military Medical University), Chongqing, China
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Rasetto NB, Giacomini D, Berardino AA, Waichman TV, Beckel MS, Di Bella DJ, Brown J, Davies-Sala MG, Gerhardinger C, Lie DC, Arlotta P, Chernomoretz A, Schinder AF. Transcriptional dynamics orchestrating the development and integration of neurons born in the adult hippocampus. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.11.03.565477. [PMID: 38260428 PMCID: PMC10802403 DOI: 10.1101/2023.11.03.565477] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
The adult hippocampus generates new granule cells (aGCs) that exhibit distinct functional capabilities along development, conveying a unique form of plasticity to the preexisting circuits. While early differentiation of adult radial glia-like neural stem cells (RGL) has been studied extensively, the molecular mechanisms guiding the maturation of postmitotic neurons remain unknown. Here, we used a precise birthdating strategy to follow newborn aGCs along differentiation using single-nuclei RNA sequencing (snRNA-seq). Transcriptional profiling revealed a continuous trajectory from RGLs to mature aGCs, with multiple sequential immature stages bearing increasing levels of effector genes supporting growth, excitability and synaptogenesis. Remarkably, four discrete cellular states were defined by the expression of distinct sets of transcription factors (TFs): quiescent neural stem cells, proliferative progenitors, postmitotic immature aGCs, and mature aGCs. The transition from immature to mature aCGs involved a transcriptional switch that shutdown molecular cascades promoting cell growth, such as the SoxC family of TFs, to activate programs controlling neuronal homeostasis. Indeed, aGCs overexpressing Sox4 or Sox11 remained stalled at the immature state. Our results unveil precise molecular mechanisms driving adult neural stem cells through the pathway of neuronal differentiation.
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75
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Yuan Y, Huo Q, Zhang Z, Wang Q, Wang J, Chang S, Cai P, Song KM, Galbraith DW, Zhang W, Huang L, Song R, Ma Z. Decoding the gene regulatory network of endosperm differentiation in maize. Nat Commun 2024; 15:34. [PMID: 38167709 PMCID: PMC10762121 DOI: 10.1038/s41467-023-44369-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Accepted: 12/11/2023] [Indexed: 01/05/2024] Open
Abstract
The persistent cereal endosperm constitutes the majority of the grain volume. Dissecting the gene regulatory network underlying cereal endosperm development will facilitate yield and quality improvement of cereal crops. Here, we use single-cell transcriptomics to analyze the developing maize (Zea mays) endosperm during cell differentiation. After obtaining transcriptomic data from 17,022 single cells, we identify 12 cell clusters corresponding to five endosperm cell types and revealing complex transcriptional heterogeneity. We delineate the temporal gene-expression pattern from 6 to 7 days after pollination. We profile the genomic DNA-binding sites of 161 transcription factors differentially expressed between cell clusters and constructed a gene regulatory network by combining the single-cell transcriptomic data with the direct DNA-binding profiles, identifying 181 regulons containing genes encoding transcription factors along with their high-confidence targets, Furthermore, we map the regulons to endosperm cell clusters, identify cell-cluster-specific essential regulators, and experimentally validated three predicted key regulators. This study provides a framework for understanding cereal endosperm development and function at single-cell resolution.
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Affiliation(s)
- Yue Yuan
- State Key Laboratory of Maize Bio-breeding, Frontiers Science Center for Molecular Design Breeding, Joint International Research Laboratory of Crop Molecular Breeding, National Maize Improvement Center, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China
- Sanya Institute of China Agricultural University, Sanya, 572025, China
- Hainan Yazhou Bay Seed Laboratory, Sanya, 572025, China
| | - Qiang Huo
- State Key Laboratory of Maize Bio-breeding, Frontiers Science Center for Molecular Design Breeding, Joint International Research Laboratory of Crop Molecular Breeding, National Maize Improvement Center, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China
| | - Ziru Zhang
- State Key Laboratory of Maize Bio-breeding, Frontiers Science Center for Molecular Design Breeding, Joint International Research Laboratory of Crop Molecular Breeding, National Maize Improvement Center, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China
| | - Qun Wang
- State Key Laboratory of Maize Bio-breeding, Frontiers Science Center for Molecular Design Breeding, Joint International Research Laboratory of Crop Molecular Breeding, National Maize Improvement Center, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China
| | - Juanxia Wang
- State Key Laboratory of Maize Bio-breeding, Frontiers Science Center for Molecular Design Breeding, Joint International Research Laboratory of Crop Molecular Breeding, National Maize Improvement Center, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China
| | - Shuaikang Chang
- State Key Laboratory of Maize Bio-breeding, Frontiers Science Center for Molecular Design Breeding, Joint International Research Laboratory of Crop Molecular Breeding, National Maize Improvement Center, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China
| | - Peng Cai
- State Key Laboratory of Maize Bio-breeding, Frontiers Science Center for Molecular Design Breeding, Joint International Research Laboratory of Crop Molecular Breeding, National Maize Improvement Center, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China
| | - Karen M Song
- Department of Biology, Trinity College of Arts and Sciences, Duke University, Durham, NC, 27708, USA
| | - David W Galbraith
- School of Plant Sciences and Bio5 Institute, University of Arizona, Tucson, AZ, 85721, USA
| | - Weixiao Zhang
- State Key Laboratory of Maize Bio-breeding, Frontiers Science Center for Molecular Design Breeding, Joint International Research Laboratory of Crop Molecular Breeding, National Maize Improvement Center, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China
| | - Long Huang
- State Key Laboratory of Maize Bio-breeding, Frontiers Science Center for Molecular Design Breeding, Joint International Research Laboratory of Crop Molecular Breeding, National Maize Improvement Center, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China
| | - Rentao Song
- State Key Laboratory of Maize Bio-breeding, Frontiers Science Center for Molecular Design Breeding, Joint International Research Laboratory of Crop Molecular Breeding, National Maize Improvement Center, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China.
- Sanya Institute of China Agricultural University, Sanya, 572025, China.
- Hainan Yazhou Bay Seed Laboratory, Sanya, 572025, China.
| | - Zeyang Ma
- State Key Laboratory of Maize Bio-breeding, Frontiers Science Center for Molecular Design Breeding, Joint International Research Laboratory of Crop Molecular Breeding, National Maize Improvement Center, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China.
- Sanya Institute of China Agricultural University, Sanya, 572025, China.
- Hainan Yazhou Bay Seed Laboratory, Sanya, 572025, China.
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76
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Wen S, Lv X, Li P, Li J, Qin D. Analysis of cancer-associated fibroblasts in cervical cancer by single-cell RNA sequencing. Aging (Albany NY) 2023; 15:15340-15359. [PMID: 38157264 PMCID: PMC10781451 DOI: 10.18632/aging.205353] [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: 07/10/2023] [Accepted: 11/10/2023] [Indexed: 01/03/2024]
Abstract
OBJECTIVE Since scRNA-seq is an effective tool to study tumor heterogeneity, this paper intends to reveal the differences of cervical cancer in patients at the individual cell level by scRNA-seq, and focus on the biological functions of cancer-associated fibroblasts (CAFs) in cervical cancer, facilitating the provision of a new interpretation of the heterogeneity of the microenvironment of cervical cancer, and an in-depth exploration of the pathogenesis of cervical cancer as well as pursuit of effective means of treatment intake. METHODS 3 cervical cancer specimens were collected by clinical surgery for single-cell RNA sequencing. Cell suspensions of fresh cervical cancer tissues were prepared, and cDNA libraries were created and sequenced on the machine. Furthermore, the sequencing data were analyzed using bioinformatics, including descending clustering of cells, identification of cell populations, mimetic time series analysis, inferCNV, cell communication analysis, and identification of transcription factors. RESULTS A total of 9 cell types were identified, encompassing T cells, epithelial cells, smooth muscle cells, CAFs, endothelial cells, macrophages, B cells, lymphocytes, and plasma cells. CAFs were further divided into three cell subtypes, named type1 cells, type2 cells, and type3 cells. With key transcription factors for the three cells, TCF21, ZC3H11A, and MYEF2 obtained, this research revealed the communication relationship between CAFs and several other cells, and found an important role of CAFs in the MK signaling pathway. CONCLUSIONS scRNA-seq technology contributed to exploring the tumor heterogeneity of cervical cancer more deeply, and also further gaining insight into the biological functions of CAFs in cervical cancer.
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Affiliation(s)
- Shuang Wen
- Reproductive Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Xuefeng Lv
- Department of Laboratory Medicine, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Pengxiang Li
- Henan Provincial Chest Hospital, Zhengzhou, Henan, China
| | - Jinpeng Li
- Department of Laboratory Medicine, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Dongchun Qin
- Department of Laboratory Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
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77
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Li R, Zhao M, Miao C, Shi X, Lu J. Identification and validation of key biomarkers associated with macrophages in nonalcoholic fatty liver disease based on hdWGCNA and machine learning. Aging (Albany NY) 2023; 15:15451-15472. [PMID: 38147020 PMCID: PMC10781485 DOI: 10.18632/aging.205374] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2023] [Accepted: 11/21/2023] [Indexed: 12/27/2023]
Abstract
BACKGROUND NAFLD has attracted increasing attention because of its high prevalence and risk of progression to cirrhosis or even hepatocellular carcinoma. Therefore, research into the root causes and molecular indicators of NAFLD is crucial. METHODS We analyzed scRNA-seq data and RNA-seq data from normal and NAFLD liver samples. We utilized hdWGCNA to find module-related genes associated with the phenotype. Multiple machine learning algorithms were used to validate the model diagnostics and further screen for genes that are characteristic of NAFLD. The NAFLD mouse model was constructed using the MCD diet to validate the diagnostic effect of the genes. RESULTS We identified a specific macrophage population called NASH-macrophages by single-cell sequencing analysis. Cell communication analysis and Pseudo-time trajectory analysis revealed the specific role and temporal distribution of NASH-macrophages in NAFLD. The hdWGCNA screening yielded 30 genes associated with NASH-macrophages, and machine learning algorithms screened and obtained two genes characterizing NAFLD. The immune infiltration indicated that these genes were highly associated with macrophages. Notably, we verified by RT-qPCR, IHC, and WB that MAFB and CX3CR1 are highly expressed in the MCD mouse model and may play important roles. CONCLUSIONS Our study revealed a macrophage population that is closely associated with NAFLD. Using hdWGCNA analysis and multiple machine learning algorithms, we identified two NAFLD signature genes that are highly correlated with macrophages. Our findings may provide potential feature markers and therapeutic targets for NAFLD.
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Affiliation(s)
- Ruowen Li
- Department of General Surgery, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan 250012, Shandong Province, China
- School of Medicine, Cheeloo College of Medicine, Shandong University, Jinan 250012, Shandong Province, China
| | - Mingjian Zhao
- Department of General Surgery, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan 250012, Shandong Province, China
- School of Medicine, Cheeloo College of Medicine, Shandong University, Jinan 250012, Shandong Province, China
| | - Chengxu Miao
- Department of General Surgery, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan 250012, Shandong Province, China
- School of Medicine, Cheeloo College of Medicine, Shandong University, Jinan 250012, Shandong Province, China
| | - Xiaojia Shi
- School of Medicine, Cheeloo College of Medicine, Shandong University, Jinan 250012, Shandong Province, China
| | - Jinghui Lu
- Department of General Surgery, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan 250012, Shandong Province, China
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78
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Liang Q, Huang Y, He S, Chen K. Pathway centric analysis for single-cell RNA-seq and spatial transcriptomics data with GSDensity. Nat Commun 2023; 14:8416. [PMID: 38110427 PMCID: PMC10728201 DOI: 10.1038/s41467-023-44206-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Accepted: 12/04/2023] [Indexed: 12/20/2023] Open
Abstract
Advances in single-cell technology have enabled molecular dissection of heterogeneous biospecimens at unprecedented scales and resolutions. Cluster-centric approaches are widely applied in analyzing single-cell data, however they have limited power in dissecting and interpreting highly heterogenous, dynamically evolving data. Here, we present GSDensity, a graph-modeling approach that allows users to obtain pathway-centric interpretation and dissection of single-cell and spatial transcriptomics (ST) data without performing clustering. Using pathway gene sets, we show that GSDensity can accurately detect biologically distinct cells and reveal novel cell-pathway associations ignored by existing methods. Moreover, GSDensity, combined with trajectory analysis can identify curated pathways that are active at various stages of mouse brain development. Finally, GSDensity can identify spatially relevant pathways in mouse brains and human tumors including those following high-order organizational patterns in the ST data. Particularly, we create a pan-cancer ST map revealing spatially relevant and recurrently active pathways across six different tumor types.
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Affiliation(s)
- Qingnan Liang
- Department of Bioinformatics and Computational Biology, UT MD Anderson Cancer Center, Houston, TX, USA
| | - Yuefan Huang
- Department of Bioinformatics and Computational Biology, UT MD Anderson Cancer Center, Houston, TX, USA
| | - Shan He
- Department of Bioinformatics and Computational Biology, UT MD Anderson Cancer Center, Houston, TX, USA
| | - Ken Chen
- Department of Bioinformatics and Computational Biology, UT MD Anderson Cancer Center, Houston, TX, USA.
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Wang R, Wang M, Pei S, Zhang Y, Guo S, Guo W, Wu Z, Wang H, Li Y, Zhu Y, Meng LH, Lang J, Jin G, Xiao Y, Hu L, Kong X. Protocol for PPP1R15A-inhibited mouse model establishment with subcutaneous B16F1 tumor and single-cell analysis. STAR Protoc 2023; 4:102616. [PMID: 37756156 PMCID: PMC10539956 DOI: 10.1016/j.xpro.2023.102616] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Revised: 05/31/2023] [Accepted: 09/11/2023] [Indexed: 09/29/2023] Open
Abstract
Here, we present a protocol for exploring the effects of PPP1R15A inhibitor, Sephin1, on antitumor immunity of B16F1 subcutaneous tumor in mice. We describe steps for constructing single-cell transcriptome and TCR libraries, sequencing, and using sequencing data for the integration of expression and TCR data. We then detail procedures for gene differentiation, regulon and cell-cell communication analysis, and validation of single-cell analysis results. For complete details on the use and execution of this protocol, please refer to Wang et al.1.
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Affiliation(s)
- Rongjing Wang
- Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai, China
| | - Minghui Wang
- Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai, China; University of Chinese Academy of Sciences, Shanghai, China
| | - Siyu Pei
- Department of Thoracic Surgical Oncology, Shanghai Lung Cancer Center, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine (SJTUSM), Shanghai 200030, China
| | - Yuchao Zhang
- Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai, China
| | - Shiwei Guo
- Changhai Hospital, Department of Hepatobiliary Pancreatic Surgery, Shanghai, China
| | - Wei Guo
- Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai, China
| | - Zhenchuan Wu
- Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai, China; University of Chinese Academy of Sciences, Shanghai, China
| | - Hailong Wang
- Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai, China; ShanghaiTech University, School of Life Science and Technology, Shanghai, China
| | - Yizhe Li
- Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai, China; University of Chinese Academy of Sciences, Shanghai, China
| | - Yufei Zhu
- Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai, China
| | - Ling-Hua Meng
- Division of Anti-tumor Pharmacology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, China
| | - Jingyu Lang
- Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai, China
| | - Gang Jin
- Changhai Hospital, Department of Hepatobiliary Pancreatic Surgery, Shanghai, China.
| | - Yichuan Xiao
- Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai, China.
| | - Landian Hu
- Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai, China; Anda Biology Medicine Development (Shenzhen) Co., Ltd, Shenzhen, China.
| | - Xiangyin Kong
- Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai, China; ShanghaiTech University, School of Life Science and Technology, Shanghai, China.
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80
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Li H, Liu P, Zhang B, Yuan Z, Guo M, Zou X, Qian Y, Deng S, Zhu L, Cao X, Tao T, Xia S, Bao X, Xu Y. Acute ischemia induces spatially and transcriptionally distinct microglial subclusters. Genome Med 2023; 15:109. [PMID: 38082331 PMCID: PMC10712107 DOI: 10.1186/s13073-023-01257-5] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Accepted: 11/13/2023] [Indexed: 12/18/2023] Open
Abstract
BACKGROUND Damage in the ischemic core and penumbra after stroke affects patient prognosis. Microglia immediately respond to ischemic insult and initiate immune inflammation, playing an important role in the cellular injury after stroke. However, the microglial heterogeneity and the mechanisms involved remain unclear. METHODS We first performed single-cell RNA-sequencing (scRNA-seq) and spatial transcriptomics (ST) on middle cerebral artery occlusion (MCAO) mice from three time points to determine stroke-associated microglial subclusters and their spatial distributions. Furthermore, the expression of microglial subcluster-specific marker genes and the localization of different microglial subclusters were verified on MCAO mice through RNAscope and immunofluorescence. Gene set variation analysis (GSVA) was performed to reveal functional characteristics of microglia sub-clusters. Additionally, ingenuity pathway analysis (IPA) was used to explore upstream regulators of microglial subclusters, which was confirmed by immunofluorescence, RT-qPCR, shRNA-mediated knockdown, and targeted metabolomics. Finally, the infarct size, neurological deficits, and neuronal apoptosis were evaluated in MCAO mice after manipulation of specific microglial subcluster. RESULTS We discovered stroke-associated microglial subclusters in the brains of MCAO mice. We also identified novel marker genes of these microglial subclusters and defined these cells as ischemic core-associated (ICAM) and ischemic penumbra-associated (IPAM) microglia, according to their spatial distribution. ICAM, induced by damage-associated molecular patterns, are probably fueled by glycolysis, and exhibit increased pro-inflammatory cytokines and chemokines production. BACH1 is a key transcription factor driving ICAM generation. In contrast, glucocorticoids, which are enriched in the penumbra, likely trigger IPAM formation, which are presumably powered by the citrate cycle and oxidative phosphorylation and are characterized by moderate pro-inflammatory responses, inflammation-alleviating metabolic features, and myelinotrophic properties. CONCLUSIONS ICAM could induce excessive neuroinflammation, aggravating brain injury, whereas IPAM probably exhibit neuroprotective features, which could be essential for the homeostasis and survival of cells in the penumbra. Our findings provide a biological basis for targeting specific microglial subclusters as a potential therapeutic strategy for ischemic stroke.
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Affiliation(s)
- Huiya Li
- Department of Neurology, Drum Tower Hospital, Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Translational Medicine for Brain Critical Diseases, Nanjing University, Nanjing, 210008, China
- Department of Radiology, The Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, 210008, China
| | - Pinyi Liu
- Department of Neurology, Drum Tower Hospital, Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Translational Medicine for Brain Critical Diseases, Nanjing University, Nanjing, 210008, China
| | - Bing Zhang
- Department of Radiology, The Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, 210008, China
| | - Zengqiang Yuan
- The Brain Science Centre, Beijing Institute of Basic Medical Sciences, Beijing, 100850, China
- Centre of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, 100069, China
| | - Mengdi Guo
- Department of Neurology, Drum Tower Hospital, Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Translational Medicine for Brain Critical Diseases, Nanjing University, Nanjing, 210008, China
| | - Xinxin Zou
- Department of Neurology, Drum Tower Hospital, Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Translational Medicine for Brain Critical Diseases, Nanjing University, Nanjing, 210008, China
| | - Yi Qian
- Department of Neurology, Drum Tower Hospital, Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Translational Medicine for Brain Critical Diseases, Nanjing University, Nanjing, 210008, China
| | - Shiji Deng
- Department of Neurology, Drum Tower Hospital, Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Translational Medicine for Brain Critical Diseases, Nanjing University, Nanjing, 210008, China
| | - Liwen Zhu
- Department of Neurology, Drum Tower Hospital, Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Translational Medicine for Brain Critical Diseases, Nanjing University, Nanjing, 210008, China
| | - Xiang Cao
- Department of Neurology, Drum Tower Hospital, Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Translational Medicine for Brain Critical Diseases, Nanjing University, Nanjing, 210008, China
| | - Tao Tao
- Department of Neurology, Drum Tower Hospital, Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Translational Medicine for Brain Critical Diseases, Nanjing University, Nanjing, 210008, China
| | - Shengnan Xia
- Department of Neurology, Drum Tower Hospital, Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Translational Medicine for Brain Critical Diseases, Nanjing University, Nanjing, 210008, China
| | - Xinyu Bao
- Department of Neurology, Drum Tower Hospital, Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Translational Medicine for Brain Critical Diseases, Nanjing University, Nanjing, 210008, China
| | - Yun Xu
- Department of Neurology, Drum Tower Hospital, Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Translational Medicine for Brain Critical Diseases, Nanjing University, Nanjing, 210008, China.
- Jiangsu Key Laboratory for Molecular Medicine, Medical School of Nanjing University, Nanjing, 210008, China.
- Jiangsu Provincial Key Discipline of Neurology, Nanjing, 210008, China.
- Nanjing Neurology Medical Centre, Nanjing, 210008, China.
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Yu H, Xue W, Yu H, Song Y, Liu X, Qin L, Wang S, Bao H, Gu H, Chen G, Zhao D, Tu Y, Cheng J, Wang L, Ai Z, Hu D, Wang L, Peng A. Single-cell transcriptomics reveals variations in monocytes and Tregs between gout flare and remission. JCI Insight 2023; 8:e171417. [PMID: 38063198 PMCID: PMC10795830 DOI: 10.1172/jci.insight.171417] [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: 04/12/2023] [Accepted: 10/25/2023] [Indexed: 12/18/2023] Open
Abstract
Gout commonly manifests as a painful, self-limiting inflammatory arthritis. Nevertheless, the understanding of the inflammatory and immune responses underlying gout flares and remission remains ambiguous. Here, based on single-cell RNA-Seq and an independent validation cohort, we identified the potential mechanism of gout flare, which likely involves the upregulation of HLA-DQA1+ nonclassical monocytes and is related to antigen processing and presentation. Furthermore, Tregs also play an essential role in the suppressive capacity during gout remission. Cell communication analysis suggested the existence of altered crosstalk between monocytes and other T cell types, such as Tregs. Moreover, we observed the systemic upregulation of inflammatory and cytokine genes, primarily in classical monocytes, during gout flares. All monocyte subtypes showed increased arachidonic acid metabolic activity along with upregulation of prostaglandin-endoperoxide synthase 2 (PTGS2). We also detected a decrease in blood arachidonic acid and an increase in leukotriene B4 levels during gout flares. In summary, our study illustrates the distinctive immune cell responses and systemic inflammation patterns that characterize the transition from gout flares to remission, and it suggests that blood monocyte subtypes and Tregs are potential intervention targets for preventing recurrent gout attacks and progression.
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Affiliation(s)
- Hanjie Yu
- Center for Nephrology and Clinical Metabolomics and Division of Nephrology, Shanghai Tenth People’s Hospital, and
| | - Wen Xue
- Center for Nephrology and Clinical Metabolomics and Division of Nephrology, Shanghai Tenth People’s Hospital, and
| | - Hanqing Yu
- Center for Nephrology and Clinical Metabolomics and Division of Nephrology, Shanghai Tenth People’s Hospital, and
| | - Yaxiang Song
- Center for Nephrology and Clinical Metabolomics and Division of Nephrology, Shanghai Tenth People’s Hospital, and
| | - Xinying Liu
- Center for Nephrology and Clinical Metabolomics and Division of Nephrology, Shanghai Tenth People’s Hospital, and
| | - Ling Qin
- Center for Nephrology and Clinical Metabolomics and Division of Nephrology, Shanghai Tenth People’s Hospital, and
| | - Shu Wang
- Center for Nephrology and Clinical Metabolomics and Division of Nephrology, Shanghai Tenth People’s Hospital, and
| | - Hui Bao
- Center for Nephrology and Clinical Metabolomics and Division of Nephrology, Shanghai Tenth People’s Hospital, and
| | - Hongchen Gu
- Center for Nephrology and Clinical Metabolomics and Division of Nephrology, Shanghai Tenth People’s Hospital, and
| | - Guangqi Chen
- Center for Nephrology and Clinical Metabolomics and Division of Nephrology, Shanghai Tenth People’s Hospital, and
| | - Dake Zhao
- Center for Nephrology and Clinical Metabolomics and Division of Nephrology, Shanghai Tenth People’s Hospital, and
| | - Yang Tu
- Center for Nephrology and Clinical Metabolomics and Division of Nephrology, Shanghai Tenth People’s Hospital, and
| | - Jiafen Cheng
- Center for Nephrology and Clinical Metabolomics and Division of Nephrology, Shanghai Tenth People’s Hospital, and
| | - Liya Wang
- Center for Nephrology and Clinical Metabolomics and Division of Nephrology, Shanghai Tenth People’s Hospital, and
| | - Zisheng Ai
- Department of Medical Statistics, Tongji University School of Medicine, Shanghai, China
| | - Dayong Hu
- Center for Nephrology and Clinical Metabolomics and Division of Nephrology, Shanghai Tenth People’s Hospital, and
| | - Ling Wang
- Center for Nephrology and Clinical Metabolomics and Division of Nephrology, Shanghai Tenth People’s Hospital, and
| | - Ai Peng
- Center for Nephrology and Clinical Metabolomics and Division of Nephrology, Shanghai Tenth People’s Hospital, and
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Sarieva K, Kagermeier T, Khakipoor S, Atay E, Yentür Z, Becker K, Mayer S. Human brain organoid model of maternal immune activation identifies radial glia cells as selectively vulnerable. Mol Psychiatry 2023; 28:5077-5089. [PMID: 36878967 PMCID: PMC9986664 DOI: 10.1038/s41380-023-01997-1] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Revised: 02/07/2023] [Accepted: 02/10/2023] [Indexed: 03/08/2023]
Abstract
Maternal immune activation (MIA) during critical windows of gestation is correlated with long-term neurodevelopmental deficits in the offspring, including increased risk for autism spectrum disorder (ASD) in humans. Interleukin 6 (IL-6) derived from the gestational parent is one of the major molecular mediators by which MIA alters the developing brain. In this study, we establish a human three-dimensional (3D) in vitro model of MIA by treating induced pluripotent stem cell-derived dorsal forebrain organoids with a constitutively active form of IL-6, Hyper-IL-6. We validate our model by showing that dorsal forebrain organoids express the molecular machinery necessary for responding to Hyper-IL-6 and activate STAT signaling upon Hyper-IL-6 treatment. RNA sequencing analysis reveals the upregulation of major histocompatibility complex class I (MHCI) genes in response to Hyper-IL-6 exposure, which have been implicated with ASD. We find a small increase in the proportion of radial glia cells after Hyper-IL-6 treatment through immunohistochemistry and single-cell RNA-sequencing. We further show that radial glia cells are the cell type with the highest number of differentially expressed genes, and Hyper-IL-6 treatment leads to the downregulation of genes related to protein translation in line with a mouse model of MIA. Additionally, we identify differentially expressed genes not found in mouse models of MIA, which might drive species-specific responses to MIA. Finally, we show abnormal cortical layering as a long-term consequence of Hyper-IL-6 treatment. In summary, we establish a human 3D model of MIA, which can be used to study the cellular and molecular mechanisms underlying the increased risk for developing disorders such as ASD.
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Affiliation(s)
- Kseniia Sarieva
- Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
- International Max Planck Research School, Graduate Training Centre of Neuroscience, University of Tübingen, Tübingen, Germany
| | - Theresa Kagermeier
- Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
- International Max Planck Research School, Graduate Training Centre of Neuroscience, University of Tübingen, Tübingen, Germany
| | - Shokoufeh Khakipoor
- Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
| | - Ezgi Atay
- Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
| | - Zeynep Yentür
- Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
- International Max Planck Research School, Graduate Training Centre of Neuroscience, University of Tübingen, Tübingen, Germany
- Heidelberger Akademie der Wissenschaften, Heidelberg, Germany
| | - Katharina Becker
- Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
| | - Simone Mayer
- Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany.
- International Max Planck Research School, Graduate Training Centre of Neuroscience, University of Tübingen, Tübingen, Germany.
- Heidelberger Akademie der Wissenschaften, Heidelberg, Germany.
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83
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Su Z, Liu Z, Lei W, Xia K, Xiao A, Hu Z, Zhou M, Zhu F, Tian J, Yang M, Wang D, Xiang AP, Nie J. Hyperhomocysteinemia lowers serum testosterone concentration via impairing testosterone production in Leydig cells. Cell Biol Toxicol 2023; 39:3077-3100. [PMID: 37495868 DOI: 10.1007/s10565-023-09819-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2022] [Accepted: 07/12/2023] [Indexed: 07/28/2023]
Abstract
Hyperhomocysteinemia (HHcy) plays a salient role in male infertility. However, whether HHcy interferes with testosterone production remains inconclusive. Here, we reported a lower serum testosterone level in HHcy mice. Single-cell RNA sequencing revealed that genes related to testosterone biosynthesis, together with nuclear receptor subfamily 5 group A member 1 (Nr5a1), a key transcription factor for steroidogenic genes, were downregulated in the Leydig cells (LCs) of HHcy mice. Mechanistically, Hcy lowered trimethylation of histone H3 on lysine 4 (H3K4me3), which was bound on the promoter region of Nr5a1, resulting in downregulation of Nr5a1. Intriguingly, we identified an unknown cell cluster annotated as Macrophage-like Leydig cells (McLCs), expressing both LCs and macrophages markers. In HHcy mice, McLCs were shifted toward pro-inflammatory phenotype and thus promoted inflammatory response in LC. Betaine supplementation rescued the downregulation of NR5A1 and restored the serum testosterone level in HHcy mice. Overall, our study highlights an etiological role of HHcy in LCs dysfunction.
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Affiliation(s)
- Zhiyuan Su
- The State Key Laboratory of Organ Failure Research, National Clinical Research Center of Kidney Disease, Key Laboratory of Organ Failure Research (Ministry of Education), Division of Nephrology, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, China
| | - Zhuoliang Liu
- The State Key Laboratory of Organ Failure Research, National Clinical Research Center of Kidney Disease, Key Laboratory of Organ Failure Research (Ministry of Education), Division of Nephrology, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, China
| | - Wenjing Lei
- Department of Nephrology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230001, Anhui, China
| | - Kai Xia
- Center for Stem Cell Biology and Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Sun Yat-Sen University, Guangzhou, 510080, Guangdong, China
- National-Local Joint Engineering Research Center for Stem Cells and Regenerative Medicine, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, 510080, Guangdong, China
| | - An Xiao
- The State Key Laboratory of Organ Failure Research, National Clinical Research Center of Kidney Disease, Key Laboratory of Organ Failure Research (Ministry of Education), Division of Nephrology, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, China
| | - Zheng Hu
- The State Key Laboratory of Organ Failure Research, National Clinical Research Center of Kidney Disease, Key Laboratory of Organ Failure Research (Ministry of Education), Division of Nephrology, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, China
| | - Miaomiao Zhou
- The State Key Laboratory of Organ Failure Research, National Clinical Research Center of Kidney Disease, Key Laboratory of Organ Failure Research (Ministry of Education), Division of Nephrology, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, China
| | - Fengxin Zhu
- The State Key Laboratory of Organ Failure Research, National Clinical Research Center of Kidney Disease, Key Laboratory of Organ Failure Research (Ministry of Education), Division of Nephrology, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, China
| | - Jianwei Tian
- The State Key Laboratory of Organ Failure Research, National Clinical Research Center of Kidney Disease, Key Laboratory of Organ Failure Research (Ministry of Education), Division of Nephrology, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, China
| | - Manqiu Yang
- The State Key Laboratory of Organ Failure Research, National Clinical Research Center of Kidney Disease, Key Laboratory of Organ Failure Research (Ministry of Education), Division of Nephrology, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, China
| | - Dong Wang
- Department of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou, 510515, Guangdong, China
| | - Andy Peng Xiang
- Center for Stem Cell Biology and Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Sun Yat-Sen University, Guangzhou, 510080, Guangdong, China
- National-Local Joint Engineering Research Center for Stem Cells and Regenerative Medicine, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, 510080, Guangdong, China
| | - Jing Nie
- The State Key Laboratory of Organ Failure Research, National Clinical Research Center of Kidney Disease, Key Laboratory of Organ Failure Research (Ministry of Education), Division of Nephrology, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, China.
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84
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Rao L, Cai L, Huang L. Single-cell dynamics of liver development in postnatal pigs. Sci Bull (Beijing) 2023; 68:2583-2597. [PMID: 37783617 DOI: 10.1016/j.scib.2023.09.021] [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: 04/24/2023] [Revised: 06/21/2023] [Accepted: 09/14/2023] [Indexed: 10/04/2023]
Abstract
The postnatal development of the liver, an essential organ for metabolism and immunity, remains poorly characterized at the single-cell resolution. Here, we generated single-nucleus and single-cell transcriptomes of 84,824 pig liver cells at four postnatal time points: day 30, 42, 150, and 730. We uncovered 23 cell types, including three rare cell types: plasmacytoid dendritic cells, CAVIN3+IGF2+ endothelial cells, and EBF1+ fibroblasts. The latter two were verified by multiplex immunohistochemistry. Trajectory and gene regulatory analyses revealed 33 genes that encode transcription factors associated with hepatocyte development and function, including NFIL3 involved in regulating hepatic metabolism. We characterized the spatiotemporal heterogeneity of liver endothelial cells, identified and validated leucine zipper protein 2 (LUZP2) as a novel adult liver sinusoidal endothelial cell-specific transcription factor. Lymphoid cells (NK and T cells) governed the immune system of the pig liver since day 30. Furthermore, we identified a cluster of tissue-resident NK cells, which displayed virus defense functions, maintained proliferative features at day 730, and manifested a higher conservative transcription factor expression pattern in humans than in mouse liver. Our study presents the most comprehensive postnatal liver development single-cell atlas and demonstrates the metabolic and immune changes across the four age stages.
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Affiliation(s)
- Lin Rao
- National Key Laboratory for Swine Genetic Improvement and Germplasm Innovation, Ministry of Science and Technology of China, Jiangxi Agricultural University, Nanchang 330045, China.
| | - Liping Cai
- National Key Laboratory for Swine Genetic Improvement and Germplasm Innovation, Ministry of Science and Technology of China, Jiangxi Agricultural University, Nanchang 330045, China
| | - Lusheng Huang
- National Key Laboratory for Swine Genetic Improvement and Germplasm Innovation, Ministry of Science and Technology of China, Jiangxi Agricultural University, Nanchang 330045, China.
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85
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Golino JL, Bian J, Wang X, Fu J, Zhu XB, Yeo J, Kelly M, Escorcia FE, Cam M, Xie C. Single-cell RNA sequencing reveals cancer stem-like cells and dynamics in tumor microenvironment during cholangiocarcinoma progression. Front Cell Dev Biol 2023; 11:1250215. [PMID: 38020927 PMCID: PMC10667919 DOI: 10.3389/fcell.2023.1250215] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Accepted: 10/23/2023] [Indexed: 12/01/2023] Open
Abstract
Cholangiocarcinoma is a malignancy of the bile ducts that is driven by activities of cancer stem-like cells and characterized by a heterogeneous tumor microenvironment. To better understand the transcriptional profiles of cancer stem-like cells and dynamics in the tumor microenvironment during the progression of cholangiocarcinoma, we performed single-cell RNA analysis on cells collected from three different timepoints of tumorigenesis in a YAP/AKT mouse model. Bulk RNA sequencing data from TCGA (The Cancer Genome Atlas program) and ICGC cohorts were used to verify and support the finding. In vitro and in vivo experiments were performed to assess the stemness of cancer stem-like cells. We identified Tm4sf1high malignant cells as cancer stem-like cells. Across timepoints of cholangiocarcinoma formation in YAP/AKT mice, we found dynamic change in cancer stem-like cell/stromal/immune cell composition. Nevertheless, the dynamic interaction among cancer stem-like cells, immune cells, and stromal cells at different timepoints was elaborated. Collectively, these data serve as a useful resource for better understanding cancer stem-like cell and malignant cell heterogeneity, stromal cell remodeling, and immune cell reprogramming. It also sheds new light on transcriptomic dynamics during cholangiocarcinoma progression at single-cell resolution.
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Affiliation(s)
- Jihye L. Golino
- Thoracic and GI Malignancies Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, United States
| | - Jing Bian
- CCR Collaborative Bioinformatics Resource, National Cancer Institute, National Institutes of Health, Bethesda, MD, United States
| | - Xin Wang
- Thoracic and GI Malignancies Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, United States
| | - Jianyang Fu
- Thoracic and GI Malignancies Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, United States
| | - Xiao Bin Zhu
- Thoracic and GI Malignancies Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, United States
| | - Julie Yeo
- Thoracic and GI Malignancies Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, United States
| | - Michael Kelly
- Frederick National Laboratory for Cancer Research, Leidos Biomedical Research, Inc., Frederick, MD, United States
| | - Freddy E. Escorcia
- Molecular Imaging Branch, Radiation Oncology Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, United States
- NCI CCR Liver Cancer Program, Bethesda, MD, United States
| | - Maggie Cam
- CCR Collaborative Bioinformatics Resource, National Cancer Institute, National Institutes of Health, Bethesda, MD, United States
| | - Changqing Xie
- Thoracic and GI Malignancies Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, United States
- NCI CCR Liver Cancer Program, Bethesda, MD, United States
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86
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Xu J, Wang Y, Li P, Chen C, Jiang Z, Wang X, Liu P. PRUNE1 (located on chromosome 1q21.3) promotes multiple myeloma with 1q21 Gain by enhancing the links between purine and mitochondrion. Br J Haematol 2023; 203:599-613. [PMID: 37666675 DOI: 10.1111/bjh.19088] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Revised: 08/05/2023] [Accepted: 08/21/2023] [Indexed: 09/06/2023]
Abstract
Patients with multiple myeloma (MM) with chromosome 1q21 Gain (1q21+) are clinically and biologically heterogeneous. 1q21+ in the real world actually reflects the prognosis for gain/amplification of the CKS1B gene. In this study, we found that the copy number of prune exopolyphosphatase 1 (PRUNE1), located on chromosome 1q21.3, could further stratify the prognosis of MM patients with 1q21+. Using selected reaction monitoring/multiple reaction monitoring (SRM/MRM) analysis, liquid chromatography-tandem mass spectrometry (LC-MS/MS), transmission electron microscopy (TEM), confocal fluorescence microscopy, calculation of adenosine triphosphate (ATP), intracellular reactive oxygen species (ROS) and mitochondrial oxygen consumption rates (OCRs), we demonstrated for the first time that PRUNE1 promotes the proliferation and invasion of MM cells by stimulating purine metabolism, purine synthesis enzymes and mitochondrial functions, enhancing links between purinosomes and mitochondria. SOX11 was identified as a transcription factor for PRUNE1. Through integrated analysis of the transcriptome and proteome, CD73 was determined to be the downstream target of PRUNE1. Furthermore, it has been determined that dipyridamole can effectively suppress the proliferation of MM cells with high-expression levels of PRUNE1 in vitro and in vivo. These findings provide insights into disease-causing mechanisms and new therapeutic targets for MM patients with 1q21+.
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Affiliation(s)
- Jiadai Xu
- Department of Hematology, Zhongshan Hospital, Fudan University, Shanghai, China
- Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Yawen Wang
- Department of Hematology, Zhongshan Hospital, Fudan University, Shanghai, China
- Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Panpan Li
- Department of Hematology, Zhongshan Hospital, Fudan University, Shanghai, China
- Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Chen Chen
- Department of Hematology, Zhongshan Hospital, Fudan University, Shanghai, China
- Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Zhihong Jiang
- Department of Hematology, Zhongshan Hospital (Xiamen), Fudan University, Xiamen, China
| | - Xiaona Wang
- Department of Hematology, Zhongshan Hospital (Xiamen), Fudan University, Xiamen, China
| | - Peng Liu
- Department of Hematology, Zhongshan Hospital, Fudan University, Shanghai, China
- Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, China
- Department of Hematology, Zhongshan Hospital (Xiamen), Fudan University, Xiamen, China
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87
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Han M, Geng J, Zhang S, Rao J, Zhu Y, Xu S, Wang F, Ma F, Zhou M, Zhou H. Invariant natural killer T cells drive hepatic homeostasis in nonalcoholic fatty liver disease via sustained IL-10 expression in CD170 + Kupffer cells. Eur J Immunol 2023; 53:e2350474. [PMID: 37489253 DOI: 10.1002/eji.202350474] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Revised: 07/05/2023] [Accepted: 07/24/2023] [Indexed: 07/26/2023]
Abstract
Kupffer cells (KCs) are liver-resident macrophages involved in hepatic inflammatory responses, including nonalcoholic fatty liver disease (NAFLD) development. However, the contribution of KC subsets to liver inflammation remains unclear. Here, using high-dimensional single-cell RNA sequencing, we characterized murine embryo-derived KCs and identified two KC populations with different gene expression profiles: KC-1 and KC-2. KC-1 expressed CD170, exhibiting immunoreactivity and immune-regulatory abilities, while KC-2 highly expressed lipid metabolism-associated genes. In a high-fat diet-induced NAFLD model, KC-1 cells differentiated into pro-inflammatory phenotypes and initiated more frequent communications with invariant natural killer T (iNKT) cells. In KC-1, interleukin (IL)-10 expression was unaffected by the high-fat diet but impaired by iNKT cell ablation and upregulated by iNKT cell adoptive transfer in vivo. Moreover, in a cellular co-culture system, primary hepatic iNKT cells promoted IL-10 expression in RAW264.7 and primary KC-1 cells. CD206 signal blocking in KC-1 or CD206 knockdown in RAW264.7 cells significantly reduced IL-10 expression. In conclusion, we identified two embryo-derived KC subpopulations with distinct transcriptional profiles. The CD206-mediated crosstalk between iNKT and KC-1 cells maintains IL-10 expression in KC-1 cells, affecting hepatic immune balance. Therefore, KC-based therapeutic strategies must consider cellular heterogeneity and the local immune microenvironment for enhanced specificity and efficiency.
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Affiliation(s)
- Mutian Han
- Department of Immunology, College of Basic Medical Science, Anhui Medical University, Anhui, China
| | - Jinke Geng
- Department of Immunology, College of Basic Medical Science, Anhui Medical University, Anhui, China
| | - Shuangshuang Zhang
- Department of Immunology, College of Basic Medical Science, Anhui Medical University, Anhui, China
| | - Jia Rao
- Department of Immunology, College of Basic Medical Science, Anhui Medical University, Anhui, China
| | - Yansong Zhu
- Department of Cell and Biology, College of Life Sciences, Anhui Medical University, Anhui, China
| | - Shaodong Xu
- Department of Cell and Biology, College of Life Sciences, Anhui Medical University, Anhui, China
| | - Fei Wang
- Department of Immunology, College of Basic Medical Science, Anhui Medical University, Anhui, China
| | - Fang Ma
- Center for Scientific Research, Anhui Medical University, Anhui, China
| | - Meng Zhou
- Department of Cell and Biology, College of Life Sciences, Anhui Medical University, Anhui, China
| | - Hong Zhou
- Department of Immunology, College of Basic Medical Science, Anhui Medical University, Anhui, China
- Department of Cell and Biology, College of Life Sciences, Anhui Medical University, Anhui, China
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88
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Shima Y, Skibbe H, Sasagawa Y, Fujimori N, Iwayama Y, Isomura-Matoba A, Yano M, Ichikawa T, Nikaido I, Hattori N, Kato T. Distinctiveness and continuity in transcriptome and connectivity in the anterior-posterior axis of the paraventricular nucleus of the thalamus. Cell Rep 2023; 42:113309. [PMID: 37862168 DOI: 10.1016/j.celrep.2023.113309] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Revised: 09/20/2023] [Accepted: 10/04/2023] [Indexed: 10/22/2023] Open
Abstract
The paraventricular nucleus of the thalamus (PVT) projects axons to multiple areas, mediates a wide range of behaviors, and exhibits regional heterogeneity in both functions and axonal projections. Still, questions regarding the cell types present in the PVT and the extent of their differences remain inadequately addressed. We applied single-cell RNA sequencing to depict the transcriptomic characteristics of mouse PVT neurons. We found that one of the most significant variances in the PVT transcriptome corresponded to the anterior-posterior axis. While the single-cell transcriptome classified PVT neurons into five types, our transcriptomic and histological analyses showed continuity among the cell types. We discovered that anterior and posterior subpopulations had nearly non-overlapping projection patterns, while another population showed intermediate patterns. In addition, these subpopulations responded differently to appetite-related neuropeptides, with their activation showing opposing effects on food consumption. Our studies unveiled the contrasts and the continuity of PVT neurons that underpin their function.
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Affiliation(s)
- Yasuyuki Shima
- Neurodegenerative Disorders Collaborative Laboratory, RIKEN, Wako, Saitama 351-0198, Japan; Laboratory of Molecular Dynamics of Mental Disorders, RIKEN, Wako, Saitama 351-0198, Japan.
| | - Henrik Skibbe
- Brain Image Analysis Unit, RIKEN, Wako, Saitama 351-0198, Japan
| | - Yohei Sasagawa
- Laboratory for Bioinformatics Research, Center for Biosystems Dynamics Research, RIKEN, Wako, Saitama 351-0198, Japan; Department of Functional Genome Informatics, Division of Biological Data Science, Medical Research Institute, Tokyo Medical and Dental University (TMDU), Hongo, Bunkyo City, Tokyo 113-8519, Japan
| | - Noriko Fujimori
- Laboratory of Molecular Dynamics of Mental Disorders, RIKEN, Wako, Saitama 351-0198, Japan; Support Unit for Bio-Material Analysis, Research Resource Division, Center for Brain Science, RIKEN, Wako, Saitama 351-0198, Japan
| | - Yoshimi Iwayama
- Laboratory for Bioinformatics Research, Center for Biosystems Dynamics Research, RIKEN, Wako, Saitama 351-0198, Japan; Department of Functional Genome Informatics, Division of Biological Data Science, Medical Research Institute, Tokyo Medical and Dental University (TMDU), Hongo, Bunkyo City, Tokyo 113-8519, Japan
| | - Ayako Isomura-Matoba
- Laboratory for Bioinformatics Research, Center for Biosystems Dynamics Research, RIKEN, Wako, Saitama 351-0198, Japan
| | - Minoru Yano
- Department of Functional Genome Informatics, Division of Biological Data Science, Medical Research Institute, Tokyo Medical and Dental University (TMDU), Hongo, Bunkyo City, Tokyo 113-8519, Japan
| | - Takumi Ichikawa
- Laboratory for Bioinformatics Research, Center for Biosystems Dynamics Research, RIKEN, Wako, Saitama 351-0198, Japan; Department of Functional Genome Informatics, Division of Biological Data Science, Medical Research Institute, Tokyo Medical and Dental University (TMDU), Hongo, Bunkyo City, Tokyo 113-8519, Japan
| | - Itoshi Nikaido
- Laboratory for Bioinformatics Research, Center for Biosystems Dynamics Research, RIKEN, Wako, Saitama 351-0198, Japan; Department of Functional Genome Informatics, Division of Biological Data Science, Medical Research Institute, Tokyo Medical and Dental University (TMDU), Hongo, Bunkyo City, Tokyo 113-8519, Japan
| | - Nobutaka Hattori
- Neurodegenerative Disorders Collaborative Laboratory, RIKEN, Wako, Saitama 351-0198, Japan; Department of Neurology, Juntendo University, Hongo, Bunkyo City, Tokyo 113-8421, Japan
| | - Tadafumi Kato
- Laboratory of Molecular Dynamics of Mental Disorders, RIKEN, Wako, Saitama 351-0198, Japan; Department of Psychiatry, Juntendo University, Hongo, Bunkyo City, Tokyo 113-8421, Japan; Department of Molecular Pathology of Mood Disorders, Juntendo University, Hongo, Bunkyo City, Tokyo 113-8421, Japan.
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89
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Zhuang BM, Cao DD, Li TX, Liu XF, Lyu MM, Wang SD, Cui XY, Wang L, Chen XL, Lin XL, Lee CL, Chiu PCN, Yeung WSB, Yao YQ. Single-cell characterization of self-renewing primary trophoblast organoids as modeling of EVT differentiation and interactions with decidual natural killer cells. BMC Genomics 2023; 24:618. [PMID: 37853336 PMCID: PMC10583354 DOI: 10.1186/s12864-023-09690-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Accepted: 09/20/2023] [Indexed: 10/20/2023] Open
Abstract
BACKGROUND Extravillous trophoblast cell (EVT) differentiation and its communication with maternal decidua especially the leading immune cell type natural killer (NK) cell are critical events for placentation. However, appropriate in vitro modelling system and regulatory programs of these two events are still lacking. Recent trophoblast organoid (TO) has advanced the molecular and mechanistic research in placentation. Here, we firstly generated the self-renewing TO from human placental villous and differentiated it into EVTs (EVT-TO) for investigating the differentiation events. We then co-cultured EVT-TO with freshly isolated decidual NKs for further study of cell communication. TO modelling of EVT differentiation as well as EVT interaction with dNK might cast new aspect for placentation research. RESULTS Single-cell RNA sequencing (scRNA-seq) was applied for comprehensive characterization and molecular exploration of TOs modelling of EVT differentiation and interaction with dNKs. Multiple distinct trophoblast states and dNK subpopulations were identified, representing CTB, STB, EVT, dNK1/2/3 and dNKp. Lineage trajectory and Seurat mapping analysis identified the close resemblance of TO and EVT-TO with the human placenta characteristic. Transcription factors regulatory network analysis revealed the cell-type specific essential TFs for controlling EVT differentiation. CellphoneDB analysis predicted the ligand-receptor complexes in dNK-EVT-TO co-cultures, which relate to cytokines, immunomodulation and angiogenesis. EVT was known to affect the immune properties of dNK. Our study found out that on the other way around, dNKs could exert effects on EVT causing expression changes which are functionally important. CONCLUSION Our study documented a single-cell atlas for TO and its applications on EVT differentiation and communications with dNKs, and thus provide methodology and novel research cues for future study of human placentation.
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Affiliation(s)
- Bai-Mei Zhuang
- Shenzhen Key Laboratory of Fertility Regulation, The University of Hong Kong-Shenzhen Hospital, Haiyuan 1st Road, Futian District, Shenzhen, Guangdong, P.R. China
- Medical school of Chinese People's Liberation Army, Chinese People's Liberation Army General Hospital, Beijing, China
| | - Dan-Dan Cao
- Shenzhen Key Laboratory of Fertility Regulation, The University of Hong Kong-Shenzhen Hospital, Haiyuan 1st Road, Futian District, Shenzhen, Guangdong, P.R. China.
| | - Tian-Xi Li
- Geneplus-Shenzhen Institute, Shenzhen, China
| | - Xiao-Feng Liu
- Shenzhen Key Laboratory of Fertility Regulation, The University of Hong Kong-Shenzhen Hospital, Haiyuan 1st Road, Futian District, Shenzhen, Guangdong, P.R. China
| | - Min-Min Lyu
- Department of Clinical-Translational and Basic Research Laboratory, The University of Hong Kong-Shenzhen Hospital, Haiyuan 1st Road, Shenzhen, Futian District, Guangdong, P.R. China
| | - Si-Dong Wang
- Shenzhen Key Laboratory of Fertility Regulation, The University of Hong Kong-Shenzhen Hospital, Haiyuan 1st Road, Futian District, Shenzhen, Guangdong, P.R. China
- Medical school of Chinese People's Liberation Army, Chinese People's Liberation Army General Hospital, Beijing, China
| | - Xin-Yuan Cui
- Shenzhen Key Laboratory of Fertility Regulation, The University of Hong Kong-Shenzhen Hospital, Haiyuan 1st Road, Futian District, Shenzhen, Guangdong, P.R. China
| | - Li Wang
- Department of Obstetrics and Gynecology, Affiliated Shenzhen Maternity & Child Healthcare Hospital, Southern Medical University, Shenzhen, China
| | - Xiao-Lin Chen
- Department of Obstetrics and Gynecology, Affiliated Shenzhen Maternity & Child Healthcare Hospital, Southern Medical University, Shenzhen, China
| | - Xiao-Li Lin
- Department of Obstetrics and Gynecology, Affiliated Shenzhen Maternity & Child Healthcare Hospital, Southern Medical University, Shenzhen, China
| | - Cheuk-Lun Lee
- Shenzhen Key Laboratory of Fertility Regulation, The University of Hong Kong-Shenzhen Hospital, Haiyuan 1st Road, Futian District, Shenzhen, Guangdong, P.R. China
- Department of Obstetrics and Gynecology, LKS Faculty of Medicine, The University of Hong Kong, Pok Fu Lam, Hong Kong S.A.R
| | - Philip C N Chiu
- Shenzhen Key Laboratory of Fertility Regulation, The University of Hong Kong-Shenzhen Hospital, Haiyuan 1st Road, Futian District, Shenzhen, Guangdong, P.R. China
- Department of Obstetrics and Gynecology, LKS Faculty of Medicine, The University of Hong Kong, Pok Fu Lam, Hong Kong S.A.R
| | - William S B Yeung
- Shenzhen Key Laboratory of Fertility Regulation, The University of Hong Kong-Shenzhen Hospital, Haiyuan 1st Road, Futian District, Shenzhen, Guangdong, P.R. China
- Department of Obstetrics and Gynecology, LKS Faculty of Medicine, The University of Hong Kong, Pok Fu Lam, Hong Kong S.A.R
| | - Yuan-Qing Yao
- Shenzhen Key Laboratory of Fertility Regulation, The University of Hong Kong-Shenzhen Hospital, Haiyuan 1st Road, Futian District, Shenzhen, Guangdong, P.R. China.
- Medical school of Chinese People's Liberation Army, Chinese People's Liberation Army General Hospital, Beijing, China.
- Department of Obstetrics and Gynecology, The First Medical Centre, Chinese People's Liberation Army General Hospital, Beijing, China.
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90
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Ma C, Yang C, Peng A, Sun T, Ji X, Mi J, Wei L, Shen S, Feng Q. Pan-cancer spatially resolved single-cell analysis reveals the crosstalk between cancer-associated fibroblasts and tumor microenvironment. Mol Cancer 2023; 22:170. [PMID: 37833788 PMCID: PMC10571470 DOI: 10.1186/s12943-023-01876-x] [Citation(s) in RCA: 92] [Impact Index Per Article: 46.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2023] [Accepted: 10/02/2023] [Indexed: 10/15/2023] Open
Abstract
Cancer-associated fibroblasts (CAFs) are a heterogeneous cell population that plays a crucial role in remodeling the tumor microenvironment (TME). Here, through the integrated analysis of spatial and single-cell transcriptomics data across six common cancer types, we identified four distinct functional subgroups of CAFs and described their spatial distribution characteristics. Additionally, the analysis of single-cell RNA sequencing (scRNA-seq) data from three additional common cancer types and two newly generated scRNA-seq datasets of rare cancer types, namely epithelial-myoepithelial carcinoma (EMC) and mucoepidermoid carcinoma (MEC), expanded our understanding of CAF heterogeneity. Cell-cell interaction analysis conducted within the spatial context highlighted the pivotal roles of matrix CAFs (mCAFs) in tumor angiogenesis and inflammatory CAFs (iCAFs) in shaping the immunosuppressive microenvironment. In patients with breast cancer (BRCA) undergoing anti-PD-1 immunotherapy, iCAFs demonstrated heightened capacity in facilitating cancer cell proliferation, promoting epithelial-mesenchymal transition (EMT), and contributing to the establishment of an immunosuppressive microenvironment. Furthermore, a scoring system based on iCAFs showed a significant correlation with immune therapy response in melanoma patients. Lastly, we provided a web interface ( https://chenxisd.shinyapps.io/pancaf/ ) for the research community to investigate CAFs in the context of pan-cancer.
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Affiliation(s)
- Chenxi Ma
- Department of Human Microbiome and Periodontology and Implantology and Orthodontics, School and Hospital of Stomatology, Cheeloo College of Medicine, Shandong University and Shandong Key Laboratory of Oral Tissue Regeneration and Shandong Engineering Laboratory for Dental Materials and Oral Tissue Regeneration and Shandong Provincial Clinical Research Center for Oral Diseases, Jinan, 250012, China
| | - Chengzhe Yang
- Department of Oral and Maxillofacial Surgery, Qilu Hospital of Shandong University, Jinan, Shandong, China
- Institute of Stomatology, Shandong University, Jinan, Shandong, China
| | - Ai Peng
- Department of Human Microbiome and Periodontology and Implantology and Orthodontics, School and Hospital of Stomatology, Cheeloo College of Medicine, Shandong University and Shandong Key Laboratory of Oral Tissue Regeneration and Shandong Engineering Laboratory for Dental Materials and Oral Tissue Regeneration and Shandong Provincial Clinical Research Center for Oral Diseases, Jinan, 250012, China
| | - Tianyong Sun
- Department of Human Microbiome and Periodontology and Implantology and Orthodontics, School and Hospital of Stomatology, Cheeloo College of Medicine, Shandong University and Shandong Key Laboratory of Oral Tissue Regeneration and Shandong Engineering Laboratory for Dental Materials and Oral Tissue Regeneration and Shandong Provincial Clinical Research Center for Oral Diseases, Jinan, 250012, China
| | - Xiaoli Ji
- Department of Stomatology, Central Hospital Affiliated to Shandong First Medical University, No.105 Jiefang Road, Jinan, Shandong, China
| | - Jun Mi
- Department of Human Microbiome and Periodontology and Implantology and Orthodontics, School and Hospital of Stomatology, Cheeloo College of Medicine, Shandong University and Shandong Key Laboratory of Oral Tissue Regeneration and Shandong Engineering Laboratory for Dental Materials and Oral Tissue Regeneration and Shandong Provincial Clinical Research Center for Oral Diseases, Jinan, 250012, China
| | - Li Wei
- Department of Human Microbiome and Periodontology and Implantology and Orthodontics, School and Hospital of Stomatology, Cheeloo College of Medicine, Shandong University and Shandong Key Laboratory of Oral Tissue Regeneration and Shandong Engineering Laboratory for Dental Materials and Oral Tissue Regeneration and Shandong Provincial Clinical Research Center for Oral Diseases, Jinan, 250012, China
| | - Song Shen
- Department of Human Microbiome and Periodontology and Implantology and Orthodontics, School and Hospital of Stomatology, Cheeloo College of Medicine, Shandong University and Shandong Key Laboratory of Oral Tissue Regeneration and Shandong Engineering Laboratory for Dental Materials and Oral Tissue Regeneration and Shandong Provincial Clinical Research Center for Oral Diseases, Jinan, 250012, China
| | - Qiang Feng
- Department of Human Microbiome and Periodontology and Implantology and Orthodontics, School and Hospital of Stomatology, Cheeloo College of Medicine, Shandong University and Shandong Key Laboratory of Oral Tissue Regeneration and Shandong Engineering Laboratory for Dental Materials and Oral Tissue Regeneration and Shandong Provincial Clinical Research Center for Oral Diseases, Jinan, 250012, China.
- State Key Laboratory of Microbial Technology, Shandong University, Qingdao, 266237, China.
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91
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Zou G, Huang Y, Zhang S, Ko KP, Kim B, Zhang J, Venkatesan V, Pizzi MP, Fan Y, Jun S, Niu N, Wang H, Song S, Ajani JA, Park JI. CDH1 loss promotes diffuse-type gastric cancer tumorigenesis via epigenetic reprogramming and immune evasion. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.23.533976. [PMID: 36993615 PMCID: PMC10055394 DOI: 10.1101/2023.03.23.533976] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Diffuse-type gastric adenocarcinoma (DGAC) is a deadly cancer often diagnosed late and resistant to treatment. While hereditary DGAC is linked to CDH1 gene mutations, causing E-Cadherin loss, its role in sporadic DGAC is unclear. We discovered CDH1 inactivation in a subset of DGAC patient tumors. Analyzing single-cell transcriptomes in malignant ascites, we identified two DGAC subtypes: DGAC1 (CDH1 loss) and DGAC2 (lacking immune response). DGAC1 displayed distinct molecular signatures, activated DGAC-related pathways, and an abundance of exhausted T cells in ascites. Genetically engineered murine gastric organoids showed that Cdh1 knock-out (KO), KrasG12D, Trp53 KO (EKP) accelerates tumorigenesis with immune evasion compared to KrasG12D, Trp53 KO (KP). We also identified EZH2 as a key mediator promoting CDH1 loss-associated DGAC tumorigenesis. These findings highlight DGAC's molecular diversity and potential for personalized treatment in CDH1-inactivated patients.
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Affiliation(s)
- Gengyi Zou
- Department of Experimental Radiation Oncology, Division of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Yuanjian Huang
- Department of Experimental Radiation Oncology, Division of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
- Department of General Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China
| | - Shengzhe Zhang
- Department of Experimental Radiation Oncology, Division of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Kyung-Pil Ko
- Department of Experimental Radiation Oncology, Division of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Bongjun Kim
- Department of Experimental Radiation Oncology, Division of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Jie Zhang
- Department of Experimental Radiation Oncology, Division of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Vishwa Venkatesan
- Department of Experimental Radiation Oncology, Division of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Melissa P. Pizzi
- Department of GI Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Yibo Fan
- Department of GI Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Sohee Jun
- Department of Experimental Radiation Oncology, Division of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Na Niu
- Department of Pathology, Yale School of Medicine, New Haven, CT 06510, USA
| | - Huamin Wang
- Department of Pathology, Division of Pathology/Lab Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Shumei Song
- Department of GI Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Jaffer A. Ajani
- Department of GI Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Jae-Il Park
- Department of Experimental Radiation Oncology, Division of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
- Graduate School of Biomedical Sciences, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
- Program in Genetics and Epigenetics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
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92
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Yang W, Wang P, Luo M, Cai Y, Xu C, Xue G, Jin X, Cheng R, Que J, Pang F, Yang Y, Nie H, Jiang Q, Liu Z, Xu Z. DeepCCI: a deep learning framework for identifying cell-cell interactions from single-cell RNA sequencing data. Bioinformatics 2023; 39:btad596. [PMID: 37740953 PMCID: PMC10558043 DOI: 10.1093/bioinformatics/btad596] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Revised: 08/29/2023] [Accepted: 09/22/2023] [Indexed: 09/25/2023] Open
Abstract
MOTIVATION Cell-cell interactions (CCIs) play critical roles in many biological processes such as cellular differentiation, tissue homeostasis, and immune response. With the rapid development of high throughput single-cell RNA sequencing (scRNA-seq) technologies, it is of high importance to identify CCIs from the ever-increasing scRNA-seq data. However, limited by the algorithmic constraints, current computational methods based on statistical strategies ignore some key latent information contained in scRNA-seq data with high sparsity and heterogeneity. RESULTS Here, we developed a deep learning framework named DeepCCI to identify meaningful CCIs from scRNA-seq data. Applications of DeepCCI to a wide range of publicly available datasets from diverse technologies and platforms demonstrate its ability to predict significant CCIs accurately and effectively. Powered by the flexible and easy-to-use software, DeepCCI can provide the one-stop solution to discover meaningful intercellular interactions and build CCI networks from scRNA-seq data. AVAILABILITY AND IMPLEMENTATION The source code of DeepCCI is available online at https://github.com/JiangBioLab/DeepCCI.
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Affiliation(s)
- Wenyi Yang
- School of Life Science and Technology, Harbin Institute of Technology, Harbin 150006, China
| | - Pingping Wang
- School of Life Science and Technology, Harbin Institute of Technology, Harbin 150006, China
| | - Meng Luo
- School of Life Science and Technology, Harbin Institute of Technology, Harbin 150006, China
| | - Yideng Cai
- School of Life Science and Technology, Harbin Institute of Technology, Harbin 150006, China
| | - Chang Xu
- School of Life Science and Technology, Harbin Institute of Technology, Harbin 150006, China
| | - Guangfu Xue
- School of Life Science and Technology, Harbin Institute of Technology, Harbin 150006, China
| | - Xiyun Jin
- School of Life Science and Technology, Harbin Institute of Technology, Harbin 150006, China
| | - Rui Cheng
- School of Life Science and Technology, Harbin Institute of Technology, Harbin 150006, China
| | - Jinhao Que
- School of Life Science and Technology, Harbin Institute of Technology, Harbin 150006, China
| | - Fenglan Pang
- School of Life Science and Technology, Harbin Institute of Technology, Harbin 150006, China
| | - Yuexin Yang
- School of Life Science and Technology, Harbin Institute of Technology, Harbin 150006, China
| | - Huan Nie
- School of Life Science and Technology, Harbin Institute of Technology, Harbin 150006, China
| | - Qinghua Jiang
- School of Life Science and Technology, Harbin Institute of Technology, Harbin 150006, China
| | - Zhigang Liu
- Affiliated Foshan Maternity & Child Healthcare Hospital, Southern Medical University, Guangzhou 510515, China
| | - Zhaochun Xu
- School of Life Science and Technology, Harbin Institute of Technology, Harbin 150006, China
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93
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Wei X, Fang X, Yu X, Li H, Guo Y, Qi Y, Sun C, Han D, Liu X, Li N, Hu H. Integrative analysis of single-cell embryo data reveals transcriptome signatures for the human pre-implantation inner cell mass. Dev Biol 2023; 502:39-49. [PMID: 37437860 DOI: 10.1016/j.ydbio.2023.07.004] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Revised: 07/05/2023] [Accepted: 07/09/2023] [Indexed: 07/14/2023]
Abstract
As the source of embryonic stem cells (ESCs), inner cell mass (ICM) can form all tissues of the embryo proper, however, its role in early human lineage specification remains controversial. Although a stepwise differentiation model has been proposed suggesting the existence of ICM as a distinct developmental stage, the underlying molecular mechanism remains unclear. In the present study, we perform an integrated analysis on the public human preimplantation embryonic single-cell transcriptomic data and apply a trajectory inference algorithm to measure the cell plasticity. In our results, ICM population can be clearly discriminated on the dimension-reduced graph and confirmed by compelling evidences, thus validating the two-step hypothesis of lineage commitment. According to the branch probabilities and differentiation potential, we determine the precise time points for two lineage segregations. Further analysis on gene expression dynamics and regulatory network indicates that transcription factors including GSC, PRDM1, and SPIC may underlie the decisions of ICM fate. In addition, new human ICM marker genes, such as EPHA4 and CCR8 are discovered and validated by immunofluorescence. Given the potential clinical applications of ESCs, our analysis provides a further understanding of human ICM cells and facilitates the exploration of more unique characteristics in early human development.
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Affiliation(s)
- Xinshu Wei
- School of Medicine, South China University of Technology, Guangzhou, China; Laboratory of Medical Systems Biology, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangdong Provincial Clinical Research Center for Child Health, Guangzhou, 510623, China
| | - Xiang Fang
- Medical Research Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, China
| | - Xiu Yu
- School of Medicine, Jiaying University, Meizhou, 514015, China; Department of Histology and Embryology, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China; Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Sun Yat-sen University, Guangzhou, 510080, China
| | - Hong Li
- Laboratory of Medical Systems Biology, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangdong Provincial Clinical Research Center for Child Health, Guangzhou, 510623, China
| | - Yuyang Guo
- Laboratory of Medical Systems Biology, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangdong Provincial Clinical Research Center for Child Health, Guangzhou, 510623, China
| | - Yifei Qi
- Laboratory of Medical Systems Biology, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangdong Provincial Clinical Research Center for Child Health, Guangzhou, 510623, China
| | - Chuanbo Sun
- Laboratory of Medical Systems Biology, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangdong Provincial Clinical Research Center for Child Health, Guangzhou, 510623, China
| | - Dingding Han
- Department of Clinical Laboratory, Shanghai Children's Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200062, China
| | - Xiaonan Liu
- Department of Assisted Reproductive Technology, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangdong Provincial Clinical Research Center for Child Health, Guangzhou, 510623, China
| | - Na Li
- Laboratory of Medical Systems Biology, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangdong Provincial Clinical Research Center for Child Health, Guangzhou, 510623, China.
| | - Hao Hu
- Laboratory of Medical Systems Biology, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangdong Provincial Clinical Research Center for Child Health, Guangzhou, 510623, China; Provincial Key Laboratory of Research in Structure Birth Defect Disease and Department of Pediatric Surgery, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, 510623, China; Third Affiliatied Hospital of Zhengzhou University, Zhengzhou, China.
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94
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Rexach JE, Cheng Y, Chen L, Polioudakis D, Lin LC, Mitri V, Elkins A, Yin A, Calini D, Kawaguchi R, Ou J, Huang J, Williams C, Robinson J, Gaus SE, Spina S, Lee EB, Grinberg LT, Vinters H, Trojanowski JQ, Seeley WW, Malhotra D, Geschwind DH. Disease-specific selective vulnerability and neuroimmune pathways in dementia revealed by single cell genomics. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.29.560245. [PMID: 37808727 PMCID: PMC10557766 DOI: 10.1101/2023.09.29.560245] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/10/2023]
Abstract
The development of successful therapeutics for dementias requires an understanding of their shared and distinct molecular features in the human brain. We performed single-nuclear RNAseq and ATACseq in Alzheimer disease (AD), Frontotemporal degeneration (FTD), and Progressive Supranuclear Palsy (PSP), analyzing 40 participants, yielding over 1.4M cells from three brain regions ranging in vulnerability and pathological burden. We identify 35 shared disease-associated cell types and 14 that are disease-specific, replicating those previously identified in AD. Disease - specific cell states represent molecular features of disease-specific glial-immune mechanisms and neuronal vulnerability in each disorder, layer 4/5 intra-telencephalic neurons in AD, layer 2/3 intra-telencephalic neurons in FTD, and layer 5/6 near-projection neurons in PSP. We infer intrinsic disease-associated gene regulatory networks, which we empirically validate by chromatin footprinting. We find that causal genetic risk acts in specific neuronal and glial cells that differ across disorders, primarily non-neuronal cells in AD and specific neuronal subtypes in FTD and PSP. These data illustrate the heterogeneous spectrum of glial and neuronal composition and gene expression alterations in different dementias and identify new therapeutic targets by revealing shared and disease-specific cell states.
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95
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Rzasa P, Whelan S, Farahmand P, Cai H, Guterman I, Palacios-Gallego R, Undru SS, Sandford L, Green C, Andreadi C, Mintseva M, Parrott E, Jin H, Hey F, Giblett S, Sylvius NB, Allcock NS, Straatman-Iwanowska A, Feuda R, Tufarelli C, Brown K, Pritchard C, Rufini A. BRAF V600E-mutated serrated colorectal neoplasia drives transcriptional activation of cholesterol metabolism. Commun Biol 2023; 6:962. [PMID: 37735514 PMCID: PMC10514332 DOI: 10.1038/s42003-023-05331-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Accepted: 09/07/2023] [Indexed: 09/23/2023] Open
Abstract
BRAF mutations occur early in serrated colorectal cancers, but their long-term influence on tissue homeostasis is poorly characterized. We investigated the impact of short-term (3 days) and long-term (6 months) expression of BrafV600E in the intestinal tissue of an inducible mouse model. We show that BrafV600E perturbs the homeostasis of intestinal epithelial cells, with impaired differentiation of enterocytes emerging after prolonged expression of the oncogene. Moreover, BrafV600E leads to a persistent transcriptional reprogramming with enrichment of numerous gene signatures indicative of proliferation and tumorigenesis, and signatures suggestive of metabolic rewiring. We focused on the top-ranking cholesterol biosynthesis signature and confirmed its increased expression in human serrated lesions. Functionally, the cholesterol lowering drug atorvastatin prevents the establishment of intestinal crypt hyperplasia in BrafV600E-mutant mice. Overall, our work unveils the long-term impact of BrafV600E expression in intestinal tissue and suggests that colorectal cancers with mutations in BRAF might be prevented by statins.
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Affiliation(s)
- Paulina Rzasa
- Leicester Cancer Research Centre, University of Leicester, Leicester, UK
| | - Sarah Whelan
- Leicester Cancer Research Centre, University of Leicester, Leicester, UK
| | - Pooyeh Farahmand
- Leicester Cancer Research Centre, University of Leicester, Leicester, UK
| | - Hong Cai
- Leicester Cancer Research Centre, University of Leicester, Leicester, UK
| | - Inna Guterman
- Leicester Cancer Research Centre, University of Leicester, Leicester, UK
| | | | - Shanthi S Undru
- Leicester Cancer Research Centre, University of Leicester, Leicester, UK
| | - Lauren Sandford
- Leicester Cancer Research Centre, University of Leicester, Leicester, UK
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK
| | - Caleb Green
- Leicester Cancer Research Centre, University of Leicester, Leicester, UK
| | - Catherine Andreadi
- Leicester Cancer Research Centre, University of Leicester, Leicester, UK
| | - Maria Mintseva
- Leicester Cancer Research Centre, University of Leicester, Leicester, UK
- Area of Neuroscience, International School for Advanced Studies (SISSA), Trieste, Italy
| | - Emma Parrott
- Leicester Cancer Research Centre, University of Leicester, Leicester, UK
| | - Hong Jin
- Leicester Cancer Research Centre, University of Leicester, Leicester, UK
| | - Fiona Hey
- Leicester Cancer Research Centre, University of Leicester, Leicester, UK
| | - Susan Giblett
- Leicester Cancer Research Centre, University of Leicester, Leicester, UK
| | - Nicolas B Sylvius
- NUCLEUS Genomics, Core Biotechnology Services, University of Leicester, Leicester, UK
| | - Natalie S Allcock
- University of Leicester Core Biotechnology Services Electron Microscopy Facility, Leicester, UK
| | | | - Roberto Feuda
- Department of Genetics and Genome Biology, University of Leicester, Leicester, UK
| | - Cristina Tufarelli
- Leicester Cancer Research Centre, University of Leicester, Leicester, UK
| | - Karen Brown
- Leicester Cancer Research Centre, University of Leicester, Leicester, UK
| | - Catrin Pritchard
- Leicester Cancer Research Centre, University of Leicester, Leicester, UK
| | - Alessandro Rufini
- Leicester Cancer Research Centre, University of Leicester, Leicester, UK.
- Dipartimento di Bioscienze, University of Milan, Milan, Italy.
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96
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Wu Z, Liang J, Zhu S, Liu N, Zhao M, Xiao F, Li G, Yu C, Jin C, Ma J, Sun T, Zhu P. Single-cell analysis of graft-infiltrating host cells identifies caspase-1 as a potential therapeutic target for heart transplant rejection. Front Immunol 2023; 14:1251028. [PMID: 37781362 PMCID: PMC10535112 DOI: 10.3389/fimmu.2023.1251028] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Accepted: 08/29/2023] [Indexed: 10/03/2023] Open
Abstract
Aims Understanding the cellular mechanisms underlying early allograft rejection is crucial for the development of effective immunosuppressant strategies. This study aims to investigate the cellular composition of graft-infiltrating cells during the early rejection stage at a single-cell level and identify potential therapeutic targets. Methods A heterotopic heart transplant model was established using enhanced green fluorescent protein (eGFP)-expressing mice as recipients of allogeneic or syngeneic grafts. At 3 days post-transplant, eGFP-positive cells infiltrating the grafts were sorted and subjected to single-cell RNA-seq analysis. Potential molecular targets were evaluated by assessing graft survival and functions following administration of various pharmacological inhibitors. Results A total of 27,053 cells recovered from syngrafts and allografts were classified into 20 clusters based on expression profiles and annotated with a reference dataset. Innate immune cells, including monocytes, macrophages, neutrophils, and dendritic cells, constituted the major infiltrating cell types (>90%) in the grafts. Lymphocytes, fibroblasts, and endothelial cells represented a smaller population. Allografts exhibited significantly increased proportions of monocyte-derived cells involved in antigen processing and presentation, as well as activated lymphocytes, as compared to syngrafts. Differential expression analysis revealed upregulation of interferon activation-related genes in the innate immune cells infiltrating allografts. Pro-inflammatory polarization gene signatures were also enriched in these infiltrating cells of allografts. Gene profiling and intercellular communication analysis identified natural killer cells as the primary source of interferon-γ signaling, activating inflammatory monocytes that displayed strong signals of major histocompatibility complexes and co-stimulatory molecules. The inflammatory response was also associated with promoted T cell proliferation and activation in allografts during the early transplant stages. Notably, caspase-1 exhibited specific upregulation in inflammatory monocytes in response to interferon signaling. The regulon analysis also revealed a significant enrichment of interferon-related motifs within the transcriptional regulatory network of downstream inflammatory genes including caspase-1. Remarkably, pharmacological inhibition of caspase-1 was shown to reduce immune infiltration, prevent acute graft rejection, and improve cardiac contractile function. Conclusion The single-cell transcriptional profile highlighted the crucial role of caspase-1 in interferon-mediated inflammatory monocytes infiltrating heart transplants, suggesting its potential as a therapeutic target for attenuating rejection.
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Affiliation(s)
- Zhichao Wu
- Guangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China
- Guangdong Provincial Key Laboratory of Pathogenesis, Targeted Prevention and Treatment of Heart Disease, Guangzhou Key Laboratory of Cardiac Pathogenesis and Prevention, Guangzhou, Guangdong, China
- Department of Thoracic Surgery, People’s Hospital of Xinjiang Uygur Autonomous Region, Urumqi, Xinjiang, China
| | - Jialiang Liang
- Guangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China
- Guangdong Provincial Key Laboratory of Pathogenesis, Targeted Prevention and Treatment of Heart Disease, Guangzhou Key Laboratory of Cardiac Pathogenesis and Prevention, Guangzhou, Guangdong, China
| | - Shuoji Zhu
- Guangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China
- Guangdong Provincial Key Laboratory of Pathogenesis, Targeted Prevention and Treatment of Heart Disease, Guangzhou Key Laboratory of Cardiac Pathogenesis and Prevention, Guangzhou, Guangdong, China
| | - Nanbo Liu
- Guangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China
- Guangdong Provincial Key Laboratory of Pathogenesis, Targeted Prevention and Treatment of Heart Disease, Guangzhou Key Laboratory of Cardiac Pathogenesis and Prevention, Guangzhou, Guangdong, China
| | - Mingyi Zhao
- Guangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China
- Guangdong Provincial Key Laboratory of Pathogenesis, Targeted Prevention and Treatment of Heart Disease, Guangzhou Key Laboratory of Cardiac Pathogenesis and Prevention, Guangzhou, Guangdong, China
| | - Fei Xiao
- Guangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China
- Guangdong Provincial Key Laboratory of Pathogenesis, Targeted Prevention and Treatment of Heart Disease, Guangzhou Key Laboratory of Cardiac Pathogenesis and Prevention, Guangzhou, Guangdong, China
| | - Guanhua Li
- Guangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China
- Guangdong Provincial Key Laboratory of Pathogenesis, Targeted Prevention and Treatment of Heart Disease, Guangzhou Key Laboratory of Cardiac Pathogenesis and Prevention, Guangzhou, Guangdong, China
| | - Changjiang Yu
- Guangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China
- Guangdong Provincial Key Laboratory of Pathogenesis, Targeted Prevention and Treatment of Heart Disease, Guangzhou Key Laboratory of Cardiac Pathogenesis and Prevention, Guangzhou, Guangdong, China
| | - Chengyu Jin
- Department of Thoracic Surgery, People’s Hospital of Xinjiang Uygur Autonomous Region, Urumqi, Xinjiang, China
| | - Jinshan Ma
- Department of Thoracic Surgery, People’s Hospital of Xinjiang Uygur Autonomous Region, Urumqi, Xinjiang, China
| | - Tucheng Sun
- Guangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China
- Guangdong Provincial Key Laboratory of Pathogenesis, Targeted Prevention and Treatment of Heart Disease, Guangzhou Key Laboratory of Cardiac Pathogenesis and Prevention, Guangzhou, Guangdong, China
| | - Ping Zhu
- Guangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China
- Guangdong Provincial Key Laboratory of Pathogenesis, Targeted Prevention and Treatment of Heart Disease, Guangzhou Key Laboratory of Cardiac Pathogenesis and Prevention, Guangzhou, Guangdong, China
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97
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Dillard LJ, Rosenow WT, Calabrese GM, Mesner LD, Al-Barghouthi BM, Abood A, Farber EA, Onengut-Gumuscu S, Tommasini SM, Horowitz MA, Rosen CJ, Yao L, Qin L, Farber CR. Single-Cell Transcriptomics of Bone Marrow Stromal Cells in Diversity Outbred Mice: A Model for Population-Level scRNA-Seq Studies. J Bone Miner Res 2023; 38:1350-1363. [PMID: 37436066 PMCID: PMC10528806 DOI: 10.1002/jbmr.4882] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Revised: 06/30/2023] [Accepted: 07/06/2023] [Indexed: 07/13/2023]
Abstract
Genome-wide association studies (GWASs) have advanced our understanding of the genetics of osteoporosis; however, the challenge has been converting associations to causal genes. Studies have utilized transcriptomics data to link disease-associated variants to genes, but few population transcriptomics data sets have been generated on bone at the single-cell level. To address this challenge, we profiled the transcriptomes of bone marrow-derived stromal cells (BMSCs) cultured under osteogenic conditions from five diversity outbred (DO) mice using single-cell RNA-seq (scRNA-seq). The goal of the study was to determine if BMSCs could serve as a model to generate cell type-specific transcriptomic profiles of mesenchymal lineage cells from large populations of mice to inform genetic studies. By enriching for mesenchymal lineage cells in vitro, coupled with pooling of multiple samples and downstream genotype deconvolution, we demonstrate the scalability of this model for population-level studies. We demonstrate that dissociation of BMSCs from a heavily mineralized matrix had little effect on viability or their transcriptomic signatures. Furthermore, we show that BMSCs cultured under osteogenic conditions are diverse and consist of cells with characteristics of mesenchymal progenitors, marrow adipogenic lineage precursors (MALPs), osteoblasts, osteocyte-like cells, and immune cells. Importantly, all cells were similar from a transcriptomic perspective to cells isolated in vivo. We employed scRNA-seq analytical tools to confirm the biological identity of profiled cell types. SCENIC was used to reconstruct gene regulatory networks (GRNs), and we observed that cell types show GRNs expected of osteogenic and pre-adipogenic lineage cells. Further, CELLECT analysis showed that osteoblasts, osteocyte-like cells, and MALPs captured a significant component of bone mineral density (BMD) heritability. Together, these data suggest that BMSCs cultured under osteogenic conditions coupled with scRNA-seq can be used as a scalable and biologically informative model to generate cell type-specific transcriptomic profiles of mesenchymal lineage cells in large populations. © 2023 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).
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Affiliation(s)
- Luke J Dillard
- Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville, VA, USA
| | - Will T Rosenow
- Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville, VA, USA
| | - Gina M Calabrese
- Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville, VA, USA
| | - Larry D Mesner
- Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville, VA, USA
- Department of Public Health Sciences, School of Medicine, University of Virginia, Charlottesville, VA, USA
| | - Basel M Al-Barghouthi
- Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville, VA, USA
- Department of Biochemistry and Molecular Genetics, School of Medicine, University of Virginia, Charlottesville, VA, USA
| | - Abdullah Abood
- Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville, VA, USA
- Department of Biochemistry and Molecular Genetics, School of Medicine, University of Virginia, Charlottesville, VA, USA
| | - Emily A Farber
- Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville, VA, USA
| | - Suna Onengut-Gumuscu
- Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville, VA, USA
- Department of Public Health Sciences, School of Medicine, University of Virginia, Charlottesville, VA, USA
| | - Steven M Tommasini
- Department of Orthopaedics and Rehabilitation, Yale School of Medicine, New Haven, CT, USA
| | - Mark A Horowitz
- Department of Orthopaedics and Rehabilitation, Yale School of Medicine, New Haven, CT, USA
| | | | - Lutian Yao
- Department of Orthopaedic Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Ling Qin
- Department of Orthopaedic Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Charles R Farber
- Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville, VA, USA
- Department of Public Health Sciences, School of Medicine, University of Virginia, Charlottesville, VA, USA
- Department of Biochemistry and Molecular Genetics, School of Medicine, University of Virginia, Charlottesville, VA, USA
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98
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Bravo González-Blas C, De Winter S, Hulselmans G, Hecker N, Matetovici I, Christiaens V, Poovathingal S, Wouters J, Aibar S, Aerts S. SCENIC+: single-cell multiomic inference of enhancers and gene regulatory networks. Nat Methods 2023; 20:1355-1367. [PMID: 37443338 PMCID: PMC10482700 DOI: 10.1038/s41592-023-01938-4] [Citation(s) in RCA: 223] [Impact Index Per Article: 111.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2022] [Accepted: 06/06/2023] [Indexed: 07/15/2023]
Abstract
Joint profiling of chromatin accessibility and gene expression in individual cells provides an opportunity to decipher enhancer-driven gene regulatory networks (GRNs). Here we present a method for the inference of enhancer-driven GRNs, called SCENIC+. SCENIC+ predicts genomic enhancers along with candidate upstream transcription factors (TFs) and links these enhancers to candidate target genes. To improve both recall and precision of TF identification, we curated and clustered a motif collection with more than 30,000 motifs. We benchmarked SCENIC+ on diverse datasets from different species, including human peripheral blood mononuclear cells, ENCODE cell lines, melanoma cell states and Drosophila retinal development. Next, we exploit SCENIC+ predictions to study conserved TFs, enhancers and GRNs between human and mouse cell types in the cerebral cortex. Finally, we use SCENIC+ to study the dynamics of gene regulation along differentiation trajectories and the effect of TF perturbations on cell state. SCENIC+ is available at scenicplus.readthedocs.io .
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Affiliation(s)
- Carmen Bravo González-Blas
- VIB Center for Brain & Disease Research, Leuven, Belgium
- Department of Human Genetics, KU Leuven, Leuven, Belgium
| | - Seppe De Winter
- VIB Center for Brain & Disease Research, Leuven, Belgium
- Department of Human Genetics, KU Leuven, Leuven, Belgium
| | - Gert Hulselmans
- VIB Center for Brain & Disease Research, Leuven, Belgium
- Department of Human Genetics, KU Leuven, Leuven, Belgium
| | - Nikolai Hecker
- VIB Center for Brain & Disease Research, Leuven, Belgium
- Department of Human Genetics, KU Leuven, Leuven, Belgium
| | - Irina Matetovici
- VIB Center for Brain & Disease Research, Leuven, Belgium
- VIB Tech Watch, VIB Headquarters, Ghent, Belgium
| | - Valerie Christiaens
- VIB Center for Brain & Disease Research, Leuven, Belgium
- Department of Human Genetics, KU Leuven, Leuven, Belgium
| | | | - Jasper Wouters
- VIB Center for Brain & Disease Research, Leuven, Belgium
- Department of Human Genetics, KU Leuven, Leuven, Belgium
| | - Sara Aibar
- VIB Center for Brain & Disease Research, Leuven, Belgium
- Department of Human Genetics, KU Leuven, Leuven, Belgium
| | - Stein Aerts
- VIB Center for Brain & Disease Research, Leuven, Belgium.
- Department of Human Genetics, KU Leuven, Leuven, Belgium.
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99
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Sun J, Lin Y, Ha N, Zhang J, Wang W, Wang X, Bian Q. Single-cell RNA-Seq reveals transcriptional regulatory networks directing the development of mouse maxillary prominence. J Genet Genomics 2023; 50:676-687. [PMID: 36841529 DOI: 10.1016/j.jgg.2023.02.008] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Revised: 01/15/2023] [Accepted: 02/08/2023] [Indexed: 02/27/2023]
Abstract
During vertebrate embryonic development, neural crest-derived ectomesenchyme within the maxillary prominences undergoes precisely coordinated proliferation and differentiation to give rise to diverse craniofacial structures, such as tooth and palate. However, the transcriptional regulatory networks underpinning such an intricate process have not been fully elucidated. Here, we perform single-cell RNA-Seq to comprehensively characterize the transcriptional dynamics during mouse maxillary development from embryonic day (E) 10.5-E14.5. Our single-cell transcriptome atlas of ∼28,000 cells uncovers mesenchymal cell populations representing distinct differentiating states and reveals their developmental trajectory, suggesting that the segregation of dental from the palatal mesenchyme occurs at E11.5. Moreover, we identify a series of key transcription factors (TFs) associated with mesenchymal fate transitions and deduce the gene regulatory networks directed by these TFs. Collectively, our study provides important resources and insights for achieving a systems-level understanding of craniofacial morphogenesis and abnormality.
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Affiliation(s)
- Jian Sun
- Department of Oral and Cranio-Maxillofacial Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200011, China; National Clinical Research Center for Oral Diseases, Shanghai Key Laboratory of Stomatology, Shanghai Research Institute of Stomatology, Shanghai 200011, China
| | - Yijun Lin
- Department of Oral and Cranio-Maxillofacial Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200011, China; Shanghai Institute of Precision Medicine, Shanghai 200125, China
| | - Nayoung Ha
- Department of Oral and Cranio-Maxillofacial Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200011, China; National Clinical Research Center for Oral Diseases, Shanghai Key Laboratory of Stomatology, Shanghai Research Institute of Stomatology, Shanghai 200011, China
| | - Jianfei Zhang
- Department of Oral and Cranio-Maxillofacial Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200011, China; National Clinical Research Center for Oral Diseases, Shanghai Key Laboratory of Stomatology, Shanghai Research Institute of Stomatology, Shanghai 200011, China
| | - Weiqi Wang
- Department of Oral and Cranio-Maxillofacial Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200011, China; National Clinical Research Center for Oral Diseases, Shanghai Key Laboratory of Stomatology, Shanghai Research Institute of Stomatology, Shanghai 200011, China
| | - Xudong Wang
- Department of Oral and Cranio-Maxillofacial Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200011, China; National Clinical Research Center for Oral Diseases, Shanghai Key Laboratory of Stomatology, Shanghai Research Institute of Stomatology, Shanghai 200011, China.
| | - Qian Bian
- Department of Oral and Cranio-Maxillofacial Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200011, China; Shanghai Institute of Precision Medicine, Shanghai 200125, China; Shanghai Key Laboratory of Reproductive Medicine, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China.
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100
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Wiggins BG, Wang YF, Burke A, Grunberg N, Vlachaki Walker JM, Dore M, Chahrour C, Pennycook BR, Sanchez-Garrido J, Vernia S, Barr AR, Frankel G, Birdsey GM, Randi AM, Schiering C. Endothelial sensing of AHR ligands regulates intestinal homeostasis. Nature 2023; 621:821-829. [PMID: 37586410 PMCID: PMC10533400 DOI: 10.1038/s41586-023-06508-4] [Citation(s) in RCA: 34] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Accepted: 08/02/2023] [Indexed: 08/18/2023]
Abstract
Endothelial cells line the blood and lymphatic vasculature, and act as an essential physical barrier, control nutrient transport, facilitate tissue immunosurveillance and coordinate angiogenesis and lymphangiogenesis1,2. In the intestine, dietary and microbial cues are particularly important in the regulation of organ homeostasis. However, whether enteric endothelial cells actively sense and integrate such signals is currently unknown. Here we show that the aryl hydrocarbon receptor (AHR) acts as a critical node for endothelial cell sensing of dietary metabolites in adult mice and human primary endothelial cells. We first established a comprehensive single-cell endothelial atlas of the mouse small intestine, uncovering the cellular complexity and functional heterogeneity of blood and lymphatic endothelial cells. Analyses of AHR-mediated responses at single-cell resolution identified tissue-protective transcriptional signatures and regulatory networks promoting cellular quiescence and vascular normalcy at steady state. Endothelial AHR deficiency in adult mice resulted in dysregulated inflammatory responses and the initiation of proliferative pathways. Furthermore, endothelial sensing of dietary AHR ligands was required for optimal protection against enteric infection. In human endothelial cells, AHR signalling promoted quiescence and restrained activation by inflammatory mediators. Together, our data provide a comprehensive dissection of the effect of environmental sensing across the spectrum of enteric endothelia, demonstrating that endothelial AHR signalling integrates dietary cues to maintain tissue homeostasis by promoting endothelial cell quiescence and vascular normalcy.
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Affiliation(s)
- Benjamin G Wiggins
- Institute of Clinical Sciences, Faculty of Medicine, Imperial College London, London, UK.
- MRC London Institute of Medical Sciences, London, UK.
| | - Yi-Fang Wang
- MRC London Institute of Medical Sciences, London, UK
| | - Alice Burke
- Institute of Clinical Sciences, Faculty of Medicine, Imperial College London, London, UK
- MRC London Institute of Medical Sciences, London, UK
| | - Nil Grunberg
- Institute of Clinical Sciences, Faculty of Medicine, Imperial College London, London, UK
- MRC London Institute of Medical Sciences, London, UK
| | - Julia M Vlachaki Walker
- Institute of Clinical Sciences, Faculty of Medicine, Imperial College London, London, UK
- MRC London Institute of Medical Sciences, London, UK
| | - Marian Dore
- MRC London Institute of Medical Sciences, London, UK
| | | | - Betheney R Pennycook
- Institute of Clinical Sciences, Faculty of Medicine, Imperial College London, London, UK
- MRC London Institute of Medical Sciences, London, UK
| | | | - Santiago Vernia
- Institute of Clinical Sciences, Faculty of Medicine, Imperial College London, London, UK
- MRC London Institute of Medical Sciences, London, UK
| | - Alexis R Barr
- Institute of Clinical Sciences, Faculty of Medicine, Imperial College London, London, UK
- MRC London Institute of Medical Sciences, London, UK
| | - Gad Frankel
- Department of Life Sciences, Imperial College London, London, UK
| | - Graeme M Birdsey
- National Heart and Lung Institute, Imperial College London, London, UK
| | - Anna M Randi
- National Heart and Lung Institute, Imperial College London, London, UK
| | - Chris Schiering
- Institute of Clinical Sciences, Faculty of Medicine, Imperial College London, London, UK.
- MRC London Institute of Medical Sciences, London, UK.
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