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Wang J, Ye F, Chai H, Jiang Y, Wang T, Ran X, Xia Q, Xu Z, Fu Y, Zhang G, Wu H, Guo G, Guo H, Ruan Y, Wang Y, Xing D, Xu X, Zhang Z. Advances and applications in single-cell and spatial genomics. SCIENCE CHINA. LIFE SCIENCES 2024:10.1007/s11427-024-2770-x. [PMID: 39792333 DOI: 10.1007/s11427-024-2770-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/20/2024] [Accepted: 10/10/2024] [Indexed: 01/12/2025]
Abstract
The applications of single-cell and spatial technologies in recent times have revolutionized the present understanding of cellular states and the cellular heterogeneity inherent in complex biological systems. These advancements offer unprecedented resolution in the examination of the functional genomics of individual cells and their spatial context within tissues. In this review, we have comprehensively discussed the historical development and recent progress in the field of single-cell and spatial genomics. We have reviewed the breakthroughs in single-cell multi-omics technologies, spatial genomics methods, and the computational strategies employed toward the analyses of single-cell atlas data. Furthermore, we have highlighted the advances made in constructing cellular atlases and their clinical applications, particularly in the context of disease. Finally, we have discussed the emerging trends, challenges, and opportunities in this rapidly evolving field.
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Affiliation(s)
- Jingjing Wang
- Bone Marrow Transplantation Center of the First Affiliated Hospital & Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou, 310058, China
| | - Fang Ye
- Bone Marrow Transplantation Center of the First Affiliated Hospital & Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou, 310058, China
| | - Haoxi Chai
- Life Sciences Institute and The Second Affiliated Hospital, Zhejiang University, Hangzhou, 310058, China
| | - Yujia Jiang
- BGI Research, Shenzhen, 518083, China
- BGI Research, Hangzhou, 310030, China
| | - Teng Wang
- Biomedical Pioneering Innovation Center (BIOPIC) and School of Life Sciences, Peking University, Beijing, 100871, China
- Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, 100871, China
| | - Xia Ran
- Bone Marrow Transplantation Center of the First Affiliated Hospital & Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou, 310058, China
- Institute of Hematology, Zhejiang University, Hangzhou, 310000, China
| | - Qimin Xia
- Biomedical Pioneering Innovation Center (BIOPIC) and School of Life Sciences, Peking University, Beijing, 100871, China
| | - Ziye Xu
- Department of Laboratory Medicine of The First Affiliated Hospital & Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou, 310058, China
| | - Yuting Fu
- Bone Marrow Transplantation Center of the First Affiliated Hospital & Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou, 310058, China
- Center for Stem Cell and Regenerative Medicine, Zhejiang University School of Medicine, Hangzhou, 310058, China
| | - Guodong Zhang
- Bone Marrow Transplantation Center of the First Affiliated Hospital & Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou, 310058, China
- Center for Stem Cell and Regenerative Medicine, Zhejiang University School of Medicine, Hangzhou, 310058, China
| | - Hanyu Wu
- Bone Marrow Transplantation Center of the First Affiliated Hospital & Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou, 310058, China
- Center for Stem Cell and Regenerative Medicine, Zhejiang University School of Medicine, Hangzhou, 310058, China
| | - Guoji Guo
- Bone Marrow Transplantation Center of the First Affiliated Hospital & Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou, 310058, China.
- Center for Stem Cell and Regenerative Medicine, Zhejiang University School of Medicine, Hangzhou, 310058, China.
- Zhejiang Provincial Key Lab for Tissue Engineering and Regenerative Medicine, Dr. Li Dak Sum & Yip Yio Chin Center for Stem Cell and Regenerative Medicine, Hangzhou, 310058, China.
- Institute of Hematology, Zhejiang University, Hangzhou, 310000, China.
| | - Hongshan Guo
- Bone Marrow Transplantation Center of the First Affiliated Hospital & Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou, 310058, China.
- Institute of Hematology, Zhejiang University, Hangzhou, 310000, China.
| | - Yijun Ruan
- Life Sciences Institute and The Second Affiliated Hospital, Zhejiang University, Hangzhou, 310058, China.
| | - Yongcheng Wang
- Department of Laboratory Medicine of The First Affiliated Hospital & Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou, 310058, China.
| | - Dong Xing
- Biomedical Pioneering Innovation Center (BIOPIC) and School of Life Sciences, Peking University, Beijing, 100871, China.
- Beijing Advanced Innovation Center for Genomics (ICG), Peking University, Beijing, 100871, China.
| | - Xun Xu
- BGI Research, Shenzhen, 518083, China.
- BGI Research, Hangzhou, 310030, China.
- Guangdong Provincial Key Laboratory of Genome Read and Write, BGI Research, Shenzhen, 518083, China.
| | - Zemin Zhang
- Biomedical Pioneering Innovation Center (BIOPIC) and School of Life Sciences, Peking University, Beijing, 100871, China.
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Chen Y, Liang R, Li Y, Jiang L, Ma D, Luo Q, Song G. Chromatin accessibility: biological functions, molecular mechanisms and therapeutic application. Signal Transduct Target Ther 2024; 9:340. [PMID: 39627201 PMCID: PMC11615378 DOI: 10.1038/s41392-024-02030-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2024] [Revised: 08/04/2024] [Accepted: 10/17/2024] [Indexed: 12/06/2024] Open
Abstract
The dynamic regulation of chromatin accessibility is one of the prominent characteristics of eukaryotic genome. The inaccessible regions are mainly located in heterochromatin, which is multilevel compressed and access restricted. The remaining accessible loci are generally located in the euchromatin, which have less nucleosome occupancy and higher regulatory activity. The opening of chromatin is the most important prerequisite for DNA transcription, replication, and damage repair, which is regulated by genetic, epigenetic, environmental, and other factors, playing a vital role in multiple biological progresses. Currently, based on the susceptibility difference of occupied or free DNA to enzymatic cleavage, solubility, methylation, and transposition, there are many methods to detect chromatin accessibility both in bulk and single-cell level. Through combining with high-throughput sequencing, the genome-wide chromatin accessibility landscape of many tissues and cells types also have been constructed. The chromatin accessibility feature is distinct in different tissues and biological states. Research on the regulation network of chromatin accessibility is crucial for uncovering the secret of various biological processes. In this review, we comprehensively introduced the major functions and mechanisms of chromatin accessibility variation in different physiological and pathological processes, meanwhile, the targeted therapies based on chromatin dynamics regulation are also summarized.
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Affiliation(s)
- Yang Chen
- Key Laboratory of Biorheological Science and Technology, Ministry of Education, College of Bioengineering, Chongqing University, Chongqing, PR China
| | - Rui Liang
- Key Laboratory of Biorheological Science and Technology, Ministry of Education, College of Bioengineering, Chongqing University, Chongqing, PR China
| | - Yong Li
- Hepatobiliary Pancreatic Surgery, Yunnan Cancer Hospital, The Third Affiliated Hospital of Kunming Medical University, Kunming, PR China
| | - Lingli Jiang
- Key Laboratory of Biorheological Science and Technology, Ministry of Education, College of Bioengineering, Chongqing University, Chongqing, PR China
| | - Di Ma
- Key Laboratory of Biorheological Science and Technology, Ministry of Education, College of Bioengineering, Chongqing University, Chongqing, PR China
| | - Qing Luo
- Key Laboratory of Biorheological Science and Technology, Ministry of Education, College of Bioengineering, Chongqing University, Chongqing, PR China
| | - Guanbin Song
- Key Laboratory of Biorheological Science and Technology, Ministry of Education, College of Bioengineering, Chongqing University, Chongqing, PR China.
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Adameyko I, Bakken T, Bhaduri A, Chhatbar C, Filbin MG, Gate D, Hochgerner H, Kim CN, Krull J, La Manno G, Li Q, Linnarsson S, Ma Q, Mayer C, Menon V, Nano P, Prinz M, Quake S, Walsh CA, Yang J, Bayraktar OA, Gokce O, Habib N, Konopka G, Liddelow SA, Nowakowski TJ. Applying single-cell and single-nucleus genomics to studies of cellular heterogeneity and cell fate transitions in the nervous system. Nat Neurosci 2024; 27:2278-2291. [PMID: 39627588 DOI: 10.1038/s41593-024-01827-9] [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: 12/05/2023] [Accepted: 10/22/2024] [Indexed: 12/13/2024]
Abstract
Single-cell and single-nucleus genomic approaches can provide unbiased and multimodal insights. Here, we discuss what constitutes a molecular cell atlas and how to leverage single-cell omics data to generate hypotheses and gain insights into cell transitions in development and disease of the nervous system. We share points of reflection on what to consider during study design and implementation as well as limitations and pitfalls.
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Affiliation(s)
- Igor Adameyko
- Department of Neuroimmunology, Center for Brain Research, Medical University of Vienna, Vienna, Austria
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
| | | | - Aparna Bhaduri
- Department of Biological Chemistry, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Chintan Chhatbar
- Institute of Neuropathology, Medical Faculty, University of Freiburg, Freiburg, Germany
| | - Mariella G Filbin
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Boston Children's Hospital, Boston, MA, USA
| | - David Gate
- The Ken and Ruth Davee Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Hannah Hochgerner
- Faculty of Biotechnology and Food Engineering, Technion Israel Institute of Technology, Haifa, Israel
| | - Chang Nam Kim
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA, USA
- Department of Anatomy, University of California San Francisco, San Francisco, CA, USA
| | - Jordan Krull
- Department of Biomedical Informatics, College of Medicine, the Ohio State University, Columbus, OH, USA
- Pelotonia Institute for Immuno-Oncology, the James Comprehensive Cancer Center, the Ohio State University, Columbus, OH, USA
| | - Gioele La Manno
- Laboratory of Neurodevelopmental Systems Biology, Brain Mind Institute, School of Life Sciences, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Qingyun Li
- Department of Neuroscience, Washington University in St. Louis School of Medicine, St. Louis, MO, USA
- Department of Genetics, Washington University in St. Louis School of Medicine, St. Louis, MO, USA
| | - Sten Linnarsson
- Division of Molecular Neurobiology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
| | - Qin Ma
- Department of Biomedical Informatics, College of Medicine, the Ohio State University, Columbus, OH, USA
- Pelotonia Institute for Immuno-Oncology, the James Comprehensive Cancer Center, the Ohio State University, Columbus, OH, USA
| | - Christian Mayer
- Max Planck Institute for Biological Intelligence, Martinsried, Germany
| | - Vilas Menon
- Department of Neurology, Center for Translational and Computational Neuroimmunology, Columbia University, New York, NY, USA
| | - Patricia Nano
- Department of Biological Chemistry, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Marco Prinz
- Institute of Neuropathology, Medical Faculty, University of Freiburg, Freiburg, Germany
- Signalling Research Centres BIOSS and CIBSS, University of Freiburg, Freiburg, Germany
| | - Steve Quake
- Department of Bioengineering, Stanford University, Stanford, CA, USA
- Department of Applied Physics, Stanford University, Stanford, CA, USA
- Chan Zuckerberg Biohub, San Francisco, CA, USA
| | - Christopher A Walsh
- Division of Genetics and Genomics, Manton Center for Orphan Disease, Boston Children's Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Howard Hughes Medical Institute, Boston Children's Hospital, Boston, MA, USA
| | - Jin Yang
- Department of Neuroscience, Washington University in St. Louis School of Medicine, St. Louis, MO, USA
- Department of Genetics, Washington University in St. Louis School of Medicine, St. Louis, MO, USA
| | | | - Ozgun Gokce
- Department of Old Age Psychiatry and Cognitive Disorders, University Hospital Bonn, Bonn, Germany.
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany.
| | - Naomi Habib
- The Edmond and Lily Safra Center for Brain Sciences, the Hebrew University of Jerusalem, Jerusalem, Israel.
| | - Genevieve Konopka
- Department of Neuroscience, UT Southwestern Medical Center, Dallas, TX, USA.
- Peter O'Donnell Jr. Brain Institute, UT Southwestern Medical Center, Dallas, TX, USA.
| | - Shane A Liddelow
- Neuroscience Institute, NYU Grossman School of Medicine, New York, NY, USA.
- Department of Neuroscience and Physiology, NYU Grossman School of Medicine, New York, NY, USA.
- Parekh Center for Interdisciplinary Neurology, NYU Grossman School of Medicine, New York, NY, USA.
- Department of Ophthalmology, NYU Grossman School of Medicine, New York, NY, USA.
| | - Tomasz J Nowakowski
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA, USA.
- Department of Anatomy, University of California San Francisco, San Francisco, CA, USA.
- Department of Psychiatry and Behavioral Sciences, University of California San Francisco, San Francisco, CA, USA.
- Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA.
- The Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California San Francisco, San Francisco, CA, USA.
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Wu J, Liu Y, Ou L, Gan T, Zhangding Z, Yuan S, Liu X, Liu M, Li J, Yin J, Xin C, Tian Y, Hu J. Transfer of mitochondrial DNA into the nuclear genome during induced DNA breaks. Nat Commun 2024; 15:9438. [PMID: 39487167 PMCID: PMC11530683 DOI: 10.1038/s41467-024-53806-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2024] [Accepted: 10/22/2024] [Indexed: 11/04/2024] Open
Abstract
Mitochondria serve as the cellular powerhouse, and their distinct DNA makes them a prospective target for gene editing to treat genetic disorders. However, the impact of genome editing on mitochondrial DNA (mtDNA) stability remains a mystery. Our study reveals previously unknown risks of genome editing that both nuclear and mitochondrial editing cause discernible transfer of mitochondrial DNA segments into the nuclear genome in various cell types including human cell lines, primary T cells, and mouse embryos. Furthermore, drug-induced mitochondrial stresses and mtDNA breaks exacerbate this transfer of mtDNA into the nuclear genome. Notably, we observe that mitochondrial editors, including mitoTALEN and recently developed base editor DdCBE, can also enhance crosstalk between mtDNA and the nuclear genome. Moreover, we provide a practical solution by co-expressing TREX1 or TREX2 exonucleases during DdCBE editing. These findings imply genome instability of mitochondria during induced DNA breaks and explain the origins of mitochondrial-nuclear DNA segments.
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Affiliation(s)
- Jinchun Wu
- State Key Laboratory of Protein and Plant Gene Research, Genome Editing Research Center, School of Life Sciences, PKU-THU Center for Life Sciences, Peking University, Beijing, China
| | - Yang Liu
- State Key Laboratory of Protein and Plant Gene Research, Genome Editing Research Center, School of Life Sciences, PKU-THU Center for Life Sciences, Peking University, Beijing, China
| | - Liqiong Ou
- State Key Laboratory of Protein and Plant Gene Research, Genome Editing Research Center, School of Life Sciences, PKU-THU Center for Life Sciences, Peking University, Beijing, China
| | - Tingting Gan
- State Key Laboratory of Protein and Plant Gene Research, Genome Editing Research Center, School of Life Sciences, PKU-THU Center for Life Sciences, Peking University, Beijing, China
- Peking University Chengdu Academy for Advanced Interdisciplinary Biotechnologies, Chengdu, Sichuan, China
| | - Zhengrong Zhangding
- State Key Laboratory of Protein and Plant Gene Research, Genome Editing Research Center, School of Life Sciences, PKU-THU Center for Life Sciences, Peking University, Beijing, China
| | - Shaopeng Yuan
- State Key Laboratory of Protein and Plant Gene Research, Genome Editing Research Center, School of Life Sciences, PKU-THU Center for Life Sciences, Peking University, Beijing, China
| | - Xinyi Liu
- State Key Laboratory of Protein and Plant Gene Research, Genome Editing Research Center, School of Life Sciences, PKU-THU Center for Life Sciences, Peking University, Beijing, China
| | - Mengzhu Liu
- State Key Laboratory of Protein and Plant Gene Research, Genome Editing Research Center, School of Life Sciences, PKU-THU Center for Life Sciences, Peking University, Beijing, China
| | - Jiasheng Li
- State Key Laboratory of Molecular Developmental Biology, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Jianhang Yin
- State Key Laboratory of Protein and Plant Gene Research, Genome Editing Research Center, School of Life Sciences, PKU-THU Center for Life Sciences, Peking University, Beijing, China
| | - Changchang Xin
- State Key Laboratory of Protein and Plant Gene Research, Genome Editing Research Center, School of Life Sciences, PKU-THU Center for Life Sciences, Peking University, Beijing, China
| | - Ye Tian
- State Key Laboratory of Molecular Developmental Biology, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Jiazhi Hu
- State Key Laboratory of Protein and Plant Gene Research, Genome Editing Research Center, School of Life Sciences, PKU-THU Center for Life Sciences, Peking University, Beijing, China.
- Peking University Chengdu Academy for Advanced Interdisciplinary Biotechnologies, Chengdu, Sichuan, China.
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5
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Penter L, Cieri N, Maurer K, Kwok M, Lyu H, Lu WS, Oliveira G, Gohil SH, Leshchiner I, Lareau CA, Ludwig LS, Neuberg DS, Kim HT, Li S, Bullinger L, Ritz J, Getz G, Garcia JS, Soiffer RJ, Livak KJ, Wu CJ. Tracking Rare Single Donor and Recipient Immune and Leukemia Cells after Allogeneic Hematopoietic Cell Transplantation Using Mitochondrial DNA Mutations. Blood Cancer Discov 2024; 5:442-459. [PMID: 39236287 PMCID: PMC11528187 DOI: 10.1158/2643-3230.bcd-23-0138] [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: 08/01/2023] [Revised: 06/30/2024] [Accepted: 09/03/2024] [Indexed: 09/07/2024] Open
Abstract
Combined tracking of clonal evolution and chimeric cell phenotypes could enable detection of the key cellular populations associated with response following therapy, including after allogeneic hematopoietic stem cell transplantation (HSCT). We demonstrate that mitochondrial DNA (mtDNA) mutations coevolve with somatic nuclear DNA mutations at relapse post-HSCT and provide a sensitive means to monitor these cellular populations. Furthermore, detection of mtDNA mutations via single-cell assay for transposase-accessible chromatin with select antigen profiling by sequencing (ASAP-seq) simultaneously determines not only donor and recipient cells but also their phenotype at frequencies of 0.1% to 1%. Finally, integration of mtDNA mutations, surface markers, and chromatin accessibility profiles enables the phenotypic resolution of leukemic populations from normal immune cells, thereby providing fresh insights into residual donor-derived engraftment and short-term clonal evolution following therapy for post-transplant leukemia relapse. As throughput evolves, we envision future development of single-cell sequencing-based post-transplant monitoring as a powerful approach for guiding clinical decision-making. Significance: mtDNA mutations enable single-cell tracking of leukemic clonal evolution and donor-recipient origin following allogeneic HSCT. This provides unprecedented insight into chimeric cellular phenotypes of early immune reconstitution, incipient relapse, and quality of donor engraftment with immediate translational potential for future clinical post-transplant monitoring and decision-making.
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Affiliation(s)
- Livius Penter
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, Massachusetts
- Harvard Medical School, Boston, Massachusetts
- Department of Hematology, Oncology, and Tumorimmunology, Campus Virchow Klinikum, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
- Berlin Institute of Health at Charité–Universitätsmedizin Berlin, BIH Biomedical Innovation Academy, BIH Charité Digital Clinician Scientist Program, Berlin, Germany
| | - Nicoletta Cieri
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, Massachusetts
- Harvard Medical School, Boston, Massachusetts
| | - Katie Maurer
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, Massachusetts
- Harvard Medical School, Boston, Massachusetts
| | - Marwan Kwok
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, Massachusetts
- Harvard Medical School, Boston, Massachusetts
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, United Kingdom
| | - Haoxiang Lyu
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Translational Immunogenomics Lab, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Wesley S. Lu
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Translational Immunogenomics Lab, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Giacomo Oliveira
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, Massachusetts
- Harvard Medical School, Boston, Massachusetts
| | - Satyen H. Gohil
- Department of Haematology, University College London Hospitals, London, United Kingdom
| | - Ignaty Leshchiner
- Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, Massachusetts
| | - Caleb A. Lareau
- Memorial Sloan Kettering Cancer Center, New York City, New York
| | - Leif S. Ludwig
- Department of Hematology, Oncology, and Tumorimmunology, Campus Virchow Klinikum, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
- Berlin Institute of Health at Charité Universitätsmedizin Berlin, Berlin, Germany
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association, Berlin Institute for Medical Systems Biology, Berlin, Germany
| | - Donna S. Neuberg
- Department of Data Science, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Haesook T. Kim
- Department of Data Science, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Shuqiang Li
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Translational Immunogenomics Lab, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Lars Bullinger
- Department of Hematology, Oncology, and Tumorimmunology, Campus Virchow Klinikum, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Jerome Ritz
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
| | - Gad Getz
- Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, Massachusetts
- Harvard Medical School, Boston, Massachusetts
| | - Jacqueline S. Garcia
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
| | - Robert J. Soiffer
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
| | - Kenneth J. Livak
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Translational Immunogenomics Lab, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Catherine J. Wu
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, Massachusetts
- Harvard Medical School, Boston, Massachusetts
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6
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Liang S, Li C, Ning Y, Su R, Li M, Huang Y, Zou Y, Yang L, Xu X, Yang C. DMF-Bimol: Counting mRNA and Protein Molecules in Single Cells with Digital Microfluidics. Anal Chem 2024; 96:17253-17261. [PMID: 39428609 DOI: 10.1021/acs.analchem.4c03277] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2024]
Abstract
Analyzing single-cell protein and mRNA levels yields invaluable insights into cellular functions and the intricacies of biologically heterogeneous systems. Current joint mRNAs and protein analysis methodologies suffer from relative quantification, low sensitivity, possible background interference, and tedious manual manipulation. Therefore, we propose DMF-Bimol that leverages addressable digital microfluidics to automate digital counting of single-cell mRNA and protein based on proximity ligation assay (PLA) and one-step RT-droplet digital PCR (RT-ddPCR). Through an engineered hydrophilic-hydrophobic interface, DMF-Bimol enables efficient single-cell isolation and lossless protein and nucleic acid processing. The closed droplet reaction system enhances the protein concentration and isolates exogenous contaminants, thereby dramatically improving the efficiency of the PLA reaction. The limit of detection of this approach achieves 3313 protein copies, marking a significant 17-fold enhancement in sensitivity over traditional benchtop PLA. This heightened sensitivity also uncovers a lower correlation between mRNA and protein levels in individual cells (Spearman r = 0.255) than bulk results, reflecting the complex relationship in heterogeneous cells. Using DMF-Bimol, we observed a significant upsurge of CD147 protein in CD138+ myeloma cells but consistent levels of CD147 mRNAs compared with normal leukocytes. This discovery indicates a possible consequence of CD147 oncogenic activation that tends to harness protein translation to bolster tumor cell survival and enhance invasiveness, highlighting the potential of DMF-Bimol in unveiling intricate dynamics in translation processes at the single-cell level.
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Affiliation(s)
- Shanshan Liang
- Collaborative Innovation Center of Chemistry for Energy Materials, the MOE Key Laboratory of Spectrochemical Analysis and Instrumentation, State Key Laboratory of Physical Chemistry of Solid Surfaces, Department of Hematology, The First Affiliated Hospital of Xiamen University and Institute of Hematology, School of Medicine, Xiamen University, Xiamen 361005, China
| | - Chong Li
- Collaborative Innovation Center of Chemistry for Energy Materials, the MOE Key Laboratory of Spectrochemical Analysis and Instrumentation, State Key Laboratory of Physical Chemistry of Solid Surfaces, Department of Hematology, The First Affiliated Hospital of Xiamen University and Institute of Hematology, School of Medicine, Xiamen University, Xiamen 361005, China
| | - Yu Ning
- Collaborative Innovation Center of Chemistry for Energy Materials, the MOE Key Laboratory of Spectrochemical Analysis and Instrumentation, State Key Laboratory of Physical Chemistry of Solid Surfaces, Department of Hematology, The First Affiliated Hospital of Xiamen University and Institute of Hematology, School of Medicine, Xiamen University, Xiamen 361005, China
| | - Rui Su
- Collaborative Innovation Center of Chemistry for Energy Materials, the MOE Key Laboratory of Spectrochemical Analysis and Instrumentation, State Key Laboratory of Physical Chemistry of Solid Surfaces, Department of Hematology, The First Affiliated Hospital of Xiamen University and Institute of Hematology, School of Medicine, Xiamen University, Xiamen 361005, China
| | - Mingyin Li
- Collaborative Innovation Center of Chemistry for Energy Materials, the MOE Key Laboratory of Spectrochemical Analysis and Instrumentation, State Key Laboratory of Physical Chemistry of Solid Surfaces, Department of Hematology, The First Affiliated Hospital of Xiamen University and Institute of Hematology, School of Medicine, Xiamen University, Xiamen 361005, China
| | - Yihao Huang
- Collaborative Innovation Center of Chemistry for Energy Materials, the MOE Key Laboratory of Spectrochemical Analysis and Instrumentation, State Key Laboratory of Physical Chemistry of Solid Surfaces, Department of Hematology, The First Affiliated Hospital of Xiamen University and Institute of Hematology, School of Medicine, Xiamen University, Xiamen 361005, China
| | - Yuning Zou
- Collaborative Innovation Center of Chemistry for Energy Materials, the MOE Key Laboratory of Spectrochemical Analysis and Instrumentation, State Key Laboratory of Physical Chemistry of Solid Surfaces, Department of Hematology, The First Affiliated Hospital of Xiamen University and Institute of Hematology, School of Medicine, Xiamen University, Xiamen 361005, China
| | - Liu Yang
- Collaborative Innovation Center of Chemistry for Energy Materials, the MOE Key Laboratory of Spectrochemical Analysis and Instrumentation, State Key Laboratory of Physical Chemistry of Solid Surfaces, Department of Hematology, The First Affiliated Hospital of Xiamen University and Institute of Hematology, School of Medicine, Xiamen University, Xiamen 361005, China
| | - Xing Xu
- Collaborative Innovation Center of Chemistry for Energy Materials, the MOE Key Laboratory of Spectrochemical Analysis and Instrumentation, State Key Laboratory of Physical Chemistry of Solid Surfaces, Department of Hematology, The First Affiliated Hospital of Xiamen University and Institute of Hematology, School of Medicine, Xiamen University, Xiamen 361005, China
- Department of Laboratory Medicine, Key Laboratory of Clinical Laboratory Technology for Precision Medicine, School of Medical Technology and Engineering Fujian Medical University, Fuzhou 350005, China
| | - Chaoyong Yang
- Collaborative Innovation Center of Chemistry for Energy Materials, the MOE Key Laboratory of Spectrochemical Analysis and Instrumentation, State Key Laboratory of Physical Chemistry of Solid Surfaces, Department of Hematology, The First Affiliated Hospital of Xiamen University and Institute of Hematology, School of Medicine, Xiamen University, Xiamen 361005, China
- Institute of Molecular Medicine, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200127, China
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7
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Fu Y, Land M, Cui R, Kavlashvili T, Kim M, Lieber T, Ryu KW, DeBitetto E, Masilionis I, Saha R, Takizawa M, Baker D, Tigano M, Reznik E, Sharma R, Chaligne R, Thompson CB, Pe'er D, Sfeir A. Engineering mtDNA Deletions by Reconstituting End-Joining in Human Mitochondria. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.10.15.618543. [PMID: 39463974 PMCID: PMC11507875 DOI: 10.1101/2024.10.15.618543] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/29/2024]
Abstract
Recent breakthroughs in the genetic manipulation of mitochondrial DNA (mtDNA) have enabled the precise introduction of base substitutions and the effective removal of genomes carrying harmful mutations. However, the reconstitution of mtDNA deletions responsible for severe mitochondrial myopathies and age-related diseases has not yet been achieved in human cells. Here, we developed a method to engineer specific mtDNA deletions in human cells by co-expressing end-joining (EJ) machinery and targeted endonucleases. As a proof-of-concept, we used mito-EJ and mito-ScaI to generate a panel of clonal cell lines harboring a ∼3.5 kb mtDNA deletion with the full spectrum of heteroplasmy. Investigating these isogenic cells revealed a critical threshold of ∼75% deleted genomes, beyond which cells exhibited depletion of OXPHOS proteins, severe metabolic disruption, and impaired growth in galactose-containing media. Single-cell multiomic analysis revealed two distinct patterns of nuclear gene deregulation in response to mtDNA deletion accumulation; one triggered at the deletion threshold and another progressively responding to increasing heteroplasmy. In summary, the co-expression of mito-EJ and programable nucleases provides a powerful tool to model disease-associated mtDNA deletions in different cell types. Establishing a panel of cell lines with a large-scale deletion at varying levels of heteroplasmy is a valuable resource for understanding the impact of mtDNA deletions on diseases and guiding the development of potential therapeutic strategies. Highlights Combining prokaryotic end-joining with targeted endonucleases generates specific mtDNA deletions in human cellsEngineering a panel of cell lines with a large-scale deletion that spans the full spectrum of heteroplasmy75% heteroplasmy is the threshold that triggers mitochondrial and cellular dysfunctionTwo distinct nuclear transcriptional programs in response to mtDNA deletions: threshold-triggered and heteroplasmy-sensing.
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8
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Zhang A, Liu W, Qiu S. Mitochondrial genetic variations in leukemia: a comprehensive overview. BLOOD SCIENCE 2024; 6:e00205. [PMID: 39247535 PMCID: PMC11379488 DOI: 10.1097/bs9.0000000000000205] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2024] [Accepted: 08/13/2024] [Indexed: 09/10/2024] Open
Abstract
Leukemias are a group of heterogeneous hematological malignancies driven by diverse genetic variations, and the advent of genomic sequencing technologies facilitates the investigation of genetic abnormalities in leukemia. However, these sequencing-based studies mainly focus on nuclear DNAs. Increasing evidence indicates that mitochondrial dysfunction is an important mechanism of leukemia pathogenesis, which is closely related to the mitochondrial genome variations. Here, we provide an overview of current research progress concerning mitochondrial genetic variations in leukemia, encompassing gene mutations and copy number variations. We also summarize currently accessible mitochondrial DNA (mtDNA) sequencing methods. Notably, somatic mtDNA mutations may serve as natural genetic barcodes for lineage tracing and longitudinal assessment of clonal dynamics. Collectively, these findings enhance our understanding of leukemia pathogenesis and foster the identification of novel therapeutic targets and interventions.
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Affiliation(s)
- Ao Zhang
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China
- Tianjin Institutes of Health Science, Tianjin, China
| | - Wenbing Liu
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China
- Tianjin Institutes of Health Science, Tianjin, China
| | - Shaowei Qiu
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China
- Tianjin Institutes of Health Science, Tianjin, China
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9
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Zhou X, Lin L. Mechanisms and therapeutic target of anti-tumour treatment-related Ferroptosis: How to improve cancer therapy? Biomed Pharmacother 2024; 179:117323. [PMID: 39208665 DOI: 10.1016/j.biopha.2024.117323] [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: 07/21/2024] [Revised: 08/19/2024] [Accepted: 08/21/2024] [Indexed: 09/04/2024] Open
Abstract
Recently, increased attention has been focused on the regulatory mechanism and potential clinical application of ferroptosis in cancer cells, especially therapy-related ferroptosis. However, the mechanism of treatment-related ferroptosis and the application prospects and strategies for future treatment still require further clarification. This review highlights the molecular relationships between different clinical antitumour drugs, including commonly used chemotherapy drugs, radiation therapy and vitamins, and ferroptosis. This review also proposes strategies for future treatments that involve ferroptosis, with an aim to develop a new strategy for the transformative potential of the emerging field of ferroptosis to improve cancer therapy.
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Affiliation(s)
- Xiangyu Zhou
- Department of General Surgery, Fourth Affiliated Hospital of China Medical University, Shenyang, China
| | - Lin Lin
- Department of General Surgery, Fourth Affiliated Hospital of China Medical University, Shenyang, China.
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10
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Jin X, Zhang R, Fu Y, Zhu Q, Hong L, Wu A, Wang H. Unveiling aging dynamics in the hematopoietic system insights from single-cell technologies. Brief Funct Genomics 2024; 23:639-650. [PMID: 38688725 DOI: 10.1093/bfgp/elae019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2024] [Revised: 04/10/2024] [Accepted: 04/15/2024] [Indexed: 05/02/2024] Open
Abstract
As the demographic structure shifts towards an aging society, strategies aimed at slowing down or reversing the aging process become increasingly essential. Aging is a major predisposing factor for many chronic diseases in humans. The hematopoietic system, comprising blood cells and their associated bone marrow microenvironment, intricately participates in hematopoiesis, coagulation, immune regulation and other physiological phenomena. The aging process triggers various alterations within the hematopoietic system, serving as a spectrum of risk factors for hematopoietic disorders, including clonal hematopoiesis, immune senescence, myeloproliferative neoplasms and leukemia. The emerging single-cell technologies provide novel insights into age-related changes in the hematopoietic system. In this review, we summarize recent studies dissecting hematopoietic system aging using single-cell technologies. We discuss cellular changes occurring during aging in the hematopoietic system at the levels of the genomics, transcriptomics, epigenomics, proteomics, metabolomics and spatial multi-omics. Finally, we contemplate the future prospects of single-cell technologies, emphasizing the impact they may bring to the field of hematopoietic system aging research.
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Affiliation(s)
- Xinrong Jin
- Zhejiang Key Laboratory of Medical Epigenetics, School of Basic Medical Sciences, The Third People's Hospital of Deqing, Deqing Hospital of Hangzhou Normal University, Hangzhou Normal University, Hangzhou 311121, China
| | - Ruohan Zhang
- Zhejiang Key Laboratory of Medical Epigenetics, School of Basic Medical Sciences, The Third People's Hospital of Deqing, Deqing Hospital of Hangzhou Normal University, Hangzhou Normal University, Hangzhou 311121, China
| | - Yunqi Fu
- Zhejiang Key Laboratory of Medical Epigenetics, School of Basic Medical Sciences, The Third People's Hospital of Deqing, Deqing Hospital of Hangzhou Normal University, Hangzhou Normal University, Hangzhou 311121, China
| | - Qiunan Zhu
- Zhejiang Key Laboratory of Medical Epigenetics, School of Basic Medical Sciences, The Third People's Hospital of Deqing, Deqing Hospital of Hangzhou Normal University, Hangzhou Normal University, Hangzhou 311121, China
| | - Liquan Hong
- Zhejiang Key Laboratory of Medical Epigenetics, School of Basic Medical Sciences, The Third People's Hospital of Deqing, Deqing Hospital of Hangzhou Normal University, Hangzhou Normal University, Hangzhou 311121, China
| | - Aiwei Wu
- Zhejiang Key Laboratory of Medical Epigenetics, School of Basic Medical Sciences, The Third People's Hospital of Deqing, Deqing Hospital of Hangzhou Normal University, Hangzhou Normal University, Hangzhou 311121, China
| | - Hu Wang
- Zhejiang Key Laboratory of Medical Epigenetics, School of Basic Medical Sciences, The Third People's Hospital of Deqing, Deqing Hospital of Hangzhou Normal University, Hangzhou Normal University, Hangzhou 311121, China
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11
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An J, Nam CH, Kim R, Lee Y, Won H, Park S, Lee WH, Park H, Yoon CJ, An Y, Kim JH, Jun JK, Bae JM, Shin EC, Kim B, Cha YJ, Kwon HW, Oh JW, Park JY, Kim MJ, Ju YS. Mitochondrial DNA mosaicism in normal human somatic cells. Nat Genet 2024; 56:1665-1677. [PMID: 39039280 PMCID: PMC11319206 DOI: 10.1038/s41588-024-01838-z] [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: 11/12/2023] [Accepted: 06/21/2024] [Indexed: 07/24/2024]
Abstract
Somatic cells accumulate genomic alterations with age; however, our understanding of mitochondrial DNA (mtDNA) mosaicism remains limited. Here we investigated the genomes of 2,096 clones derived from three cell types across 31 donors, identifying 6,451 mtDNA variants with heteroplasmy levels of ≳0.3%. While the majority of these variants were unique to individual clones, suggesting stochastic acquisition with age, 409 variants (6%) were shared across multiple embryonic lineages, indicating their origin from heteroplasmy in fertilized eggs. The mutational spectrum exhibited replication-strand bias, implicating mtDNA replication as a major mutational process. We evaluated the mtDNA mutation rate (5.0 × 10-8 per base pair) and a turnover frequency of 10-20 per year, which are fundamental components shaping the landscape of mtDNA mosaicism over a lifetime. The expansion of mtDNA-truncating mutations toward homoplasmy was substantially suppressed. Our findings provide comprehensive insights into the origins, dynamics and functional consequences of mtDNA mosaicism in human somatic cells.
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Affiliation(s)
- Jisong An
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea
| | - Chang Hyun Nam
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea
| | - Ryul Kim
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea
- Inocras Inc, Daejeon, Republic of Korea
| | - Yunah Lee
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea
| | - Hyein Won
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea
| | - Seongyeol Park
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea
- Inocras Inc, Daejeon, Republic of Korea
| | - Won Hee Lee
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea
| | - Hansol Park
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea
- Inocras Inc, Daejeon, Republic of Korea
| | - Christopher J Yoon
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea
- Department of Medicine, Washington University School of Medicine, St. Louis, MO, USA
| | - Yohan An
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea
| | - Jie-Hyun Kim
- Department of Internal Medicine, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Jong Kwan Jun
- Department of Obstetrics and Gynecology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Jeong Mo Bae
- Department of Pathology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Eui-Cheol Shin
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea
| | - Bun Kim
- Center for Colorectal Cancer, Research Institute and Hospital, National Cancer Center, Goyang, Republic of Korea
| | - Yong Jun Cha
- Center for Colorectal Cancer, Research Institute and Hospital, National Cancer Center, Goyang, Republic of Korea
| | - Hyun Woo Kwon
- Department of Nuclear Medicine, Korea University College of Medicine, Seoul, Republic of Korea
| | - Ji Won Oh
- Department of Anatomy, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Jee Yoon Park
- Department of Obstetrics and Gynecology, Seoul National University Bundang Hospital, Seongnam, Republic of Korea
- Department of Obstetrics and Gynecology, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Min Jung Kim
- Department of Surgery, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Young Seok Ju
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea.
- Inocras Inc, Daejeon, Republic of Korea.
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12
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Nitsch L, Lareau CA, Ludwig LS. Mitochondrial genetics through the lens of single-cell multi-omics. Nat Genet 2024; 56:1355-1365. [PMID: 38951641 PMCID: PMC11260401 DOI: 10.1038/s41588-024-01794-8] [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: 09/17/2023] [Accepted: 05/09/2024] [Indexed: 07/03/2024]
Abstract
Mitochondria carry their own genetic information encoding for a subset of protein-coding genes and translational machinery essential for cellular respiration and metabolism. Despite its small size, the mitochondrial genome, its natural genetic variation and molecular phenotypes have been challenging to study using bulk sequencing approaches, due to its variation in cellular copy number, non-Mendelian modes of inheritance and propensity for mutations. Here we highlight emerging strategies designed to capture mitochondrial genetic variation across individual cells for lineage tracing and studying mitochondrial genetics in primary human cells and clinical specimens. We review recent advances surrounding single-cell mitochondrial genome sequencing and its integration with functional genomic readouts, including leveraging somatic mitochondrial DNA mutations as clonal markers that can resolve cellular population dynamics in complex human tissues. Finally, we discuss how single-cell whole mitochondrial genome sequencing approaches can be utilized to investigate mitochondrial genetics and its contribution to cellular heterogeneity and disease.
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Affiliation(s)
- Lena Nitsch
- Berlin Institute of Health at Charité Universitätsmedizin Berlin, Berlin, Germany
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association, Berlin Institute for Medical Systems Biology, Berlin, Germany
- Department of Biology, Chemistry, Pharmacy, Freie Universität Berlin, Berlin, Germany
| | - Caleb A Lareau
- Computational and Systems Biology Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
| | - Leif S Ludwig
- Berlin Institute of Health at Charité Universitätsmedizin Berlin, Berlin, Germany.
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association, Berlin Institute for Medical Systems Biology, Berlin, Germany.
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13
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Liao X, Scheidereit E, Kuppe C. New tools to study renal fibrogenesis. Curr Opin Nephrol Hypertens 2024; 33:420-426. [PMID: 38587103 PMCID: PMC11139246 DOI: 10.1097/mnh.0000000000000988] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/09/2024]
Abstract
PURPOSE OF REVIEW Kidney fibrosis is a key pathological aspect and outcome of chronic kidney disease (CKD). The advent of multiomic analyses using human kidney tissue, enabled by technological advances, marks a new chapter of discovery in fibrosis research of the kidney. This review highlights the rapid advancements of single-cell and spatial multiomic techniques that offer new avenues for exploring research questions related to human kidney fibrosis development. RECENT FINDINGS We recently focused on understanding the origin and transition of myofibroblasts in kidney fibrosis using single-cell RNA sequencing (scRNA-seq) [1] . We analysed cells from healthy human kidneys and compared them to patient samples with CKD. We identified PDGFRα+/PDGFRβ+ mesenchymal cells as the primary cellular source of extracellular matrix (ECM) in human kidney fibrosis. We found several commonly shared cell states of fibroblasts and myofibroblasts and provided insights into molecular regulators. Novel single-cell and spatial multiomics tools are now available to shed light on cell lineages, the plasticity of kidney cells and cell-cell communication in fibrosis. SUMMARY As further single-cell and spatial multiomic approaches are being developed, opportunities to apply these methods to human kidney tissues expand similarly. Careful design and optimisation of the multiomic experiments are needed to answer questions related to cell lineages, plasticity and cell-cell communication in kidney fibrosis.
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Affiliation(s)
- Xian Liao
- Division of Nephrology and Clinical Immunology, RWTH Aachen University, Aachen, Germany
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14
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Sashittal P, Chen V, Pasarkar A, Raphael BJ. Joint inference of cell lineage and mitochondrial evolution from single-cell sequencing data. Bioinformatics 2024; 40:i218-i227. [PMID: 38940122 PMCID: PMC11211840 DOI: 10.1093/bioinformatics/btae231] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/29/2024] Open
Abstract
MOTIVATION Eukaryotic cells contain organelles called mitochondria that have their own genome. Most cells contain thousands of mitochondria which replicate, even in nondividing cells, by means of a relatively error-prone process resulting in somatic mutations in their genome. Because of the higher mutation rate compared to the nuclear genome, mitochondrial mutations have been used to track cellular lineage, particularly using single-cell sequencing that measures mitochondrial mutations in individual cells. However, existing methods to infer the cell lineage tree from mitochondrial mutations do not model "heteroplasmy," which is the presence of multiple mitochondrial clones with distinct sets of mutations in an individual cell. Single-cell sequencing data thus provide a mixture of the mitochondrial clones in individual cells, with the ancestral relationships between these clones described by a mitochondrial clone tree. While deconvolution of somatic mutations from a mixture of evolutionarily related genomes has been extensively studied in the context of bulk sequencing of cancer tumor samples, the problem of mitochondrial deconvolution has the additional constraint that the mitochondrial clone tree must be concordant with the cell lineage tree. RESULTS We formalize the problem of inferring a concordant pair of a mitochondrial clone tree and a cell lineage tree from single-cell sequencing data as the Nested Perfect Phylogeny Mixture (NPPM) problem. We derive a combinatorial characterization of the solutions to the NPPM problem, and formulate an algorithm, MERLIN, to solve this problem exactly using a mixed integer linear program. We show on simulated data that MERLIN outperforms existing methods that do not model mitochondrial heteroplasmy nor the concordance between the mitochondrial clone tree and the cell lineage tree. We use MERLIN to analyze single-cell whole-genome sequencing data of 5220 cells of a gastric cancer cell line and show that MERLIN infers a more biologically plausible cell lineage tree and mitochondrial clone tree compared to existing methods. AVAILABILITY AND IMPLEMENTATION https://github.com/raphael-group/MERLIN.
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Affiliation(s)
- Palash Sashittal
- Department of Computer Science, Princeton University, Princeton, NJ 08540, United States
| | - Viola Chen
- Department of Computer Science, Princeton University, Princeton, NJ 08540, United States
| | - Amey Pasarkar
- Department of Computer Science, Princeton University, Princeton, NJ 08540, United States
| | - Benjamin J Raphael
- Department of Computer Science, Princeton University, Princeton, NJ 08540, United States
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15
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Li F, Xiang R, Liu Y, Hu G, Jiang Q, Jia T. Approaches and challenges in identifying, quantifying, and manipulating dynamic mitochondrial genome variations. Cell Signal 2024; 117:111123. [PMID: 38417637 DOI: 10.1016/j.cellsig.2024.111123] [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: 12/07/2023] [Revised: 02/14/2024] [Accepted: 02/25/2024] [Indexed: 03/01/2024]
Abstract
Mitochondria, the cellular powerhouses, possess their own unique genetic system, including replication, transcription, and translation. Studying these processes is crucial for comprehending mitochondrial disorders, energy production, and their related diseases. Over the past decades, various approaches have been applied in detecting and quantifying mitochondrial genome variations with also the purpose of manipulation of mitochondria or mitochondrial genome for therapeutics. Understanding the scope and limitations of above strategies is not only fundamental to the understanding of basic biology but also critical for exploring disease-related novel target(s), as well to develop innovative therapies. Here, this review provides an overview of different tools and techniques for accurate mitochondrial genome variations identification, quantification, and discuss novel strategies for the manipulation of mitochondria to develop innovative therapeutic interventions, through combining the insights gained from the study of mitochondrial genetics with ongoing single cell omics combined with advanced single molecular tools.
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Affiliation(s)
- Fei Li
- Key Laboratory of Drug-Targeting and Drug Delivery System of the Education Ministry and Sichuan Province, Sichuan Engineering Laboratory for Plant-Sourced Drug and Sichuan Research Center for Drug Precision Industrial Technology, West China School of Pharmacy, Sichuan University, Chengdu 610041, China
| | - Run Xiang
- Key Laboratory of Drug-Targeting and Drug Delivery System of the Education Ministry and Sichuan Province, Sichuan Engineering Laboratory for Plant-Sourced Drug and Sichuan Research Center for Drug Precision Industrial Technology, West China School of Pharmacy, Sichuan University, Chengdu 610041, China; Department of Thoracic Surgery, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of China, Chengdu, China
| | - Yue Liu
- Key Laboratory of Drug-Targeting and Drug Delivery System of the Education Ministry and Sichuan Province, Sichuan Engineering Laboratory for Plant-Sourced Drug and Sichuan Research Center for Drug Precision Industrial Technology, West China School of Pharmacy, Sichuan University, Chengdu 610041, China
| | - Guoliang Hu
- Key Laboratory of Drug-Targeting and Drug Delivery System of the Education Ministry and Sichuan Province, Sichuan Engineering Laboratory for Plant-Sourced Drug and Sichuan Research Center for Drug Precision Industrial Technology, West China School of Pharmacy, Sichuan University, Chengdu 610041, China; Department of Thoracic Surgery, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of China, Chengdu, China
| | - Quanbo Jiang
- Light, Nanomaterials, Nanotechnologies (L2n) Laboratory, CNRS EMR 7004, University of Technology of Troyes, 12 rue Marie Curie, 10004 Troyes, France
| | - Tao Jia
- Key Laboratory of Drug-Targeting and Drug Delivery System of the Education Ministry and Sichuan Province, Sichuan Engineering Laboratory for Plant-Sourced Drug and Sichuan Research Center for Drug Precision Industrial Technology, West China School of Pharmacy, Sichuan University, Chengdu 610041, China; CNRS-UMR9187, INSERM U1196, PSL-Research University, 91405 Orsay, France; CNRS-UMR9187, INSERM U1196, Université Paris Saclay, 91405 Orsay, France.
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16
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Isaac RS, Tullius TW, Hansen KG, Dubocanin D, Couvillion M, Stergachis AB, Churchman LS. Single-nucleoid architecture reveals heterogeneous packaging of mitochondrial DNA. Nat Struct Mol Biol 2024; 31:568-577. [PMID: 38347148 PMCID: PMC11370055 DOI: 10.1038/s41594-024-01225-6] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Accepted: 01/09/2024] [Indexed: 03/03/2024]
Abstract
Cellular metabolism relies on the regulation and maintenance of mitochondrial DNA (mtDNA). Hundreds to thousands of copies of mtDNA exist in each cell, yet because mitochondria lack histones or other machinery important for nuclear genome compaction, it remains unresolved how mtDNA is packaged into individual nucleoids. In this study, we used long-read single-molecule accessibility mapping to measure the compaction of individual full-length mtDNA molecules at near single-nucleotide resolution. We found that, unlike the nuclear genome, human mtDNA largely undergoes all-or-none global compaction, with most nucleoids existing in an inaccessible, inactive state. Highly accessible mitochondrial nucleoids are co-occupied by transcription and replication components and selectively form a triple-stranded displacement loop structure. In addition, we showed that the primary nucleoid-associated protein TFAM directly modulates the fraction of inaccessible nucleoids both in vivo and in vitro, acting consistently with a nucleation-and-spreading mechanism to coat and compact mitochondrial nucleoids. Together, these findings reveal the primary architecture of mtDNA packaging and regulation in human cells.
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Affiliation(s)
- R Stefan Isaac
- Department of Genetics, Blavatnik Institute, Harvard Medical School, Boston, MA, USA
| | - Thomas W Tullius
- Department of Genetics, Blavatnik Institute, Harvard Medical School, Boston, MA, USA
| | - Katja G Hansen
- Department of Genetics, Blavatnik Institute, Harvard Medical School, Boston, MA, USA
| | - Danilo Dubocanin
- Division of Medical Genetics, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Mary Couvillion
- Department of Genetics, Blavatnik Institute, Harvard Medical School, Boston, MA, USA
| | - Andrew B Stergachis
- Division of Medical Genetics, Department of Medicine, University of Washington, Seattle, WA, USA.
- Department of Genome Sciences, University of Washington, Seattle, WA, USA.
| | - L Stirling Churchman
- Department of Genetics, Blavatnik Institute, Harvard Medical School, Boston, MA, USA.
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17
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Li K, Chen X, Song S, Hou L, Chen S, Jiang R. Cofea: correlation-based feature selection for single-cell chromatin accessibility data. Brief Bioinform 2023; 25:bbad458. [PMID: 38113078 PMCID: PMC10782922 DOI: 10.1093/bib/bbad458] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Revised: 11/19/2023] [Accepted: 11/20/2023] [Indexed: 12/21/2023] Open
Abstract
Single-cell chromatin accessibility sequencing (scCAS) technologies have enabled characterizing the epigenomic heterogeneity of individual cells. However, the identification of features of scCAS data that are relevant to underlying biological processes remains a significant gap. Here, we introduce a novel method Cofea, to fill this gap. Through comprehensive experiments on 5 simulated and 54 real datasets, Cofea demonstrates its superiority in capturing cellular heterogeneity and facilitating downstream analysis. Applying this method to identification of cell type-specific peaks and candidate enhancers, as well as pathway enrichment analysis and partitioned heritability analysis, we illustrate the potential of Cofea to uncover functional biological process.
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Affiliation(s)
- Keyi Li
- Ministry of Education Key Laboratory of Bioinformatics, Bioinformatics Division at the Beijing National Research Center for Information Science and Technology, Center for Synthetic and Systems Biology, Department of Automation, Tsinghua University, Beijing 100084, China
| | - Xiaoyang Chen
- Ministry of Education Key Laboratory of Bioinformatics, Bioinformatics Division at the Beijing National Research Center for Information Science and Technology, Center for Synthetic and Systems Biology, Department of Automation, Tsinghua University, Beijing 100084, China
| | - Shuang Song
- Center for Statistical Science, Department of Industrial Engineering, Tsinghua University, Beijing 100084, China
| | - Lin Hou
- Center for Statistical Science, Department of Industrial Engineering, Tsinghua University, Beijing 100084, China
| | - Shengquan Chen
- School of Mathematical Sciences and LPMC, Nankai University, Tianjin 300071, China
| | - Rui Jiang
- Ministry of Education Key Laboratory of Bioinformatics, Bioinformatics Division at the Beijing National Research Center for Information Science and Technology, Center for Synthetic and Systems Biology, Department of Automation, Tsinghua University, Beijing 100084, China
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18
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Tao Y, He C, Lin D, Gu Z, Pu W. Comprehensive Identification of Mitochondrial Pseudogenes (NUMTs) in the Human Telomere-to-Telomere Reference Genome. Genes (Basel) 2023; 14:2092. [PMID: 38003036 PMCID: PMC10671835 DOI: 10.3390/genes14112092] [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: 09/28/2023] [Revised: 11/09/2023] [Accepted: 11/12/2023] [Indexed: 11/26/2023] Open
Abstract
Practices related to mitochondrial research have long been hindered by the presence of mitochondrial pseudogenes within the nuclear genome (NUMTs). Even though partially assembled human reference genomes like hg38 have included NUMTs compilation, the exhaustive NUMTs within the only complete reference genome (T2T-CHR13) remain unknown. Here, we comprehensively identified the fixed NUMTs within the reference genome using human pan-mitogenome (HPMT) from GeneBank. The inclusion of HPMT serves the purpose of establishing an authentic mitochondrial DNA (mtDNA) mutational spectrum for the identification of NUMTs, distinguishing it from the polymorphic variations found in NUMTs. Using HPMT, we identified approximately 10% of additional NUMTs in three human reference genomes under stricter thresholds. And we also observed an approximate 6% increase in NUMTs in T2T-CHR13 compared to hg38, including NUMTs on the short arms of chromosomes 13, 14, and 15 that were not assembled previously. Furthermore, alignments based on 20-mer from mtDNA suggested the presence of more mtDNA-like short segments within the nuclear genome, which should be avoided for short amplicon or cell free mtDNA detection. Finally, through the assay of transposase-accessible chromatin with high-throughput sequencing (ATAC-seq) on cell lines before and after mtDNA elimination, we concluded that NUMTs have a minimal impact on bulk ATAC-seq, even though 16% of sequencing data originated from mtDNA.
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Affiliation(s)
- Yichen Tao
- MOE Key Laboratory of Contemporary Anthropology, School of Life Sciences, Fudan University, Shanghai 200438, China; (Y.T.); (D.L.)
| | - Chengpeng He
- Greater Bay Area Institute of Precision Medicine (Guangzhou), Fudan University, Nansha District, Guangzhou 511458, China;
| | - Deng Lin
- MOE Key Laboratory of Contemporary Anthropology, School of Life Sciences, Fudan University, Shanghai 200438, China; (Y.T.); (D.L.)
| | - Zhenglong Gu
- MOE Key Laboratory of Contemporary Anthropology, School of Life Sciences, Fudan University, Shanghai 200438, China; (Y.T.); (D.L.)
- Greater Bay Area Institute of Precision Medicine (Guangzhou), Fudan University, Nansha District, Guangzhou 511458, China;
| | - Weilin Pu
- Greater Bay Area Institute of Precision Medicine (Guangzhou), Fudan University, Nansha District, Guangzhou 511458, China;
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Yazdani M, Mach L, Noseda M. Single cell RNA sequencing sheds light on infiltrating T cells in idiopathic inflammatory myopathies. EMBO Mol Med 2023; 15:e18190. [PMID: 37768011 PMCID: PMC10565633 DOI: 10.15252/emmm.202318190] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Revised: 09/08/2023] [Accepted: 09/08/2023] [Indexed: 09/29/2023] Open
Abstract
Idiopathic inflammatory myopathies (IIM), also referred to as "myositis," are a group of heterogeneous autoimmune disorders characterised by muscle weakness, atrophy and progressive reduced mobility (Lundberg et al, 2021). IIM represent a significant health burden in adult populations, affecting individuals at a mean age of 50 with an estimated prevalence of 2.9-34 per 100,000 (Dobloug et al, 2015; Svensson et al, 2017). IIM encompass several subtypes including dermatomyositis, immune-mediated necrotising myopathy, inclusion-body myositis, antisynthetase syndrome and polymyositis, which are characterised by specific clinical features, histopathological findings and autoantibody status (Pinal-Fernandez et al, 2020).
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Affiliation(s)
- Momina Yazdani
- National Heart and Lung InstituteImperial College LondonLondonUK
| | - Lukas Mach
- National Heart and Lung InstituteImperial College LondonLondonUK
| | - Michela Noseda
- National Heart and Lung InstituteImperial College LondonLondonUK
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20
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Zhang H, Yu X, Ye J, Li H, Hu J, Tan Y, Fang Y, Akbay E, Yu F, Weng C, Sankaran VG, Bachoo RM, Maher E, Minna J, Zhang A, Li B. Systematic investigation of mitochondrial transfer between cancer cells and T cells at single-cell resolution. Cancer Cell 2023; 41:1788-1802.e10. [PMID: 37816332 PMCID: PMC10568073 DOI: 10.1016/j.ccell.2023.09.003] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/24/2023] [Revised: 06/27/2023] [Accepted: 09/05/2023] [Indexed: 10/12/2023]
Abstract
Mitochondria (MT) participate in most metabolic activities of mammalian cells. A near-unidirectional mitochondrial transfer from T cells to cancer cells was recently observed to "metabolically empower" cancer cells while "depleting immune cells," providing new insights into tumor-T cell interaction and immune evasion. Here, we leverage single-cell RNA-seq technology and introduce MERCI, a statistical deconvolution method for tracing and quantifying mitochondrial trafficking between cancer and T cells. Through rigorous benchmarking and validation, MERCI accurately predicts the recipient cells and their relative mitochondrial compositions. Application of MERCI to human cancer samples identifies a reproducible MT transfer phenotype, with its signature genes involved in cytoskeleton remodeling, energy production, and TNF-α signaling pathways. Moreover, MT transfer is associated with increased cell cycle activity and poor clinical outcome across different cancer types. In summary, MERCI enables systematic investigation of an understudied aspect of tumor-T cell interactions that may lead to the development of therapeutic opportunities.
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Affiliation(s)
- Hongyi Zhang
- Lyda Hill Department of Bioinformatics, UT Southwestern Medical Center, Dallas, TX 75390, USA; Center for Computational and Genomic Medicine, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Xuexin Yu
- Lyda Hill Department of Bioinformatics, UT Southwestern Medical Center, Dallas, TX 75390, USA; Center for Computational and Genomic Medicine, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Jianfeng Ye
- Lyda Hill Department of Bioinformatics, UT Southwestern Medical Center, Dallas, TX 75390, USA
| | - Huiyu Li
- Hamon Center for Therapeutic Oncology Research, UT Southwestern Medical Center, Dallas, TX 75390, USA
| | - Jing Hu
- Lyda Hill Department of Bioinformatics, UT Southwestern Medical Center, Dallas, TX 75390, USA; Center for Computational and Genomic Medicine, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Yuhao Tan
- Lyda Hill Department of Bioinformatics, UT Southwestern Medical Center, Dallas, TX 75390, USA
| | - Yan Fang
- Department of Molecular Biology, UT Southwestern Medical Center, Dallas, TX 75390, USA
| | - Esra Akbay
- Department of Pathology, UT Southwestern Medical Center, Dallas, TX 75390, USA
| | - Fulong Yu
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA
| | - Chen Weng
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA
| | - Vijay G Sankaran
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA
| | - Robert M Bachoo
- Department of Neurology and Neurotherapeutics, UT Southwestern Medical Center, Dallas, TX 75390, USA
| | - Elizabeth Maher
- Department of Neurology and Neurotherapeutics, UT Southwestern Medical Center, Dallas, TX 75390, USA
| | - John Minna
- Hamon Center for Therapeutic Oncology Research, UT Southwestern Medical Center, Dallas, TX 75390, USA
| | - Anli Zhang
- Lyda Hill Department of Bioinformatics, UT Southwestern Medical Center, Dallas, TX 75390, USA.
| | - Bo Li
- Lyda Hill Department of Bioinformatics, UT Southwestern Medical Center, Dallas, TX 75390, USA; Center for Computational and Genomic Medicine, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
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21
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Taylor L, Walsh S, Ashton A, Varga N, Kapoor S, George C, Jagannath A. The Mycoplasma hyorhinis genome displays differential chromatin accessibility. Heliyon 2023; 9:e17362. [PMID: 37389046 PMCID: PMC10300207 DOI: 10.1016/j.heliyon.2023.e17362] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2023] [Revised: 06/09/2023] [Accepted: 06/14/2023] [Indexed: 07/01/2023] Open
Abstract
Whilst the regulation of chromatin accessibility and its effect on gene expression have been well studied in eukaryotic species, the role of chromatin dynamics and 3D organisation in genome reduced bacteria remains poorly understood [1,2]. In this study we profiled the accessibility of the Mycoplasma hyorhinis genome, these data were collected fortuitously as part of an experiment where ATAC-Seq was conducted on mycoplasma, contaminated mammalian cells. We found a differential and highly reproducible chromatin accessibility landscape, with regions of increased accessibility corresponding to genes important for the bacteria's life cycle and infectivity. Furthermore, accessibility in general correlated with transcriptionally active genes as profiled by RNA-Seq, but peaks of high accessibility were also seen in non-coding and intergenic regions, which could contribute to the topological organisation of the genome. However, changes in transcription induced by starvation or application of the RNA polymerase inhibitor rifampicin did not themselves change the accessibility profile, which confirms that the differential accessibility is inherently a property of the genome, and not a consequence of its function. These results together show that differential chromatin accessibility is a key feature of the regulation of gene expression in bacteria.
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Affiliation(s)
- Lewis Taylor
- Sleep and Circadian Neuroscience Institute (SCNi), Nuffield Department of Clinical Neurosciences, University of Oxford, New Biochemistry Building, , South Parks Road, Oxford, OX1 3QU, UK
| | - Steven Walsh
- Sleep and Circadian Neuroscience Institute (SCNi), Nuffield Department of Clinical Neurosciences, University of Oxford, New Biochemistry Building, , South Parks Road, Oxford, OX1 3QU, UK
| | - Anna Ashton
- Sleep and Circadian Neuroscience Institute (SCNi), Nuffield Department of Clinical Neurosciences, University of Oxford, New Biochemistry Building, , South Parks Road, Oxford, OX1 3QU, UK
| | - Norbert Varga
- Sleep and Circadian Neuroscience Institute (SCNi), Nuffield Department of Clinical Neurosciences, University of Oxford, New Biochemistry Building, , South Parks Road, Oxford, OX1 3QU, UK
| | - Sejal Kapoor
- Sleep and Circadian Neuroscience Institute (SCNi), Nuffield Department of Clinical Neurosciences, University of Oxford, New Biochemistry Building, , South Parks Road, Oxford, OX1 3QU, UK
| | - Charlotte George
- MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, John Radcliffe Hospital, Oxford, OX3 9DU, UK
| | - Aarti Jagannath
- Sleep and Circadian Neuroscience Institute (SCNi), Nuffield Department of Clinical Neurosciences, University of Oxford, New Biochemistry Building, , South Parks Road, Oxford, OX1 3QU, UK
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