51
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Cai S, Li H, Tie R, Shan W, Luo Q, Wang S, Feng C, Chen H, Zhang M, Xu Y, Li X, Chen M, Lu J, Qian P, Huang H. Nlrc3 signaling is indispensable for hematopoietic stem cell emergence via Notch signaling in vertebrates. Nat Commun 2024; 15:226. [PMID: 38172511 PMCID: PMC10764762 DOI: 10.1038/s41467-023-44251-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2022] [Accepted: 12/06/2023] [Indexed: 01/05/2024] Open
Abstract
Hematopoietic stem and progenitor cells generate all the lineages of blood cells throughout the lifespan of vertebrates. The emergence of hematopoietic stem and progenitor cells is finely tuned by a variety of signaling pathways. Previous studies have revealed the roles of pattern-recognition receptors such as Toll-like receptors and RIG-I-like receptors in hematopoiesis. In this study, we find that Nlrc3, a nucleotide-binding domain leucine-rich repeat containing family gene, is highly expressed in hematopoietic differentiation stages in vivo and vitro and is required in hematopoiesis in zebrafish. Mechanistically, nlrc3 activates the Notch pathway and the downstream gene of Notch hey1. Furthermore, NF-kB signaling acts upstream of nlrc3 to enhance its transcriptional activity. Finally, we find that Nlrc3 signaling is conserved in the regulation of murine embryonic hematopoiesis. Taken together, our findings uncover an indispensable role of Nlrc3 signaling in hematopoietic stem and progenitor cell emergence and provide insights into inflammation-related hematopoietic ontogeny and the in vitro expansion of hematopoietic stem and progenitor cells.
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Affiliation(s)
- Shuyang Cai
- Bone Marrow Transplantation Center, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Liangzhu Laboratory, Zhejiang University Medical Center, Hangzhou, China
- Institute of Hematology, Zhejiang University, Hangzhou, China
- Zhejiang Engineering Laboratory for Stem Cell and Immunotherapy, Hangzhou, China
- Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Honghu Li
- Bone Marrow Transplantation Center, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Liangzhu Laboratory, Zhejiang University Medical Center, Hangzhou, China
- Institute of Hematology, Zhejiang University, Hangzhou, China
- Zhejiang Engineering Laboratory for Stem Cell and Immunotherapy, Hangzhou, China
| | - Ruxiu Tie
- Bone Marrow Transplantation Center, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Liangzhu Laboratory, Zhejiang University Medical Center, Hangzhou, China
- Institute of Hematology, Zhejiang University, Hangzhou, China
- Zhejiang Engineering Laboratory for Stem Cell and Immunotherapy, Hangzhou, China
- Department of Hematology, the Second Clinical Medical College, Shanxi Medical University, Taiyuan, China
- Department of Hematology, Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University, Linhai, China
| | - Wei Shan
- Bone Marrow Transplantation Center, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Liangzhu Laboratory, Zhejiang University Medical Center, Hangzhou, China
- Institute of Hematology, Zhejiang University, Hangzhou, China
- Zhejiang Engineering Laboratory for Stem Cell and Immunotherapy, Hangzhou, China
| | - Qian Luo
- Bone Marrow Transplantation Center, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Liangzhu Laboratory, Zhejiang University Medical Center, Hangzhou, China
- Institute of Hematology, Zhejiang University, Hangzhou, China
- Zhejiang Engineering Laboratory for Stem Cell and Immunotherapy, Hangzhou, China
| | - Shufen Wang
- Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Cong Feng
- Department of Bioinformatics, College of Life Sciences, Zhejiang University, Hangzhou, China
- Bioinformatics Center, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Huiqiao Chen
- Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Meng Zhang
- Bone Marrow Transplantation Center, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Liangzhu Laboratory, Zhejiang University Medical Center, Hangzhou, China
- Institute of Hematology, Zhejiang University, Hangzhou, China
- Zhejiang Engineering Laboratory for Stem Cell and Immunotherapy, Hangzhou, China
| | - Yulin Xu
- Bone Marrow Transplantation Center, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Liangzhu Laboratory, Zhejiang University Medical Center, Hangzhou, China
- Institute of Hematology, Zhejiang University, Hangzhou, China
- Zhejiang Engineering Laboratory for Stem Cell and Immunotherapy, Hangzhou, China
| | - Xia Li
- Bone Marrow Transplantation Center, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Liangzhu Laboratory, Zhejiang University Medical Center, Hangzhou, China
- Institute of Hematology, Zhejiang University, Hangzhou, China
- Zhejiang Engineering Laboratory for Stem Cell and Immunotherapy, Hangzhou, China
| | - Ming Chen
- Department of Bioinformatics, College of Life Sciences, Zhejiang University, Hangzhou, China
- Bioinformatics Center, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Jiahui Lu
- Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
| | - Pengxu Qian
- Liangzhu Laboratory, Zhejiang University Medical Center, Hangzhou, China.
- Institute of Hematology, Zhejiang University, Hangzhou, China.
- Zhejiang Engineering Laboratory for Stem Cell and Immunotherapy, Hangzhou, China.
- Center for Stem Cell and Regenerative Medicine and Bone Marrow Transplantation Center of the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
| | - He Huang
- Bone Marrow Transplantation Center, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
- Liangzhu Laboratory, Zhejiang University Medical Center, Hangzhou, China.
- Institute of Hematology, Zhejiang University, Hangzhou, China.
- Zhejiang Engineering Laboratory for Stem Cell and Immunotherapy, Hangzhou, China.
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52
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Zhang Y, Liu F. The evolving views of hematopoiesis: from embryo to adulthood and from in vivo to in vitro. J Genet Genomics 2024; 51:3-15. [PMID: 37734711 DOI: 10.1016/j.jgg.2023.09.005] [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: 08/23/2023] [Revised: 09/13/2023] [Accepted: 09/13/2023] [Indexed: 09/23/2023]
Abstract
The hematopoietic system composed of hematopoietic stem and progenitor cells (HSPCs) and their differentiated lineages serves as an ideal model to uncover generic principles of cell fate transitions. From gastrulation onwards, there successively emerge primitive hematopoiesis (that produces specialized hematopoietic cells), pro-definitive hematopoiesis (that produces lineage-restricted progenitor cells), and definitive hematopoiesis (that produces multipotent HSPCs). These nascent lineages develop in several transient hematopoietic sites and finally colonize into lifelong hematopoietic sites. The development and maintenance of hematopoietic lineages are orchestrated by cell-intrinsic gene regulatory networks and cell-extrinsic microenvironmental cues. Owing to the progressive methodology (e.g., high-throughput lineage tracing and single-cell functional and omics analyses), our understanding of the developmental origin of hematopoietic lineages and functional properties of certain hematopoietic organs has been updated; meanwhile, new paradigms to characterize rare cell types, cell heterogeneity and its causes, and comprehensive regulatory landscapes have been provided. Here, we review the evolving views of HSPC biology during developmental and postnatal hematopoiesis. Moreover, we discuss recent advances in the in vitro induction and expansion of HSPCs, with a focus on the implications for clinical applications.
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Affiliation(s)
- Yifan Zhang
- Shandong Provincial Key Laboratory of Animal Cell and Developmental Biology, School of Life Sciences, Shandong University, Qingdao, Shandong 266237, China
| | - Feng Liu
- Shandong Provincial Key Laboratory of Animal Cell and Developmental Biology, School of Life Sciences, Shandong University, Qingdao, Shandong 266237, China; State Key Laboratory of Membrane Biology, Institute of Zoology, Institute for Stem Cell and Regeneration, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Beijing 100101, China.
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53
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Gayoso A, Weiler P, Lotfollahi M, Klein D, Hong J, Streets A, Theis FJ, Yosef N. Deep generative modeling of transcriptional dynamics for RNA velocity analysis in single cells. Nat Methods 2024; 21:50-59. [PMID: 37735568 PMCID: PMC10776389 DOI: 10.1038/s41592-023-01994-w] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Accepted: 08/08/2023] [Indexed: 09/23/2023]
Abstract
RNA velocity has been rapidly adopted to guide interpretation of transcriptional dynamics in snapshot single-cell data; however, current approaches for estimating RNA velocity lack effective strategies for quantifying uncertainty and determining the overall applicability to the system of interest. Here, we present veloVI (velocity variational inference), a deep generative modeling framework for estimating RNA velocity. veloVI learns a gene-specific dynamical model of RNA metabolism and provides a transcriptome-wide quantification of velocity uncertainty. We show that veloVI compares favorably to previous approaches with respect to goodness of fit, consistency across transcriptionally similar cells and stability across preprocessing pipelines for quantifying RNA abundance. Further, we demonstrate that veloVI's posterior velocity uncertainty can be used to assess whether velocity analysis is appropriate for a given dataset. Finally, we highlight veloVI as a flexible framework for modeling transcriptional dynamics by adapting the underlying dynamical model to use time-dependent transcription rates.
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Affiliation(s)
- Adam Gayoso
- Center for Computational Biology, University of California, Berkeley, Berkeley, CA, USA
| | - Philipp Weiler
- Institute of Computational Biology, Helmholtz Center Munich, Munich, Germany
- Department of Mathematics, Technical University of Munich, Munich, Germany
| | - Mohammad Lotfollahi
- Institute of Computational Biology, Helmholtz Center Munich, Munich, Germany
- Wellcome Sanger Institute, Cambridge, UK
| | - Dominik Klein
- Institute of Computational Biology, Helmholtz Center Munich, Munich, Germany
- Department of Mathematics, Technical University of Munich, Munich, Germany
| | - Justin Hong
- Center for Computational Biology, University of California, Berkeley, Berkeley, CA, USA
- Department of Computer Science, Columbia University, New York, NY, USA
| | - Aaron Streets
- Center for Computational Biology, University of California, Berkeley, Berkeley, CA, USA
- Department of Bioengineering, University of California, Berkeley, Berkeley, CA, USA
- Chan Zuckerberg Biohub, San Francisco, CA, USA
| | - Fabian J Theis
- Institute of Computational Biology, Helmholtz Center Munich, Munich, Germany.
- Department of Mathematics, Technical University of Munich, Munich, Germany.
- TUM School of Life Sciences Weihenstephan, Technical University of Munich, Munich, Germany.
| | - Nir Yosef
- Center for Computational Biology, University of California, Berkeley, Berkeley, CA, USA.
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley, CA, USA.
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54
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Lambo S, Trinh DL, Ries RE, Jin D, Setiadi A, Ng M, Leblanc VG, Loken MR, Brodersen LE, Dai F, Pardo LM, Ma X, Vercauteren SM, Meshinchi S, Marra MA. A longitudinal single-cell atlas of treatment response in pediatric AML. Cancer Cell 2023; 41:2117-2135.e12. [PMID: 37977148 DOI: 10.1016/j.ccell.2023.10.008] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Revised: 09/15/2023] [Accepted: 10/26/2023] [Indexed: 11/19/2023]
Abstract
Pediatric acute myeloid leukemia (pAML) is characterized by heterogeneous cellular composition, driver alterations and prognosis. Characterization of this heterogeneity and how it affects treatment response remains understudied in pediatric patients. We used single-cell RNA sequencing and single-cell ATAC sequencing to profile 28 patients representing different pAML subtypes at diagnosis, remission and relapse. At diagnosis, cellular composition differed between genetic subgroups. Upon relapse, cellular hierarchies transitioned toward a more primitive state regardless of subtype. Primitive cells in the relapsed tumor were distinct compared to cells at diagnosis, with under-representation of myeloid transcriptional programs and over-representation of other lineage programs. In some patients, this was accompanied by the appearance of a B-lymphoid-like hierarchy. Our data thus reveal the emergence of apparent subtype-specific plasticity upon treatment and inform on potentially targetable processes.
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Affiliation(s)
- Sander Lambo
- Canada's Michael Smith Genome Sciences Centre, BC Cancer, Vancouver, BC, Canada
| | - Diane L Trinh
- Canada's Michael Smith Genome Sciences Centre, BC Cancer, Vancouver, BC, Canada
| | - Rhonda E Ries
- Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Dan Jin
- Canada's Michael Smith Genome Sciences Centre, BC Cancer, Vancouver, BC, Canada
| | - Audi Setiadi
- British Columbia Children's Hospital Research Institute, Vancouver, BC, Canada; Department of Pathology & Laboratory Medicine, Division of Hematopathology, Children's and Women's Health Centre of British Columbia, Vancouver, BC, Canada; Department of Pathology & Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Michelle Ng
- Canada's Michael Smith Genome Sciences Centre, BC Cancer, Vancouver, BC, Canada; Department of Medical Genetics and Michael Smith Laboratories, University of British Columbia, Vancouver, BC, Canada
| | - Veronique G Leblanc
- Canada's Michael Smith Genome Sciences Centre, BC Cancer, Vancouver, BC, Canada
| | | | | | - Fangyan Dai
- Hematologics, Incorporated, Seattle, WA, USA
| | | | - Xiaotu Ma
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Suzanne M Vercauteren
- British Columbia Children's Hospital Research Institute, Vancouver, BC, Canada; Department of Pathology & Laboratory Medicine, Division of Hematopathology, Children's and Women's Health Centre of British Columbia, Vancouver, BC, Canada; Department of Pathology & Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Soheil Meshinchi
- Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Marco A Marra
- Canada's Michael Smith Genome Sciences Centre, BC Cancer, Vancouver, BC, Canada; Department of Medical Genetics and Michael Smith Laboratories, University of British Columbia, Vancouver, BC, Canada.
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55
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Wang K, Zhang X, Cheng H, Ma W, Bao G, Dong L, Gou Y, Yang J, Cai H. SingleScan: a comprehensive resource for single-cell sequencing data processing and mining. BMC Bioinformatics 2023; 24:463. [PMID: 38062357 PMCID: PMC10704760 DOI: 10.1186/s12859-023-05590-9] [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: 07/24/2023] [Accepted: 11/30/2023] [Indexed: 12/18/2023] Open
Abstract
Single-cell sequencing has shed light on previously inaccessible biological questions from different fields of research, including organism development, immune function, and disease progression. The number of single-cell-based studies increased dramatically over the past decade. Several new methods and tools have been continuously developed, making it extremely tricky to navigate this research landscape and develop an up-to-date workflow to analyze single-cell sequencing data, particularly for researchers seeking to enter this field without computational experience. Moreover, choosing appropriate tools and optimal parameters to meet the demands of researchers represents a major challenge in processing single-cell sequencing data. However, a specific resource for easy access to detailed information on single-cell sequencing methods and data processing pipelines is still lacking. In the present study, an online resource called SingleScan was developed to curate all up-to-date single-cell transcriptome/genome analyzing tools and pipelines. All the available tools were categorized according to their main tasks, and several typical workflows for single-cell data analysis were summarized. In addition, spatial transcriptomics, which is a breakthrough molecular analysis method that enables researchers to measure all gene activity in tissue samples and map the site of activity, was included along with a portion of single-cell and spatial analysis solutions. For each processing step, the available tools and specific parameters used in published articles are provided and how these parameters affect the results is shown in the resource. All information used in the resource was manually extracted from related literature. An interactive website was designed for data retrieval, visualization, and download. By analyzing the included tools and literature, users can gain insights into the trends of single-cell studies and easily grasp the specific usage of a specific tool. SingleScan will facilitate the analysis of single-cell sequencing data and promote the development of new tools to meet the growing and diverse needs of the research community. The SingleScan database is publicly accessible via the website at http://cailab.labshare.cn/SingleScan .
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Affiliation(s)
- Kun Wang
- Center of Growth, Metabolism and Aging, Key Laboratory of Bio-Resource and Eco-Environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, 610065, China
| | - Xiao Zhang
- Department of Breast Surgery, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, 611731, China
- Chinese Academy of Sciences Sichuan Translational Medicine Research Hospital, Chengdu, 610072, China
| | - Hansen Cheng
- Center of Growth, Metabolism and Aging, Key Laboratory of Bio-Resource and Eco-Environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, 610065, China
| | - Wenhao Ma
- Center of Growth, Metabolism and Aging, Key Laboratory of Bio-Resource and Eco-Environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, 610065, China
| | - Guangchao Bao
- Center of Growth, Metabolism and Aging, Key Laboratory of Bio-Resource and Eco-Environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, 610065, China
| | - Liting Dong
- Center of Growth, Metabolism and Aging, Key Laboratory of Bio-Resource and Eco-Environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, 610065, China
| | - Yixiong Gou
- Center of Growth, Metabolism and Aging, Key Laboratory of Bio-Resource and Eco-Environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, 610065, China
| | - Jian Yang
- Center of Growth, Metabolism and Aging, Key Laboratory of Bio-Resource and Eco-Environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, 610065, China.
| | - Haoyang Cai
- Center of Growth, Metabolism and Aging, Key Laboratory of Bio-Resource and Eco-Environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, 610065, China.
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56
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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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57
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Akhtyamov P, Shaheen L, Raevskiy M, Stupnikov A, Medvedeva YA. scATAC-seq preprocessing and imputation evaluation system for visualization, clustering and digital footprinting. Brief Bioinform 2023; 25:bbad447. [PMID: 38084919 PMCID: PMC10714317 DOI: 10.1093/bib/bbad447] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Revised: 10/29/2023] [Accepted: 11/14/2023] [Indexed: 12/18/2023] Open
Abstract
Single-cell ATAC-seq (scATAC-seq) is a recently developed approach that provides means to investigate open chromatin at single cell level, to assess epigenetic regulation and transcription factors binding landscapes. The sparsity of the scATAC-seq data calls for imputation. Similarly, preprocessing (filtering) may be required to reduce computational load due to the large number of open regions. However, optimal strategies for both imputation and preprocessing have not been yet evaluated together. We present SAPIEnS (scATAC-seq Preprocessing and Imputation Evaluation System), a benchmark for scATAC-seq imputation frameworks, a combination of state-of-the-art imputation methods with commonly used preprocessing techniques. We assess different types of scATAC-seq analysis, i.e. clustering, visualization and digital genomic footprinting, and attain optimal preprocessing-imputation strategies. We discuss the benefits of the imputation framework depending on the task and the number of the dataset features (peaks). We conclude that the preprocessing with the Boruta method is beneficial for the majority of tasks, while imputation is helpful mostly for small datasets. We also implement a SAPIEnS database with pre-computed transcription factor footprints based on imputed data with their activity scores in a specific cell type. SAPIEnS is published at: https://github.com/lab-medvedeva/SAPIEnS. SAPIEnS database is available at: https://sapiensdb.com.
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Affiliation(s)
- Pavel Akhtyamov
- Department of Biomedical Physics, Moscow Institute of Physics and Technology (National Research University), 9 Institutskiy per., 141701, Moscow Region, Russian Federation
- The National Medical Research Center for Endocrinology, Dm. Ulyanova, 11, 117036, Moscow, Russian Federation
| | - Layal Shaheen
- Department of Biomedical Physics, Moscow Institute of Physics and Technology (National Research University), 9 Institutskiy per., 141701, Moscow Region, Russian Federation
- The National Medical Research Center for Endocrinology, Dm. Ulyanova, 11, 117036, Moscow, Russian Federation
| | - Mikhail Raevskiy
- Department, École Polytechnique Fédérale de Lausanne, Rte Cantonale, 1015, Lausanne, Vaud, Switzerland
| | - Alexey Stupnikov
- Department of Biomedical Physics, Moscow Institute of Physics and Technology (National Research University), 9 Institutskiy per., 141701, Moscow Region, Russian Federation
- The National Medical Research Center for Endocrinology, Dm. Ulyanova, 11, 117036, Moscow, Russian Federation
- Institute of Bioengineering, Research Center of Biotechnology, Russian Academy of Science, Leninsky prospect, 33, build. 2, 119071, Moscow, Russian Federation
| | - Yulia A Medvedeva
- Department of Biomedical Physics, Moscow Institute of Physics and Technology (National Research University), 9 Institutskiy per., 141701, Moscow Region, Russian Federation
- The National Medical Research Center for Endocrinology, Dm. Ulyanova, 11, 117036, Moscow, Russian Federation
- Institute of Bioengineering, Research Center of Biotechnology, Russian Academy of Science, Leninsky prospect, 33, build. 2, 119071, Moscow, Russian Federation
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58
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Grillo G, Keshavarzian T, Linder S, Arlidge C, Mout L, Nand A, Teng M, Qamra A, Zhou S, Kron KJ, Murison A, Hawley JR, Fraser M, van der Kwast TH, Raj GV, He HH, Zwart W, Lupien M. Transposable Elements Are Co-opted as Oncogenic Regulatory Elements by Lineage-Specific Transcription Factors in Prostate Cancer. Cancer Discov 2023; 13:2470-2487. [PMID: 37694973 PMCID: PMC10618745 DOI: 10.1158/2159-8290.cd-23-0331] [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: 03/21/2023] [Revised: 07/30/2023] [Accepted: 09/08/2023] [Indexed: 09/12/2023]
Abstract
Transposable elements hold regulatory functions that impact cell fate determination by controlling gene expression. However, little is known about the transcriptional machinery engaged at transposable elements in pluripotent and mature versus oncogenic cell states. Through positional analysis over repetitive DNA sequences of H3K27ac chromatin immunoprecipitation sequencing data from 32 normal cell states, we report pluripotent/stem and mature cell state-specific "regulatory transposable elements." Pluripotent/stem elements are binding sites for pluripotency factors (e.g., NANOG, SOX2, OCT4). Mature cell elements are docking sites for lineage-specific transcription factors, including AR and FOXA1 in prostate epithelium. Expanding the analysis to prostate tumors, we identify a subset of regulatory transposable elements shared with pluripotent/stem cells, including Tigger3a. Using chromatin editing technology, we show how such elements promote prostate cancer growth by regulating AR transcriptional activity. Collectively, our results suggest that oncogenesis arises from lineage-specific transcription factors hijacking pluripotent/stem cell regulatory transposable elements. SIGNIFICANCE We show that oncogenesis relies on co-opting transposable elements from pluripotent stem cells as regulatory elements altering the recruitment of lineage-specific transcription factors. We further discover how co-option is dependent on active chromatin states with important implications for developing treatment options against drivers of oncogenesis across the repetitive DNA. This article is featured in Selected Articles from This Issue, p. 2293.
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Affiliation(s)
- Giacomo Grillo
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
| | - Tina Keshavarzian
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
| | - Simon Linder
- Division of Oncogenomics, Oncode Institute, The Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Christopher Arlidge
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
| | - Lisanne Mout
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
| | - Ankita Nand
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
| | - Mona Teng
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
| | - Aditi Qamra
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
| | - Stanley Zhou
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
| | - Ken J. Kron
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
| | - Alex Murison
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
| | - James R. Hawley
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
| | - Michael Fraser
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
- Ontario Institute for Cancer Research, Toronto, Ontario, Canada
| | - Theodorus H. van der Kwast
- Laboratory Medicine Program, Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
| | - Ganesh V. Raj
- Department of Urology, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Housheng Hansen He
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
| | - Wilbert Zwart
- Division of Oncogenomics, Oncode Institute, The Netherlands Cancer Institute, Amsterdam, the Netherlands
- Laboratory of Chemical Biology and Institute for Complex Molecular Systems, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands
| | - Mathieu Lupien
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
- Ontario Institute for Cancer Research, Toronto, Ontario, Canada
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59
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Chang Y, Hummel SN, Jung J, Jin G, Deng Q, Bao X. Engineered hematopoietic and immune cells derived from human pluripotent stem cells. Exp Hematol 2023; 127:14-27. [PMID: 37611730 PMCID: PMC10615717 DOI: 10.1016/j.exphem.2023.08.006] [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: 05/31/2023] [Revised: 08/09/2023] [Accepted: 08/17/2023] [Indexed: 08/25/2023]
Abstract
For the past decade, significant advances have been achieved in human hematopoietic stem cell (HSC) transplantation for treating various blood diseases and cancers. However, challenges remain with the quality control, amount, and cost of HSCs and HSC-derived immune cells. The advent of human pluripotent stem cells (hPSCs) may transform HSC transplantation and cancer immunotherapy by providing a cost-effective and scalable cell source for fundamental studies and translational applications. In this review, we discuss the current developments in the field of stem cell engineering for hematopoietic stem and progenitor cell (HSPC) differentiation and further differentiation of HSPCs into functional immune cells. The key advances in stem cell engineering include the generation of HSPCs from hPSCs, genetic modification of hPSCs, and hPSC-derived HSPCs for improved function, further differentiation of HPSCs into functional immune cells, and applications of cell culture platforms for hematopoietic cell manufacturing. Current challenges impeding the translation of hPSC-HSPCs and immune cells as well as further directions to address these challenges are also discussed.
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Affiliation(s)
- Yun Chang
- Davidson School of Chemical Engineering, Purdue University, West Lafayette, Indiana; Purdue University Institute for Cancer Research, West Lafayette, Indiana
| | - Sydney N Hummel
- Davidson School of Chemical Engineering, Purdue University, West Lafayette, Indiana; Purdue University Institute for Cancer Research, West Lafayette, Indiana
| | - Juhyung Jung
- Davidson School of Chemical Engineering, Purdue University, West Lafayette, Indiana; Purdue University Institute for Cancer Research, West Lafayette, Indiana
| | - Gyuhyung Jin
- Davidson School of Chemical Engineering, Purdue University, West Lafayette, Indiana; Purdue University Institute for Cancer Research, West Lafayette, Indiana
| | - Qing Deng
- Purdue University Institute for Cancer Research, West Lafayette, Indiana; Department of Biological Sciences, Purdue University, West Lafayette, Indiana
| | - Xiaoping Bao
- Davidson School of Chemical Engineering, Purdue University, West Lafayette, Indiana; Purdue University Institute for Cancer Research, West Lafayette, Indiana.
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60
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Subramanian S, Thoms JAI, Huang Y, Cornejo-Páramo P, Koch FC, Jacquelin S, Shen S, Song E, Joshi S, Brownlee C, Woll PS, Chacon-Fajardo D, Beck D, Curtis DJ, Yehson K, Antonenas V, O'Brien T, Trickett A, Powell JA, Lewis ID, Pitson SM, Gandhi MK, Lane SW, Vafaee F, Wong ES, Göttgens B, Alinejad-Rokny H, Wong JWH, Pimanda JE. Genome-wide transcription factor-binding maps reveal cell-specific changes in the regulatory architecture of human HSPCs. Blood 2023; 142:1448-1462. [PMID: 37595278 PMCID: PMC10651876 DOI: 10.1182/blood.2023021120] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2023] [Revised: 07/06/2023] [Accepted: 07/25/2023] [Indexed: 08/20/2023] Open
Abstract
Hematopoietic stem and progenitor cells (HSPCs) rely on a complex interplay among transcription factors (TFs) to regulate differentiation into mature blood cells. A heptad of TFs (FLI1, ERG, GATA2, RUNX1, TAL1, LYL1, LMO2) bind regulatory elements in bulk CD34+ HSPCs. However, whether specific heptad-TF combinations have distinct roles in regulating hematopoietic differentiation remains unknown. We mapped genome-wide chromatin contacts (HiC, H3K27ac, HiChIP), chromatin modifications (H3K4me3, H3K27ac, H3K27me3) and 10 TF binding profiles (heptad, PU.1, CTCF, STAG2) in HSPC subsets (stem/multipotent progenitors plus common myeloid, granulocyte macrophage, and megakaryocyte erythrocyte progenitors) and found TF occupancy and enhancer-promoter interactions varied significantly across cell types and were associated with cell-type-specific gene expression. Distinct regulatory elements were enriched with specific heptad-TF combinations, including stem-cell-specific elements with ERG, and myeloid- and erythroid-specific elements with combinations of FLI1, RUNX1, GATA2, TAL1, LYL1, and LMO2. Furthermore, heptad-occupied regions in HSPCs were subsequently bound by lineage-defining TFs, including PU.1 and GATA1, suggesting that heptad factors may prime regulatory elements for use in mature cell types. We also found that enhancers with cell-type-specific heptad occupancy shared a common grammar with respect to TF binding motifs, suggesting that combinatorial binding of TF complexes was at least partially regulated by features encoded in DNA sequence motifs. Taken together, this study comprehensively characterizes the gene regulatory landscape in rare subpopulations of human HSPCs. The accompanying data sets should serve as a valuable resource for understanding adult hematopoiesis and a framework for analyzing aberrant regulatory networks in leukemic cells.
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Affiliation(s)
- Shruthi Subramanian
- School of Clinical Medicine, University of New South Wales, Sydney, Australia
| | - Julie A. I. Thoms
- School of Biomedical Sciences, University of New South Wales, Sydney, Australia
| | - Yizhou Huang
- Centre for Health Technologies and the School of Biomedical Engineering, University of Technology Sydney, Sydney, Australia
| | | | - Forrest C. Koch
- School of Biotechnology and Biomolecular Sciences, Faculty of Science, University of New South Wales, Sydney, Australia
| | | | - Sylvie Shen
- Bone Marrow Transplant Laboratory, NSW Health Pathology, Prince of Wales Hospital, Randwick, NSW, Australia
| | - Emma Song
- Bone Marrow Transplant Laboratory, NSW Health Pathology, Prince of Wales Hospital, Randwick, NSW, Australia
| | - Swapna Joshi
- School of Clinical Medicine, University of New South Wales, Sydney, Australia
| | - Chris Brownlee
- Mark Wainwright Analytical Centre, University of New South Wales, Sydney, Australia
| | - Petter S. Woll
- Department of Medicine, Center for Hematology and Regenerative Medicine, Karolinska Institutet, Huddinge, Sweden
| | - Diego Chacon-Fajardo
- Centre for Health Technologies and the School of Biomedical Engineering, University of Technology Sydney, Sydney, Australia
| | - Dominik Beck
- Centre for Health Technologies and the School of Biomedical Engineering, University of Technology Sydney, Sydney, Australia
| | - David J. Curtis
- Australian Centre for Blood Diseases, Monash University, Melbourne, VIC, Australia
| | - Kenneth Yehson
- Blood Transplant and Cell Therapies Laboratory, NSW Health Pathology, Westmead, NSW, Australia
| | - Vicki Antonenas
- Blood Transplant and Cell Therapies Laboratory, NSW Health Pathology, Westmead, NSW, Australia
| | | | - Annette Trickett
- Bone Marrow Transplant Laboratory, NSW Health Pathology, Prince of Wales Hospital, Randwick, NSW, Australia
| | - Jason A. Powell
- Centre for Cancer Biology, SA Pathology, University of South Australia, Adelaide, Australia
- Adelaide Medical School, The University of Adelaide, Adelaide, Australia
| | - Ian D. Lewis
- Centre for Cancer Biology, SA Pathology, University of South Australia, Adelaide, Australia
| | - Stuart M. Pitson
- Centre for Cancer Biology, SA Pathology, University of South Australia, Adelaide, Australia
| | - Maher K. Gandhi
- Blood Cancer Research Group, Mater Research, The University of Queensland, Brisbane, QLD, Australia
| | - Steven W. Lane
- Cancer Program, QIMR Berghofer Medical Research, Brisbane, Australia
| | - Fatemeh Vafaee
- School of Biotechnology and Biomolecular Sciences, Faculty of Science, University of New South Wales, Sydney, Australia
- UNSW Data Science Hub, University of New South Wales, Sydney, Australia
| | - Emily S. Wong
- Victor Chang Cardiac Research Institute, Sydney, Australia
- School of Biotechnology and Biomolecular Sciences, Faculty of Science, University of New South Wales, Sydney, Australia
| | - Berthold Göttgens
- Wellcome-MRC Cambridge Stem Cell Institute, Cambridge, United Kingdom
| | - Hamid Alinejad-Rokny
- BioMedical Machine Learning Lab, Graduate School of Biomedical Engineering, University of New South Wales, Sydney, Australia
| | - Jason W. H. Wong
- School of Biomedical Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - John E. Pimanda
- School of Clinical Medicine, University of New South Wales, Sydney, Australia
- School of Biomedical Sciences, University of New South Wales, Sydney, Australia
- Haematology Department, Prince of Wales Hospital, Sydney, Australia
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61
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Carbonetto P, Luo K, Sarkar A, Hung A, Tayeb K, Pott S, Stephens M. GoM DE: interpreting structure in sequence count data with differential expression analysis allowing for grades of membership. Genome Biol 2023; 24:236. [PMID: 37858253 PMCID: PMC10588049 DOI: 10.1186/s13059-023-03067-9] [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: 03/03/2023] [Accepted: 09/20/2023] [Indexed: 10/21/2023] Open
Abstract
Parts-based representations, such as non-negative matrix factorization and topic modeling, have been used to identify structure from single-cell sequencing data sets, in particular structure that is not as well captured by clustering or other dimensionality reduction methods. However, interpreting the individual parts remains a challenge. To address this challenge, we extend methods for differential expression analysis by allowing cells to have partial membership to multiple groups. We call this grade of membership differential expression (GoM DE). We illustrate the benefits of GoM DE for annotating topics identified in several single-cell RNA-seq and ATAC-seq data sets.
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Affiliation(s)
- Peter Carbonetto
- Department of Human Genetics, University of Chicago, Chicago, IL, USA
- Research Computing Center, University of Chicago, Chicago, IL, USA
| | - Kaixuan Luo
- Department of Human Genetics, University of Chicago, Chicago, IL, USA
| | - Abhishek Sarkar
- Department of Human Genetics, University of Chicago, Chicago, IL, USA
- Vesalius Therapeutics, Cambridge, MA, USA
| | - Anthony Hung
- Department of Human Genetics, University of Chicago, Chicago, IL, USA
- Section of Genetic Medicine, University of Chicago, Chicago, IL, USA
| | - Karl Tayeb
- Department of Human Genetics, University of Chicago, Chicago, IL, USA
- Committee on Genetics, Genomics and Systems Biology, University of Chicago, Chicago, IL, USA
| | - Sebastian Pott
- Department of Human Genetics, University of Chicago, Chicago, IL, USA
- Section of Genetic Medicine, University of Chicago, Chicago, IL, USA
| | - Matthew Stephens
- Department of Human Genetics, University of Chicago, Chicago, IL, USA.
- Department of Statistics, University of Chicago, Chicago, IL, USA.
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62
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Chen S, Jiang W, Du Y, Yang M, Pan Y, Li H, Cui M. Single-cell analysis technologies for cancer research: from tumor-specific single cell discovery to cancer therapy. Front Genet 2023; 14:1276959. [PMID: 37900181 PMCID: PMC10602688 DOI: 10.3389/fgene.2023.1276959] [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: 08/13/2023] [Accepted: 09/25/2023] [Indexed: 10/31/2023] Open
Abstract
Single-cell sequencing (SCS) technology is changing our understanding of cellular components, functions, and interactions across organisms, because of its inherent advantage of avoiding noise resulting from genotypic and phenotypic heterogeneity across numerous samples. By directly and individually measuring multiple molecular characteristics of thousands to millions of single cells, SCS technology can characterize multiple cell types and uncover the mechanisms of gene regulatory networks, the dynamics of transcription, and the functional state of proteomic profiling. In this context, we conducted systematic research on SCS techniques, including the fundamental concepts, procedural steps, and applications of scDNA, scRNA, scATAC, scCITE, and scSNARE methods, focusing on the unique clinical advantages of SCS, particularly in cancer therapy. We have explored challenging but critical areas such as circulating tumor cells (CTCs), lineage tracing, tumor heterogeneity, drug resistance, and tumor immunotherapy. Despite challenges in managing and analyzing the large amounts of data that result from SCS, this technique is expected to reveal new horizons in cancer research. This review aims to emphasize the key role of SCS in cancer research and promote the application of single-cell technologies to cancer therapy.
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Affiliation(s)
- Siyuan Chen
- Department of Hepatobiliary and Pancreatic Surgery, The Second Hospital of Jilin University, Changchun, China
| | - Weibo Jiang
- Department of Orthopaedic, The Second Hospital of Jilin University, Changchun, China
| | - Yanhui Du
- Department of Orthopaedics, Jilin Province People’s Hospital, Changchun, China
| | - Manshi Yang
- Department of Hepatobiliary and Pancreatic Surgery, The Second Hospital of Jilin University, Changchun, China
| | - Yihan Pan
- Department of Hepatobiliary and Pancreatic Surgery, The Second Hospital of Jilin University, Changchun, China
| | - Huan Li
- Department of Hepatobiliary and Pancreatic Surgery, The Second Hospital of Jilin University, Changchun, China
| | - Mengying Cui
- Department of Hepatobiliary and Pancreatic Surgery, The Second Hospital of Jilin University, Changchun, China
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63
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Heuts BMH, Martens JHA. Understanding blood development and leukemia using sequencing-based technologies and human cell systems. Front Mol Biosci 2023; 10:1266697. [PMID: 37886034 PMCID: PMC10598665 DOI: 10.3389/fmolb.2023.1266697] [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: 07/25/2023] [Accepted: 09/06/2023] [Indexed: 10/28/2023] Open
Abstract
Our current understanding of human hematopoiesis has undergone significant transformation throughout the years, challenging conventional views. The evolution of high-throughput technologies has enabled the accumulation of diverse data types, offering new avenues for investigating key regulatory processes in blood cell production and disease. In this review, we will explore the opportunities presented by these advancements for unraveling the molecular mechanisms underlying normal and abnormal hematopoiesis. Specifically, we will focus on the importance of enhancer-associated regulatory networks and highlight the crucial role of enhancer-derived transcription regulation. Additionally, we will discuss the unprecedented power of single-cell methods and the progression in using in vitro human blood differentiation system, in particular induced pluripotent stem cell models, in dissecting hematopoietic processes. Furthermore, we will explore the potential of ever more nuanced patient profiling to allow precision medicine approaches. Ultimately, we advocate for a multiparameter, regulatory network-based approach for providing a more holistic understanding of normal hematopoiesis and blood disorders.
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Affiliation(s)
- Branco M H Heuts
- Department of Molecular Biology, Faculty of Science, Radboud University, Nijmegen, Netherlands
| | - Joost H A Martens
- Department of Molecular Biology, Faculty of Science, Radboud University, Nijmegen, Netherlands
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64
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Arenas-Mena C, Akin S. Widespread priming of transcriptional regulatory elements by incipient accessibility or RNA polymerase II pause in early embryos of the sea urchin Strongylocentrotus purpuratus. Genetics 2023; 225:iyad145. [PMID: 37551428 PMCID: PMC10789315 DOI: 10.1093/genetics/iyad145] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Revised: 05/17/2023] [Accepted: 07/25/2023] [Indexed: 08/09/2023] Open
Abstract
Transcriptional regulatory elements (TREs) are the primary nodes that control developmental gene regulatory networks. In embryo stages, larvae, and adult differentiated red spherule cells of the sea urchin Strongylocentrotus purpuratus, transcriptionally engaged TREs are detected by Precision Run-On Sequencing (PRO-seq), which maps genome-wide at base pair resolution the location of paused or elongating RNA polymerase II (Pol II). In parallel, TRE accessibility is estimated by the Assay for Transposase-Accessible Chromatin using Sequencing (ATAC-seq). Our analysis identifies surprisingly early and widespread TRE accessibility in 4-cell cleavage embryos that is not necessarily followed by concurrent or subsequent transcription. TRE transcriptional differences identified by PRO-seq provide more contrast among embryonic stages than ATAC-seq accessibility differences, in agreement with the apparent excess of accessible but inactive TREs during embryogenesis. Global TRE accessibility reaches a maximum around the 20-hour late blastula stage, which coincides with the consolidation of major embryo regionalizations and peak histone variant H2A.Z expression. A transcriptional potency model based on labile nucleosome TRE occupancy driven by DNA sequences and the prevalence of histone variants is proposed in order to explain the basal accessibility of transcriptionally inactive TREs during embryogenesis. However, our results would not reconcile well with labile nucleosome models based on simple A/T sequence enrichment. In addition, a large number of distal TREs become transcriptionally disengaged during developmental progression, in support of an early Pol II paused model for developmental gene regulation that eventually resolves in transcriptional activation or silencing. Thus, developmental potency in early embryos may be facilitated by incipient accessibility and transcriptional pause at TREs.
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Affiliation(s)
- Cesar Arenas-Mena
- Department of Biology, College of Staten Island, City University of New York (CUNY), 2800 Victory Boulevard, Staten Island, NY, 10314, USA
- PhD Programs in Biology and Biochemistry at the City University of New York (CUNY), Graduate Center, 365 Fifth Avenue, New York, NY, 10016, USA
| | - Serhat Akin
- Department of Biology, College of Staten Island, City University of New York (CUNY), 2800 Victory Boulevard, Staten Island, NY, 10314, USA
- PhD Program in Biology at the City University of New York (CUNY), Graduate Center, 365 Fifth Avenue, New York, NY, 10016, USA
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65
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Phan QM, Salz L, Kindl SS, Lopez JS, Thompson SM, Makkar J, Driskell IM, Driskell RR. Lineage commitment of dermal fibroblast progenitors is controlled by Kdm6b-mediated chromatin demethylation. EMBO J 2023; 42:e113880. [PMID: 37602956 PMCID: PMC10548174 DOI: 10.15252/embj.2023113880] [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: 03/02/2023] [Revised: 07/26/2023] [Accepted: 08/01/2023] [Indexed: 08/22/2023] Open
Abstract
Dermal Fibroblast Progenitors (DFPs) differentiate into distinct fibroblast lineages during skin development. However, the epigenetic mechanisms that regulate DFP differentiation are not known. Our objective was to use multimodal single-cell approaches, epigenetic assays, and allografting techniques to define a DFP state and the mechanism that governs its differentiation potential. Our initial results indicated that the overall transcription profile of DFPs is repressed by H3K27me3 and has inaccessible chromatin at lineage-specific genes. Surprisingly, the repressive chromatin profile of DFPs renders them unable to reform the skin in allograft assays despite their multipotent potential. We hypothesized that chromatin derepression was modulated by the H3K27me3 demethylase, Kdm6b/Jmjd3. Dermal fibroblast-specific deletion of Kdm6b/Jmjd3 in mice resulted in adipocyte compartment ablation and inhibition of mature dermal papilla functions, confirmed by additional single-cell RNA-seq, ChIP-seq, and allografting assays. We conclude that DFPs are functionally derepressed during murine skin development by Kdm6b/Jmjd3. Our studies therefore reveal a multimodal understanding of how DFPs differentiate into distinct fibroblast lineages and provide a novel publicly available multiomics search tool.
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Affiliation(s)
- Quan M Phan
- School of Molecular BiosciencesWashington State UniversityPullmanWAUSA
| | - Lucia Salz
- North Rhine‐Westphalia Technical University of AachenAachenGermany
| | - Sam S Kindl
- School of Molecular BiosciencesWashington State UniversityPullmanWAUSA
| | - Jayden S Lopez
- School of Molecular BiosciencesWashington State UniversityPullmanWAUSA
| | - Sean M Thompson
- School of Molecular BiosciencesWashington State UniversityPullmanWAUSA
| | - Jasson Makkar
- School of Molecular BiosciencesWashington State UniversityPullmanWAUSA
| | - Iwona M Driskell
- School of Molecular BiosciencesWashington State UniversityPullmanWAUSA
| | - Ryan R Driskell
- School of Molecular BiosciencesWashington State UniversityPullmanWAUSA
- Center for Reproductive BiologyWashington State UniversityPullmanWAUSA
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66
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Li W, Gurdziel K, Pitchaikannu A, Gupta N, Hazlett LD, Xu S. The miR-183/96/182 cluster is a checkpoint for resident immune cells and shapes the cellular landscape of the cornea. Ocul Surf 2023; 30:17-41. [PMID: 37536656 PMCID: PMC10834862 DOI: 10.1016/j.jtos.2023.07.012] [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: 01/30/2023] [Revised: 07/28/2023] [Accepted: 07/31/2023] [Indexed: 08/05/2023]
Abstract
PURPOSE The conserved miR-183/96/182 cluster (miR-183C) regulates both corneal sensory innervation and corneal resident immune cells (CRICs). This study is to uncover its role in CRICs and in shaping the corneal cellular landscape at a single-cell (sc) level. METHODS Corneas of naïve, young adult [2 and 6 months old (mo)], female miR-183C knockout (KO) mice and wild-type (WT) littermates were harvested and dissociated into single cells. Dead cells were removed using a Dead Cell Removal kit. CD45+ CRICs were enriched by Magnetic Activated Cell Sorting (MACS). scRNA libraries were constructed and sequenced followed by comprehensive bioinformatic analyses. RESULTS The composition of major cell types of the cornea stays relatively stable in WT mice from 2 to 6 mo, however the compositions of subtypes of corneal cells shift with age. Inactivation of miR-183C disrupts the stability of the major cell-type composition and age-related transcriptomic shifts of subtypes of corneal cells. The diversity of CRICs is enhanced with age. Naïve mouse cornea contains previously-unrecognized resident fibrocytes and neutrophils. Resident macrophages (ResMφ) adopt cornea-specific function by expressing abundant extracellular matrix (ECM) and ECM organization-related genes. Naïve cornea is endowed with partially-differentiated proliferative ResMφ and contains microglia-like Mφ. Resident lymphocytes, including innate lymphoid cells (ILCs), NKT and γδT cells, are the major source of innate IL-17a. miR-183C limits the diversity and polarity of ResMφ. CONCLUSION miR-183C serves as a checkpoint for CRICs and imposes a global regulation of the cellular landscape of the cornea.
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Affiliation(s)
- Weifeng Li
- Predoctoral Training Program in Human Genetics, McKusick-Nathans Institute of Genetic Medicine, Department of Genetic Medicine, USA; Wilmer Eye Institute, School of Medicine, The Johns Hopkins University, Baltimore, MD, USA
| | | | - Ahalya Pitchaikannu
- Department of Ophthalmology, Visual and Anatomical Sciences, School of Medicine, Wayne State University, Detroit, MI, USA
| | - Naman Gupta
- Department of Ophthalmology, Visual and Anatomical Sciences, School of Medicine, Wayne State University, Detroit, MI, USA
| | - Linda D Hazlett
- Department of Ophthalmology, Visual and Anatomical Sciences, School of Medicine, Wayne State University, Detroit, MI, USA
| | - Shunbin Xu
- Department of Ophthalmology, Visual and Anatomical Sciences, School of Medicine, Wayne State University, Detroit, MI, USA.
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67
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Vallelonga V, Gandolfi F, Ficara F, Della Porta MG, Ghisletti S. Emerging Insights into Molecular Mechanisms of Inflammation in Myelodysplastic Syndromes. Biomedicines 2023; 11:2613. [PMID: 37892987 PMCID: PMC10603842 DOI: 10.3390/biomedicines11102613] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Revised: 09/15/2023] [Accepted: 09/21/2023] [Indexed: 10/29/2023] Open
Abstract
Inflammation impacts human hematopoiesis across physiologic and pathologic conditions, as signals derived from the bone marrow microenvironment, such as pro-inflammatory cytokines and chemokines, have been shown to alter hematopoietic stem cell (HSCs) homeostasis. Dysregulated inflammation can skew HSC fate-related decisions, leading to aberrant hematopoiesis and potentially contributing to the pathogenesis of hematological disorders such as myelodysplastic syndromes (MDS). Recently, emerging studies have used single-cell sequencing and muti-omic approaches to investigate HSC cellular heterogeneity and gene expression in normal hematopoiesis as well as in myeloid malignancies. This review summarizes recent reports mechanistically dissecting the role of inflammatory signaling and innate immune response activation due to MDS progression. Furthermore, we highlight the growing importance of using multi-omic techniques, such as single-cell profiling and deconvolution methods, to unravel MDSs' heterogeneity. These approaches have provided valuable insights into the patterns of clonal evolution that drive MDS progression and have elucidated the impact of inflammation on the composition of the bone marrow immune microenvironment in MDS.
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Affiliation(s)
- Veronica Vallelonga
- Department of Experimental Oncology, European Institute of Oncology (IEO) IRCCS, 20139 Milan, Italy
| | - Francesco Gandolfi
- Department of Experimental Oncology, European Institute of Oncology (IEO) IRCCS, 20139 Milan, Italy
| | - Francesca Ficara
- Milan Unit, CNR-IRGB, 20090 Milan, Italy
- IRCCS Humanitas Research Hospital, 20089 Milan, Italy
| | - Matteo Giovanni Della Porta
- IRCCS Humanitas Research Hospital, 20089 Milan, Italy
- Department of Biomedical Sciences, Humanitas University, 20072 Milan, Italy
| | - Serena Ghisletti
- Department of Experimental Oncology, European Institute of Oncology (IEO) IRCCS, 20139 Milan, Italy
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Athaya T, Ripan RC, Li X, Hu H. Multimodal deep learning approaches for single-cell multi-omics data integration. Brief Bioinform 2023; 24:bbad313. [PMID: 37651607 PMCID: PMC10516349 DOI: 10.1093/bib/bbad313] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Revised: 06/23/2023] [Accepted: 07/18/2023] [Indexed: 09/02/2023] Open
Abstract
Integrating single-cell multi-omics data is a challenging task that has led to new insights into complex cellular systems. Various computational methods have been proposed to effectively integrate these rapidly accumulating datasets, including deep learning. However, despite the proven success of deep learning in integrating multi-omics data and its better performance over classical computational methods, there has been no systematic study of its application to single-cell multi-omics data integration. To fill this gap, we conducted a literature review to explore the use of multimodal deep learning techniques in single-cell multi-omics data integration, taking into account recent studies from multiple perspectives. Specifically, we first summarized different modalities found in single-cell multi-omics data. We then reviewed current deep learning techniques for processing multimodal data and categorized deep learning-based integration methods for single-cell multi-omics data according to data modality, deep learning architecture, fusion strategy, key tasks and downstream analysis. Finally, we provided insights into using these deep learning models to integrate multi-omics data and better understand single-cell biological mechanisms.
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Affiliation(s)
- Tasbiraha Athaya
- Department of Computer Science, University of Central Florida, Orlando, Florida, United States of America
| | - Rony Chowdhury Ripan
- Department of Computer Science, University of Central Florida, Orlando, Florida, United States of America
| | - Xiaoman Li
- Burnett School of Biomedical Science, College of Medicine, University of Central Florida, Orlando, Florida, United States of America
| | - Haiyan Hu
- Department of Computer Science, University of Central Florida, Orlando, Florida, United States of America
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Zhang K, Zemke NR, Armand EJ, Ren B. SnapATAC2: a fast, scalable and versatile tool for analysis of single-cell omics data. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.11.557221. [PMID: 37745443 PMCID: PMC10515871 DOI: 10.1101/2023.09.11.557221] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/26/2023]
Abstract
Single-cell omics technologies have ushered in a new era for the study of dynamic gene regulation in complex tissues during development and disease pathogenesis. A major computational challenge in analyzing these datasets is to project the large-scale and high dimensional data into low-dimensional space while retaining the relative relationships between cells in order to decompose the cellular heterogeneity and reconstruct cell-type-specific gene regulatory programs. Conventional dimensionality reduction methods suffer from computational inefficiency, difficulty to capture the full spectrum of cellular heterogeneity, or inability to apply across diverse molecular modalities. Here, we report a fast and nonlinear dimensionality reduction algorithm that not only more accurately captures the heterogeneities of single-cell omics data, but also features runtime and memory usage that is computational efficient and linearly proportional to cell numbers. We implement this algorithm in a Python package named SnapATAC2, and demonstrate its superior performance, remarkable scalability and general adaptability using an array of single-cell omics data types, including single-cell ATAC-seq, single-cell RNA-seq, single-cell Hi-C, and single-cell multiomics datasets.
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Carbonetto P, Luo K, Sarkar A, Hung A, Tayeb K, Pott S, Stephens M. GoM DE: interpreting structure in sequence count data with differential expression analysis allowing for grades of membership. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.03.531029. [PMID: 36945441 PMCID: PMC10028846 DOI: 10.1101/2023.03.03.531029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/11/2023]
Abstract
Parts-based representations, such as non-negative matrix factorization and topic modeling, have been used to identify structure from single-cell sequencing data sets, in particular structure that is not as well captured by clustering or other dimensionality reduction methods. However, interpreting the individual parts remains a challenge. To address this challenge, we extend methods for differential expression analysis by allowing cells to have partial membership to multiple groups. We call this grade of membership differential expression (GoM DE). We illustrate the benefits of GoM DE for annotating topics identified in several single-cell RNA-seq and ATAC-seq data sets.
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Affiliation(s)
- Peter Carbonetto
- Department of Human Genetics, University of Chicago, Chicago, IL, USA
- Research Computing Center, University of Chicago, Chicago, IL, USA
| | - Kaixuan Luo
- Department of Human Genetics, University of Chicago, Chicago, IL, USA
| | - Abhishek Sarkar
- Department of Human Genetics, University of Chicago, Chicago, IL, USA
- Vesalius Therapeutics, Cambridge, MA, USA
| | - Anthony Hung
- Department of Human Genetics, University of Chicago, Chicago, IL, USA
- Section of Genetic Medicine, University of Chicago, Chicago, IL, USA
| | - Karl Tayeb
- Department of Human Genetics, University of Chicago, Chicago, IL, USA
- Committee on Genetics, Genomics and Systems Biology, University of Chicago, Chicago, IL, USA
| | - Sebastian Pott
- Department of Human Genetics, University of Chicago, Chicago, IL, USA
- Section of Genetic Medicine, University of Chicago, Chicago, IL, USA
| | - Matthew Stephens
- Department of Human Genetics, University of Chicago, Chicago, IL, USA
- Department of Statistics, University of Chicago, Chicago, IL, USA
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71
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Liu S, Wu W, Du Y, Yin H, Chen Q, Yu W, Wang W, Yu J, Liu L, Lou W, Pu N. The evolution and heterogeneity of neutrophils in cancers: origins, subsets, functions, orchestrations and clinical applications. Mol Cancer 2023; 22:148. [PMID: 37679744 PMCID: PMC10483725 DOI: 10.1186/s12943-023-01843-6] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2023] [Accepted: 08/14/2023] [Indexed: 09/09/2023] Open
Abstract
Neutrophils, the most prevalent innate immune cells in humans, have garnered significant attention in recent years due to their involvement in cancer progression. This comprehensive review aimed to elucidate the important roles and underlying mechanisms of neutrophils in cancer from the perspective of their whole life cycle, tracking them from development in the bone marrow to circulation and finally to the tumor microenvironment (TME). Based on an understanding of their heterogeneity, we described the relationship between abnormal neutrophils and clinical manifestations in cancer. Specifically, we explored the function, origin, and polarization of neutrophils within the TME. Furthermore, we also undertook an extensive analysis of the intricate relationship between neutrophils and clinical management, including neutrophil-based clinical treatment strategies. In conclusion, we firmly assert that directing future research endeavors towards comprehending the remarkable heterogeneity exhibited by neutrophils is of paramount importance.
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Affiliation(s)
- Siyao Liu
- Department of Pancreatic Surgery, Zhongshan Hospital, Fudan University, Shanghai, 200032, P.R. China
- Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Wenchuan Wu
- Department of Pancreatic Surgery, Zhongshan Hospital, Fudan University, Shanghai, 200032, P.R. China
- Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Yueshan Du
- Department of Pancreatic Surgery, Zhongshan Hospital, Fudan University, Shanghai, 200032, P.R. China
- Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Hanlin Yin
- Department of Pancreatic Surgery, Zhongshan Hospital, Fudan University, Shanghai, 200032, P.R. China
- Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Qiangda Chen
- Department of Pancreatic Surgery, Zhongshan Hospital, Fudan University, Shanghai, 200032, P.R. China
- Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Weisheng Yu
- Department of Pancreatic Surgery, Zhongshan Hospital, Fudan University, Shanghai, 200032, P.R. China
- Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Wenquan Wang
- Department of Pancreatic Surgery, Zhongshan Hospital, Fudan University, Shanghai, 200032, P.R. China
- Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Jun Yu
- Departments of Medicine and Oncology, Johns Hopkins University School of Medicine, Baltimore, MD, 21287, USA
| | - Liang Liu
- Department of Pancreatic Surgery, Zhongshan Hospital, Fudan University, Shanghai, 200032, P.R. China.
- Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
| | - Wenhui Lou
- Department of Pancreatic Surgery, Zhongshan Hospital, Fudan University, Shanghai, 200032, P.R. China.
- Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
| | - Ning Pu
- Department of Pancreatic Surgery, Zhongshan Hospital, Fudan University, Shanghai, 200032, P.R. China.
- Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
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72
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Korzhenevich J, Janowska I, van der Burg M, Rizzi M. Human and mouse early B cell development: So similar but so different. Immunol Lett 2023; 261:1-12. [PMID: 37442242 DOI: 10.1016/j.imlet.2023.07.004] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Revised: 06/09/2023] [Accepted: 07/10/2023] [Indexed: 07/15/2023]
Abstract
Early B cell development in the bone marrow ensures the replenishment of the peripheral B cell pool. Immature B cells continuously develop from hematopoietic stem cells, in a process guided by an intricate network of transcription factors as well as chemokine and cytokine signals. Humans and mice possess somewhat similar regulatory mechanisms of B lymphopoiesis. The continuous discovery of monogenetic defects that impact early B cell development in humans substantiates the similarities and differences with B cell development in mice. These differences become relevant when targeted therapeutic approaches are used in patients; therefore, predicting potential immunological adverse events is crucial. In this review, we have provided a phenotypical classification of human and murine early progenitors and B cell stages, based on surface and intracellular protein expression. Further, we have critically compared the role of key transcription factors (Ikaros, E2A, EBF1, PAX5, and Aiolos) and chemo- or cytokine signals (FLT3, c-kit, IL-7R, and CXCR4) during homeostatic and aberrant B lymphopoiesis in both humans and mice.
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Affiliation(s)
- Jakov Korzhenevich
- Division of Clinical and Experimental Immunology, Institute of Immunology, Center for Pathophysiology, Infectiology and Immunology, Medical University of Vienna, 1090, Vienna, Austria
| | - Iga Janowska
- Department of Rheumatology and Clinical Immunology, Freiburg University Medical Center, University of Freiburg, 79106, Freiburg, Germany
| | - Mirjam van der Burg
- Department of Pediatrics, Laboratory for Pediatric Immunology, Willem-Alexander Children's Hospital, Leiden University Medical Center, 2333, ZA Leiden, The Netherlands
| | - Marta Rizzi
- Division of Clinical and Experimental Immunology, Institute of Immunology, Center for Pathophysiology, Infectiology and Immunology, Medical University of Vienna, 1090, Vienna, Austria; Department of Rheumatology and Clinical Immunology, Freiburg University Medical Center, University of Freiburg, 79106, Freiburg, Germany; Center for Chronic Immunodeficiency, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, 79106, Freiburg, Germany; CIBSS - Centre for Integrative Biological Signalling Studies, University of Freiburg, 79104, Freiburg, Germany.
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73
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Wong M, Wei Y, Ho YC. Single-cell multiomic understanding of HIV-1 reservoir at epigenetic, transcriptional, and protein levels. Curr Opin HIV AIDS 2023; 18:246-256. [PMID: 37535039 PMCID: PMC10442869 DOI: 10.1097/coh.0000000000000809] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/04/2023]
Abstract
PURPOSE OF REVIEW The success of HIV-1 eradication strategies relies on in-depth understanding of HIV-1-infected cells. However, HIV-1-infected cells are extremely heterogeneous and rare. Single-cell multiomic approaches resolve the heterogeneity and rarity of HIV-1-infected cells. RECENT FINDINGS Advancement in single-cell multiomic approaches enabled HIV-1 reservoir profiling across the epigenetic (ATAC-seq), transcriptional (RNA-seq), and protein levels (CITE-seq). Using HIV-1 RNA as a surrogate, ECCITE-seq identified enrichment of HIV-1-infected cells in clonally expanded cytotoxic CD4+ T cells. Using HIV-1 DNA PCR-activated microfluidic sorting, FIND-seq captured the bulk transcriptome of HIV-1 DNA+ cells. Using targeted HIV-1 DNA amplification, PheP-seq identified surface protein expression of intact versus defective HIV-1-infected cells. Using ATAC-seq to identify HIV-1 DNA, ASAP-seq captured transcription factor activity and surface protein expression of HIV-1 DNA+ cells. Combining HIV-1 mapping by ATAC-seq and HIV-1 RNA mapping by RNA-seq, DOGMA-seq captured the epigenetic, transcriptional, and surface protein expression of latent and transcriptionally active HIV-1-infected cells. To identify reproducible biological insights and authentic HIV-1-infected cells and avoid false-positive discovery of artifacts, we reviewed current practices of single-cell multiomic experimental design and bioinformatic analysis. SUMMARY Single-cell multiomic approaches may identify innovative mechanisms of HIV-1 persistence, nominate therapeutic strategies, and accelerate discoveries.
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Affiliation(s)
- Michelle Wong
- Department of Microbial Pathogenesis, Yale University School of Medicine, New Haven, Connecticut, USA
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74
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Liang KL, Laurenti E, Taghon T. Circulating IRF8-expressing CD123 +CD127 + lymphoid progenitors: key players in human hematopoiesis. Trends Immunol 2023; 44:678-692. [PMID: 37591714 PMCID: PMC7614993 DOI: 10.1016/j.it.2023.07.004] [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: 06/23/2023] [Revised: 07/12/2023] [Accepted: 07/12/2023] [Indexed: 08/19/2023]
Abstract
Lymphopoiesis is the process in which B and T cells, and innate lymphoid cells (ILCs) develop from hematopoietic progenitors that exhibit early lymphoid priming. The branching points where lymphoid-primed human progenitors are further specified to B/T/ILC differentiation trajectories remain unclear. Here, we discuss the emerging role of interferon regulatory factor (IRF)8 as a key factor to bridge human lymphoid and dendritic cell (DC) differentiation, and the current evidence for the existence of circulating and tissue-resident CD123+CD127+ lymphoid progenitors. We propose a model whereby DC/B/T/ILC lineage programs in circulating CD123+CD127+ lymphoid progenitors are expressed in balance. Upon tissue seeding, the tissue microenvironment tilts this molecular balance towards a specific lineage, thereby determining in vivo lineage fates. Finally, we discuss the translational implication of these lymphoid precursors.
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Affiliation(s)
- Kai Ling Liang
- Department of Diagnostic Sciences, Ghent University, Ghent, Belgium; Cancer Research Institute Ghent, Ghent, Belgium
| | - Elisa Laurenti
- Department of Haematology, University of Cambridge, Cambridge, UK; Wellcome-MRC Cambridge Stem Cell Institute, Cambridge, UK
| | - Tom Taghon
- Department of Diagnostic Sciences, Ghent University, Ghent, Belgium; Cancer Research Institute Ghent, Ghent, Belgium.
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75
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Guo X, He C, Xin S, Gao H, Wang B, Liu X, Zhang S, Gong F, Yu X, Pan L, Sun F, Xu J. Current perspective on biological properties of plasmacytoid dendritic cells and dysfunction in gut. Immun Inflamm Dis 2023; 11:e1005. [PMID: 37773693 PMCID: PMC10510335 DOI: 10.1002/iid3.1005] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2023] [Revised: 08/27/2023] [Accepted: 08/30/2023] [Indexed: 10/01/2023] Open
Abstract
Plasmacytoid dendritic cells (pDCs), a subtype of DC, possess unique developmental, morphological, and functional traits that have sparked much debate over the years whether they should be categorized as DCs. The digestive system has the greatest mucosal tissue overall, and the pDC therein is responsible for shaping the adaptive and innate immunity of the gastrointestinal tract, resisting pathogen invasion through generating type I interferons, presenting antigens, and participating in immunological responses. Therefore, its alleged importance in the gut has received a lot of attention in recent years, and a fresh functional overview is still required. Here, we summarize the current understanding of mouse and human pDCs, ranging from their formation and different qualities compared with related cell types to their functional characteristics in intestinal disorders, including colon cancer, infections, autoimmune diseases, and intestinal graft-versus-host disease. The purpose of this review is to convey our insights, demonstrate the limits of existing research, and lay a theoretical foundation for the rational development and use of pDCs in future clinical practice.
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Affiliation(s)
- Xueran Guo
- Department of Clinical Medicine, Beijing An Zhen HospitalCapital Medical UniversityBeijingChina
| | - Chengwei He
- Department of Physiology and Pathophysiology, School of Basic Medical SciencesCapital Medical UniversityBeijingChina
| | - Shuzi Xin
- Department of Physiology and Pathophysiology, School of Basic Medical SciencesCapital Medical UniversityBeijingChina
| | - Han Gao
- Department of Physiology and Pathophysiology, School of Basic Medical SciencesCapital Medical UniversityBeijingChina
- Department of Clinical Laboratory, Aerospace Center HospitalPeking UniversityBeijingChina
| | - Boya Wang
- Key laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing)Peking University Cancer Hospital & InstituteBeijingChina
| | - Xiaohui Liu
- Department of Physiology and Pathophysiology, School of Basic Medical SciencesCapital Medical UniversityBeijingChina
| | - Sitian Zhang
- Department of Clinical Medicine, School of Basic Medical SciencesCapital Medical UniversityBeijingChina
| | - Fengrong Gong
- Department of Clinical Medicine, School of Basic Medical SciencesCapital Medical UniversityBeijingChina
| | - Xinyi Yu
- Department of Clinical Medicine, School of Basic Medical SciencesCapital Medical UniversityBeijingChina
| | - Luming Pan
- Department of Clinical Medicine, School of Basic Medical SciencesCapital Medical UniversityBeijingChina
| | - Fangling Sun
- Department of Laboratory Animal Research, Xuan Wu HospitalCapital Medical UniversityBeijingChina
| | - Jingdong Xu
- Department of Physiology and Pathophysiology, School of Basic Medical SciencesCapital Medical UniversityBeijingChina
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76
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Cheong JG, Ravishankar A, Sharma S, Parkhurst CN, Grassmann SA, Wingert CK, Laurent P, Ma S, Paddock L, Miranda IC, Karakaslar EO, Nehar-Belaid D, Thibodeau A, Bale MJ, Kartha VK, Yee JK, Mays MY, Jiang C, Daman AW, Martinez de Paz A, Ahimovic D, Ramos V, Lercher A, Nielsen E, Alvarez-Mulett S, Zheng L, Earl A, Yallowitz A, Robbins L, LaFond E, Weidman KL, Racine-Brzostek S, Yang HS, Price DR, Leyre L, Rendeiro AF, Ravichandran H, Kim J, Borczuk AC, Rice CM, Jones RB, Schenck EJ, Kaner RJ, Chadburn A, Zhao Z, Pascual V, Elemento O, Schwartz RE, Buenrostro JD, Niec RE, Barrat FJ, Lief L, Sun JC, Ucar D, Josefowicz SZ. Epigenetic memory of coronavirus infection in innate immune cells and their progenitors. Cell 2023; 186:3882-3902.e24. [PMID: 37597510 PMCID: PMC10638861 DOI: 10.1016/j.cell.2023.07.019] [Citation(s) in RCA: 66] [Impact Index Per Article: 66.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Revised: 04/20/2023] [Accepted: 07/12/2023] [Indexed: 08/21/2023]
Abstract
Inflammation can trigger lasting phenotypes in immune and non-immune cells. Whether and how human infections and associated inflammation can form innate immune memory in hematopoietic stem and progenitor cells (HSPC) has remained unclear. We found that circulating HSPC, enriched from peripheral blood, captured the diversity of bone marrow HSPC, enabling investigation of their epigenomic reprogramming following coronavirus disease 2019 (COVID-19). Alterations in innate immune phenotypes and epigenetic programs of HSPC persisted for months to 1 year following severe COVID-19 and were associated with distinct transcription factor (TF) activities, altered regulation of inflammatory programs, and durable increases in myelopoiesis. HSPC epigenomic alterations were conveyed, through differentiation, to progeny innate immune cells. Early activity of IL-6 contributed to these persistent phenotypes in human COVID-19 and a mouse coronavirus infection model. Epigenetic reprogramming of HSPC may underlie altered immune function following infection and be broadly relevant, especially for millions of COVID-19 survivors.
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Affiliation(s)
- Jin-Gyu Cheong
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY 10065, USA; Immunology and Microbial Pathogenesis Program, Weill Cornell Medicine, New York, NY 10065, USA
| | - Arjun Ravishankar
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY 10065, USA
| | - Siddhartha Sharma
- The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032, USA
| | | | - Simon A Grassmann
- Immunology Program, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
| | - Claire K Wingert
- Immunology Program, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
| | - Paoline Laurent
- HSS Research Institute, Hospital for Special Surgery, New York, NY 10021, USA
| | - Sai Ma
- Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA 02142, USA
| | - Lucinda Paddock
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY 10065, USA
| | | | - Emin Onur Karakaslar
- The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032, USA; Leiden University Medical Center (LUMC), Leiden, The Netherlands
| | | | - Asa Thibodeau
- The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032, USA
| | - Michael J Bale
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY 10065, USA; Immunology and Microbial Pathogenesis Program, Weill Cornell Medicine, New York, NY 10065, USA
| | - Vinay K Kartha
- Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA 02142, USA
| | - Jim K Yee
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY 10065, USA
| | - Minh Y Mays
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY 10065, USA
| | - Chenyang Jiang
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY 10065, USA
| | - Andrew W Daman
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY 10065, USA; Immunology and Microbial Pathogenesis Program, Weill Cornell Medicine, New York, NY 10065, USA
| | - Alexia Martinez de Paz
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY 10065, USA
| | - Dughan Ahimovic
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY 10065, USA; Immunology and Microbial Pathogenesis Program, Weill Cornell Medicine, New York, NY 10065, USA
| | - Victor Ramos
- The Rockefeller University, New York, NY 10065, USA
| | | | - Erik Nielsen
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY 10065, USA; Department of Medicine, Weill Cornell Medicine, New York, NY 10065, USA
| | | | - Ling Zheng
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY 10065, USA
| | - Andrew Earl
- Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA 02142, USA
| | - Alisha Yallowitz
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY 10065, USA
| | - Lexi Robbins
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY 10065, USA
| | | | - Karissa L Weidman
- Department of Medicine, Weill Cornell Medicine, New York, NY 10065, USA
| | - Sabrina Racine-Brzostek
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY 10065, USA
| | - He S Yang
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY 10065, USA
| | - David R Price
- Department of Medicine, Weill Cornell Medicine, New York, NY 10065, USA
| | - Louise Leyre
- Immunology and Microbial Pathogenesis Program, Weill Cornell Medicine, New York, NY 10065, USA
| | - André F Rendeiro
- Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY 10065, USA; Caryl and Israel Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, NY 10065, USA; CeMM Research Center for Molecular Medicine, Austrian Academy of Sciences, 1090 Vienna, Austria
| | - Hiranmayi Ravichandran
- Caryl and Israel Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, NY 10065, USA; Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY 10065, USA
| | - Junbum Kim
- Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY 10065, USA
| | - Alain C Borczuk
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY 10065, USA; Department of Pathology and Laboratory Medicine, Northwell Health, Greenvale, NY 11548, USA
| | | | - R Brad Jones
- Department of Medicine, Division of Infectious Diseases, Weill Cornell Medicine, New York, NY 10065, USA; Department of Microbiology and Immunology, Weill Cornell Medicine, New York, NY 10065, USA
| | - Edward J Schenck
- Department of Medicine, Weill Cornell Medicine, New York, NY 10065, USA
| | - Robert J Kaner
- Department of Genetic Medicine, Weill Cornell Medicine, New York, NY 10065, USA
| | - Amy Chadburn
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY 10065, USA
| | - Zhen Zhao
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY 10065, USA
| | - Virginia Pascual
- Department of Pediatrics, Gale and Ira Drukier Institute for Children's Health, Weill Cornell Medicine, New York, NY 10065, USA
| | - Olivier Elemento
- Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY 10065, USA; Caryl and Israel Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, NY 10065, USA
| | - Robert E Schwartz
- Department of Medicine, Weill Cornell Medicine, New York, NY 10065, USA
| | - Jason D Buenrostro
- Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA 02142, USA
| | - Rachel E Niec
- Department of Medicine, Weill Cornell Medicine, New York, NY 10065, USA; The Rockefeller University, New York, NY 10065, USA
| | - Franck J Barrat
- Immunology and Microbial Pathogenesis Program, Weill Cornell Medicine, New York, NY 10065, USA; HSS Research Institute, Hospital for Special Surgery, New York, NY 10021, USA; Department of Microbiology and Immunology, Weill Cornell Medicine, New York, NY 10065, USA
| | - Lindsay Lief
- Department of Medicine, Weill Cornell Medicine, New York, NY 10065, USA
| | - Joseph C Sun
- Immunology Program, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
| | - Duygu Ucar
- The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032, USA; Institute for Systems Genomics, University of Connecticut Health Center, Farmington, CT, USA.
| | - Steven Z Josefowicz
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY 10065, USA; Immunology and Microbial Pathogenesis Program, Weill Cornell Medicine, New York, NY 10065, USA.
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77
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Rhee C, Scadden EW, Wong LP, Schiroli G, Mazzola MC, Chea PL, Kato H, Hoyer FF, Mistry M, Lee BK, Kim J, Nahrendorf M, Mansour MK, Sykes DB, Sadreyev RI, Scadden DT. Limited plasticity of monocyte fate and function associated with epigenetic scripting at the level of progenitors. Blood 2023; 142:658-674. [PMID: 37267513 PMCID: PMC10447620 DOI: 10.1182/blood.2023020257] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Revised: 05/17/2023] [Accepted: 05/20/2023] [Indexed: 06/04/2023] Open
Abstract
Myeloid cell heterogeneity is known, but whether it is cell-intrinsic or environmentally-directed remains unclear. Here, an inducible/reversible system pausing myeloid differentiation allowed the definition of clone-specific functions that clustered monocytes into subsets with distinctive molecular features. These subsets were orthogonal to the classical/nonclassical categorization and had inherent, restricted characteristics that did not shift under homeostasis, after irradiation, or with infectious stress. Rather, their functional fate was constrained by chromatin accessibility established at or before the granulocyte-monocyte or monocyte-dendritic progenitor level. Subsets of primary monocytes had differential ability to control distinct infectious agents in vivo. Therefore, monocytes are a heterogeneous population of functionally restricted subtypes defined by the epigenome of their progenitors that are differentially selected by physiologic challenges with limited plasticity to transition from one subset to another.
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Affiliation(s)
- Catherine Rhee
- Center for Regenerative Medicine, Massachusetts General Hospital, Boston, MA
- Harvard Stem Cell Institute, Cambridge, MA
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA
| | - Elizabeth W. Scadden
- Center for Regenerative Medicine, Massachusetts General Hospital, Boston, MA
- Harvard Stem Cell Institute, Cambridge, MA
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA
| | - Lai Ping Wong
- Department of Molecular Biology, Massachusetts General Hospital, Boston, MA
- Department of Genetics, Harvard Medical School, Cambridge, MA
| | - Giulia Schiroli
- Center for Regenerative Medicine, Massachusetts General Hospital, Boston, MA
- Harvard Stem Cell Institute, Cambridge, MA
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA
| | - Michael C. Mazzola
- Center for Regenerative Medicine, Massachusetts General Hospital, Boston, MA
- Harvard Stem Cell Institute, Cambridge, MA
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA
| | - Phillip L. Chea
- Center for Regenerative Medicine, Massachusetts General Hospital, Boston, MA
- Harvard Stem Cell Institute, Cambridge, MA
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA
| | - Hiroki Kato
- Center for Regenerative Medicine, Massachusetts General Hospital, Boston, MA
- Harvard Stem Cell Institute, Cambridge, MA
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA
| | | | - Meeta Mistry
- Bioinformatics Core, Harvard TH Chan School of Public Health, Boston, MA
| | - Bum-Kyu Lee
- Institute for Cellular and Molecular Biology, Center for Systems and Synthetic Biology, The University of Texas at Austin, Austin, TX
| | - Jonghwan Kim
- Institute for Cellular and Molecular Biology, Center for Systems and Synthetic Biology, The University of Texas at Austin, Austin, TX
| | | | - Michael K. Mansour
- Division of Infectious Diseases, Department of Medicine, Massachusetts General Hospital, Boston, MA
| | - David B. Sykes
- Center for Regenerative Medicine, Massachusetts General Hospital, Boston, MA
- Harvard Stem Cell Institute, Cambridge, MA
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA
| | - Ruslan I. Sadreyev
- Department of Molecular Biology, Massachusetts General Hospital, Boston, MA
- Department of Pathology, Massachusetts General Hospital and Harvard Medical School, Boston, MA
| | - David T. Scadden
- Center for Regenerative Medicine, Massachusetts General Hospital, Boston, MA
- Harvard Stem Cell Institute, Cambridge, MA
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA
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78
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Selewa A, Luo K, Wasney M, Smith L, Sun X, Tang C, Eckart H, Moskowitz IP, Basu A, He X, Pott S. Single-cell genomics improves the discovery of risk variants and genes of atrial fibrillation. Nat Commun 2023; 14:4999. [PMID: 37591828 PMCID: PMC10435551 DOI: 10.1038/s41467-023-40505-5] [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: 02/11/2022] [Accepted: 08/01/2023] [Indexed: 08/19/2023] Open
Abstract
Genome-wide association studies (GWAS) have linked hundreds of loci to cardiac diseases. However, in most loci the causal variants and their target genes remain unknown. We developed a combined experimental and analytical approach that integrates single cell epigenomics with GWAS to prioritize risk variants and genes. We profiled accessible chromatin in single cells obtained from human hearts and leveraged the data to study genetics of Atrial Fibrillation (AF), the most common cardiac arrhythmia. Enrichment analysis of AF risk variants using cell-type-resolved open chromatin regions (OCRs) implicated cardiomyocytes as the main mediator of AF risk. We then performed statistical fine-mapping, leveraging the information in OCRs, and identified putative causal variants in 122 AF-associated loci. Taking advantage of the fine-mapping results, our novel statistical procedure for gene discovery prioritized 46 high-confidence risk genes, highlighting transcription factors and signal transduction pathways important for heart development. In summary, our analysis provides a comprehensive map of AF risk variants and genes, and a general framework to integrate single-cell genomics with genetic studies of complex traits.
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Affiliation(s)
- Alan Selewa
- Biophysical Sciences Graduate Program, The University of Chicago, Chicago, IL, 60637, USA
| | - Kaixuan Luo
- Department of Human Genetics, The University of Chicago, Chicago, IL, 60637, USA
| | - Michael Wasney
- Department of Medicine, Section of Genetic Medicine, The University of Chicago, Chicago, IL, 60637, USA
| | - Linsin Smith
- Committee on Genetics, Genomics and Systems Biology, The University of Chicago, Chicago, IL, 60637, USA
| | - Xiaotong Sun
- Department of Human Genetics, The University of Chicago, Chicago, IL, 60637, USA
| | - Chenwei Tang
- The College, The University of Chicago, Chicago, IL, 60637, USA
| | - Heather Eckart
- Department of Medicine, Section of Genetic Medicine, The University of Chicago, Chicago, IL, 60637, USA
| | - Ivan P Moskowitz
- Department of Human Genetics, The University of Chicago, Chicago, IL, 60637, USA
- Department of Pediatrics, The University of Chicago, Chicago, IL, 60637, USA
| | - Anindita Basu
- Department of Medicine, Section of Genetic Medicine, The University of Chicago, Chicago, IL, 60637, USA.
| | - Xin He
- Department of Human Genetics, The University of Chicago, Chicago, IL, 60637, USA.
| | - Sebastian Pott
- Department of Medicine, Section of Genetic Medicine, The University of Chicago, Chicago, IL, 60637, USA.
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79
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Yuan Y, Chen Q, Brovkina M, Clowney EJ, Yadlapalli S. Clock-dependent chromatin accessibility rhythms regulate circadian transcription. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.08.15.553315. [PMID: 37645872 PMCID: PMC10462003 DOI: 10.1101/2023.08.15.553315] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/31/2023]
Abstract
Chromatin organization plays a crucial role in gene regulation by controlling the accessibility of DNA to transcription machinery. While significant progress has been made in understanding the regulatory role of clock proteins in circadian rhythms, how chromatin organization affects circadian rhythms remains poorly understood. Here, we employed ATAC-seq (Assay for Transposase-Accessible Chromatin with Sequencing) on FAC-sorted Drosophila clock neurons to assess genome-wide chromatin accessibility over the circadian cycle. We observed significant circadian oscillations in chromatin accessibility at promoter and enhancer regions of hundreds of genes, with enhanced accessibility either at dusk or dawn, which correlated with their peak transcriptional activity. Notably, genes with enhanced accessibility at dusk were enriched with E-box motifs, while those more accessible at dawn were enriched with VRI/PDP1-box motifs, indicating that they are regulated by the core circadian feedback loops, PER/CLK and VRI/PDP1, respectively. Further, we observed a complete loss of chromatin accessibility rhythms in per01 null mutants, with chromatin consistently accessible throughout the circadian cycle, underscoring the critical role of Period protein in driving chromatin compaction during the repression phase. Together, this study demonstrates the significant role of chromatin organization in circadian regulation, revealing how the interplay between clock proteins and chromatin structure orchestrates the precise timing of biological processes throughout the day. This work further implies that variations in chromatin accessibility might play a central role in the generation of diverse circadian gene expression patterns in clock neurons.
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Affiliation(s)
- Ye Yuan
- Cellular and Molecular Biology Program, University of Michigan, Ann Arbor, MI 48109, USA
| | - Qianqian Chen
- Department of Cell and Developmental Biology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Margarita Brovkina
- Cellular and Molecular Biology Program, University of Michigan, Ann Arbor, MI 48109, USA
| | - E Josephine Clowney
- Cellular and Molecular Biology Program, University of Michigan, Ann Arbor, MI 48109, USA
- Department of Molecular, Cellular and Developmental Biology, University of Michigan, Ann Arbor, MI 48109, USA
- Michigan Neuroscience Institute Affiliate, University of Michigan, Ann Arbor, MI 48109, USA
| | - Swathi Yadlapalli
- Cellular and Molecular Biology Program, University of Michigan, Ann Arbor, MI 48109, USA
- Department of Cell and Developmental Biology, University of Michigan, Ann Arbor, MI 48109, USA
- Michigan Neuroscience Institute Affiliate, University of Michigan, Ann Arbor, MI 48109, USA
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80
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Jassinskaja M, Gonka M, Kent DG. Resolving the hematopoietic stem cell state by linking functional and molecular assays. Blood 2023; 142:543-552. [PMID: 36735913 PMCID: PMC10644060 DOI: 10.1182/blood.2022017864] [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: 11/30/2022] [Revised: 01/17/2023] [Accepted: 01/17/2023] [Indexed: 02/05/2023] Open
Abstract
One of the most challenging aspects of stem cell research is the reliance on retrospective assays for ascribing function. This is especially problematic for hematopoietic stem cell (HSC) research in which the current functional assay that formally establishes its HSC identity involves long-term serial transplantation assays that necessitate the destruction of the initial cell state many months before knowing that it was, in fact, an HSC. In combination with the explosion of equally destructive single-cell molecular assays, the paradox facing researchers is how to determine the molecular state of a functional HSC when you cannot concomitantly assess its functional and molecular properties. In this review, we will give a historical overview of the functional and molecular assays in the field, identify new tools that combine molecular and functional readouts in populations of HSCs, and imagine the next generation of computational and molecular profiling tools that may help us better link cell function with molecular state.
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Affiliation(s)
- Maria Jassinskaja
- Department of Biology, York Biomedical Research Institute, University of York, York, United Kingdom
| | - Monika Gonka
- Department of Biology, York Biomedical Research Institute, University of York, York, United Kingdom
| | - David G. Kent
- Department of Biology, York Biomedical Research Institute, University of York, York, United Kingdom
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81
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Ghersi JJ, Baldissera G, Hintzen J, Luff SA, Cheng S, Xia IF, Sturgeon CM, Nicoli S. Haematopoietic stem and progenitor cell heterogeneity is inherited from the embryonic endothelium. Nat Cell Biol 2023; 25:1135-1145. [PMID: 37460694 PMCID: PMC10415179 DOI: 10.1038/s41556-023-01187-9] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2022] [Accepted: 06/09/2023] [Indexed: 08/12/2023]
Abstract
Definitive haematopoietic stem and progenitor cells (HSPCs) generate erythroid, lymphoid and myeloid lineages. HSPCs are produced in the embryo via transdifferentiation of haemogenic endothelial cells in the aorta-gonad-mesonephros (AGM). HSPCs in the AGM are heterogeneous in differentiation and proliferative output, but how these intrinsic differences are acquired remains unanswered. Here we discovered that loss of microRNA (miR)-128 in zebrafish leads to an expansion of HSPCs in the AGM with different cell cycle states and a skew towards erythroid and lymphoid progenitors. Manipulating miR-128 in differentiating haemogenic endothelial cells, before their transition to HSPCs, recapitulated the lineage skewing in both zebrafish and human pluripotent stem cells. miR-128 promotes Wnt and Notch signalling in the AGM via post-transcriptional repression of the Wnt inhibitor csnk1a1 and the Notch ligand jag1b. De-repression of cskn1a1 resulted in replicative and erythroid-biased HSPCs, whereas de-repression of jag1b resulted in G2/M and lymphoid-biased HSPCs with long-term consequence on the respective blood lineages. We propose that HSPC heterogeneity arises in the AGM endothelium and is programmed in part by Wnt and Notch signalling.
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Affiliation(s)
- Joey J Ghersi
- Yale Cardiovascular Research Center, Department of Internal Medicine, Section of Cardiology, Yale University School of Medicine, New Haven, CT, USA
- Department of Genetics, Yale University School of Medicine, New Haven, CT, USA
- Vascular Biology & Therapeutics Program, Yale University School of Medicine, New Haven, CT, USA
| | - Gabriel Baldissera
- Yale Cardiovascular Research Center, Department of Internal Medicine, Section of Cardiology, Yale University School of Medicine, New Haven, CT, USA
- Department of Genetics, Yale University School of Medicine, New Haven, CT, USA
- Vascular Biology & Therapeutics Program, Yale University School of Medicine, New Haven, CT, USA
| | - Jared Hintzen
- Yale Cardiovascular Research Center, Department of Internal Medicine, Section of Cardiology, Yale University School of Medicine, New Haven, CT, USA
- Department of Genetics, Yale University School of Medicine, New Haven, CT, USA
- Vascular Biology & Therapeutics Program, Yale University School of Medicine, New Haven, CT, USA
| | - Stephanie A Luff
- Black Family Stem Cell Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Center for Advancement of Blood Cancer Therapies, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Cell, Developmental and Regenerative Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Siyuan Cheng
- Yale Cardiovascular Research Center, Department of Internal Medicine, Section of Cardiology, Yale University School of Medicine, New Haven, CT, USA
- Department of Genetics, Yale University School of Medicine, New Haven, CT, USA
- Vascular Biology & Therapeutics Program, Yale University School of Medicine, New Haven, CT, USA
| | - Ivan Fan Xia
- Yale Cardiovascular Research Center, Department of Internal Medicine, Section of Cardiology, Yale University School of Medicine, New Haven, CT, USA
- Department of Genetics, Yale University School of Medicine, New Haven, CT, USA
- Vascular Biology & Therapeutics Program, Yale University School of Medicine, New Haven, CT, USA
| | - Christopher M Sturgeon
- Black Family Stem Cell Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Center for Advancement of Blood Cancer Therapies, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Cell, Developmental and Regenerative Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Stefania Nicoli
- Yale Cardiovascular Research Center, Department of Internal Medicine, Section of Cardiology, Yale University School of Medicine, New Haven, CT, USA.
- Department of Genetics, Yale University School of Medicine, New Haven, CT, USA.
- Vascular Biology & Therapeutics Program, Yale University School of Medicine, New Haven, CT, USA.
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82
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Li C, Chen X, Chen S, Jiang R, Zhang X. simCAS: an embedding-based method for simulating single-cell chromatin accessibility sequencing data. Bioinformatics 2023; 39:btad453. [PMID: 37494428 PMCID: PMC10394124 DOI: 10.1093/bioinformatics/btad453] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Revised: 06/25/2023] [Accepted: 07/25/2023] [Indexed: 07/28/2023] Open
Abstract
MOTIVATION Single-cell chromatin accessibility sequencing (scCAS) technology provides an epigenomic perspective to characterize gene regulatory mechanisms at single-cell resolution. With an increasing number of computational methods proposed for analyzing scCAS data, a powerful simulation framework is desirable for evaluation and validation of these methods. However, existing simulators generate synthetic data by sampling reads from real data or mimicking existing cell states, which is inadequate to provide credible ground-truth labels for method evaluation. RESULTS We present simCAS, an embedding-based simulator, for generating high-fidelity scCAS data from both cell- and peak-wise embeddings. We demonstrate simCAS outperforms existing simulators in resembling real data and show that simCAS can generate cells of different states with user-defined cell populations and differentiation trajectories. Additionally, simCAS can simulate data from different batches and encode user-specified interactions of chromatin regions in the synthetic data, which provides ground-truth labels more than cell states. We systematically demonstrate that simCAS facilitates the benchmarking of four core tasks in downstream analysis: cell clustering, trajectory inference, data integration, and cis-regulatory interaction inference. We anticipate simCAS will be a reliable and flexible simulator for evaluating the ongoing computational methods applied on scCAS data. AVAILABILITY AND IMPLEMENTATION simCAS is freely available at https://github.com/Chen-Li-17/simCAS.
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Affiliation(s)
- Chen Li
- MOE Key Laboratory of Bioinformatics and Bioinformatics Division of BNRIST, Department of Automation, Tsinghua University, Beijing 100084, China
| | - Xiaoyang Chen
- MOE Key Laboratory of Bioinformatics and Bioinformatics Division of BNRIST, Department of Automation, Tsinghua University, Beijing 100084, China
| | - Shengquan Chen
- School of Mathematical Sciences and LPMC, Nankai University, Tianjin 300071, China
| | - Rui Jiang
- MOE Key Laboratory of Bioinformatics and Bioinformatics Division of BNRIST, Department of Automation, Tsinghua University, Beijing 100084, China
| | - Xuegong Zhang
- MOE Key Laboratory of Bioinformatics and Bioinformatics Division of BNRIST, Department of Automation, Tsinghua University, Beijing 100084, China
- Center for Synthetic and Systems Biology, School of Life Sciences and School of Medicine, Tsinghua University, Beijing 100084, China
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83
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Fan H, Wang F, Zeng A, Murison A, Tomczak K, Hao D, Jelloul FZ, Wang B, Barrodia P, Liang S, Chen K, Wang L, Zhao Z, Rai K, Jain AK, Dick J, Daver N, Futreal A, Abbas HA. Single-cell chromatin accessibility profiling of acute myeloid leukemia reveals heterogeneous lineage composition upon therapy-resistance. Commun Biol 2023; 6:765. [PMID: 37479893 PMCID: PMC10362028 DOI: 10.1038/s42003-023-05120-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2023] [Accepted: 07/07/2023] [Indexed: 07/23/2023] Open
Abstract
Acute myeloid leukemia (AML) is a heterogeneous disease characterized by high rate of therapy resistance. Since the cell of origin can impact response to therapy, it is crucial to understand the lineage composition of AML cells at time of therapy resistance. Here we leverage single-cell chromatin accessibility profiling of 22 AML bone marrow aspirates from eight patients at time of therapy resistance and following subsequent therapy to characterize their lineage landscape. Our findings reveal a complex lineage architecture of therapy-resistant AML cells that are primed for stem and progenitor lineages and spanning quiescent, activated and late stem cell/progenitor states. Remarkably, therapy-resistant AML cells are also composed of cells primed for differentiated myeloid, erythroid and even lymphoid lineages. The heterogeneous lineage composition persists following subsequent therapy, with early progenitor-driven features marking unfavorable prognosis in The Cancer Genome Atlas AML cohort. Pseudotime analysis further confirms the vast degree of heterogeneity driven by the dynamic changes in chromatin accessibility. Our findings suggest that therapy-resistant AML cells are characterized not only by stem and progenitor states, but also by a continuum of differentiated cellular lineages. The heterogeneity in lineages likely contributes to their therapy resistance by harboring different degrees of lineage-specific susceptibilities to therapy.
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Affiliation(s)
- Huihui Fan
- Department of Neurology, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX, USA
- Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Feng Wang
- Department of Genomic Medicine, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Andy Zeng
- Princess Margaret Cancer Center, University Health Network, Toronto, ON, M5S 1A8, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, Canada
| | - Alex Murison
- Princess Margaret Cancer Center, University Health Network, Toronto, ON, M5S 1A8, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, Canada
| | - Katarzyna Tomczak
- Department of Genomic Medicine, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Dapeng Hao
- Department of Genomic Medicine, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Fatima Zahra Jelloul
- Department of Hematopathology, University of Texas M D Anderson Cancer Center, Houston, TX, USA
| | - Bofei Wang
- Department of Leukemia, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Praveen Barrodia
- Department of Genomic Medicine, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Shaoheng Liang
- Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
- Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Ken Chen
- Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Linghua Wang
- Department of Genomic Medicine, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Zhongming Zhao
- Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, USA
- Human Genetics Center, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Kunal Rai
- Department of Genomic Medicine, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Abhinav K Jain
- Department of Epigenetics and Molecular Carcinogenesis, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - John Dick
- Princess Margaret Cancer Center, University Health Network, Toronto, ON, M5S 1A8, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, Canada
| | - Naval Daver
- Department of Leukemia, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Andy Futreal
- Department of Genomic Medicine, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Hussein A Abbas
- Department of Genomic Medicine, University of Texas MD Anderson Cancer Center, Houston, TX, USA.
- Department of Leukemia, University of Texas MD Anderson Cancer Center, Houston, TX, USA.
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84
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Otto D, Jordan C, Dury B, Dien C, Setty M. Quantifying Cell-State Densities in Single-Cell Phenotypic Landscapes using Mellon. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.09.548272. [PMID: 37502954 PMCID: PMC10369887 DOI: 10.1101/2023.07.09.548272] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
Cell-state density characterizes the distribution of cells along phenotypic landscapes and is crucial for unraveling the mechanisms that drive cellular differentiation, regeneration, and disease. Here, we present Mellon, a novel computational algorithm for high-resolution estimation of cell-state densities from single-cell data. We demonstrate Mellon's efficacy by dissecting the density landscape of various differentiating systems, revealing a consistent pattern of high-density regions corresponding to major cell types intertwined with low-density, rare transitory states. Utilizing hematopoietic stem cell fate specification to B-cells as a case study, we present evidence implicating enhancer priming and the activation of master regulators in the emergence of these transitory states. Mellon offers the flexibility to perform temporal interpolation of time-series data, providing a detailed view of cell-state dynamics during the inherently continuous developmental processes. Scalable and adaptable, Mellon facilitates density estimation across various single-cell data modalities, scaling linearly with the number of cells. Our work underscores the importance of cell-state density in understanding the differentiation processes, and the potential of Mellon to provide new insights into the regulatory mechanisms guiding cellular fate decisions.
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Affiliation(s)
- Dominik Otto
- Basic Sciences Division, Fred Hutchinson Cancer Center, Seattle WA
- Computational Biology Program, Public Health Sciences Division, Seattle WA
- Translational Data Science IRC, Fred Hutchinson Cancer Center, Seattle WA
| | - Cailin Jordan
- Basic Sciences Division, Fred Hutchinson Cancer Center, Seattle WA
- Computational Biology Program, Public Health Sciences Division, Seattle WA
- Translational Data Science IRC, Fred Hutchinson Cancer Center, Seattle WA
- Molecular and Cellular Biology Program, University of Washington, Seattle WA
| | - Brennan Dury
- Basic Sciences Division, Fred Hutchinson Cancer Center, Seattle WA
- Computational Biology Program, Public Health Sciences Division, Seattle WA
- Translational Data Science IRC, Fred Hutchinson Cancer Center, Seattle WA
| | - Christine Dien
- Basic Sciences Division, Fred Hutchinson Cancer Center, Seattle WA
- Computational Biology Program, Public Health Sciences Division, Seattle WA
- Translational Data Science IRC, Fred Hutchinson Cancer Center, Seattle WA
| | - Manu Setty
- Basic Sciences Division, Fred Hutchinson Cancer Center, Seattle WA
- Computational Biology Program, Public Health Sciences Division, Seattle WA
- Translational Data Science IRC, Fred Hutchinson Cancer Center, Seattle WA
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85
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Yashar WM, Curtiss BM, Coleman DJ, VanCampen J, Kong G, Macaraeg J, Estabrook J, Demir E, Long N, Bottomly D, McWeeney SK, Tyner JW, Druker BJ, Maxson JE, Braun TP. Disruption of the MYC Superenhancer Complex by Dual Targeting of FLT3 and LSD1 in Acute Myeloid Leukemia. Mol Cancer Res 2023; 21:631-647. [PMID: 36976323 PMCID: PMC10330306 DOI: 10.1158/1541-7786.mcr-22-0745] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Revised: 01/25/2023] [Accepted: 03/24/2023] [Indexed: 03/29/2023]
Abstract
Mutations in Fms-like tyrosine kinase 3 (FLT3) are common drivers in acute myeloid leukemia (AML) yet FLT3 inhibitors only provide modest clinical benefit. Prior work has shown that inhibitors of lysine-specific demethylase 1 (LSD1) enhance kinase inhibitor activity in AML. Here we show that combined LSD1 and FLT3 inhibition induces synergistic cell death in FLT3-mutant AML. Multi-omic profiling revealed that the drug combination disrupts STAT5, LSD1, and GFI1 binding at the MYC blood superenhancer, suppressing superenhancer accessibility as well as MYC expression and activity. The drug combination simultaneously results in the accumulation of repressive H3K9me1 methylation, an LSD1 substrate, at MYC target genes. We validated these findings in 72 primary AML samples with the nearly every sample demonstrating synergistic responses to the drug combination. Collectively, these studies reveal how epigenetic therapies augment the activity of kinase inhibitors in FLT3-ITD (internal tandem duplication) AML. IMPLICATIONS This work establishes the synergistic efficacy of combined FLT3 and LSD1 inhibition in FLT3-ITD AML by disrupting STAT5 and GFI1 binding at the MYC blood-specific superenhancer complex.
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Affiliation(s)
- William M. Yashar
- Knight Cancer Institute, Oregon Health & Science University; Portland, OR, 97239, USA
- Division of Oncologic Sciences, Department of Medicine, Oregon Health & Science University; Portland, OR, 97239, USA
- Department of Biomedical Engineering, Oregon Health & Science University; Portland, OR, 97239, USA
- These authors contributed equally to this work
| | - Brittany M. Curtiss
- Knight Cancer Institute, Oregon Health & Science University; Portland, OR, 97239, USA
- Division of Oncologic Sciences, Department of Medicine, Oregon Health & Science University; Portland, OR, 97239, USA
- These authors contributed equally to this work
| | - Daniel J. Coleman
- Knight Cancer Institute, Oregon Health & Science University; Portland, OR, 97239, USA
| | - Jake VanCampen
- Knight Cancer Institute, Oregon Health & Science University; Portland, OR, 97239, USA
- Division of Oncologic Sciences, Department of Medicine, Oregon Health & Science University; Portland, OR, 97239, USA
| | - Garth Kong
- Knight Cancer Institute, Oregon Health & Science University; Portland, OR, 97239, USA
- Division of Oncologic Sciences, Department of Medicine, Oregon Health & Science University; Portland, OR, 97239, USA
| | - Jommel Macaraeg
- Knight Cancer Institute, Oregon Health & Science University; Portland, OR, 97239, USA
- Division of Oncologic Sciences, Department of Medicine, Oregon Health & Science University; Portland, OR, 97239, USA
| | - Joseph Estabrook
- Cancer Early Detection Advanced Research Center, Oregon Health & Science University; Portland, OR, 97239, USA
| | - Emek Demir
- Division of Oncologic Sciences, Department of Medicine, Oregon Health & Science University; Portland, OR, 97239, USA
- Department of Molecular and Medical Genetics, Oregon Health and Science University, 3181 SW Sam Jackson Park Rd; Portland, OR 97239, USA
- Pacific Northwest National Laboratories; Richland, WA 99354, USA
| | - Nicola Long
- Knight Cancer Institute, Oregon Health & Science University; Portland, OR, 97239, USA
- Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University; Portland, OR, 97239, USA
| | - Daniel Bottomly
- Knight Cancer Institute, Oregon Health & Science University; Portland, OR, 97239, USA
- Division of Bioinformatics and Computational Biology, Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University; Portland, OR, 97239, USA
| | - Shannon K. McWeeney
- Knight Cancer Institute, Oregon Health & Science University; Portland, OR, 97239, USA
- Division of Bioinformatics and Computational Biology, Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University; Portland, OR, 97239, USA
| | - Jeffrey W. Tyner
- Division of Oncologic Sciences, Department of Medicine, Oregon Health & Science University; Portland, OR, 97239, USA
- Department of Cell, Developmental & Cancer Biology, Oregon Health & Science University; Portland, OR, 97239, USA
| | - Brian J. Druker
- Knight Cancer Institute, Oregon Health & Science University; Portland, OR, 97239, USA
- Division of Oncologic Sciences, Department of Medicine, Oregon Health & Science University; Portland, OR, 97239, USA
- Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University; Portland, OR, 97239, USA
| | - Julia E. Maxson
- Knight Cancer Institute, Oregon Health & Science University; Portland, OR, 97239, USA
- Division of Oncologic Sciences, Department of Medicine, Oregon Health & Science University; Portland, OR, 97239, USA
| | - Theodore P. Braun
- Knight Cancer Institute, Oregon Health & Science University; Portland, OR, 97239, USA
- Division of Oncologic Sciences, Department of Medicine, Oregon Health & Science University; Portland, OR, 97239, USA
- Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University; Portland, OR, 97239, USA
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86
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Lareau CA, Dubois SM, Buquicchio FA, Hsieh YH, Garg K, Kautz P, Nitsch L, Praktiknjo SD, Maschmeyer P, Verboon JM, Gutierrez JC, Yin Y, Fiskin E, Luo W, Mimitou EP, Muus C, Malhotra R, Parikh S, Fleming MD, Oevermann L, Schulte J, Eckert C, Kundaje A, Smibert P, Vardhana SA, Satpathy AT, Regev A, Sankaran VG, Agarwal S, Ludwig LS. Single-cell multi-omics of mitochondrial DNA disorders reveals dynamics of purifying selection across human immune cells. Nat Genet 2023; 55:1198-1209. [PMID: 37386249 PMCID: PMC10548551 DOI: 10.1038/s41588-023-01433-8] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Accepted: 05/24/2023] [Indexed: 07/01/2023]
Abstract
Pathogenic mutations in mitochondrial DNA (mtDNA) compromise cellular metabolism, contributing to cellular heterogeneity and disease. Diverse mutations are associated with diverse clinical phenotypes, suggesting distinct organ- and cell-type-specific metabolic vulnerabilities. Here we establish a multi-omics approach to quantify deletions in mtDNA alongside cell state features in single cells derived from six patients across the phenotypic spectrum of single large-scale mtDNA deletions (SLSMDs). By profiling 206,663 cells, we reveal the dynamics of pathogenic mtDNA deletion heteroplasmy consistent with purifying selection and distinct metabolic vulnerabilities across T-cell states in vivo and validate these observations in vitro. By extending analyses to hematopoietic and erythroid progenitors, we reveal mtDNA dynamics and cell-type-specific gene regulatory adaptations, demonstrating the context-dependence of perturbing mitochondrial genomic integrity. Collectively, we report pathogenic mtDNA heteroplasmy dynamics of individual blood and immune cells across lineages, demonstrating the power of single-cell multi-omics for revealing fundamental properties of mitochondrial genetics.
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Affiliation(s)
- Caleb A Lareau
- Department of Pathology, Stanford University, Stanford, CA, USA.
- Parker Institute of Cancer Immunotherapy, San Francisco, CA, USA.
- Department of Genetics, Stanford University, Stanford, CA, USA.
- Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Division of Hematology/Oncology, Boston Children's Hospital and Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA.
| | - Sonia M Dubois
- Division of Hematology/Oncology, Boston Children's Hospital and Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
| | | | - Yu-Hsin Hsieh
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin Institute for Medical Systems Biology (BIMSB), Berlin, Germany
| | - Kopal Garg
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Hematology/Oncology, Boston Children's Hospital and Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
| | - Pauline Kautz
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin Institute for Medical Systems Biology (BIMSB), Berlin, Germany
- Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany
- Technische Universität Berlin, Institute of Biotechnology, Berlin, Germany
| | - Lena Nitsch
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin Institute for Medical Systems Biology (BIMSB), Berlin, Germany
- Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany
- Department of Biology, Chemistry, Pharmacy, Freie Universität Berlin, Berlin, Germany
| | - Samantha D Praktiknjo
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin Institute for Medical Systems Biology (BIMSB), Berlin, Germany
- Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Patrick Maschmeyer
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin Institute for Medical Systems Biology (BIMSB), Berlin, Germany
- Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Jeffrey M Verboon
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Hematology/Oncology, Boston Children's Hospital and Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
| | | | - Yajie Yin
- Department of Pathology, Stanford University, Stanford, CA, USA
| | | | - Wendy Luo
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Eleni P Mimitou
- Technology Innovation Lab, New York Genome Center, New York City, NY, USA
- Immunai, New York City, NY, USA
| | - Christoph Muus
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
| | - Rhea Malhotra
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Sumit Parikh
- Center for Pediatric Neurosciences, Mitochondrial Medicine, Cleveland Clinic, Cleveland, OH, USA
| | - Mark D Fleming
- Department of Pathology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Lena Oevermann
- Department of Pediatric Oncology, Charité-Universitätsmedizin Berlin, Campus Virchow Klinikum, Berlin, Germany
| | - Johannes Schulte
- Department of Pediatric Oncology, Charité-Universitätsmedizin Berlin, Campus Virchow Klinikum, Berlin, Germany
| | - Cornelia Eckert
- Department of Pediatric Oncology, Charité-Universitätsmedizin Berlin, Campus Virchow Klinikum, Berlin, Germany
| | - Anshul Kundaje
- Department of Genetics, Stanford University, Stanford, CA, USA
- Department of Computer Science, Stanford University, Stanford, CA, USA
| | - Peter Smibert
- Technology Innovation Lab, New York Genome Center, New York City, NY, USA
- 10x Genomics, San Francisco, CA, USA
| | | | - Ansuman T Satpathy
- Department of Pathology, Stanford University, Stanford, CA, USA
- Parker Institute of Cancer Immunotherapy, San Francisco, CA, USA
| | - Aviv Regev
- Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Department of Biology and Koch Institute, Massachusetts Institute of Technology, Cambridge, MA, USA.
- Genentech, San Francisco, CA, USA.
| | - Vijay G Sankaran
- Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Division of Hematology/Oncology, Boston Children's Hospital and Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA.
| | - Suneet Agarwal
- Division of Hematology/Oncology, Boston Children's Hospital and Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA.
| | - Leif S Ludwig
- Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Division of Hematology/Oncology, Boston Children's Hospital and Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA.
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin Institute for Medical Systems Biology (BIMSB), Berlin, Germany.
- Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany.
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87
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Steimle JD, Kim C, Rowton M, Nadadur RD, Wang Z, Stocker M, Hoffmann AD, Hanson E, Kweon J, Sinha T, Choi K, Black BL, Cunningham JM, Moskowitz IP, Ikegami K. ETV2 primes hematoendothelial gene enhancers prior to hematoendothelial fate commitment. Cell Rep 2023; 42:112665. [PMID: 37330911 PMCID: PMC10592526 DOI: 10.1016/j.celrep.2023.112665] [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: 06/07/2021] [Revised: 03/14/2023] [Accepted: 06/02/2023] [Indexed: 06/20/2023] Open
Abstract
Mechanisms underlying distinct specification, commitment, and differentiation phases of cell fate determination remain undefined due to difficulties capturing these processes. Here, we interrogate the activity of ETV2, a transcription factor necessary and sufficient for hematoendothelial differentiation, within isolated fate intermediates. We observe transcriptional upregulation of Etv2 and opening of ETV2-binding sites, indicating new ETV2 binding, in a common cardiac-hematoendothelial progenitor population. Accessible ETV2-binding sites are active at the Etv2 locus but not at other hematoendothelial regulator genes. Hematoendothelial commitment coincides with the activation of a small repertoire of previously accessible ETV2-binding sites at hematoendothelial regulators. Hematoendothelial differentiation accompanies activation of a large repertoire of new ETV2-binding sites and upregulation of hematopoietic and endothelial gene regulatory networks. This work distinguishes specification, commitment, and sublineage differentiation phases of ETV2-dependent transcription and suggests that the shift from ETV2 binding to ETV2-bound enhancer activation, not ETV2 binding to target enhancers, drives hematoendothelial fate commitment.
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Affiliation(s)
- Jeffrey D Steimle
- Departments of Pediatrics, Pathology, and Human Genetics, University of Chicago, Chicago, IL 60637, USA
| | - Chul Kim
- Departments of Pediatrics, Pathology, and Human Genetics, University of Chicago, Chicago, IL 60637, USA; Department of Pediatrics, Section of Hematology/Oncology, University of Chicago, Chicago, IL 60637, USA
| | - Megan Rowton
- Departments of Pediatrics, Pathology, and Human Genetics, University of Chicago, Chicago, IL 60637, USA
| | - Rangarajan D Nadadur
- Departments of Pediatrics, Pathology, and Human Genetics, University of Chicago, Chicago, IL 60637, USA
| | - Zhezhen Wang
- Departments of Pediatrics, Pathology, and Human Genetics, University of Chicago, Chicago, IL 60637, USA
| | - Matthew Stocker
- Departments of Pediatrics, Pathology, and Human Genetics, University of Chicago, Chicago, IL 60637, USA
| | - Andrew D Hoffmann
- Departments of Pediatrics, Pathology, and Human Genetics, University of Chicago, Chicago, IL 60637, USA
| | - Erika Hanson
- Departments of Pediatrics, Pathology, and Human Genetics, University of Chicago, Chicago, IL 60637, USA
| | - Junghun Kweon
- Departments of Pediatrics, Pathology, and Human Genetics, University of Chicago, Chicago, IL 60637, USA
| | - Tanvi Sinha
- Cardiovascular Research Institute, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Kyunghee Choi
- Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Brian L Black
- Cardiovascular Research Institute, University of California, San Francisco, San Francisco, CA 94143, USA; Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, CA 94143, USA
| | - John M Cunningham
- Department of Pediatrics, Section of Hematology/Oncology, University of Chicago, Chicago, IL 60637, USA
| | - Ivan P Moskowitz
- Departments of Pediatrics, Pathology, and Human Genetics, University of Chicago, Chicago, IL 60637, USA.
| | - Kohta Ikegami
- Division of Molecular and Cardiovascular Biology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229, USA; Department of Pediatrics, University of Cincinnati, Cincinnati, OH 45229, USA.
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88
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Bobbitt JR, Seachrist DD, Keri RA. Chromatin Organization and Transcriptional Programming of Breast Cancer Cell Identity. Endocrinology 2023; 164:bqad100. [PMID: 37394919 PMCID: PMC10370366 DOI: 10.1210/endocr/bqad100] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/01/2023] [Revised: 06/26/2023] [Accepted: 06/28/2023] [Indexed: 07/04/2023]
Abstract
The advent of sequencing technologies for assessing chromosome conformations has provided a wealth of information on the organization of the 3-dimensional genome and its role in cancer progression. It is now known that changes in chromatin folding and accessibility can promote aberrant activation or repression of transcriptional programs that can drive tumorigenesis and progression in diverse cancers. This includes breast cancer, which comprises several distinct subtypes defined by their unique transcriptomes that dictate treatment response and patient outcomes. Of these, basal-like breast cancer is an aggressive subtype controlled by a pluripotency-enforcing transcriptome. Meanwhile, the more differentiated luminal subtype of breast cancer is driven by an estrogen receptor-dominated transcriptome that underlies its responsiveness to antihormone therapies and conveys improved patient outcomes. Despite the clear differences in molecular signatures, the genesis of each subtype from normal mammary epithelial cells remains unclear. Recent technical advances have revealed key distinctions in chromatin folding and organization between subtypes that could underlie their transcriptomic and, hence, phenotypic differences. These studies also suggest that proteins controlling particular chromatin states may be useful targets for treating aggressive disease. In this review, we explore the current state of understanding of chromatin architecture in breast cancer subtypes and its potential role in defining their phenotypic characteristics.
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Affiliation(s)
- Jessica R Bobbitt
- Department of Cancer Biology, Cleveland Clinic Lerner Research Institute, Cleveland, OH 44195, USA
- Department of Pathology, Case Western Reserve University School of Medicine, Cleveland, OH 44106, USA
| | - Darcie D Seachrist
- Department of Cancer Biology, Cleveland Clinic Lerner Research Institute, Cleveland, OH 44195, USA
| | - Ruth A Keri
- Department of Cancer Biology, Cleveland Clinic Lerner Research Institute, Cleveland, OH 44195, USA
- Case Comprehensive Cancer Center, Case Western Reserve University School of Medicine, Cleveland, OH 44106, USA
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89
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Gibellini L, Borella R, Santacroce E, Serattini E, Boraldi F, Quaglino D, Aramini B, De Biasi S, Cossarizza A. Circulating and Tumor-Associated Neutrophils in the Era of Immune Checkpoint Inhibitors: Dynamics, Phenotypes, Metabolism, and Functions. Cancers (Basel) 2023; 15:3327. [PMID: 37444436 DOI: 10.3390/cancers15133327] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Revised: 06/16/2023] [Accepted: 06/22/2023] [Indexed: 07/15/2023] Open
Abstract
Neutrophils are the most abundant myeloid cells in the blood and are a considerable immunological component of the tumor microenvironment. However, their functional importance has often been ignored, as they have always been considered a mono-dimensional population of terminally differentiated, short-living cells. During the last decade, the use of cutting-edge, single-cell technologies has revolutionized the classical view of these cells, unmasking their phenotypic and functional heterogeneity. In this review, we summarize the emerging concepts in the field of neutrophils in cancer, by reviewing the recent literature on the heterogeneity of both circulating neutrophils and tumor-associated neutrophils, as well as their possible significance in tumor prognosis and resistance to immune checkpoint inhibitors.
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Affiliation(s)
- Lara Gibellini
- Department of Medical and Surgical Sciences for Children and Adults, University of Modena and Reggio Emilia, 41121 Modena, Italy
| | - Rebecca Borella
- Department of Medical and Surgical Sciences for Children and Adults, University of Modena and Reggio Emilia, 41121 Modena, Italy
| | - Elena Santacroce
- Department of Medical and Surgical Sciences for Children and Adults, University of Modena and Reggio Emilia, 41121 Modena, Italy
| | - Eugenia Serattini
- Department of Medical and Surgical Sciences for Children and Adults, University of Modena and Reggio Emilia, 41121 Modena, Italy
| | - Federica Boraldi
- Department of Life Sciences, University of Modena and Reggio Emilia, 41125 Modena, Italy
| | - Daniela Quaglino
- Department of Life Sciences, University of Modena and Reggio Emilia, 41125 Modena, Italy
| | - Beatrice Aramini
- Division of Thoracic Surgery, Department of Medical and Surgical Sciences (DIMEC), University Hospital GB Morgagni-L Pierantoni, 47121 Forlì, Italy
| | - Sara De Biasi
- Department of Medical and Surgical Sciences for Children and Adults, University of Modena and Reggio Emilia, 41121 Modena, Italy
| | - Andrea Cossarizza
- Department of Medical and Surgical Sciences for Children and Adults, University of Modena and Reggio Emilia, 41121 Modena, Italy
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90
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Kim Y, Greenleaf WJ, Bendall SC. Systems biology approaches to unravel lymphocyte subsets and function. Curr Opin Immunol 2023; 82:102323. [PMID: 37028221 PMCID: PMC10330158 DOI: 10.1016/j.coi.2023.102323] [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: 02/02/2023] [Revised: 03/11/2023] [Accepted: 03/13/2023] [Indexed: 04/09/2023]
Abstract
Single-cell technologies have revealed the extensive heterogeneity and complexity of the immune system. Systems biology approaches in immunology have taken advantage of the high-parameter, high-throughput data and analyzed immune cell types in a 'bottom-up' data-driven method. This approach has discovered previously unrecognized cell types and functions. Especially for human immunology, in which experimental manipulations are challenging, systems approach has become a successful means to investigate physiologically relevant contexts. This review focuses on the recent findings in lymphocyte biology, from their development, differentiation into subsets, and heterogeneity in their functions, enabled by these systems approaches. Furthermore, we review examples of the application of findings from systems approach studies and discuss how now to leave the rich dataset in the curse of high dimensionality.
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Affiliation(s)
- YeEun Kim
- Immunology Graduate Program, Stanford University, Stanford, CA, USA; Department of Pathology, Stanford University, Stanford, CA, USA
| | | | - Sean C Bendall
- Department of Pathology, Stanford University, Stanford, CA, USA.
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91
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Zhang S, Pyne S, Pietrzak S, Halberg S, McCalla SG, Siahpirani AF, Sridharan R, Roy S. Inference of cell type-specific gene regulatory networks on cell lineages from single cell omic datasets. Nat Commun 2023; 14:3064. [PMID: 37244909 PMCID: PMC10224950 DOI: 10.1038/s41467-023-38637-9] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Accepted: 05/10/2023] [Indexed: 05/29/2023] Open
Abstract
Cell type-specific gene expression patterns are outputs of transcriptional gene regulatory networks (GRNs) that connect transcription factors and signaling proteins to target genes. Single-cell technologies such as single cell RNA-sequencing (scRNA-seq) and single cell Assay for Transposase-Accessible Chromatin using sequencing (scATAC-seq), can examine cell-type specific gene regulation at unprecedented detail. However, current approaches to infer cell type-specific GRNs are limited in their ability to integrate scRNA-seq and scATAC-seq measurements and to model network dynamics on a cell lineage. To address this challenge, we have developed single-cell Multi-Task Network Inference (scMTNI), a multi-task learning framework to infer the GRN for each cell type on a lineage from scRNA-seq and scATAC-seq data. Using simulated and real datasets, we show that scMTNI is a broadly applicable framework for linear and branching lineages that accurately infers GRN dynamics and identifies key regulators of fate transitions for diverse processes such as cellular reprogramming and differentiation.
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Affiliation(s)
- Shilu Zhang
- Wisconsin Institute for Discovery, University of Wisconsin-Madison, Madison, WI, USA
| | - Saptarshi Pyne
- Wisconsin Institute for Discovery, University of Wisconsin-Madison, Madison, WI, USA
| | - Stefan Pietrzak
- Wisconsin Institute for Discovery, University of Wisconsin-Madison, Madison, WI, USA
- Department of Cell and Regenerative Biology, University of Wisconsin-Madison, Madison, WI, USA
| | - Spencer Halberg
- Wisconsin Institute for Discovery, University of Wisconsin-Madison, Madison, WI, USA
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI, USA
| | - Sunnie Grace McCalla
- Wisconsin Institute for Discovery, University of Wisconsin-Madison, Madison, WI, USA
- Laboratory of Genetics, University of Wisconsin-Madison, Madison, WI, 53706, USA
| | - Alireza Fotuhi Siahpirani
- Wisconsin Institute for Discovery, University of Wisconsin-Madison, Madison, WI, USA
- Department of Bioinformatics, Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran
| | - Rupa Sridharan
- Wisconsin Institute for Discovery, University of Wisconsin-Madison, Madison, WI, USA
- Department of Cell and Regenerative Biology, University of Wisconsin-Madison, Madison, WI, USA
| | - Sushmita Roy
- Wisconsin Institute for Discovery, University of Wisconsin-Madison, Madison, WI, USA.
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI, USA.
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92
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Gong W, Dsouza N, Garry DJ. SeATAC: a tool for exploring the chromatin landscape and the role of pioneer factors. Genome Biol 2023; 24:125. [PMID: 37218013 DOI: 10.1186/s13059-023-02954-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Accepted: 04/27/2023] [Indexed: 05/24/2023] Open
Abstract
Assay for Transposase-Accessible Chromatin with sequencing (ATAC-seq) reveals chromatin accessibility across the genome. Currently, no method specifically detects differential chromatin accessibility. Here, SeATAC uses a conditional variational autoencoder model to learn the latent representation of ATAC-seq V-plots and outperforms MACS2 and NucleoATAC on six separate tasks. Applying SeATAC to several pioneer factor-induced differentiation or reprogramming ATAC-seq datasets suggests that induction of these factors not only relaxes the closed chromatin but also decreases chromatin accessibility of 20% to 30% of their target sites. SeATAC is a novel tool to accurately reveal genomic regions with differential chromatin accessibility from ATAC-seq data.
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Affiliation(s)
- Wuming Gong
- Cardiovascular Division, Department of Medicine, University of Minnesota, Minneapolis, MN, 55455, USA.
- Lillehei Heart Institute, University of Minnesota, 2231 6Th St SE, Minneapolis, MN, 55455, USA.
| | - Nikita Dsouza
- Cardiovascular Division, Department of Medicine, University of Minnesota, Minneapolis, MN, 55455, USA
| | - Daniel J Garry
- Cardiovascular Division, Department of Medicine, University of Minnesota, Minneapolis, MN, 55455, USA.
- Lillehei Heart Institute, University of Minnesota, 2231 6Th St SE, Minneapolis, MN, 55455, USA.
- Stem Cell Institute, University of Minnesota, Minneapolis, MN, 55455, USA.
- Paul and Sheila Wellstone Muscular Dystrophy Center, University of Minnesota, Minneapolis, MN, 55455, USA.
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93
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Tognon M, Giugno R, Pinello L. A survey on algorithms to characterize transcription factor binding sites. Brief Bioinform 2023; 24:bbad156. [PMID: 37099664 PMCID: PMC10422928 DOI: 10.1093/bib/bbad156] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Revised: 03/27/2023] [Accepted: 04/01/2023] [Indexed: 04/28/2023] Open
Abstract
Transcription factors (TFs) are key regulatory proteins that control the transcriptional rate of cells by binding short DNA sequences called transcription factor binding sites (TFBS) or motifs. Identifying and characterizing TFBS is fundamental to understanding the regulatory mechanisms governing the transcriptional state of cells. During the last decades, several experimental methods have been developed to recover DNA sequences containing TFBS. In parallel, computational methods have been proposed to discover and identify TFBS motifs based on these DNA sequences. This is one of the most widely investigated problems in bioinformatics and is referred to as the motif discovery problem. In this manuscript, we review classical and novel experimental and computational methods developed to discover and characterize TFBS motifs in DNA sequences, highlighting their advantages and drawbacks. We also discuss open challenges and future perspectives that could fill the remaining gaps in the field.
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Affiliation(s)
- Manuel Tognon
- Computer Science Department, University of Verona, Verona, Italy
- Molecular Pathology Unit, Center for Computational and Integrative Biology and Center for Cancer Research, Massachusetts General Hospital, Charlestown, Massachusetts, United States of America
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
| | - Rosalba Giugno
- Computer Science Department, University of Verona, Verona, Italy
| | - Luca Pinello
- Molecular Pathology Unit, Center for Computational and Integrative Biology and Center for Cancer Research, Massachusetts General Hospital, Charlestown, Massachusetts, United States of America
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
- Department of Pathology, Harvard Medical School, Boston, Massachusetts, United States of America
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94
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Salemme V, Centonze G, Avalle L, Natalini D, Piccolantonio A, Arina P, Morellato A, Ala U, Taverna D, Turco E, Defilippi P. The role of tumor microenvironment in drug resistance: emerging technologies to unravel breast cancer heterogeneity. Front Oncol 2023; 13:1170264. [PMID: 37265795 PMCID: PMC10229846 DOI: 10.3389/fonc.2023.1170264] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Accepted: 04/28/2023] [Indexed: 06/03/2023] Open
Abstract
Breast cancer is a highly heterogeneous disease, at both inter- and intra-tumor levels, and this heterogeneity is a crucial determinant of malignant progression and response to treatments. In addition to genetic diversity and plasticity of cancer cells, the tumor microenvironment contributes to tumor heterogeneity shaping the physical and biological surroundings of the tumor. The activity of certain types of immune, endothelial or mesenchymal cells in the microenvironment can change the effectiveness of cancer therapies via a plethora of different mechanisms. Therefore, deciphering the interactions between the distinct cell types, their spatial organization and their specific contribution to tumor growth and drug sensitivity is still a major challenge. Dissecting intra-tumor heterogeneity is currently an urgent need to better define breast cancer biology and to develop therapeutic strategies targeting the microenvironment as helpful tools for combined and personalized treatment. In this review, we analyze the mechanisms by which the tumor microenvironment affects the characteristics of tumor heterogeneity that ultimately result in drug resistance, and we outline state of the art preclinical models and emerging technologies that will be instrumental in unraveling the impact of the tumor microenvironment on resistance to therapies.
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Affiliation(s)
- Vincenzo Salemme
- Department of Molecular Biotechnology and Health Sciences, University of Turin, Turin, Italy
- Molecular Biotechnology Center (MBC) “Guido Tarone”, Turin, Italy
| | - Giorgia Centonze
- Department of Molecular Biotechnology and Health Sciences, University of Turin, Turin, Italy
- Molecular Biotechnology Center (MBC) “Guido Tarone”, Turin, Italy
| | - Lidia Avalle
- Department of Molecular Biotechnology and Health Sciences, University of Turin, Turin, Italy
- Molecular Biotechnology Center (MBC) “Guido Tarone”, Turin, Italy
| | - Dora Natalini
- Department of Molecular Biotechnology and Health Sciences, University of Turin, Turin, Italy
- Molecular Biotechnology Center (MBC) “Guido Tarone”, Turin, Italy
| | - Alessio Piccolantonio
- Department of Molecular Biotechnology and Health Sciences, University of Turin, Turin, Italy
- Molecular Biotechnology Center (MBC) “Guido Tarone”, Turin, Italy
| | - Pietro Arina
- UCL, Bloomsbury Institute of Intensive Care Medicine, Division of Medicine, University College London, London, United Kingdom
| | - Alessandro Morellato
- Department of Molecular Biotechnology and Health Sciences, University of Turin, Turin, Italy
- Molecular Biotechnology Center (MBC) “Guido Tarone”, Turin, Italy
| | - Ugo Ala
- Department of Veterinary Sciences, University of Turin, Grugliasco, TO, Italy
| | - Daniela Taverna
- Department of Molecular Biotechnology and Health Sciences, University of Turin, Turin, Italy
- Molecular Biotechnology Center (MBC) “Guido Tarone”, Turin, Italy
| | - Emilia Turco
- Department of Molecular Biotechnology and Health Sciences, University of Turin, Turin, Italy
| | - Paola Defilippi
- Department of Molecular Biotechnology and Health Sciences, University of Turin, Turin, Italy
- Molecular Biotechnology Center (MBC) “Guido Tarone”, Turin, Italy
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95
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Hu N, Wang J, Ju B, Li Y, Fan P, Jin X, Kang X, Wu S. Recent advances of osteoimmunology research in rheumatoid arthritis: From single-cell omics approach. Chin Med J (Engl) 2023:00029330-990000000-00608. [PMID: 37166215 DOI: 10.1097/cm9.0000000000002678] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Indexed: 05/12/2023] Open
Abstract
ABSTRACT Cellular immune responses as well as generalized and periarticular bone loss are the key pathogenic features of rheumatoid arthritis (RA). Under the pathological conditions of RA, dysregulated inflammation and immune processes tightly interact with skeletal system, resulting in pathological bone damage via inhibition of bone formation or induction of bone resorption. Single-cell omics technologies are revolutionary tools in the field of modern biological research.They enable the display of the state and function of cells in various environments from a single-cell resolution, thus making it conducive to identify the dysregulated molecular mechanisms of bone destruction in RA as well as the discovery of potential therapeutic targets and biomarkers. Here, we summarize the latest findings of single-cell omics technologies in osteoimmunology research in RA. These results suggest that single-cell omics have made significant contributions to transcriptomics and dynamics of specific cells involved in bone remodeling, providing a new direction for our understanding of cellular heterogeneity in the study of osteoimmunology in RA.
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Affiliation(s)
- Nan Hu
- Department of Rheumatology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710061, China
| | - Jing Wang
- Department of Rheumatology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710061, China
| | - Bomiao Ju
- Department of Rheumatology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710061, China
| | - Yuanyuan Li
- Department of Rheumatology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710061, China
| | - Ping Fan
- Department of Rheumatology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710061, China
| | - Xinxin Jin
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi 710061, China
| | - Xiaomin Kang
- Center for Translational Medicine, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710061, China
| | - Shufang Wu
- Center for Translational Medicine, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710061, China
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96
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Turkalj S, Jakobsen NA, Groom A, Metzner M, Riva SG, Gür ER, Usukhbayar B, Salazar MA, Hentges LD, Mickute G, Clark K, Sopp P, Davies JOJ, Hughes JR, Vyas P. GTAC enables parallel genotyping of multiple genomic loci with chromatin accessibility profiling in single cells. Cell Stem Cell 2023; 30:722-740.e11. [PMID: 37146586 DOI: 10.1016/j.stem.2023.04.012] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2022] [Revised: 02/23/2023] [Accepted: 04/12/2023] [Indexed: 05/07/2023]
Abstract
Understanding clonal evolution and cancer development requires experimental approaches for characterizing the consequences of somatic mutations on gene regulation. However, no methods currently exist that efficiently link high-content chromatin accessibility with high-confidence genotyping in single cells. To address this, we developed Genotyping with the Assay for Transposase-Accessible Chromatin (GTAC), enabling accurate mutation detection at multiple amplified loci, coupled with robust chromatin accessibility readout. We applied GTAC to primary acute myeloid leukemia, obtaining high-quality chromatin accessibility profiles and clonal identities for multiple mutations in 88% of cells. We traced chromatin variation throughout clonal evolution, showing the restriction of different clones to distinct differentiation stages. Furthermore, we identified switches in transcription factor motif accessibility associated with a specific combination of driver mutations, which biased transformed progenitors toward a leukemia stem cell-like chromatin state. GTAC is a powerful tool to study clonal heterogeneity across a wide spectrum of pre-malignant and neoplastic conditions.
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Affiliation(s)
- Sven Turkalj
- MRC Molecular Haematology Unit, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK; Oxford Centre for Haematology, NIHR Oxford Biomedical Research Centre, Oxford, UK
| | - Niels Asger Jakobsen
- MRC Molecular Haematology Unit, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK; Oxford Centre for Haematology, NIHR Oxford Biomedical Research Centre, Oxford, UK; Department of Haematology, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Angus Groom
- MRC Molecular Haematology Unit, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK; Oxford Centre for Haematology, NIHR Oxford Biomedical Research Centre, Oxford, UK
| | - Marlen Metzner
- MRC Molecular Haematology Unit, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK; Oxford Centre for Haematology, NIHR Oxford Biomedical Research Centre, Oxford, UK
| | - Simone G Riva
- MRC Molecular Haematology Unit, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK; MRC WIMM Centre for Computational Biology, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - E Ravza Gür
- MRC Molecular Haematology Unit, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK; MRC WIMM Centre for Computational Biology, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - Batchimeg Usukhbayar
- MRC Molecular Haematology Unit, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK; Oxford Centre for Haematology, NIHR Oxford Biomedical Research Centre, Oxford, UK
| | - Mirian Angulo Salazar
- MRC Molecular Haematology Unit, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK; Oxford Centre for Haematology, NIHR Oxford Biomedical Research Centre, Oxford, UK
| | - Lance D Hentges
- MRC Molecular Haematology Unit, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK; MRC WIMM Centre for Computational Biology, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - Gerda Mickute
- MRC Molecular Haematology Unit, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK; Oxford Centre for Haematology, NIHR Oxford Biomedical Research Centre, Oxford, UK
| | - Kevin Clark
- Flow Cytometry Facility, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - Paul Sopp
- Flow Cytometry Facility, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - James O J Davies
- MRC Molecular Haematology Unit, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK; Oxford Centre for Haematology, NIHR Oxford Biomedical Research Centre, Oxford, UK; Department of Haematology, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Jim R Hughes
- MRC Molecular Haematology Unit, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK; MRC WIMM Centre for Computational Biology, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - Paresh Vyas
- MRC Molecular Haematology Unit, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK; Oxford Centre for Haematology, NIHR Oxford Biomedical Research Centre, Oxford, UK; Department of Haematology, Oxford University Hospitals NHS Foundation Trust, Oxford, UK.
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97
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Salma M, Andrieu-Soler C, Deleuze V, Soler E. High-throughput methods for the analysis of transcription factors and chromatin modifications: Low input, single cell and spatial genomic technologies. Blood Cells Mol Dis 2023; 101:102745. [PMID: 37121019 DOI: 10.1016/j.bcmd.2023.102745] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2023] [Revised: 04/20/2023] [Accepted: 04/20/2023] [Indexed: 05/02/2023]
Abstract
Genome-wide analysis of transcription factors and epigenomic features is instrumental to shed light on DNA-templated regulatory processes such as transcription, cellular differentiation or to monitor cellular responses to environmental cues. Two decades of technological developments have led to a rich set of approaches progressively pushing the limits of epigenetic profiling towards single cells. More recently, disruptive technologies using innovative biochemistry came into play. Assays such as CUT&RUN, CUT&Tag and variations thereof show considerable potential to survey multiple TFs or histone modifications in parallel from a single experiment and in native conditions. These are in the path to become the dominant assays for genome-wide analysis of TFs and chromatin modifications in bulk, single-cell, and spatial genomic applications. The principles together with pros and cons are discussed.
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Affiliation(s)
- Mohammad Salma
- Institut de Génétique Moléculaire de Montpellier, Univ Montpellier, CNRS, Montpellier, France; Université de Paris, Laboratory of Excellence GR-Ex, France
| | - Charlotte Andrieu-Soler
- Institut de Génétique Moléculaire de Montpellier, Univ Montpellier, CNRS, Montpellier, France; Université de Paris, Laboratory of Excellence GR-Ex, France
| | - Virginie Deleuze
- Institut de Génétique Moléculaire de Montpellier, Univ Montpellier, CNRS, Montpellier, France; Université de Paris, Laboratory of Excellence GR-Ex, France
| | - Eric Soler
- Institut de Génétique Moléculaire de Montpellier, Univ Montpellier, CNRS, Montpellier, France; Université de Paris, Laboratory of Excellence GR-Ex, France.
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98
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Ueda K. Review: MDMX plays a central role in leukemic transformation and may be a promising target for leukemia prevention strategies. Exp Hematol 2023:S0301-472X(23)00161-3. [PMID: 37086813 DOI: 10.1016/j.exphem.2023.04.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2023] [Revised: 04/13/2023] [Accepted: 04/14/2023] [Indexed: 04/24/2023]
Abstract
Acute myeloid leukemia (AML) is a fatal disease resulting from preleukemic hematopoietic conditions including asymptomatic clonal hematopoiesis. The accumulation of genetic changes is one of the causes of leukemic transformation. However, nongenetic factors including the overexpression of specific genes also contribute to preleukemic to leukemic transition. Among them, the p53 inhibitor Murine Double Minute X (MDMX) plays crucial roles especially in leukemia initiation. MDMX is broadly overexpressed in vast majority of AML cases, including in hematopoietic stem/progenitor cell (HSPC) level. Recently, high expression of MDMX in HSPC has been shown to be associated with leukemic transformation in patients with myelodysplastic syndromes, and preclinical studies demonstrated that MDMX overexpression accelerates the transformation of preleukemic murine models, including models of clonal hematopoiesis. MDMX inhibition, through activation of cell-intrinsic p53 activity, shows antileukemic effects. However, the molecular mechanisms of MDMX in provoking leukemic transformation are complicated. Both p53-dependent and independent mechanisms are involved in the progression of the disease. This review discusses the canonical and noncanonical functions of MDMX and how these functions are involved in the maintenance, expansion, and progression to malignancy of preleukemic stem cells. Moreover, strategies on how leukemic transformation could possibly be prevented by targeting MDMX in preleukemic stem cells are discussed.
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Affiliation(s)
- Koki Ueda
- Department of Blood Transfusion and Transplantation Immunology, Fukushima Medical University, Fukushima, Fukushima 9601295, Japan; Department of Cell Biology, Albert Einstein College of Medicine, Bronx, New York 10461, USA.
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99
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Montalban-Bravo G, Ma F, Thongon N, Yang H, Gomez IG, Rodriguez-Sevilla JJ, Adema V, Wildeman B, Lockyer P, Kim YJ, Tanaka T, Darbaniyan F, Pancholy S, Zhang G, Al-Atrash G, Dwyer K, Takahashi K, Garcia-Manero G, Kantarjian H, Colla S. Targeting MCL1-driven anti-apoptotic pathways to overcome hypomethylating agent resistance in RAS -mutated chronic myelomonocytic leukemia. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.04.07.535928. [PMID: 37066354 PMCID: PMC10104149 DOI: 10.1101/2023.04.07.535928] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/18/2023]
Abstract
RAS pathway mutations, which are present in 30% of patients with chronic myelomonocytic leukemia (CMML) at diagnosis, confer a high risk of resistance to and progression after hypomethylating agent (HMA) therapy, the current standard of care for the disease. Using single-cell, multi-omics technologies, we sought to dissect the biological mechanisms underlying the initiation and progression of RAS pathway-mutated CMML. We found that RAS pathway mutations induced the transcriptional reprogramming of hematopoietic stem and progenitor cells (HSPCs), which underwent proliferation and monocytic differentiation in response to cell-intrinsic and -extrinsic inflammatory signaling that also impaired immune cells' functions. HSPCs expanded at disease progression and relied on the NF- K B pathway effector MCL1 to maintain their survival, which explains why patients with RAS pathway- mutated CMML do not benefit from BCL2 inhibitors such as venetoclax. Our study has implications for developing therapies to improve the survival of patients with RAS pathway- mutated CMML.
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100
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Pregizer S, Vreven T, Mathur M, Robinson LN. Multi-omic single cell sequencing: Overview and opportunities for kidney disease therapeutic development. Front Mol Biosci 2023; 10:1176856. [PMID: 37091871 PMCID: PMC10113659 DOI: 10.3389/fmolb.2023.1176856] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Accepted: 03/21/2023] [Indexed: 04/09/2023] Open
Abstract
Single cell sequencing technologies have rapidly advanced in the last decade and are increasingly applied to gain unprecedented insights by deconstructing complex biology to its fundamental unit, the individual cell. First developed for measurement of gene expression, single cell sequencing approaches have evolved to allow simultaneous profiling of multiple additional features, including chromatin accessibility within the nucleus and protein expression at the cell surface. These multi-omic approaches can now further be applied to cells in situ, capturing the spatial context within which their biology occurs. To extract insights from these complex datasets, new computational tools have facilitated the integration of information across different data types and the use of machine learning approaches. Here, we summarize current experimental and computational methods for generation and integration of single cell multi-omic datasets. We focus on opportunities for multi-omic single cell sequencing to augment therapeutic development for kidney disease, including applications for biomarkers, disease stratification and target identification.
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