101
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The evolving metabolic landscape of chromatin biology and epigenetics. Nat Rev Genet 2020; 21:737-753. [PMID: 32908249 DOI: 10.1038/s41576-020-0270-8] [Citation(s) in RCA: 241] [Impact Index Per Article: 60.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/16/2020] [Indexed: 12/12/2022]
Abstract
Molecular inputs to chromatin via cellular metabolism are modifiers of the epigenome. These inputs - which include both nutrient availability as a result of diet and growth factor signalling - are implicated in linking the environment to the maintenance of cellular homeostasis and cell identity. Recent studies have demonstrated that these inputs are much broader than had previously been known, encompassing metabolism from a wide variety of sources, including alcohol and microbiotal metabolism. These factors modify DNA and histones and exert specific effects on cell biology, systemic physiology and pathology. In this Review, we discuss the nature of these molecular networks, highlight their role in mediating cellular responses and explore their modifiability through dietary and pharmacological interventions.
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102
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Zion EH, Chandrasekhara C, Chen X. Asymmetric inheritance of epigenetic states in asymmetrically dividing stem cells. Curr Opin Cell Biol 2020; 67:27-36. [PMID: 32871437 DOI: 10.1016/j.ceb.2020.08.003] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2020] [Revised: 07/30/2020] [Accepted: 08/03/2020] [Indexed: 12/12/2022]
Abstract
Asymmetric cell division produces two cells that are genetically identical but each have distinctly different cell fates. During this process, epigenetic mechanisms play an important role in allowing the two daughter cells to have unique gene expression profiles that lead to their specific cell identities. Although the process of duplicating and segregating the genetic information during the cell cycle has been well studied, the question of how epigenetic information is duplicated and partitioned still remains. In this review, we discuss recent advances in understanding how epigenetic states are established and inherited, with emphasis on the asymmetric inheritance patterns of histones, DNA methylation, nonhistone proteins, RNAs, and organelles. We also discuss how misregulation of these processes may lead to diseases such as cancer and tissue degeneration.
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Affiliation(s)
- Emily H Zion
- Department of Biology, The Johns Hopkins University, 3400 North Charles Street, Baltimore, MD, 21218, USA
| | - Chinmayi Chandrasekhara
- Department of Biology, The Johns Hopkins University, 3400 North Charles Street, Baltimore, MD, 21218, USA
| | - Xin Chen
- Department of Biology, The Johns Hopkins University, 3400 North Charles Street, Baltimore, MD, 21218, USA.
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103
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de Vries NL, Mahfouz A, Koning F, de Miranda NFCC. Unraveling the Complexity of the Cancer Microenvironment With Multidimensional Genomic and Cytometric Technologies. Front Oncol 2020; 10:1254. [PMID: 32793500 PMCID: PMC7390924 DOI: 10.3389/fonc.2020.01254] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2020] [Accepted: 06/17/2020] [Indexed: 12/26/2022] Open
Abstract
Cancers are characterized by extensive heterogeneity that occurs intratumorally, between lesions, and across patients. To study cancer as a complex biological system, multidimensional analyses of the tumor microenvironment are paramount. Single-cell technologies such as flow cytometry, mass cytometry, or single-cell RNA-sequencing have revolutionized our ability to characterize individual cells in great detail and, with that, shed light on the complexity of cancer microenvironments. However, a key limitation of these single-cell technologies is the lack of information on spatial context and multicellular interactions. Investigating spatial contexts of cells requires the incorporation of tissue-based techniques such as multiparameter immunofluorescence, imaging mass cytometry, or in situ detection of transcripts. In this Review, we describe the rise of multidimensional single-cell technologies and provide an overview of their strengths and weaknesses. In addition, we discuss the integration of transcriptomic, genomic, epigenomic, proteomic, and spatially-resolved data in the context of human cancers. Lastly, we will deliberate on how the integration of multi-omics data will help to shed light on the complex role of cell types present within the human tumor microenvironment, and how such system-wide approaches may pave the way toward more effective therapies for the treatment of cancer.
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Affiliation(s)
- Natasja L. de Vries
- Pathology, Leiden University Medical Center, Leiden, Netherlands
- Immunohematology and Blood Transfusion, Leiden University Medical Center, Leiden, Netherlands
| | - Ahmed Mahfouz
- Human Genetics, Leiden University Medical Center, Leiden, Netherlands
- Delft Bioinformatics Laboratory, Delft University of Technology, Delft, Netherlands
- Leiden Computational Biology Center, Leiden University Medical Center, Leiden, Netherlands
| | - Frits Koning
- Immunohematology and Blood Transfusion, Leiden University Medical Center, Leiden, Netherlands
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104
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Abstract
Organ constructs are organ-like structures grown in vitro or in vivo that harbor the components, architecture, and function of in vivo organs, in part or in toto. The convergence of stem cell biology, bioengineering, and gene editing tools have substantially broadened our ability to generate various types of organ constructs for regenerative medicine as well as to address pressing biomedical questions. In this Review, we highlight prevailing approaches for generating organ constructs, from organoids to chimeric organ engineering. We also discuss design principles of different approaches, their utility and limitations, and propose strategies to resolve existing hurdles.
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Affiliation(s)
- Yun Xia
- Lee Kong Chian School of Medicine, Nanyang Technological University, 11 Mandalay Road, Singapore 308232, Singapore.
| | - Juan Carlos Izpisua Belmonte
- Gene Expression Laboratory, Salk Institute for Biological Studies, 10010 North Torrey Pines Road, La Jolla, CA 92037, USA.
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105
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Hu X, Hu Y, Wu F, Leung RWT, Qin J. Integration of single-cell multi-omics for gene regulatory network inference. Comput Struct Biotechnol J 2020; 18:1925-1938. [PMID: 32774787 PMCID: PMC7385034 DOI: 10.1016/j.csbj.2020.06.033] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2020] [Revised: 06/17/2020] [Accepted: 06/20/2020] [Indexed: 12/20/2022] Open
Abstract
The advancement of single-cell sequencing technology in recent years has provided an opportunity to reconstruct gene regulatory networks (GRNs) with the data from thousands of single cells in one sample. This uncovers regulatory interactions in cells and speeds up the discoveries of regulatory mechanisms in diseases and biological processes. Therefore, more methods have been proposed to reconstruct GRNs using single-cell sequencing data. In this review, we introduce technologies for sequencing single-cell genome, transcriptome, and epigenome. At the same time, we present an overview of current GRN reconstruction strategies utilizing different single-cell sequencing data. Bioinformatics tools were grouped by their input data type and mathematical principles for reader's convenience, and the fundamental mathematics inherent in each group will be discussed. Furthermore, the adaptabilities and limitations of these different methods will also be summarized and compared, with the hope to facilitate researchers recognizing the most suitable tools for them.
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Affiliation(s)
- Xinlin Hu
- Shenzhen Key Laboratory of Advanced Machine Learning and Applications, College of Mathematics and Statistics, Shenzhen University, Shenzhen 518060, China
| | - Yaohua Hu
- Shenzhen Key Laboratory of Advanced Machine Learning and Applications, College of Mathematics and Statistics, Shenzhen University, Shenzhen 518060, China
| | - Fanjie Wu
- School of Pharmaceutical Sciences (Shenzhen), Sun Yat-sen University, Shenzhen 518107, China
| | - Ricky Wai Tak Leung
- School of Pharmaceutical Sciences (Shenzhen), Sun Yat-sen University, Shenzhen 518107, China
| | - Jing Qin
- School of Pharmaceutical Sciences (Shenzhen), Sun Yat-sen University, Shenzhen 518107, China
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106
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Markodimitraki CM, Rang FJ, Rooijers K, de Vries SS, Chialastri A, de Luca KL, Lochs SJA, Mooijman D, Dey SS, Kind J. Simultaneous quantification of protein-DNA interactions and transcriptomes in single cells with scDam&T-seq. Nat Protoc 2020; 15:1922-1953. [PMID: 32350457 PMCID: PMC7779467 DOI: 10.1038/s41596-020-0314-8] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2019] [Accepted: 02/17/2020] [Indexed: 12/31/2022]
Abstract
Protein-DNA interactions are essential for establishing cell type-specific chromatin architecture and gene expression. We recently developed scDam&T-seq, a multi-omics method that can simultaneously quantify protein-DNA interactions and the transcriptome in single cells. The method effectively combines two existing methods: DNA adenine methyltransferase identification (DamID) and CEL-Seq2. DamID works through the tethering of a protein of interest (POI) to the Escherichia coli DNA adenine methyltransferase (Dam). Upon expression of this fusion protein, DNA in proximity to the POI is methylated by Dam and can be selectively digested and amplified. CEL-Seq2, in contrast, makes use of poly-dT primers to reverse transcribe mRNA, followed by linear amplification through in vitro transcription. scDam&T-seq is the first technique capable of providing a combined readout of protein-DNA contact and transcription from single-cell samples. Once suitable cell lines have been established, the protocol can be completed in 5 d, with a throughput of hundreds to thousands of cells. The processing of raw sequencing data takes an additional 1-2 d. Our method can be used to understand the transcriptional changes a cell undergoes upon the DNA binding of a POI. It can be performed in any laboratory with access to FACS, robotic and high-throughput-sequencing facilities.
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Affiliation(s)
- Corina M Markodimitraki
- Oncode Institute, Hubrecht Institute-KNAW and University Medical Center Utrecht, Utrecht, the Netherlands
| | - Franka J Rang
- Oncode Institute, Hubrecht Institute-KNAW and University Medical Center Utrecht, Utrecht, the Netherlands
| | - Koos Rooijers
- Oncode Institute, Hubrecht Institute-KNAW and University Medical Center Utrecht, Utrecht, the Netherlands
| | - Sandra S de Vries
- Oncode Institute, Hubrecht Institute-KNAW and University Medical Center Utrecht, Utrecht, the Netherlands
| | - Alex Chialastri
- Department of Chemical Engineering, University of California Santa Barbara, Santa Barbara, CA, USA
- Center for Bioengineering, University of California Santa Barbara, Santa Barbara, CA, USA
| | - Kim L de Luca
- Oncode Institute, Hubrecht Institute-KNAW and University Medical Center Utrecht, Utrecht, the Netherlands
| | - Silke J A Lochs
- Oncode Institute, Hubrecht Institute-KNAW and University Medical Center Utrecht, Utrecht, the Netherlands
| | - Dylan Mooijman
- Oncode Institute, Hubrecht Institute-KNAW and University Medical Center Utrecht, Utrecht, the Netherlands
- Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Siddharth S Dey
- Department of Chemical Engineering, University of California Santa Barbara, Santa Barbara, CA, USA.
- Center for Bioengineering, University of California Santa Barbara, Santa Barbara, CA, USA.
| | - Jop Kind
- Oncode Institute, Hubrecht Institute-KNAW and University Medical Center Utrecht, Utrecht, the Netherlands.
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107
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Lederer AR, La Manno G. The emergence and promise of single-cell temporal-omics approaches. Curr Opin Biotechnol 2020; 63:70-78. [DOI: 10.1016/j.copbio.2019.12.005] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2019] [Revised: 12/03/2019] [Accepted: 12/08/2019] [Indexed: 12/13/2022]
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108
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Hosur V, Skelly DA, Francis C, Low BE, Kohar V, Burzenski LM, Amiji MM, Shultz LD, Wiles MV. Improved mouse models and advanced genetic and genomic technologies for the study of neutrophils. Drug Discov Today 2020; 25:1013-1025. [PMID: 32387410 DOI: 10.1016/j.drudis.2020.03.018] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2020] [Revised: 03/16/2020] [Accepted: 03/30/2020] [Indexed: 12/31/2022]
Abstract
Mice have been excellent surrogates for studying neutrophil biology and, furthermore, murine models of human disease have provided fundamental insights into the roles of human neutrophils in innate immunity. The emergence of novel humanized mice and high-diversity mouse populations offers the research community innovative and powerful platforms for better understanding, respectively, the mechanisms by which human neutrophils drive pathogenicity, and how genetic differences underpin the variation in neutrophil biology observed among humans. Here, we review key examples of these new resources. Additionally, we provide an overview of advanced genetic engineering tools available to further improve such murine model systems, of sophisticated neutrophil-profiling technologies, and of multifunctional nanoparticle (NP)-based neutrophil-targeting strategies.
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Affiliation(s)
- Vishnu Hosur
- The Jackson Laboratory for Mammalian Genetics, 600 Main Street, Bar Harbor, ME 04609 USA.
| | - Daniel A Skelly
- The Jackson Laboratory for Mammalian Genetics, 600 Main Street, Bar Harbor, ME 04609 USA
| | - Christopher Francis
- Department of Pharmaceutical Sciences, School of Pharmacy, Northeastern University, 360 Huntington Avenue, Boston, MA 02115 USA
| | - Benjamin E Low
- The Jackson Laboratory for Mammalian Genetics, 600 Main Street, Bar Harbor, ME 04609 USA
| | - Vivek Kohar
- The Jackson Laboratory for Mammalian Genetics, 600 Main Street, Bar Harbor, ME 04609 USA
| | - Lisa M Burzenski
- The Jackson Laboratory for Mammalian Genetics, 600 Main Street, Bar Harbor, ME 04609 USA
| | - Mansoor M Amiji
- Department of Pharmaceutical Sciences, School of Pharmacy, Northeastern University, 360 Huntington Avenue, Boston, MA 02115 USA
| | - Leonard D Shultz
- The Jackson Laboratory for Mammalian Genetics, 600 Main Street, Bar Harbor, ME 04609 USA
| | - Michael V Wiles
- The Jackson Laboratory for Mammalian Genetics, 600 Main Street, Bar Harbor, ME 04609 USA
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109
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Gasperini M, Tome JM, Shendure J. Towards a comprehensive catalogue of validated and target-linked human enhancers. Nat Rev Genet 2020; 21:292-310. [PMID: 31988385 PMCID: PMC7845138 DOI: 10.1038/s41576-019-0209-0] [Citation(s) in RCA: 159] [Impact Index Per Article: 39.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/13/2019] [Indexed: 12/14/2022]
Abstract
The human gene catalogue is essentially complete, but we lack an equivalently vetted inventory of bona fide human enhancers. Hundreds of thousands of candidate enhancers have been nominated via biochemical annotations; however, only a handful of these have been validated and confidently linked to their target genes. Here we review emerging technologies for discovering, characterizing and validating human enhancers at scale. We furthermore propose a new framework for operationally defining enhancers that accommodates the heterogeneous and complementary results that are emerging from reporter assays, biochemical measurements and CRISPR screens.
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Affiliation(s)
- Molly Gasperini
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Jacob M Tome
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Jay Shendure
- Department of Genome Sciences, University of Washington, Seattle, WA, USA.
- Brotman Baty Institute for Precision Medicine, Seattle, WA, USA.
- Allen Discovery Center for Cell Lineage, Seattle, WA, USA.
- Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA.
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110
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Domingues AF, Kulkarni R, Giotopoulos G, Gupta S, Vinnenberg L, Arede L, Foerner E, Khalili M, Adao RR, Johns A, Tan S, Zeka K, Huntly BJ, Prabakaran S, Pina C. Loss of Kat2a enhances transcriptional noise and depletes acute myeloid leukemia stem-like cells. eLife 2020; 9:e51754. [PMID: 31985402 PMCID: PMC7039681 DOI: 10.7554/elife.51754] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2019] [Accepted: 01/24/2020] [Indexed: 12/21/2022] Open
Abstract
Acute Myeloid Leukemia (AML) is an aggressive hematological malignancy with abnormal progenitor self-renewal and defective white blood cell differentiation. Its pathogenesis comprises subversion of transcriptional regulation, through mutation and by hijacking normal chromatin regulation. Kat2a is a histone acetyltransferase central to promoter activity, that we recently associated with stability of pluripotency networks, and identified as a genetic vulnerability in AML. Through combined chromatin profiling and single-cell transcriptomics of a conditional knockout mouse, we demonstrate that Kat2a contributes to leukemia propagation through preservation of leukemia stem-like cells. Kat2a loss impacts transcription factor binding and reduces transcriptional burst frequency in a subset of gene promoters, generating enhanced variability of transcript levels. Destabilization of target programs shifts leukemia cell fate out of self-renewal into differentiation. We propose that control of transcriptional variability is central to leukemia stem-like cell propagation, and establish a paradigm exploitable in different tumors and distinct stages of cancer evolution.
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Affiliation(s)
- Ana Filipa Domingues
- Department of HaematologyUniversity of Cambridge, NHS-BT Blood Donor CentreCambridgeUnited Kingdom
| | - Rashmi Kulkarni
- Department of HaematologyUniversity of Cambridge, NHS-BT Blood Donor CentreCambridgeUnited Kingdom
| | - George Giotopoulos
- Department of HaematologyUniversity of Cambridge, Cambridge Institute for Medical ResearchCambridgeUnited Kingdom
- Wellcome Trust-Medical Research Council Cambridge Stem Cell InstituteCambridgeUnited Kingdom
| | - Shikha Gupta
- Department of HaematologyUniversity of Cambridge, NHS-BT Blood Donor CentreCambridgeUnited Kingdom
- Department of GeneticsUniversity of CambridgeCambridgeUnited Kingdom
| | - Laura Vinnenberg
- Department of HaematologyUniversity of Cambridge, NHS-BT Blood Donor CentreCambridgeUnited Kingdom
| | - Liliana Arede
- Department of HaematologyUniversity of Cambridge, NHS-BT Blood Donor CentreCambridgeUnited Kingdom
- Department of GeneticsUniversity of CambridgeCambridgeUnited Kingdom
| | - Elena Foerner
- Department of HaematologyUniversity of Cambridge, NHS-BT Blood Donor CentreCambridgeUnited Kingdom
| | - Mitra Khalili
- Department of HaematologyUniversity of Cambridge, NHS-BT Blood Donor CentreCambridgeUnited Kingdom
- Department of Medical Genetics and Molecular Medicine, School of MedicineZanjan University of Medical Sciences (ZUMS)ZanjanIslamic Republic of Iran
| | - Rita Romano Adao
- Department of HaematologyUniversity of Cambridge, NHS-BT Blood Donor CentreCambridgeUnited Kingdom
| | - Ayona Johns
- Division of Biosciences, College of Health and Life SciencesBrunel University LondonUxbridgeUnited Kingdom
| | - Shengjiang Tan
- Department of HaematologyUniversity of Cambridge, Cambridge Institute for Medical ResearchCambridgeUnited Kingdom
| | - Keti Zeka
- Department of HaematologyUniversity of Cambridge, NHS-BT Blood Donor CentreCambridgeUnited Kingdom
- Department of GeneticsUniversity of CambridgeCambridgeUnited Kingdom
| | - Brian J Huntly
- Department of HaematologyUniversity of Cambridge, Cambridge Institute for Medical ResearchCambridgeUnited Kingdom
- Wellcome Trust-Medical Research Council Cambridge Stem Cell InstituteCambridgeUnited Kingdom
| | - Sudhakaran Prabakaran
- Department of GeneticsUniversity of CambridgeCambridgeUnited Kingdom
- Department of BiologyIISERPuneIndia
| | - Cristina Pina
- Department of GeneticsUniversity of CambridgeCambridgeUnited Kingdom
- Division of Biosciences, College of Health and Life SciencesBrunel University LondonUxbridgeUnited Kingdom
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111
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Kang K, Wang X, Meng C, He L, Sang X, Zheng Y, Xu H. The application of single-cell sequencing technology in the diagnosis and treatment of hepatocellular carcinoma. ANNALS OF TRANSLATIONAL MEDICINE 2019; 7:790. [PMID: 32042806 DOI: 10.21037/atm.2019.11.116] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Single-cell sequencing technology refers to the sequencing of the genome, transcriptome and epigenome in one single cell. Comparing to traditional histology, single-cell sequencing can reveal the genetic heterogeneity among different cells. Due to the complex pathogenesis and various pathological types of hepatocellular carcinoma (HCC), studies on the heterogeneity of tumor cells confer improvement for its clinical diagnosis, treatment and prognosis. This article summarizes the principal basis and development of single-cell sequencing technology, as well as its increasing application in the field of HCC.
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Affiliation(s)
- Kai Kang
- Department of Liver Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China
| | - Xuezhu Wang
- Department of Liver Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China
| | - Chan Meng
- Department of Pathology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Li He
- Department of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Xinting Sang
- Department of Liver Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China
| | - Yongchang Zheng
- Department of Liver Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China
| | - Haifeng Xu
- Department of Liver Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China
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112
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Qi Z, Barrett T, Parikh AS, Tirosh I, Puram SV. Single-cell sequencing and its applications in head and neck cancer. Oral Oncol 2019; 99:104441. [PMID: 31689639 PMCID: PMC6981283 DOI: 10.1016/j.oraloncology.2019.104441] [Citation(s) in RCA: 57] [Impact Index Per Article: 11.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2019] [Accepted: 10/01/2019] [Indexed: 01/22/2023]
Abstract
Head and neck squamous cell carcinoma (HNSCC), like many tumors, is characterized by significant intra-tumoral heterogeneity, namely transcriptional, genetic, and epigenetic differences that define distinct cellular subpopulations. While it has been established that intra-tumoral heterogeneity may have prognostic significance in HNSCC, we are only beginning to describe and define such heterogeneity at a cellular resolution. Recent advances in single-cell sequencing technologies have been critical in this regard, opening new avenues in our understanding of more nuanced tumor biology by identifying distinct cellular subpopulations, dissecting signaling within the tumor microenvironment, and characterizing cellular genomic mutations and copy number aberrations. The combined effect of these insights is likely to be robust and meaningful changes in existing diagnostic and treatment algorithms through the application of novel biomarkers as well as targeted therapeutics. Here, we review single-cell technological and computational advances at the genomic, transcriptomic, and epigenomic levels, and discuss their applications in cancer research and clinical practice, with a specific focus on HNSCC.
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Affiliation(s)
- Zongtai Qi
- Department of Otolaryngology-Head and Neck Surgery, Washington University School of Medicine, St. Louis, USA; Department of Genetics, Washington University School of Medicine, St. Louis, USA
| | - Thomas Barrett
- Department of Otolaryngology-Head and Neck Surgery, Washington University School of Medicine, St. Louis, USA; Department of Genetics, Washington University School of Medicine, St. Louis, USA
| | - Anuraag S Parikh
- Department of Otolaryngology, Massachusetts Eye and Ear, Boston, MA, USA; Department of Otolaryngology, Harvard Medical School, Boston, MA, USA
| | - Itay Tirosh
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel
| | - Sidharth V Puram
- Department of Otolaryngology-Head and Neck Surgery, Washington University School of Medicine, St. Louis, USA; Department of Genetics, Washington University School of Medicine, St. Louis, USA.
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113
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Klein DC, Hainer SJ. Genomic methods in profiling DNA accessibility and factor localization. Chromosome Res 2019; 28:69-85. [PMID: 31776829 PMCID: PMC7125251 DOI: 10.1007/s10577-019-09619-9] [Citation(s) in RCA: 55] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2019] [Revised: 10/10/2019] [Accepted: 10/15/2019] [Indexed: 12/24/2022]
Abstract
Recent advancements in next-generation sequencing technologies and accompanying reductions in cost have led to an explosion of techniques to examine DNA accessibility and protein localization on chromatin genome-wide. Generally, accessible regions of chromatin are permissive for factor binding and are therefore hotspots for regulation of gene expression; conversely, genomic regions that are highly occupied by histone proteins are not permissive for factor binding and are less likely to be active regulatory regions. Identifying regions of differential accessibility can be useful to uncover putative gene regulatory regions, such as enhancers, promoters, and insulators. In addition, DNA-binding proteins, such as transcription factors that preferentially bind certain DNA sequences and histone proteins that form the core of the nucleosome, play essential roles in all DNA-templated processes. Determining the genomic localization of chromatin-bound proteins is therefore essential in determining functional roles, sequence motifs important for factor binding, and regulatory networks controlling gene expression. In this review, we discuss techniques for determining DNA accessibility and nucleosome positioning (DNase-seq, FAIRE-seq, MNase-seq, and ATAC-seq) and techniques for detecting and functionally characterizing chromatin-bound proteins (ChIP-seq, DamID, and CUT&RUN). These methods have been optimized to varying degrees of resolution, specificity, and ease of use. Here, we outline some advantages and disadvantages of these techniques, their general protocols, and a brief discussion of their development. Together, these complimentary approaches have provided an unparalleled view of chromatin architecture and functional gene regulation.
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Affiliation(s)
- David C Klein
- Department of Biological Sciences, University of Pittsburgh, Pittsburgh, PA, 15260, USA
| | - Sarah J Hainer
- Department of Biological Sciences, University of Pittsburgh, Pittsburgh, PA, 15260, USA.
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114
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Org T, Hensen K, Kreevan R, Mark E, Sarv O, Andreson R, Jaakma Ü, Salumets A, Kurg A. Genome-wide histone modification profiling of inner cell mass and trophectoderm of bovine blastocysts by RAT-ChIP. PLoS One 2019; 14:e0225801. [PMID: 31765427 PMCID: PMC6876874 DOI: 10.1371/journal.pone.0225801] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2019] [Accepted: 11/12/2019] [Indexed: 12/29/2022] Open
Abstract
Chromatin immunoprecipitation coupled with next-generation sequencing (ChIP-seq) has revolutionized our understanding of chromatin-related biological processes. The method, however, requires thousands of cells and has therefore limited applications in situations where cell numbers are limited. Here we describe a novel method called Restriction Assisted Tagmentation Chromatin Immunoprecipitation (RAT-ChIP) that enables global histone modification profiling from as few as 100 cells. The method is simple, cost-effective and takes a single day to complete. We demonstrate the sensitivity of the method by deriving the first genome-wide maps of histone H3K4me3 and H3K27me3 modifications of inner cell mass and trophectoderm of bovine blastocyst stage embryos.
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Affiliation(s)
- Tõnis Org
- Department of Biotechnology, Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia
- * E-mail:
| | - Kati Hensen
- Department of Biotechnology, Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia
| | - Rita Kreevan
- Department of Biotechnology, Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia
| | - Elina Mark
- Chair of Animal Breeding and Biotechnology, Estonian University of Life Sciences, Tartu, Estonia
| | - Olav Sarv
- Competence Centre on Health Technologies, Tartu, Estonia
| | - Reidar Andreson
- Department of Bioinformatics, Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia
- Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Ülle Jaakma
- Chair of Animal Breeding and Biotechnology, Estonian University of Life Sciences, Tartu, Estonia
| | - Andres Salumets
- Competence Centre on Health Technologies, Tartu, Estonia
- Department of Obstetrics and Gynaecology, Institute of Clinical Medicine, University of Tartu, Tartu, Estonia
- Institute of Biomedicine and Translational Medicine, University of Tartu, Tartu, Estonia
- Department of Obstetrics and Gynaecology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Ants Kurg
- Department of Biotechnology, Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia
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115
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Kribelbauer JF, Lu XJ, Rohs R, Mann RS, Bussemaker HJ. Toward a Mechanistic Understanding of DNA Methylation Readout by Transcription Factors. J Mol Biol 2019:S0022-2836(19)30617-5. [PMID: 31689433 DOI: 10.1016/j.jmb.2019.10.021] [Citation(s) in RCA: 43] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2019] [Revised: 10/23/2019] [Accepted: 10/24/2019] [Indexed: 01/09/2023]
Abstract
Epigenetic DNA modification impacts gene expression, but the underlying molecular mechanisms are only partly understood. Adding a methyl group to a cytosine base locally modifies the structural features of DNA in multiple ways, which may change the interaction with DNA-binding transcription factors (TFs) and trigger a cascade of downstream molecular events. Cells can be probed using various functional genomics assays, but it is difficult to disentangle the confounded effects of DNA modification on TF binding, chromatin accessibility, intranuclear variation in local TF concentration, and rate of transcription. Here we discuss how high-throughput in vitro profiling of protein-DNA interactions has enabled comprehensive characterization and quantification of the methylation sensitivity of TFs. Despite the limited structural data for DNA containing methylated cytosine, automated analysis of structural information in the Protein Data Bank (PDB) shows how 5-methylcytosine (5mC) can be recognized in various ways by amino acid side chains. We discuss how a context-dependent effect of methylation on DNA groove geometry can affect DNA binding by homeodomain proteins and how principled modeling of ChIP-seq data can overcome the confounding that makes the interpretation of in vivo data challenging. The emerging picture is that epigenetic modifications affect TF binding in a highly context-specific manner, with a direction and effect size that depend critically on their position within the TF binding site and the amino acid sequence of the TF. With this improved mechanistic knowledge, we have come closer to understanding how cells use DNA modification to acquire, retain, and change their identity.
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Affiliation(s)
- Judith F Kribelbauer
- Department of Biological Sciences, Columbia University, New York, NY 10027, USA; Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY 10027, USA; Department of Systems Biology, Columbia University, New York, NY 10032, USA
| | - Xiang-Jun Lu
- Department of Biological Sciences, Columbia University, New York, NY 10027, USA
| | - Remo Rohs
- Quantitative and Computational Biology, Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089, USA; Department of Chemistry, University of Southern California, Los Angeles, CA 90089, USA; Department of Physics & Astronomy, University of Southern California, Los Angeles, CA 90089, USA; Department of Computer Science, University of Southern California, Los Angeles, CA 90089, USA
| | - Richard S Mann
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY 10027, USA; Department of Systems Biology, Columbia University, New York, NY 10032, USA; Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY 10032, USA; Department of Neuroscience, Columbia University, New York, NY 10027, USA
| | - Harmen J Bussemaker
- Department of Biological Sciences, Columbia University, New York, NY 10027, USA; Department of Systems Biology, Columbia University, New York, NY 10032, USA.
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116
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Wang Q, Xiong H, Ai S, Yu X, Liu Y, Zhang J, He A. CoBATCH for High-Throughput Single-Cell Epigenomic Profiling. Mol Cell 2019; 76:206-216.e7. [DOI: 10.1016/j.molcel.2019.07.015] [Citation(s) in RCA: 107] [Impact Index Per Article: 21.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2019] [Revised: 06/17/2019] [Accepted: 07/10/2019] [Indexed: 12/20/2022]
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117
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Wen L, Tang F. Human Germline Cell Development: from the Perspective of Single-Cell Sequencing. Mol Cell 2019; 76:320-328. [PMID: 31563431 DOI: 10.1016/j.molcel.2019.08.025] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2019] [Revised: 08/22/2019] [Accepted: 08/27/2019] [Indexed: 01/01/2023]
Abstract
Germline cells are the beginning of new individuals in multicellular animals, including humans. Our understanding of these cell types is limited by the difficulty of analyzing the precious and heterogeneous germline tissue samples. The rapid development of single-cell sequencing technologies provides a chance for comprehensive profiling of the omics dynamics of human germline development. In this review, we discuss progress in analyzing the development of human germline cells, including preimplantation and implantation embryos, fetal germ cells (FGCs), and adult spermatogenesis by single-cell transcriptome and epigenome sequencing technologies.
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Affiliation(s)
- Lu Wen
- Beijing Advanced Innovation Center for Genomics (ICG), Biomedical Pioneering Innovation Center (BIOPIC), College of Life Sciences, Peking University, Beijing 100871, China.
| | - Fuchou Tang
- Beijing Advanced Innovation Center for Genomics (ICG), Biomedical Pioneering Innovation Center (BIOPIC), College of Life Sciences, Peking University, Beijing 100871, China.
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118
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Ai S, Xiong H, Li CC, Luo Y, Shi Q, Liu Y, Yu X, Li C, He A. Profiling chromatin states using single-cell itChIP-seq. Nat Cell Biol 2019; 21:1164-1172. [DOI: 10.1038/s41556-019-0383-5] [Citation(s) in RCA: 77] [Impact Index Per Article: 15.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2019] [Accepted: 07/26/2019] [Indexed: 12/13/2022]
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119
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Fosslie M, Manaf A, Lerdrup M, Hansen K, Gilfillan GD, Dahl JA. Going low to reach high: Small-scale ChIP-seq maps new terrain. WILEY INTERDISCIPLINARY REVIEWS-SYSTEMS BIOLOGY AND MEDICINE 2019; 12:e1465. [PMID: 31478357 DOI: 10.1002/wsbm.1465] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/15/2019] [Revised: 07/02/2019] [Accepted: 07/25/2019] [Indexed: 12/20/2022]
Abstract
Chromatin immunoprecipitation (ChIP) enables mapping of specific histone modifications or chromatin-associated factors in the genome and represents a powerful tool in the study of chromatin and genome regulation. Importantly, recent technological advances that couple ChIP with whole-genome high-throughput sequencing (ChIP-seq) now allow the mapping of chromatin factors throughout the genome. However, the requirement for large amounts of ChIP-seq input material has long made it challenging to assess chromatin profiles of cell types only available in limited numbers. For many cell types, it is not feasible to reach high numbers when collecting them as homogeneous cell populations in vivo. Nonetheless, it is an advantage to work with pure cell populations to reach robust biological conclusions. Here, we review (a) how ChIP protocols have been scaled down for use with as little as a few hundred cells; (b) which considerations to be aware of when preparing small-scale ChIP-seq and analyzing data; and (c) the potential of small-scale ChIP-seq datasets for elucidating chromatin dynamics in various biological systems, including some examples such as oocyte maturation and preimplantation embryo development. This article is categorized under: Laboratory Methods and Technologies > Genetic/Genomic Methods Developmental Biology > Developmental Processes in Health and Disease Biological Mechanisms > Cell Fates.
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Affiliation(s)
| | - Adeel Manaf
- Department of Microbiology, Oslo University Hospital, Oslo, Norway
| | - Mads Lerdrup
- The Biotech Research and Innovation Centre, University of Copenhagen, Copenhagen, Denmark.,Centre for Epigenetics, University of Copenhagen, Copenhagen, Denmark
| | - Klaus Hansen
- The Biotech Research and Innovation Centre, University of Copenhagen, Copenhagen, Denmark.,Centre for Epigenetics, University of Copenhagen, Copenhagen, Denmark
| | - Gregor D Gilfillan
- Department of Medical Genetics, Oslo University Hospital and University of Oslo, Oslo, Norway
| | - John Arne Dahl
- Department of Microbiology, Oslo University Hospital, Oslo, Norway
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120
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The transcription factor TCF-1 enforces commitment to the innate lymphoid cell lineage. Nat Immunol 2019; 20:1150-1160. [PMID: 31358996 PMCID: PMC6707869 DOI: 10.1038/s41590-019-0445-7] [Citation(s) in RCA: 71] [Impact Index Per Article: 14.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2018] [Accepted: 06/12/2019] [Indexed: 01/25/2023]
Abstract
Innate lymphoid cells (ILCs) play important functions in immunity and tissue homeostasis, but their development is poorly understood. Through the use of single-cell approaches, we examined the transcriptional and functional heterogeneity of ILC progenitors, and studied the precursor-product relationships that link the subsets identified. This analysis identified two successive stages of ILC development within T cell factor 1-positive (TCF-1+) early innate lymphoid progenitors (EILPs), which we named 'specified EILPs' and 'committed EILPs'. Specified EILPs generated dendritic cells, whereas this potential was greatly decreased in committed EILPs. TCF-1 was dispensable for the generation of specified EILPs, but required for the generation of committed EILPs. TCF-1 used a pre-existing regulatory landscape established in upstream lymphoid precursors to bind chromatin in EILPs. Our results provide insight into the mechanisms by which TCF-1 promotes developmental progression of ILC precursors, while constraining their dendritic cell lineage potential and enforcing commitment to ILC fate.
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121
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Abstract
Understanding chromatin regulation holds enormous promise for controlling gene regulation, predicting cellular identity, and developing diagnostics and cellular therapies. However, the dynamic nature of chromatin, together with cell-to-cell heterogeneity in its structure, limits our ability to extract its governing principles. Single cell mapping of chromatin modifications, in conjunction with expression measurements, could help overcome these limitations. Here, we review recent advances in single cell-based measurements of chromatin modifications, including optimization to reduce DNA loss, improved DNA sequencing, barcoding, and antibody engineering. We also highlight several applications of these techniques that have provided insights into cell-type classification, mapping modification co-occurrence and heterogeneity, and monitoring chromatin dynamics.
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Affiliation(s)
- Connor H Ludwig
- Department of Bioengineering, Stanford University, Shriram Center, 443 Via Ortega, Rm 042, Stanford, CA 94305, USA
| | - Lacramioara Bintu
- Department of Bioengineering, Stanford University, Shriram Center, 443 Via Ortega, Rm 042, Stanford, CA 94305, USA
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122
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The Spatial and Genomic Hierarchy of Tumor Ecosystems Revealed by Single-Cell Technologies. Trends Cancer 2019; 5:411-425. [PMID: 31311656 DOI: 10.1016/j.trecan.2019.05.009] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2019] [Revised: 05/23/2019] [Accepted: 05/28/2019] [Indexed: 12/23/2022]
Abstract
Many malignancies display heterogeneous features that support cancer progression. Emerging high-resolution methods provide a view of heterogeneity that recognizes the influence of diverse cell types and cell states of the tumor microenvironment. Here we outline a hierarchical organization of tumor heterogeneity from a genomic perspective, summarize the origins of spatially patterned metabolic features, and review recent developments in single-cell and spatially resolved techniques for genome-wide study of multicellular tissues. We also discuss how integrating these approaches can yield new insights into human cancer and emerging immune therapies. Applying these technologies for the analysis of primary tumors, patient-derived xenografts, and in vitro systems holds great promise for understanding the hierarchical structure and environmental influences that underlie tumor ecosystems.
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