151
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Chen H, Eling N, Martinez‐Jimenez CP, O'Brien LM, Carbonaro V, Marioni JC, Odom DT, de la Roche M. IL-7-dependent compositional changes within the γδ T cell pool in lymph nodes during ageing lead to an unbalanced anti-tumour response. EMBO Rep 2019; 20:e47379. [PMID: 31283095 PMCID: PMC6680116 DOI: 10.15252/embr.201847379] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2018] [Revised: 05/29/2019] [Accepted: 06/05/2019] [Indexed: 12/21/2022] Open
Abstract
How the age-associated decline of immune function leads to increased cancer incidence is poorly understood. Here, we have characterised the cellular composition of the γδ T-cell pool in peripheral lymph nodes (pLNs) upon ageing. We find that ageing has minimal cell-intrinsic effects on function and global gene expression of γδ T cells, and γδTCR diversity remains stable. However, ageing alters TCRδ chain usage and clonal structure of γδ T-cell subsets. Importantly, IL-17-producing γδ17 T cells dominate the γδ T-cell pool of aged mice-mainly due to the selective expansion of Vγ6+ γδ17 T cells and augmented γδ17 polarisation of Vγ4+ T cells. Expansion of the γδ17 T-cell compartment is mediated by increased IL-7 expression in the T-cell zone of old mice. In a Lewis lung cancer model, pro-tumourigenic Vγ6+ γδ17 T cells are exclusively activated in the tumour-draining LN and their infiltration into the tumour correlates with increased tumour size in aged mice. Thus, upon ageing, substantial compositional changes in γδ T-cell pool in the pLN lead to an unbalanced γδ T-cell response in the tumour that is associated with accelerated tumour growth.
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MESH Headings
- Aging/genetics
- Aging/immunology
- Animals
- Carcinoma, Lewis Lung/genetics
- Carcinoma, Lewis Lung/immunology
- Carcinoma, Lewis Lung/pathology
- Cell Differentiation
- Cell Lineage/genetics
- Cell Lineage/immunology
- Gene Expression Regulation, Neoplastic
- Immunophenotyping
- Interleukin-17/genetics
- Interleukin-17/immunology
- Interleukin-7/genetics
- Interleukin-7/immunology
- Lymph Nodes/immunology
- Lymph Nodes/pathology
- Mice
- Mice, Inbred C57BL
- Receptors, Antigen, T-Cell, gamma-delta/classification
- Receptors, Antigen, T-Cell, gamma-delta/genetics
- Receptors, Antigen, T-Cell, gamma-delta/immunology
- Signal Transduction
- T-Lymphocyte Subsets/classification
- T-Lymphocyte Subsets/immunology
- T-Lymphocyte Subsets/pathology
- Tumor Burden/genetics
- Tumor Burden/immunology
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Affiliation(s)
- Hung‐Chang Chen
- Cancer Research UK Cambridge InstituteUniversity of CambridgeCambridgeUK
| | - Nils Eling
- Cancer Research UK Cambridge InstituteUniversity of CambridgeCambridgeUK
- European Molecular Biology LaboratoryEuropean Bioinformatics Institute (EMBL‐EBI), Wellcome Genome CampusCambridgeUK
| | - Celia Pilar Martinez‐Jimenez
- Cancer Research UK Cambridge InstituteUniversity of CambridgeCambridgeUK
- Wellcome Sanger Institute, Wellcome Genome CampusCambridgeUK
- Helmholtz Pioneer Campus, Helmholtz Zentrum MünchenNeuherbergGermany
| | | | | | - John C Marioni
- Cancer Research UK Cambridge InstituteUniversity of CambridgeCambridgeUK
- European Molecular Biology LaboratoryEuropean Bioinformatics Institute (EMBL‐EBI), Wellcome Genome CampusCambridgeUK
- Wellcome Sanger Institute, Wellcome Genome CampusCambridgeUK
| | - Duncan T Odom
- Cancer Research UK Cambridge InstituteUniversity of CambridgeCambridgeUK
- Wellcome Sanger Institute, Wellcome Genome CampusCambridgeUK
- Division of Signalling and Functional GenomicsGerman Cancer Research Center (DKFZ)HeidelbergGermany
| | - Maike de la Roche
- Cancer Research UK Cambridge InstituteUniversity of CambridgeCambridgeUK
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152
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Hao J, Cao W, Huang J, Zou X, Han ZG. Optimal Gene Filtering for Single-Cell data (OGFSC)-a gene filtering algorithm for single-cell RNA-seq data. Bioinformatics 2019; 35:2602-2609. [PMID: 30535000 DOI: 10.1093/bioinformatics/bty1016] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2018] [Revised: 11/16/2018] [Accepted: 12/07/2018] [Indexed: 02/05/2023] Open
Abstract
MOTIVATION Single-cell transcriptomic data are commonly accompanied by extremely high technical noise due to the low RNA concentrations from individual cells. Precise identification of differentially expressed genes and cell populations are heavily dependent on the effective reduction of technical noise, e.g. by gene filtering. However, there is still no well-established standard in the current approaches of gene filtering. Investigators usually filter out genes based on single fixed threshold, which commonly leads to both over- and under-stringent errors. RESULTS In this study, we propose a novel algorithm, termed as Optimal Gene Filtering for Single-Cell data, to construct a thresholding curve based on gene expression levels and the corresponding variances. We validated our method on multiple single-cell RNA-seq datasets, including simulated and published experimental datasets. The results show that the known signal and known noise are reliably discriminated in the simulated datasets. In addition, the results of seven experimental datasets demonstrate that these cells of the same annotated types are more sharply clustered using our method. Interestingly, when we re-analyze the dataset from an aging research recently published in Science, we find a list of regulated genes which is different from that reported in the original study, because of using different filtering methods. However, the knowledge based on our findings better matches the progression of immunosenescence. In summary, we here provide an alternative opportunity to probe into the true level of technical noise in single-cell transcriptomic data. AVAILABILITY AND IMPLEMENTATION https://github.com/XZouProjects/OGFSC.git. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Jie Hao
- Shanghai Centre for Systems Biomedicine, Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Centre for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai, China
| | - Wei Cao
- Department of Oral Maxillofacial-Head and Neck Oncology, Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai Key Laboratory of Stomatology & Shanghai Research Institute of Stomatology, National Clinical Research Center of Stomatology, Shanghai, China
| | - Jian Huang
- Shanghai Centre for Systems Biomedicine, Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Centre for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai, China
| | - Xin Zou
- Shanghai Centre for Systems Biomedicine, Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Centre for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai, China
| | - Ze-Guang Han
- Shanghai Centre for Systems Biomedicine, Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Centre for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai, China
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153
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Elyahu Y, Hekselman I, Eizenberg-Magar I, Berner O, Strominger I, Schiller M, Mittal K, Nemirovsky A, Eremenko E, Vital A, Simonovsky E, Chalifa-Caspi V, Friedman N, Yeger-Lotem E, Monsonego A. Aging promotes reorganization of the CD4 T cell landscape toward extreme regulatory and effector phenotypes. SCIENCE ADVANCES 2019; 5:eaaw8330. [PMID: 31457092 PMCID: PMC6703865 DOI: 10.1126/sciadv.aaw8330] [Citation(s) in RCA: 150] [Impact Index Per Article: 30.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/30/2019] [Accepted: 07/12/2019] [Indexed: 05/29/2023]
Abstract
Age-associated changes in CD4 T-cell functionality have been linked to chronic inflammation and decreased immunity. However, a detailed characterization of CD4 T cell phenotypes that could explain these dysregulated functional properties is lacking. We used single-cell RNA sequencing and multidimensional protein analyses to profile thousands of CD4 T cells obtained from young and old mice. We found that the landscape of CD4 T cell subsets differs markedly between young and old mice, such that three cell subsets-exhausted, cytotoxic, and activated regulatory T cells (aTregs)-appear rarely in young mice but gradually accumulate with age. Most unexpected were the extreme pro- and anti-inflammatory phenotypes of cytotoxic CD4 T cells and aTregs, respectively. These findings provide a comprehensive view of the dynamic reorganization of the CD4 T cell milieu with age and illuminate dominant subsets associated with chronic inflammation and immunity decline, suggesting new therapeutic avenues for age-related diseases.
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Affiliation(s)
- Yehezqel Elyahu
- The Shraga Segal Department of Microbiology, Immunology and Genetics, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva 8410501, Israel
- Zlotowski Neuroscience Center and Regenerative Medicine and Stem Cell Research Center, Ben-Gurion University of the Negev, Beer-Sheva, Israel
- National Institute for Biotechnology in the Negev, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Idan Hekselman
- National Institute for Biotechnology in the Negev, Ben-Gurion University of the Negev, Beer-Sheva, Israel
- Department of Clinical Biochemistry and Pharmacology, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | | | - Omer Berner
- The Shraga Segal Department of Microbiology, Immunology and Genetics, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva 8410501, Israel
- Zlotowski Neuroscience Center and Regenerative Medicine and Stem Cell Research Center, Ben-Gurion University of the Negev, Beer-Sheva, Israel
- National Institute for Biotechnology in the Negev, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Itai Strominger
- The Shraga Segal Department of Microbiology, Immunology and Genetics, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva 8410501, Israel
- Zlotowski Neuroscience Center and Regenerative Medicine and Stem Cell Research Center, Ben-Gurion University of the Negev, Beer-Sheva, Israel
- National Institute for Biotechnology in the Negev, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Maya Schiller
- Departments of Immunology and Neuroscience, Rappaport Faculty of Medicine, and the Integrated Cancer Center, Technion-Israel Institute of Technology, Haifa 3525422, Israel
| | - Kritika Mittal
- The Shraga Segal Department of Microbiology, Immunology and Genetics, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva 8410501, Israel
- Zlotowski Neuroscience Center and Regenerative Medicine and Stem Cell Research Center, Ben-Gurion University of the Negev, Beer-Sheva, Israel
- National Institute for Biotechnology in the Negev, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Anna Nemirovsky
- The Shraga Segal Department of Microbiology, Immunology and Genetics, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva 8410501, Israel
- Zlotowski Neuroscience Center and Regenerative Medicine and Stem Cell Research Center, Ben-Gurion University of the Negev, Beer-Sheva, Israel
- National Institute for Biotechnology in the Negev, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Ekaterina Eremenko
- The Shraga Segal Department of Microbiology, Immunology and Genetics, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva 8410501, Israel
- Zlotowski Neuroscience Center and Regenerative Medicine and Stem Cell Research Center, Ben-Gurion University of the Negev, Beer-Sheva, Israel
- National Institute for Biotechnology in the Negev, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Assaf Vital
- National Institute for Biotechnology in the Negev, Ben-Gurion University of the Negev, Beer-Sheva, Israel
- Department of Clinical Biochemistry and Pharmacology, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Eyal Simonovsky
- National Institute for Biotechnology in the Negev, Ben-Gurion University of the Negev, Beer-Sheva, Israel
- Department of Clinical Biochemistry and Pharmacology, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Vered Chalifa-Caspi
- National Institute for Biotechnology in the Negev, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Nir Friedman
- Department of Immunology, Weizmann Institute of Science, Rehovot 7610001, Israel
| | - Esti Yeger-Lotem
- National Institute for Biotechnology in the Negev, Ben-Gurion University of the Negev, Beer-Sheva, Israel
- Department of Clinical Biochemistry and Pharmacology, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Alon Monsonego
- The Shraga Segal Department of Microbiology, Immunology and Genetics, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva 8410501, Israel
- Zlotowski Neuroscience Center and Regenerative Medicine and Stem Cell Research Center, Ben-Gurion University of the Negev, Beer-Sheva, Israel
- National Institute for Biotechnology in the Negev, Ben-Gurion University of the Negev, Beer-Sheva, Israel
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154
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Tang X, Huang Y, Lei J, Luo H, Zhu X. The single-cell sequencing: new developments and medical applications. Cell Biosci 2019; 9:53. [PMID: 31391919 PMCID: PMC6595701 DOI: 10.1186/s13578-019-0314-y] [Citation(s) in RCA: 167] [Impact Index Per Article: 33.4] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2019] [Accepted: 06/18/2019] [Indexed: 02/06/2023] Open
Abstract
Single-cell sequencing technologies can be used to detect the genome, transcriptome and other multi-omics of single cells. They can show the differences and evolutionary relationships of various cells. This review introduces the latest advances in single-cell sequencing technologies and their applications in oncology, microbiology, neurology, reproduction, immunology, digestive and urinary systems, highlighting the important role that single-cell sequencing techniques play in these areas.
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Affiliation(s)
- Xiaoning Tang
- 1The Marine Biomedical Research Institute, Guangdong Medical University, Zhanjiang, 524023 China.,Guangdong Provincial Zhanjiang Bay Key Laboratory, Zhanjiang, 524023 China
| | - Yongmei Huang
- 1The Marine Biomedical Research Institute, Guangdong Medical University, Zhanjiang, 524023 China.,Guangdong Provincial Zhanjiang Bay Key Laboratory, Zhanjiang, 524023 China
| | - Jinli Lei
- 1The Marine Biomedical Research Institute, Guangdong Medical University, Zhanjiang, 524023 China.,Guangdong Provincial Zhanjiang Bay Key Laboratory, Zhanjiang, 524023 China
| | - Hui Luo
- 1The Marine Biomedical Research Institute, Guangdong Medical University, Zhanjiang, 524023 China.,Guangdong Provincial Zhanjiang Bay Key Laboratory, Zhanjiang, 524023 China
| | - Xiao Zhu
- 1The Marine Biomedical Research Institute, Guangdong Medical University, Zhanjiang, 524023 China.,Guangdong Provincial Zhanjiang Bay Key Laboratory, Zhanjiang, 524023 China
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155
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Giudice G, Petsalaki E. Proteomics and phosphoproteomics in precision medicine: applications and challenges. Brief Bioinform 2019; 20:767-777. [PMID: 29077858 PMCID: PMC6585152 DOI: 10.1093/bib/bbx141] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2017] [Revised: 09/21/2017] [Indexed: 12/11/2022] Open
Abstract
Recent advances in proteomics allow the accurate measurement of abundances for thousands of proteins and phosphoproteins from multiple samples in parallel. Therefore, for the first time, we have the opportunity to measure the proteomic profiles of thousands of patient samples or disease model cell lines in a systematic way, to identify the precise underlying molecular mechanism and discover personalized biomarkers, networks and treatments. Here, we review examples of successful use of proteomics and phosphoproteomics data sets in as well as their integration other omics data sets with the aim of precision medicine. We will discuss the bioinformatics challenges posed by the generation, analysis and integration of such large data sets and present potential reasons why proteomics profiling and biomarkers are not currently widely used in the clinical setting. We will finally discuss ways to contribute to the better use of proteomics data in precision medicine and the clinical setting.
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Affiliation(s)
- Girolamo Giudice
- European Molecular Biology Laboratory European Bioinformatics Institute
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156
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Lai RW, Lu R, Danthi PS, Bravo JI, Goumba A, Sampathkumar NK, Benayoun BA. Multi-level remodeling of transcriptional landscapes in aging and longevity. BMB Rep 2019. [PMID: 30526773 PMCID: PMC6386224 DOI: 10.5483/bmbrep.2019.52.1.296] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023] Open
Abstract
In multi-cellular organisms, the control of gene expression is key not only for development, but also for adult cellular homeostasis, and gene expression has been observed to be deregulated with aging. In this review, we discuss the current knowledge on the transcriptional alterations that have been described to occur with age in metazoans. First, we discuss age-related transcriptional changes in protein-coding genes, the expected functional impact of such changes, and how known pro-longevity interventions impact these changes. Second, we discuss the changes and impact of emerging aspects of transcription in aging, including age-related changes in splicing, lncRNAs and circRNAs. Third, we discuss the changes and potential impact of transcription of transposable elements with aging. Fourth, we highlight small ncRNAs and their potential impact on the regulation of aging phenotypes. Understanding the aging transcriptome will be key to identify important regulatory targets, and ultimately slow-down or reverse aging and extend healthy lifespan in humans.
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Affiliation(s)
- Rochelle W Lai
- Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA 90089, USA
| | - Ryan Lu
- Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA 90089, USA
| | - Prakroothi S Danthi
- Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA 90089, USA
| | - Juan I Bravo
- Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA 90089; Graduate program in the Biology of Aging, University of Southern California, Los Angeles, CA 90089, USA
| | - Alexandre Goumba
- Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA 90089, USA
| | | | - Bérénice A Benayoun
- Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA 90089; USC Norris Comprehensive Cancer Center, Epigenetics and Gene Regulation, Los Angeles, CA 90089; USC Stem Cell Initiative, Los Angeles, CA 90089, USA
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157
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de Jong TV, Moshkin YM, Guryev V. Gene expression variability: the other dimension in transcriptome analysis. Physiol Genomics 2019; 51:145-158. [DOI: 10.1152/physiolgenomics.00128.2018] [Citation(s) in RCA: 37] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
Transcriptome sequencing is a powerful technique to study molecular changes that underlie the differences in physiological conditions and disease progression. A typical question that is posed in such studies is finding genes with significant changes between sample groups. In this respect expression variability is regarded as a nuisance factor that is primarily of technical origin and complicates the data analysis. However, it is becoming apparent that the biological variation in gene expression might be an important molecular phenotype that can affect physiological parameters. In this review we explore the recent literature on technical and biological variability in gene expression, sources of expression variability, (epi-)genetic hallmarks, and evolutionary constraints in genes with robust and variable gene expression. We provide an overview of recent findings on effects of external cues, such as diet and aging, on expression variability and on other biological phenomena that can be linked to it. We discuss metrics and tools that were developed for quantification of expression variability and highlight the importance of future studies in this direction. To assist the adoption of expression variability analysis, we also provide a detailed description and computer code, which can easily be utilized by other researchers. We also provide a reanalysis of recently published data to highlight the value of the analysis method.
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Affiliation(s)
- Tristan V. de Jong
- European Research Institute for the Biology of Ageing, University of Groningen, University Medical Centre Groningen, Groningen, The Netherlands
| | - Yuri M. Moshkin
- Institute of Cytology and Genetics, Siberian Branch of RAS, Novosibirsk, Russia
- Institute of Molecular and Cellular Biology, Siberian Branch of RAS, Novosibirsk, Russia
| | - Victor Guryev
- European Research Institute for the Biology of Ageing, University of Groningen, University Medical Centre Groningen, Groningen, The Netherlands
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158
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Zhang L, Dong X, Lee M, Maslov AY, Wang T, Vijg J. Single-cell whole-genome sequencing reveals the functional landscape of somatic mutations in B lymphocytes across the human lifespan. Proc Natl Acad Sci U S A 2019; 116:9014-9019. [PMID: 30992375 PMCID: PMC6500118 DOI: 10.1073/pnas.1902510116] [Citation(s) in RCA: 147] [Impact Index Per Article: 29.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
Accumulation of mutations in somatic cells has been implicated as a cause of aging since the 1950s. However, attempts to establish a causal relationship between somatic mutations and aging have been constrained by the lack of methods to directly identify mutational events in primary human tissues. Here we provide genome-wide mutation frequencies and spectra of human B lymphocytes from healthy individuals across the entire human lifespan using a highly accurate single-cell whole-genome sequencing method. We found that the number of somatic mutations increases from <500 per cell in newborns to >3,000 per cell in centenarians. We discovered mutational hotspot regions, some of which, as expected, were located at Ig genes associated with somatic hypermutation (SHM). B cell-specific mutation signatures associated with development, aging, or SHM were found. The SHM signature strongly correlated with the signature found in human B cell tumors, indicating that potential cancer-causing events are already present even in B cells of healthy individuals. We also identified multiple mutations in sequence features relevant to cellular function (i.e., transcribed genes and gene regulatory regions). Such mutations increased significantly during aging, but only at approximately one-half the rate of the genome average, indicating selection against mutations that impact B cell function. This full characterization of the landscape of somatic mutations in human B lymphocytes indicates that spontaneous somatic mutations accumulating with age can be deleterious and may contribute to both the increased risk for leukemia and the functional decline of B lymphocytes in the elderly.
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Affiliation(s)
- Lei Zhang
- Department of Genetics, Albert Einstein College of Medicine, Bronx, NY 10461
| | - Xiao Dong
- Department of Genetics, Albert Einstein College of Medicine, Bronx, NY 10461
| | - Moonsook Lee
- Department of Genetics, Albert Einstein College of Medicine, Bronx, NY 10461
| | - Alexander Y Maslov
- Department of Genetics, Albert Einstein College of Medicine, Bronx, NY 10461
| | - Tao Wang
- Department of Epidemiology & Population Health, Albert Einstein College of Medicine, Bronx, NY 10461
| | - Jan Vijg
- Department of Genetics, Albert Einstein College of Medicine, Bronx, NY 10461;
- Center for Single-Cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, 200025 Shanghai, China
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159
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Nikopoulou C, Parekh S, Tessarz P. Ageing and sources of transcriptional heterogeneity. Biol Chem 2019; 400:867-878. [DOI: 10.1515/hsz-2018-0449] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2018] [Accepted: 03/27/2019] [Indexed: 12/14/2022]
Abstract
Abstract
Cellular heterogeneity is an important contributor to biological function and is employed by cells, tissues and organisms to adapt, compensate, respond, defend and/or regulate specific processes. Research over the last decades has revealed that transcriptional noise is a major driver for cell-to-cell variability. In this review we will discuss sources of transcriptional variability, in particular bursting of gene expression and how it could contribute to cellular states and fate decisions. We will highlight recent developments in single cell sequencing technologies that make it possible to address cellular heterogeneity in unprecedented detail. Finally, we will review recent literature, in which these new technologies are harnessed to address pressing questions in the field of ageing research, such as transcriptional noise and cellular heterogeneity in the course of ageing.
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Affiliation(s)
- Chrysa Nikopoulou
- Max Planck Research Group ‘Chromatin and Ageing’ , Max Planck Institute for Biology of Ageing , Joseph-Stelzmann-Str. 9b , D-50931 Cologne , Germany
| | - Swati Parekh
- Max Planck Research Group ‘Chromatin and Ageing’ , Max Planck Institute for Biology of Ageing , Joseph-Stelzmann-Str. 9b , D-50931 Cologne , Germany
| | - Peter Tessarz
- Max Planck Research Group ‘Chromatin and Ageing’ , Max Planck Institute for Biology of Ageing , Joseph-Stelzmann-Str. 9b , D-50931 Cologne , Germany
- Cluster of Excellence in Cellular Stress Responses in Aging-Associated Diseases (CECAD) , University of Cologne , Joseph-Stelzmann-Str. 26 , D-50931 Cologne , Germany
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160
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RNA-Seq-Based Gene Expression Pattern and Morphological Alterations in Chick Thymus during Postnatal Development. Int J Genomics 2019; 2019:6905194. [PMID: 31179312 PMCID: PMC6501151 DOI: 10.1155/2019/6905194] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2018] [Revised: 12/20/2018] [Accepted: 02/25/2019] [Indexed: 12/23/2022] Open
Abstract
The thymus is a lobulated unique lymphoid immune organ that plays a critical role in the selection, development, proliferation, and differentiation of T cells. The thymus of developing chickens undergoes continued morphological alterations; however, the biomolecular and transcriptional dynamics of the postnatal thymus in avian species is not clear yet. Therefore, the thymuses from chickens at different stages of development (at weeks 0, 1, 5, 9, 18, and 27) were used in the present study. The RNA-seq method was used to study the gene expression patterns. On average, 24120819 clean reads were mapped, differentially expressed genes (DEGs) were identified on the basis of log values (fold change), including 744 upregulated and 425 downregulated genes. The expression pattern revealed by RNA-seq was validated by quantitative real-time PCR (qPCR) analysis of four important genes, which are PCNA, CCNA2, CCNB2, and CDK1. Thus, the current study revealed that during postnatal development, the thymus undergoes severe atrophy. Thymus structure was damaged and gene expression changed dramatically, especially at the 27th week of age. Moreover, we found significant changes of several signaling pathways such as the cytokine-cytokine receptor interaction and cell cycle signaling pathways. Hence, it may be inferred that those signaling pathways might be closely related to the postnatal chicken thymus development.
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161
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Kedlian VR, Donertas HM, Thornton JM. The widespread increase in inter-individual variability of gene expression in the human brain with age. Aging (Albany NY) 2019; 11:2253-2280. [PMID: 31003228 PMCID: PMC6520006 DOI: 10.18632/aging.101912] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2019] [Accepted: 04/05/2019] [Indexed: 11/25/2022]
Abstract
Aging is broadly defined as a time-dependent progressive decline in the functional and physiological integrity of organisms. Previous studies and evolutionary theories of aging suggest that aging is not a programmed process but reflects dynamic stochastic events. In this study, we test whether transcriptional noise shows an increase with age, which would be expected from stochastic theories. Using human brain transcriptome dataset, we analyzed the heterogeneity in the transcriptome for individual genes and functional pathways, employing different analysis methods and pre-processing steps. We show that unlike expression level changes, changes in heterogeneity are highly dependent on the methodology and the underlying assumptions. Although the particular set of genes that can be characterized as differentially variable is highly dependent on the methods, we observe a consistent increase in heterogeneity at every level, independent of the method. In particular, we demonstrate a weak but reproducible transcriptome-wide shift towards an increase in heterogeneity, with twice as many genes significantly increasing as opposed to decreasing their heterogeneity. Furthermore, this pattern of increasing heterogeneity is not specific but is associated with a wide range of pathways.
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Affiliation(s)
- Veronika R. Kedlian
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton CB10 1SD, UK
- Current Address - Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton CB10 1SA, UK
- Equal contribution
| | - Handan Melike Donertas
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton CB10 1SD, UK
- Equal contribution
| | - Janet M. Thornton
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton CB10 1SD, UK
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162
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Angelidis I, Simon LM, Fernandez IE, Strunz M, Mayr CH, Greiffo FR, Tsitsiridis G, Ansari M, Graf E, Strom TM, Nagendran M, Desai T, Eickelberg O, Mann M, Theis FJ, Schiller HB. An atlas of the aging lung mapped by single cell transcriptomics and deep tissue proteomics. Nat Commun 2019; 10:963. [PMID: 30814501 PMCID: PMC6393476 DOI: 10.1038/s41467-019-08831-9] [Citation(s) in RCA: 344] [Impact Index Per Article: 68.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2018] [Accepted: 02/01/2019] [Indexed: 12/30/2022] Open
Abstract
Aging promotes lung function decline and susceptibility to chronic lung diseases, which are the third leading cause of death worldwide. Here, we use single cell transcriptomics and mass spectrometry-based proteomics to quantify changes in cellular activity states across 30 cell types and chart the lung proteome of young and old mice. We show that aging leads to increased transcriptional noise, indicating deregulated epigenetic control. We observe cell type-specific effects of aging, uncovering increased cholesterol biosynthesis in type-2 pneumocytes and lipofibroblasts and altered relative frequency of airway epithelial cells as hallmarks of lung aging. Proteomic profiling reveals extracellular matrix remodeling in old mice, including increased collagen IV and XVI and decreased Fraser syndrome complex proteins and collagen XIV. Computational integration of the aging proteome with the single cell transcriptomes predicts the cellular source of regulated proteins and creates an unbiased reference map of the aging lung. Aging impacts lung functionality and makes it more susceptible to chronic diseases. Combining proteomics and single cell transcriptomics, the authors chart molecular and cellular changes in the aging mouse lung, discover aging hallmarks, and predict the cellular sources of regulated proteins.
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Affiliation(s)
- Ilias Angelidis
- Helmholtz Zentrum München, Institute of Lung Biology and Disease, Member of the German Center for Lung Research (DZL), Munich, 85764, Germany
| | - Lukas M Simon
- Helmholtz Zentrum München, Institute of Computational Biology, Munich, 85764, Germany
| | - Isis E Fernandez
- Helmholtz Zentrum München, Institute of Lung Biology and Disease, Member of the German Center for Lung Research (DZL), Munich, 85764, Germany
| | - Maximilian Strunz
- Helmholtz Zentrum München, Institute of Lung Biology and Disease, Member of the German Center for Lung Research (DZL), Munich, 85764, Germany
| | - Christoph H Mayr
- Helmholtz Zentrum München, Institute of Lung Biology and Disease, Member of the German Center for Lung Research (DZL), Munich, 85764, Germany
| | - Flavia R Greiffo
- Helmholtz Zentrum München, Institute of Lung Biology and Disease, Member of the German Center for Lung Research (DZL), Munich, 85764, Germany
| | - George Tsitsiridis
- Helmholtz Zentrum München, Institute of Computational Biology, Munich, 85764, Germany
| | - Meshal Ansari
- Helmholtz Zentrum München, Institute of Lung Biology and Disease, Member of the German Center for Lung Research (DZL), Munich, 85764, Germany.,Helmholtz Zentrum München, Institute of Computational Biology, Munich, 85764, Germany
| | - Elisabeth Graf
- Helmholtz Zentrum München, Institute of Human Genetics, Munich, 85764, Germany
| | - Tim-Matthias Strom
- Helmholtz Zentrum München, Institute of Human Genetics, Munich, 85764, Germany
| | - Monica Nagendran
- Department of Internal Medicine, Division of Pulmonary and Critical Care, Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, 94305, CA, USA
| | - Tushar Desai
- Department of Internal Medicine, Division of Pulmonary and Critical Care, Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, 94305, CA, USA
| | - Oliver Eickelberg
- Department of Medicine, Division of Respiratory Sciences and Critical Care Medicine, University of Colorado, Aurora, 80045, CO, USA
| | - Matthias Mann
- Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Munich, 82152, Germany
| | - Fabian J Theis
- Helmholtz Zentrum München, Institute of Computational Biology, Munich, 85764, Germany. .,Department of Mathematics, Technische Universität München, Munich, 85748, Germany.
| | - Herbert B Schiller
- Helmholtz Zentrum München, Institute of Lung Biology and Disease, Member of the German Center for Lung Research (DZL), Munich, 85764, Germany.
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163
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Angelidis I, Simon LM, Fernandez IE, Strunz M, Mayr CH, Greiffo FR, Tsitsiridis G, Ansari M, Graf E, Strom TM, Nagendran M, Desai T, Eickelberg O, Mann M, Theis FJ, Schiller HB. An atlas of the aging lung mapped by single cell transcriptomics and deep tissue proteomics. Nat Commun 2019; 10:963. [PMID: 30814501 DOI: 10.1101/351353] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2018] [Accepted: 02/01/2019] [Indexed: 05/28/2023] Open
Abstract
Aging promotes lung function decline and susceptibility to chronic lung diseases, which are the third leading cause of death worldwide. Here, we use single cell transcriptomics and mass spectrometry-based proteomics to quantify changes in cellular activity states across 30 cell types and chart the lung proteome of young and old mice. We show that aging leads to increased transcriptional noise, indicating deregulated epigenetic control. We observe cell type-specific effects of aging, uncovering increased cholesterol biosynthesis in type-2 pneumocytes and lipofibroblasts and altered relative frequency of airway epithelial cells as hallmarks of lung aging. Proteomic profiling reveals extracellular matrix remodeling in old mice, including increased collagen IV and XVI and decreased Fraser syndrome complex proteins and collagen XIV. Computational integration of the aging proteome with the single cell transcriptomes predicts the cellular source of regulated proteins and creates an unbiased reference map of the aging lung.
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Affiliation(s)
- Ilias Angelidis
- Helmholtz Zentrum München, Institute of Lung Biology and Disease, Member of the German Center for Lung Research (DZL), Munich, 85764, Germany
| | - Lukas M Simon
- Helmholtz Zentrum München, Institute of Computational Biology, Munich, 85764, Germany
| | - Isis E Fernandez
- Helmholtz Zentrum München, Institute of Lung Biology and Disease, Member of the German Center for Lung Research (DZL), Munich, 85764, Germany
| | - Maximilian Strunz
- Helmholtz Zentrum München, Institute of Lung Biology and Disease, Member of the German Center for Lung Research (DZL), Munich, 85764, Germany
| | - Christoph H Mayr
- Helmholtz Zentrum München, Institute of Lung Biology and Disease, Member of the German Center for Lung Research (DZL), Munich, 85764, Germany
| | - Flavia R Greiffo
- Helmholtz Zentrum München, Institute of Lung Biology and Disease, Member of the German Center for Lung Research (DZL), Munich, 85764, Germany
| | - George Tsitsiridis
- Helmholtz Zentrum München, Institute of Computational Biology, Munich, 85764, Germany
| | - Meshal Ansari
- Helmholtz Zentrum München, Institute of Lung Biology and Disease, Member of the German Center for Lung Research (DZL), Munich, 85764, Germany
- Helmholtz Zentrum München, Institute of Computational Biology, Munich, 85764, Germany
| | - Elisabeth Graf
- Helmholtz Zentrum München, Institute of Human Genetics, Munich, 85764, Germany
| | - Tim-Matthias Strom
- Helmholtz Zentrum München, Institute of Human Genetics, Munich, 85764, Germany
| | - Monica Nagendran
- Department of Internal Medicine, Division of Pulmonary and Critical Care, Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, 94305, CA, USA
| | - Tushar Desai
- Department of Internal Medicine, Division of Pulmonary and Critical Care, Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, 94305, CA, USA
| | - Oliver Eickelberg
- Department of Medicine, Division of Respiratory Sciences and Critical Care Medicine, University of Colorado, Aurora, 80045, CO, USA
| | - Matthias Mann
- Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Munich, 82152, Germany
| | - Fabian J Theis
- Helmholtz Zentrum München, Institute of Computational Biology, Munich, 85764, Germany.
- Department of Mathematics, Technische Universität München, Munich, 85748, Germany.
| | - Herbert B Schiller
- Helmholtz Zentrum München, Institute of Lung Biology and Disease, Member of the German Center for Lung Research (DZL), Munich, 85764, Germany.
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164
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Revolutionizing immunology with single-cell RNA sequencing. Cell Mol Immunol 2019; 16:242-249. [PMID: 30796351 DOI: 10.1038/s41423-019-0214-4] [Citation(s) in RCA: 110] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2019] [Accepted: 01/30/2019] [Indexed: 12/30/2022] Open
Abstract
The immune system is composed of a complex hierarchy of cell types that protect the organism against disease and maintain homeostasis. Identifying heterogeneity of immune cells is the key to understanding the immune system. Advanced single-cell RNA sequencing (scRNA-seq) technologies are revolutionizing our ability to study immunology. By measuring transcriptomes at the single-cell level, scRNA-seq enables identification of cellular heterogeneity in far greater detail than conventional methods. In this review, we introduce the existing scRNA-seq technologies and present their strengths and weaknesses. We also discuss potential applications and future innovations of scRNA-seq in immunology.
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165
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Ogrodnik M, Salmonowicz H, Gladyshev VN. Integrating cellular senescence with the concept of damage accumulation in aging: Relevance for clearance of senescent cells. Aging Cell 2019; 18:e12841. [PMID: 30346102 PMCID: PMC6351832 DOI: 10.1111/acel.12841] [Citation(s) in RCA: 98] [Impact Index Per Article: 19.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2018] [Revised: 07/31/2018] [Accepted: 08/20/2018] [Indexed: 12/12/2022] Open
Abstract
Understanding the aging process and ways to manipulate it is of major importance for biology and medicine. Among the many aging theories advanced over the years, the concept most consistent with experimental evidence posits the buildup of numerous forms of molecular damage as a foundation of the aging process. Here, we discuss that this concept integrates well with recent findings on cellular senescence, offering a novel view on the role of senescence in aging and age‐related disease. Cellular senescence has a well‐established role in cellular aging, but its impact on the rate of organismal aging is less defined. One of the most prominent features of cellular senescence is its association with macromolecular damage. The relationship between cell senescence and damage concerns both damage as a molecular signal of senescence induction and accelerated accumulation of damage in senescent cells. We describe the origin, regulatory mechanisms, and relevance of various damage forms in senescent cells. This view on senescent cells as carriers and inducers of damage puts new light on senescence, considering it as a significant contributor to the rise in organismal damage. Applying these ideas, we critically examine current evidence for a role of cellular senescence in aging and age‐related diseases. We also discuss the differential impact of longevity interventions on senescence burden and other types of age‐related damage. Finally, we propose a model on the role of aging‐related damage accumulation and the rate of aging observed upon senescent cell clearance.
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Affiliation(s)
- Mikolaj Ogrodnik
- Institute for Cell and Molecular Biosciences; Newcastle University Institute for Ageing; Newcastle upon Tyne UK
| | - Hanna Salmonowicz
- Institute for Cell and Molecular Biosciences; Newcastle University Institute for Ageing; Newcastle upon Tyne UK
| | - Vadim N. Gladyshev
- Division of Genetics; Department of Medicine; Brigham and Women's Hospital and Harvard Medical School; Boston Massachusetts
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166
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Lai RW, Lu R, Danthi PS, Bravo JI, Goumba A, Sampathkumar NK, Benayoun BA. Multi-level remodeling of transcriptional landscapes in aging and longevity. BMB Rep 2019; 52:86-108. [PMID: 30526773 PMCID: PMC6386224] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2018] [Indexed: 07/15/2024] Open
Abstract
In multi-cellular organisms, the control of gene expression is key not only for development, but also for adult cellular homeostasis, and gene expression has been observed to be deregulated with aging. In this review, we discuss the current knowledge on the transcriptional alterations that have been described to occur with age in metazoans. First, we discuss age-related transcriptional changes in protein-coding genes, the expected functional impact of such changes, and how known pro-longevity interventions impact these changes. Second, we discuss the changes and impact of emerging aspects of transcription in aging, including age-related changes in splicing, lncRNAs and circRNAs. Third, we discuss the changes and potential impact of transcription of transposable elements with aging. Fourth, we highlight small ncRNAs and their potential impact on the regulation of aging phenotypes. Understanding the aging transcriptome will be key to identify important regulatory targets, and ultimately slow-down or reverse aging and extend healthy lifespan in humans. [BMB Reports 2019; 52(1): 86-108].
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Affiliation(s)
| | | | - Prakroothi S. Danthi
- Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA 90089,
USA
| | - Juan I. Bravo
- Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA 90089,
USA
- Graduate program in the Biology of Aging, University of Southern California, Los Angeles, CA 90089,
USA
| | - Alexandre Goumba
- Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA 90089,
USA
| | | | - Bérénice A. Benayoun
- Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA 90089,
USA
- USC Norris Comprehensive Cancer Center, Epigenetics and Gene Regulation, Los Angeles, CA 90089,
USA
- USC Stem Cell Initiative, Los Angeles, CA 90089,
USA
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167
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Hinohara K, Wu HJ, Vigneau S, McDonald TO, Igarashi KJ, Yamamoto KN, Madsen T, Fassl A, Egri SB, Papanastasiou M, Ding L, Peluffo G, Cohen O, Kales SC, Lal-Nag M, Rai G, Maloney DJ, Jadhav A, Simeonov A, Wagle N, Brown M, Meissner A, Sicinski P, Jaffe JD, Jeselsohn R, Gimelbrant AA, Michor F, Polyak K. KDM5 Histone Demethylase Activity Links Cellular Transcriptomic Heterogeneity to Therapeutic Resistance. Cancer Cell 2018; 34:939-953.e9. [PMID: 30472020 PMCID: PMC6310147 DOI: 10.1016/j.ccell.2018.10.014] [Citation(s) in RCA: 145] [Impact Index Per Article: 24.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/22/2017] [Revised: 08/17/2018] [Accepted: 10/25/2018] [Indexed: 12/30/2022]
Abstract
Members of the KDM5 histone H3 lysine 4 demethylase family are associated with therapeutic resistance, including endocrine resistance in breast cancer, but the underlying mechanism is poorly defined. Here we show that genetic deletion of KDM5A/B or inhibition of KDM5 activity increases sensitivity to anti-estrogens by modulating estrogen receptor (ER) signaling and by decreasing cellular transcriptomic heterogeneity. Higher KDM5B expression levels are associated with higher transcriptomic heterogeneity and poor prognosis in ER+ breast tumors. Single-cell RNA sequencing, cellular barcoding, and mathematical modeling demonstrate that endocrine resistance is due to selection for pre-existing genetically distinct cells, while KDM5 inhibitor resistance is acquired. Our findings highlight the importance of cellular phenotypic heterogeneity in therapeutic resistance and identify KDM5A/B as key regulators of this process.
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Affiliation(s)
- Kunihiko Hinohara
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
| | - Hua-Jun Wu
- Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA; Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA 02138, USA
| | - Sébastien Vigneau
- Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Thomas O McDonald
- Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA; Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA 02138, USA; Center for Cancer Evolution, Dana-Farber Cancer Institute, Boston, MA 02215, USA
| | - Kyomi J Igarashi
- Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Kimiyo N Yamamoto
- Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA; Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA 02138, USA
| | - Thomas Madsen
- Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA; Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA 02138, USA
| | - Anne Fassl
- Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Shawn B Egri
- The Eli and Edythe L Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
| | | | - Lina Ding
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
| | - Guillermo Peluffo
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
| | - Ofir Cohen
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; The Eli and Edythe L Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
| | - Stephen C Kales
- National Center for Advancing Translational Sciences, Bethesda, MD 20892, USA
| | - Madhu Lal-Nag
- National Center for Advancing Translational Sciences, Bethesda, MD 20892, USA
| | - Ganesha Rai
- National Center for Advancing Translational Sciences, Bethesda, MD 20892, USA
| | - David J Maloney
- National Center for Advancing Translational Sciences, Bethesda, MD 20892, USA
| | - Ajit Jadhav
- National Center for Advancing Translational Sciences, Bethesda, MD 20892, USA
| | - Anton Simeonov
- National Center for Advancing Translational Sciences, Bethesda, MD 20892, USA
| | - Nikhil Wagle
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Medicine, Harvard Medical School, Boston, MA 02115, USA; The Eli and Edythe L Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
| | - Myles Brown
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Medicine, Harvard Medical School, Boston, MA 02115, USA; Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Ludwig Center at Harvard, Boston, MA 02215, USA
| | - Alexander Meissner
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA 02138, USA; The Eli and Edythe L Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
| | - Piotr Sicinski
- Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Jacob D Jaffe
- The Eli and Edythe L Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
| | - Rinath Jeselsohn
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
| | - Alexander A Gimelbrant
- Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Franziska Michor
- Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA; Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA 02138, USA; Center for Cancer Evolution, Dana-Farber Cancer Institute, Boston, MA 02215, USA; The Eli and Edythe L Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA; Ludwig Center at Harvard, Boston, MA 02215, USA.
| | - Kornelia Polyak
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Medicine, Harvard Medical School, Boston, MA 02115, USA; Center for Cancer Evolution, Dana-Farber Cancer Institute, Boston, MA 02215, USA; The Eli and Edythe L Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA; Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Ludwig Center at Harvard, Boston, MA 02215, USA.
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168
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Abstract
The growing scale and declining cost of single-cell RNA-sequencing (RNA-seq) now permit a repetition of cell sampling that increases the power to detect rare cell states, reconstruct developmental trajectories, and measure phenotype in new terms such as cellular variance. The characterization of anatomy and developmental dynamics has not had an equivalent breakthrough since groundbreaking advances in live fluorescent microscopy. The new resolution obtained by single-cell RNA-seq is a boon to genetics because the novel description of phenotype offers the opportunity to refine gene function and dissect pleiotropy. In addition, the recent pairing of high-throughput genetic perturbation with single-cell RNA-seq has made practical a scale of genetic screening not previously possible.
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Affiliation(s)
- Kenneth D Birnbaum
- Center for Genomics and Systems Biology, New York University, New York, NY 10003, USA;
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169
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Gene expression variability across cells and species shapes innate immunity. Nature 2018; 563:197-202. [PMID: 30356220 PMCID: PMC6347972 DOI: 10.1038/s41586-018-0657-2] [Citation(s) in RCA: 125] [Impact Index Per Article: 20.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2017] [Accepted: 08/17/2018] [Indexed: 11/09/2022]
Abstract
As the first line of defence against pathogens, cells mount an innate immune response, which varies widely from cell to cell. The response must be potent but carefully controlled to avoid self-damage. How these constraints have shaped the evolution of innate immunity remains poorly understood. Here we characterize the innate immune response's transcriptional divergence between species and variability in expression among cells. Using bulk and single-cell transcriptomics in fibroblasts and mononuclear phagocytes from different species, challenged with immune stimuli, we map the architecture of the innate immune response. Transcriptionally diverging genes, including those that encode cytokines and chemokines, vary across cells and have distinct promoter structures. Conversely, genes that are involved in the regulation of this response, such as those that encode transcription factors and kinases, are conserved between species and display low cell-to-cell variability in expression. We suggest that this expression pattern, which is observed across species and conditions, has evolved as a mechanism for fine-tuned regulation to achieve an effective but balanced response.
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170
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Cao W, Zheng H. Peripheral immune system in aging and Alzheimer's disease. Mol Neurodegener 2018; 13:51. [PMID: 30285785 PMCID: PMC6169078 DOI: 10.1186/s13024-018-0284-2] [Citation(s) in RCA: 131] [Impact Index Per Article: 21.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2018] [Accepted: 09/21/2018] [Indexed: 12/13/2022] Open
Abstract
Alzheimer's disease (AD) represents an urgent public health mandate. AD is no longer considered a neural-centric disease; rather, a plethora of recent studies strongly implicate a critical role played by neuroinflammation in the pathogeneses of AD and other neurodegenerative conditions. A close functional connection between the immune system and central nervous system is increasingly recognized. In late-onset AD, aging represents the most significant risk factor. Here, from an immunological perspective, we summarize the prominent molecular and cellular changes in the periphery of aging individuals and AD patients. Moreover, we review the knowledge gained in the past several years that implicate specific arms of the peripheral immune system and other types of immune responses in modulating AD progression. Taken together, these findings collectively emphasize a dynamic role of a concert of brain-extrinsic, peripheral signals in the aging and degenerative processes in the CNS. We believe that a systematic view synthesizing the vast amounts of existing results will help guide the development of next-generation therapeutics and inform future directions of AD investigation.
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Affiliation(s)
- Wei Cao
- Department of Molecular and Human Genetics, Baylor College of Medicine, Huffington Center on Aging, Houston, TX, 77030, USA.
| | - Hui Zheng
- Department of Molecular and Human Genetics, Baylor College of Medicine, Huffington Center on Aging, Houston, TX, 77030, USA.
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171
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Todhunter ME, Sayaman RW, Miyano M, LaBarge MA. Tissue aging: the integration of collective and variant responses of cells to entropic forces over time. Curr Opin Cell Biol 2018; 54:121-129. [PMID: 29908481 PMCID: PMC6258070 DOI: 10.1016/j.ceb.2018.05.016] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2018] [Revised: 04/13/2018] [Accepted: 05/30/2018] [Indexed: 01/08/2023]
Abstract
Aging is driven by unavoidable entropic forces, physicochemical in nature, that damage the raw materials that constitute biological systems. Single cells experience and respond to stochastic physicochemical insults that occur either to the cells themselves or to their microenvironment, in a dynamic and reciprocal manner, leading to increased age-related cell-to-cell variation. We will discuss the biological mechanisms that integrate cell-to-cell variation across tissues resulting in stereotypical phenotypes of age.
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Affiliation(s)
- Michael E Todhunter
- Department of Populations Sciences, and Center for Cancer and Aging, Beckman Research Institute at City of Hope, 1500 E Duarte Rd, Duarte, CA 91011 USA
| | - Rosalyn W Sayaman
- Department of Populations Sciences, and Center for Cancer and Aging, Beckman Research Institute at City of Hope, 1500 E Duarte Rd, Duarte, CA 91011 USA
| | - Masaru Miyano
- Department of Populations Sciences, and Center for Cancer and Aging, Beckman Research Institute at City of Hope, 1500 E Duarte Rd, Duarte, CA 91011 USA
| | - Mark A LaBarge
- Department of Populations Sciences, and Center for Cancer and Aging, Beckman Research Institute at City of Hope, 1500 E Duarte Rd, Duarte, CA 91011 USA.
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172
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Song R, Sarnoski EA, Acar M. The Systems Biology of Single-Cell Aging. iScience 2018; 7:154-169. [PMID: 30267677 PMCID: PMC6153419 DOI: 10.1016/j.isci.2018.08.023] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2018] [Revised: 07/30/2018] [Accepted: 08/29/2018] [Indexed: 12/12/2022] Open
Abstract
Aging is a leading cause of human morbidity and mortality, but efforts to slow or reverse its effects are hampered by an incomplete understanding of its multi-faceted origins. Systems biology, the use of quantitative and computational methods to understand complex biological systems, offers a toolkit well suited to elucidating the root cause of aging. We describe the known components of the aging network and outline innovative techniques that open new avenues of investigation to the aging research community. We propose integration of the systems biology and aging fields, identifying areas of complementarity based on existing and impending technological capabilities.
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Affiliation(s)
- Ruijie Song
- Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, 300 George Street, Suite 501, New Haven, CT 06511, USA; Systems Biology Institute, Yale University, 850 West Campus Drive, West Haven, CT 06516, USA
| | - Ethan A Sarnoski
- Systems Biology Institute, Yale University, 850 West Campus Drive, West Haven, CT 06516, USA; Department of Molecular Cellular and Developmental Biology, Yale University, 219 Prospect Street, New Haven, CT 06511, USA
| | - Murat Acar
- Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, 300 George Street, Suite 501, New Haven, CT 06511, USA; Systems Biology Institute, Yale University, 850 West Campus Drive, West Haven, CT 06516, USA; Department of Molecular Cellular and Developmental Biology, Yale University, 219 Prospect Street, New Haven, CT 06511, USA; Department of Physics, Yale University, 217 Prospect Street, New Haven, CT 06511, USA.
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Eling N, Richard AC, Richardson S, Marioni JC, Vallejos CA. Correcting the Mean-Variance Dependency for Differential Variability Testing Using Single-Cell RNA Sequencing Data. Cell Syst 2018; 7:284-294.e12. [PMID: 30172840 PMCID: PMC6167088 DOI: 10.1016/j.cels.2018.06.011] [Citation(s) in RCA: 41] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2017] [Revised: 05/02/2018] [Accepted: 06/25/2018] [Indexed: 01/10/2023]
Abstract
Cell-to-cell transcriptional variability in otherwise homogeneous cell populations plays an important role in tissue function and development. Single-cell RNA sequencing can characterize this variability in a transcriptome-wide manner. However, technical variation and the confounding between variability and mean expression estimates hinder meaningful comparison of expression variability between cell populations. To address this problem, we introduce an analysis approach that extends the BASiCS statistical framework to derive a residual measure of variability that is not confounded by mean expression. This includes a robust procedure for quantifying technical noise in experiments where technical spike-in molecules are not available. We illustrate how our method provides biological insight into the dynamics of cell-to-cell expression variability, highlighting a synchronization of biosynthetic machinery components in immune cells upon activation. In contrast to the uniform up-regulation of the biosynthetic machinery, CD4+ T cells show heterogeneous up-regulation of immune-related and lineage-defining genes during activation and differentiation.
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Affiliation(s)
- Nils Eling
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK; Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Cambridge CB2 0RE, UK
| | - Arianne C Richard
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Cambridge CB2 0RE, UK; Cambridge Institute for Medical Research, University of Cambridge, Cambridge Biomedical Campus, Hills Road, Cambridge CB2 0XY, UK
| | - Sylvia Richardson
- MRC Biostatistics Unit, University of Cambridge, Cambridge Institute of Public Health, Forvie Site, Robinson Way, Cambridge Biomedical Campus, Cambridge CB2 0SR, UK
| | - John C Marioni
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK; Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Cambridge CB2 0RE, UK.
| | - Catalina A Vallejos
- The Alan Turing Institute, British Library, 96 Euston Road, London NW1 2DB, UK; Department of Statistical Science, University College London, 1-19 Torrington Place, London WC1E 7HB, UK; MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh EH4 2XY, UK.
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174
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Simonsen AT, Hansen MC, Kjeldsen E, Møller PL, Hindkjær JJ, Hokland P, Aggerholm A. Systematic evaluation of signal-to-noise ratio in variant detection from single cell genome multiple displacement amplification and exome sequencing. BMC Genomics 2018; 19:681. [PMID: 30223769 PMCID: PMC6142419 DOI: 10.1186/s12864-018-5063-5] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2018] [Accepted: 09/10/2018] [Indexed: 12/19/2022] Open
Abstract
Background The current literature on single cell genomic analyses on the DNA level is conflicting regarding requirements for cell quality, amplification success rates, allelic dropouts and resolution, lacking a systematic comparison of multiple cell input down to the single cell. We hypothesized that such a correlation assay would provide an approach to address the latter issues, utilizing the leukemic cell line OCI-AML3 with a known set of genetic aberrations. Results By analyzing single and multiple cell replicates (2 to 50 cells) purified by micromanipulation and serial dilution we stringently assessed the signal-to-noise ratio (SNR) from single as well as a discrete number of cells based on a multiple displacement amplification method, with whole exome sequencing as signal readout. In this setting, known OCI-AML3 mutations as well as large copy number alterations could be identified, adding to the current knowledge of cytogenetic status. The presence of DNMT3A R882C, NPM1 W288 fs and NRAS Q61L was consistent, in spite of uneven allelic read depths. In contrast, at the level of single cells, we observed that one-third to half of all variants were not reproduced in the replicate sample, and this allelic mismatch displayed an exponential function of cell input. Large signature duplications were discernible from 5 cells, whereas deletions were visible down to the single cell. Thus, even under highly optimized conditions, single cell whole genome amplification and interpretation must be taken with considerable caution, given that allelic change is frequent and displays low SNR. Allelic noise is rapidly alleviated with increased cell input, and the SNR is doubled from 2 to 50 cells. Conclusions In conclusion, we demonstrate noisy allele distributions, when analyzing genetic aberrations within single cells relative to multiple cells. Based on the presented data we recommend that single cell analyses should include replicate cell dilution assays for a given setup for relative assessment of procedure-specific SNR to ensure that the resolution supports the specific hypotheses. Electronic supplementary material The online version of this article (10.1186/s12864-018-5063-5) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Anita T Simonsen
- Department of Hematology, Aarhus University Hospital, Aarhus, Denmark
| | - Marcus C Hansen
- Department of Hematology, Aarhus University Hospital, Aarhus, Denmark.
| | - Eigil Kjeldsen
- Department of Hematology, Aarhus University Hospital, Aarhus, Denmark
| | - Peter L Møller
- Department of Hematology, Aarhus University Hospital, Aarhus, Denmark
| | | | - Peter Hokland
- Department of Hematology, Aarhus University Hospital, Aarhus, Denmark
| | - Anni Aggerholm
- Department of Hematology, Aarhus University Hospital, Aarhus, Denmark
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175
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Koohy H, Bolland DJ, Matheson LS, Schoenfelder S, Stellato C, Dimond A, Várnai C, Chovanec P, Chessa T, Denizot J, Manzano Garcia R, Wingett SW, Freire-Pritchett P, Nagano T, Hawkins P, Stephens L, Elderkin S, Spivakov M, Fraser P, Corcoran AE, Varga-Weisz PD. Genome organization and chromatin analysis identify transcriptional downregulation of insulin-like growth factor signaling as a hallmark of aging in developing B cells. Genome Biol 2018; 19:126. [PMID: 30180872 PMCID: PMC6124017 DOI: 10.1186/s13059-018-1489-y] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2018] [Accepted: 07/20/2018] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND Aging is characterized by loss of function of the adaptive immune system, but the underlying causes are poorly understood. To assess the molecular effects of aging on B cell development, we profiled gene expression and chromatin features genome-wide, including histone modifications and chromosome conformation, in bone marrow pro-B and pre-B cells from young and aged mice. RESULTS Our analysis reveals that the expression levels of most genes are generally preserved in B cell precursors isolated from aged compared with young mice. Nonetheless, age-specific expression changes are observed at numerous genes, including microRNA encoding genes. Importantly, these changes are underpinned by multi-layered alterations in chromatin structure, including chromatin accessibility, histone modifications, long-range promoter interactions, and nuclear compartmentalization. Previous work has shown that differentiation is linked to changes in promoter-regulatory element interactions. We find that aging in B cell precursors is accompanied by rewiring of such interactions. We identify transcriptional downregulation of components of the insulin-like growth factor signaling pathway, in particular downregulation of Irs1 and upregulation of Let-7 microRNA expression, as a signature of the aged phenotype. These changes in expression are associated with specific alterations in H3K27me3 occupancy, suggesting that Polycomb-mediated repression plays a role in precursor B cell aging. CONCLUSIONS Changes in chromatin and 3D genome organization play an important role in shaping the altered gene expression profile of aged precursor B cells. Components of the insulin-like growth factor signaling pathways are key targets of epigenetic regulation in aging in bone marrow B cell precursors.
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Affiliation(s)
- Hashem Koohy
- Nuclear Dynamics Programme, Babraham Institute, Cambridge, UK
- Human Immunology Unit, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - Daniel J Bolland
- Nuclear Dynamics Programme, Babraham Institute, Cambridge, UK
- Laboratory of Lymphocyte Signalling and Development, Babraham Institute, Cambridge, UK
| | - Louise S Matheson
- Nuclear Dynamics Programme, Babraham Institute, Cambridge, UK
- Laboratory of Lymphocyte Signalling and Development, Babraham Institute, Cambridge, UK
| | | | | | - Andrew Dimond
- Nuclear Dynamics Programme, Babraham Institute, Cambridge, UK
| | - Csilla Várnai
- Nuclear Dynamics Programme, Babraham Institute, Cambridge, UK
| | - Peter Chovanec
- Nuclear Dynamics Programme, Babraham Institute, Cambridge, UK
- Laboratory of Lymphocyte Signalling and Development, Babraham Institute, Cambridge, UK
| | | | - Jeremy Denizot
- Nuclear Dynamics Programme, Babraham Institute, Cambridge, UK
- Present address: Université Clermont Auvergne, Inserm U1071, M2iSH, USC-INRA 2018, F-, 63000, Clermont-Ferrand, France
| | | | - Steven W Wingett
- Nuclear Dynamics Programme, Babraham Institute, Cambridge, UK
- Bioinformatics, Babraham Institute, Cambridge, UK
| | - Paula Freire-Pritchett
- Nuclear Dynamics Programme, Babraham Institute, Cambridge, UK
- Division of Cell Biology, Medical Research Council Laboratory of Molecular Biology, Cambridge, CB2 0QH, UK
| | - Takashi Nagano
- Nuclear Dynamics Programme, Babraham Institute, Cambridge, UK
| | | | | | - Sarah Elderkin
- Nuclear Dynamics Programme, Babraham Institute, Cambridge, UK
| | - Mikhail Spivakov
- Nuclear Dynamics Programme, Babraham Institute, Cambridge, UK
- Functional Gene Control Group, MRC London Institute of Medical Sciences (LMS), Du Cane Road, London, W12 0NN, UK
| | - Peter Fraser
- Nuclear Dynamics Programme, Babraham Institute, Cambridge, UK
- Department of Biological Science, Florida State University, Tallahassee, FL, USA
| | - Anne E Corcoran
- Nuclear Dynamics Programme, Babraham Institute, Cambridge, UK.
- Laboratory of Lymphocyte Signalling and Development, Babraham Institute, Cambridge, UK.
| | - Patrick D Varga-Weisz
- Nuclear Dynamics Programme, Babraham Institute, Cambridge, UK.
- School of Biological Sciences, University of Essex, Colchester, UK.
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176
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Radzinski M, Reichmann D. Variety is the spice of life: how to explore a redox-dependent heterogeneity in genomically identical cellular populations. Curr Genet 2018; 65:301-306. [DOI: 10.1007/s00294-018-0878-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2018] [Revised: 08/12/2018] [Accepted: 08/12/2018] [Indexed: 11/29/2022]
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177
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Mertz DR, Ahmed T, Takayama S. Engineering cell heterogeneity into organs-on-a-chip. LAB ON A CHIP 2018; 18:2378-2395. [PMID: 30040104 PMCID: PMC6081245 DOI: 10.1039/c8lc00413g] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/17/2023]
Abstract
Organ-on-a-chip development is an application that will benefit from advances in cell heterogeneity characterization because these culture models are intended to mimic in vivo microenvironments, which are complex and dynamic. Due in no small part to advances in microfluidic single cell analysis methods, cell-to-cell variability is an increasingly understood feature of physiological tissues, with cell types from as common as 1 out of every 2 cells to as rare as 1 out of every 100 000 cells having important roles in the biochemical and biological makeup of tissues and organs. Variability between neighboring cells can be transient or maintained, and ordered or stochastic. This review covers three areas of well-studied cell heterogeneity that are informative for organ-on-a-chip development efforts: tumors, the lung, and the intestine. Then we look at how recent single cell analysis strategies have enabled better understanding of heterogeneity within in vitro and in vivo tissues. Finally, we provide a few work-arounds for adapting current on-chip culture methods to better mimic physiological cell heterogeneity including accounting for crucial rare cell types and events.
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Affiliation(s)
- David R Mertz
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Tech College of Engineering and Emory School of Medicine, USA.
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178
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Wang L, Felts SJ, Van Keulen VP, Scheid AD, Block MS, Markovic SN, Pease LR, Zhang Y. Integrative Genome-Wide Analysis of Long Noncoding RNAs in Diverse Immune Cell Types of Melanoma Patients. Cancer Res 2018; 78:4411-4423. [PMID: 29895674 PMCID: PMC6072578 DOI: 10.1158/0008-5472.can-18-0529] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2018] [Revised: 04/17/2018] [Accepted: 06/05/2018] [Indexed: 12/12/2022]
Abstract
Genome-wide identification and characterization of long noncoding RNAs (lncRNA) in individual immune cell lineages helps us better understand the driving mechanisms behind melanoma and advance personalized patient treatment. To elucidate the transcriptional landscape in diverse immune cell types of peripheral blood cells (PBC) in stage IV melanoma, we used whole transcriptome RNA sequencing to profile lncRNAs in CD4+, CD8+, and CD14+ PBC from 132 patient samples. Our integrative computational approach identified 27,625 expressed lncRNAs, 2,744 of which were novel. Both T cells (i.e., CD4+ and CD8+ PBC) and monocytes (i.e., CD14+ PBC) exhibited differential transcriptional expression profiles between patients with melanoma and healthy subjects. Cis- and trans-level coexpression analysis suggested that lncRNAs are potentially involved in many important immune-related pathways and the programmed cell death receptor 1 checkpoint pathways. We also identified nine gene coexpression modules significantly associated with melanoma status, all of which were significantly enriched for three mRNA translation processes. Age and melanoma traits closely correlated with each other, implying that melanoma contains age-associated immune changes. Our computational prediction analysis suggests that many cis- and trans-regulatory lncRNAs could interact with multiple transcriptional and posttranscriptional regulatory elements in CD4+, CD8+, and CD14+ PBC, respectively. These results provide novel insights into the regulatory mechanisms involving lncRNAs in individual immune cell types in melanoma and can help expedite cell type-specific immunotherapy treatments for such diseases.Significance: These findings elucidate melanoma-associated changes to the noncoding transcriptional landscape of distinct immune cell classes, thus providing cell type-specific guidance to targeted immunotherapy regimens. Cancer Res; 78(15); 4411-23. ©2018 AACR.
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Affiliation(s)
- Lei Wang
- Division of Biostatistics and Bioinformatics, University of Maryland Marlene and Stewart Greenebaum Comprehensive Cancer Center, Baltimore, Maryland
- Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, Maryland
| | - Sara J Felts
- Department of Immunology, Mayo Clinic College of Medicine and Science, Rochester, Minnesota
| | - Virginia P Van Keulen
- Department of Immunology, Mayo Clinic College of Medicine and Science, Rochester, Minnesota
| | - Adam D Scheid
- Department of Immunology, Mayo Clinic College of Medicine and Science, Rochester, Minnesota
| | - Matthew S Block
- Department of Oncology, Mayo Clinic College of Medicine and Science, Rochester, Minnesota
| | - Svetomir N Markovic
- Department of Oncology, Mayo Clinic College of Medicine and Science, Rochester, Minnesota
| | - Larry R Pease
- Department of Immunology, Mayo Clinic College of Medicine and Science, Rochester, Minnesota.
| | - Yuji Zhang
- Division of Biostatistics and Bioinformatics, University of Maryland Marlene and Stewart Greenebaum Comprehensive Cancer Center, Baltimore, Maryland.
- Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, Maryland
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179
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Carter S, Miard S, Caron A, Sallé-Lefort S, St-Pierre P, Anhê FF, Lavoie-Charland E, Blais-Lecours P, Drolet MC, Lefebvre JS, Lacombe J, Deshaies Y, Couet J, Laplante M, Ferron M, Bossé Y, Marette A, Richard D, Marsolais D, Picard F. Loss of OcaB Prevents Age-Induced Fat Accretion and Insulin Resistance by Altering B-Lymphocyte Transition and Promoting Energy Expenditure. Diabetes 2018; 67:1285-1296. [PMID: 29496744 DOI: 10.2337/db17-0558] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/15/2017] [Accepted: 02/19/2018] [Indexed: 11/13/2022]
Abstract
The current demographic shift toward an aging population has led to a robust increase in the prevalence of age-associated metabolic disorders. Recent studies have demonstrated that the etiology of obesity-related insulin resistance that develops with aging differs from that induced by high-calorie diets. Whereas the role of adaptive immunity in changes in energy metabolism driven by nutritional challenges has recently gained attention, its impact on aging remains mostly unknown. Here we found that the number of follicular B2 lymphocytes and expression of the B-cell-specific transcriptional coactivator OcaB increase with age in spleen and in intra-abdominal epididymal white adipose tissue (eWAT), concomitantly with higher circulating levels of IgG and impaired glucose homeostasis. Reduction of B-cell maturation and Ig production-especially that of IgG2c-by ablation of OcaB prevented age-induced glucose intolerance and insulin resistance and promoted energy expenditure by stimulating fatty acid utilization in eWAT and brown adipose tissue. Transfer of wild-type bone marrow in OcaB-/- mice replenished the eWAT B2-cell population and IgG levels, which diminished glucose tolerance, insulin sensitivity, and energy expenditure while increasing body weight gain in aged mice. Thus these findings demonstrate that upon aging, modifications in B-cell-driven adaptive immunity contribute to glucose intolerance and fat accretion.
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Affiliation(s)
- Sophie Carter
- Centre de recherche de l'Institut universitaire de cardiologie et de pneumologie de Québec, Québec, QC, Canada
- Faculty of Pharmacy, Université Laval, Québec, QC, Canada
| | - Stéphanie Miard
- Centre de recherche de l'Institut universitaire de cardiologie et de pneumologie de Québec, Québec, QC, Canada
| | - Alexandre Caron
- Centre de recherche de l'Institut universitaire de cardiologie et de pneumologie de Québec, Québec, QC, Canada
- Department of Medicine, Faculty of Medicine, Université Laval, Québec, QC, Canada
| | - Sandrine Sallé-Lefort
- Centre de recherche de l'Institut universitaire de cardiologie et de pneumologie de Québec, Québec, QC, Canada
- Faculty of Pharmacy, Université Laval, Québec, QC, Canada
| | - Philippe St-Pierre
- Centre de recherche de l'Institut universitaire de cardiologie et de pneumologie de Québec, Québec, QC, Canada
- Institute for Nutrition and Functional Foods, Québec, QC, Canada
| | - Fernando Forato Anhê
- Centre de recherche de l'Institut universitaire de cardiologie et de pneumologie de Québec, Québec, QC, Canada
- Institute for Nutrition and Functional Foods, Québec, QC, Canada
| | - Emilie Lavoie-Charland
- Centre de recherche de l'Institut universitaire de cardiologie et de pneumologie de Québec, Québec, QC, Canada
- Department of Molecular Medicine, Faculty of Medicine, Université Laval, Québec, QC, Canada
| | - Pascale Blais-Lecours
- Centre de recherche de l'Institut universitaire de cardiologie et de pneumologie de Québec, Québec, QC, Canada
- Department of Medicine, Faculty of Medicine, Université Laval, Québec, QC, Canada
| | - Marie-Claude Drolet
- Centre de recherche de l'Institut universitaire de cardiologie et de pneumologie de Québec, Québec, QC, Canada
| | - Julie S Lefebvre
- Centre de recherche de l'Institut universitaire de cardiologie et de pneumologie de Québec, Québec, QC, Canada
| | - Julie Lacombe
- Integrative and Molecular Physiology Research Unit, Institut de recherches cliniques de Montréal, Montréal, QC, Canada
| | - Yves Deshaies
- Centre de recherche de l'Institut universitaire de cardiologie et de pneumologie de Québec, Québec, QC, Canada
- Department of Medicine, Faculty of Medicine, Université Laval, Québec, QC, Canada
| | - Jacques Couet
- Centre de recherche de l'Institut universitaire de cardiologie et de pneumologie de Québec, Québec, QC, Canada
- Department of Medicine, Faculty of Medicine, Université Laval, Québec, QC, Canada
| | - Mathieu Laplante
- Centre de recherche de l'Institut universitaire de cardiologie et de pneumologie de Québec, Québec, QC, Canada
- Department of Medicine, Faculty of Medicine, Université Laval, Québec, QC, Canada
| | - Mathieu Ferron
- Integrative and Molecular Physiology Research Unit, Institut de recherches cliniques de Montréal, Montréal, QC, Canada
- Department of Medicine and Biochemistry, Faculty of Medicine, Université de Montréal, Montréal, QC, Canada
| | - Yohan Bossé
- Centre de recherche de l'Institut universitaire de cardiologie et de pneumologie de Québec, Québec, QC, Canada
- Department of Molecular Medicine, Faculty of Medicine, Université Laval, Québec, QC, Canada
| | - André Marette
- Centre de recherche de l'Institut universitaire de cardiologie et de pneumologie de Québec, Québec, QC, Canada
- Department of Medicine, Faculty of Medicine, Université Laval, Québec, QC, Canada
- Institute for Nutrition and Functional Foods, Québec, QC, Canada
| | - Denis Richard
- Centre de recherche de l'Institut universitaire de cardiologie et de pneumologie de Québec, Québec, QC, Canada
- Department of Medicine, Faculty of Medicine, Université Laval, Québec, QC, Canada
| | - David Marsolais
- Centre de recherche de l'Institut universitaire de cardiologie et de pneumologie de Québec, Québec, QC, Canada
- Department of Medicine, Faculty of Medicine, Université Laval, Québec, QC, Canada
| | - Frédéric Picard
- Centre de recherche de l'Institut universitaire de cardiologie et de pneumologie de Québec, Québec, QC, Canada
- Faculty of Pharmacy, Université Laval, Québec, QC, Canada
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180
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Vegh P, Haniffa M. The impact of single-cell RNA sequencing on understanding the functional organization of the immune system. Brief Funct Genomics 2018; 17:265-272. [PMID: 29547972 PMCID: PMC6063276 DOI: 10.1093/bfgp/ely003] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
Application of single-cell genomics technologies has revolutionized our approach to study the immune system. Unravelling the functional diversity of immune cells and their coordinated response is key to understanding immunity. Single-cell transcriptomics technologies provide high-dimensional assessment of the transcriptional states of immune cells and have been successfully applied to discover new immune cell types, reveal haematopoietic lineages, identify gene modules dictating immune responses and investigate lymphocyte antigen receptor diversity. In this review, we discuss the impact and applications of single-cell RNA sequencing technologies in immunology.
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Affiliation(s)
- Peter Vegh
- Institute of Cellular Medicine, Newcastle University, Newcastle upon Tyne, UK
| | - Muzlifah Haniffa
- Department of Dermatology, Newcastle upon Tyne NHS Foundation Trust, Newcastle upon Tyne, UK
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181
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Abstract
Single-cell RNA sequencing (scRNA-seq) is currently transforming our understanding of biology, as it is a powerful tool to resolve cellular heterogeneity and molecular networks. Over 50 protocols have been developed in recent years and also data processing and analyzes tools are evolving fast. Here, we review the basic principles underlying the different experimental protocols and how to benchmark them. We also review and compare the essential methods to process scRNA-seq data from mapping, filtering, normalization and batch corrections to basic differential expression analysis. We hope that this helps to choose appropriate experimental and computational methods for the research question at hand.
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Affiliation(s)
- Christoph Ziegenhain
- Anthropology and Human Genomics, Department of Biology II, Ludwig-Maximilians University, Großhaderner Str. 2, Martinsried, Germany
| | - Beate Vieth
- Anthropology and Human Genomics, Department of Biology II, Ludwig-Maximilians University, Großhaderner Str. 2, Martinsried, Germany
| | - Swati Parekh
- Anthropology and Human Genomics, Department of Biology II, Ludwig-Maximilians University, Großhaderner Str. 2, Martinsried, Germany
| | - Ines Hellmann
- Anthropology and Human Genomics, Department of Biology II, Ludwig-Maximilians University, Großhaderner Str. 2, Martinsried, Germany
| | - Wolfgang Enard
- Anthropology and Human Genomics, Department of Biology II, Ludwig-Maximilians University, Großhaderner Str. 2, Martinsried, Germany
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182
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Davie K, Janssens J, Koldere D, De Waegeneer M, Pech U, Kreft Ł, Aibar S, Makhzami S, Christiaens V, Bravo González-Blas C, Poovathingal S, Hulselmans G, Spanier KI, Moerman T, Vanspauwen B, Geurs S, Voet T, Lammertyn J, Thienpont B, Liu S, Konstantinides N, Fiers M, Verstreken P, Aerts S. A Single-Cell Transcriptome Atlas of the Aging Drosophila Brain. Cell 2018; 174:982-998.e20. [PMID: 29909982 PMCID: PMC6086935 DOI: 10.1016/j.cell.2018.05.057] [Citation(s) in RCA: 437] [Impact Index Per Article: 72.8] [Reference Citation Analysis] [Abstract] [Key Words] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2017] [Revised: 03/30/2018] [Accepted: 05/25/2018] [Indexed: 02/06/2023]
Abstract
The diversity of cell types and regulatory states in the brain, and how these change during aging, remains largely unknown. We present a single-cell transcriptome atlas of the entire adult Drosophila melanogaster brain sampled across its lifespan. Cell clustering identified 87 initial cell clusters that are further subclustered and validated by targeted cell-sorting. Our data show high granularity and identify a wide range of cell types. Gene network analyses using SCENIC revealed regulatory heterogeneity linked to energy consumption. During aging, RNA content declines exponentially without affecting neuronal identity in old brains. This single-cell brain atlas covers nearly all cells in the normal brain and provides the tools to study cellular diversity alongside other Drosophila and mammalian single-cell datasets in our unique single-cell analysis platform: SCope (http://scope.aertslab.org). These results, together with SCope, allow comprehensive exploration of all transcriptional states of an entire aging brain. A single-cell atlas of the adult fly brain during aging Network inference reveals regulatory states related to oxidative phosphorylation Cell identity is retained during aging despite exponential decline of gene expression SCope: An online tool to explore and compare single-cell datasets across species
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Affiliation(s)
- Kristofer Davie
- VIB Center for Brain & Disease Research, KU Leuven, Leuven 3000, Belgium; Department of Human Genetics KU Leuven, Leuven 3000, Belgium
| | - Jasper Janssens
- VIB Center for Brain & Disease Research, KU Leuven, Leuven 3000, Belgium; Department of Human Genetics KU Leuven, Leuven 3000, Belgium
| | - Duygu Koldere
- VIB Center for Brain & Disease Research, KU Leuven, Leuven 3000, Belgium; Department of Human Genetics KU Leuven, Leuven 3000, Belgium
| | - Maxime De Waegeneer
- VIB Center for Brain & Disease Research, KU Leuven, Leuven 3000, Belgium; Department of Human Genetics KU Leuven, Leuven 3000, Belgium
| | - Uli Pech
- VIB Center for Brain & Disease Research, KU Leuven, Leuven 3000, Belgium; Department of Neurosciences, KU Leuven, Leuven 3000, Belgium
| | - Łukasz Kreft
- VIB Bioinformatics Core, VIB, Ghent 9052, Belgium
| | - Sara Aibar
- VIB Center for Brain & Disease Research, KU Leuven, Leuven 3000, Belgium; Department of Human Genetics KU Leuven, Leuven 3000, Belgium
| | - Samira Makhzami
- VIB Center for Brain & Disease Research, KU Leuven, Leuven 3000, Belgium; Department of Human Genetics KU Leuven, Leuven 3000, Belgium
| | - Valerie Christiaens
- VIB Center for Brain & Disease Research, KU Leuven, Leuven 3000, Belgium; Department of Human Genetics KU Leuven, Leuven 3000, Belgium
| | - Carmen Bravo González-Blas
- VIB Center for Brain & Disease Research, KU Leuven, Leuven 3000, Belgium; Department of Human Genetics KU Leuven, Leuven 3000, Belgium
| | | | - Gert Hulselmans
- VIB Center for Brain & Disease Research, KU Leuven, Leuven 3000, Belgium; Department of Human Genetics KU Leuven, Leuven 3000, Belgium
| | - Katina I Spanier
- VIB Center for Brain & Disease Research, KU Leuven, Leuven 3000, Belgium; Department of Human Genetics KU Leuven, Leuven 3000, Belgium
| | - Thomas Moerman
- ESAT, KU Leuven, Leuven 3001, Belgium; Smart Applications and Innovation Services, IMEC, Leuven 3001, Belgium
| | | | - Sarah Geurs
- Department of Human Genetics KU Leuven, Leuven 3000, Belgium
| | - Thierry Voet
- Department of Human Genetics KU Leuven, Leuven 3000, Belgium
| | | | | | - Sha Liu
- VIB Center for Brain & Disease Research, KU Leuven, Leuven 3000, Belgium; Department of Neurosciences, KU Leuven, Leuven 3000, Belgium
| | | | - Mark Fiers
- VIB Center for Brain & Disease Research, KU Leuven, Leuven 3000, Belgium; Department of Neurosciences, KU Leuven, Leuven 3000, Belgium
| | - Patrik Verstreken
- VIB Center for Brain & Disease Research, KU Leuven, Leuven 3000, Belgium; Department of Neurosciences, KU Leuven, Leuven 3000, Belgium
| | - Stein Aerts
- VIB Center for Brain & Disease Research, KU Leuven, Leuven 3000, Belgium; Department of Human Genetics KU Leuven, Leuven 3000, Belgium.
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183
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Cheung P, Vallania F, Warsinske HC, Donato M, Schaffert S, Chang SE, Dvorak M, Dekker CL, Davis MM, Utz PJ, Khatri P, Kuo AJ. Single-Cell Chromatin Modification Profiling Reveals Increased Epigenetic Variations with Aging. Cell 2018; 173:1385-1397.e14. [PMID: 29706550 PMCID: PMC5984186 DOI: 10.1016/j.cell.2018.03.079] [Citation(s) in RCA: 214] [Impact Index Per Article: 35.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2018] [Revised: 02/27/2018] [Accepted: 03/28/2018] [Indexed: 12/17/2022]
Abstract
Post-translational modifications of histone proteins and exchanges of histone variants of chromatin are central to the regulation of nearly all DNA-templated biological processes. However, the degree and variability of chromatin modifications in specific human immune cells remain largely unknown. Here, we employ a highly multiplexed mass cytometry analysis to profile the global levels of a broad array of chromatin modifications in primary human immune cells at the single-cell level. Our data reveal markedly different cell-type- and hematopoietic-lineage-specific chromatin modification patterns. Differential analysis between younger and older adults shows that aging is associated with increased heterogeneity between individuals and elevated cell-to-cell variability in chromatin modifications. Analysis of a twin cohort unveils heritability of chromatin modifications and demonstrates that aging-related chromatin alterations are predominantly driven by non-heritable influences. Together, we present a powerful platform for chromatin and immunology research. Our discoveries highlight the profound impacts of aging on chromatin modifications.
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Affiliation(s)
- Peggie Cheung
- Institute for Immunity, Transplantation, and Infection, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Medicine, Division of Immunology and Rheumatology, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Francesco Vallania
- Institute for Immunity, Transplantation, and Infection, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Medicine, Division of Biomedical Informatics Research, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Hayley C Warsinske
- Institute for Immunity, Transplantation, and Infection, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Medicine, Division of Biomedical Informatics Research, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Michele Donato
- Institute for Immunity, Transplantation, and Infection, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Medicine, Division of Biomedical Informatics Research, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Steven Schaffert
- Institute for Immunity, Transplantation, and Infection, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Medicine, Division of Biomedical Informatics Research, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Sarah E Chang
- Institute for Immunity, Transplantation, and Infection, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Medicine, Division of Immunology and Rheumatology, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Mai Dvorak
- Institute for Immunity, Transplantation, and Infection, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Medicine, Division of Immunology and Rheumatology, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Cornelia L Dekker
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Mark M Davis
- Institute for Immunity, Transplantation, and Infection, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA 94304, USA; Howard Hughes Medical Institute, Stanford University School of Medicine, Stanford, CA 94304, USA
| | - Paul J Utz
- Institute for Immunity, Transplantation, and Infection, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Medicine, Division of Immunology and Rheumatology, Stanford University School of Medicine, Stanford, CA 94305, USA.
| | - Purvesh Khatri
- Institute for Immunity, Transplantation, and Infection, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Medicine, Division of Biomedical Informatics Research, Stanford University School of Medicine, Stanford, CA 94305, USA.
| | - Alex J Kuo
- Institute for Immunity, Transplantation, and Infection, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Medicine, Division of Immunology and Rheumatology, Stanford University School of Medicine, Stanford, CA 94305, USA.
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184
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Intrinsic and extrinsic contributors to defective CD8+ T cell responses with aging. Exp Gerontol 2018; 105:140-145. [DOI: 10.1016/j.exger.2018.01.011] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2017] [Revised: 01/08/2018] [Accepted: 01/08/2018] [Indexed: 12/20/2022]
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185
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Single-Cell Sequencing in Normal and Malignant Hematopoiesis. Hemasphere 2018; 2:e34. [PMID: 31723762 PMCID: PMC6745901 DOI: 10.1097/hs9.0000000000000034] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2017] [Revised: 01/19/2018] [Accepted: 01/22/2018] [Indexed: 12/31/2022] Open
Abstract
Hematopoiesis is one of the best studied adult stem-cell systems, with a differentiation hierarchy progressing from immature hematopoietic stem cells to over 10 distinct mature cell types. Recent technological breakthroughs now make it possible to define transcriptional profiles in thousands of individual cells. Facilitated by the wealth of prior data on cell purification and analysis strategies, hematopoiesis has been one of the earliest experimental systems to which many of these new single-cell sequencing technologies have been applied. In this review, the authors focus on recent studies, which have shed light on heterogeneity within individual populations as well as the relationships between populations, and also attempt to characterize the differences between normal and disease/perturbed states.
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186
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Abstract
Ageing leads to dramatic changes in the physiology of many different tissues resulting in a spectrum of pathology. Nonetheless, many lines of evidence suggest that ageing is driven by highly conserved cell intrinsic processes, and a set of unifying hallmarks of ageing has been defined. Here, we survey reports of age-linked changes in basal gene expression across eukaryotes from yeast to human and identify six gene expression hallmarks of cellular ageing: downregulation of genes encoding mitochondrial proteins; downregulation of the protein synthesis machinery; dysregulation of immune system genes; reduced growth factor signalling; constitutive responses to stress and DNA damage; dysregulation of gene expression and mRNA processing. These encompass widely reported features of ageing such as increased senescence and inflammation, reduced electron transport chain activity and reduced ribosome synthesis, but also reveal a surprising lack of gene expression responses to known age-linked cellular stresses. We discuss how the existence of conserved transcriptomic hallmarks relates to genome-wide epigenetic differences underlying ageing clocks, and how the changing transcriptome results in proteomic alterations where data is available and to variations in cell physiology characteristic of ageing. Identification of gene expression events that occur during ageing across distant organisms should be informative as to conserved underlying mechanisms of ageing, and provide additional biomarkers to assess the effects of diet and other environmental factors on the rate of ageing.
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Affiliation(s)
- Stephen Frenk
- Department of Genetics, University of North Carolina, Chapel Hill, NC, 27599-3280, USA
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187
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Microfluidic single-cell technology in immunology and antibody screening. Mol Aspects Med 2018; 59:47-61. [DOI: 10.1016/j.mam.2017.09.004] [Citation(s) in RCA: 56] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2017] [Revised: 09/06/2017] [Accepted: 09/13/2017] [Indexed: 11/20/2022]
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188
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Kelsey G, Stegle O, Reik W. Single-cell epigenomics: Recording the past and predicting the future. Science 2018; 358:69-75. [PMID: 28983045 DOI: 10.1126/science.aan6826] [Citation(s) in RCA: 253] [Impact Index Per Article: 42.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Single-cell multi-omics has recently emerged as a powerful technology by which different layers of genomic output-and hence cell identity and function-can be recorded simultaneously. Integrating various components of the epigenome into multi-omics measurements allows for studying cellular heterogeneity at different time scales and for discovering new layers of molecular connectivity between the genome and its functional output. Measurements that are increasingly available range from those that identify transcription factor occupancy and initiation of transcription to long-lasting and heritable epigenetic marks such as DNA methylation. Together with techniques in which cell lineage is recorded, this multilayered information will provide insights into a cell's past history and its future potential. This will allow new levels of understanding of cell fate decisions, identity, and function in normal development, physiology, and disease.
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Affiliation(s)
- Gavin Kelsey
- Epigenetics Programme, Babraham Institute, Cambridge CB22 3AT, UK. .,Centre for Trophoblast Research, University of Cambridge, Cambridge CB2 3EG, UK
| | - Oliver Stegle
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, CB10 1SD Hinxton, Cambridge, UK. .,European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg 69117, Germany
| | - Wolf Reik
- Epigenetics Programme, Babraham Institute, Cambridge CB22 3AT, UK. .,Centre for Trophoblast Research, University of Cambridge, Cambridge CB2 3EG, UK.,Wellcome Trust Sanger Institute, Cambridge CB10 1SA, UK
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189
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Flavahan WA, Gaskell E, Bernstein BE. Epigenetic plasticity and the hallmarks of cancer. Science 2018; 357:357/6348/eaal2380. [PMID: 28729483 DOI: 10.1126/science.aal2380] [Citation(s) in RCA: 799] [Impact Index Per Article: 133.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Chromatin and associated epigenetic mechanisms stabilize gene expression and cellular states while also facilitating appropriate responses to developmental or environmental cues. Genetic, environmental, or metabolic insults can induce overly restrictive or overly permissive epigenetic landscapes that contribute to pathogenesis of cancer and other diseases. Restrictive chromatin states may prevent appropriate induction of tumor suppressor programs or block differentiation. By contrast, permissive or "plastic" states may allow stochastic oncogene activation or nonphysiologic cell fate transitions. Whereas many stochastic events will be inconsequential "passengers," some will confer a fitness advantage to a cell and be selected as "drivers." We review the broad roles played by epigenetic aberrations in tumor initiation and evolution and their potential to give rise to all classic hallmarks of cancer.
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Affiliation(s)
- William A Flavahan
- Department of Pathology and Center for Cancer Research, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA, and Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
| | - Elizabeth Gaskell
- Department of Pathology and Center for Cancer Research, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA, and Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
| | - Bradley E Bernstein
- Department of Pathology and Center for Cancer Research, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA, and Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA.
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190
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Abstract
As the popular adage goes, all diseases run into old age and almost all physiological changes are associated with alterations in gene expression, irrespective of whether they are causal or consequential. Therefore, the quest for mechanisms that delay ageing and decrease age-associated diseases has propelled researchers to unravel regulatory factors that lead to changes in chromatin structure and function, which ultimately results in deregulated gene expression. It is therefore essential to bring together literature, which until recently has investigated gene expression and chromatin independently. With advances in biomedical research and the emergence of epigenetic regulators as potential therapeutic targets, enhancing our understanding of mechanisms that 'derail' transcription and identification of causal genes/pathways during ageing will have a significant impact. In this context, this chapter aims to not only summarize the key features of age-associated changes in epigenetics and transcription, but also identifies gaps in the field and proposes aspects that need to be investigated in the future.
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191
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Abstract
Systems biology is an approach to collect high-dimensional data and analyze in an integrated manner. As aging is a complicated physiological functional decline in biological system, the methods in systems biology could be utilized in aging studies. Here we reviewed recent advances in systems biology in aging research and divide them into two major parts. One is the data resource, which includes omics data from DNA, RNA, proteins, epigenetic changes, metabolisms, and recently single-cell-level variations. The other is the data analysis methods consisting of network and modeling approaches. With all the data and the tools to analyze them, we could further promote our understanding of the systematic aging.
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192
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A cellular and molecular view of T helper 17 cell plasticity in autoimmunity. J Autoimmun 2017; 87:1-15. [PMID: 29275836 DOI: 10.1016/j.jaut.2017.12.007] [Citation(s) in RCA: 190] [Impact Index Per Article: 27.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2017] [Accepted: 12/06/2017] [Indexed: 02/08/2023]
Abstract
Since the original identification of the T helper 17 (Th17) subset in 2005, it has become evident that these cells do not only contribute to host defence against pathogens, such as bacteria and fungi, but that they are also critically involved in the pathogenesis of many autoimmune diseases. In contrast to the classic Th1 and Th2 cells, which represent rather stably polarized subsets, Th17 cells display remarkable heterogeneity and plasticity. This has been attributed to the characteristics of the key transcription factor that guides Th17 differentiation, retinoic acid receptor-related orphan nuclear receptor gamma (RORγ). Unlike the 'master regulators' T-bet and GATA3 that orchestrate Th1 and Th2 differentiation, respectively, RORγ controls transcription at relatively few loci in Th17 cells. Moreover, its expression is not stabilized by positive feedback loops but rather influenced by environmental cues, allowing for substantial functional plasticity. Importantly, a subset of IL-17/IFNγ double-producing Th17 cells was identified in both human and mouse models. Evidence is accumulating that these IL-17/IFNγ double-producing cells are pathogenic drivers in autoimmune diseases, including rheumatoid arthritis, multiple sclerosis and inflammatory bowel disease. In addition, IL-17/IFNγ double-producing cells have been identified in disorders in which the role of autoimmunity remains unclear, such as sarcoidosis. The observed plasticity of Th17 cells towards the Th1 phenotype can be explained by extensive epigenetic priming of the IFNG locus in Th17 cells. In fact, Th17 cells display an IFNG chromatin landscape that is remarkably similar to that of Th1 cells. On the other hand, pathogenic capabilities of Th17 cells can be restrained by stimulating IL-10 production and transdifferentiation into IL-10 producing T regulatory type 1 (Tr1) cells. In this review, we discuss recent advances in our knowledge on the cellular and molecular mechanisms involved in Th17 differentiation, heterogeneity and plasticity. We focus on transcriptional regulation of the Th17 expression program, the epigenetic dynamics involved, and how genetic variants associated with autoimmunity may affect immune responses through distal gene regulatory elements. Finally, the implications of Th17 cell plasticity for the pathogenesis and treatment of human autoimmune diseases will be discussed.
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193
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Nikolich-Žugich J. The twilight of immunity: emerging concepts in aging of the immune system. Nat Immunol 2017; 19:10-19. [PMID: 29242543 DOI: 10.1038/s41590-017-0006-x] [Citation(s) in RCA: 608] [Impact Index Per Article: 86.9] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2017] [Accepted: 10/26/2017] [Indexed: 02/06/2023]
Abstract
Immunosenescence is a series of age-related changes that affect the immune system and, with time, lead to increased vulnerability to infectious diseases. This Review addresses recent developments in the understanding of age-related changes that affect key components of immunity, including the effect of aging on cells of the (mostly adaptive) immune system, on soluble molecules that guide the maintenance and function of the immune system and on lymphoid organs that coordinate both the maintenance of lymphocytes and the initiation of immune responses. I further address the effect of the metagenome and exposome as key modifiers of immune-system aging and discuss a conceptual framework in which age-related changes in immunity might also affect the basic rules by which the immune system operates.
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Affiliation(s)
- Janko Nikolich-Žugich
- Department of Immunobiology and the Arizona Center on Aging, University of Arizona College of Medicine-Tucson, Tucson, AZ, USA.
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194
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Schrom EC, Graham AL. Instructed subsets or agile swarms: how T-helper cells may adaptively counter uncertainty with variability and plasticity. Curr Opin Genet Dev 2017; 47:75-82. [PMID: 28926759 DOI: 10.1016/j.gde.2017.08.008] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2017] [Revised: 08/11/2017] [Accepted: 08/31/2017] [Indexed: 10/25/2022]
Abstract
Over recent years, extensive phenotypic variability and plasticity have been revealed among the T-helper cells of the mammalian adaptive immune system, even within clonal lineages of identical antigen specificity. This challenges the conventional view that T-helper cells assort into functionally distinct subsets following differential instruction by the innate immune system. We argue that the adaptive value of coping with uncertainty can reconcile the 'instructed subset' framework with T-helper variability and plasticity. However, we also suggest that T-helper cells might better be understood as agile swarms engaged in collective decision-making to promote host fitness. With rigorous testing, the 'agile swarms' framework may illuminate how variable and plastic individual T-helper cells interact to create coherent immunity.
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Affiliation(s)
- Edward C Schrom
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA.
| | - Andrea L Graham
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA.
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195
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Stubbington MJT, Rozenblatt-Rosen O, Regev A, Teichmann SA. Single-cell transcriptomics to explore the immune system in health and disease. Science 2017; 358:58-63. [PMID: 28983043 PMCID: PMC5654495 DOI: 10.1126/science.aan6828] [Citation(s) in RCA: 334] [Impact Index Per Article: 47.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
The immune system varies in cell types, states, and locations. The complex networks, interactions, and responses of immune cells produce diverse cellular ecosystems composed of multiple cell types, accompanied by genetic diversity in antigen receptors. Within this ecosystem, innate and adaptive immune cells maintain and protect tissue function, integrity, and homeostasis upon changes in functional demands and diverse insults. Characterizing this inherent complexity requires studies at single-cell resolution. Recent advances such as massively parallel single-cell RNA sequencing and sophisticated computational methods are catalyzing a revolution in our understanding of immunology. Here we provide an overview of the state of single-cell genomics methods and an outlook on the use of single-cell techniques to decipher the adaptive and innate components of immunity.
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Affiliation(s)
| | - Orit Rozenblatt-Rosen
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Aviv Regev
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
- Howard Hughes Medical Institute, Koch Institute for Integrative Cancer Research, Department of Biology, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Sarah A Teichmann
- Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK.
- Theory of Condensed Matter, Cavendish Laboratory, 19 JJ Thomson Ave, Cambridge CB3 0HE, UK
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196
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Abstract
The recent flood of single-cell data not only boosts our knowledge of cells and cell types, but also provides new insight into development and evolution from a cellular perspective. For example, assaying the genomes of multiple cells during development reveals developmental lineage trees-the kinship lineage-whereas cellular transcriptomes inform us about the regulatory state of cells and their gradual restriction in potency-the Waddington lineage. Beyond that, the comparison of single-cell data across species allows evolutionary changes to be tracked at all stages of development from the zygote, via different kinds of stem cells, to the differentiating cells. We discuss recent insights into the evolution of stem cells and initial attempts to reconstruct the evolutionary cell type tree of the mammalian forebrain, for example, by the comparative analysis of neuron types in the mesencephalic floor. These studies illustrate the immense potential of single-cell genomics to open up a new era in developmental and evolutionary research.
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Affiliation(s)
- John C Marioni
- EMBL-European Bioinformatics Institute, Wellcome Genome Campus, Cambridge CB10 1SD, United Kingdom;
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge CB2 0RE, United Kingdom
- Wellcome Trust Sanger Institute, Wellcome Genome Campus, Cambridge CB10 1SA, United Kingdom
| | - Detlev Arendt
- Developmental Biology Unit, EMBL, 69117 Heidelberg, Germany;
- Centre for Organismal Studies, University of Heidelberg, 69120 Heidelberg, Germany
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197
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Deschênes M, Chabot B. The emerging role of alternative splicing in senescence and aging. Aging Cell 2017; 16:918-933. [PMID: 28703423 PMCID: PMC5595669 DOI: 10.1111/acel.12646] [Citation(s) in RCA: 114] [Impact Index Per Article: 16.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/12/2017] [Indexed: 12/22/2022] Open
Abstract
Deregulation of precursor mRNA splicing is associated with many illnesses and has been linked to age-related chronic diseases. Here we review recent progress documenting how defects in the machinery that performs intron removal and controls splice site selection contribute to cellular senescence and organismal aging. We discuss the functional association linking p53, IGF-1, SIRT1, and ING-1 splice variants with senescence and aging, and review a selection of splicing defects occurring in accelerated aging (progeria), vascular aging, and Alzheimer's disease. Overall, it is becoming increasingly clear that changes in the activity of splicing factors and in the production of key splice variants can impact cellular senescence and the aging phenotype.
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Affiliation(s)
- Mathieu Deschênes
- Department of Microbiology and Infectious DiseasesFaculty of Medicine and Health SciencesUniversité de SherbrookeSherbrookeQuebecJ1E 4K8Canada
| | - Benoit Chabot
- Department of Microbiology and Infectious DiseasesFaculty of Medicine and Health SciencesUniversité de SherbrookeSherbrookeQuebecJ1E 4K8Canada
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198
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Miragaia RJ, Teichmann SA, Hagai T. Single-cell insights into transcriptomic diversity in immunity. ACTA ACUST UNITED AC 2017. [DOI: 10.1016/j.coisb.2017.08.003] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
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199
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200
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Noise reduction as an emergent property of single-cell aging. Nat Commun 2017; 8:680. [PMID: 28947742 PMCID: PMC5613028 DOI: 10.1038/s41467-017-00752-9] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2017] [Accepted: 07/25/2017] [Indexed: 11/08/2022] Open
Abstract
Noise-induced heterogeneity in gene expression is an inherent reality for cells. However, it is not well understood how noise strength changes for a single gene while the host cell is aging. Using a state-of-the-art microfluidic platform, we measure noise dynamics in aging yeast cells by tracking the generation-specific activity of the canonical GAL1 promoter. We observe noise reduction during normal aging of a cell, followed by a short catastrophe phase in which noise increased. We hypothesize that aging-associated increases in chromatin state transitions are behind the observed noise reduction and a stochastic model provides quantitative support to the proposed mechanism. Noise trends measured from strains with altered GAL1 promoter dynamics (constitutively active, synthetic with nucleosome-disfavoring sequences, and in the absence of RPD3, a global remodeling regulator) lend further support to our hypothesis. Observing similar noise dynamics from a different promoter (HHF2) provides support to the generality of our findings. Gene expression is a noisy process, but it is not known how noise in gene expression changes during the aging of single cells. Here the authors show that noise decreases during normal aging, and provide support for aging-associated increases in chromatin state transitions governing noise reduction.
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