Single-cell RNA-seq reveals new types of human blood dendritic cells, monocytes, and progenitors.
Alexandra-Chloé Villani,Alexandra-Chloé Villani,Rahul Satija,Rahul Satija,Gary Reynolds,Siranush Sarkizova,Karthik Shekhar,James Fletcher,Morgane Griesbeck,Andrew Butler,Shiwei Zheng,Suzan Lazo,Laura Jardine,David Dixon,Emily Stephenson,Emil Nilsson,Ida Grundberg,David McDonald,Andrew Filby,Weibo Li,Weibo Li,Philip L. De Jager,Philip L. De Jager,Orit Rozenblatt-Rosen,Andrew A. Lane,Andrew A. Lane,Muzlifah Haniffa,Muzlifah Haniffa,Aviv Regev,Aviv Regev,Aviv Regev,Nir Hacohen,Nir Hacohen +32 more
TLDR
This refined analysis has identified, among others, a previously unknown dendritic cell population that potently activates T cells and reclassify pDCs as the originally described “natural interferon-producing cells (IPCs)” with weaker T cell proliferation induction ability.Abstract:
INTRODUCTION Dendritic cells (DCs) and monocytes consist of multiple specialized subtypes that play a central role in pathogen sensing, phagocytosis, and antigen presentation. However, their identities and interrelationships are not fully understood, as these populations have historically been defined by a combination of morphology, physical properties, localization, functions, developmental origins, and expression of a restricted set of surface markers. RATIONALE To overcome this inherently biased strategy for cell identification, we performed single-cell RNA sequencing of ~2400 cells isolated from healthy blood donors and enriched for HLA-DR + lineage − cells. This single-cell profiling strategy and unbiased genomic classification, together with follow-up profiling and functional and phenotypic characterization of prospectively isolated subsets, led us to identify and validate six DC subtypes and four monocyte subtypes, and thus revise the taxonomy of these cells. RESULTS Our study reveals: 1) A new DC subset, representing 2 to 3% of the DC populations across all 10 donors tested, characterized by the expression of AXL , SIGLEC1 , and SIGLEC6 antigens, named AS DCs. The AS DC population further divides into two populations captured in the traditionally defined plasmacytoid DC (pDC) and CD1C + conventional DC (cDC) gates. This split is further reflected through AS DC gene expression signatures spanning a spectrum between cDC-like and pDC-like gene sets. Although AS DCs share properties with pDCs, they more potently activate T cells. This discovery led us to reclassify pDCs as the originally described “natural interferon-producing cells (IPCs)” with weaker T cell proliferation induction ability. 2) A new subdivision within the CD1C + DC subset: one defined by a major histocompatibility complex class II–like gene set and one by a CD14 + monocyte–like prominent gene set. These CD1C + DC subsets, which can be enriched by combining CD1C with CD32B, CD36, and CD163 antigens, can both potently induce T cell proliferation. 3) The existence of a circulating and dividing cDC progenitor giving rise to CD1C + and CLEC9A + DCs through in vitro differentiation assays. This blood precursor is defined by the expression of CD100 + CD34 int and observed at a frequency of ~0.02% of the LIN – HLA-DR + fraction. 4) Two additional monocyte populations: one expressing classical monocyte genes and cytotoxic genes, and the other with unknown functions. 5) Evidence for a relationship between blastic plasmacytoid DC neoplasia (BPDCN) cells and healthy DCs. CONCLUSION Our revised taxonomy will enable more accurate functional and developmental analyses as well as immune monitoring in health and disease. The discovery of AS DCs within the traditionally defined pDC population explains many of the cDC properties previously assigned to pDCs, highlighting the need to revisit the definition of pDCs. Furthermore, the discovery of blood cDC progenitors represents a new therapeutic target readily accessible in the bloodstream for manipulation, as well as a new source for better in vitro DC generation. Although the current results focus on DCs and monocytes, a similar strategy can be applied to build a comprehensive human immune cell atlas.read more
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Integrating single-cell transcriptomic data across different conditions, technologies, and species.
TL;DR: An analytical strategy for integrating scRNA-seq data sets based on common sources of variation is introduced, enabling the identification of shared populations across data sets and downstream comparative analysis.
Journal ArticleDOI
Integrated analysis of multimodal single-cell data
Yuhan Hao,Stephanie Hao,Erica Andersen-Nissen,William M. Mauck,Shiwei Zheng,Andrew Butler,Maddie Jane Lee,Aaron J. Wilk,Charlotte A. Darby,Michael Zager,Paul Hoffman,Marlon Stoeckius,Efthymia Papalexi,Eleni P. Mimitou,Jaison Jain,Avi Srivastava,Tim Stuart,Lamar M. Fleming,Bertrand Z. Yeung,Angela J. Rogers,Juliana M. McElrath,Catherine A. Blish,Raphael Gottardo,Peter Smibert,Rahul Satija +24 more
TL;DR: Weighted-nearest neighbor analysis as mentioned in this paper is an unsupervised framework to learn the relative utility of each data type in each cell, enabling an integrative analysis of multiple modalities.
Journal ArticleDOI
Single-cell transcriptomics of 20 mouse organs creates a "Tabula Muris"
Overall coordination,Logistical coordination,Library preparation,Cell type annotation,Principal investigators +4 more
TL;DR: A compendium of single-cell transcriptomic data from the model organism Mus musculus that comprises more than 100,000 cells from 20 organs and tissues is presented, representing a new resource for cell biology and enabling the direct and controlled comparison of gene expression in cell types that are shared between tissues.
Journal ArticleDOI
B cells and tertiary lymphoid structures promote immunotherapy response
Beth A. Helmink,Sangeetha M. Reddy,Jianjun Gao,Shaojun Zhang,Rafet Basar,Rohit Thakur,Keren Yizhak,Moshe Sade-Feldman,Moshe Sade-Feldman,Jorge Blando,Guangchun Han,Vancheswaran Gopalakrishnan,Yuanxin Xi,Hao Zhao,Rodabe N. Amaria,Hussein Abdul-Hassan Tawbi,Alex P. Cogdill,Wenbin Liu,Valerie S. LeBleu,Fernanda G. Kugeratski,Sapna Pradyuman Patel,Michael A. Davies,Patrick Hwu,Jeffrey E. Lee,Jeffrey E. Gershenwald,Anthony Lucci,Reetakshi Arora,Scott E. Woodman,Emily Z. Keung,Pierre Olivier Gaudreau,Alexandre Reuben,Christine N. Spencer,Elizabeth M. Burton,Lauren E. Haydu,Alexander J. Lazar,Roberta Zapassodi,Courtney W. Hudgens,Deborah A. Ledesma,SuFey Ong,Michael Bailey,Sarah Warren,Disha Rao,Oscar Krijgsman,Elisa A. Rozeman,Daniel S. Peeper,Christian U. Blank,Ton N. Schumacher,Lisa H. Butterfield,Monika A. Zelazowska,Kevin M. McBride,Raghu Kalluri,James P. Allison,Florent Petitprez,Florent Petitprez,Wolf H. Fridman,Wolf H. Fridman,Catherine Sautès-Fridman,Catherine Sautès-Fridman,Nir Hacohen,Nir Hacohen,Katayoun Rezvani,Padmanee Sharma,Michael T. Tetzlaff,Linghua Wang,Jennifer A. Wargo +64 more
TL;DR: B cell markers were the most differentially expressed genes in the tumours of responders versus non-responders and insights are provided into the potential role of B cells and tertiary lymphoid structures in the response to ICB treatment, with implications for the development of biomarkers and therapeutic targets.
Journal ArticleDOI
A single-cell atlas of the peripheral immune response in patients with severe COVID-19.
Aaron J. Wilk,Arjun Rustagi,Nancy Q. Zhao,Jonasel Roque,Giovanny J Martínez-Colón,Julia L. McKechnie,Geoffrey T. Ivison,Thanmayi Ranganath,Rosemary Vergara,Taylor Mi Hollis,Laura J. Simpson,Philip M. Grant,Aruna Subramanian,Albert J. Rogers,Catherine A. Blish +14 more
TL;DR: Single-cell transcriptomic analysis identifies changes in peripheral immune cells in seven hospitalized patients with COVID-19, including HLA class II downregulation, a heterogeneous interferon-stimulated gene signature and low pro-inflammatory cytokine gene expression in monocytes and lymphocytes.
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