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      Redefining the Foreign Antigen and Self-Driven Memory CD4 + T-Cell Compartments via Transcriptomic, Phenotypic, and Functional Analyses

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          Abstract

          Under steady-state conditions, conventional CD4 + T lymphocytes are classically divided into naïve (CD44 lo CD62L hi) and memory (CD44 hi CD62L lo) cell compartments. While the latter population is presumed to comprise a mixture of distinct subpopulations of explicit foreign antigen (Ag)-specific “authentic” memory and foreign Ag-independent memory-phenotype (MP) cells, phenotypic markers differentially expressed in these two cell types have yet to be identified. Moreover, while MP cells themselves have been previously described as heterogeneous, it is unknown whether they consist of distinct subsets defined by marker expression. In this study, we demonstrate using combined single-cell RNA sequencing and flow cytometric approaches that self-driven MP CD4 + T lymphocytes are divided into CD127 hi Sca1 lo, CD127 hi Sca1 hi, CD127 lo Sca1 hi, and CD127 lo Sca1 lo subpopulations that are Bcl2 lo, while foreign Ag-specific memory cells are CD127 hi Sca1 hi Bcl2 hi. We further show that among the four MP subsets, CD127 hi Sca1 hi lymphocytes represent the most mature and cell division-experienced subpopulation derived from peripheral naïve precursors. Finally, we provide evidence arguing that this MP subpopulation exerts the highest responsiveness to Th1-differentiating cytokines and can induce colitis. Together, our findings define MP CD4 + T lymphocytes as a unique, self-driven population consisting of distinct subsets that differ from conventional foreign Ag-specific memory cells in marker expression and establish functional relevance for the mature subset of CD127 hi Sca1 hi MP cells.

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          Comprehensive Integration of Single-Cell Data

          Single-cell transcriptomics has transformed our ability to characterize cell states, but deep biological understanding requires more than a taxonomic listing of clusters. As new methods arise to measure distinct cellular modalities, a key analytical challenge is to integrate these datasets to better understand cellular identity and function. Here, we develop a strategy to "anchor" diverse datasets together, enabling us to integrate single-cell measurements not only across scRNA-seq technologies, but also across different modalities. After demonstrating improvement over existing methods for integrating scRNA-seq data, we anchor scRNA-seq experiments with scATAC-seq to explore chromatin differences in closely related interneuron subsets and project protein expression measurements onto a bone marrow atlas to characterize lymphocyte populations. Lastly, we harmonize in situ gene expression and scRNA-seq datasets, allowing transcriptome-wide imputation of spatial gene expression patterns. Our work presents a strategy for the assembly of harmonized references and transfer of information across datasets.
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            Massively parallel digital transcriptional profiling of single cells

            Characterizing the transcriptome of individual cells is fundamental to understanding complex biological systems. We describe a droplet-based system that enables 3′ mRNA counting of tens of thousands of single cells per sample. Cell encapsulation, of up to 8 samples at a time, takes place in ∼6 min, with ∼50% cell capture efficiency. To demonstrate the system's technical performance, we collected transcriptome data from ∼250k single cells across 29 samples. We validated the sensitivity of the system and its ability to detect rare populations using cell lines and synthetic RNAs. We profiled 68k peripheral blood mononuclear cells to demonstrate the system's ability to characterize large immune populations. Finally, we used sequence variation in the transcriptome data to determine host and donor chimerism at single-cell resolution from bone marrow mononuclear cells isolated from transplant patients.
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              Cell cycle proteins as promising targets in cancer therapy

              Cancer is characterized by uncontrolled tumour cell proliferation resulting from aberrant activity of various cell cycle proteins. Therefore, cell cycle regulators are considered attractive targets in cancer therapy. Intriguingly, animal models demonstrate that some of these proteins are not essential for proliferation of non-transformed cells
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                Author and article information

                Contributors
                Journal
                Front Immunol
                Front Immunol
                Front. Immunol.
                Frontiers in Immunology
                Frontiers Media S.A.
                1664-3224
                30 May 2022
                2022
                : 13
                : 870542
                Affiliations
                [1] 1 Department of Microbiology and Immunology, Tohoku University Graduate School of Medicine , Sendai, Japan
                [2] 2 Immunobiology Section, Laboratory of Parasitic Diseases, National Institute of Allergy and Infectious Diseases, National Institutes of Health , Bethesda, MD, United States
                [3] 3 Laboratory of Immune Cell Biology, Center for Cancer Research, National Cancer Institute, National Institutes of Health , Bethesda, MD, United States
                [4] 4 David H. Smith Center for Vaccine Biology and Immunology, Department of Microbiology and Immunology, University of Rochester , Rochester, NY, United States
                [5] 5 Department of Integrative Biosciences and Biotechnology, Pohang University of Science and Technology , Pohang, South Korea
                [6] 6 Molecular and Cellular Immunoregulation Section, Laboratory of Immune System Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health , Bethesda, MD, United States
                [7] 7 Immunology Division, Garvan Institute of Medical Research , Darlinghurst, NSW, Australia
                [8] 8 St. Vincent’s Clinical School, University of New South Wales , Sydney, NSW, Australia
                Author notes

                Edited by: Francesca Di Rosa, Italian National Research Council, Italy

                Reviewed by: Jose Borghans, Utrecht University, Netherlands; Wolfgang Kastenmüller, Julius Maximilian University of Würzburg, Germany

                *Correspondence: Takeshi Kawabe, kawabet@ 123456med.tohoku.ac.jp ; Alan Sher, asher@ 123456niaid.nih.gov

                †These authors have contributed equally to this work

                This article was submitted to Immunological Memory, a section of the journal Frontiers in Immunology

                Article
                10.3389/fimmu.2022.870542
                9190281
                35707543
                b9cb7592-d953-4b77-a6a0-ea6e531f4414
                Copyright © 2022 Kawabe, Ciucci, Kim, Tayama, Kawajiri, Suzuki, Tanaka, Ishii, Jankovic, Zhu, Sprent, Bosselut and Sher

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 07 February 2022
                : 29 April 2022
                Page count
                Figures: 6, Tables: 0, Equations: 0, References: 61, Pages: 16, Words: 9486
                Categories
                Immunology
                Original Research

                Immunology
                cd4+ t lymphocytes,memory,homeostasis,innate immunity,phenotypic analysis
                Immunology
                cd4+ t lymphocytes, memory, homeostasis, innate immunity, phenotypic analysis

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