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      Research progress of single-cell sequencing in tuberculosis

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          Abstract

          Tuberculosis is a major infectious disease caused by Mycobacterium tuberculosis infection. The pathogenesis and immune mechanism of tuberculosis are not clear, and it is urgent to find new drugs, diagnosis, and treatment targets. A useful tool in the quest to reveal the enigmas related to Mycobacterium tuberculosis infection and disease is the single-cell sequencing technique. By clarifying cell heterogeneity, identifying pathogenic cell groups, and finding key gene targets, the map at the single cell level enables people to better understand the cell diversity of complex organisms and the immune state of hosts during infection. Here, we briefly reviewed the development of single-cell sequencing, and emphasized the different applications and limitations of various technologies. Single-cell sequencing has been widely used in the study of the pathogenesis and immune response of tuberculosis. We review these works summarizing the most influential findings. Combined with the multi-molecular level and multi-dimensional analysis, we aim to deeply understand the blank and potential future development of the research on Mycobacterium tuberculosis infection using single-cell sequencing technology.

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          Most cited references131

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          Integrating single-cell transcriptomic data across different conditions, technologies, and species

          Computational single-cell RNA-seq (scRNA-seq) methods have been successfully applied to experiments representing a single condition, technology, or species to discover and define cellular phenotypes. However, identifying subpopulations of cells that are present across multiple data sets remains challenging. Here, we introduce an analytical strategy for integrating scRNA-seq data sets based on common sources of variation, enabling the identification of shared populations across data sets and downstream comparative analysis. We apply this approach, implemented in our R toolkit Seurat (http://satijalab.org/seurat/), to align scRNA-seq data sets of peripheral blood mononuclear cells under resting and stimulated conditions, hematopoietic progenitors sequenced using two profiling technologies, and pancreatic cell 'atlases' generated from human and mouse islets. In each case, we learn distinct or transitional cell states jointly across data sets, while boosting statistical power through integrated analysis. Our approach facilitates general comparisons of scRNA-seq data sets, potentially deepening our understanding of how distinct cell states respond to perturbation, disease, and evolution.
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            Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets.

            Cells, the basic units of biological structure and function, vary broadly in type and state. Single-cell genomics can characterize cell identity and function, but limitations of ease and scale have prevented its broad application. Here we describe Drop-seq, a strategy for quickly profiling thousands of individual cells by separating them into nanoliter-sized aqueous droplets, associating a different barcode with each cell's RNAs, and sequencing them all together. Drop-seq analyzes mRNA transcripts from thousands of individual cells simultaneously while remembering transcripts' cell of origin. We analyzed transcriptomes from 44,808 mouse retinal cells and identified 39 transcriptionally distinct cell populations, creating a molecular atlas of gene expression for known retinal cell classes and novel candidate cell subtypes. Drop-seq will accelerate biological discovery by enabling routine transcriptional profiling at single-cell resolution. VIDEO ABSTRACT.
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              Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position.

              We describe an assay for transposase-accessible chromatin using sequencing (ATAC-seq), based on direct in vitro transposition of sequencing adaptors into native chromatin, as a rapid and sensitive method for integrative epigenomic analysis. ATAC-seq captures open chromatin sites using a simple two-step protocol with 500-50,000 cells and reveals the interplay between genomic locations of open chromatin, DNA-binding proteins, individual nucleosomes and chromatin compaction at nucleotide resolution. We discovered classes of DNA-binding factors that strictly avoided, could tolerate or tended to overlap with nucleosomes. Using ATAC-seq maps of human CD4(+) T cells from a proband obtained on consecutive days, we demonstrated the feasibility of analyzing an individual's epigenome on a timescale compatible with clinical decision-making.
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                Author and article information

                Contributors
                URI : https://loop.frontiersin.org/people/2406443Role: Role: Role:
                URI : https://loop.frontiersin.org/people/2399562Role: Role: Role:
                URI : https://loop.frontiersin.org/people/1331672Role: Role:
                Role: Role:
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                URI : https://loop.frontiersin.org/people/1776003Role: Role:
                URI : https://loop.frontiersin.org/people/807658Role: Role:
                Journal
                Front Immunol
                Front Immunol
                Front. Immunol.
                Frontiers in Immunology
                Frontiers Media S.A.
                1664-3224
                13 October 2023
                2023
                : 14
                : 1276194
                Affiliations
                [1] Key Laboratory of Pathobiology Ministry of Education, College of Basic Medical Sciences/China-Japan Union Hospital of Jilin University, Jilin University , Changchun, China
                Author notes

                Edited by: Mohlopheni Jackson Marakalala, Africa Health Research Institute (AHRI), South Africa

                Reviewed by: Quan Zou, University of Electronic Science and Technology of China, China; Thabo Mpotje, Africa Health Research Institute (AHRI), South Africa

                *Correspondence: Guoqing Wang, qing@ 123456jlu.edu.cn ; Jingwei Shi, shijingwei@ 123456jlu.edu.cn

                †These authors have contributed equally to this work

                Article
                10.3389/fimmu.2023.1276194
                10611525
                37901241
                e0765055-ba5e-49db-91a7-bc73b013107f
                Copyright © 2023 Pan, Chang, Zhang, Dong, Zhao, Shi and Wang

                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
                : 14 August 2023
                : 29 September 2023
                Page count
                Figures: 3, Tables: 1, Equations: 0, References: 131, Pages: 13, Words: 6487
                Funding
                Funded by: National Natural Science Foundation of China , doi 10.13039/501100001809;
                Funded by: National Natural Science Foundation of China , doi 10.13039/501100001809;
                The authors declare financial support was received for the research, authorship, and/or publication of this article. This work was supported by the National Natural Science Foundation of China [82072330, 32271511]; Jilin University China-Japan Union Hospital-Basic Medical College Joint Project [KYXZ2022JC02] and International Joint Research Center for Pathogen and Infection Informatics, Jilin Province [20210504004GH].
                Categories
                Immunology
                Review
                Custom metadata
                Microbial Immunology

                Immunology
                single-cell sequencing,scrna-seq,tuberculosis,mycobacterium tuberculosis,host-pathogen interaction

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