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      Single-Cell RNA and ATAC Sequencing Reveal Hemodialysis-Related Immune Dysregulation of Circulating Immune Cell Subpopulations

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          Abstract

          Background

          An increased risk of infection, malignancy, and cardiovascular diseases in maintenance hemodialysis patients is associated with hemodialysis-related immunity disturbances. Although defects in T-lymphocyte-dependent immune responses and preactivation of antigen-presenting cells have been documented in hemodialysis patients, the effects of long-term hemodialysis on the transcriptional program and chromosomal accessibility of circulating immune cell subpopulations remain poorly defined.

          Methods

          We integrated single-cell RNA sequencing (scRNA-seq) and single-cell assay for transposase-accessible chromatin sequencing (scATAC-seq) to characterize the transcriptome profiles of peripheral mononuclear cells (PBMCs) from healthy controls and maintenance hemodialysis patients. Validation of differentially expressed genes in CD4+ T cells and monocytes were performed by magnetic bead separation and quantitative real-time PCR.

          Results

          We identified 16 and 15 PBMC subgroups in scRNA-seq and scATAC-seq datasets, respectively. Hemodialysis significantly suppressed the expression levels of T cell receptor (TCR) genes in CD4+ T cell subsets (e.g., TRAV4, CD45, CD3G, CD3D, CD3E) and major histocompatibility complex II (MHC-II) pathway-related genes in monocytes (HLA-DRB1, HLA-DQA2, HLA-DQA1, HLA-DPB1). Downstream pathways of TCR signaling, including PI3K-Akt-mTOR, MAPK, TNF, and NF-κB pathways, were also inhibited in CD4+ T cell subpopulations during the hemodialysis procedure. Hemodialysis altered cellular communication patterns between PBMC subgroups, particularly TGF-TGFBR, HVEM-BTLA, and IL16-CD4 signalings between CD4+ T cells and monocytes. Additionally, we found that hemodialysis inhibited the expression of AP-1 family transcription factors (JUN, JUND, FOS, FOSB) by interfering with the chromatin accessibility profile.

          Conclusions

          Our study provides a valuable framework for future investigations of hemodialysis-related immune dysregulation and identifies potential therapeutic targets for reconstituting the circulating immune system in maintenance hemodialysis patients.

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          Most cited references50

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          Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles

          Although genomewide RNA expression analysis has become a routine tool in biomedical research, extracting biological insight from such information remains a major challenge. Here, we describe a powerful analytical method called Gene Set Enrichment Analysis (GSEA) for interpreting gene expression data. The method derives its power by focusing on gene sets, that is, groups of genes that share common biological function, chromosomal location, or regulation. We demonstrate how GSEA yields insights into several cancer-related data sets, including leukemia and lung cancer. Notably, where single-gene analysis finds little similarity between two independent studies of patient survival in lung cancer, GSEA reveals many biological pathways in common. The GSEA method is embodied in a freely available software package, together with an initial database of 1,325 biologically defined gene sets.
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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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              Inference and analysis of cell-cell communication using CellChat

              Understanding global communications among cells requires accurate representation of cell-cell signaling links and effective systems-level analyses of those links. We construct a database of interactions among ligands, receptors and their cofactors that accurately represent known heteromeric molecular complexes. We then develop CellChat, a tool that is able to quantitatively infer and analyze intercellular communication networks from single-cell RNA-sequencing (scRNA-seq) data. CellChat predicts major signaling inputs and outputs for cells and how those cells and signals coordinate for functions using network analysis and pattern recognition approaches. Through manifold learning and quantitative contrasts, CellChat classifies signaling pathways and delineates conserved and context-specific pathways across different datasets. Applying CellChat to mouse and human skin datasets shows its ability to extract complex signaling patterns. Our versatile and easy-to-use toolkit CellChat and a web-based Explorer (http://www.cellchat.org/) will help discover novel intercellular communications and build cell-cell communication atlases in diverse tissues.
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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
                26 May 2022
                2022
                : 13
                : 878226
                Affiliations
                [1] 1 The Second Clinical Medical College of Jinan University, Shenzhen People’s Hospital , Shenzhen, China
                [2] 2 Institute of Nephrology and Blood Purification, The First Affiliated Hospital of Jinan University, Jinan University , Guangzhou, China
                [3] 3 College of Natural Science, University of Texas at Austin , Austin, TX, United States
                Author notes

                Edited by: Elodie Segura, Institut Curie, France

                Reviewed by: Yoke Seng Lee, Brigham and Women’s Hospital and Harvard Medical School, United States; Damien Chaussabel, Jackson Laboratory for Genomic Medicine, United States

                *Correspondence: Yong Dai, daiyong22@ 123456aliyun.com ; Donge Tang, donge66@ 123456126.com ; Fanna Liu, lfn-au@ 123456126.com

                †These authors have contributed equally to this work

                This article was submitted to T Cell Biology, a section of the journal Frontiers in Immunology

                Article
                10.3389/fimmu.2022.878226
                9205630
                35720370
                5e9f98e5-6581-49ea-ba53-0cba363cad40
                Copyright © 2022 Wu, Dong, Yu, Wang, Dai, Zhang, Hu, Yin, Tang, Liu and Dai

                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
                : 23 February 2022
                : 27 April 2022
                Page count
                Figures: 6, Tables: 0, Equations: 0, References: 50, Pages: 14, Words: 6677
                Categories
                Immunology
                Original Research

                Immunology
                maintenance hemodialysis,single-cell rna sequencing,single-cell assaying transposase accessible chromatin sequencing,t cell receptor,antigen presentation,immune pathways

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