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      Characteristics of alveolar macrophages in bronchioalveolar lavage fluids from active tuberculosis patients identified by single-cell RNA sequencing

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          Abstract

          Tuberculosis (TB), is an infectious disease caused by Mycobacterium tuberculosis ( M. tuberculosis), and presents with high morbidity and mortality. Alveolar macrophages play an important role in TB pathogenesis although there is heterogeneity and functional plasticity. This study aimed to show the characteristics of alveolar macrophages from bronchioalveolar lavage fluid (BALF) in active TB patients. Single-cell RNA sequencing (scRNA-seq) was performed on BALF cells from three patients with active TB and additional scRNA-seq data from three healthy adults were established as controls. Transcriptional profiles were analyzed and compared by differential geneexpression and functional enrichment analysis. We applied pseudo-temporal trajectory analysis to investigate correlations and heterogeneity within alveolar macrophage subclusters. Alveolar macrophages from active TB patients at the single-cell resolution are described. We found that TB patients have higher cellular percentages in five macrophage subclusters. Alveolar macrophage subclusters with increased percentages were involved in inflammatory signaling pathways as well as the basic macrophage functions. The TB-increased alveolar macrophage subclusters might be derived from M1-like polarization state, before switching to an M2-like polarization state with the development of M. tuberculosis infection. Cell-cell communications of alveolar macrophages also increased and enhanced in active TB patients. Overall, our study demonstrated the characteristics of alveolar macrophages from BALF in active TB patients by using scRNA-seq.

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          Most cited references54

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          Cytoscape: a software environment for integrated models of biomolecular interaction networks.

          Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified conceptual framework. Although applicable to any system of molecular components and interactions, Cytoscape is most powerful when used in conjunction with large databases of protein-protein, protein-DNA, and genetic interactions that are increasingly available for humans and model organisms. Cytoscape's software Core provides basic functionality to layout and query the network; to visually integrate the network with expression profiles, phenotypes, and other molecular states; and to link the network to databases of functional annotations. The Core is extensible through a straightforward plug-in architecture, allowing rapid development of additional computational analyses and features. Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.
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            KEGG: kyoto encyclopedia of genes and genomes.

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            KEGG (Kyoto Encyclopedia of Genes and Genomes) is a knowledge base for systematic analysis of gene functions, linking genomic information with higher order functional information. The genomic information is stored in the GENES database, which is a collection of gene catalogs for all the completely sequenced genomes and some partial genomes with up-to-date annotation of gene functions. The higher order functional information is stored in the PATHWAY database, which contains graphical representations of cellular processes, such as metabolism, membrane transport, signal transduction and cell cycle. The PATHWAY database is supplemented by a set of ortholog group tables for the information about conserved subpathways (pathway motifs), which are often encoded by positionally coupled genes on the chromosome and which are especially useful in predicting gene functions. A third database in KEGG is LIGAND for the information about chemical compounds, enzyme molecules and enzymatic reactions. KEGG provides Java graphics tools for browsing genome maps, comparing two genome maps and manipulating expression maps, as well as computational tools for sequence comparison, graph comparison and path computation. The KEGG databases are daily updated and made freely available (http://www. genome.ad.jp/kegg/).
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                Author and article information

                Contributors
                Journal
                J Biomed Res
                J Biomed Res
                J Biomed Res
                Journal of Biomedical Research
                Editorial Department of Journal of Biomedical Research
                1674-8301
                2352-4685
                May 2022
                28 May 2022
                : 36
                : 3
                : 167-180
                Affiliations
                [1 ] Department of Respiratory and Critical Care Medicine, the First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China
                [2 ] Department of Tuberculosis, the Second Hospital of Nanjing, Nanjing, Jiangsu 210029, China
                [3 ] Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, Jiangsu 210029, China
                [4 ] Department of Bioinformatics, Nanjing Medical University, Nanjing, Jiangsu 210029, China
                [5 ] School of Biological Science and Medical Engineering, Southeast University, Nanjing, Jiangsu 210029, China
                Author notes
                Weiping Xie, Xiaoning Zeng, and Hong Wang. Department of Respiratory and Critical Care Medicine, the First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Road, Nanjing, Jiangsu 210029, China. Tel/Fax: +86-25-68306030/+86-25-68306030. E-mails: wpxie@ 123456njmu.edu.cn , zeng_xiao_ning@ 123456hotmail.com , and hongwang@ 123456njmu.edu.cn
                Article
                jbr-36-3-167
                10.7555/JBR.36.20220007
                9179115
                35635159
                93f62ccf-f922-4809-be41-c4e373ca4eaf
                © 2022 by the Journal of Biomedical Research.

                This is an open access article under the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited.

                History
                : 8 January 2022
                : 6 April 2022
                : 11 April 2022
                Categories
                Original Article

                tuberculosis,macrophage,bronchioalveolar lavage fluid,single-cell rna sequencing

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