Dissecting the single-cell transcriptomeunderlying chronic liver injury

Chronic liver disease (CLD) is currently a major health problem worldwide, which is accompanied by chronic liver injury and lack of clinically effective treatment; however, systematic characterization of chronic liver injury procedures at single-cell resolution is lacking. In the present study, we e...

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Autores principales:	Junjun Wang, Wei Hu, Zhenyang Shen, Teng Liu, Weiming Dai, Bo Shen, Xiaoman Li, Jingni Wu, Lungen Lu, Shengli Li, Xiaobo Cai
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	chronic liver injury single-cell transcriptome macrophage cell-cell communications Therapeutics. Pharmacology RM1-950
Acceso en línea:	https://doaj.org/article/dbff1da3b28a49448aee398496663a23
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spelling	oai:doaj.org-article:dbff1da3b28a49448aee398496663a232021-11-24T04:28:42ZDissecting the single-cell transcriptomeunderlying chronic liver injury2162-253110.1016/j.omtn.2021.11.008https://doaj.org/article/dbff1da3b28a49448aee398496663a232021-12-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S2162253121002833https://doaj.org/toc/2162-2531Chronic liver disease (CLD) is currently a major health problem worldwide, which is accompanied by chronic liver injury and lack of clinically effective treatment; however, systematic characterization of chronic liver injury procedures at single-cell resolution is lacking. In the present study, we established chronic liver injury mouse models and conducted single-cell RNA sequencing (scRNA-seq), including choline-deficient, ethionine-supplemented (CDE) and 3,5-diethoxycarbonyl 1,4-dihydrocollidinen (DDC) mouse models. We captured in total 16,389 high-quality cells and identified 12 main cell types in scRNA-seq data. Macrophages and endothelial cells are the largest cell populations in our dataset. Transcriptional trajectory analysis revealed different expression patterns of cells between CDE and DDC models and identified potential liver injury markers, such as Ets1, Gda, Itgam, and Sparc. Differential analysis identified 25 and 152 differentially expressed genes in CDE and DDC macrophages, respectively. In addition, 413 genes were detected to exclusively express in specific pseudotime states of macrophages. These genes were found to participate in immune-related biological processes. Further cell-cell communication analysis found extensive receding of cell-cell interactions between different cell types in the liver injury process, especially in the DDC model. Our study characterized the single-cell transcriptional landscape in the process of chronic liver injury, promoting the understanding of the underlying molecular mechanisms and providing candidate clinical strategy for effective intervention of chronic liver diseases.Junjun WangWei HuZhenyang ShenTeng LiuWeiming DaiBo ShenXiaoman LiJingni WuLungen LuShengli LiXiaobo CaiElsevierarticlechronic liver injurysingle-cell transcriptomemacrophagecell-cell communicationsTherapeutics. PharmacologyRM1-950ENMolecular Therapy: Nucleic Acids, Vol 26, Iss , Pp 1364-1373 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	chronic liver injury single-cell transcriptome macrophage cell-cell communications Therapeutics. Pharmacology RM1-950
spellingShingle	chronic liver injury single-cell transcriptome macrophage cell-cell communications Therapeutics. Pharmacology RM1-950 Junjun Wang Wei Hu Zhenyang Shen Teng Liu Weiming Dai Bo Shen Xiaoman Li Jingni Wu Lungen Lu Shengli Li Xiaobo Cai Dissecting the single-cell transcriptomeunderlying chronic liver injury
description	Chronic liver disease (CLD) is currently a major health problem worldwide, which is accompanied by chronic liver injury and lack of clinically effective treatment; however, systematic characterization of chronic liver injury procedures at single-cell resolution is lacking. In the present study, we established chronic liver injury mouse models and conducted single-cell RNA sequencing (scRNA-seq), including choline-deficient, ethionine-supplemented (CDE) and 3,5-diethoxycarbonyl 1,4-dihydrocollidinen (DDC) mouse models. We captured in total 16,389 high-quality cells and identified 12 main cell types in scRNA-seq data. Macrophages and endothelial cells are the largest cell populations in our dataset. Transcriptional trajectory analysis revealed different expression patterns of cells between CDE and DDC models and identified potential liver injury markers, such as Ets1, Gda, Itgam, and Sparc. Differential analysis identified 25 and 152 differentially expressed genes in CDE and DDC macrophages, respectively. In addition, 413 genes were detected to exclusively express in specific pseudotime states of macrophages. These genes were found to participate in immune-related biological processes. Further cell-cell communication analysis found extensive receding of cell-cell interactions between different cell types in the liver injury process, especially in the DDC model. Our study characterized the single-cell transcriptional landscape in the process of chronic liver injury, promoting the understanding of the underlying molecular mechanisms and providing candidate clinical strategy for effective intervention of chronic liver diseases.
format	article
author	Junjun Wang Wei Hu Zhenyang Shen Teng Liu Weiming Dai Bo Shen Xiaoman Li Jingni Wu Lungen Lu Shengli Li Xiaobo Cai
author_facet	Junjun Wang Wei Hu Zhenyang Shen Teng Liu Weiming Dai Bo Shen Xiaoman Li Jingni Wu Lungen Lu Shengli Li Xiaobo Cai
author_sort	Junjun Wang
title	Dissecting the single-cell transcriptomeunderlying chronic liver injury
title_short	Dissecting the single-cell transcriptomeunderlying chronic liver injury
title_full	Dissecting the single-cell transcriptomeunderlying chronic liver injury
title_fullStr	Dissecting the single-cell transcriptomeunderlying chronic liver injury
title_full_unstemmed	Dissecting the single-cell transcriptomeunderlying chronic liver injury
title_sort	dissecting the single-cell transcriptomeunderlying chronic liver injury
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/dbff1da3b28a49448aee398496663a23
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_version_	1718416006352732160

Dissecting the single-cell transcriptomeunderlying chronic liver injury

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