Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Wang, Junjun, Hu, Wei, Shen, Zhenyang, Liu, Teng, Dai, Weiming, Shen, Bo, Li, Xiaoman, Wu, Jingni, Lu, Lungen, Li, Shengli, Cai, Xiaobo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Society of Gene & Cell Therapy 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8626669/
https://www.ncbi.nlm.nih.gov/pubmed/34900395
http://dx.doi.org/10.1016/j.omtn.2021.11.008
_version_ 1784606700495437824
author Wang, Junjun
Hu, Wei
Shen, Zhenyang
Liu, Teng
Dai, Weiming
Shen, Bo
Li, Xiaoman
Wu, Jingni
Lu, Lungen
Li, Shengli
Cai, Xiaobo
author_facet Wang, Junjun
Hu, Wei
Shen, Zhenyang
Liu, Teng
Dai, Weiming
Shen, Bo
Li, Xiaoman
Wu, Jingni
Lu, Lungen
Li, Shengli
Cai, Xiaobo
author_sort Wang, Junjun
collection PubMed
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 Online
Article
Text
id pubmed-8626669
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher American Society of Gene & Cell Therapy
record_format MEDLINE/PubMed
spelling pubmed-86266692021-12-09 Dissecting the single-cell transcriptomeunderlying chronic liver injury Wang, Junjun Hu, Wei Shen, Zhenyang Liu, Teng Dai, Weiming Shen, Bo Li, Xiaoman Wu, Jingni Lu, Lungen Li, Shengli Cai, Xiaobo Mol Ther Nucleic Acids Original Article 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. American Society of Gene & Cell Therapy 2021-11-10 /pmc/articles/PMC8626669/ /pubmed/34900395 http://dx.doi.org/10.1016/j.omtn.2021.11.008 Text en © 2021 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Original Article
Wang, Junjun
Hu, Wei
Shen, Zhenyang
Liu, Teng
Dai, Weiming
Shen, Bo
Li, Xiaoman
Wu, Jingni
Lu, Lungen
Li, Shengli
Cai, Xiaobo
Dissecting the single-cell transcriptomeunderlying chronic liver injury
title 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_short Dissecting the single-cell transcriptomeunderlying chronic liver injury
title_sort dissecting the single-cell transcriptomeunderlying chronic liver injury
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8626669/
https://www.ncbi.nlm.nih.gov/pubmed/34900395
http://dx.doi.org/10.1016/j.omtn.2021.11.008
work_keys_str_mv AT wangjunjun dissectingthesinglecelltranscriptomeunderlyingchronicliverinjury
AT huwei dissectingthesinglecelltranscriptomeunderlyingchronicliverinjury
AT shenzhenyang dissectingthesinglecelltranscriptomeunderlyingchronicliverinjury
AT liuteng dissectingthesinglecelltranscriptomeunderlyingchronicliverinjury
AT daiweiming dissectingthesinglecelltranscriptomeunderlyingchronicliverinjury
AT shenbo dissectingthesinglecelltranscriptomeunderlyingchronicliverinjury
AT lixiaoman dissectingthesinglecelltranscriptomeunderlyingchronicliverinjury
AT wujingni dissectingthesinglecelltranscriptomeunderlyingchronicliverinjury
AT lulungen dissectingthesinglecelltranscriptomeunderlyingchronicliverinjury
AT lishengli dissectingthesinglecelltranscriptomeunderlyingchronicliverinjury
AT caixiaobo dissectingthesinglecelltranscriptomeunderlyingchronicliverinjury