Single-cell RNA analysis reveals the potential risk of organ-specific cell types vulnerable to SARS-CoV-2 infections

Zilong Zhang; Feifei Cui; Chen Cao; Qingsuo Wang; Quan Zou

doi:10.1016/j.compbiomed.2021.105092

Single-cell RNA analysis reveals the potential risk of organ-specific cell types vulnerable to SARS-CoV-2 infections

Comput Biol Med. 2022 Jan:140:105092. doi: 10.1016/j.compbiomed.2021.105092. Epub 2021 Nov 29.

Authors

Zilong Zhang¹, Feifei Cui¹, Chen Cao², Qingsuo Wang³, Quan Zou⁴

Affiliations

¹ Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu, 610054, China; Yangtze Delta Region Institute (Quzhou), University of Electronic Science and Technology of China, Quzhou, 324000, China.
² Yangtze Delta Region Institute (Quzhou), University of Electronic Science and Technology of China, Quzhou, 324000, China.
³ Beidahuang Industry Group General Hospital, Harbin, 150001, China. Electronic address: 7200067@uestc.edu.cn.
⁴ Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu, 610054, China; Yangtze Delta Region Institute (Quzhou), University of Electronic Science and Technology of China, Quzhou, 324000, China. Electronic address: zouquan@nclab.net.

Abstract

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a global pandemic of coronavirus disease 2019 (COVID-19) since December 2019 that has led to more than 160 million confirmed cases, including 3.3 million deaths. To understand the mechanism by which SARS-CoV-2 invades human cells and reveal organ-specific susceptible cell types for COVID-19, we conducted comprehensive bioinformatic analysis using public single-cell RNA sequencing datasets. Utilizing the expression information of six confirmed COVID-19 receptors (ACE2, TMPRSS2, NRP1, AXL, FURIN and CTSL), we demonstrated that macrophages are the most likely cells that may be associated with SARS-CoV-2 pathogenesis in lung. Besides the widely reported 'chemokine storm', we identified ribosome related pathways that may also be potential therapeutic target for COVID-19 lung infection patients. Moreover, cell-cell communication analysis and trajectory analysis revealed that M1-like macrophages showed the highest relation to severe COVID-19 patients. And we also demonstrated that up-regulation of chemokine pathways generally lead to severe symptoms, while down-regulation of ribosome and RNA activity related pathways are more likely to be mild. Other organ-specific susceptible cell type analyses could also provide potential targets for COVID-19 therapy. This work can provide clues for understanding the pathogenesis of COVID-19 and contribute to understanding the mechanism by which SARS-CoV-2 invades human cells.

Keywords: Bioinformatics; COVID-19; Data mining; Macrophage; Single-cell RNA sequencing.