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通过推断人肺细胞类型特异性转录调控网络鉴定调控 SARS-CoV-2 嗜性因子表达的转录因子。

Identification of Transcription Factors Regulating SARS-CoV-2 Tropism Factor Expression by Inferring Cell-Type-Specific Transcriptional Regulatory Networks in Human Lungs.

机构信息

Electrical and Computer Engineering, North Carolina State University, Raleigh, NC 27695, USA.

Program in Genetics, Department of Plant and Microbial Biology, North Carolina State University, Raleigh, NC 27695, USA.

出版信息

Viruses. 2022 Apr 17;14(4):837. doi: 10.3390/v14040837.

DOI:10.3390/v14040837
PMID:35458567
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9026071/
Abstract

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the virus that caused the coronavirus disease 2019 (COVID-19) pandemic. Though previous studies have suggested that SARS-CoV-2 cellular tropism depends on the host-cell-expressed proteins, whether transcriptional regulation controls SARS-CoV-2 tropism factors in human lung cells remains unclear. In this study, we used computational approaches to identify transcription factors (TFs) regulating SARS-CoV-2 tropism for different types of lung cells. We constructed transcriptional regulatory networks (TRNs) controlling SARS-CoV-2 tropism factors for healthy donors and COVID-19 patients using lung single-cell RNA-sequencing (scRNA-seq) data. Through differential network analysis, we found that the altered regulatory role of TFs in the same cell types of healthy and SARS-CoV-2-infected networks may be partially responsible for differential tropism factor expression. In addition, we identified the TFs with high centralities from each cell type and proposed currently available drugs that target these TFs as potential candidates for the treatment of SARS-CoV-2 infection. Altogether, our work provides valuable cell-type-specific TRN models for understanding the transcriptional regulation and gene expression of SARS-CoV-2 tropism factors.

摘要

严重急性呼吸综合征冠状病毒 2(SARS-CoV-2)是引发 2019 年冠状病毒病(COVID-19)大流行的病毒。尽管先前的研究表明,SARS-CoV-2 的细胞嗜性取决于宿主细胞表达的蛋白,但转录调控是否控制人类肺细胞中的 SARS-CoV-2 嗜性因子尚不清楚。在这项研究中,我们使用计算方法来鉴定调节 SARS-CoV-2 对不同类型肺细胞嗜性的转录因子(TFs)。我们使用肺单细胞 RNA 测序(scRNA-seq)数据构建了用于健康供体和 COVID-19 患者的控制 SARS-CoV-2 嗜性因子的转录调控网络(TRNs)。通过差异网络分析,我们发现健康和 SARS-CoV-2 感染网络中同一细胞类型中 TF 的调节作用的改变可能部分导致了差异嗜性因子表达。此外,我们从每种细胞类型中鉴定出具有高中心度的 TF,并提出了针对这些 TF 的现有药物作为 SARS-CoV-2 感染治疗的潜在候选药物。总之,我们的工作为理解 SARS-CoV-2 嗜性因子的转录调控和基因表达提供了有价值的细胞类型特异性 TRN 模型。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9a7d/9026071/259326fd18c4/viruses-14-00837-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9a7d/9026071/8d149075012b/viruses-14-00837-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9a7d/9026071/410345633307/viruses-14-00837-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9a7d/9026071/ff917b72db46/viruses-14-00837-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9a7d/9026071/6b9b1e9a7204/viruses-14-00837-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9a7d/9026071/709dad49fe42/viruses-14-00837-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9a7d/9026071/259326fd18c4/viruses-14-00837-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9a7d/9026071/8d149075012b/viruses-14-00837-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9a7d/9026071/410345633307/viruses-14-00837-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9a7d/9026071/ff917b72db46/viruses-14-00837-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9a7d/9026071/6b9b1e9a7204/viruses-14-00837-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9a7d/9026071/709dad49fe42/viruses-14-00837-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9a7d/9026071/259326fd18c4/viruses-14-00837-g006.jpg

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