TY - JOUR
T1 - Gene signatures and potential therapeutic targets of Middle East respiratory syndrome coronavirus (MERS-CoV)-infected human lung adenocarcinoma epithelial cells
AU - Wu, Yen Hung
AU - Yeh, I. Jeng
AU - Phan, Nam Nhut
AU - Yen, Meng Chi
AU - Hung, Jui Hsiang
AU - Chiao, Chung Chieh
AU - Chen, Chien Fu
AU - Sun, Zhengda
AU - Hsu, Hui Ping
AU - Wang, Chih Yang
AU - Lai, Ming Derg
N1 - Funding Information:
The study was supported by the Ministry of Science and Technology (MOST) of Taiwan (grants MOST105-2325-B-006-003 to M.-D.L., MOST 109-2314-B-006-018-MY3 to H.-P.H., and MOST109-2320-B-038-009-MY2 to C.-Y.W.), the National Cheng Kung University Hospital (grant NCKUH-10601002 to M.-D.L. and NCKUH-11002013 to H.-P.H. ), Kaohsiung Medical University Hospital ( KMUH108-8R72 to M.-C.Y.), and Taipei Medical University (grant TMU-108-AE1-B16 to C.-Y.W.).
Funding Information:
Bioinformatics analyses and data mining were conducted at Taipei Medical University and the Bioinformatics Core at the National Cheng Kung University (Tainan, Taiwan). The authors give special thanks to EM695 from Scribendi ( https://www.scribendi.com/ ) for excellent Academic Proofreading during revising and to Mr. Dan Chamberlin from the Office of Research and Development at Taipei Medical University for the edited first draft. This research was supported in part by the Higher Education Sprout Project, Ministry of Education to the Headquarters of University Advancement at NCKU. Meanwhile, we are grateful to the National Center for High-performance Computing in Taiwan for computer time and facilities ( https://www.nchc.org.tw/ ).
Publisher Copyright:
© 2021
PY - 2021/10
Y1 - 2021/10
N2 - Background: Pathogenic coronaviruses include Middle East respiratory syndrome coronavirus (MERS-CoV), severe acute respiratory syndrome coronavirus (SARS-CoV), and SARS-CoV-2. These viruses have induced outbreaks worldwide, and there are currently no effective medications against them. Therefore, there is an urgent need to develop potential drugs against coronaviruses. Methods: High-throughput technology is widely used to explore differences in messenger (m)RNA and micro (mi)RNA expression profiles, especially to investigate protein–protein interactions and search for new therapeutic compounds. We integrated miRNA and mRNA expression profiles in MERS-CoV-infected cells and compared them to mock-infected controls from public databases. Results: Through the bioinformatics analysis, there were 251 upregulated genes and eight highly differentiated miRNAs that overlapped in the two datasets. External validation verified that these genes had high expression in MERS-CoV-infected cells, including RC3H1, NF-κB, CD69, TNFAIP3, LEAP-2, DUSP10, CREB5, CXCL2, etc. We revealed that immune, olfactory or sensory system-related, and signal-transduction networks were discovered from upregulated mRNAs in MERS-CoV-infected cells. In total, 115 genes were predicted to be related to miRNAs, with the intersection of upregulated mRNAs and miRNA-targeting prediction genes such as TCF4, NR3C1, and POU2F2. Through the Connectivity Map (CMap) platform, we suggested potential compounds to use against MERS-CoV infection, including diethylcarbamazine, harpagoside, bumetanide, enalapril, and valproic acid. Conclusions: The present study illustrates the crucial roles of miRNA-mRNA interacting networks in MERS-CoV-infected cells. The genes we identified are potential targets for treating MERS-CoV infection; however, these could possibly be extended to other coronavirus infections.
AB - Background: Pathogenic coronaviruses include Middle East respiratory syndrome coronavirus (MERS-CoV), severe acute respiratory syndrome coronavirus (SARS-CoV), and SARS-CoV-2. These viruses have induced outbreaks worldwide, and there are currently no effective medications against them. Therefore, there is an urgent need to develop potential drugs against coronaviruses. Methods: High-throughput technology is widely used to explore differences in messenger (m)RNA and micro (mi)RNA expression profiles, especially to investigate protein–protein interactions and search for new therapeutic compounds. We integrated miRNA and mRNA expression profiles in MERS-CoV-infected cells and compared them to mock-infected controls from public databases. Results: Through the bioinformatics analysis, there were 251 upregulated genes and eight highly differentiated miRNAs that overlapped in the two datasets. External validation verified that these genes had high expression in MERS-CoV-infected cells, including RC3H1, NF-κB, CD69, TNFAIP3, LEAP-2, DUSP10, CREB5, CXCL2, etc. We revealed that immune, olfactory or sensory system-related, and signal-transduction networks were discovered from upregulated mRNAs in MERS-CoV-infected cells. In total, 115 genes were predicted to be related to miRNAs, with the intersection of upregulated mRNAs and miRNA-targeting prediction genes such as TCF4, NR3C1, and POU2F2. Through the Connectivity Map (CMap) platform, we suggested potential compounds to use against MERS-CoV infection, including diethylcarbamazine, harpagoside, bumetanide, enalapril, and valproic acid. Conclusions: The present study illustrates the crucial roles of miRNA-mRNA interacting networks in MERS-CoV-infected cells. The genes we identified are potential targets for treating MERS-CoV infection; however, these could possibly be extended to other coronavirus infections.
KW - Bioinformatics
KW - Connectivity map
KW - Coronavirus
KW - Lung adenocarcinoma
KW - Middle East respiratory syndrome coronavirus (MERS-CoV)
KW - miRNA
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U2 - 10.1016/j.jmii.2021.03.007
DO - 10.1016/j.jmii.2021.03.007
M3 - Article
C2 - 34176764
AN - SCOPUS:85108677145
SN - 1684-1182
VL - 54
SP - 845
EP - 857
JO - Journal of Microbiology, Immunology and Infection
JF - Journal of Microbiology, Immunology and Infection
IS - 5
ER -