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      High-sensitivity profiling of SARS-CoV-2 noncoding region–host protein interactome reveals the potential regulatory role of negative-sense viral RNA

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          ABSTRACT

          A deep understanding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)–host interactions is crucial to developing effective therapeutics and addressing the threat of emerging coronaviruses. The role of noncoding regions of viral RNA (ncrRNAs) has yet to be systematically scrutinized. We developed a method using MS2 affinity purification coupled with liquid chromatography-mass spectrometry and designed a diverse set of bait ncrRNAs to systematically map the interactome of SARS-CoV-2 ncrRNA in Calu-3, Huh7, and HEK293T cells. Integration of the results defined the core ncrRNA–host protein interactomes among cell lines. The 5′ UTR interactome is enriched with proteins in the small nuclear ribonucleoproteins family and is a target for the regulation of viral replication and transcription. The 3′ UTR interactome is enriched with proteins involved in the stress granules and heterogeneous nuclear ribonucleoproteins family. Intriguingly, compared with the positive-sense ncrRNAs, the negative-sense ncrRNAs, especially the negative-sense of 3′ UTR, interacted with a large array of host proteins across all cell lines. These proteins are involved in the regulation of the viral production process, host cell apoptosis, and immune response. Taken together, our study depicts the comprehensive landscape of the SARS-CoV-2 ncrRNA–host protein interactome and unveils the potential regulatory role of the negative-sense ncrRNAs, providing a new perspective on virus–host interactions and the design of future therapeutics. Given the highly conserved nature of UTRs in positive-strand viruses, the regulatory role of negative-sense ncrRNAs should not be exclusive to SARS-CoV-2.

          IMPORTANCE

          Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes COVID-19, a pandemic affecting millions of lives. During replication and transcription, noncoding regions of the viral RNA (ncrRNAs) may play an important role in the virus–host interactions. Understanding which and how these ncrRNAs interact with host proteins is crucial for understanding the mechanism of SARS-CoV-2 pathogenesis. We developed the MS2 affinity purification coupled with liquid chromatography-mass spectrometry method and designed a diverse set of ncrRNAs to identify the SARS-CoV-2 ncrRNA interactome comprehensively in different cell lines and found that the 5′ UTR binds to proteins involved in U1 small nuclear ribonucleoprotein, while the 3′ UTR interacts with proteins involved in stress granules and the heterogeneous nuclear ribonucleoprotein family. Interestingly, negative-sense ncrRNAs showed interactions with a large number of diverse host proteins, indicating a crucial role in infection. The results demonstrate that ncrRNAs could serve diverse regulatory functions.

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          Clinical Characteristics of Coronavirus Disease 2019 in China

          Abstract Background Since December 2019, when coronavirus disease 2019 (Covid-19) emerged in Wuhan city and rapidly spread throughout China, data have been needed on the clinical characteristics of the affected patients. Methods We extracted data regarding 1099 patients with laboratory-confirmed Covid-19 from 552 hospitals in 30 provinces, autonomous regions, and municipalities in mainland China through January 29, 2020. The primary composite end point was admission to an intensive care unit (ICU), the use of mechanical ventilation, or death. Results The median age of the patients was 47 years; 41.9% of the patients were female. The primary composite end point occurred in 67 patients (6.1%), including 5.0% who were admitted to the ICU, 2.3% who underwent invasive mechanical ventilation, and 1.4% who died. Only 1.9% of the patients had a history of direct contact with wildlife. Among nonresidents of Wuhan, 72.3% had contact with residents of Wuhan, including 31.3% who had visited the city. The most common symptoms were fever (43.8% on admission and 88.7% during hospitalization) and cough (67.8%). Diarrhea was uncommon (3.8%). The median incubation period was 4 days (interquartile range, 2 to 7). On admission, ground-glass opacity was the most common radiologic finding on chest computed tomography (CT) (56.4%). No radiographic or CT abnormality was found in 157 of 877 patients (17.9%) with nonsevere disease and in 5 of 173 patients (2.9%) with severe disease. Lymphocytopenia was present in 83.2% of the patients on admission. Conclusions During the first 2 months of the current outbreak, Covid-19 spread rapidly throughout China and caused varying degrees of illness. Patients often presented without fever, and many did not have abnormal radiologic findings. (Funded by the National Health Commission of China and others.)
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            Cytoscape: a software environment for integrated models of biomolecular interaction networks.

            Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified conceptual framework. Although applicable to any system of molecular components and interactions, Cytoscape is most powerful when used in conjunction with large databases of protein-protein, protein-DNA, and genetic interactions that are increasingly available for humans and model organisms. Cytoscape's software Core provides basic functionality to layout and query the network; to visually integrate the network with expression profiles, phenotypes, and other molecular states; and to link the network to databases of functional annotations. The Core is extensible through a straightforward plug-in architecture, allowing rapid development of additional computational analyses and features. Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.
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              clusterProfiler: an R package for comparing biological themes among gene clusters.

              Increasing quantitative data generated from transcriptomics and proteomics require integrative strategies for analysis. Here, we present an R package, clusterProfiler that automates the process of biological-term classification and the enrichment analysis of gene clusters. The analysis module and visualization module were combined into a reusable workflow. Currently, clusterProfiler supports three species, including humans, mice, and yeast. Methods provided in this package can be easily extended to other species and ontologies. The clusterProfiler package is released under Artistic-2.0 License within Bioconductor project. The source code and vignette are freely available at http://bioconductor.org/packages/release/bioc/html/clusterProfiler.html.
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                Author and article information

                Contributors
                Role: Data curationRole: Project administrationRole: VisualizationRole: Writing – original draftRole: Writing – review and editing
                Role: InvestigationRole: Project administrationRole: SupervisionRole: ValidationRole: Writing – review and editing
                Role: Investigation
                Role: Investigation
                Role: Investigation
                Role: Investigation
                Role: Supervision
                Role: Supervision
                Role: SupervisionRole: Writing – review and editing
                Role: Supervision
                Role: Editor
                Journal
                mSystems
                mSystems
                mSystems
                mSystems
                American Society for Microbiology (1752 N St., N.W., Washington, DC )
                2379-5077
                Jul-Aug 2023
                14 June 2023
                14 June 2023
                : 8
                : 4
                : e00135-23
                Affiliations
                [1 ] Life Sciences Institute, Zhejiang University; , Hangzhou, Zhejiang, China
                [2 ] Zhejiang Provincial Key Laboratory of Cancer Molecular Cell Biology, Life Sciences Institute, Zhejiang University; , Hangzhou, Zhejiang, China
                [3 ] The MOE Key Laboratory of Biosystems Homeostasis & Protection and Innovation Center for Cell Signaling Network, Life Sciences Institute, Zhejiang University; , Hangzhou, Zhejiang, China
                Princeton University; , Princeton, New Jersey, USA
                Author notes
                Address correspondence to Mu Xiao, mu_xiao@ 123456zju.edu.cn
                Address correspondence to Luqian Zheng, luqianz@ 123456zju.edu.cn
                Address correspondence to Bing Yang, bingyang@ 123456zju.edu.cn
                Address correspondence to Aiming Ren, aimingren@ 123456zju.edu.cn
                Address correspondence to Chao Jiang, jiang_chao@ 123456zju.edu.cn
                Address correspondence to Xin-Hua Feng, fenglab@ 123456zju.edu.cn

                Liuyiqi Jiang, Mu Xiao, Qing-Qing Liao, and Luqian Zheng contributed equally to this article. The order of names was determined based on the contributions to the writing of the manuscript.

                The authors declare no conflict of interest.

                Article
                00135-23 msystems.00135-23
                10.1128/msystems.00135-23
                10469612
                37314180
                c6ad833a-c4d4-4dfb-b3f0-d72ea8d648de
                Copyright © 2023 Jiang et al.

                This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license.

                History
                : 07 February 2023
                : 11 April 2023
                Page count
                supplementary-material: 9, authors: 10, Figures: 6, References: 95, Pages: 24, Words: 14093
                Categories
                Resource Report
                genomics-and-proteomics, Genomics and Proteomics
                Custom metadata
                July/August 2023

                sars-cov-2,noncoding region rna,ncrrna-host protein interactions

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