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      Betacoronaviruses SARS-CoV-2 and HCoV-OC43 infections in IGROV-1 cell line require aryl hydrocarbon receptor

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          ABSTRACT

          The emergence of novel betacoronaviruses has posed significant financial and human health burdens, necessitating the development of appropriate tools to combat future outbreaks. In this study, we have characterized a human cell line, IGROV-1, as a robust tool to detect, propagate, and titrate betacoronaviruses SARS-CoV-2 and HCoV-OC43. IGROV-1 cells can be used for serological assays, antiviral drug testing, and isolating SARS-CoV-2 variants from patient samples. Using time-course transcriptomics, we confirmed that IGROV-1 cells exhibit a robust innate immune response upon SARS-CoV-2 infection, recapitulating the response previously observed in primary human nasal epithelial cells. We performed genome-wide CRISPR knockout genetic screens in IGROV-1 cells and identified Aryl hydrocarbon receptor (AHR) as a critical host dependency factor for both SARS-CoV-2 and HCoV-OC43. Using DiMNF, a small molecule inhibitor of AHR, we observed that the drug selectively inhibits HCoV-OC43 infection but not SARS-CoV-2. Transcriptomic analysis in primary normal human bronchial epithelial cells revealed that DiMNF blocks HCoV-OC43 infection via basal activation of innate immune responses. Our findings highlight the potential of IGROV-1 cells as a valuable diagnostic and research tool to combat betacoronavirus diseases.

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          Most cited references60

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          Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

          In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
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            STAR: ultrafast universal RNA-seq aligner.

            Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases. To align our large (>80 billon reads) ENCODE Transcriptome RNA-seq dataset, we developed the Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. STAR outperforms other aligners by a factor of >50 in mapping speed, aligning to the human genome 550 million 2 × 76 bp paired-end reads per hour on a modest 12-core server, while at the same time improving alignment sensitivity and precision. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences. Using Roche 454 sequencing of reverse transcription polymerase chain reaction amplicons, we experimentally validated 1960 novel intergenic splice junctions with an 80-90% success rate, corroborating the high precision of the STAR mapping strategy. STAR is implemented as a standalone C++ code. STAR is free open source software distributed under GPLv3 license and can be downloaded from http://code.google.com/p/rna-star/.
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              A Novel Coronavirus from Patients with Pneumonia in China, 2019

              Summary In December 2019, a cluster of patients with pneumonia of unknown cause was linked to a seafood wholesale market in Wuhan, China. A previously unknown betacoronavirus was discovered through the use of unbiased sequencing in samples from patients with pneumonia. Human airway epithelial cells were used to isolate a novel coronavirus, named 2019-nCoV, which formed a clade within the subgenus sarbecovirus, Orthocoronavirinae subfamily. Different from both MERS-CoV and SARS-CoV, 2019-nCoV is the seventh member of the family of coronaviruses that infect humans. Enhanced surveillance and further investigation are ongoing. (Funded by the National Key Research and Development Program of China and the National Major Project for Control and Prevention of Infectious Disease in China.)
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                Author and article information

                Journal
                Emerg Microbes Infect
                Emerg Microbes Infect
                Emerging Microbes & Infections
                Taylor & Francis
                2222-1751
                6 September 2023
                2023
                6 September 2023
                : 12
                : 2
                : 2256416
                Affiliations
                [a ]Program in Emerging Infectious Diseases, Duke-NUS Medical School , Singapore, Singapore
                [b ]Victorian Infectious Diseases Reference Laboratory, The Peter Doherty Institute for Infection and Immunity , Melbourne, Australia
                [c ]Centre for Computational Biology, Duke-NUS Medical School , Singapore, Singapore
                [d ]Yunnan Key Laboratory of Biodiversity Information, Kunming Institute of Zoology, Chinese Academy of Sciences , Kunming, People’s Republic of China
                [e ]Immune Health Research Program, Hunter Medical Research Institute , New Lambton Heights, Australia
                [f ]College of Health, Medicine and Wellbeing, The University of Newcastle , Callaghan, Australia
                [g ]Program in Cancer and Stem Cell Biology, Duke-NUS Medical School , Singapore, Singapore
                [h ]Program in Cardiovascular and Metabolic Disorders, Duke-NUS Medical School , Singapore, Singapore
                [i ]Department of Microbiology and Immunology, The University of Melbourne, The Peter Doherty Institute for Infection and Immunity , Melbourne, Australia
                [j ]Infectious Diseases Translation Research Program, Department of Microbiology and Immunology, Yong Loo Lin School of Medicine, National University of Singapore , Singapore, Singapore
                [k ]Infectious Diseases Labs, Agency for Science, Technology and Research (A*STAR) , Singapore, Singapore
                Author notes
                [CONTACT ] Yaw Shin Ooi yawshin.ooi@ 123456duke-nus.edu.sg Program in Emerging Infectious Diseases, Duke-NUS Medical School , Singapore 169857, Singapore; Infectious Diseases Labs, Agency for Science, Technology and Research (A*STAR) , Singapore 138648, Singapore
                Lin-Fa Wang linfa.wang@ 123456duke-nus.edu.sg Program in Emerging Infectious Diseases, Duke-NUS Medical School , Singapore 169857, Singapore; Department of Microbiology and Immunology, The University of Melbourne, The Peter Doherty Institute for Infection and Immunity , Melbourne 3000, Australia
                Chee Wah Tan cheewah.tan@ 123456duke-nus.edu.sg Program in Emerging Infectious Diseases, Duke-NUS Medical School , Singapore 169857, Singapore; Singapore Infectious Diseases Translation Research Program, Department of Microbiology and Immunology, Yong Loo Lin School of Medicine , National University of Singapore , Singapore 119228, Singapore
                Gavin J. D. Smith gavin.smith@ 123456duke-nus.edu.sg Program in Emerging Infectious Diseases, Duke-NUS Medical School , Singapore 169857, Singapore
                [*]

                Equal contributions.

                Supplemental data for this article can be accessed online at https://doi.org/10.1080/22221751.2023.2256416.

                Author information
                https://orcid.org/0000-0002-7346-803X
                https://orcid.org/0000-0002-4526-470X
                https://orcid.org/0000-0003-2636-2512
                https://orcid.org/0000-0003-4791-5024
                https://orcid.org/0000-0001-5031-468X
                https://orcid.org/0000-0003-2752-0535
                https://orcid.org/0000-0001-9014-1365
                Article
                2256416
                10.1080/22221751.2023.2256416
                10512916
                37672505
                e2d82511-66bd-4d2d-9464-730b0c026683
                © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group, on behalf of Shanghai Shangyixun Cultural Communication Co., Ltd

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent.

                History
                Page count
                Figures: 6, Tables: 1, Equations: 0, References: 60, Pages: 18
                Categories
                Coronaviruses
                Research Article

                igrov-1,covid-19,betacoronavirus,sars-cov-2,hcov-oc43,genome-scale crispr screening,ahr,dimnf

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