{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,16]],"date-time":"2026-03-16T02:57:18Z","timestamp":1773629838606,"version":"3.50.1"},"update-to":[{"DOI":"10.12688\/f1000research.25390.1","type":"new_version","label":"New version","source":"publisher","updated":{"date-parts":[[2021,1,6]],"date-time":"2021-01-06T00:00:00Z","timestamp":1609891200000}}],"reference-count":73,"publisher":"F1000 Research Ltd","license":[{"start":{"date-parts":[[2021,1,6]],"date-time":"2021-01-06T00:00:00Z","timestamp":1609891200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000196","name":"Canada Foundation for Innovation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100000196","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100013020","name":"Compute Canada","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100013020","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001804","name":"Canada Research Chairs","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001804","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["f1000research.com"],"crossmark-restriction":false},"short-container-title":["F1000Res"],"abstract":"<ns3:p>\n                    <ns3:bold>Background:<\/ns3:bold>\n                    Certain riboviruses can cause severe pulmonary complications leading to death in some infected patients. We propose that DNA damage induced-apoptosis accelerates viral release, triggered by depletion of host RNA binding proteins (RBPs) from nuclear RNA bound to replicating viral sequences.\n                  <\/ns3:p>\n                  <ns3:p>\n                    <ns3:bold>Methods:<\/ns3:bold>\n                    Information theory-based analysis of interactions between RBPs and individual sequences in the Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS-CoV-2), Influenza A (H3N2), HIV-1, and Dengue genomes identifies strong RBP binding sites in these viral genomes. Replication and expression of viral sequences is expected to increasingly sequester RBPs - SRSF1 and RNPS1. Ordinarily, RBPs bound to nascent host transcripts prevents their annealing to complementary DNA. Their depletion induces destabilizing R-loops. Chromosomal breakage occurs when an excess of unresolved R-loops collide with incoming replication forks, overwhelming the DNA repair machinery. We estimated stoichiometry of inhibition of RBPs in host nuclear RNA by counting competing binding sites in replicating viral genomes and host RNA.\n                  <\/ns3:p>\n                  <ns3:p>\n                    <ns3:bold>Results:<\/ns3:bold>\n                    Host RBP binding sites are frequent and conserved among different strains of RNA viral genomes. Similar binding motifs of SRSF1 and RNPS1 explain why DNA damage resulting from SRSF1 depletion is complemented by expression of RNPS1. Clustering of strong RBP binding sites coincides with the distribution of RNA-DNA hybridization sites across the genome. SARS-CoV-2 replication is estimated to require 32.5-41.8 hours to effectively compete for binding of an equal proportion of SRSF1 binding sites in host encoded nuclear RNAs. Significant changes in expression of transcripts encoding DNA repair and apoptotic proteins were found in an analysis of influenza A and Dengue-infected cells in some individuals.\n                  <\/ns3:p>\n                  <ns3:p>\n                    <ns3:bold>Conclusions:<\/ns3:bold>\n                    R-loop-induced apoptosis indirectly resulting from viral replication could release significant quantities of membrane-associated virions into neighboring alveoli. These could infect adjacent pneumocytes and other tissues, rapidly compromising lung function, causing multiorgan system failure and other described symptoms.\n                  <\/ns3:p>","DOI":"10.12688\/f1000research.25390.2","type":"journal-article","created":{"date-parts":[[2021,1,6]],"date-time":"2021-01-06T10:56:34Z","timestamp":1609930594000},"page":"943","update-policy":"https:\/\/doi.org\/10.12688\/f1000research.crossmark-policy","source":"Crossref","is-referenced-by-count":7,"title":["A proposed molecular mechanism for pathogenesis of severe RNA-viral pulmonary infections"],"prefix":"10.12688","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2070-5254","authenticated-orcid":false,"given":"Peter K.","family":"Rogan","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Eliseos J.","family":"Mucaki","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ben C.","family":"Shirley","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"2560","published-online":{"date-parts":[[2021,1,6]]},"reference":[{"key":"ref-1","doi-asserted-by":"publisher","first-page":"343-58","DOI":"10.1093\/ilar\/ilx026","article-title":"Are RNA Viruses Candidate Agents for the Next Global Pandemic? A Review.","volume":"58","author":"R Carrasco-Hernandez","year":"2017","journal-title":"ILAR J."},{"key":"ref-2","doi-asserted-by":"publisher","first-page":"656-657","DOI":"10.1016\/S1473-3099(20)30232-2","article-title":"Viral dynamics in mild and severe cases of COVID-19.","volume":"20","author":"Y Liu","year":"2020","journal-title":"Lancet Infect Dis."},{"key":"ref-3","doi-asserted-by":"publisher","first-page":"m1443","DOI":"10.1136\/bmj.m1443","article-title":"Viral load dynamics and disease severity in patients infected with SARS-CoV-2 in Zhejiang province, China, January-March 2020: retrospective cohort study.","volume":"369","author":"S Zheng","year":"2020","journal-title":"BMJ."},{"key":"ref-4","doi-asserted-by":"publisher","first-page":"929-36","DOI":"10.1056\/NEJMoa2001191","article-title":"First Case of 2019 Novel Coronavirus in the United States.","volume":"382","author":"M Holshue","year":"2020","journal-title":"N Engl J Med."},{"key":"ref-5","doi-asserted-by":"publisher","first-page":"2065","DOI":"10.3390\/ijms19072065","article-title":"Programmed Cell Death in the Pathogenesis of Influenza.","volume":"19","author":"D Fujikura","year":"2018","journal-title":"Int J Mol Sci."},{"key":"ref-6","doi-asserted-by":"publisher","first-page":"115-24","DOI":"10.1016\/j.molcel.2012.04.009","article-title":"R loops: from transcription byproducts to threats to genome stability.","volume":"46","author":"A Aguilera","year":"2012","journal-title":"Mol Cell."},{"key":"ref-7","doi-asserted-by":"publisher","first-page":"1569-79","DOI":"10.1101\/gad.10.13.1569","article-title":"SR proteins and splicing control.","volume":"10","author":"J Manley","year":"1996","journal-title":"Genes Dev."},{"key":"ref-8","doi-asserted-by":"publisher","first-page":"35-42","DOI":"10.1016\/0092-8674(90)90237-9","article-title":"The essential pre-mRNA splicing factor SF2 influences 5\u2019 splice site selection by activating proximal sites.","volume":"62","author":"A Krainer","year":"1990","journal-title":"Cell."},{"key":"ref-9","doi-asserted-by":"publisher","first-page":"291-336","DOI":"10.1146\/annurev.biochem.72.121801.161720","article-title":"Mechanisms of alternative pre-messenger RNA splicing.","volume":"72","author":"D Black","year":"2003","journal-title":"Annu Rev Biochem."},{"key":"ref-10","doi-asserted-by":"publisher","first-page":"365-78","DOI":"10.1016\/j.cell.2005.06.008","article-title":"Inactivation of the SR protein splicing factor ASF\/SF2 results in genomic instability.","volume":"122","author":"X Li","year":"2005","journal-title":"Cell."},{"key":"ref-11","doi-asserted-by":"publisher","first-page":"2108-15","DOI":"10.1261\/rna.734407","article-title":"The RNA binding protein RNPS1 alleviates ASF\/SF2 depletion-induced genomic instability.","volume":"13","author":"X Li","year":"2007","journal-title":"RNA."},{"key":"ref-12","doi-asserted-by":"publisher","first-page":"89","DOI":"10.1038\/msb4100134","article-title":"Large-scale mapping of human protein-protein interactions by mass spectrometry.","volume":"3","author":"R Ewing","year":"2007","journal-title":"Mol Syst Biol."},{"key":"ref-13","doi-asserted-by":"publisher","first-page":"545-60","DOI":"10.7150\/ijbs.18649","article-title":"Multifaceted Regulation of Gene Expression by the Apoptosis- and Splicing-Associated Protein Complex and Its Components.","volume":"13","author":"B Deka","year":"2017","journal-title":"Int J Biol Sci."},{"key":"ref-14","doi-asserted-by":"publisher","first-page":"3106-19","DOI":"10.1038\/emboj.2011.206","article-title":"Genome-wide function of THO\/TREX in active genes prevents R-loop-dependent replication obstacles.","volume":"30","author":"B G\u00f3mez-Gonz\u00e1lez","year":"2011","journal-title":"EMBO J."},{"key":"ref-15","doi-asserted-by":"publisher","first-page":"1551-1563.e7","DOI":"10.1016\/j.celrep.2019.07.010","article-title":"Depletion of the MFAP1\/SPP381 Splicing Factor Causes R-Loop-Independent Genome Instability.","volume":"28","author":"I Salas-Armenteros","year":"2019","journal-title":"Cell Rep."},{"key":"ref-16","doi-asserted-by":"publisher","first-page":"163-75","DOI":"10.1101\/gad.179721.111","article-title":"R-loop-mediated genome instability in mRNA cleavage and polyadenylation mutants.","volume":"26","author":"P Stirling","year":"2012","journal-title":"Genes Dev."},{"key":"ref-17","doi-asserted-by":"publisher","first-page":"282","DOI":"10.12688\/f1000research.5654.1","article-title":"Interpretation of mRNA splicing mutations in genetic disease: review of the literature and guidelines for information-theoretical analysis [version 1; peer review: 2 approved].","volume":"3","author":"N Caminsky","year":"2014","journal-title":"F1000Res."},{"key":"ref-18","doi-asserted-by":"publisher","first-page":"74-6","DOI":"10.1002\/humu.1380060114","article-title":"Using information content and base frequencies to distinguish mutations from genetic polymorphisms in splice junction recognition sites.","volume":"6","author":"P Rogan","year":"1995","journal-title":"Hum Mutat."},{"key":"ref-19","doi-asserted-by":"publisher","first-page":"153-71","DOI":"10.1002\/(SICI)1098-1004(1998)12:3<153::AID-HUMU3>3.0.CO;2-I","article-title":"Information analysis of human splice site mutations.","volume":"12","author":"P Rogan","year":"1998","journal-title":"Hum Mutat."},{"key":"ref-20","doi-asserted-by":"publisher","first-page":"735-42","DOI":"10.1002\/humu.21513","article-title":"Comprehensive prediction of mRNA splicing effects of BRCA1 and BRCA2 variants.","volume":"32","author":"E Mucaki","year":"2011","journal-title":"Hum Mutat."},{"key":"ref-21","doi-asserted-by":"publisher","first-page":"557-65","DOI":"10.1002\/humu.22277","article-title":"Prediction of mutant mRNA splice isoforms by information theory-based exon definition.","volume":"34","author":"E Mucaki","year":"2013","journal-title":"Hum Mutat."},{"key":"ref-22","doi-asserted-by":"publisher","first-page":"5345-55","DOI":"10.1093\/hmg\/ddv251","article-title":"FANCM c.5791C>T nonsense mutation (rs144567652) induces exon skipping, affects DNA repair activity and is a familial breast cancer risk factor.","volume":"24","author":"P Peterlongo","year":"2015","journal-title":"Hum Mol Genet."},{"key":"ref-23","doi-asserted-by":"publisher","first-page":"19","DOI":"10.1186\/s12920-016-0178-5","article-title":"A unified analytic framework for prioritization of non-coding variants of uncertain significance in heritable breast and ovarian cancer.","volume":"9","author":"E Mucaki","year":"2016","journal-title":"BMC Med Genomics."},{"key":"ref-24","doi-asserted-by":"publisher","first-page":"e27","DOI":"10.1093\/nar\/gkw1036","article-title":"Discovery and validation of information theory-based transcription factor and cofactor binding site motifs.","volume":"45","author":"R Lu","year":"2017","journal-title":"Nucleic Acids Res."},{"key":"ref-25","doi-asserted-by":"publisher","first-page":"1933","DOI":"10.12688\/f1000research.17363.2","article-title":"Transcription factor binding site clusters identify target genes with similar tissue-wide expression and buffer against mutations [version 2; peer review: 2 approved].","volume":"7","author":"R Lu","year":"2018","journal-title":"F1000Res."},{"key":"ref-26","doi-asserted-by":"publisher","first-page":"427-41","DOI":"10.1006\/jtbi.1997.0540","article-title":"Information content of individual genetic sequences.","volume":"189","author":"T Schneider","year":"1997","journal-title":"J Theor Biol."},{"key":"ref-27","doi-asserted-by":"publisher","DOI":"10.1101\/2020.07.15.204404","article-title":"A direct RNA-protein interaction atlas of the SARS-CoV-2 RNA in infected human cells.","author":"N Schmidt","year":"2020","journal-title":"bioRxiv."},{"key":"ref-28","doi-asserted-by":"publisher","DOI":"10.6084\/m9.figshare.12718799.v2","article-title":"Proposed mechanism of SARS-CoV-2 severe infection.","author":"P Rogan","year":"2020","journal-title":"Figshare."},{"key":"ref-29","doi-asserted-by":"publisher","first-page":"e00070-00014","DOI":"10.1128\/mBio.00070-14","article-title":"Influenza viruses and mRNA splicing: doing more with less.","volume":"5","author":"J Dubois","year":"2014","journal-title":"mBio."},{"key":"ref-30","doi-asserted-by":"publisher","first-page":"1838-47","DOI":"10.1101\/gad.1438306","article-title":"Cotranscriptional processes and their influence on genome stability.","volume":"20","author":"X Li","year":"2006","journal-title":"Genes Dev."},{"key":"ref-31","doi-asserted-by":"publisher","first-page":"1588-603","DOI":"10.1016\/j.celrep.2016.06.096","article-title":"Exon Junction Complexes Show a Distributional Bias toward Alternatively Spliced mRNAs and against mRNAs Coding for Ribosomal Proteins.","volume":"16","author":"C Hauer","year":"2016","journal-title":"Cell Rep."},{"key":"ref-32","doi-asserted-by":"publisher","first-page":"e1005841","DOI":"10.1371\/journal.ppat.1005841","article-title":"The Dengue Virus NS5 Protein Intrudes in the Cellular Spliceosome and Modulates Splicing.","volume":"12","author":"F De Maio","year":"2016","journal-title":"PLoS Pathog."},{"key":"ref-33","first-page":"153-9","article-title":"Influenza A: understanding the viral life cycle.","volume":"82","author":"T Samji","year":"2009","journal-title":"Yale J Biol Med."},{"key":"ref-34","doi-asserted-by":"publisher","first-page":"711-719","DOI":"10.1038\/s41586-020-2077-3","article-title":"A Large-Scale Binding and Functional Map of Human RNA Binding Proteins.","volume":"583","author":"E Van Nostrand","year":"2020","journal-title":"Nature."},{"key":"ref-35","doi-asserted-by":"publisher","first-page":"W253-258","DOI":"10.1093\/nar\/gkm272","article-title":"STAMP: a web tool for exploring DNA-binding motif similarities.","volume":"35","author":"S Mahony","year":"2007","journal-title":"Nucleic Acids Res."},{"key":"ref-36","doi-asserted-by":"publisher","first-page":"3836-45","DOI":"10.1093\/nar\/24.19.3836","article-title":"Searching databases of conserved sequence regions by aligning protein multiple-alignments.","volume":"24","author":"S Pietrokovski","year":"1996","journal-title":"Nucleic Acids Res."},{"key":"ref-37","doi-asserted-by":"publisher","first-page":"142","DOI":"10.1007\/82_2017_25","article-title":"Host Factors in Coronavirus Replication.","volume":"419","author":"A de Wilde","year":"2017","journal-title":"Roles Host Gene Non-Coding RNA Expr Virus Infect."},{"key":"ref-38","doi-asserted-by":"publisher","first-page":"439-50","DOI":"10.1038\/nrmicro2147","article-title":"Coronaviruses post-SARS: update on replication and pathogenesis.","volume":"7","author":"S Perlman","year":"2009","journal-title":"Nat Rev Microbiol."},{"key":"ref-39","article-title":"Characteristics of human and viral RNA binding sites and site clusters recognized by SRSF1 and RNPS1","author":"P Rogan","year":"2020","journal-title":"Zenodo."},{"key":"ref-40","doi-asserted-by":"publisher","first-page":"204","DOI":"10.1186\/1471-2105-6-204","article-title":"Tandem machine learning for the identification of genes regulated by transcription factors.","volume":"6","author":"D Dinakarpandian","year":"2005","journal-title":"BMC Bioinformatics."},{"key":"ref-41","doi-asserted-by":"publisher","first-page":"179","DOI":"10.1186\/s12967-020-02344-6","article-title":"Emerging SARS-CoV-2 mutation hot spots include a novel RNA-dependent-RNA polymerase variant.","volume":"18","author":"M Pachetti","year":"2020","journal-title":"J Transl Med."},{"key":"ref-42","doi-asserted-by":"publisher","DOI":"10.1093\/nsr\/nwaa036","article-title":"On the origin and continuing evolution of SARS-CoV-2.","author":"X Tang","year":"2020","journal-title":"Natl Sci Rev."},{"key":"ref-43","doi-asserted-by":"publisher","first-page":"2020.04.29.069054","DOI":"10.1101\/2020.04.29.069054","article-title":"Spike mutation pipeline reveals the emergence of a more transmissible form of SARS-CoV-2.","author":"B Korber","year":"2020","journal-title":"bioRxiv."},{"key":"ref-44","doi-asserted-by":"publisher","first-page":"4121-3","DOI":"10.1093\/bioinformatics\/bty407","article-title":"Nextstrain: real-time tracking of pathogen evolution.","volume":"34","author":"J Hadfield","year":"2018","journal-title":"Bioinformatics."},{"key":"ref-45","doi-asserted-by":"publisher","first-page":"2020.03.11.987222","DOI":"10.1101\/2020.03.11.987222","article-title":"Discovery of a 382-nt deletion during the early evolution of SARS-CoV-2.","author":"Y Su","year":"2020","journal-title":"bioRxiv."},{"key":"ref-46","doi-asserted-by":"publisher","first-page":"1734-55","DOI":"10.1038\/s41596-019-0159-1","article-title":"High-resolution, strand-specific R-loop mapping via S9.6-based DNA-RNA immunoprecipitation and high-throughput sequencing.","volume":"14","author":"L Sanz","year":"2019","journal-title":"Nat Protoc."},{"key":"ref-47","doi-asserted-by":"publisher","first-page":"45-52","DOI":"10.1016\/j.ymgme.2019.08.005","article-title":"Multigene signatures of responses to chemotherapy derived by biochemically-inspired machine learning.","volume":"128","author":"P Rogan","year":"2019","journal-title":"Mol Genet Metab."},{"key":"ref-48","doi-asserted-by":"publisher","first-page":"233","DOI":"10.12688\/f1000research.14048.2","article-title":"Predicting ionizing radiation exposure using biochemically-inspired genomic machine learning [version 2; peer review: 3 approved].","volume":"7","author":"J Zhao","year":"2018","journal-title":"F1000Res."},{"key":"ref-49","doi-asserted-by":"publisher","first-page":"RRN1154","DOI":"10.1371\/currents.rrn1154","article-title":"Lymphocyte to monocyte ratio as a screening tool for influenza.","volume":"2","author":"G Merekoulias","year":"2010","journal-title":"PLoS Curr."},{"key":"ref-50","doi-asserted-by":"publisher","first-page":"1213-23","DOI":"10.1016\/j.cell.2008.10.045","article-title":"Structural basis of UV DNA-damage recognition by the DDB1-DDB2 complex.","volume":"135","author":"A Scrima","year":"2008","journal-title":"Cell."},{"key":"ref-51","doi-asserted-by":"publisher","first-page":"383-94","DOI":"10.1016\/j.molcel.2006.03.035","article-title":"Histone H3 and H4 Ubiquitylation by the CUL4-DDB-ROC1 Ubiquitin Ligase Facilitates Cellular Response to DNA Damage.","volume":"22","author":"H Wang","year":"2006","journal-title":"Mol Cell."},{"key":"ref-52","doi-asserted-by":"publisher","first-page":"496-510","DOI":"10.1101\/gr.161034.113","article-title":"From single-cell to cell-pool transcriptomes: stochasticity in gene expression and RNA splicing.","volume":"24","author":"G Marinov","year":"2014","journal-title":"Genome Res."},{"key":"ref-53","doi-asserted-by":"publisher","first-page":"19490-9","DOI":"10.1073\/pnas.1912459116","article-title":"Spatial transcriptome profiling by MERFISH reveals subcellular RNA compartmentalization and cell cycle-dependent gene expression.","volume":"116","author":"C Xia","year":"2019","journal-title":"Proc Natl Acad Sci U S A."},{"key":"ref-54","doi-asserted-by":"publisher","first-page":"105-17","DOI":"10.1016\/j.molcel.2015.09.005","article-title":"SRSF1-Regulated Alternative Splicing in Breast Cancer.","volume":"60","author":"O Anczuk\u00f3w","year":"2015","journal-title":"Mol Cell."},{"key":"ref-55","doi-asserted-by":"publisher","first-page":"1036-1045.e9","DOI":"10.1016\/j.cell.2020.04.026","article-title":"Imbalanced Host Response to SARS-CoV-2 Drives Development of COVID-19.","volume":"181","author":"D Blanco-Melo","year":"2020","journal-title":"Cell."},{"key":"ref-56","doi-asserted-by":"publisher","first-page":"1655-62","DOI":"10.1002\/bit.25578","article-title":"Robust kinetics of an RNA virus: Transcription rates are set by genome levels.","volume":"112","author":"C Timm","year":"2015","journal-title":"Biotechnol Bioeng."},{"key":"ref-57","doi-asserted-by":"publisher","first-page":"4682","DOI":"10.1038\/s41467-020-18463-z","article-title":"Rapid incorporation of Favipiravir by the fast and permissive viral RNA polymerase complex results in SARS-CoV-2 lethal mutagenesis.","volume":"11","author":"A Shannon","year":"2020","journal-title":"Nat Commun."},{"key":"ref-58","doi-asserted-by":"publisher","first-page":"1016-1020","DOI":"10.1126\/science.abb7015","article-title":"Susceptibility of ferrets, cats, dogs, and other domesticated animals to SARS-coronavirus 2.","volume":"368","author":"J Shi","year":"2020","journal-title":"Science."},{"key":"ref-59","doi-asserted-by":"publisher","first-page":"144","DOI":"10.1186\/s12879-017-2253-8","article-title":"Effective inhibition of MERS-CoV infection by resveratrol.","volume":"17","author":"S Lin","year":"2017","journal-title":"BMC Infect Dis."},{"key":"ref-60","doi-asserted-by":"publisher","first-page":"1752-8","DOI":"10.3892\/mmr.2014.2925","article-title":"Resveratrol exerts an anti-apoptotic effect on human bronchial epithelial cells undergoing cigarette smoke exposure.","volume":"11","author":"L Zhang","year":"2015","journal-title":"Mol Med Rep."},{"key":"ref-61","doi-asserted-by":"publisher","first-page":"763","DOI":"10.3390\/molecules24040763","article-title":"Computer-Aided Discovery of Small Molecules Targeting the RNA Splicing Activity of hnRNP A1 in Castration-Resistant Prostate Cancer.","volume":"24","author":"L Carabet","year":"2019","journal-title":"Mol Basel Switz."},{"key":"ref-62","doi-asserted-by":"publisher","first-page":"2020.02.12.945576","DOI":"10.1101\/2020.02.12.945576","article-title":"Aberrant pathogenic GM-CSF+ T cells and inflammatory CD14+CD16+ monocytes in severe pulmonary syndrome patients of a new coronavirus.","author":"Y Zhou","year":"2020","journal-title":"bioRxiv."},{"key":"ref-63","doi-asserted-by":"publisher","first-page":"6055-66","DOI":"10.1128\/JVI.00365-12","article-title":"Integrated Clinical, Pathologic, Virologic, and Transcriptomic Analysis of H5N1 Influenza Virus-Induced Viral Pneumonia in the Rhesus Macaque.","volume":"86","author":"K Shinya","year":"2012","journal-title":"J Virol."},{"key":"ref-64","doi-asserted-by":"publisher","first-page":"109588","DOI":"10.1016\/j.cellsig.2020.109588","article-title":"Chronic WNT\/\u03b2-catenin signaling induces cellular senescence in lung epithelial cells.","volume":"70","author":"M Lehmann","year":"2020","journal-title":"Cell Signal."},{"key":"ref-65","doi-asserted-by":"publisher","first-page":"2020.05.11.088179","DOI":"10.1101\/2020.05.11.088179","article-title":"SARS-CoV-2 ORF3b is a potent interferon antagonist whose activity is further increased by a naturally occurring elongation variant.","author":"Y Konno","year":"2020","journal-title":"bioRxiv."},{"key":"ref-66","doi-asserted-by":"publisher","first-page":"1628","DOI":"10.12688\/f1000research.11827.1","article-title":"Origins and pathogenesis of Middle East respiratory syndrome-associated coronavirus: recent advances [version 1; peer review: 3 approved].","volume":"6","author":"S Goldstein","year":"2017","journal-title":"F1000Res."},{"key":"ref-67","doi-asserted-by":"publisher","first-page":"510","DOI":"10.3390\/v12050510","article-title":"Asian Zika Virus Isolate Significantly Changes the Transcriptional Profile and Alternative RNA Splicing Events in a Neuroblastoma Cell Line.","volume":"12","author":"G Bonenfant","year":"2020","journal-title":"Viruses."},{"key":"ref-68","doi-asserted-by":"publisher","first-page":"29","DOI":"10.1186\/s12985-019-1137-5","article-title":"The Epstein-Barr virus EBNA1 protein modulates the alternative splicing of cellular genes.","volume":"16","author":"S Boudreault","year":"2019","journal-title":"Virol J."},{"key":"ref-69","doi-asserted-by":"publisher","first-page":"568-82","DOI":"10.1038\/nprot.2013.019","article-title":"Reprogramming human fibroblasts to pluripotency using modified mRNA.","volume":"8","author":"P Mandal","year":"2013","journal-title":"Nat Protoc."},{"key":"ref-70","doi-asserted-by":"publisher","first-page":"167-78","DOI":"10.1016\/j.celrep.2012.02.001","article-title":"Integrative genome-wide analysis reveals cooperative regulation of alternative splicing by hnRNP proteins.","volume":"1","author":"S Huelga","year":"2012","journal-title":"Cell Rep."},{"key":"ref-71","doi-asserted-by":"publisher","first-page":"4979-91","DOI":"10.1093\/nar\/gkh825","article-title":"Bipartite pattern discovery by entropy minimization-based multiple local alignment.","volume":"32","author":"C Bi","year":"2004","journal-title":"Nucleic Acids Res."},{"key":"ref-72","doi-asserted-by":"crossref","article-title":"ggplot2: Elegant Graphics for Data Analysis.","author":"H Wickham","DOI":"10.1007\/978-0-387-98141-3"},{"key":"ref-73","doi-asserted-by":"publisher","first-page":"453-4","DOI":"10.1038\/s41592-019-0430-y","article-title":"trackViewer: a Bioconductor package for interactive and integrative visualization of multi-omics data.","volume":"16","author":"J Ou","year":"2019","journal-title":"Nat Methods."}],"container-title":["F1000Research"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/f1000research.com\/articles\/9-943\/v2\/xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/f1000research.com\/articles\/9-943\/v2\/pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/f1000research.com\/articles\/9-943\/v2\/iparadigms","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,10,16]],"date-time":"2023-10-16T22:13:33Z","timestamp":1697494413000},"score":1,"resource":{"primary":{"URL":"https:\/\/f1000research.com\/articles\/9-943\/v2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,1,6]]},"references-count":73,"URL":"https:\/\/doi.org\/10.12688\/f1000research.25390.2","relation":{"has-review":[{"id-type":"doi","id":"10.5256\/f1000research.31422.r76719","asserted-by":"object"},{"id-type":"doi","id":"10.5256\/f1000research.31422.r76718","asserted-by":"object"}]},"ISSN":["2046-1402"],"issn-type":[{"value":"2046-1402","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,1,6]]},"assertion":[{"value":"Indexed","URL":"https:\/\/f1000research.com\/articles\/9-943\/v2#article-reports","order":0,"name":"referee-status","label":"Referee status","group":{"name":"current-referee-status","label":"Current Referee Status"}},{"value":"10.5256\/f1000research.28014.r73888, Maurizio Romano, Department of Life Sciences, University of Trieste, Trieste, Italy, 13 Nov 2020, version 1, indexed","URL":"https:\/\/f1000research.com\/articles\/9-943\/v1#referee-response-73888","order":0,"name":"referee-response-73888","label":"Referee Report","group":{"name":"article-reports","label":"Article Reports"}},{"value":"<b>Peter Rogan<\/b>; <i>Posted: 11 Dec 2020<\/i>; Thank you for reviewing our manuscript. We concur that the Discussion section of the manuscript is lengthy. We have therefore removed the paragraph beginning with \u201c\u201cThe immune system appears to be a witness, rather than a direct participant \u2026\u201d, as it is only tangentially related from the mechanism being proposed.","URL":"https:\/\/f1000research.com\/articles\/9-943\/v2#referee-comment-6188","order":1,"name":"referee-comment-6188","label":"Referee Comment","group":{"name":"article-reports","label":"Article Reports"}},{"value":"10.5256\/f1000research.28014.r73885, Mansi Srivastava, Indiana University School of Medicine, Indianapolis, IN, USA, 18 Nov 2020, version 1, indexed","URL":"https:\/\/f1000research.com\/articles\/9-943\/v1#referee-response-73885","order":2,"name":"referee-response-73885","label":"Referee Report","group":{"name":"article-reports","label":"Article Reports"}},{"value":"<b>Peter Rogan<\/b>; <i>Posted: 11 Dec 2020<\/i>; Thank you for reviewing our manuscript. Newly synthesized RBPs imported into the nucleus and bound to nascent transcripts do not necessarily have an impact on R-loop formation. Our study put a strong focus on SRSF1 and RNPS1, which have been documented to be antagonistic to R-loop formation. We have not investigated other RNA binding proteins that are known to stabilize nascent transcripts, such as the THO complex, <i>PCF11<\/i>, and the exoribonucleases <i>EXOSC3<\/i> and <i>EXOSC10<\/i> (Santos-Pereira &amp; Aguilera. <i>Nat Rev Genet<\/i>. 2015. 16: 583-597). The CLIP data required to analyze RNA for binding sites is not currently available for many of these RBPs. Ribosomal RNA (rRNA) constitutes the most abundant RNA in the cytoplasm (indeed, the cell), and would likely be the most likely to interact with SRSF1 and RNPS1. Ribosomal proteins interacting with rRNA-scaffold would likely represent the most abundant competitor to viral RNAs in infected cells. rRNA interactions have a structural basis (e.g. bulged duplexes, hairpin loops) that explains their affinity for ribosomal proteins. This contrasts with the sequence-specific binding by SRSF1 and RNPS1 and other RBPs containing one or more RRM domains (Ciriello et al. BMC Bioinformatics. 2010; 11(Suppl 1): S41). The method we describe does not detect or quantify the type of structural interactions seen in rRNA and ribosomal proteins. The present approach cannot determine whether viral RNAs could bind to ribosomal proteins.","URL":"https:\/\/f1000research.com\/articles\/9-943\/v2#referee-comment-6189","order":3,"name":"referee-comment-6189","label":"Referee Comment","group":{"name":"article-reports","label":"Article Reports"}},{"value":"10.5256\/f1000research.28014.r73887, Gregory Fonseca, Division of Experimental Medicine, Department of Medicine, McGill University, Montreal, Canada, 24 Nov 2020, version 1, indexed","URL":"https:\/\/f1000research.com\/articles\/9-943\/v1#referee-response-73887","order":4,"name":"referee-response-73887","label":"Referee Report","group":{"name":"article-reports","label":"Article Reports"}},{"value":"<b>Peter Rogan<\/b>; <i>Posted: 11 Dec 2020<\/i>; <i>1. It should be mentioned whether IWM discovery was compared to background to understand if IWNs are found above random chance.<\/i> Response: We derived IWMs from (mock) control binding studies for SRSF1 and RNPS1. Sequences obtained for 3 negative controls were generated in the same dataset that was used to build IWMs for RNPS1 (E-MTAB-4215; control datasets \u2018ERR1201436\u2019, \u2018ERR1201437\u2019 and \u2018ERR1201438\u2019). These were samples containing a GFP-tag (lacking the RNPS1 fusion protein for pulldown). IWMs were also derived from two SRSF1 control datasets (\u2018ENCFF241ORF\u2019 and \u2018ENCFF773PUP\u2019; positive and negative strands from mock input sample). From these datasets, we derived IWMs of length 6nt from the top 5,000 peaks from each dataset with Maskminent using the same parameters (see Methods). The motifs of the newly derived control IWMs were compared to the true SRSF1 and RNPS1 models using STAMP software (described in Methods). The e-value obtained from STAMP is the number of hits expected against a database of the same size (i.e. 5,000 sequences containing random sequences of the same length). The comparison is based on the log likelihood ratio of the e-values of the IWM motifs derived from the RBP bound sequences relative to the sequences obtained from the mock control, which is a modified LOD score. The LOD scores for the RNPS1 model ranged from 3.8 to 6.1 depending on which control IWM was compared, and for SRSF1, these scores ranged from 4.4 to 8.8. We therefore conclude that the motifs obtained for these protein binding sites are <i>significantly<\/i> more robust (and different from a random set of sequences of the same size and composition generated from control samples). Please note that this analysis has been incorporated into the manuscript (the fourth paragraph of the Results and in the second and fourth paragraphs of the Methods). <i>2. If you randomly curate IWMs from 5000 sites of Rep1 or bin 5000 sites do the results compare to Rep2?<\/i> Response: In this study, the two SRSF1 IWMs utilized were derived from two separate replicates from publicly available eCLIP data. The first model \u201cSRSF1 Replicate 1\u201d was based on the 50,000 largest eCLIP peaks from the \u2018ENCFF179SCM\u2019 replicate, while \u201cSRSF1 Replicate 2\u201d was based on the top 5,000 peaks in the \u2018ENCFF184TBM\u2019 replicate. Despite being derived from a far smaller dataset, the models were computed to be quite similar and non-random by STAMP analysis (e-score: 7.4e-10). While the SRSF1 \u201cReplicate 1\u201d and \u201cReplicate 2\u201d models were those which were selected to be used in the study, IWMs for SRSF1 were derived utilizing a series of different conditions (i.e. number of peaks, number of Monte Carlo cycles, etc.), however discussion of these additional derived SRSF1 models was not included in the final manuscript. Most commonly, models derived under these varying conditions were similar to that of the final models. On occasion, the method used here has been reported to identify binding motifs of other factors whose binding site sequences are in close proximity with the factor being crosslinked, as well as IWMs with a noise motifs that can resemble repetitive sequences (Lu et al. Nucleic Acids Res. 2017 Mar 17;45(5):e27). We carefully evaluated each IWM before it was utilized in any downstream analyses. For example, while the SRSF1 model derived from 10,000 peaks from the \u2018replicate 1\u2019 dataset is highly similar to that of the 50,000 replicate 1 peak model (as well as those models derived from replicate 2 data), the 5,000 replicate 1 peak model contained a slight variation of the primary motif, reporting instead an unexpected \u201cG[G\/C]AG\u201d sub-motif. &nbsp;The pairwise IWM e-values from comparison of SRSF1 Replicates 1 and 2 are: \u201cSRSF1 Replicate 2\u201d (self comparison): 3.9e-11;&nbsp; \u201cSRSF1 Replicate 1\u201d (top e-CLIP 50,000 peaks): 7.4e-10;&nbsp; \u201cSRSF1 Replicate 1\u201d (top 10,000 peaks): 3.6e-09;&nbsp; and \u201cSRSF1 Replicate 1\u201d (top 5,000 peaks: 5.0e-03.&nbsp; In general, however, modifying the number of binding sites from which models are derived generally leads to IWMs with highly similar binding motifs. <i>3. What would the predicted likelihood of IWMs changing by chance compare to observed?<\/i> Response: See response to Question 1. <i>4. Is there a correlation of SRSF and RNPS1 sites in the mRNA and gene expression at basal and during infection?<\/i> Response: The expression of basal SRSF1 and RNPS1 may be significantly altered in an infected cell. Blanco-Melo et al. (Ref. 55) performed differential gene expression analysis of A549 immortalized cell lines, comparing infection with influenza A- or SARS-CoV-2 with controls and ranking genes by fold change p-values adjusted for multiple testing. Both SRSF1 and RNPS1 exhibited statistically significant lowered expression in SARS-CoV-2 infected A549 cell lines (73% [p=3.7e-16] and 47% [p=3.5e-89] of controls, respectively). Their expression was also significant decreased in SARS-CoV-2 infected Calu-3 cell lines (74% for SRSF1 and 75% for RNPS1). Expression of SRSF1 and RNPS1 in A549 cells infected with respiratory syncytial virus was also significantly reduced (73% for both). No significant differences were evident in A549 infected with either SARS-CoV-1, MERS nor influenza A. Expression of SRSF1 and RNPS1 is not only altered by viral infection, but the extent of these changes is related to the specific infectious pathogen. We have added a statement to the manuscript acknowledging that the gene expression datasets utilized in this study were from uninfected cells which may differ in infected cells (new text bolded): &nbsp; &nbsp; &nbsp; &nbsp;\u201cThese are derived from the number of SRSF1 and RNPS1 sites expressed in either a single A549 cell or a type II pneumocyte <b>(cells were not infected; note that infection would be expected to alter the expression profile, which could affect expressed binding site estimates)<\/b>.\u201d","URL":"https:\/\/f1000research.com\/articles\/9-943\/v2#referee-comment-6191","order":5,"name":"referee-comment-6191","label":"Referee Comment","group":{"name":"article-reports","label":"Article Reports"}},{"value":"10.5256\/f1000research.28014.r73886, Ian Eperon, Leicester Institute of Structural & Chemical Biology, Department of Molecular & Cell Biology, University of Leicester, Leicester, UK, 26 Nov 2020, version 1, indexed","URL":"https:\/\/f1000research.com\/articles\/9-943\/v1#referee-response-73886","order":6,"name":"referee-response-73886","label":"Referee Report","group":{"name":"article-reports","label":"Article Reports"}},{"value":"<b>Peter Rogan<\/b>; <i>Posted: 11 Dec 2020<\/i>; <i>It was assumed, but has not yet been tested, that the sites elected are the stronger binding sites. It is not clear whether this has any biological relevance, i.e., how bound lifetimes (affinity) vary across all the sequences in the model and whether the threshold chosen is likely to reflect the real behaviour of the proteins.&nbsp;<\/i> Response: The IWMs derived in this manuscript may not yet been verified in the laboratory, however we have verified binding sites by such approaches previously (Vyhlidal, Rogan et al. <i>J Biol Chem<\/i>. 2004. 279:46779-86). The information theory framework used to derive them has been well validated and the relationships between information content and binding affinity have been rigorously proven (Schneider. <i>J Theor Biol.<\/i> 1997; 189:427-41). While the models used in this study were recently derived, other information theory-based RNA-protein binding site models have been utilized in hundreds of published studies, some involving the verification of phenotypes of mutations that alter splice sites, and others applied to transcription factor binding site recognition (Rogan et al. <i>Hum Mutat.<\/i>&nbsp;1998;&nbsp; <b>12<\/b>: 153\u2013171; Rogan et al. <i>Pharmacogenetics.<\/i>&nbsp;2003;&nbsp; <b>13<\/b>: 207\u2013218; Caminsky et al. F1000Res. 2014; 3:282; Lu et al. Nucl. Ac. Res. 45: e27, 2017). Our assumptions regarding binding site strength are well founded both theoretically and experimentally for many proteins. Quantification of the predicted strengths of these binding sites made by these models is reasonable and may likely reflect actual protein binding events. <i>The Kd term they use is taken from assays with just the second RRM domain, but the value with both RRM domains is around 0.2 &micro;M (Anczukow et al. (2015).<\/i>&nbsp; <i>The authors also assume that there is no free protein, but this is not supported by any arguments. <\/i> Response: We are grateful to the reviewer for pointing out the updated dissociation constant of SRSF1 (Anczukow et al. 2015; Ref. 54), based on assays that included both RRM domains. We had inadvertently overlooked this study. The K <sub>d<\/sub> value used in the initial version of our paper (0.8&micro;M) was based on an earlier publication from the same group (Cl&eacute;ry et al. <i>Proc Natl Acad Sci U S A.<\/i> 2013; 110(30):E2802\u20132811). &nbsp;The new K <sub>d<\/sub> value altered Scatchard analysis presented in Figure 6. The number of doublings for replicated virus was significantly increased, which reduced the discrepancy with the number of viral genomes required to compete with host transcriptome biding sites in A549 cell lines. In this revision, we have recomputed all values based on K <sub>d<\/sub> from Anczukow et al. (2015) and have updated the main text, Figure 6 and Section 1 Tables 9A and 9B (extended data; Ref. 39). We previously did not include a justification for our assumption that [L] = 0 (no free protein) in our derivation of the Scatchard plot. The proposed mechanism relies on the likelihood that these RBPs are largely sequestered by binding to viral sequences, so that their effective concentration in the nucleus is inadequate to prevent R-loops (thus, [L] \u2248 0). SARS-CoV-2 replication is highly efficient and rapid, leading to levels constituting up to 60% of the total cellular RNA (Blanco-Melo et al. 2020; Ref. 55). Viral replication produces an excess of viral binding sites that will perturb the equilibrium between bound and free RBPs (Le Chatelier\u2019s Principle) and drive binding of free RBPs and reduce the pool of free RBPs. The degree of viral replication that depletes nuclear RBP concentrations to a point at which the abundance of these factors becomes insufficient to prevent R-loop formation is not known. To clarify our assumption that all RBPs are bound to viral (or host), we have added the following to the Results: &nbsp; &nbsp; &nbsp;\u201cWe assumed no free RNA binding protein (that the vast majority of SRSF1 is bound to either host or viral binding sites) as the concentration of free RBPs is likely to be low due to sequestration of RBPs by the excess of viral sequences present in infected cells (~60% of all RNA <sup>55 <\/sup>)\u201d and to the Methods: &nbsp; &nbsp; &nbsp;\u201cUpon infection and viral replication, it is assumed there is no free RNA binding protein (all RBP is assumed to be bound to either viral or host RNA).\u201d <i>However, and this is a significant caveat, the protein is not distributed evenly throughout the cell: it is largely nuclear and, within the nucleus, may be sequestered in speckles. Thus, the concentration in the cytoplasm, where it would encounter the viral RNA, might be much lower and thus affect the authors\u2019 argument. The authors\u2019 model involves competition between the nascent transcripts (nuclear) and the viral RNA (cytoplasmic) for SRSF1 binding, and any difference in the local concentrations and proportions of sites bound would undermine the model. <\/i> Response:&nbsp;The reviewer has commented that the difference in local RBP concentrations between the cytoplasm and the nucleus would have an impact on the amount of RBP (such as SRSF1) that could possibly be sequestered in the cytoplasm by viral RNA. We do not state that we assume that these RBPs are uniformly distributed within the cell. We suggest that viral RNA binds to newly synthesized RBPs that have been translated in the cytoplasm, which could result in such an imbalance by limiting their nuclear entry (last paragraph of the \u201cProposed molecular pathogenetic mechanism of RNA-viral infection\u201d section). It was also illustrated in panels 3 and 4 of the infographic of our proposed mechanism (Ref. 28; (http:\/\/doi.org\/10.6084\/m9.figshare.12718799.v2).","URL":"https:\/\/f1000research.com\/articles\/9-943\/v2#referee-comment-6192","order":7,"name":"referee-comment-6192","label":"Referee Comment","group":{"name":"article-reports","label":"Article Reports"}},{"value":"PKR acknowledges Compute Canada for a special allocation of computing resources dedicated to COVID-19 research. He has been supported previously by the Canada Foundation for Innovation and Canada Research Chairs. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.","order":8,"name":"grant-information","label":"Grant Information"},{"value":"This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.","order":0,"name":"copyright-info","label":"Copyright"}]}}