Shell disorder analysis predicts greater resilience of the SARS-CoV-2 (COVID-19) outside the body and in body fluids
Identifieur interne : 000F19 ( Pmc/Curation ); précédent : 000F18; suivant : 000F20Shell disorder analysis predicts greater resilience of the SARS-CoV-2 (COVID-19) outside the body and in body fluids
Auteurs : Gerard Kian-Meng Goh [Singapour] ; A. Keith Dunker [États-Unis] ; James A. Foster [États-Unis] ; Vladimir N. Uversky [États-Unis, Russie]Source :
- Microbial Pathogenesis [ 0882-4010 ] ; 2020.
Abstract
The coronavirus (CoV) family consists of viruses that infects a variety of animals including humans with various levels of respiratory and fecal-oral transmission levels depending on the behavior of the viruses' natural hosts and optimal viral fitness. A model to classify and predict the levels of respective respiratory and fecal-oral transmission potentials of the various viruses was built before the outbreak of MERS-CoV using AI and empirically-based molecular tools to predict the disorder level of proteins. Using the percentages of intrinsic disorder (PID) of the nucleocapsid (N) and membrane (M) proteins of CoV, the model easily clustered the viruses into three groups with the SARS-CoV (M PID = 8%, N PID = 50%) falling into Category B, in which viruses have intermediate levels of both respiratory and fecal-oral transmission potentials. Later, MERS-CoV (M PID = 9%, N PID = 44%) was found to be in Category C, which consists of viruses with lower respiratory transmission potential but with higher fecal-oral transmission capabilities. Based on the peculiarities of disorder distribution, the SARS-CoV-2 (M PID = 6%, N PID = 48%) has to be placed in Category B. Our data show however, that the SARS-CoV-2 is very strange with one of the hardest protective outer shell, (M PID = 6%) among coronaviruses. This means that it might be expected to be highly resilient in saliva or other body fluids and outside the body. An infected body is likelier to shed greater numbers of viral particles since the latter is more resistant to antimicrobial enzymes in body fluids. These particles are also likelier to remain active longer. These factors could account for the greater contagiousness of the SARS-CoV-2 and have implications for efforts to prevent its spread.
Url:
DOI: 10.1016/j.micpath.2020.104177
PubMed: 32244041
PubMed Central: 7118597
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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Shell disorder analysis predicts greater resilience of the SARS-CoV-2 (COVID-19) outside the body and in body fluids</title><author><name sortKey="Goh, Gerard Kian Meng" sort="Goh, Gerard Kian Meng" uniqKey="Goh G" first="Gerard Kian-Meng" last="Goh">Gerard Kian-Meng Goh</name><affiliation wicri:level="1"><nlm:aff id="aff1">Goh's BioComputing, Singapore</nlm:aff><country xml:lang="fr">Singapour</country><wicri:regionArea>Goh's BioComputing</wicri:regionArea></affiliation></author><author><name sortKey="Dunker, A Keith" sort="Dunker, A Keith" uniqKey="Dunker A" first="A. Keith" last="Dunker">A. Keith Dunker</name><affiliation wicri:level="1"><nlm:aff id="aff2">Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, USA</nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN</wicri:regionArea></affiliation></author><author><name sortKey="Foster, James A" sort="Foster, James A" uniqKey="Foster J" first="James A." last="Foster">James A. Foster</name><affiliation wicri:level="1"><nlm:aff id="aff3">Department of Biological Sciences, University of Idaho, Moscow, ID, USA</nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Biological Sciences, University of Idaho, Moscow, ID</wicri:regionArea></affiliation><affiliation wicri:level="1"><nlm:aff id="aff4">Institute for Bioinformatics and Evolutionary Studies, University of Idaho, Moscow, ID, USA</nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Institute for Bioinformatics and Evolutionary Studies, University of Idaho, Moscow, ID</wicri:regionArea></affiliation></author><author><name sortKey="Uversky, Vladimir N" sort="Uversky, Vladimir N" uniqKey="Uversky V" first="Vladimir N." last="Uversky">Vladimir N. Uversky</name><affiliation wicri:level="1"><nlm:aff id="aff5">Department of Molecular Medicine, Morsani College of Medicine, University of South Florida, Tampa, FL, USA</nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Molecular Medicine, Morsani College of Medicine, University of South Florida, Tampa, FL</wicri:regionArea></affiliation><affiliation wicri:level="1"><nlm:aff id="aff6">Institute for Biological Instrumentation, Russian Academy of Sciences, Pushchino, Moscow region, Russia</nlm:aff><country xml:lang="fr">Russie</country><wicri:regionArea>Institute for Biological Instrumentation, Russian Academy of Sciences, Pushchino, Moscow region</wicri:regionArea></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">32244041</idno><idno type="pmc">7118597</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7118597</idno><idno type="RBID">PMC:7118597</idno><idno type="doi">10.1016/j.micpath.2020.104177</idno><date when="2020">2020</date><idno type="wicri:Area/Pmc/Corpus">000F19</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">000F19</idno><idno type="wicri:Area/Pmc/Curation">000F19</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Curation">000F19</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Shell disorder analysis predicts greater resilience of the SARS-CoV-2 (COVID-19) outside the body and in body fluids</title><author><name sortKey="Goh, Gerard Kian Meng" sort="Goh, Gerard Kian Meng" uniqKey="Goh G" first="Gerard Kian-Meng" last="Goh">Gerard Kian-Meng Goh</name><affiliation wicri:level="1"><nlm:aff id="aff1">Goh's BioComputing, Singapore</nlm:aff><country xml:lang="fr">Singapour</country><wicri:regionArea>Goh's BioComputing</wicri:regionArea></affiliation></author><author><name sortKey="Dunker, A Keith" sort="Dunker, A Keith" uniqKey="Dunker A" first="A. Keith" last="Dunker">A. Keith Dunker</name><affiliation wicri:level="1"><nlm:aff id="aff2">Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, USA</nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN</wicri:regionArea></affiliation></author><author><name sortKey="Foster, James A" sort="Foster, James A" uniqKey="Foster J" first="James A." last="Foster">James A. Foster</name><affiliation wicri:level="1"><nlm:aff id="aff3">Department of Biological Sciences, University of Idaho, Moscow, ID, USA</nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Biological Sciences, University of Idaho, Moscow, ID</wicri:regionArea></affiliation><affiliation wicri:level="1"><nlm:aff id="aff4">Institute for Bioinformatics and Evolutionary Studies, University of Idaho, Moscow, ID, USA</nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Institute for Bioinformatics and Evolutionary Studies, University of Idaho, Moscow, ID</wicri:regionArea></affiliation></author><author><name sortKey="Uversky, Vladimir N" sort="Uversky, Vladimir N" uniqKey="Uversky V" first="Vladimir N." last="Uversky">Vladimir N. Uversky</name><affiliation wicri:level="1"><nlm:aff id="aff5">Department of Molecular Medicine, Morsani College of Medicine, University of South Florida, Tampa, FL, USA</nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Molecular Medicine, Morsani College of Medicine, University of South Florida, Tampa, FL</wicri:regionArea></affiliation><affiliation wicri:level="1"><nlm:aff id="aff6">Institute for Biological Instrumentation, Russian Academy of Sciences, Pushchino, Moscow region, Russia</nlm:aff><country xml:lang="fr">Russie</country><wicri:regionArea>Institute for Biological Instrumentation, Russian Academy of Sciences, Pushchino, Moscow region</wicri:regionArea></affiliation></author></analytic><series><title level="j">Microbial Pathogenesis</title><idno type="ISSN">0882-4010</idno><idno type="eISSN">1096-1208</idno><imprint><date when="2020">2020</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p>The coronavirus (CoV) family consists of viruses that infects a variety of animals including humans with various levels of respiratory and fecal-oral transmission levels depending on the behavior of the viruses' natural hosts and optimal viral fitness. A model to classify and predict the levels of respective respiratory and fecal-oral transmission potentials of the various viruses was built before the outbreak of MERS-CoV using AI and empirically-based molecular tools to predict the disorder level of proteins. Using the percentages of intrinsic disorder (PID) of the nucleocapsid (N) and membrane (M) proteins of CoV, the model easily clustered the viruses into three groups with the SARS-CoV (M PID = 8%, N PID = 50%) falling into Category B, in which viruses have intermediate levels of both respiratory and fecal-oral transmission potentials. Later, MERS-CoV (M PID = 9%, N PID = 44%) was found to be in Category C, which consists of viruses with lower respiratory transmission potential but with higher fecal-oral transmission capabilities. Based on the peculiarities of disorder distribution, the SARS-CoV-2 (M PID = 6%, N PID = 48%) has to be placed in Category B. Our data show however, that the SARS-CoV-2 is very strange with one of the hardest protective outer shell, (M PID = 6%) among coronaviruses. This means that it might be expected to be highly resilient in saliva or other body fluids and outside the body. An infected body is likelier to shed greater numbers of viral particles since the latter is more resistant to antimicrobial enzymes in body fluids. These particles are also likelier to remain active longer. These factors could account for the greater contagiousness of the SARS-CoV-2 and have implications for efforts to prevent its spread.</p></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Who" uniqKey="Who">WHO</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Goh, G K" uniqKey="Goh G">G.K. Goh</name></author><author><name sortKey="Dunker, A K" uniqKey="Dunker A">A.K. Dunker</name></author><author><name sortKey="Foster, J A" uniqKey="Foster J">J.A. 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<front><journal-meta><journal-id journal-id-type="nlm-ta">Microb Pathog</journal-id><journal-id journal-id-type="iso-abbrev">Microb. Pathog</journal-id><journal-title-group><journal-title>Microbial Pathogenesis</journal-title></journal-title-group><issn pub-type="ppub">0882-4010</issn><issn pub-type="epub">1096-1208</issn><publisher><publisher-name>Elsevier Ltd.</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">32244041</article-id><article-id pub-id-type="pmc">7118597</article-id><article-id pub-id-type="publisher-id">S0882-4010(20)30464-2</article-id><article-id pub-id-type="doi">10.1016/j.micpath.2020.104177</article-id><article-id pub-id-type="publisher-id">104177</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title-group><article-title>Shell disorder analysis predicts greater resilience of the SARS-CoV-2 (COVID-19) outside the body and in body fluids</article-title></title-group><contrib-group><contrib contrib-type="author" id="au1"><name><surname>Goh</surname><given-names>Gerard Kian-Meng</given-names></name><email>gohsbiocomputing@yahoo.com</email><xref rid="aff1" ref-type="aff">a</xref><xref rid="cor1" ref-type="corresp">∗</xref></contrib><contrib contrib-type="author" id="au2"><name><surname>Dunker</surname><given-names>A. Keith</given-names></name><xref rid="aff2" ref-type="aff">b</xref></contrib><contrib contrib-type="author" id="au3"><name><surname>Foster</surname><given-names>James A.</given-names></name><xref rid="aff3" ref-type="aff">c</xref><xref rid="aff4" ref-type="aff">d</xref></contrib><contrib contrib-type="author" id="au4"><name><surname>Uversky</surname><given-names>Vladimir N.</given-names></name><xref rid="aff5" ref-type="aff">e</xref><xref rid="aff6" ref-type="aff">f</xref></contrib></contrib-group><aff id="aff1"><label>a</label>Goh's BioComputing, Singapore</aff><aff id="aff2"><label>b</label>Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, USA</aff><aff id="aff3"><label>c</label>Department of Biological Sciences, University of Idaho, Moscow, ID, USA</aff><aff id="aff4"><label>d</label>Institute for Bioinformatics and Evolutionary Studies, University of Idaho, Moscow, ID, USA</aff><aff id="aff5"><label>e</label>Department of Molecular Medicine, Morsani College of Medicine, University of South Florida, Tampa, FL, USA</aff><aff id="aff6"><label>f</label>Institute for Biological Instrumentation, Russian Academy of Sciences, Pushchino, Moscow region, Russia</aff><author-notes><corresp id="cor1"><label>∗</label>Corresponding author. <email>gohsbiocomputing@yahoo.com</email></corresp></author-notes><pub-date pub-type="pmc-release"><day>31</day><month>3</month><year>2020</year></pub-date><pmc-comment> PMC Release delay is 0 months and 0 days and was based on .</pmc-comment>
<pub-date pub-type="ppub"><month>7</month><year>2020</year></pub-date><pub-date pub-type="epub"><day>31</day><month>3</month><year>2020</year></pub-date><volume>144</volume><fpage>104177</fpage><lpage>104177</lpage><history><date date-type="received"><day>17</day><month>2</month><year>2020</year></date><date date-type="rev-recd"><day>18</day><month>3</month><year>2020</year></date><date date-type="accepted"><day>27</day><month>3</month><year>2020</year></date></history><permissions><copyright-statement>© 2020 Elsevier Ltd. All rights reserved.</copyright-statement><copyright-year>2020</copyright-year><copyright-holder>Elsevier Ltd</copyright-holder><license><license-p>Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.</license-p></license></permissions><abstract id="abs0010"><p>The coronavirus (CoV) family consists of viruses that infects a variety of animals including humans with various levels of respiratory and fecal-oral transmission levels depending on the behavior of the viruses' natural hosts and optimal viral fitness. A model to classify and predict the levels of respective respiratory and fecal-oral transmission potentials of the various viruses was built before the outbreak of MERS-CoV using AI and empirically-based molecular tools to predict the disorder level of proteins. Using the percentages of intrinsic disorder (PID) of the nucleocapsid (N) and membrane (M) proteins of CoV, the model easily clustered the viruses into three groups with the SARS-CoV (M PID = 8%, N PID = 50%) falling into Category B, in which viruses have intermediate levels of both respiratory and fecal-oral transmission potentials. Later, MERS-CoV (M PID = 9%, N PID = 44%) was found to be in Category C, which consists of viruses with lower respiratory transmission potential but with higher fecal-oral transmission capabilities. Based on the peculiarities of disorder distribution, the SARS-CoV-2 (M PID = 6%, N PID = 48%) has to be placed in Category B. Our data show however, that the SARS-CoV-2 is very strange with one of the hardest protective outer shell, (M PID = 6%) among coronaviruses. This means that it might be expected to be highly resilient in saliva or other body fluids and outside the body. An infected body is likelier to shed greater numbers of viral particles since the latter is more resistant to antimicrobial enzymes in body fluids. These particles are also likelier to remain active longer. These factors could account for the greater contagiousness of the SARS-CoV-2 and have implications for efforts to prevent its spread.</p></abstract><abstract abstract-type="author-highlights" id="abs0015"><title>Highlights</title><p><list list-type="simple" id="ulist0010"><list-item id="u0010"><label>•</label><p id="p0010">AI molecular tools cluster percentages of intrinsic disorder (PID) of the nucleocapsid (N) and membrane (M) proteins.</p></list-item><list-item id="u0020"><label>•</label><p id="p0020">SARS-CoV-2 has intermediate levels of respiratory and fecal-oral transmission potentials.</p></list-item><list-item id="u0025"><label>•</label><p id="p0025">SARS-CoV-2 is very strange with one of the hardest protective outer shell, (M PID=6%) among coronaviruses.</p></list-item><list-item id="u0030"><label>•</label><p id="p0030">Because of its harder outer shell, SARS-CoV-2 is likely to be more resistant to antimicrobial enzymes in body fluids.</p></list-item><list-item id="u0035"><label>•</label><p id="p0035">As a result, an infected body is likelier to shed greater numbers of viral particles that remain active longer.</p></list-item></list></p></abstract><kwd-group id="kwrds0010"><title>Keywords</title><kwd>Intrinsically disordered protein</kwd><kwd>Nucleocapsid</kwd><kwd>CoV</kwd><kwd>Coronavirus</kwd><kwd>Spread</kwd><kwd>Membrane</kwd><kwd>SARS</kwd><kwd>MERS</kwd><kwd>COVID</kwd></kwd-group></article-meta></front></pmc></record>Pour manipuler ce document sous Unix (Dilib)
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