Shell disorder analysis predicts greater resilience of the SARS-CoV-2 (COVID-19) outside the body and in body fluids.
Identifieur interne : 000082 ( PubMed/Checkpoint ); précédent : 000081; suivant : 000083Shell 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 [Russie]Source :
- Microbial pathogenesis [ 1096-1208 ] ; 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.
DOI: 10.1016/j.micpath.2020.104177
PubMed: 32244041
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Electronic address: gohsbiocomputing@yahoo.com.</nlm:affiliation><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="2"><nlm:affiliation>Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN</wicri:regionArea><placeName><region type="state">Indiana</region></placeName></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="2"><nlm:affiliation>Department of Biological Sciences, University of Idaho, Moscow, ID, USA; Institute for Bioinformatics and Evolutionary Studies, University of Idaho, Moscow, ID, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Biological Sciences, University of Idaho, Moscow, ID, USA; Institute for Bioinformatics and Evolutionary Studies, University of Idaho, Moscow, ID</wicri:regionArea><placeName><region type="state">Idaho</region></placeName></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="4"><nlm:affiliation>Department of Molecular Medicine, Morsani College of Medicine, University of South Florida, Tampa, FL, USA; Institute for Biological Instrumentation, Russian Academy of Sciences, Pushchino, Moscow region, Russia.</nlm:affiliation><country xml:lang="fr">Russie</country><wicri:regionArea>Department of Molecular Medicine, Morsani College of Medicine, University of South Florida, Tampa, FL, USA; Institute for Biological Instrumentation, Russian Academy of Sciences, Pushchino, Moscow region</wicri:regionArea><orgName type="university">Université de Floride du Sud</orgName><placeName><settlement type="city">Tampa</settlement><region type="state">Floride</region></placeName></affiliation></author></analytic><series><title level="j">Microbial pathogenesis</title><idno type="eISSN">1096-1208</idno><imprint><date when="2020" type="published">2020</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">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.</div></front></TEI><pubmed><MedlineCitation Status="Publisher" Owner="NLM"><PMID Version="1">32244041</PMID><DateRevised><Year>2020</Year><Month>04</Month><Day>19</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">1096-1208</ISSN><JournalIssue CitedMedium="Internet"><Volume>144</Volume><PubDate><Year>2020</Year><Month>Mar</Month><Day>31</Day></PubDate></JournalIssue><Title>Microbial pathogenesis</Title><ISOAbbreviation>Microb. Pathog.</ISOAbbreviation></Journal><ArticleTitle>Shell disorder analysis predicts greater resilience of the SARS-CoV-2 (COVID-19) outside the body and in body fluids.</ArticleTitle><Pagination><MedlinePgn>104177</MedlinePgn></Pagination><ELocationID EIdType="pii" ValidYN="Y">S0882-4010(20)30464-2</ELocationID><ELocationID EIdType="doi" ValidYN="Y">10.1016/j.micpath.2020.104177</ELocationID><Abstract><AbstractText>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.</AbstractText><CopyrightInformation>Copyright © 2020 Elsevier Ltd. All rights reserved.</CopyrightInformation></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Goh</LastName><ForeName>Gerard Kian-Meng</ForeName><Initials>GK</Initials><AffiliationInfo><Affiliation>Goh's BioComputing, Singapore. Electronic address: gohsbiocomputing@yahoo.com.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Dunker</LastName><ForeName>A Keith</ForeName><Initials>AK</Initials><AffiliationInfo><Affiliation>Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Foster</LastName><ForeName>James A</ForeName><Initials>JA</Initials><AffiliationInfo><Affiliation>Department of Biological Sciences, University of Idaho, Moscow, ID, USA; Institute for Bioinformatics and Evolutionary Studies, University of Idaho, Moscow, ID, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Uversky</LastName><ForeName>Vladimir N</ForeName><Initials>VN</Initials><AffiliationInfo><Affiliation>Department of Molecular Medicine, Morsani College of Medicine, University of South Florida, Tampa, FL, USA; Institute for Biological Instrumentation, Russian Academy of Sciences, Pushchino, Moscow region, Russia.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2020</Year><Month>03</Month><Day>31</Day></ArticleDate></Article><MedlineJournalInfo><Country>England</Country><MedlineTA>Microb Pathog</MedlineTA><NlmUniqueID>8606191</NlmUniqueID><ISSNLinking>0882-4010</ISSNLinking></MedlineJournalInfo><CitationSubset>IM</CitationSubset><KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="N">COVID</Keyword><Keyword MajorTopicYN="N">CoV</Keyword><Keyword MajorTopicYN="N">Coronavirus</Keyword><Keyword MajorTopicYN="N">Intrinsically disordered protein</Keyword><Keyword MajorTopicYN="N">MERS</Keyword><Keyword MajorTopicYN="N">Membrane</Keyword><Keyword MajorTopicYN="N">Nucleocapsid</Keyword><Keyword MajorTopicYN="N">SARS</Keyword><Keyword MajorTopicYN="N">Spread</Keyword></KeywordList><CoiStatement>Declaration of competing interest GKMG. is an independent researcher and the owner of Goh's BioComputing, Singapore. GKMG. has also written a book (“Viral Shapeshifters: Strange Behaviors of HIV and Other Viruses”) on a related subject. The authors have no other potential conflict of interests.</CoiStatement></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2020</Year><Month>02</Month><Day>17</Day></PubMedPubDate><PubMedPubDate PubStatus="revised"><Year>2020</Year><Month>03</Month><Day>18</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2020</Year><Month>03</Month><Day>27</Day></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2020</Year><Month>4</Month><Day>4</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2020</Year><Month>4</Month><Day>4</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2020</Year><Month>4</Month><Day>4</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>aheadofprint</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">32244041</ArticleId><ArticleId IdType="pii">S0882-4010(20)30464-2</ArticleId><ArticleId IdType="doi">10.1016/j.micpath.2020.104177</ArticleId><ArticleId IdType="pmc">PMC7118597</ArticleId></ArticleIdList></PubmedData></pubmed><affiliations><list><country><li>Russie</li><li>Singapour</li><li>États-Unis</li></country><region><li>Floride</li><li>Idaho</li><li>Indiana</li></region><settlement><li>Tampa</li></settlement><orgName><li>Université de Floride du Sud</li></orgName></list><tree><country name="Singapour"><noRegion><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></noRegion></country><country name="États-Unis"><region name="Indiana"><name sortKey="Dunker, A Keith" sort="Dunker, A Keith" uniqKey="Dunker A" first="A Keith" last="Dunker">A Keith Dunker</name></region><name sortKey="Foster, James A" sort="Foster, James A" uniqKey="Foster J" first="James A" last="Foster">James A. Foster</name></country><country name="Russie"><region name="Floride"><name sortKey="Uversky, Vladimir N" sort="Uversky, Vladimir N" uniqKey="Uversky V" first="Vladimir N" last="Uversky">Vladimir N. Uversky</name></region></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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