Rapid detection and non-subjective characterisation of infectious bronchitis virus isolates using high-resolution melt curve analysis and a mathematical model
Identifieur interne : 000874 ( Pmc/Checkpoint ); précédent : 000873; suivant : 000875Rapid detection and non-subjective characterisation of infectious bronchitis virus isolates using high-resolution melt curve analysis and a mathematical model
Auteurs : Kylie Hewson ; Amir H. Noormohammadi ; Joanne M. Devlin ; Karim Mardani ; Jagoda IgnjatovicSource :
- Archives of Virology [ 0304-8608 ] ; 2009.
Abstract
Infectious bronchitis virus (IBV) is a coronavirus that causes upper respiratory, renal and/or reproductive diseases with high morbidity in poultry. Classification of IBV is important for implementation of vaccination strategies to control the disease in commercial poultry. Currently, the lengthy process of sequence analysis of the IBV S1 gene is considered the gold standard for IBV strain identification, with a high nucleotide identity (e.g. ≥95%) indicating related strains. However, this gene has a high propensity to mutate and/or undergo recombination, and alone it may not be reliable for strain identification. A real-time polymerase chain reaction (RT-PCR) combined with high-resolution melt (HRM) curve analysis was developed based on the 3′UTR of IBV for rapid detection and classification of IBV from commercial poultry. HRM curves generated from 230 to 435-bp PCR products of several IBV strains were subjected to further analysis using a mathematical model also developed during this study. It was shown that a combination of HRM curve analysis and the mathematical model could reliably group 189 out of 190 comparisons of pairs of IBV strains in accordance with their 3′UTR and S1 gene identities. The newly developed RT-PCR/HRM curve analysis model could detect and rapidly identify novel and vaccine-related IBV strains, as confirmed by S1 gene and 3′UTR nucleotide sequences. This model is a rapid, reliable, accurate and non-subjective system for detection of IBVs in poultry flocks.
Url:
DOI: 10.1007/s00705-009-0357-1
PubMed: 19301093
PubMed Central: 7086978
Affiliations:
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Noormohammadi</name><affiliation><nlm:aff id="Aff1"><institution-wrap><institution-id institution-id-type="GRID">grid.1008.9</institution-id><institution-id institution-id-type="ISNI">000000012179088X</institution-id><institution>Department of Veterinary Science,</institution><institution>The University of Melbourne,</institution></institution-wrap>250 Princes Highway Werribee, Melbourne, VIC 3030 Australia</nlm:aff><wicri:noCountry code="subfield">VIC 3030 Australia</wicri:noCountry></affiliation></author><author><name sortKey="Devlin, Joanne M" sort="Devlin, Joanne M" uniqKey="Devlin J" first="Joanne M." last="Devlin">Joanne M. Devlin</name><affiliation><nlm:aff id="Aff2"><institution-wrap><institution-id institution-id-type="GRID">grid.1008.9</institution-id><institution-id institution-id-type="ISNI">000000012179088X</institution-id><institution>Department of Veterinary Science,</institution><institution>The University of Melbourne,</institution></institution-wrap>Parkville, Melbourne, VIC 3010 Australia</nlm:aff><wicri:noCountry code="subfield">VIC 3010 Australia</wicri:noCountry></affiliation></author><author><name sortKey="Mardani, Karim" sort="Mardani, Karim" uniqKey="Mardani K" first="Karim" last="Mardani">Karim Mardani</name><affiliation><nlm:aff id="Aff3"><institution-wrap><institution-id institution-id-type="GRID">grid.412763.5</institution-id><institution-id institution-id-type="ISNI">0000000404428645</institution-id><institution>Faculty of Veterinary Medicine,</institution><institution>The University of Urmia,</institution></institution-wrap>Nazloo, Urmia, West Azarbaijan Iran</nlm:aff><wicri:noCountry code="subfield">West Azarbaijan Iran</wicri:noCountry></affiliation></author><author><name sortKey="Ignjatovic, Jagoda" sort="Ignjatovic, Jagoda" uniqKey="Ignjatovic J" first="Jagoda" last="Ignjatovic">Jagoda Ignjatovic</name><affiliation><nlm:aff id="Aff1"><institution-wrap><institution-id institution-id-type="GRID">grid.1008.9</institution-id><institution-id institution-id-type="ISNI">000000012179088X</institution-id><institution>Department of Veterinary Science,</institution><institution>The University of Melbourne,</institution></institution-wrap>250 Princes Highway Werribee, Melbourne, VIC 3030 Australia</nlm:aff><wicri:noCountry code="subfield">VIC 3030 Australia</wicri:noCountry></affiliation></author></analytic><series><title level="j">Archives of Virology</title><idno type="ISSN">0304-8608</idno><idno type="eISSN">1432-8798</idno><imprint><date when="2009">2009</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p>Infectious bronchitis virus (IBV) is a coronavirus that causes upper respiratory, renal and/or reproductive diseases with high morbidity in poultry. Classification of IBV is important for implementation of vaccination strategies to control the disease in commercial poultry. Currently, the lengthy process of sequence analysis of the IBV S1 gene is considered the gold standard for IBV strain identification, with a high nucleotide identity (e.g. ≥95%) indicating related strains. However, this gene has a high propensity to mutate and/or undergo recombination, and alone it may not be reliable for strain identification. A real-time polymerase chain reaction (RT-PCR) combined with high-resolution melt (HRM) curve analysis was developed based on the 3′UTR of IBV for rapid detection and classification of IBV from commercial poultry. HRM curves generated from 230 to 435-bp PCR products of several IBV strains were subjected to further analysis using a mathematical model also developed during this study. It was shown that a combination of HRM curve analysis and the mathematical model could reliably group 189 out of 190 comparisons of pairs of IBV strains in accordance with their 3′UTR and S1 gene identities. The newly developed RT-PCR/HRM curve analysis model could detect and rapidly identify novel and vaccine-related IBV strains, as confirmed by S1 gene and 3′UTR nucleotide sequences. This model is a rapid, reliable, accurate and non-subjective system for detection of IBVs in poultry flocks.</p></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Beaudette, Fr" uniqKey="Beaudette F">FR Beaudette</name></author><author><name sortKey="Hudson, Cb" uniqKey="Hudson C">CB Hudson</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Benson, Da" uniqKey="Benson D">DA Benson</name></author><author><name sortKey="Karsch Mizrachi, I" uniqKey="Karsch Mizrachi I">I Karsch-Mizrachi</name></author><author><name sortKey="Lipman, Dj" uniqKey="Lipman D">DJ Lipman</name></author><author><name sortKey="Ostell, J" uniqKey="Ostell J">J Ostell</name></author><author><name sortKey="Wheeler, Dl" uniqKey="Wheeler D">DL Wheeler</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Cavanagh, D" uniqKey="Cavanagh D">D 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<front><journal-meta><journal-id journal-id-type="nlm-ta">Arch Virol</journal-id><journal-id journal-id-type="iso-abbrev">Arch. Virol</journal-id><journal-title-group><journal-title>Archives of Virology</journal-title></journal-title-group><issn pub-type="ppub">0304-8608</issn><issn pub-type="epub">1432-8798</issn><publisher><publisher-name>Springer Vienna</publisher-name><publisher-loc>Vienna</publisher-loc></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">19301093</article-id><article-id pub-id-type="pmc">7086978</article-id><article-id pub-id-type="publisher-id">357</article-id><article-id pub-id-type="doi">10.1007/s00705-009-0357-1</article-id><article-categories><subj-group subj-group-type="heading"><subject>Original Article</subject></subj-group></article-categories><title-group><article-title>Rapid detection and non-subjective characterisation of infectious bronchitis virus isolates using high-resolution melt curve analysis and a mathematical model</article-title></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><name><surname>Hewson</surname><given-names>Kylie</given-names></name><address><phone>+61-3-97312030</phone><fax>+61-3-97312366</fax><email>khewson@unimelb.edu.au</email></address><xref ref-type="aff" rid="Aff1">1</xref></contrib><contrib contrib-type="author"><name><surname>Noormohammadi</surname><given-names>Amir H.</given-names></name><xref ref-type="aff" rid="Aff1">1</xref></contrib><contrib contrib-type="author"><name><surname>Devlin</surname><given-names>Joanne M.</given-names></name><xref ref-type="aff" rid="Aff2">2</xref></contrib><contrib contrib-type="author"><name><surname>Mardani</surname><given-names>Karim</given-names></name><xref ref-type="aff" rid="Aff3">3</xref></contrib><contrib contrib-type="author"><name><surname>Ignjatovic</surname><given-names>Jagoda</given-names></name><xref ref-type="aff" rid="Aff1">1</xref></contrib><aff id="Aff1"><label>1</label><institution-wrap><institution-id institution-id-type="GRID">grid.1008.9</institution-id><institution-id institution-id-type="ISNI">000000012179088X</institution-id><institution>Department of Veterinary Science,</institution><institution>The University of Melbourne,</institution></institution-wrap>250 Princes Highway Werribee, Melbourne, VIC 3030 Australia</aff><aff id="Aff2"><label>2</label><institution-wrap><institution-id institution-id-type="GRID">grid.1008.9</institution-id><institution-id institution-id-type="ISNI">000000012179088X</institution-id><institution>Department of Veterinary Science,</institution><institution>The University of Melbourne,</institution></institution-wrap>Parkville, Melbourne, VIC 3010 Australia</aff><aff id="Aff3"><label>3</label><institution-wrap><institution-id institution-id-type="GRID">grid.412763.5</institution-id><institution-id institution-id-type="ISNI">0000000404428645</institution-id><institution>Faculty of Veterinary Medicine,</institution><institution>The University of Urmia,</institution></institution-wrap>Nazloo, Urmia, West Azarbaijan Iran</aff></contrib-group><pub-date pub-type="epub"><day>20</day><month>3</month><year>2009</year></pub-date><pub-date pub-type="ppub"><year>2009</year></pub-date><volume>154</volume><issue>4</issue><elocation-id>649</elocation-id><history><date date-type="received"><day>14</day><month>10</month><year>2008</year></date><date date-type="accepted"><day>2</day><month>3</month><year>2009</year></date></history><permissions><copyright-statement>© Springer-Verlag 2009</copyright-statement><license><license-p>This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.</license-p></license></permissions><abstract id="Abs1"><p>Infectious bronchitis virus (IBV) is a coronavirus that causes upper respiratory, renal and/or reproductive diseases with high morbidity in poultry. Classification of IBV is important for implementation of vaccination strategies to control the disease in commercial poultry. Currently, the lengthy process of sequence analysis of the IBV S1 gene is considered the gold standard for IBV strain identification, with a high nucleotide identity (e.g. ≥95%) indicating related strains. However, this gene has a high propensity to mutate and/or undergo recombination, and alone it may not be reliable for strain identification. A real-time polymerase chain reaction (RT-PCR) combined with high-resolution melt (HRM) curve analysis was developed based on the 3′UTR of IBV for rapid detection and classification of IBV from commercial poultry. HRM curves generated from 230 to 435-bp PCR products of several IBV strains were subjected to further analysis using a mathematical model also developed during this study. It was shown that a combination of HRM curve analysis and the mathematical model could reliably group 189 out of 190 comparisons of pairs of IBV strains in accordance with their 3′UTR and S1 gene identities. The newly developed RT-PCR/HRM curve analysis model could detect and rapidly identify novel and vaccine-related IBV strains, as confirmed by S1 gene and 3′UTR nucleotide sequences. This model is a rapid, reliable, accurate and non-subjective system for detection of IBVs in poultry flocks.</p></abstract><kwd-group xml:lang="en"><title>Keywords</title><kwd>Vaccine Strain</kwd><kwd>Infectious Bronchitis Virus</kwd><kwd>Infectious Bronchitis Virus Strain</kwd><kwd>Infectious Bronchitis Virus Infection</kwd><kwd>Infectious Bronchitis Virus Isolate</kwd></kwd-group><custom-meta-group><custom-meta><meta-name>issue-copyright-statement</meta-name><meta-value>© Springer-Verlag 2009</meta-value></custom-meta></custom-meta-group></article-meta></front></pmc><affiliations><list></list><tree><noCountry><name sortKey="Devlin, Joanne M" sort="Devlin, Joanne M" uniqKey="Devlin J" first="Joanne M." last="Devlin">Joanne M. Devlin</name><name sortKey="Hewson, Kylie" sort="Hewson, Kylie" uniqKey="Hewson K" first="Kylie" last="Hewson">Kylie Hewson</name><name sortKey="Ignjatovic, Jagoda" sort="Ignjatovic, Jagoda" uniqKey="Ignjatovic J" first="Jagoda" last="Ignjatovic">Jagoda Ignjatovic</name><name sortKey="Mardani, Karim" sort="Mardani, Karim" uniqKey="Mardani K" first="Karim" last="Mardani">Karim Mardani</name><name sortKey="Noormohammadi, Amir H" sort="Noormohammadi, Amir H" uniqKey="Noormohammadi A" first="Amir H." last="Noormohammadi">Amir H. Noormohammadi</name></noCountry></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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