Evaluation of multiplex assay platforms for detection of influenza hemagglutinin subtype specific antibody responses.
J Virol Methods
; 243: 61-67, 2017 05.
Article
en En
| MEDLINE
| ID: mdl-28108183
Influenza hemagglutination inhibition (HI) and virus microneutralization assays (MN) are widely used for seroprevalence studies. However, these assays have limited field portability and are difficult to fully automate for high throughput laboratory testing. To address these issues, three multiplex influenza subtype-specific antibody detection assays were developed using recombinant hemagglutinin antigens in combination with Chembio, Luminex®, and ForteBio® platforms. Assay sensitivity, specificity, and subtype cross-reactivity were evaluated using a panel of well characterized human sera. Compared to the traditional HI, assay sensitivity ranged from 87% to 92% and assay specificity in sera collected from unexposed persons ranged from 65% to 100% across the platforms. High assay specificity (86-100%) for A(H5N1) rHA was achieved for sera from exposed or unexposed to hetorosubtype influenza HAs. In contrast, assay specificity for A(H1N1)pdm09 rHA using sera collected from A/Vietnam/1204/2004 (H5N1) vaccinees in 2008 was low (22-30%) in all platforms. Although cross-reactivity against rHA subtype proteins was observed in each assay platform, the correct subtype specific responses were identified 78%-94% of the time when paired samples were available for analysis. These results show that high throughput and portable multiplex assays that incorporate rHA can be used to identify influenza subtype specific infections.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Pruebas Serológicas
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Glicoproteínas Hemaglutininas del Virus de la Influenza
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Gripe Humana
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Ensayos Analíticos de Alto Rendimiento
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Anticuerpos Antivirales
Tipo de estudio:
Diagnostic_studies
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Evaluation_studies
Límite:
Adolescent
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Adult
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Aged
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Aged80
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Child
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Child, preschool
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Humans
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Middle aged
Idioma:
En
Revista:
J Virol Methods
Año:
2017
Tipo del documento:
Article