Literature DB >> 24402634

Simultaneous discrimination and detection of influenza A(H1N1)pdm09 and seasonal influenza A viruses using a rapid immunogold biosensor.

Chayachon Apiwat1, Natpapas Wiriyachaiporn, Weerakanya Maneeprakorn, Tararaj Dharakul, Charin Thepthai, Pilaipan Puthavathana, Sontana Siritantikorn, Navin Horthongkham.   

Abstract

A rapid immunogold biosensor for the simultaneous discrimination of influenza A(H1N1)pdm09 and seasonal influenza A viruses was developed successfully. Monoclonal antibodies (mAbs) that were specific for the hemagglutinin protein of the A(H1N1)pdm09 virus were produced, and the best mAb pairs were selected. Using an mAb that was specific for the influenza A nucleoprotein, a rapid immunogold biosensor for the discrimination and detection of A(H1N1)pdm09/seasonal influenza viruses was developed. When tested with 72 virus isolates, the system achieved 100 % detection of the A(H1N1)pdm09 virus without cross-reactivity against seasonal influenza A (H1, H3 subtypes) and B viruses, parainfluenza viruses, respiratory syncytial viruses, and adenoviruses. The detection limits for A(H1N1)pdm09 and seasonal strains were 5 × 10(2)-7.5 × 10(3) and 1 × 10(3)-7.5 × 10(5) TCID50/mL, respectively. When tested with 49 clinical specimens, the specificity was high (100 %). The sensitivity for the detection of A(H1N1)pdm09 and seasonal strains was 90 % and 100 %, respectively, which correlated with the results of real-time reverse transcription polymerase chain reaction as a reference method. The ability of the system to detect and discriminate the A(H1N1)pdm09 strain from the seasonal strains suggests that this method may be beneficial for investigation of outbreaks and diagnostic applications. Furthermore, this method might be a useful platform for developing a rapid diagnostic system for the simultaneous discrimination of other influenza virus subtypes during future outbreaks.

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Year:  2014        PMID: 24402634     DOI: 10.1007/s00705-013-1974-2

Source DB:  PubMed          Journal:  Arch Virol        ISSN: 0304-8608            Impact factor:   2.574


  1 in total

Review 1.  Detecting and Predicting Emerging Disease in Poultry With the Implementation of New Technologies and Big Data: A Focus on Avian Influenza Virus.

Authors:  Jake Astill; Rozita A Dara; Evan D G Fraser; Shayan Sharif
Journal:  Front Vet Sci       Date:  2018-10-30
  1 in total

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