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Detection of swine-origin influenza A (H1N1) viruses using a localized surface plasmon coupled fluorescence fiber-optic biosensor

  • Ying Feng Chang
  • , Sheng Fan Wang
  • , Jason C. Huang
  • , Li Chen Su
  • , Ling Yao
  • , Ying Chang Li
  • , Suh Chin Wu
  • , Yi Ming A. Chen
  • , Jo Ping Hsieh
  • , Chien Chou*
  • *Corresponding author for this work
  • National Yang Ming Chiao Tung University
  • Taipei City Hospital
  • Chang Gung University
  • National Central University
  • National Tsing Hua University

Research output: Contribution to journalJournal Article peer-review

59 Scopus citations

Abstract

Swine-origin influenza A (H1N1) virus (S-OIV) was identified as a new reassortant strain of influenza A virus in April 2009 and led to an influenza pandemic. Accurate and timely diagnoses are crucial for the control of influenza disease. We developed a localized surface plasmon coupled fluorescence fiber-optic biosensor (LSPCF-FOB) which combines a sandwich immunoassay with the LSP technique using antibodies against the hemagglutinin (HA) proteins of S-OIVs. The detection limit of the LSPCF-FOB for recombinant S-OIV H1 protein detection was estimated at 13.9pg/mL, which is 103-fold better than that of conventional capture ELISA when using the same capture antibodies. For clinical S-OIV isolates measurement, meanwhile, the detection limit of the LSPCF-FOB platform was calculated to be 8.25×104copies/mL, compared with 2.06×106copies/mL using conventional capture ELISA. Furthermore, in comparison with the influenza A/B rapid test, the detection limit of the LSPCF-FOB for S-OIV was almost 50-fold in PBS solution and 25-fold lower in mimic solution, which used nasal mucosa from healthy donors as the diluent. The findings of this study therefore indicate that the high detection sensitivity and specificity of the LSPCF-FOB make it a potentially effective diagnostic tool for clinical S-OIV infection and this technique has the potential to be applied to the development of other clinical microbe detection platforms.

Original languageEnglish
Pages (from-to)1068-1073
Number of pages6
JournalBiosensors and Bioelectronics
Volume26
Issue number3
DOIs
StatePublished - 15 11 2010

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Fiber-optic biosensor
  • Gold nanoparticle
  • H1N1
  • Localized surface plasmon
  • Swine-origin influenza A virus

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