Global Surveillance of Emerging Influenza Virus Genotypes by Mass Spectrometry

Rangarajan Sampath(Ionis Pharmaceuticals (United States)), Kevin L. Russell(Naval Health Research Center), Christian Massire(Ionis Pharmaceuticals (United States)), Mark W. Eshoo(Ionis Pharmaceuticals (United States)), Vanessa Harpin(Ionis Pharmaceuticals (United States)), Lawrence B. Blyn(Ionis Pharmaceuticals (United States)), Rachael Melton(Ionis Pharmaceuticals (United States)), Cristina Ivy(Ionis Pharmaceuticals (United States)), Thuy Pennella(Ionis Pharmaceuticals (United States)), Feng Li(Ionis Pharmaceuticals (United States)), Harold Levene(Ionis Pharmaceuticals (United States)), Thomas A. Hall(Ionis Pharmaceuticals (United States)), Brian Libby(Ionis Pharmaceuticals (United States)), Nancy Fan(Ionis Pharmaceuticals (United States)), Demetrius J. Walcott(Ionis Pharmaceuticals (United States)), Raymond Ranken(Ionis Pharmaceuticals (United States)), Michael Pear(Ionis Pharmaceuticals (United States)), Amy Schink(Ionis Pharmaceuticals (United States)), Jose R. Gutierrez(Ionis Pharmaceuticals (United States)), Jared J. Drader(Ionis Pharmaceuticals (United States)), David Moore(Ionis Pharmaceuticals (United States)), David Metzgar(Naval Health Research Center), Lynda Addington(Naval Health Research Center), Richard E. Rothman(Johns Hopkins University), Charlotte A. Gaydos(Johns Hopkins University), Samuel Yang(Johns Hopkins University), Kirsten St. George(Wadsworth Center), Meghan Fuschino(New York State Department of Health), Amy B. Dean(Wadsworth Center), David E. Stallknecht(University of Georgia), Ginger Goekjian(University of Georgia), Samuel Yingst(United States Naval Medical Research Unit III), Marshall R. Monteville(United States Naval Medical Research Unit III), Magdi D. Saad(United States Naval Medical Research Unit III), Chris A. Whitehouse(United States Army Medical Research Institute of Infectious Diseases), Carson Baldwin(United States Army Medical Research Institute of Infectious Diseases), Karl Rudnick(Science Applications International Corporation (United States)), Steven A. Hofstadler(Ionis Pharmaceuticals (United States)), Stanley M. Lemon(The University of Texas Medical Branch at Galveston), David J. Ecker(Ionis Pharmaceuticals (United States))
PLoS ONE
May 30, 2007
Cited by 128Open Access
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Abstract

BACKGROUND: Effective influenza surveillance requires new methods capable of rapid and inexpensive genomic analysis of evolving viral species for pandemic preparedness, to understand the evolution of circulating viral species, and for vaccine strain selection. We have developed one such approach based on previously described broad-range reverse transcription PCR/electrospray ionization mass spectrometry (RT-PCR/ESI-MS) technology. METHODS AND PRINCIPAL FINDINGS: Analysis of base compositions of RT-PCR amplicons from influenza core gene segments (PB1, PB2, PA, M, NS, NP) are used to provide sub-species identification and infer influenza virus H and N subtypes. Using this approach, we detected and correctly identified 92 mammalian and avian influenza isolates, representing 30 different H and N types, including 29 avian H5N1 isolates. Further, direct analysis of 656 human clinical respiratory specimens collected over a seven-year period (1999-2006) showed correct identification of the viral species and subtypes with >97% sensitivity and specificity. Base composition derived clusters inferred from this analysis showed 100% concordance to previously established clades. Ongoing surveillance of samples from the recent influenza virus seasons (2005-2006) showed evidence for emergence and establishment of new genotypes of circulating H3N2 strains worldwide. Mixed viral quasispecies were found in approximately 1% of these recent samples providing a view into viral evolution. CONCLUSION/SIGNIFICANCE: Thus, rapid RT-PCR/ESI-MS analysis can be used to simultaneously identify all species of influenza viruses with clade-level resolution, identify mixed viral populations and monitor global spread and emergence of novel viral genotypes. This high-throughput method promises to become an integral component of influenza surveillance.


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