"Sequence-First:" Integration of Next Generation Sequencing to advance influenza virus antigenic surveillance and preparedness

The Centers for Disease Control and Prevention, Influenza Division tracks influenza A and B virus evolution and evaluates antigenic drift between circulating strains and vaccines as part of its core public health surveillance... [ view full abstract ]

The Centers for Disease Control and Prevention, Influenza Division tracks influenza A and B virus evolution and evaluates antigenic drift between circulating strains and vaccines as part of its core public health surveillance mission. Twice yearly, antigenic and genotypic trends are reported to the World Health Organization to advise annual vaccine strain recommendations in the Northern and Southern Hemispheres. The inherent time-lines involved in comprehensive genetic, antigenic, and serological testing can delay real-time responses to changing surveillance trends despite extensive efforts between laboratories and international collaborators to support these efforts. Integration of a next generation sequencing (NGS) pipeline coupled with routine antigenic testing provides an ideal platform to better inform vaccine preparedness. Over the last few years, the CDC has used NGS to increase its capacity to characterize genomic information for specimens received. This initiative, dubbed “Sequence-First”, is intended to dramatically strengthen viral surveillance and vaccine strain selection through increased information and timeliness. Cross-referencing antigenic data with genomic sequence allows the detection of real-time shifts in the molecular determinants of antigenicity. Consequently, phenotypic changes detected by hemagglutination inhibition (HI) assay may be correlated with specific nucleotide substitutions and further inferences among other closely related sequences may be made. To demonstrate the capability of an integrated approach, we analyzed HI test records for hundreds of zoonotic influenza A virus strains (subtypes H5, H7, and H9) using antigenic cartography [1]. Next, we established antigenic clusters using Euclidean distance-based k-means clustering on these cartographic data. Integration of sequence data (both consensus and major/minor virus populations) from our IRMA-guided NGS pipeline [2] with these antigenic clusters provided a mechanism to link specific molecular determinants identified in H5, H7, and H9 influenza strains to the observed shifts in viral antigenicity. Directed application of collected, paired HI data and codon complete genome sequence records for historic changes in antigenicity will validate identified antigenic-genotypic links in our model. Furthermore, initial evaluation of smaller zoonotic data sets will enable optimization for the analysis of larger epidemic influenza A (H1 and H3 subtypes) and B viruses.

References:

[1] Smith DJ, Lapedes AS, de Jong JC, Bestebroer TM, Rimmelzwaan GF, Osterhaus AD, Fouchier RA. “Mapping the antigenic and genetic evolution of influenza virus.” Science 305, 5682 (2004).

[2] SS Shepard, S Meno, J Bahl, MM Wilson, J Barnes, and E Neuhaus. “Viral deep sequencing needs an adaptive approach: IRMA, the iterative refinement meta-assembler.” BMC Genomics 17, 708 (2016).