Rapid changes in influenza A virus (IAV) antigenicity create challenges in surveillance, disease diagnosis, and vaccine development. Further, serological methods for studying antigenic properties of influenza viruses often rely on animal models and therefore may not fully reflect the dynamics of human immunity. We hypothesized that arrays of human monoclonal antibodies (hmAbs) to influenza could be employed in a pattern-recognition approach to expedite IAV serology and to study the antigenic evolution of newly emerging viruses. Using the multiplex, label-free Arrayed Imaging Reflectometry (AIR) platform, we have demonstrated that such arrays readily discriminated among various subtypes of IAVs, including H1, H3 seasonal strains, and avian-sourced human H7 viruses. Array responses also allowed the first determination of antigenic relationships among IAV strains directly from hmAb responses. Finally, correlation analysis of antibody binding to all tested IAV subtypes allowed efficient identification of broadly reactive clones. In addition to specific applications in the context of understanding influenza biology with potential utility in universal flu vaccine development, these studies validate AIR as a platform technology for studying antigenic properties of viruses and also antibody properties in a high-throughput manner. We further anticipate that this approach will facilitate advances in the study of other viral pathogens.
Hanyuan Zhang, Carole Henry, Christopher S Anderson, Aitor Nogales, Marta L DeDiego, Joseph Bucukovski, Luis Martinez-Sobrido, Patrick C Wilson, David J Topham, Benjamin L Miller. (2018). Crowd on a chip: label-free human monoclonal antibody arrays for serotyping influenza. Analytical Chemistry, 90(15)