A general method for characterization of humoral immunity induced by a vaccine or infection

Abstract A universal system to diagnose disease, characterize infection or evaluate the response to a vaccine would be useful. Towards this end we introduce a machine-readable platform that we term “Immunosignaturing”. Rather than attempt to identify antibodies one by one, we splay the entire immune response across an array of 10,000 random sequence peptides. This segregates serum antibodies sufficiently to group and characterize responses caused by disease or vaccination. In the present study, we explore in detail the murine immunosignature to influenza A/PR/8/34 immunization and subsequent challenge. Even though the peptides are random sequence, the response to immunization and challenge is quite apparent. We find that the immunosignatures contained information not evident in whole virus ELISA. Antibody recognition of 283 influenza-specific peptides increased upon immunization and remained elevated for 211 days post-challenge. A set of 65 peptides, which overlapped 39 of the peptides that were consistent across time, was capable of distinguishing mice based on infectious dose, while whole virus ELISA could not. These peptide populations are consistently recognized in independent biological replicates of infection and are largely, but not solely, composed of virus reactive antibodies. The immunosignaturing analysis was expanded to analysis of human recipients of the 2006/2007 seasonal influenza vaccine. We find that 30 peptides are significantly recognized by all donors 21 days post-immunization and have the power to distinguish immune from pre-immune samples. Taken together the data suggest that immunosignaturing on a random peptide array can serve as a universal platform to assess antibody status in ways that cannot be replicated by conventional immunological assays.