One of the main challenges in compiling the complete collection of protein antigens from pathogens for the selection of vaccine candidates or intervention targets is to acquire a broad enough representation of them to be recognized by the highly diversified immunoglobulin repertoire in human populations. Dried serum spot sampling (DSS) retains a large repertoire of circulating immunoglobulins from each individual that can be representative of a population, according to the sample size. In this work, shotgun proteomics of an infectious pathogen based on DSS sampling coupled with IgM immunoprecipitation, liquid chromatography-mass spectrometry (LC-MS/MS), and bioinformatic analyses was combined to characterize the circulating IgM antigenome. Serum samples from a malaria endemic region at different clinical statuses were studied to optimize IgM binding efficiency and antibody leaching by varying serum/immunomagnetic bead ratios and elution conditions. The method was validated using Plasmodium falciparum extracts identifying 110 of its IgM-reactive antigens while minimizing the presence of human proteins and antibodies. Furthermore, the IgM antigen recognition profile differentiated between malaria-infected and noninfected individuals at the time of sampling. We conclude that a shotgun proteomics approach offers advantages in providing a high-throughput, reliable, and clean way to identify IgM-recognized antigens from trace amounts of serum. The mass spectrometry raw data and metadata have been deposited with ProteomeXchange via MassIVE with the PXD identifier PXD043800.
Keywords: antigens; immunoglobulin; immunomics; immunoprecipitation; infection; malaria.