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UBC Theses and Dissertations

Serological immune profiling using mass spectrometry Bundala, Matthew Matus

Abstract

The adaptive immune system is a fantastically complex system comprised of specialized cells, organs and molecules. When properly functioning, our adaptive immune system is continually responding to, and protecting us from, a myriad of disease threats ranging from viruses to cancer. Immune dysfunction leaves us vulnerable to pathogens and can result in autoimmune disorders. Despite the adaptive immune system’s central importance in health, efficient immune profiling methods, and in particular approaches capable of functional characterization of adaptive immune responses, are still in their infancy. In this thesis I present a rapid and scalable serological immune profiling protocol based on antibody mediated identification of antigens (AMIDA). Serological antibodies are extracted from serum, covalently bound to magnetic beads, and washed with a panel of antigens. The bound immunoreactive antigens are then eluted, in-gel trypsin digested, and identified by tandem mass spectrometry. I demonstrate the application of this protocol for profiling immune responses of nine patients to a set of bacterial pathogens including Escherichia coli, Pseudomonas aeruginosa, Klebsiella pneumoniae, and Salmonella typhimurium. The identified list of antigens includes outer membrane proteins known to cause immune reaction, as well as novel immunogenic proteins. The data allows for characterization of differences in the global antigen reactivity between different patients and identifies individuals having pronounced pathogen recognition. In a small study I show that K. pneumoniae and P. aeruginosa are generally more reactive across the pathogens tested, and that S. typhimurium showed the weakest reactivity. The improved AMIDA-based protocol allows for efficient identification of immunoreactive antigens and the profiling of patient reactivity. When coupled with complementary technologies such as immune repertoire sequencing this approach can be applied to high-value applications including vaccine development, biomarker identification, and therapeutic antibody discovery.

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Attribution-NonCommercial-NoDerivatives 4.0 International