Optimization of a high-throughput shotgun immunoproteomics pipeline for antigen identification.

Identification of proteins which initiate and/or perpetuate adaptive immune responses has potential to greatly impact pre-clinical and clinical work across numerous fields. To date, however, the methodologies available to identify antigens responsible for driving adaptive immune responses have been plagued by numerous issues which have drastically limited their widespread adoption. Therefore, in this study, we sought to optimize a shotgun immunoproteomics approach to alleviate these persistent issues and create a high-throughput, quantitative methodology for antigen identification. Three individual components of a previously published approach, namely the protein extraction, antigen elution, and LC-MS/MS analysis steps, were optimized in a systematic manner. These studies determined that preparation of protein extracts using a one-step tissue disruption method in immunoprecipitation (IP) buffer, eluting antigens from affinity chromatography columns with 1% trifluoroacetic acid (TFA), and TMT-labeling & multiplexing equal volumes of eluted samples for LC-MS/MS analysis, resulted in quantitative longitudinal antigen identification, with reduced variability between replicates and increased total number of antigens identified. This optimized pipeline provides a multiplexed, highly reproducible, and fully quantitative approach to antigen identification which is broadly applicable to determine the role of antigenic proteins in inciting (i.e., primary antigens) and perpetuating (i.e., secondary antigens) a wide range of diseases. SIGNIFICANCE: Using a systematic, hypothesis-driven approach, we identified potential improvements for three individual steps of a previously published approach for antigen-identification. Optimization of each step created a methodology which resolved many of the persistent issues associated with previous antigen identification approaches. The optimized high-throughput shotgun immunoproteomics approach described herein identifies more than five times as many unique antigens as the previously published method, greatly reduces protocol cost and mass spectrometry time per experiment, minimizes both inter- and intra-experimental variability, and ensures each experiment is fully quantitative. Ultimately, this optimized antigen identification approach has the potential to facilitate novel antigen identification studies, allowing evaluation of the adaptive immune response in a longitudinal manner and encourage innovations in a wide array of fields.