A Competitive Library-Free DIA Workflow for Immunopeptidomics Data

Analysis of the immunopeptidome affords insight into disease mechanisms and paves way for the development of targeted therapies. MS-based immunopeptidomics methods still widely rely on data dependent acquisition while the remainder of the proteomics field has widely opted
instead for data independent approaches. Owing to an exponentially larger non-tryptic search space, library-free DIA analysis of immunopeptides presents a unique computational challenge. To address these challenges, we improved directDIA^® in Spectronaut^® to make library-free analysis of immunopeptidomics competitive. We evaluated DDA, library-based, and library-free DIA approaches to evaluate the performance of each with regards to extracting meaningful biological information from immunopeptidomics samples. With our improvements, library-free DIA identifies more biologically relevant peptides with high confidence.