Finely tuned DDA-PASEF-based immunopeptidomics workflow enhances HLA class I coverage

Mass spectrometry-based immunopeptidomics facilitates the direct identification of HLA-presented peptides, yet its application to low-input and clinical samples poses challenges. Researchers have now developed an optimized workflow that enhances HLA class I peptide coverage. The protocol begins with a magnetic bead-based sample preparation method, enabling analysis from smaller starting quantities and improved compatibility with automation.

Researchers then examined liquid chromatography gradient length and column dimensions to identify the most suitable configurations for high-throughput and comprehensive sample analysis. Additionally, they meticulously fine-tuned several mass spectrometry (MS) acquisition parameters such as ion accumulation time, number of PASEF scans, ion mobility range, and polygon filtering. These adjustments aimed to increase sensitivity while preserving a reasonable cycle time and reducing pre-CID truncations.

A customized polygon filter was incorporated to enhance the detection of singly charged HLA class I peptides, thereby expanding the identified immunopeptide repertoire. Finally, TIMS2Rescore was integrated into the workflow to further improve confidence in peptide identification. Overall, this optimized immunopeptidomics workflow significantly improves HLA class I immunopeptide coverage across various sample types, even when starting from low injected sample amounts. This advancement holds promise for future applications in clinically relevant samples.