Year: 2026
Type: preprint
Abstract: Mass spectrometry-based immunopeptidomics is essential for the direct identification of HLA-presented peptides, but its application to low-input and clinical samples remains challenging. In this study, we present an optimized DDA-PASEF-based workflow to improve HLA class I peptide coverage. First, we optimized a magnetic bead-based sample preparation protocol to support analysis from reduced starting material and increase compatibility with automation. We then evaluated LC gradient length and column dimensions to define complementary configurations for high-throughput and high-coverage analysis. For MS acquisition, we fine-tuned key parameters, including ion accumulation time, number of PASEF scans, ion mobility range, and polygon filtering, to improve sensitivity while maintaining a suitable cycle time and limiting pre-CID truncations. The customized polygon filter improved the detection of singly charged HLA class I peptides, thereby broadening the identified immunopeptide repertoire. Finally, TIMS2Rescore was integrated to improve confidence in peptide identification. Overall, this optimized workflow improves HLA class I immunopeptide coverage across different sample types, even from low injected sample amounts, supporting its future applicability to clinically relevant samples.
Language: English
Subfield: Spectroscopy
Field: Chemistry
Domain: Physical Sciences
Open Access status: green
Funders: European Commission, Agence Nationale de la Recherche, Institut National de la Santé et de la Recherche Médicale, Fonds Wetenschappelijk Onderzoek, Université de Strasbourg, Universiteit Gent, Centre National de la Recherche Scientifique, HORIZON EUROPE Framework Programme, Research Executive Agency, CHIST-ERA
OpenAlex ID: W7225245412