Systematic Workflow Optimization for Ultra-sensitive Targeted Immunopeptidomics

Epitope detection sensitivity remains a primary bottleneck in mass spectrometry (MS)-based immunopeptidomics, as conventional discovery-based workflows such as data-dependent (DDA) and data-independent acquisition (DIA) frequently lack the sensitivity required to detect ultra-low abundant targets. While these untargeted methods are powerful for mapping the general immunopeptidome, the stochastic nature of precursor selection and the presence of complex, chimeric spectra mean that rare species, such as viral or mutation-derived neoepitopes, often remain undetected. In this study, we present optiPRM+, an ultra-sensitive targeted-first workflow for the Orbitrap Exploris 480 platform that integrates systematically optimized targeted acquisition with untargeted DIA contextualization to bridge this sensitivity gap. Our approach centers on the empirical characterization of target peptides using direct infusion-MS to determine optimal fragmentation conditions and inclusion list-driven data-dependent acquisition (iDDA). To maximize signal-to-noise ratios for these trace-level targets, we employed ultra-high MS2 resolutions (up to 480,000), ion injection times up to 1000 ms, and narrow precursor isolation windows. Additionally, we discovered that precursors with a charge state exceeding their basic amino acid count require unusually low energies for optimal fragmentation, which is especially relevant for the non-tryptic peptides characteristic of the immunopeptidome. We applied the optiPRM+ workflow to the challenging biological case of Human Papillomavirus type 16 (HPV16), a virus known to suppress antigen presentation pathways. This optimized strategy enabled the confident identification and validation of the human leukocyte antigen (HLA)-A∗02:01-restricted epitope TIHDIILECV and, to our knowledge, the first MS-based detection of two novel viral targets: ISEYRHYCY (HLA-A∗01:01) and CVYCKQQLLR (HLA-A∗11:01). Subsequent global immunopeptidome analysis via DIA confirmed that these ultra-low abundance peptides were not detectable through untargeted methods despite being clearly validated by our targeted approach. By successfully detecting these viral peptides, we demonstrate that a systematically optimized targeted-first approach can uncover biologically relevant epitopes that remain invisible to conventional discovery-based workflows.