STRIDE: Signal Transfer and Aligned Ion-Peak Discrimination for Peptidoform Evidence for Consistent Quantification of Site-Localized Post-Translational Modifications in Large-Scale DIA-MS

Data-independent acquisition (DIA) mass spectrometry has emerged as a powerful method for comprehensive post-translational modification profiling in proteomics, but faces challenges in consistently assigning peptidoforms to the same chromatographic peaks across multiple samples. This study introduces STRIDE to address this challenge by implementing dynamic programming alignment and propagating unique ion signature signals across runs. We benchmarked STRIDE using a synthetic phosphopeptide dilution series dataset, demonstrating an 11.3-fold reduction in false-negative rate compared to DIA-NN, from 68% with DIA-NN to 6% with STRIDE at 5% false-positive rate when requiring both correct site-localization and correct peak assignment. STRIDE also improved over the base OpenSWATH (IPF), reducing the false-negative rate from 14% to 6% for correct peak assignment. When applied to a phospho-enriched U2OS nocodazole dataset, our approach reduced missing values from 38.6% to 15.2% in a representative quantification matrix, increased highly reproducible phosphopeptide detections from 7,698 to 12,510 in nocodazole-treated samples, and identified 5,431 differentially abundant phosphopeptides compared to 2,588 with DIA-NN. This increased the number of enriched pathways recovered from differential phosphopeptide analysis, including pathways related to mitotic arrest, microtubule organization, chromatin regulation, RNA processing and kinase signalling. Lastly, we analyzed acetyllysine and glycopeptide-enriched DIA datasets, where STRIDE improved complete replicate detection, reduced missing quantification values, and increased site-specific glycan reproducibility. Together, these results demonstrate that STRIDE improves peptidoform proteomics through reduced false-negative rates, consistent peak assignment, and more complete quantification across runs.