narrowPASEF: A Sample-Aware diaPASEF Method Optimization Strategy Improving Differential Proteomics Performance on Low-Abundance Proteins.

Fiche publication

Date publication

septembre 2026

Journal

Analytical chemistry

Auteurs

Membres identifiés du Cancéropôle Est :
Dr BAGNARD Dominique , Mme SCHAEFFER-REISS Christine , Dr CARAPITO Christine

Tous les auteurs :
Rijal JB, Askar IC, Hirschler A, Declercq A, Martens L, Schaeffer-Reiss C, Bagnard D, Carapito C

Lien Pubmed

https://www.ncbi.nlm.nih.gov/pubmed/42689626

Résumé

Recent instrumental and computational innovations in mass-spectrometry-based proteomics offer new promise in biomarker discovery, thanks to unprecedented proteome coverage and depth. Data-independent acquisition (DIA) methods are very promising in this context as they allow improved proteome coverage, reduced missing value rates, and enhanced quantification precision. However, DIA methods also suffer from their own challenges, such as increased data complexity, cycle times, and background noise. In this work, we propose a sample-aware diaPASEF method optimization strategy for a timsTOF platform. Thorough method optimizations have first been conducted on standard HeLa lysates. Then, a ground-truth calibrated sample series, consisting of a range of UPS amounts spiked into a complex Arabidopsis background, was used to mimic differential analyses under controlled conditions. These benchmark experiments demonstrate clear benefits of using narrowPASEF for differential protein discovery. Finally, our strategy was applied to real use case biological samples to conduct a differential analysis of purified mouse astrocyte cells across two different conditions. narrowPASEF improved the proteome depth by 13%, considering proteins quantified with a coefficient of variation (CV) of <20%, and led to a 68% (435 vs 729) increase in differentially expressed proteins. These results provide an opportunity for a more precise and comprehensive analysis of the biological functions of biomarkers, offering a more profound understanding of the disease mechanisms. The benefits of our sample-aware narrowPASEF strategy demonstrated the most substantial impact on low-abundance proteins. Overall, these results show promise for more valuable and robust biomarker discoveries in the future.