Abstract

We compared traditional data dependent acquisition mass spectrometry (DDA MS) with the increasingly adopted data independent acquisition (DIA MS) to evaluate their relative utility for large scale quantitative biofluid proteomics of lung compartments, specifically paired bronchoalveolar lavage (BAL) cells and bronchoalveolar lavage fluid (BALF). Using beryllium related granulomatous lung disease as a focused model, we analyzed BALF and BAL cells from beryllium sensitized (BeS) individuals using both acquisition strategies to assess proteome depth, quantitative completeness, and analytical robustness. In BAL cells, 5,640 proteins were identified by DDA MS and 5,227 by DIA MS; however, DIA MS yielded markedly improved quantitative completeness, with 5,178 proteins ([~]99%) quantified across all samples compared with 3,539 (around 63%) quantified by DDA MS. While 3,397 proteins were quantified by both methods, DIA MS uniquely quantified 1,781 lower-abundance proteins. Proteins identified by both DIA and DDA MS approaches revealed pathways associated with granulomatous inflammation, including Toll like receptor, clathrin mediated endocytosis, sirtuin, and C type lectin receptor signaling, whereas DIA MS resolved additional pathways, such as the complement cascade, coagulation system, and JAK/IL 6 type cytokine signaling. In BALF, although more proteins were identified by DDA MS than by DIA MS (2,069 vs 1,742), DIA MS achieved greater quantitative completeness, with 1,695 proteins quantified across all samples compared with 1,050 using DDA MS, underscoring its suitability for biomarker oriented analyses in lung fluid compartments. Together, these results support DIA MS as a robust and sensitive platform for quantitative lung proteomics and discovery of disease relevant protein signatures. Key Words: Granulomatous inflammation, beryllium sensitization, chronic beryllium disease, mass spectrometry, DDA MS, DIA MS