Background: Mass spectrometry is a powerful technique for tear fluid proteomics, offering critical insights into its complex molecular composition. Traditional data-dependent acquisition (DDA) often favors high-abundance proteins because it selects only the most intense precursor ions within a given window during each scan cycle. A newer approach, data-independent acquisition (DIA), addresses this by fragmenting all precursor ions within defined mass windows, offering broader coverage and improved quantification. This study presents a systematic comparison of DDA and DIA workflows to assess their relative performance in detecting tear fluid proteins.
Methods: Tear fluid samples were collected from healthy individuals using Schirmer strips, processed using in-strip protein digestion, and analyzed via liquid chromatography-tandem mass spectrometry (LC-MS/MS). DDA and DIA workflows were compared for proteomic depth, reproducibility, and data completeness. Quantification accuracy was assessed using serial dilutions of tear fluid in a complex biological matrix.
Results: DIA identified 701 unique proteins and 2,444 peptides, outperforming DDA, which identified 396 unique proteins and 1,447 peptides. Across eight replicates, DIA exhibited greater data completeness (78.7% for proteins and 78.5% for peptides) compared with DDA (42% for proteins and 48% for peptides). Reproducibility was markedly improved with DIA, with a median coefficient of variation (CV) of 9.8% for proteins and 10.6% for peptides, compared to 17.3% and 22.3%, respectively, for DDA. Quantification accuracy was also enhanced, with superior consistency across the dilution series.
Conclusion: Overall, DIA provides deeper, more reproducible, and more accurate proteome profiling of tear fluid than DDA, making it well suited for biomarker discovery.
Keywords: Biomarkers; Mass spectrometry; Proteomics; Schirmer strip; Tear fluid.
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