PXD062423

PXD062423 is an original dataset announced via ProteomeXchange.

Title	Tear Fluid Proteomics: A Comparative Study of DIA and DDA Mass Spectrometry
Description	Background: Mass spectrometry is a powerful technique for tear fluid proteomics, offering critical insights into its complex molecular composition. Data-dependent acquisition (DDA), the most commonly used approach, preferentially selects high-abundance proteins, limiting reproducibility and the quantification of low-abundance proteins. In contrast, data-independent acquisition (DIA) provides an unbiased and comprehensive proteomic profile by fragmenting all precursor ions, enhancing protein coverage, quantification accuracy and reproducibility. This study presents a comparative analysis of DDA and DIA approaches for tear fluid proteomics to improve detection of low-abundance proteins and facilitate biomarker discovery. 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 samples in a complex biological matrix. Results: DIA identified 701 unique proteins and 2,444 peptides, significantly outperforming DDA, which identified 396 unique proteins and 1,447 peptides. DIA exhibited greater data completeness (78.7% proteins, 78.5% peptides) compared to DDA (42% proteins, 48% peptides) across replicates. Reproducibility was markedly improved in DIA, with median coefficients of variation (CVs) of 9.8% for proteins and 10.6% for peptides, compared to 17.3% and 22.3% in DDA, respectively. Quantification accuracy was also enhanced, demonstrating superior consistency across dilution series. Conclusion: This study demonstrates that DIA is a robust and reliable method for proteomic analysis of complex tear fluid samples, offering significantly greater depth, reproducibility, and accuracy compared to DDA.
HostingRepository	PRIDE
AnnounceDate	2025-10-20
AnnouncementXML	Submission_2025-10-20_09:12:38.564.xml
DigitalObjectIdentifier
ReviewLevel	Peer-reviewed dataset
DatasetOrigin	Original dataset
RepositorySupport	Unsupported dataset by repository
PrimarySubmitter	Ashok Sharma
SpeciesList	scientific name: Homo sapiens (Human); NCBI TaxID: NEWT:9606; scientific name: Escherichia coli; NCBI TaxID: NEWT:562;
ModificationList	iodoacetamide derivatized residue
Instrument	Orbitrap Fusion

Revision	Datetime	Status	ChangeLog Entry
0	2025-03-31 12:16:06	ID requested
⏵ 1	2025-10-20 09:12:39	announced

10.1016/J.JMSACL.2025.10.001;

submitter keyword: Tear fluid

Schirmer strip

Proteomics

Biomarkers

Mass spectrometry

Ashok Sharma
contact affiliation	Center for Biotechnology and Genomic Medicine, Medical College of Georgia, Augusta University, USA Department of Ophthalmology, Medical College of Georgia, Augusta University, USA
contact email	assharma@augusta.edu
lab head
Ashok Sharma
contact affiliation	Augusta University
contact email	assharma@augusta.edu
dataset submitter

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PRIDE project URI

• PRIDE
  1. PXD062423
     1. Label: PRIDE project
     2. Name: Tear Fluid Proteomics: A Comparative Study of DIA and DDA Mass Spectrometry