PASS-DIA: A Data-Independent Acquisition Approach for Discovery Studies

Dong Gi Mun, Santosh Renuse, Mayank Saraswat, Anil Madugundu, Savita Udainiya, Hokeun Kim, Sung Kyu Robin Park, Hui Zhao, Raja Sekhar Nirujogi, Chan Hyun Na, Nagarajan Kannan, John R. Yates, Sang Won Lee, Akhilesh Pandey

Research output: Contribution to journalArticlepeer-review

14 Citations (Scopus)


A data-independent acquisition (DIA) approach is being increasingly adopted as a promising strategy for identification and quantitation of proteomes. As most DIA data sets are acquired with wide isolation windows, highly complex MS/MS spectra are generated, which negatively impacts obtaining peptide information through classical protein database searches. Therefore, the analysis of DIA data mainly relies on the evidence of the existence of peptides from prebuilt spectral libraries. Consequently, one major weakness of this method is that it does not account for peptides that are not included in the spectral library, precluding the use of DIA for discovery studies. Here, we present a strategy termed Precursor ion And Small Slice-DIA (PASS-DIA) in which MS/MS spectra are acquired with small isolation windows (slices) and MS/MS spectra are interpreted with accurately determined precursor ion masses. This method enables the direct application of conventional spectrum-centric analysis pipelines for peptide identification and precursor ion-based quantitation. The performance of PASS-DIA was observed to be superior to both data-dependent acquisition (DDA) and conventional DIA experiments with 69 and 48% additional protein identifications, respectively. Application of PASS-DIA for the analysis of post-translationally modified peptides again highlighted its superior performance in characterizing phosphopeptides (77% more), N-terminal acetylated peptides (56% more), and N-glycopeptides (83% more) as compared to DDA alone. Finally, the use of PASS-DIA to characterize a rare proteome of human fallopian tube organoids enabled 34% additional protein identifications than DDA alone and revealed biologically relevant pathways including low abundance proteins. Overall, PASS-DIA is a novel DIA approach for use as a discovery tool that outperforms both conventional DDA and DIA experiments to provide additional protein information. We believe that the PASS-DIA method is an important strategy for discovery-type studies when deeper proteome characterization is required.

Original languageEnglish
Pages (from-to)14466-14475
Number of pages10
JournalAnalytical chemistry
Issue number21
Publication statusPublished - 2020 Nov 3

Bibliographical note

Funding Information:
This work was supported by the Wellcome Trust/DBT India Alliance Margdarshi Fellowship (Grant Number IA/M/15/1/502023) awarded to A.P. We also thank for funding support from Ovarian SPORE DRP to N.K. and Chinese Scholarship Council to H.Z. This work was also supported in part by a grant from the NRF funded by the Collaborative Genome Program for Fostering New Post-Genome Industry (NRF-2017M3C9A5031597).

Publisher Copyright:
© 2020 American Chemical Society.

ASJC Scopus subject areas

  • Analytical Chemistry


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