Dataset Information

PASS-DIA: A novel data-independent acquisition approach for discovery studies

ABSTRACT: We present a strategy termed PASS-DIA (Precursor ion And Small Slice-DIA) in which MS/MS spectra are acquired with small isolation window (slices) and MS/MS spectra are interpreted with accurately measured precursor ion masses. This method enables direct application of conventional spectrum-centric analysis pipelines for peptide identification and precursor ion-based quantitation. The performance of PASS-DIA was superior to both DDA and conventional DIA experiment with regard to identification of peptides. Application of PASS-DIA for analysis of samples with post-translationally modified peptides such as phosphorylation and N-glycosylation again revealed its superior performance. Finally, use of PASS-DIA to characterize a rare proteome of human fallopian tube organoid samples revealed biologically relevant and low abundance proteins. Overall, PASS-DIA is a novel DIA approach for use as a discovery tool which outperforms both conventional DDA and DIA experiments to provide additional protein information. We believe that PASS-DIA method could become an important strategy for discovery type studies when deeper proteome characterization is required.

INSTRUMENT(S):

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Cell Culture, Hela Cell

SUBMITTER: Akhilesh Pandey

LAB HEAD: Akhilesh Pandey

PROVIDER: PXD018180 | Pride | 2024-08-02

REPOSITORIES: pride

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			Action	DRS
	FPORG_C10_DDA_F1_130min_052719.raw	Raw
	FPORG_C10_DDA_F2_130min_052719.raw	Raw
	FPORG_C10_DDA_F3_130min_052719.raw	Raw
	FPORG_C10_DDA_F4_130min_052719.raw	Raw
	FPORG_C10_DDA_F5_130min_052719.raw	Raw

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

Mun Dong-Gi DG Renuse Santosh S Saraswat Mayank M Madugundu Anil A Udainiya Savita S Kim Hokeun H Park Sung-Kyu Robin SR Zhao Hui H Nirujogi Raja Sekhar RS Na Chan Hyun CH Kannan Nagarajan N Yates John R JR Lee Sang-Won SW Pandey Akhilesh A

Analytical chemistry 20201020 21

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, ...[more]

PMID: 33079518

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Project description:Data independent acquisition-mass spectrometry (DIA-MS) coupled with liquid chromatography is a promising approach for rapid, automatic sampling of MS/MS data in untargeted metabolomics. However, wide isolation windows in DIA-MS generate MS/MS spectra containing a mixed population of fragment ions together with their precursor ions. This precursor-fragment ion map in a comprehensive MS/MS spectral library is crucial for relative quantification of fragment ions uniquely representative of each precursor ion. However, existing reference libraries are not sufficient for this purpose since the fragmentation patterns of small molecules can vary in different instrument setups. Here we developed a bioinformatics workflow called MetaboDIA to build customized MS/MS spectral libraries using a user's own data dependent acquisition (DDA) data and to perform MS/MS-based quantification with DIA data, thus complementing conventional MS1-based quantification. MetaboDIA also allows users to build a spectral library directly from DIA data in studies of a large sample size. Using a marine algae data set, we show that quantification of fragment ions extracted with a customized MS/MS library can provide as reliable quantitative data as the direct quantification of precursor ions based on MS1 data. To test its applicability in complex samples, we applied MetaboDIA to a clinical serum metabolomics data set, where we built a DDA-based spectral library containing consensus spectra for 1829 compounds. We performed fragment ion quantification using DIA data using this library, yielding sensitive differential expression analysis. </br></br> Serum metabolome of 40 age-related macular degeneration patients and 20 control samples was analyzed using untargeted mass spectrometry. We used data dependent acquisition data to build a MS/MS spectral assay library for more than 1,000 compounds and performed targeted extraction of MS2 ion chromatograms from data independent acquisition analysis.