Dataset Information

Whole proteome of eIF2D-deficient HEK293T cells

ABSTRACT: We performed quantitative proteomics analysis using MS with data-independent acquisition (DIA).

ORGANISM(S): Homo Sapiens (human)

SUBMITTER: Akinobu Matsumoto

PROVIDER: PXD060485 | JPOST Repository | Mon Oct 27 00:00:00 GMT 2025

REPOSITORIES: jPOST

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			Action	DRS
	20220218_EVO60SPD_FAIMS45_15uDIA_AkinobuSample_01.raw	Raw
	20220218_EVO60SPD_FAIMS45_15uDIA_AkinobuSample_02.raw	Raw
	20220218_EVO60SPD_FAIMS45_15uDIA_AkinobuSample_03.raw	Raw
	20220218_EVO60SPD_FAIMS45_15uDIA_AkinobuSample_04.raw	Raw
	20220218_EVO60SPD_FAIMS45_15uDIA_AkinobuSample_05.raw	Raw

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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.

Dataset Information

Whole proteome of eIF2D-deficient HEK293T cells

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