Dataset Information

DIA-MS based plasma peptidomics workflow for profiling organ-derived peptides

ABSTRACT: In this study, we acquired DDA-MS data and DIA-MS data from peptide extracts of plasma and eleven organs (lung, spleen, adrenal gland, kidney, heart, liver, muscle, pancreas, cerebellum, hippocampus, and cerebral cortex). These data were analyzed using FragPipe v23 to obtain peptide identification results and to construct an empirical spectral library. We also acquired DIA-MS data from plasma peptide extracts and analyzed them with DIA-NN v2.3.1 using three empirical spectral libraries that we constructed, thereby obtaining peptide identification results.

ORGANISM(S): Mus Musculus (mouse)

SUBMITTER: Yoshio Kodera

PROVIDER: PXD073758 | JPOST Repository | Mon Jul 13 00:00:00 BST 2026

REPOSITORIES: jPOST

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			Action	DRS
	Adrenalgland_400ugeq.d.zip	Other
	Cerebellum_400ugeq.d.zip	Other
	Cerebralcortex_400ugeq.d.zip	Other
	DDA_organs_combined_modified_peptide.tsv	Tabular
	DDA_plasma_combined_modified_peptide.tsv	Tabular

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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

DIA-MS based plasma peptidomics workflow for profiling organ-derived peptides

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