Dataset Information

DIA-MS2pep : a library-free framework for comprehensive peptide identifications from DIA-data

ABSTRACT: We present, a new framework for library-free peptide identification from data-independent acquisition (DIA) data, DIA-MS2pep, containing two main components: 1) MS2 spectrum self-demultiplexing and 2) large precursor mass tolerance database search. DIA-MS2pep empowers the discovery capability of DIA for both peptides and their modified forms. DIA data-specific library built with DIA-MS2pep outperforms sample-specific DDA data library in accuracy and reproducibility of protein quantification, with the merit of discovering protein modification.

ORGANISM(S): Homo Sapiens Escherichia Coli Caenorhabditis Elegans Saccharomyces Cerevisiae

SUBMITTER: Tao Xu

PROVIDER: PXD032253 | iProX | Mon Mar 14 00:00:00 GMT 2022

REPOSITORIES: iProX

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DIA-MS2pep: a library-free framework for comprehensive peptide identification from data-independent acquisition data.

Hou Junjie J Wang Jifeng J Yang Fuquan F Xu Tao T

Biophysics reports 20221201 5-6

Identifying peptides directly from data-independent acquisition (DIA) data remains challenging due to the highly multiplexed MS/MS spectra. Spectral library-based peptide detection is sensitive, but it is limited to the depth of the library and mutes the discovery potential of DIA data. We present here, DIA-MS2pep, a library-free framework for comprehensive peptide identification from DIA data. DIA-MS2pep uses a data-driven algorithm for MS/MS spectrum demultiplexing using the fragments data wit ...[more]

PMID: 37287874

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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-MS2pep : a library-free framework for comprehensive peptide identifications from DIA-data

Publications

DIA-MS2pep: a library-free framework for comprehensive peptide identification from data-independent acquisition data.

Similar Datasets

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