Mixed-Data Acquisition: Next-Generation Quantitative Proteomics Data Acquisition.
Journal
Journal of proteomics
ISSN: 1876-7737
Titre abrégé: J Proteomics
Pays: Netherlands
ID NLM: 101475056
Informations de publication
Date de publication:
30 06 2020
30 06 2020
Historique:
received:
14
01
2020
revised:
01
04
2020
accepted:
02
05
2020
pubmed:
11
5
2020
medline:
22
6
2021
entrez:
11
5
2020
Statut:
ppublish
Résumé
We present the Mixed-Data Acquisition (MDA) strategy for mass spectrometry data acquisition. MDA combines Data-Dependent Acquisition (DDA) and Data-Independent Acquisition (DIA) in the same run, thus doing away with the requirements for separate DDA spectral libraries. MDA is a natural result from advances in mass spectrometry, such as high scan rates and multiple analyzers, and is tailored toward exploiting these features. We demonstrate MDA's effectiveness on a yeast proteome analysis by overcoming a common bottleneck for XIC-based label-free quantitation; namely, the coelution of precursors when m/z values cannot be distinguished. We anticipate that MDA will become the next mainstream data generation approach for proteomics. MDA can also serve as an orthogonal validation approach for DDA experiments. Specialized software for MDA data analysis is made available on the project's website.
Identifiants
pubmed: 32387712
pii: S1874-3919(20)30171-8
doi: 10.1016/j.jprot.2020.103803
pii:
doi:
Substances chimiques
Proteome
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
103803Informations de copyright
Copyright © 2020 Elsevier B.V. All rights reserved.