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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Mixed-Data Acquisition: Next-Generation Quantitative Proteomics Data Acquisition

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Author(s):
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Santos, Marlon D. M. [1] ; Camillo-Andrade, Amanda Caroline [2] ; Kurt, Louise U. [1] ; Clasen, Milan A. [1] ; Lyra, Eduardo [3] ; Gozzo, Fabio C. [3] ; Batista, Michel [4] ; Valente, Richard H. [5] ; Brunoro, Giselle V. F. [6] ; Barbosa, Valmir C. [7] ; Fischer, Juliana S. G. [1] ; Carvalho, Paulo C. [1]
Total Authors: 12
Affiliation:
[1] Fiocruz MS, Carlos Chagas Inst, Lab Struct & Computat Prote, Curitiba, Parana - Brazil
[2] Posit Univ, Master Program Ind Biotechnol, Curitiba, Parana - Brazil
[3] Univ Estadual Campinas, Inst Chem, Campinas, SP - Brazil
[4] Fiocruz MS, Carlos Chagas Inst, Mass Spectrometry Facil RPT02H, Curitiba, Parana - Brazil
[5] Oswaldo Cruz Inst Fiocruz, Lab Toxinol, Rio De Janeiro - Brazil
[6] Butantan Inst, Ctr Excellence New Target Discovery, Sao Paulo - Brazil
[7] Univ Fed Rio de Janeiro, Syst Engn & Comp Sci Program, Rio De Janeiro - Brazil
Total Affiliations: 7
Document type: Journal article
Source: JOURNAL OF PROTEOMICS; v. 222, JUN 30 2020.
Web of Science Citations: 0
Abstract

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 projects website. (AU)

FAPESP's process: 14/17264-3 - New frontiers in structural proteomics: characterizing protein and protein complex structures by mass spectrometry
Grantee:Fabio Cesar Gozzo
Support type: Research Projects - Thematic Grants