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J Am Soc Mass Spectrom. 2019 Aug;30(8):1396-1405. doi: 10.1007/s13361-019-02243-1. Epub 2019 May 30.

Assessing the Relationship Between Mass Window Width and Retention Time Scheduling on Protein Coverage for Data-Independent Acquisition.

Author information

1
Yale Cancer Biology Institute, Yale University, West Haven, CT, 06516, USA.
2
Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences (CAS), Institute of Computing Technology, CAS, Beijing, China.
3
Department of Genome Integrity, Institute of Molecular Genetics of the Czech Academy of Sciences, Prague, Czech Republic.
4
Department of Chemistry, Michigan State University, East Lansing, MI, 48824, USA.
5
Department of Systems Biology, Columbia University, New York, NY, USA.
6
Yale Cancer Biology Institute, Yale University, West Haven, CT, 06516, USA. yansheng.liu@yale.edu.
7
Department of Pharmacology, Yale University School of Medicine, New Haven, CT, 06520, USA. yansheng.liu@yale.edu.

Abstract

Due to the technical advances of mass spectrometers, particularly increased scanning speed and higher MS/MS resolution, the use of data-independent acquisition mass spectrometry (DIA-MS) became more popular, which enables high reproducibility in both proteomic identification and quantification. The current DIA-MS methods normally cover a wide mass range, with the aim to target and identify as many peptides and proteins as possible and therefore frequently generate MS/MS spectra of high complexity. In this report, we assessed the performance and benefits of using small windows with, e.g., 5-m/z width across the peptide elution time. We further devised a new DIA method named RTwinDIA that schedules the small isolation windows in different retention time blocks, taking advantage of the fact that larger peptides are normally eluting later in reversed phase chromatography. We assessed the direct proteomic identification by using shotgun database searching tools such as MaxQuant and pFind, and also Spectronaut with an external comprehensive spectral library of human proteins. We conclude that algorithms like pFind have potential in directly analyzing DIA data acquired with small windows, and that the instrumental time and DIA cycle time, if prioritized to be spent on small windows rather than on covering a broad mass range by large windows, will improve the direct proteome coverage for new biological samples and increase the quantitative precision. These results further provide perspectives for the future convergence between DDA and DIA on faster MS analyzers.

KEYWORDS:

Data-independent acquisition; Isolation windows; Maxquant; Spectronaut; pFind

PMID:
31147889
DOI:
10.1007/s13361-019-02243-1

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