Full Window Data-Independent Acquisition Method for Deeper Top-Down Proteomics

Top-down proteomics (TDP) is emerging as a vital tool for the comprehensive characterization of proteoforms. However, as its core technology, top-down mass spectrometry (TDMS) still faces significant analytical challenges. While data-independent acquisition (DIA) has revolutionized bottom-up proteomics and metabolomics, they are rarely employed in TDP. The unique feature of protein ions in an electrospray mass spectrum as well as the data complexity require the development of new DIA strategies. This study introduces a machine learning-assisted Full Window DIA (FW-DIA) method that eliminates precursor ion isolation, making it compatible with a wide range of commercial mass spectrometers. Moreover, FW-DIA leverages all precursor protein ions to generate high-quality tandem mass spectra, enhancing signal intensities by ∼50-fold and protein sequence coverage by 3-fold in a modular protein analysis. The method was successfully applied to the analysis of a five-protein mixture under native conditions and <i>Escherichia coli</i> ribosomal proteoform characterization.

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Publication Details

Journal
Analytical Chemistry
Published
2025-03-22
DOI
https://doi.org/10.1021/acs.analchem.4c06471
Citations
3
Primary Topic
Advanced Proteomics Techniques and Applications
Type
article
Field-Weighted Citation Impact
2.27

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article

Full Window Data-Independent Acquisition Method for Deeper Top-Down Proteomics

Mowei Zhou, Wei Liang Xu, Chen Sun, Wenjing Zhang et al.
3 citations
Analytical Chemistry
Advanced Proteomics Techniques and Applications
2.27
article

Full Window Data-Independent Acquisition Method for Deeper Top-Down Proteomics

Mowei Zhou, Wei Liang Xu, Chen Sun, Wenjing Zhang, Martin Myu
article en
3 citations

Abstract

Top-down proteomics (TDP) is emerging as a vital tool for the comprehensive characterization of proteoforms. However, as its core technology, top-down mass spectrometry (TDMS) still faces significant analytical challenges. While data-independent acquisition (DIA) has revolutionized bottom-up proteomics and metabolomics, they are rarely employed in TDP. The unique feature of protein ions in an electrospray mass spectrum as well as the data complexity require the development of new DIA strategies. This study introduces a machine learning-assisted Full Window DIA (FW-DIA) method that eliminates precursor ion isolation, making it compatible with a wide range of commercial mass spectrometers. Moreover, FW-DIA leverages all precursor protein ions to generate high-quality tandem mass spectra, enhancing signal intensities by ∼50-fold and protein sequence coverage by 3-fold in a modular protein analysis. The method was successfully applied to the analysis of a five-protein mixture under native conditions and <i>Escherichia coli</i> ribosomal proteoform characterization.

Analytical ChemistryVol. 97(12)
Beijing Institute of Technology (CN), Chinese Academy of Inspection and Quarantine (CN), Zhejiang University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 13%
Advanced Proteomics Techniques and Applications
2.27
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