4.7 Article

Hybrid QconCAT-Based Targeted Absolute and Data-Independent Acquisition-Based Label-Free Quantification Enables In-Depth Proteomic Characterization of Wheat Amylase/Trypsin Inhibitor Extracts

期刊

JOURNAL OF PROTEOME RESEARCH
卷 20, 期 3, 页码 1544-1557

出版社

AMER CHEMICAL SOC
DOI: 10.1021/acs.jproteome.0c00752

关键词

bottom-up proteomics data-independent acquisition; QconCAT; label-free quantification; wheat; Triticum aestivum; flour; alpha-amylase/trypsin inhibitor; celiac disease; non-celiac wheat sensitivity

资金

  1. German Research Foundation (DFG) [TE 599/3-1, Schu 646/17-1, Schu SPP1656, LO 1816/4-1]
  2. Leibniz Foundation (Wheatscan) [SAW-2016-DFA-2]
  3. Research Center for Immunotherapy (FZI) of the Johannes Gutenberg-University Mainz

向作者/读者索取更多资源

A novel hybrid LC-MS approach was introduced for the quantitative proteome analysis of ATI extracts, showing high reproducibility and precision. The method was validated for different wheat species and environmental effects on ATI expression, demonstrating its potential for generating new hypotheses or assay development.
Wheat amylase/trypsin inhibitors (ATIs) have gained significant relevance as inducers of intestinal and extra-intestinal inflammation. In this study, we present a novel hybrid data-independent acquisition (DIA) liquid chromatographymass spectrometry (LC-MS) approach, combining QconCAT technology with short microflow LC gradients and DIA and apply the method toward the quantitative proteome analysis of ATI extracts. The presented method is fast, robust, and reproducible and provides precise QconCAT-based absolute quantification of major ATI proteins while simultaneously quantifying the proteome by label-free quantification (LFQ). We analyzed extracts of 60 varieties of common wheat grown in replication and evaluated the reproducibility and precision of the workflow for the quantification of ATIs. Applying the method to analyze different wheat species (i.e., common wheat, spelt, durum wheat, emmer, and einkorn) and comparing the results to published data, we validated inter-laboratory and cross-methodology reproducibility of ATI quantification, which is essential in the context of large-scale breeding projects. Additionally, we applied our workflow to assess environmental effects on ATI expression, analyzing ATI content and proteome of same varieties grown at different locations. Finally, we explored the potential of combining QconCAT-based absolute quantification with DIA-based LFQ proteome analysis for the generation of new hypotheses or assay development.

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