4.7 Article

Accurate Peptide Fragment Mass Analysis: Multiplexed Peptide Identification and Quantification

期刊

JOURNAL OF PROTEOME RESEARCH
卷 11, 期 3, 页码 1621-1632

出版社

AMER CHEMICAL SOC
DOI: 10.1021/pr2008175

关键词

data independent acquisition; multiplexed fragmentation; accurate mass measurements; all reaction monitoring; quantification; high resolution product ion scan

资金

  1. National Institutes of Health [7S10RR025107, 5R01GM086688, 5R01RR023334, 1R01GM097112]
  2. University of Washington's Proteomics Resource [UWPR95794]

向作者/读者索取更多资源

Fourier transform-all reaction monitoring (FT-ARM) is a novel approach for the identification and quantification of peptides that relies upon the selectivity of high mass accuracy data and the specificity of peptide fragmentation patterns. An FT-ARM experiment involves continuous, data-independent, high mass accuracy MS/MS acquisition spanning a defined m/z range. Custom software was developed to search peptides against the multiplexed fragmentation spectra by comparing theoretical or empirical fragment ions against every fragmentation spectrum across the entire acquisition. A dot product score is calculated against each spectrum to generate a score chromatogram used for both identification and quantification. Chromatographic elution profile characteristics are not used to cluster precursor peptide signals to their respective fragment ions. FT-ARM identifications are demonstrated to be complementary to conventional data-dependent shotgun analysis, especially in cases where the data-dependent method fails because of fragmenting multiple overlapping precursors. The sensitivity, robustness, and specificity of FT-ARM quantification are shown to be analogous to selected reaction monitoring-based peptide quantification with the added benefit of minimal assay development. Thus, FT-ARM is demonstrated to be a novel and complementary data acquisition, identification, and quantification method for the large scale analysis of peptides.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据