Rapid and site-specific deep phosphoproteome profiling by data-independent acquisition without the need for spectral libraries.,Nature Communications

当前位置： X-MOL 学术 › Nat. Commun. › 论文详情

Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)

Rapid and site-specific deep phosphoproteome profiling by data-independent acquisition without the need for spectral libraries.
Nature Communications ( IF 14.7 ) Pub Date : 2020-02-07 , DOI: 10.1038/s41467-020-14609-1
Dorte B Bekker-Jensen ₁ , Oliver M Bernhardt ₂ , Alexander Hogrebe ₁ , Ana Martinez-Val ₁ , Lynn Verbeke ₂ , Tejas Gandhi ₂ , Christian D Kelstrup ₁ , Lukas Reiter ₂ , Jesper V Olsen ₁

Affiliation

Quantitative phosphoproteomics has transformed investigations of cell signaling, but it remains challenging to scale the technology for high-throughput analyses. Here we report a rapid and reproducible approach to analyze hundreds of phosphoproteomes using data-independent acquisition (DIA) with an accurate site localization score incorporated into Spectronaut. DIA-based phosphoproteomics achieves an order of magnitude broader dynamic range, higher reproducibility of identification, and improved sensitivity and accuracy of quantification compared to state-of-the-art data-dependent acquisition (DDA)-based phosphoproteomics. Notably, direct DIA without the need of spectral libraries performs close to analyses using project-specific libraries, quantifying > 20,000 phosphopeptides in 15 min single-shot LC-MS analysis per condition. Adaptation of a 3D multiple regression model-based algorithm enables global determination of phosphorylation site stoichiometry in DIA. Scalability of the DIA approach is demonstrated by systematically analyzing the effects of thirty kinase inhibitors in context of epidermal growth factor (EGF) signaling showing that specific protein kinases mediate EGF-dependent phospho-regulation.

中文翻译：

通过独立于数据的采集快速且特定于位点的深部磷酸化蛋白质组谱分析，而无需光谱库。

磷酸化蛋白质组学已经改变了对细胞信号转导的研究，但要扩展该技术以进行高通量分析仍然具有挑战性。在这里，我们报告了一种快速且可重现的方法，该方法使用与数据无关的获取（DIA）并结合到Spectronaut中的准确站点定位得分来分析数百种磷酸化蛋白质组。与基于最新数据依赖采集（DDA）的磷酸化蛋白质组学相比，基于DIA的磷酸化蛋白质组学可实现一个数量级的动态范围，更高的鉴定重现性以及更高的定量灵敏度和准确性。值得注意的是，不需要光谱库的直接DIA可以使用特定于项目的库进行接近的分析，每个条件下15分钟单次LC-MS分析中可定量> 20,000磷酸肽。改编基于3D多元回归模型的算法可全面确定DIA中的磷酸化位点化学计量。通过系统地分析三十种激酶抑制剂在表皮生长因子（EGF）信号传导环境中的作用，证明了DIA方法的可扩展性，表明特定的蛋白激酶介导了EGF依赖性磷酸调节。

更新日期：2020-02-07

点击分享查看原文

点击收藏

公开下载

阅读更多本刊新发论文本刊介绍/投稿指南