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首页> 外文期刊>Journal of proteome research >Insights from the First Phosphopeptide Challenge of the MS Resource Pillar of the HUPO Human Proteome Project
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Insights from the First Phosphopeptide Challenge of the MS Resource Pillar of the HUPO Human Proteome Project

机译:Hupo人类蛋白质组项目MS资源支柱的第一次磷酸肽挑战的见解

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Mass spectrometry has greatly improved the analysis of phosphorylation events in complex biological systems and on a large scale. Despite considerable progress, the correct identification of phosphorylated sites, their quantification, and their interpretation regarding physiological relevance remain challenging. The MS Resource Pillar of the Human Proteome Organization (HUPO) Human Proteome Project (HPP) initiated the Phosphopeptide Challenge as a resource to help the community evaluate methods, learn procedures and data analysis routines, and establish their own workflows by comparing results obtained from a standard set of 94 phosphopeptides (serine, threonine, tyrosine) and their nonphosphorylated counterparts mixed at different ratios in a neat sample and a yeast background. Participants analyzed both samples with their method(s) of choice to report the identification and site localization of these peptides, determine their relative abundances, and enrich for the phosphorylated peptides in the yeast background. We discuss the results from 22 laboratories that used a range of different methods, instruments, and analysis software. We reanalyzed submitted data with a single software pipeline and highlight the successes and challenges in correct phosphosite localization. All of the data from this collaborative endeavor are shared as a resource to encourage the development of even better methods and tools for diverse phosphoproteomic applications.
机译:质谱技术极大地改善了复杂生物系统中大规模磷酸化事件的分析。尽管取得了相当大的进展,但磷酸化位点的正确识别、量化以及对其生理相关性的解释仍然具有挑战性。人类蛋白质组组织(HUPO)人类蛋白质组项目(HPP)的MS资源支柱发起了磷酸肽挑战,作为帮助社区评估方法、学习程序和数据分析常规的资源,并通过比较一组标准的94种磷酸肽(丝氨酸、苏氨酸、酪氨酸)及其在纯样品和酵母背景中以不同比例混合的非磷酸化对应物的结果,建立自己的工作流程。参与者用他们选择的方法分析两个样本,以报告这些肽的鉴定和位点定位,确定它们的相对丰度,并在酵母背景中富集磷酸化肽。我们讨论了22个实验室的结果,这些实验室使用了一系列不同的方法、仪器和分析软件。我们用一个软件管道重新分析了提交的数据,并强调了在正确的磷定位方面的成功和挑战。来自这项合作努力的所有数据都作为资源共享,以鼓励开发更好的方法和工具,用于不同的磷酸蛋白质组学应用。

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