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利用贝叶斯统计和等压标记法提高绝对磷酸化计量比的测定方法。

Improved Method for Determining Absolute Phosphorylation Stoichiometry Using Bayesian Statistics and Isobaric Labeling.

机构信息

Department of Cell Biology, Harvard Medical School , Boston, Massachusetts 02115, United States.

出版信息

J Proteome Res. 2017 Nov 3;16(11):4217-4226. doi: 10.1021/acs.jproteome.7b00571.

Abstract

Phosphorylation stoichiometry, or occupancy, is one element of phosphoproteomics that can add useful biological context (Gerber et al. Proc. Natl. Acad. Sci. U. S. A. 2003, 100, 6940-5). We previously developed a method to assess phosphorylation stoichiometry on a proteome-wide scale (Wu et al. Nat. Methods 2011, 8, 677-83). The stoichiometry calculation relies on identifying and measuring the levels of each nonphosphorylated counterpart peptide with and without phosphatase treatment. The method, however, is problematic in that low stoichiometry phosphopeptides can return negative stoichiometry values if measurement error is larger than the percent stoichiometry. Here, we have improved the stoichiometry method through the use of isobaric labeling with 10-plex TMT reagents. In this way, five phosphatase treated and five untreated samples are compared simultaneously so that each stoichiometry is represented by five ratio measurements with no missing values. We applied the method to determine basal stoichiometries of HCT116 cells growing in culture. With this method, we analyzed five biological replicates simultaneously with no need for phosphopeptide enrichment. Additionally, we developed a Bayesian model to estimate phosphorylation stoichiometry as a parameter confined to an interval between 0 and 1 implemented as an R/Stan script. Consequently, both point and interval estimates are consistent with the plausible range of values for stoichiometry. Finally, we report absolute stoichiometry measurements with credible intervals for 6772 phosphopeptides containing at least a single phosphorylation site.

摘要

磷酸化计量(或占有率)是磷酸蛋白质组学的一个要素,可以添加有用的生物学背景(Gerber 等人,Proc. Natl. Acad. Sci. U. S. A. 2003,100,6940-5)。我们之前开发了一种在全蛋白质组范围内评估磷酸化计量的方法(Wu 等人,Nat. Methods 2011,8,677-83)。该计量计算依赖于识别和测量每个未经磷酸化处理的对应肽在有和没有磷酸酶处理时的水平。然而,该方法存在问题,因为低计量磷酸肽如果测量误差大于计量百分比,则可能返回负计量值。在这里,我们通过使用 10 重 TMT 试剂进行等重标记改进了计量方法。通过这种方式,同时比较了 5 个经磷酸酶处理和 5 个未经处理的样品,使得每个计量值都有 5 个比值测量值,没有缺失值。我们应用该方法来确定培养中的 HCT116 细胞的基础计量值。使用该方法,我们同时分析了五个生物学重复,而无需进行磷酸肽富集。此外,我们开发了一个贝叶斯模型,用于估计作为参数的磷酸化计量,该参数限制在 0 到 1 之间,实现为 R/Stan 脚本。因此,点估计和区间估计都与计量值的合理范围一致。最后,我们报告了至少含有一个磷酸化位点的 6772 个磷酸肽的绝对计量值及其置信区间。

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