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MethylQuant: A Tool for Sensitive Validation of Enzyme-Mediated Protein Methylation Sites from Heavy-Methyl SILAC Data
Journal of Proteome Research ( IF 3.8 ) Pub Date : 2017-11-03 00:00:00 , DOI: 10.1021/acs.jproteome.7b00601
Aidan P. Tay 1 , Vincent Geoghegan 2 , Daniel Yagoub 1 , Marc R. Wilkins 1 , Gene Hart-Smith 1
Affiliation  

The study of post-translational methylation is hampered by the fact that large-scale LC–MS/MS experiments produce high methylpeptide false discovery rates (FDRs). The use of heavy-methyl stable isotope labeling by amino acids in cell culture (heavy-methyl SILAC) can drastically reduce these FDRs; however, this approach is limited by a lack of heavy-methyl SILAC compatible software. To fill this gap, we recently developed MethylQuant. Here, using an updated version of MethylQuant, we demonstrate its methylpeptide validation and quantification capabilities and provide guidelines for its best use. Using reference heavy-methyl SILAC data sets, we show that MethylQuant predicts with statistical significance the true or false positive status of methylpeptides in samples of varying complexity, degree of methylpeptide enrichment, and heavy to light mixing ratios. We introduce methylpeptide confidence indicators, MethylQuant Confidence and MethylQuant Score, and demonstrate their strong performance in complex samples characterized by a lack of methylpeptide enrichment. For these challenging data sets, MethylQuant identifies 882 of 1165 true positive methylpeptide spectrum matches (i.e., >75% sensitivity) at high specificity (<2% FDR) and achieves near-perfect specificity at 41% sensitivity. We also demonstrate that MethylQuant produces high accuracy relative quantification data that are tolerant of interference from coeluting peptide ions. Together MethylQuant’s capabilities provide a path toward routine, accurate characterizations of the methylproteome using heavy-methyl SILAC.

中文翻译:

MethylQuant:从重甲基SILAC数据中敏感地验证酶介导的蛋白质甲基化位点的工具

大规模LC-MS / MS实验产生高甲基肽错误发现率(FDR)的事实阻碍了翻译后甲基化的研究。在细胞培养中使用氨基酸进行重甲基稳定同位素标记(重甲基SILAC)可以大大减少这些FDR;但是,这种方法受到缺少与重甲基SILAC兼容的软件的限制。为了填补这一空白,我们最近开发了MethylQuant。在这里,使用MethylQuant的更新版本,我们演示了其甲基肽验证和定量功能,并提供了最佳使用指南。使用参考的重甲基SILAC数据集,我们显示MethylQuant具有统计学意义,可以预测具有不同复杂性,甲基肽富集程度,重轻混合比例。我们介绍了甲基肽置信度指标,MethylQuant Confidence和MethylQuant Score,并展示了它们在缺乏甲基肽富集特征的复杂样品中的强大性能。对于这些具有挑战性的数据集,MethylQuant可在高特异性(<2%FDR)下鉴定出1165个真正的正甲基肽谱匹配(即> 75%灵敏度)中的882个,并在41%灵敏度下获得接近完美的特异性。我们还证明了MethylQuant可以产生高精度的相对定量数据,这些数据可以耐受共洗脱肽离子的干扰。MethylQuant的能力共同为使用重甲基SILAC进行甲基蛋白质组的常规,准确表征提供了一条途径。MethylQuant置信度和MethylQuant得分,并证明了其在缺乏甲基肽富集特征的复杂样品中的强大性能。对于这些具有挑战性的数据集,MethylQuant可在高特异性(<2%FDR)下鉴定出1165个真正的正甲基肽谱匹配(即> 75%灵敏度)中的882个,并在41%灵敏度下获得接近完美的特异性。我们还证明了MethylQuant可以产生高精度的相对定量数据,这些数据可以耐受共洗脱肽离子的干扰。MethylQuant的能力共同为使用重甲基SILAC进行甲基蛋白质组的常规,准确表征提供了一条途径。MethylQuant置信度和MethylQuant得分,并证明了其在缺乏甲基肽富集特征的复杂样品中的强大性能。对于这些具有挑战性的数据集,MethylQuant可在高特异性(<2%FDR)下鉴定出1165个真正的正甲基肽谱匹配(即> 75%灵敏度)中的882个,并在41%灵敏度下获得接近完美的特异性。我们还证明了MethylQuant可以产生高精度的相对定量数据,这些数据可以耐受共洗脱肽离子的干扰。MethylQuant的能力共同为使用重甲基SILAC进行甲基蛋白质组的常规,准确表征提供了一条途径。MethylQuant在高特异性(<2%FDR)下鉴定出1165个真正的正甲基肽谱匹配(即> 75%灵敏度)中的882个,并在41%灵敏度下达到接近完美的特异性。我们还证明了MethylQuant可以产生高精度的相对定量数据,这些数据可以耐受共洗脱肽离子的干扰。MethylQuant的能力共同为使用重甲基SILAC进行甲基蛋白质组的常规,准确表征提供了一条途径。MethylQuant在高特异性(<2%FDR)下鉴定出1165个真正的正甲基肽谱匹配(即> 75%灵敏度)中的882个,并在41%灵敏度下达到接近完美的特异性。我们还证明了MethylQuant可以产生高精度的相对定量数据,这些数据可以耐受共洗脱肽离子的干扰。MethylQuant的能力共同为使用重甲基SILAC进行甲基蛋白质组的常规,准确表征提供了一条途径。
更新日期:2017-11-05
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