The effects of mass accuracy, data acquisition speed, and search algorithm choice on peptide identification rates in phosphoproteomics
The effects of mass accuracy, data acquisition speed, and search algorithm choice on peptide identification rates in phosphoproteomics
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DOI：
10.1007/s00216-007-1563-x
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发表时间：
2007-11-01
影响因子：
4.3
通讯作者：
Gygi, Steven P.
中科院分区：
文献类型：
--
作者：
Bakalarski, Corey E.;Haas, Wilhelm;Gygi, Steven P.
通过串联质谱的蛋白质组学分析已大大提高了快速，高精度仪器的最新发展。然而，这些发展的高通量实验的成功应用，需要仔细优化的许多变量，相互产生不利影响，如质量的准确性和数据收集速度。我们研究了三种猎枪式采集方法的性能，包括数据收集速度和使用质量准确度，以从酵母衍生的复合肽和磷酸肽富集的混合物中识别蛋白质。我们发现，从一个调查扫描中产生的FT-ICR细胞，再加上10个数据相关的串联MS扫描在一个较低分辨率的线性离子阱的组合，高精度的前体质量，提供更多的识别在这两种混合物比其他检查方法。特别是对于磷酸肽鉴定，该方法从一式三份的90分钟分析中鉴定出的独特磷酸肽是第二等级的较低分辨率方法的两倍多（分别为744 +/- 50 vs. 308 +/- 50）。我们还研究了四种流行的肽分配算法（Mascot，Sequest，OMSSA和Tandem）在分析高分辨率和低分辨率数据结果时的性能。当在约1%的假阳性率的上下文中进行比较时，对于磷酸肽分析，算法之间的性能差异比对于未富集的复杂混合物大得多。基于这些发现，采集速度、质量准确度和分配算法的选择都在很大程度上影响了高通量研究中鉴定的肽和蛋白质的数量。
Proteomic analyses via tandem mass spectrometry have been greatly enhanced by the recent development of fast, highly accurate instrumentation. However, successful application of these developments to high-throughput experiments requires careful optimization of many variables which adversely affect each other, such as mass accuracy and data collection speed. We examined the performance of three shotgun-style acquisition methods ranging in their data collection speed and use of mass accuracy in identifying proteins from yeast-derived complex peptide and phosphopeptide-enriched mixtures. We find that the combination of highly accurate precursor masses generated from one survey scan in the FT-ICR cell, coupled with ten data-dependent tandem MS scans in a lower-resolution linear ion trap, provides more identifications in both mixtures than the other examined methods. For phosphopeptide identifications in particular, this method identified over twice as many unique phosphopeptides as the second-ranked, lower-resolution method from triplicate 90-min analyses (744 +/- 50 vs. 308 +/- 50, respectively). We also examined the performance of four popular peptide assignment algorithms (Mascot, Sequest, OMSSA, and Tandem) in analyzing the results from both high-and low-resolution data. When compared in the context of a false positive rate of approximately 1%, the performance differences between algorithms were much larger for phosphopeptide analyses than for an unenriched, complex mixture. Based upon these findings, acquisition speed, mass accuracy, and the choice of assignment algorithm all largely affect the number of peptides and proteins identified in high-throughput studies.