Tu Chengjian, Sheng Quanhu, Li Jun, Shen Xiaomeng, Zhang Ming, Shyr Yu, Qu Jun
Department of Pharmaceutical Sciences, University at Buffalo, State University of New York , Kapoor 318, North Campus, Buffalo, New York 14260, United States.
J Proteome Res. 2014 Dec 5;13(12):5888-97. doi: 10.1021/pr5008224. Epub 2014 Oct 20.
The rapidly expanding availability of high-resolution mass spectrometry has substantially enhanced the ion-current-based relative quantification techniques. Despite the increasing interest in ion-current-based methods, quantitative sensitivity, accuracy, and false discovery rate remain the major concerns; consequently, comprehensive evaluation and development in these regards are urgently needed. Here we describe an integrated, new procedure for data normalization and protein ratio estimation, termed ICan, for improved ion-current-based analysis of data generated by high-resolution mass spectrometry (MS). ICan achieved significantly better accuracy and precision, and lower false-positive rate for discovering altered proteins, over current popular pipelines. A spiked-in experiment was used to evaluate the performance of ICan to detect small changes. In this study E. coli extracts were spiked with moderate-abundance proteins from human plasma (MAP, enriched by IgY14-SuperMix procedure) at two different levels to set a small change of 1.5-fold. Forty-five (92%, with an average ratio of 1.71 ± 0.13) of 49 identified MAP protein (i.e., the true positives) and none of the reference proteins (1.0-fold) were determined as significantly altered proteins, with cutoff thresholds of ≥ 1.3-fold change and p ≤ 0.05. This is the first study to evaluate and prove competitive performance of the ion-current-based approach for assigning significance to proteins with small changes. By comparison, other methods showed remarkably inferior performance. ICan can be broadly applicable to reliable and sensitive proteomic survey of multiple biological samples with the use of high-resolution MS. Moreover, many key features evaluated and optimized here such as normalization, protein ratio determination, and statistical analyses are also valuable for data analysis by isotope-labeling methods.
高分辨率质谱仪的迅速普及极大地提升了基于离子流的相对定量技术。尽管人们对基于离子流的方法兴趣日益浓厚，但定量灵敏度、准确性和错误发现率仍是主要关注点；因此，迫切需要在这些方面进行全面评估和改进。在此，我们描述了一种用于数据归一化和蛋白质比率估计的全新综合程序，称为ICan，用于改进基于离子流的高分辨率质谱（MS）数据的分析。与当前流行的流程相比，ICan在发现蛋白质变化方面具有显著更高的准确性和精密度，以及更低的假阳性率。通过掺入实验来评估ICan检测微小变化的性能。在本研究中，将人血浆中的中等丰度蛋白质（通过IgY14 - SuperMix程序富集的MAP）以两种不同水平掺入大肠杆菌提取物中，设定微小变化为1.5倍。在截断阈值为≥1.3倍变化且p≤0.05的情况下，49种已鉴定的MAP蛋白质中有45种（92%，平均比率为1.71±0.13），即真阳性，而参考蛋白质（1.0倍）均未被确定为显著变化的蛋白质。这是第一项评估并证明基于离子流方法对微小变化蛋白质赋予显著性的竞争性能的研究。相比之下，其他方法表现明显较差。ICan可广泛应用于使用高分辨率MS对多种生物样品进行可靠且灵敏的蛋白质组学检测。此外，这里评估和优化的许多关键特征，如归一化、蛋白质比率测定和统计分析，对于同位素标记方法的数据分析也具有重要价值。
