Liu Kehui, Zhang Jiyang, Fu Bin, Xie Hongwei, Wang Yingchun, Qian Xiaohong
State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Radiation Medicine, Beijing, P. R. China; State Key Laboratory of Molecular and Developmental Biology, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, P. R. China.
Proteomics. 2014 Jul;14(13-14):1593-603. doi: 10.1002/pmic.201300032. Epub 2014 Jun 11.
Precise protein quantification is essential in comparative proteomics. Currently, quantification bias is inevitable when using proteotypic peptide-based quantitative proteomics strategy for the differences in peptides measurability. To improve quantification accuracy, we proposed an "empirical rule for linearly correlated peptide selection (ERLPS)" in quantitative proteomics in our previous work. However, a systematic evaluation on general application of ERLPS in quantitative proteomics under diverse experimental conditions needs to be conducted. In this study, the practice workflow of ERLPS was explicitly illustrated; different experimental variables, such as, different MS systems, sample complexities, sample preparations, elution gradients, matrix effects, loading amounts, and other factors were comprehensively investigated to evaluate the applicability, reproducibility, and transferability of ERPLS. The results demonstrated that ERLPS was highly reproducible and transferable within appropriate loading amounts and linearly correlated response peptides should be selected for each specific experiment. ERLPS was used to proteome samples from yeast to mouse and human, and in quantitative methods from label-free to O18/O16-labeled and SILAC analysis, and enabled accurate measurements for all proteotypic peptide-based quantitative proteomics over a large dynamic range.
精确的蛋白质定量在比较蛋白质组学中至关重要。目前，当使用基于蛋白型肽的定量蛋白质组学策略时，由于肽段可测量性的差异，定量偏差不可避免。为了提高定量准确性，我们在之前的工作中提出了定量蛋白质组学中的“线性相关肽段选择经验规则（ERLPS）”。然而，需要对ERLPS在不同实验条件下在定量蛋白质组学中的普遍应用进行系统评估。在本研究中，明确阐述了ERLPS的实践流程；全面研究了不同的实验变量，如不同的质谱系统、样品复杂性、样品制备、洗脱梯度、基质效应、上样量等因素，以评估ERPLS的适用性、重现性和可转移性。结果表明，在适当的上样量范围内，ERLPS具有高度的重现性和可转移性，并且应为每个特定实验选择线性相关的响应肽段。ERLPS被应用于从酵母到小鼠和人类的蛋白质组样品，以及从无标记到O18/O16标记和SILAC分析的定量方法中，并能够在大动态范围内对所有基于蛋白型肽的定量蛋白质组学进行准确测量。
