Improved method for differential expression proteomics using trypsin-catalyzed 18O labeling with a correction for labeling efficiency
Improved method for differential expression proteomics using trypsin-catalyzed 18O labeling with a correction for labeling efficiency
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DOI：
10.1074/mcp.t600029-mcp200
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发表时间：
2007-07-01
影响因子：
7
通讯作者：
Vazquez, Jesús
中科院分区：
文献类型：
--
作者：
Ramos-Fernandez, Antonio;Lopez-Ferrer, Daniel;Vazquez, Jesús
依赖于稳定同位素标记和同位素稀释质谱的定量策略已被证明是一种非常强大的替代方法，可以替代基于凝胶的动态蛋白质组研究技术。消化后O-18标记越来越受欢迎，主要是由于酶催化交换反应、肽处理和储存程序的简单性，以及将蛋白质消化与肽标记分离所带来的灵活性和多功能性。尽管最近取得了进展，但通过消化后O-18标记的肽定量仍然涉及几个计算问题。在这项工作中，我们分析了大量肽在消化后标记时的行为，并得出结论，这个过程可以用一个通用的动力学模型来解释。在此观察的基础上，我们开发了一种先进的量化算法，用于这种标记。我们的方法将整个同位素包络与动力学交换模型相关的参数拟合，同时允许精确计算原始样品中肽的相对比例以及每个肽的特定标记效率。我们证明，新方法消除了由肽亚群中不完全氧交换产生的伪影，这些伪影具有相对较低的标记效率，并且可能被认为是错误蛋白质比例偏差的指示。最后，在计算与错误表达变化相关的错误率的基础上，我们进行了严格的统计分析，通过检测由T细胞模型制备的激活产生的显著表达变化，我们在实践中证明了该方法的有效性，在100多个蛋白质池中，三个蛋白质中只有5 μ g蛋白质。通过完全控制潜在的伪影，我们的方法可以提高使用这种标记策略的相对蛋白质定量过程的自动化。
Quantitative strategies relying on stable isotope labeling and isotope dilution mass spectrometry have proven to be a very robust alternative to the well established gel-based techniques for the study of the dynamic proteome. Postdigestion O-18 labeling is becoming very popular mainly due to the simplicity of the enzyme- catalyzed exchange reaction, the peptide handling and storage procedures, and the flexibility and versatility introduced by decoupling protein digestion from peptide labeling. Despite recent progresses, peptide quantification by postdigestion O-18 labeling still involves several computational problems. In this work we analyzed the behavior of large collections of peptides when they were subjected to postdigestion labeling and concluded that this process can be explained by a universal kinetic model. On the basis of this observation, we developed an advanced quantification algorithm for this kind of labeling. Our method fits the entire isotopic envelope to parameters related with the kinetic exchange model, allowing at the same time an accurate calculation of the relative proportion of peptides in the original samples and of the specific labeling efficiency of each one of the peptides. We demonstrated that the new method eliminates artifacts produced by incomplete oxygen exchange in subsets of peptides that have a relatively low labeling efficiency and that may be considered indicative of false protein ratio deviations. Finally using a rigorous statistical analysis based on the calculation of error rates associated with false expression changes, we showed the validity of the method in the practice by detecting significant expression changes, produced by the activation of a model preparation of T cells, with only 5 mu g of protein in three proteins among a pool of more than 100. By allowing a full control over potential artifacts, our method may improve automation of the procedures for relative protein quantification using this labeling strategy.