Biological Services, Weizmann Institute of Science, Rehovot, Israel.
Proteomics. 2011 Aug;11(16):3273-87. doi: 10.1002/pmic.201000661. Epub 2011 Jul 13.
A MS-based method for the quantification of proteins termed data-independent analysis (or MS(E)) has been introduced recently. Although this method has been applied to the analysis of various types of biological samples, a thorough evaluation to assess the performance of this approach has yet to be conducted. Presented here is the first systematic and comprehensive study investigating the MS(E) approach for quantitative analysis of low-, medium-, and high-complexity samples. We demonstrate that this method has a linear dynamic range spanning three orders of magnitude with a limit of quantification of 61 amol/uL in low-complexity samples and 488 amol/uL in high-complexity samples. In addition, comprehensive sequence coverage was obtained and accurate quantification achieved for expression ratios ranging from 1:1.5 to 1:6. However, underestimation of ratios was detected independent of sample type, consistent with other quantitative proteomic methods. The present study provides validation of the MS(E) approach for accurate quantitative proteomic analysis of biological samples while, at the same time, proving high sequence coverage of target proteins.
一种基于 MS 的蛋白质定量方法，称为数据非依赖性分析（或 MS(E)），最近已经被提出。虽然该方法已被应用于各种类型的生物样本分析，但尚未对其性能进行全面评估。本文首次系统而全面地研究了 MS(E)方法在低、中、高复杂度样本定量分析中的应用。我们证明，该方法在低复杂度样本中具有三个数量级的线性动态范围，定量下限为 61 毫摩尔/微升，在高复杂度样本中为 488 毫摩尔/微升。此外，对于表达比例在 1:1.5 到 1:6 之间的样本，我们获得了全面的序列覆盖，并实现了准确的定量。然而，与其他定量蛋白质组学方法一样，我们发现该方法独立于样本类型存在低估比例的情况。本研究为 MS(E)方法在生物样本的准确定量蛋白质组学分析中提供了验证，同时证明了目标蛋白质的高序列覆盖。
