An improved mass spectrometric method for the analysis of protein 'interactomes' using SILAC labeling and parallel affinity capture.

活细胞包含一个复杂的蛋白质网络，这些蛋白质相互作用，有时稳定，有时更动态。许多有助于细胞维持和生存的关键事件，以及在疾病中受到干扰的关键事件，都依赖于这些相互作用。研究人员已经开发出了识别和描述这些相互作用的方法。一般来说，它们通常涉及“标记”或“标记”要检查的一种蛋白质，以这样一种方式，“标记”的蛋白质可以选择性地分离出来，并通过一种称为质谱的技术识别相关的伙伴。然而，目前的分析方法并不总是令人满意的，当这类蛋白质含量低或相互作用复合物不稳定时，可能会出现问题。在这里，我们提出了一种我们称之为SILAC-iPAC的方法，它结合了几种技术，每种技术都曾在其他情况下使用过，但以前从未结合使用过，我们相信这种方法将显著提高在这些条件下识别蛋白质-蛋白质伴侣的能力。此外，我们建议包括专门开发的软件，以便轻松准确地分析使用该技术获得的任何数据。

Living cells contain a complex network of proteins that interact with each other - sometimes stably, sometimes more dynamically. Many of the key events that contribute to the maintenance and viability of the cell, and that are perturbed in disease depend on these interactions. Researchers have developed methods to identify and characterise these interactions. In general terms they often involve 'marking' or 'tagging' one of the proteins to be examined in such a way that the 'tagged' protein can be selectively isolated and the associated partners identified by a technique called mass spectrometry. However, current methods for this analysis are not always satisfactory and can be probematical when there are low levels of such proteins or when the interacting complexes are not stable. Here we propose a method we call SILAC-iPAC that combines several techniques, each of which has been used in other contexts, but never before in combination, that we believe will offer a significant improvement in the ability to identify protein-protein partners under these conditions. In addition, we propose to include specifically developed software to enable the easy and accurate analysis of any data obtained with the technique.