In deciphering the regulatory networks of gene expression controlled by the small non-coding RNAs known as microRNAs (miRNAs), a major challenge has been with the identification of the true mRNA targets by these RNAs within the context of the enormous numbers of predicted targets for each of these small RNAs. To facilitate the system-wide identification of miRNA targets, a variety of system wide methods, such as proteomics, have been implemented. Here we describe the utilization of quantitative label-free proteomics and bioinformatics to identify the most significant changes to the proteome upon expression of the miR-23a-27a-24-2 miRNA cluster. In light of recent work leading to the hypothesis that only the most pronounced regulatory events by miRNAs may be physiologically relevant, our data reveal that label-free analysis circumvents the limitations of proteomic labeling techniques that limit the maximum differences that can be quantified. The result of our analysis identifies a series of novel candidate targets that are reduced in abundance by more than an order of magnitude upon the expression of the miR-23a-27a-24-2 cluster.

中文翻译：

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无标记的蛋白质组学分析揭示了miRNA-23a-27a-24-2 microRNA簇表达后细胞蛋白质组的巨大动态变化。

在破译被称为microRNA（miRNA）的小型非编码RNA所控制的基因表达的调控网络时，主要挑战在于，在大量的RNA预测靶标背景下，由这些RNA鉴定真正的mRNA靶标。这些小RNA中的每一个。为了促进miRNA靶标的全系统鉴定，已实施了多种全系统方法，例如蛋白质组学。在这里，我们描述了利用无标记的蛋白质组学和生物信息学技术来确定表达miR-23a-27a-24-2 miRNA簇后蛋白质组的最重要变化。鉴于最近的工作得出这样的假设，即只有miRNA最明显的调节事件可能与生理相关，我们的数据表明，无标记分析克服了蛋白质组学标记技术的局限性，后者限制了可以量化的最大差异。我们的分析结果确定了一系列新颖的候选目标，这些目标在miR-23a-27a-24-2簇的表达后丰度降低了一个数量级以上。