Institute of Molecular Life Sciences, University of Zurich, Zurich, Switzerland.
Nat Methods. 2010 Oct;7(10):837-42. doi: 10.1038/nmeth.1504. Epub 2010 Sep 12.
Efficient experimental strategies are needed to validate computationally predicted microRNA (miRNA) target genes. Here we present a large-scale targeted proteomics approach to validate predicted miRNA targets in Caenorhabditis elegans. Using selected reaction monitoring (SRM), we quantified 161 proteins of interest in extracts from wild-type and let-7 mutant worms. We demonstrate by independent experimental downstream analyses such as genetic interaction, as well as polysomal profiling and luciferase assays, that validation by targeted proteomics substantially enriched for biologically relevant let-7 interactors. For example, we found that the zinc finger protein ZTF-7 was a bona fide let-7 miRNA target. We also validated predicted miR-58 targets, demonstrating that this approach is adaptable to other miRNAs. We propose that targeted mass spectrometry can be applied generally to validate candidate lists generated by computational methods or in large-scale experiments, and that the described strategy should be readily adaptable to other organisms.
需要有效的实验策略来验证计算预测的 microRNA (miRNA) 靶基因。在这里，我们提出了一种大规模的靶向蛋白质组学方法，用于验证秀丽隐杆线虫中预测的 miRNA 靶标。使用选择反应监测 (SRM)，我们定量了野生型和 let-7 突变体蠕虫提取物中 161 种感兴趣的蛋白质。我们通过独立的下游实验分析（如遗传相互作用、多核糖体分析和荧光素酶测定）证明，通过靶向蛋白质组学验证大大富集了具有生物学相关性的 let-7 相互作用物。例如，我们发现锌指蛋白 ZTF-7 是一个真正的 let-7 miRNA 靶标。我们还验证了预测的 miR-58 靶标，证明了这种方法适用于其他 miRNA。我们提出，靶向质谱分析可以普遍应用于验证计算方法或大规模实验产生的候选列表，并且所描述的策略应该易于适应其他生物体。
