A quantitative targeted proteomics approach to validate predicted microRNA targets in C. elegans.
A quantitative targeted proteomics approach to validate predicted microRNA targets in C. elegans.
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DOI：
10.1038/nmeth.1504
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发表时间：
2010-10
期刊：
影响因子：
48
通讯作者：
Hengartner, Michael O.
中科院分区：
文献类型：
--
作者：
Jovanovic, Marko;Reiter, Lukas;Picotti, Paola;Lange, Vinzenz;Bogan, Erica;Hurschler, Benjamin A.;Blenkiron, Cherie;Lehrbach, Nicolas J.;Ding, Xavier C.;Weiss, Manuel;Schrimpf, Sabine P.;Miska, Eric A.;Grosshans, Helge;Aebersold, Ruedi;Hengartner, Michael O.
用于鉴定microRNA（miRNA）靶基因的计算预测方法受益于有效的实验验证策略。在这里，我们提出了一个大规模的有针对性的蛋白质组学方法来验证这种预测的miRNA目标在秀丽隐杆线虫。使用选择性反应监测（SRM），我们量化了161个感兴趣的蛋白质提取物从野生型和let-7突变蠕虫。我们通过独立的实验下游分析，如遗传相互作用，以及示例性地进行的多聚体分析和荧光素酶测定，证明了靶向蛋白质组学的验证显着丰富了生物相关的let-7相互作用。例如，我们表明锌指蛋白ZTF-7是真正的let-7 miRNA靶点。我们还验证了一组预测的miR-58靶点，证明这种方法适用于多种感兴趣的miRNA。我们建议，靶向质谱法通常可用于验证通过计算方法或大规模实验生成的候选列表，并且所描述的策略可以很容易地适用于其他生物体。
Computational prediction methods for the identification of microRNA (miRNA) target genes benefit from efficient experimental validation strategies. Here we present a large-scale targeted proteomics approach to validate such 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 exemplarily performed polysomal profiling and luciferase assays, that validation by targeted proteomics significantly enriches for biologically relevant let-7 interactors. For example, we show that the zinc finger protein ZTF-7 is a bona fide let-7 miRNA target. We also validated a set of predicted miR-58 targets, demonstrating that this approach is adaptable to multiple miRNAs of interest. We propose that targeted mass spectrometry can be applied generally to validate candidate lists generated by computational methods or by large-scale experiments, and that the described strategy can easily be adapted to other organisms.
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影响因子：
64.8
作者：
Baek, Daehyun;Villen, Judit;Shin, Chanseok;Camargo, Fernando D.;Gygi, Steven P.;Bartel, David P.
通讯作者：
Bartel, David P.
DOI：
10.4161/cc.7.19.6778
发表时间：
2008-10
期刊：
Cell cycle (Georgetown, Tex.)
影响因子：
--
作者：
Ding XC;Slack FJ;Grosshans H
通讯作者：
Grosshans H
影响因子：
11.4
作者：
Ding, Xavier C.;Grosshans, Helge
通讯作者：
Grosshans, Helge
影响因子：
11.8
作者：
Lin, SY;Johnson, SM;Slack, FJ
通讯作者：
Slack, FJ
影响因子：
11.8
作者：
Grosshans, H;Johnson, T;Slack, FJ
通讯作者：
Slack, FJ