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秀丽隐杆线虫细胞极性蛋白的二元相互作用与表型组合图谱。

A combined binary interaction and phenotypic map of C. elegans cell polarity proteins.

作者信息

Koorman Thijs, Klompstra Diana, van der Voet Monique, Lemmens Irma, Ramalho João J, Nieuwenhuize Susan, van den Heuvel Sander, Tavernier Jan, Nance Jeremy, Boxem Mike

机构信息

Division of Developmental Biology, Department of Biology, Faculty of Science, Utrecht University, 3584 CH, Utrecht, The Netherlands.

Helen L. and Martin S. Kimmel Center for Biology and Medicine at the Skirball Institute of Biomolecular Medicine, NYU School of Medicine, New York, New York 10016, USA.

出版信息

Nat Cell Biol. 2016 Mar;18(3):337-46. doi: 10.1038/ncb3300. Epub 2016 Jan 18.

Abstract

The establishment of cell polarity is an essential process for the development of multicellular organisms and the functioning of cells and tissues. Here, we combine large-scale protein interaction mapping with systematic phenotypic profiling to study the network of physical interactions that underlies polarity establishment and maintenance in the nematode Caenorhabditis elegans. Using a fragment-based yeast two-hybrid strategy, we identified 439 interactions between 296 proteins, as well as the protein regions that mediate these interactions. Phenotypic profiling of the network resulted in the identification of 100 physically interacting protein pairs for which RNAi-mediated depletion caused a defect in the same polarity-related process. We demonstrate the predictive capabilities of the network by showing that the physical interaction between the RhoGAP PAC-1 and PAR-6 is required for radial polarization of the C. elegans embryo. Our network represents a valuable resource of candidate interactions that can be used to further our insight into cell polarization.

摘要

细胞极性的建立是多细胞生物发育以及细胞和组织功能发挥的一个重要过程。在此,我们将大规模蛋白质相互作用图谱与系统表型分析相结合,以研究线虫秀丽隐杆线虫中极性建立和维持所依赖的物理相互作用网络。利用基于片段的酵母双杂交策略,我们鉴定出了296种蛋白质之间的439种相互作用,以及介导这些相互作用的蛋白质区域。对该网络进行表型分析,结果鉴定出了100对物理相互作用的蛋白质,其RNA干扰介导的缺失会在相同的极性相关过程中导致缺陷。我们通过证明RhoGAP PAC-1和PAR-6之间的物理相互作用是秀丽隐杆线虫胚胎径向极化所必需的,展示了该网络的预测能力。我们的网络代表了一个有价值的候选相互作用资源,可用于进一步深入了解细胞极化。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cf07/4767559/25bc62a26754/nihms745558f1.jpg

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