Systematic prediction of FFAT motifs across eukaryote proteomes identifies nucleolar and eisosome proteins with the predicted capacity to form bridges to the endoplasmic reticulum

对真核生物蛋白质组中 FFAT 基序的系统预测,可识别出具有形成与内质网连接桥能力的核仁和内体蛋白。

阅读:1

Abstract

The endoplasmic reticulum (ER), the most pervasive organelle, exchanges information and material with many other organelles, but the extent of its inter-organelle connections and the proteins that form bridges are not well known. The integral ER membrane protein VAMP-associated protein (VAP) is found in multiple bridges, interacting with many proteins that contain a short linear motif consisting of "two phenylalanines in an acidic tract" (FFAT). The VAP-FFAT interaction is the most common mechanism by which cytoplasmic proteins, particularly inter-organelle bridges, target the ER. Therefore, predicting new FFAT motifs may both find new individual peripheral ER proteins and identify new routes of communication involving the ER. Here we searched for FFAT motifs across whole proteomes. The excess of eukaryotic proteins with FFAT motifs over background was ≥0.8%, suggesting this is the minimum number of peripheral ER proteins. In yeast, where VAP was previously known to bind 4 proteins with FFAT motifs, a detailed analysis of a subset of proteins predicted 20 FFAT motifs. Extrapolating these findings to the whole proteome estimated the number of FFAT motifs in yeast at approximately 50-55 (0.9% of proteome). Among these previously unstudied FFAT motifs, most have known functions outside the ER, so could be involved in inter-organelle communication. Many of these can target well-characterised membrane contact sites, however some are in nucleoli and eisosomes, organelles previously unknown to have molecular bridges to the ER. We speculate that the nucleolar and eisosomal proteins with predicted motifs may function while bridging to the ER, indicating novel ER-nucleolus and ER-eisosome routes of inter-organelle communication.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。