SUMO-SIM interactions and their role in substrate recognition and autoregulation of SUMO-dependent ubiquitin ligases

SUMO-SIM 相互作用及其在 SUMO 依赖性泛素连接酶的底物识别和自动调节中的作用

• 批准号: 72189822
• 负责人: Professor Dr. Jürgen Dohmen
• 金额: --
• 依托单位: Institut für Genetik
• 依托单位国家: 德国
• 项目类别: Priority Programmes
• 财政年份: 2008
• 资助国家: 德国
• 起止时间: 2007-12-31 至 2014-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/72189822?language=en
• 关键词: SUMO; SIM; interactions; their; role

Studies on yeast and mammalian proteins in our as well as other laboratories have identified SUMO interaction motifs (SIMs) that mediate non-covalent interaction of proteins with the small ubiquitin-related modifier SUMO. Presence of such SIMs was found to be a characteristic feature of a novel class of ubiquitin ligases (ULS) that specifically recognize sumoylated proteins. We and others characterized the human RNF4 protein as the first mammalian ULS and identified the Promyelocytic Leukemia Protein (PML) as its substrate. Calorimetric assays revealed that RNF4 via its multiple SIMs preferentially binds to SUMO chains. Bioinformatical analyses identified several other mammalian proteins that combine ubiquitin ligase domains with SIMs. Several of these ligases affect SUMO conjugate levels upon expression in yeast or localized to PML bodies in human cells suggesting that SUMO-SIM interaction is relevant to their function. We observed both for yeast and human ULS proteins that they are themselves sumoylated, ubiquitylated and degraded suggesting that they subject to an auto-regulatory feedback control. We will use a combination of mutational biochemical analyses to characterize the role of individual or combinations of SIMs in the recognition of distinct types of SUMO modification in substrate recognition and auto-sumoylation of these ubiquitin ligases. We will further investigate how physiological conditions such as various stress types affects proteolytic control of ULS proteins in yeast and human cells. We have established a database screening protocol that allows to identify high probability SIMs and applied this method to predict SUMO interacting proteins encoded in the yeast genome. We will validate selected candidates and extend this approach by applying it to the analysis of the proteomes of humans and other model organisms. Furthermore, we will modify the approach to identify non-consensus SIMs und functionally related motifs.

我们和其他实验室对酵母和哺乳动物蛋白质的研究已经确定了SUMO相互作用基序（西姆斯），它们介导蛋白质与小的泛素相关修饰物SUMO的非共价相互作用。研究发现，此类西姆斯的存在是一类新型泛蛋白连接酶（ULS）的特征，它们特异性识别sumoylated蛋白质。我们和其他人将人类RNF 4蛋白表征为第一个哺乳动物ULS，并鉴定了早幼粒细胞白血病蛋白（PML）作为其底物。量热分析显示，RNF 4通过其多个西姆斯优先结合SUMO链。生物信息学分析鉴定了其他几种将联合收割机泛素连接酶结构域与西姆斯结合的哺乳动物蛋白。这些连接酶中的几种在酵母中表达或定位于人细胞中的PML体时影响SUMO缀合物水平，表明SUMO-SIM相互作用与其功能相关。我们观察到酵母和人ULS蛋白，它们本身被sumoylated，泛素化和降解，这表明它们受到自动调节反馈控制。我们将使用突变生化分析的组合来表征单个SIM或SIM组合在识别这些泛素连接酶的底物识别和自动SUMO化中不同类型的SUMO修饰中的作用。我们将进一步研究生理条件，如各种应激类型如何影响酵母和人类细胞中ULS蛋白的蛋白水解控制。我们已经建立了一个数据库筛选协议，允许识别高概率西姆斯和应用这种方法来预测酵母基因组中编码的SUMO相互作用蛋白。我们将验证选定的候选人，并通过将其应用于人类和其他模式生物的蛋白质组分析来扩展这种方法。此外，我们将修改的方法，以确定非共识西姆斯和功能相关的图案。