Geffen Yifat, Appleboim Alon, Gardner Richard G, Ravid Tommer
Department of Biological Chemistry, The Alexander Silberman Institute of Life Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel.
School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, Israel.
Methods Mol Biol. 2018;1844:121-136. doi: 10.1007/978-1-4939-8706-1_9.
Since its discovery nearly 40 years ago, many components of the ubiquitin-proteasome system (UPS) have been identified and characterized in detail. However, a key aspect of the UPS that remains largely obscure is the signals that initiate the interaction of a substrate with enzymes of the UPS machinery. Understanding these signals is of particular interest for studies that examine the mechanism of substrate recognition for proteins that have adopted a non-native structure, as part of the cellular protein quality control (PQC) defense mechanism. Such studies are quite salient as the entire proteome makes up the potential battery of PQC substrates, and yet only a limited number of ubiquitination pathways are known to handle misfolded proteins. Our current research aims at understanding how a small number of PQC ubiquitin-protein ligases specifically recognize and ubiquitinate the overwhelming assortment of misfolded proteins. Here, we present a new proteogenomic approach for identifying and characterizing recognition motifs within degradation elements (degrons) in a high-throughput manner. The method utilizes yeast growth under restrictive conditions for selecting protein fragments that confer instability. The corresponding cDNA fragments are analyzed by next-generation sequencing (NGS) that provides information about each fragment's identity, reading frame, and abundance over time. This method was used by us to identify PQC-specific and compartment-specific degrons. It can readily be modified to study protein degradation signals and pathways in other organisms and in various settings, such as different strain backgrounds and under various cell conditions, all of which can be sequenced and analyzed simultaneously.
自近40年前被发现以来,泛素-蛋白酶体系统(UPS)的许多组成部分已被详细鉴定和表征。然而,UPS中一个在很大程度上仍不清楚的关键方面是启动底物与UPS机制中的酶相互作用的信号。对于研究作为细胞蛋白质质量控制(PQC)防御机制一部分的、已采用非天然结构的蛋白质的底物识别机制而言,了解这些信号尤为重要。这类研究非常突出,因为整个蛋白质组构成了PQC底物的潜在储备,但已知只有有限数量的泛素化途径可处理错误折叠的蛋白质。我们目前的研究旨在了解少数PQC泛素-蛋白质连接酶如何特异性识别并泛素化种类繁多的错误折叠蛋白质。在此,我们提出一种新的蛋白质基因组学方法,用于高通量鉴定和表征降解元件(降解决定子)内的识别基序。该方法利用酵母在限制性条件下生长来选择赋予不稳定性的蛋白质片段。通过下一代测序(NGS)分析相应的cDNA片段,NGS可提供有关每个片段的身份、阅读框和随时间变化的丰度的信息。我们使用该方法鉴定了PQC特异性和区室特异性降解决定子。它可以很容易地进行修改,以研究其他生物体以及各种环境(如不同菌株背景和各种细胞条件)下的蛋白质降解信号和途径,所有这些都可以同时进行测序和分析。