Abstract：
Proteins form complex networks through interaction to drive biological processes. Thus, dissecting protein-protein interactions (PPIs) is essential for interpreting cellular processes. To overcome the drawbacks of traditional approaches for analyzing PPIs, enzyme-catalyzed proximity labeling (PL) techniques based on peroxidases or biotin ligases have been developed and successfully utilized in mammalian systems. However, the use of toxic H2O2 in peroxidase-based PL, the requirement of long incubation time (16-24 h), and higher incubation temperature (37 °C) with biotin in BioID-based PL significantly restricted their applications in plants. TurboID-based PL, a recently developed approach, circumvents the limitations of these methods by providing rapid PL of proteins under room temperature. We recently optimized the use of TurboID-based PL in plants and demonstrated that it performs better than BioID in labeling endogenous proteins. Here, we describe a step-by-step protocol for TurboID-based PL in studying PPIs in planta, including Agrobacterium-based transient expression of proteins, biotin treatment, protein extraction, removal of free biotin, quantification, and enrichment of the biotinylated proteins by affinity purification. We describe the PL using plant viral immune receptor N, which belongs to the nucleotide-binding leucine-rich repeat (NLR) class of immune receptors, as a model. The method described could be easily adapted to study PPI networks of other proteins in Nicotiana benthamiana and provides valuable information for future application of TurboID-based PL in other plant species.
摘要：
蛋白质通过相互作用形成复杂的网络来驱动生物过程。因此，解剖蛋白质-蛋白质相互作用（PPI）对于解释细胞过程至关重要。为了克服传统的PPI分析方法的缺点，已经开发了基于过氧化物酶或生物素连接酶的酶催化的邻近标记（PL）技术，并成功地用于哺乳动物系统。然而,在基于过氧化物酶的PL中使用有毒的H2O2，培养时间长（16-24小时）的要求，基于BioID的PL中生物素的较高孵育温度（37°C）显着限制了它们在植物中的应用。基于TurboID的PL，最近开发的一种方法，通过在室温下提供蛋白质的快速PL来规避这些方法的局限性。我们最近优化了基于TurboID的PL在植物中的使用，并证明它在标记内源性蛋白质方面比BioID表现更好。这里,我们描述了在植物中研究PPI时基于TurboID的PL的逐步协议，包括基于农杆菌的蛋白质瞬时表达，生物素治疗，蛋白质提取，去除游离生物素，量化，和通过亲和纯化富集生物素化的蛋白质。我们使用植物病毒免疫受体N，它属于免疫受体的核苷酸结合型富含亮氨酸重复序列（NLR）类，作为一个模型。所描述的方法可以很容易地适应研究烟草中其他蛋白质的PPI网络，并为基于TurboID的PL在其他植物物种中的未来应用提供有价值的信息。
