DogTag - a genetically encoded proximity labelling strategy to capture problematic protein-protein interactions

DogTag -如何在生物体中找到蛋白质的伴侣蛋白质是细胞中关键的功能分子，形成结构构件并执行细胞生存所需的许多特殊功能。确保单个蛋白质在正确的时间在正确的地点执行正确的任务，主要是通过调节与哪些其他蛋白质相互作用来实现的。定义这些相互作用是现代分子生物学的核心问题之一。目前使用的所有方法都有一些缺点：1。破坏性-在相互作用被评估之前，生物体的细胞必须被分解。这将导致许多互动破裂并被错过。对于发生在酶和它们的底物之间的弱或短暂的相互作用，或者与细胞膜中发现的蛋白质的相互作用，这是特别正确的，在这些相互作用中，必须使用洗涤剂来打破膜。酶-底物和膜蛋白的相互作用是理解疾病和开发药物的最重要的部分，使这方面的知识成为生物学的重要优先事项。2. 脱离上下文-许多方法使用不同的生物（异种系统）来测试相互作用，因为它更容易和更快（例如，酵母被用作研究人类或植物蛋白质之间相互作用的替代系统）。在异源系统中，许多组分可能缺失，这意味着无法评估由多种相互作用组成的许多大的蛋白质复合物。3. 非生理性-许多系统使用细胞培养作为整个生物体的替代品。虽然在这些情况下是必要的，但它们忽略了组织、有机体或生理条件的背景，因此错过了特定情况下蛋白质的真正相互作用模式。需要外部输入——许多用于观察蛋白质相互作用的系统需要某种形式的外部输入来揭示相互作用。这意味着整个生物体或组织不能在这些情况下使用。我们设计了一种策略来解决许多这些问题，因此这代表了蛋白质-蛋白质相互作用分析的一个里程碑，并为进行更多生理学相关的分析打开了大门，并向研究人员揭示了更多相关的数据。通过将感兴趣的蛋白质与一种细菌酶连接起来，这种酶能够在其他蛋白质上添加一个小标签，我们可以定义感兴趣的蛋白质周围的蛋白质环境。更重要的是，酶和标签本身都是蛋白质，因此可以编码为DNA并放入研究生物体的基因组中。这意味着，首次有可能在没有任何外部输入的情况下，在生理相关条件或应激（低氧、干旱等）下，在整个生物体（整株植物、动物等）中，在感兴趣的组织（植物种子、动物肝脏等）的蛋白质原生细胞环境中识别蛋白质伴侣。这项工作的目的是利用我们的原理数据证明，并证明该系统可用于发现来自真菌、植物和动物等生物的新型蛋白质相互作用，从而为迄今为止无法进入的研究领域提供新的基础研究。

DogTag - how to find a protein's partners in living organismsProteins are the key functional molecules in the cell, forming structural building blocks and performing the many specialized functions a cell requires to survive. Making sure that individual proteins perform the right task at the right time in the right place is largely achieved by regulating which other proteins it interacts with.Defining these interactions is one of the core problems of modern molecular biology. All methods used so far suffer from a number of disadvantages:1. Disruptive -the cells of the organism must be broken apart before the interactions can be assessed. This leads to many interactions falling apart and being missed. This is particularly true for weak or transient interactions such as those occurring between enzymes and their substrates or interactions with proteins found in the cell membrane where detergents have to be used to break the membrane. Enzyme-substrate and membrane protein interactions are some of the most important for understanding disease and developing drugs making this knowledge an important priority in biology. 2. Out of context - many methods use a different organism (heterologous system) to test interactions as it is easier and faster (e.g. yeast is used as a surrogate system for investigating interactions between human or plant proteins). In a heterologous system many components many be missing, this means that many large protein complexes composed of multiple interactions cannot be assessed. 3. Non-physiological - many systems use cell culture as a substitute for whole organisms. While necessary in these instances they ignore the context of the tissue, organism or physiological conditions and therefore miss the real interaction patterns of proteins in a particular situation.4. Outside input needed - Many systems used to look at protein interactions require some form of outside input to reveal the interactions. This means that whole organisms or tissues cannot be used in these circumstances.We have designed a strategy to get around many of these problems, this therefore represents a milestone in protein-protein interaction analysis and opens the door for more physiologically relevant analyses to be performed and reveal more relevant data to researchers.By taking a protein of interest and linking it to a bacterial enzyme capable of adding a small tag onto other proteins we can define the protein environment surrounding our protein of interest. Even more importantly the enzyme and tag are both proteins themselves so can be encoded as DNA and placed into the genome of the study organism. This means that, for the first time, it is possible to identify protein partners in the proteins native cellular environment in a tissue of interest (plant seed, animal liver, etc.) in a whole organism (whole plant, animal, etc.) under physiologically relevant conditions or stresses (low oxygen, drought, etc.) without any outside input.The aim of this work is to take our proof of principle data and demonstrate that this system can be used to discover novel protein interactions from organisms such as fungi, plants and animals and therefore fuel novel primary research in hitherto inaccessible study areas.