Protein Expression and Purification in the Fast Lane

全基因组序列的可获得性开始对结构生物学产生深远影响。这是第一次有可能从数千个开放阅读框中选择目标，其中任何一个都可以通过聚合酶链式反应(PCR)的力量很容易地从其基因组中检索出来。可以理解的是，这种观点唤起了人们对大规模结构生物学的看法，创造了一个新的领域，被称为“结构基因组学”。然而，要将这一梦想变成现实，将需要技术进步，以提高确定生物大分子三维结构的速度。该项目的目标是开发一种适用于大规模结构生物学倡议的蛋白质表达和纯化的综合策略。“高通量”一词常与结构基因组学联系起来使用。不过，我们认为，从“高产出”的角度来思考更为合适。毕竟，归根结底，重要的不是一个人做了多少实验，而是一个人必须为此展示多少成功的结果。产出是两个变量的函数：投入和效率，后者是衡量成功进入管道的目标从另一端出现的数量。原则上，可以通过增加这两个变量中的任何一个来增加产出。我们的研究重点是试图最大化蛋白质生产的效率。如果蛋白质表达是一项完全随意的冒险，这将是一场艰苦的战斗，但我们不相信情况是这样的。虽然我们认识到，没有一种方法会一直成功，但经验告诉我们，平均而言，一些方法总是比其他方法更有成效。我们的目标是将这些高概率方法合并到一个连贯的策略中，以实现“最大可能性”蛋白质的表达和纯化，这将使我们能够通过提高效率来增加产量，而不考虑项目的规模。我们方法的核心是自由使用基因工程亲和标签。亲和标记的优点是引人注目的：它们可以提高重组蛋白的产量，帮助保护它免受细胞内蛋白分解，增强它的溶解性，并促进它的纯化。我们认为，亲和力标签的集体属性远远大于它们的潜在缺点。此外，不可能想象一个不涉及亲和标签的通用重组蛋白生产过程。在致力于标签方法之后，我们的目标是获得比我们从亲和力标签中获得的最大可能的好处。亲和标签并不都是一样的，有些标签能更好地完成某些任务，因此我们需要认识到各种标签的优缺点，以便最大限度地利用它们。我们一直对探索亲和标签对重组蛋白质溶解性的影响特别感兴趣，因为不溶性是蛋白质表达和纯化中的一个主要问题，蛋白质的复性似乎与高产应用不相容。通过反复试验，我们发现了一种标签，特别是大肠杆菌麦芽糖结合蛋白(MBP)，它具有惊人的能力来改善其融合伙伴的溶解性并促进其正确折叠。因为我们认为这是一种罕见而有价值的属性，我们采用了MBP作为我们亲和力标记策略的基石。我们正在进行的目标之一是了解增溶效应的基本机制，以便我们能够更好地利用它来对我们有利。我们也希望通过对这个模型系统的详细研究，了解一些关于蛋白质辅助折叠过程的更基本和更一般的性质。虽然MBP有一些强大的优点，但它并不是一个特别好的亲和标签来纯化蛋白质。

The availability of complete genome sequences is beginning to have a profound impact on structural biology. For the first time, it is possible to select targets from among many thousands of open reading frames, any of which can easily be retrieved from its genome through the power of the polymerase chain reaction (PCR). Understandably, this perspective has conjured up visions of structural biology on a grand scale, creating a new field that has come to be known as "structural genomics". Yet, transforming this dream into reality will require technical advances that increase the speed with which the three-dimensional structures of biological macromolecules can be determined. The goal of this project is to develop an integrated strategy for protein expression and purification that will be suitable for large-scale structural biology initiatives. The term "high-throughput" is often used in connection with structural genomics. However, we believe it is more appropriate to think in terms of "high-output." After all, what matters in the end are not how many experiments that one does but how many successful outcomes one has to show for it. Output is a function of two variables: input and efficiency, the latter being a measure of how many targets that enter the pipeline successfully emerge from the other end. In principal, output can be augmented by increasing either of these variables. Our research focuses on trying to maximize the efficiency of protein production. This would be an uphill battle if protein expression were a completely haphazard venture, but we do not believe this is the case. While we recognize that no single method will succeed all of the time, experience has taught us that some approaches are, on average, consistently more productive than others. Our goal is to merge these high-probability approaches into a coherent strategy for "maximum likelihood" protein expression and purification that will enable us to increase output by improving efficiency, irrespective of the scale of the project.Central to our approach is the liberal use of genetically engineered affinity tags. The advantages of affinity tags are compelling: they can improve the yield of a recombinant protein, help protect it from intracellular proteolysis, enhance its solubility, and facilitate its purification. We believe that the collective attributes of affinity tags far outweigh their potential disadvantages. Moreover, it is impossible to imagine a generic process for the production of recombinant proteins that does not involve affinity tags. Having committed ourselves to the tagging approach, our objective is to derive the maximum possible benefit than we can from affinity tags. Affinity tags are not all the same; some perform certain tasks better than others do, and so we need to be cognizant of the advantages and disadvantages of various tags in order to use them to maximum advantage.We have been particularly interested in exploring the influence of affinity tags on the solubility of recombinant proteins, because insolubility is a major problem in protein expression and purification, and refolding of proteins seems incompatible with high-output applications. Through trial and error, we have discovered that one tag in particular, E. coli maltose-binding protein (MBP), has an amazing ability to improve the solubility and promote the proper folding of its fusion partners. Because we believe this to be a rare and valuable attribute, we have adopted MBP as the cornerstone of our affinity-tagging strategy. One of our ongoing objectives is to understand the underlying mechanism of the solubilizing effect so that we can better manipulate it to our advantage. We also hope to learn something of a more fundamental and general nature about the process of assisted protein folding by studying this model system in detail. Although MBP has some powerful advantages, it is not a particularly good affinity tag for protein purification.