High-throughput Pipeline for Electron Crystallography

描述（由申请人提供）：生物膜包裹着所有细胞并调节它们与外界的相互作用。根据不同的生物学背景，膜蛋白作为受体、酶、通道、转运体、结构蛋白和细胞粘附分子，并因此促进了各种基本的细胞功能。膜蛋白的结构信息相对较少，尽管它们是美国销售的60%治疗药物的靶标。我们建议建立一条利用电子晶体学测定膜蛋白结构的管道，这是低温电子显微镜在二维晶体中的应用。为了制备这种晶体，用高密度纯化的膜蛋白重构膜双分子层，从而为组成蛋白提供天然的膜环境和较少的结晶约束。电子晶体学在原子和中间分辨率下产生结构方面有着良好的记录，并且代表了x射线晶体学和核磁共振光谱的有价值的替代方法，这些方法通常仅限于研究洗涤剂溶解的物质。迄今为止，电子晶体学仍然是一种低通量操作，这大大降低了它对膜蛋白生物学的贡献。我们已经开发了一些工具来克服筛选结晶条件的瓶颈，我们正在寻求扩大目前的应用。具体来说，我们建议进一步发展96孔格式的结晶，通过实施微流控透析装置，使样本量最小化，并通过使用环糊精来控制洗涤剂去除率，以优化晶体质量。通过研究范围广泛的不同靶蛋白，我们将通过经验建立影响结晶过程的最关键因素，并开发一套通常有效筛选结晶行为未知的新蛋白的条件。我们将继续开发结晶屏幕的机器人成像方法。制备样品和在电子显微镜下成像的过程目前是限制可以探索的条件数量的最重要的瓶颈。我们已经建立了一个用于样品插入的机器人，并将其与自动图像采集软件接口，但我们建议在该软件中添加形状识别以最大化其效率。我们将把得到的图像集成到LIMS数据库中，以跟踪结构确定管道，并将实现形状识别，以便为结晶试验自动分配分数。最后，我们建议开发一种应用程序，用于从有序晶体中收集高分辨率数据，从而促进晶体尺寸和顺序的优化，并最终获得结构确定所需的数据。我们相信，通过将高通量方法应用于二维结晶和图像采集，电子晶体学可以为我们对膜蛋白生物学的理解做出实质性的贡献。

DESCRIPTION (provided by applicant): Biological membranes surround all cells and mediate their interactions with the outside world. Depending on the biological context, membrane proteins act as receptors, enzymes, channels, transporters, structural proteins and cell adhesion molecules and, as such, contribute to a wide variety of essential cellular functions. Structural information for membrane proteins is relatively scarce, despite the fact that they represent the target of 60% of therapeutic drugs sold in the United States. We propose to establish a pipeline for determining membrane protein structures by electron crystallography, which is the application of cryo-electron microscopy to two-dimensional crystals. To prepare such crystals, the membrane bilayer is reconstituted with a high density of purified membrane proteins, thus providing a native membrane environment and fewer crystallization constraints for the constituent proteins. Electron crystallography has an established track record in producing structures at both atomic and intermediate resolutions and represents a valuable alternative to X-ray crystallography and NMR spectroscopy, which are generally constrained to studying detergent-solubilized species. To date, electron crystallography remains a low-throughput operation, which has significantly reduced its contribution to membrane protein biology. We have developed some tools to overcome the bottlenecks in screening crystallization conditions, which we seek to expand in the current application. Specifically, we propose further developments for crystallization on a 96-well format by implementing a microfluidic device for dialysis that minimizes sample volumes and by using cyclodextrins to control detergent removal rates in an effort to optimize crystal quality. By studying a wide range of different target proteins, we will empirically establish factors that are most critical to influencing the crystallization process and develop a set of conditions that are generally effective for screening new proteins with unknown crystallization behaviors. We will continue developing our methods for robotic imaging of crystallization screens. The process of preparing samples and imaging them within the electron microscope currently represents the most significant bottleneck limiting the number of conditions that can be explored. We have built a robot for sample insertion and have interfaced it with automated image acquisition software, but we propose to add shape recognition to this software to maximize its efficiency. We will integrate the resulting images within an established LIMS database for keeping track of the structure determination pipeline and will implement shape recognition to enable automated assignment of scores to crystallization trials. Finally, we propose to develop an application for high resolution data collection from well-ordered crystals, thus facilitating the optimization of crystal size and order and, ultimately, acquisition of the data required for structure determination. We are convinced that by applying high- throughput methods to 2D crystallization and image acquisition, electron crystallography can make a substantial contribution to our understanding of membrane protein biology.