High-throughput Pipeline for Electron Crystallography

电子晶体学高通量管道

• 批准号: 8991232
• 负责人: David L. Stokes
• 金额: $ 9.07万
• 依托单位: NEW YORK UNIVERSITY SCHOOL OF MEDICINE
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-30 至 2015-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8991232
• 关键词: throughput; Pipeline; Electron; Crystallography

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.

描述（由申请人提供）：生物膜包围所有细胞，并介导它们与外界的相互作用。根据生物学背景，膜蛋白充当受体、酶、通道、转运蛋白、结构蛋白和细胞粘附分子，并且因此有助于多种基本细胞功能。膜蛋白的结构信息相对较少，尽管它们代表了在美国销售的60%的治疗药物的目标。我们建议建立一个管道确定膜蛋白结构的电子晶体学，这是应用低温电子显微镜二维晶体。为了制备这样的晶体，用高密度的纯化的膜蛋白重构膜双层，从而为组成蛋白提供天然的膜环境和较少的结晶约束。电子晶体学在产生原子和中间分辨率的结构方面有着既定的记录，并且代表了X射线晶体学和NMR光谱学的有价值的替代方案，X射线晶体学和NMR光谱学通常限于研究洗涤剂溶解的物质。到目前为止，电子晶体学仍然是一个低通量的操作，这大大降低了其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，我们寻求在当前的应用中扩展这些工具。具体而言，我们提出了进一步的发展结晶96孔格式通过实施微流体装置透析，最大限度地减少样品体积，并通过使用环糊精来控制洗涤剂的去除率，努力优化晶体质量。通过研究各种不同的目标蛋白质，我们将凭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具有未知结晶行为的新蛋白质的条件。我们将继续开发我们的方法，用于结晶屏幕的机器人成像。制备样品并在电子显微镜内对其成像的过程目前代表了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机器人的样品插入，并与自动图像采集软件，但我们建议添加形状识别到这个软件，以最大限度地提高其效率。我们将在已建立的LIMS数据库中整合所得图像，以跟踪结构测定流程，并将实施形状识别，以实现结晶试验评分的自动分配。最后，我们建议开发一个应用程序，从有序的晶体高分辨率的数据收集，从而促进晶体尺寸和顺序的优化，并最终，所需的结构确定的数据采集。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贡献。