用于常规和高级结构生物学的样品制备,包括序列数据收集、显微电子显微镜和低温电子显微镜

Stefan A. Kolek, Patrick Shaw Stewart, Jack Stubbs, P. Baldock
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引用次数: 0

摘要

序列数据收集通常需要相对较小的晶体,而且晶体排列有序。微播种是生成此类样品的有效方法。自随机微种子矩阵筛选(rMMS)方法发表以来的十年间,人们对该方法的理论优势有了更多的了解[2 4],并出现了几种该方法的实用变体。此外,播种可以在微批-油下装置中进行,这种装置易于按体积放大,并便于解释相图。将这些技术结合在一起,可以加强控制,提高常规和高级数据收集的样品质量。用低温电子显微镜测定蛋白质结构需要昂贵的设备,而且吞吐量低。因此,检查那些事先就能证明是聚集在一起的样品是一种浪费,因为这些样品不太可能是合适的。我们利用动态光散射的高通量筛选方法,在只有 10 μL 蛋白质溶液的情况下探索了 96 种化学条件,以确定减少聚集的条件。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Sample preparation for routine and advanced structural biology, including serial data collection, MicroED and cryo-EM
Serial data collection usually requires relatively small crystals that are well-ordered. Microseeding is an effective way to generate such samples. During the ten years since the random microseed matrix-screening (rMMS) method was published, understanding of the theoretical advantages of the method has increased [2 4], and several practical variations of the method have emerged. Moreover seeding can be carried out in a microbatch-underoil setup, which is easy to scale up, volume-wise, and allows easy interpretation of phase diagrams. By combining these techniques, control can be increased and sample quality for both routine and advanced data collection improved. Protein structure determination by cryoEM requires expensive equipment that has low throughput. It is therefore wasteful to examine samples that can be shown in advance to be aggregated, since such samples are unlikely to be suitable. We used a high-throughput screening approach with dynamic light scattering to explore 96 chemical conditions with as little as 10 μL of protein solution to identify conditions with reduced aggregation.
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