Visual Biochemistry: modular microfluidics enables kinetic insight from time-resolved cryo-EM

Märt-Erik Mäeots,Byungjin Lee,Andrea Nans, Seung-Geun Jeong,Mohammad M. N. Esfahani, Daniel J. Smith,Chang-Soo Lee,Sung Sik Lee, Matthias Peter,Radoslav I. Enchev

bioRxiv (Cold Spring Harbor Laboratory)(2020)

引用 0|浏览2
暂无评分
摘要
Mechanistic understanding of biochemical reactions requires structural and kinetic characterization of the underlying chemical processes. However, no single experimental technique can provide this information in a broadly applicable manner and thus structural studies of static macromolecules are often complemented by biophysical analysis. Moreover, the common strategy of utilizing mutants or crosslinking probes to stabilize otherwise short-lived reaction intermediates is prone to trapping off-pathway artefacts and precludes determining the order of molecular events. To overcome these limitations and allow visualisation of biochemical processes at near-atomic spatial resolution and millisecond time scales, we developed a time-resolved sample preparation method for cryo-electron microscopy (trEM). We integrated a modular microfluidic device, featuring a 3D-mixing unit and a delay line of variable length, with a gas-assisted nozzle and motorised plunge-freeze set-up that enables automated, fast, and blot-free sample vitrification. This sample preparation not only preserves high-resolution structural detail but also substantially improves protein distribution across the vitreous ice. We validated the method by examining the formation of RecA filaments on single-stranded DNA. We could reliably visualise reaction intermediates of early filament growth across three orders of magnitude on sub-second timescales. Quantification of the trEM data allowed us to characterize the kinetics of RecA filament growth. The trEM method reported here is versatile, easy to reproduce and thus readily adaptable to a broad spectrum of fundamental questions in biology.
更多
查看译文
关键词
modular microfluidics,kinetic insight,time-resolved
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要