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基于新一代测序芯片的单分子动力学的大规模平行分析。

Massively parallel analysis of single-molecule dynamics on next-generation sequencing chips.

机构信息

Department of Cell and Molecular Biology, Science for Life Laboratory, Uppsala University, 75105 Uppsala, Sweden.

Department of Medical Sciences, Science for Life Laboratory, Uppsala University, 75144 Uppsala, Sweden.

出版信息

Science. 2024 Aug 23;385(6711):892-898. doi: 10.1126/science.adn5371. Epub 2024 Aug 22.

Abstract

Single-molecule techniques are ideally poised to characterize complex dynamics but are typically limited to investigating a small number of different samples. However, a large sequence or chemical space often needs to be explored to derive a comprehensive understanding of complex biological processes. Here we describe multiplexed single-molecule characterization at the library scale (MUSCLE), a method that combines single-molecule fluorescence microscopy with next-generation sequencing to enable highly multiplexed observations of complex dynamics. We comprehensively profiled the sequence dependence of DNA hairpin properties and Cas9-induced target DNA unwinding-rewinding dynamics. The ability to explore a large sequence space for Cas9 allowed us to identify a number of target sequences with unexpected behaviors. We envision that MUSCLE will enable the mechanistic exploration of many fundamental biological processes.

摘要

单分子技术非常适合于描述复杂的动态过程,但通常仅限于研究少数不同的样本。然而,为了全面了解复杂的生物过程,往往需要探索一个大的序列或化学空间。在这里,我们描述了一种在文库规模上进行的多重单分子特性分析方法(MUSCLE),该方法将单分子荧光显微镜与下一代测序相结合,能够对复杂的动态进行高度多重化的观察。我们全面分析了 DNA 发夹特性和 Cas9 诱导的靶 DNA 解旋-缠绕动力学的序列依赖性。对 Cas9 的大规模序列空间的探索能力使我们能够识别出许多具有意外行为的靶序列。我们设想 MUSCLE 将能够对许多基本的生物学过程进行机制探索。

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