Department of Physics and Biological Physics Research Group, University of Oxford, Oxford, United Kingdom.
Biophys J. 2011 Mar 16;100(6):1568-77. doi: 10.1016/j.bpj.2011.01.066.
Histograms of single-molecule Förster resonance energy transfer (FRET) efficiency are often used to study the structures of biomolecules and relate these structures to function. Methods like probability distribution analysis analyze FRET histograms to detect heterogeneities in molecular structure, but they cannot determine whether this heterogeneity arises from dynamic processes or from the coexistence of several static structures. To this end, we introduce burst variance analysis (BVA), a method that detects dynamics by comparing the standard deviation of FRET from individual molecules over time to that expected from theory. Both simulations and experiments on DNA hairpins show that BVA can distinguish between static and dynamic sources of heterogeneity in single-molecule FRET histograms and can test models of dynamics against the observed standard deviation information. Using BVA, we analyzed the fingers-closing transition in the Klenow fragment of Escherichia coli DNA polymerase I and identified substantial dynamics in polymerase complexes formed prior to nucleotide incorporation; these dynamics may be important for the fidelity of DNA synthesis. We expect BVA to be broadly applicable to single-molecule FRET studies of molecular structure and to complement approaches such as probability distribution analysis and fluorescence correlation spectroscopy in studying molecular dynamics.
单分子Förster 共振能量转移 (FRET) 效率的直方图常用于研究生物分子的结构，并将这些结构与功能联系起来。概率分布分析等方法分析 FRET 直方图以检测分子结构中的异质性，但它们无法确定这种异质性是来自动态过程还是来自几种静态结构的共存。为此，我们引入了突发方差分析 (BVA)，这是一种通过比较随时间变化的单个分子的 FRET 标准偏差与理论预期的标准偏差来检测动力学的方法。DNA 发夹的模拟和实验都表明，BVA 可以区分单分子 FRET 直方图中静态和动态异质性的来源，并可以根据观察到的标准偏差信息对动力学模型进行测试。使用 BVA，我们分析了大肠杆菌 DNA 聚合酶 I 的 Klenow 片段的手指闭合转变，并在核苷酸掺入之前形成的聚合酶复合物中鉴定出大量动力学；这些动力学对于 DNA 合成的保真度可能很重要。我们预计 BVA 将广泛适用于单分子 FRET 研究分子结构，并补充概率分布分析和荧光相关光谱学等方法在研究分子动力学方面的作用。
