Department of Biological Sciences and NUS Centre for Bio-Imaging Sciences, National University of Singapore, Singapore, Singapore.
Department of Statistics and Applied Probability, National University of Singapore, Singapore, Singapore.
Nat Commun. 2021 Mar 19;12(1):1748. doi: 10.1038/s41467-021-22002-9.
Super-resolution microscopy and single molecule fluorescence spectroscopy require mutually exclusive experimental strategies optimizing either temporal or spatial resolution. To achieve both, we implement a GPU-supported, camera-based measurement strategy that highly resolves spatial structures (100 nm), temporal dynamics (2 ms), and molecular brightness from the exact same data set. Simultaneous super-resolution of spatial and temporal details leads to an improved precision in estimating the diffusion coefficient of the actin binding polypeptide Lifeact and corrects structural artefacts. Multi-parametric analysis of epidermal growth factor receptor (EGFR) and Lifeact suggests that the domain partitioning of EGFR is primarily determined by EGFR-membrane interactions, possibly sub-resolution clustering and inter-EGFR interactions but is largely independent of EGFR-actin interactions. These results demonstrate that pixel-wise cross-correlation of parameters obtained from different techniques on the same data set enables robust physicochemical parameter estimation and provides biological knowledge that cannot be obtained from sequential measurements.
超分辨率显微镜和单分子荧光光谱学需要相互排斥的实验策略，以优化时间或空间分辨率。为了同时实现这两个目标，我们采用了基于 GPU 的相机测量策略，该策略可从同一数据集高度解析空间结构（100nm）、时间动态（2ms）和分子亮度。对空间和时间细节的同时超分辨率处理可提高对肌动蛋白结合多肽 Lifeact 扩散系数的估计精度，并校正结构伪影。表皮生长因子受体 (EGFR) 和 Lifeact 的多参数分析表明，EGFR 的结构域分区主要由 EGFR-膜相互作用决定，可能还包括亚分辨率聚类和 EGFR 之间的相互作用，但在很大程度上与 EGFR-肌动蛋白相互作用无关。这些结果表明，对同一数据集上不同技术获得的参数进行逐像素互相关，可实现稳健的物理化学参数估计，并提供无法从顺序测量中获得的生物学知识。
