Abstract

Super-resolution microscopy and single molecule fluorescence spectroscopy require mutually exclusive experimental strategies optimizing either time or spatial resolution. To achieve both, we implement a GPU-supported, camera-based measurement strategy that highly resolves spatial structures (~60 nm), temporal dynamics ([≤] 2 ms), and molecular brightness from the exact same data set. We demonstrate the applicability and advantages of multi-parametric measurements to monitor the super-resolved structure and dynamics of two different biomolecules, the actin binding polypeptide LifeAct, and the epidermal growth factor receptor (EGFR). Simultaneous super-resolution of spatial and temporal details leads to an improved precision in estimating the diffusion coefficient of LifeAct in dependence of the cellular actin network. Multi-parametric analysis 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 new biological knowledge that cannot be obtained from sequential measurements.