Here, we overcome these problems by acquiring images with high sensitivity and high-speed, using low laser powers at physiological concentrations with genetically encoded labels from the cell-biology fluorophore toolbox 16, using commercially available cameras and applying graphics processing unit (GPU)-based data processing. While simultaneous multi-parametric fluorescence detection (MFD) has been established for point-measurements 13, 14, simultaneous parameter estimations in an imaging mode have been limited 15 and have been hampered by a lack of strategies that can bridge the limitations imposed by spatial and temporal resolution requirements and by the computationally expensive data evaluation procedures required to treat the large data sets. Attempts in the past either restricted time resolution 3, 4 or concentration 5, 6, required specialized instrumentation 7, 8, 9, 10, or needed specialized sample labelling 11, 12. Since these two limits, in general, do not lead to an overlap region, the combination of spatiotemporal super-resolution microscopy has remained a challenge. Molecular dynamics requires acquisition times shorter than the dynamics of interest and thus sets an upper limit. Spatial resolution depends on the number of photons collected and thus sets a lower limit on acquisition time. However, the acquisition of structure and dynamics requires complementary 1, often mutually exclusive optimization strategies 2. 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.įull knowledge of a biological system requires not only information on its spatial structure but also its temporal dynamics. 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. 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. 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.
Super-resolution microscopy and single molecule fluorescence spectroscopy require mutually exclusive experimental strategies optimizing either temporal or spatial resolution.