Simultaneous spatiotemporal super-resolution and multi-parametric fluorescence microscopy

Area of Science:

• Biophysics
• Cell Biology
• Microscopy

Background:

• Super-resolution microscopy and single-molecule fluorescence spectroscopy traditionally optimize for either spatial or temporal resolution, limiting simultaneous analysis.
• Achieving high resolution in both domains is crucial for understanding dynamic cellular processes and molecular interactions.

Purpose of the Study:

• To develop and validate a GPU-supported, camera-based measurement strategy for simultaneous super-resolution of spatial and temporal dynamics.
• To enable multi-parametric analysis from a single dataset for improved physicochemical parameter estimation.

Main Methods:

• Implementation of a GPU-supported, camera-based measurement strategy.
• Simultaneous acquisition of data for super-resolution of spatial structures (~100 nm) and temporal dynamics (~2 ms).
• Pixel-wise cross-correlation analysis of parameters from the same dataset.

Main Results:

• Achieved simultaneous high spatial (~100 nm) and temporal (~2 ms) resolution from a single dataset.
• Improved precision in estimating the diffusion coefficient of Lifeact and corrected structural artifacts.
• Demonstrated that epidermal growth factor receptor (EGFR) domain partitioning is mainly driven by membrane interactions, not actin interactions.

Conclusions:

• The developed method allows for robust physicochemical parameter estimation and biological discovery not possible with sequential measurements.
• Pixel-wise cross-correlation of multi-parametric data from a single dataset is a powerful approach for biological insights.
• EGFR organization within the cell membrane is primarily influenced by membrane and EGFR-EGFR interactions.