Single-molecule localization and diffusivity microscopy reveals dynamic biomolecular organization in living cells

Area of Science:

• Cellular and Molecular Biology
• Biophysics
• Microscopy and Imaging Technologies

Background:

• Single-molecule tracking is crucial for understanding protein dynamics in living cells.
• Current methods require sparse imaging, limiting the density of molecular mapping.
• High-density mapping of molecular diffusivity and organization is needed to understand complex cellular processes.

Purpose of the Study:

• To introduce a novel deep learning-based approach, single-molecule localization and diffusivity microscopy (SMLDM), for high-density mapping of molecular dynamics in live cells.
• To overcome the limitations of conventional single-molecule tracking methods.
• To provide a tool for spatially super-resolved mapping of molecular diffusivity and organization.

Main Methods:

• Developed SMLDM, a deep learning approach utilizing single-frame snapshots to estimate single-molecule movement and diffusion coefficients.
• Implemented SMLDM as mobility photoactivated localization microscopy (MPALM) with bright photoactivatable fluorophores.
• Employed U-Net-based single-molecule segmentation for accurate localization and diffusivity estimation.

Main Results:

• Achieved a 50- to 300-fold increase in data density compared to conventional tracking methods.
• Generated high-density, spatially super-resolved maps of molecular diffusivity and organization in living human cells.
• Uncovered novel insights into nucleosome clustering, receptor dynamics, focal adhesion movement, and early droplet coalescence.

Conclusions:

• SMLDM provides a powerful and efficient tool for analyzing biomolecular organization and dynamics at single-molecule resolution in live cells.
• This method enables the study of diverse dynamic cellular processes with unprecedented detail.
• SMLDM significantly advances the field of live-cell imaging and molecular dynamics research.