Fused deep-learning enables 6D single-molecule localization in polarization-resolved microscopy

Area of Science:

• Optics and Photonics
• Biophysics
• Materials Science

Background:

• Single-molecule orientation localization microscopy (SMOLM) is crucial for studying molecular dynamics in complex environments.
• Current SMOLM techniques face challenges in achieving simultaneous high-resolution spatial and orientational localization with photon efficiency.

Purpose of the Study:

• To develop an advanced optical microscope for six-dimensional (6D) single-molecule localization.
• To integrate deep learning for enhanced localization accuracy and efficiency in SMOLM.

Main Methods:

• Utilized a double-helix point spread function in an optical fluorescence microscope for 6D localization.
• Developed a fused deep learning approach for precise dipole emitter localization.
• Validated the system by localizing rhodamine B in polymer films and Nile red in lipid bilayers.

Main Results:

• Achieved median spatial precision of 10 nm and angular precision below 10° for single fluorophores.
• Demonstrated robust 6D localization, except for azimuthal angle limitations at high polar angles.
• Observed ordered molecular orientations in both polymer films and lipid bilayers.

Conclusions:

• The developed microscope and deep learning method significantly advance SMOLM capabilities.
• Enables precise spatiotemporal and orientational tracking of molecules in challenging biological and material systems.
• Opens new avenues for investigating molecular transport and organization at the nanoscale.