A correlative quantitative phase contrast and fluorescence super-resolution microscope for imaging molecules in their...

Area of Science:

• Biophysics
• Cell Biology
• Microscopy

Background:

• Fluorescence microscopy excels at visualizing labeled molecules but lacks cellular context.
• Quantitative phase contrast microscopy (QPC) offers complementary structural information.
• Integrating QPC with super-resolution fluorescence microscopy can overcome these limitations.

Purpose of the Study:

• To develop a combined microscopy platform integrating QPC and super-resolution fluorescence.
• To achieve high-sensitivity detection and 3D super-resolution imaging within cellular environments.
• To explore deep-learning-based digital staining for label-free organelle identification.

Main Methods:

• Correlative orientation-independent differential interference contrast (OI-DIC) microscopy was combined with single-molecule super-resolution fluorescence microscopy.
• Demonstrated detection sensitivity of 0.05 nm optical path difference.
• Employed deep learning for digital staining of cellular structures from OI-DIC data.

Main Results:

• Achieved 3D super-resolution fluorescence imaging within the cellular context.
• Demonstrated detection sensitivity sufficient for single microtubules.
• Successfully identified nuclei, mitochondria, and lipid droplets using deep-learning enabled digital staining.
• Showcased potential for long-term live-cell imaging of organelles without fluorescence.

Conclusions:

• The developed platform integrates QPC and super-resolution fluorescence for comprehensive cellular imaging.
• Deep learning enables label-free organelle identification and long-term live-cell imaging.
• OI-DIC is easily integrated into existing fluorescence microscopes, making it widely adoptable.