Smart event-triggered MINFLUX microscopy to catch and follow rare events

Area of Science:

• Biophysics
• Cell Biology
• Microscopy

Background:

• MINFLUX microscopy offers unparalleled spatial and temporal resolution for molecular studies.
• Current MINFLUX acquisition times are lengthy, limiting its application for dynamic cellular processes.
• Manual control restricts the efficiency and scope of MINFLUX applications in live-cell imaging.

Purpose of the Study:

• To develop an automated, event-triggered MINFLUX microscopy method to overcome acquisition speed limitations.
• To enable high-resolution imaging of dynamic cellular events in real-time.
• To expand the applicability of MINFLUX for studying complex biological processes.

Main Methods:

• Developed event-triggered MINFLUX using confocal monitoring and real-time image analysis.
• Implemented an open-source Python framework for automated control of a commercial MINFLUX microscope.
• Applied the method to investigate membrane dynamics during caveolae formation, endocytosis, and HIV-1 budding.

Main Results:

• Successfully triggered MINFLUX acquisition based on real-time detection of cellular events.
• Achieved high-resolution 2D and 3D imaging of molecular membrane dynamics during critical cellular processes.
• Acquired data previously unfeasible with manual microscope control, demonstrating significantly improved efficiency.

Conclusions:

• Event-triggered MINFLUX significantly enhances acquisition speed and data throughput for live-cell imaging.
• This smart microscopy approach enables the study of transient molecular events with unprecedented detail.
• The developed open-source framework democratizes advanced MINFLUX applications in cell biology and biophysics.