Capillary-Based and Stokes-Based Trapping of Serial Sections for Scalable 3D-EM Connectomics

Area of Science:

• Neuroscience
• Biophysics
• Materials Science

Background:

• Serial section electron microscopy (ssEM) is crucial for reconstructing brain anatomy.
• Handling delicate tissue sections (10^2-10^3) is a significant bottleneck in mesoscale ssEM.
• Current methods lack automation and precision for large-scale section handling.

Purpose of the Study:

• To develop and validate a novel device for automated handling of serial tissue sections in ssEM.
• To improve the efficiency and reliability of section transfer for 3D-EM connectomics.
• To extend the mathematical modeling of forces involved in section handling.

Main Methods:

• A tissue section handling device was designed to interface with an ultramicrotomy knife.
• The device utilizes exact-constraint trapping for precise section positioning (100-μm repeatability).
• A mathematical model incorporating capillary and Stokes forces was developed to describe section behavior.

Main Results:

• The device successfully handled hundreds of serial sections onto microscopy substrates with minimal defects (0.50% loss rate).
• Automated handling achieved a throughput of 63 seconds per section.
• Demonstrated reliable mesoscale section handling for 8 datasets (126 sections each).

Conclusions:

• The developed device and mathematical model represent a significant advancement in automated mesoscale serial sectioning.
• This system enables scalable 3D-EM connectomics by addressing critical section handling challenges.
• The findings pave the way for more efficient and comprehensive brain connectome mapping.