Modular approach for resolving and mapping complex neural and other cellular structures and their associated...

Area of Science:

• Biophysics
• Cell Biology
• Neuroscience
• Biomaterials

Background:

• Cellular mechanotransduction is critical for understanding biological processes and pathogenesis.
• Accurate measurement of deformation and strain fields around cells is essential but challenging, especially for complex 3D cellular architectures like neural networks.
• Existing methods often lack the resolution or modularity to analyze intricate cellular structures.

Purpose of the Study:

• To develop and present a modular computational approach for 3D image segmentation and strain mapping.
• To enable the analysis of material deformation and strain fields in topologically complex cellular structures.
• To provide a detailed protocol for generating and analyzing neural networks under matrix-induced strains.

Main Methods:

• A modular 3D image segmentation technique for complex cellular structures.
• A computational framework for strain mapping, including local cytoskeletal strains and average cellular strain.
• A cell culture protocol to generate neural networks for experimental analysis and strain transformation.

Main Results:

• Successful implementation of a 3D strain mapping approach for neural cells and networks.
• Quantification of matrix-induced strains and their resolution across individual cells and networks.
• Correlation of strain maps with cytoskeletal features and identification of neurite disruptions like neuronal blebs.

Conclusions:

• The developed modular approach provides a robust method for analyzing cellular mechanotransduction in complex 3D biological systems.
• This technique facilitates a deeper understanding of the role of mechanical forces in neural network biology and pathogenesis.
• The provided protocol and computational tools are valuable for researchers studying cellular mechanics and neural network function.