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Modular approach for resolving and mapping complex neural and other cellular structures and their associated deformation fields in three dimensions

Abstract

Understanding the biological implications of cellular mechanotransduction, especially in the context of pathogenesis, requires the accurate resolution of material deformation and strain fields surrounding the cells. This is particularly challenging for cells displaying branched, 3D architectures. Here, we provide a modular approach for 3D image segmentation and strain mapping of topologically complex structures. We describe how to use our approach, using neural cells and networks as an example. In addition to describing how to implement the computational analysis, we provide details of a cell culture protocol that can be used to generate neural networks for analysis and experimentation. This protocol allows for transformation of matrix-induced strains, and their full resolution across single cells or networks in three dimensions. The protocol also provides analyses to compute both the locally varying cytoskeletal strains and the average strain experienced by cells. An additional module allows spatial correlation of these strain maps with cytoskeletal features, including neurite disruptions such as neuronal blebs. Image processing and strain mapping take ≥3 h, with the exact time required being dependent on use case, software familiarity, and file size.

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Bar-Kochba, E., Scimone, M. T., Estrada, J.B. & Franck, C. Sci. Rep. 6, 30550 (2016): https://doi.org/10.1038/srep30550

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Acknowledgements

The authors acknowledge M. Patel and A.K. Landauer for helpful discussions, and J. Toyjanova for assistance in early protocol development. The authors gratefully acknowledge financial support from the RI Science and Technology Council, a Haythornthwaite Research Initiation Grant, and the Office of Naval Research (T. Bentley). E.B.-K. acknowledges support from a National Science Foundation Graduate Research Fellowship. J.B.E. acknowledges support from a Graduate Assistance in Areas of National Need (GAANN) fellowship from the Brown University Institute for Molecular and Nanoscale Innovation.

Author information

M.T.S., E.B.-K., and J.B.E. worked on the initial cell culture development. E.B.-K. developed the image processing with assistance from J.B.E. for post processing. E.B.-K. and C.F. developed the strain mapping technique. R.A. and M.T.S. worked on code refinement. E.B.-K., M.T.S., and J.B.E. acquired the test images. H.C.C. and M.T.S. performed immunostaining and imaged all immunostained samples. M.T.S., H.C.C., and C.F. wrote the paper. All authors reviewed the manuscript. C.F. supervised the project.

Competing interests

The authors declare no competing interests.

Correspondence to Christian Franck.

Integrated supplementary information

Supplementary Figure 1 Mapping strains on tagged blebs.

Maximum intensity–projected confocal micrograph of a cell with artificially introduced spherical blebs (green arrows). Artificial blebs were introduced during image processing and do not represent signal from actual morphological processes. Blebs were tagged in NeuronStudio. Axial strain values were transformed onto the blebs using the same strain field as in Fig. 6a,b. Scale bar = 20 µm.

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Supplementary Figure 1 and Supplementary Manual

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Fig. 1: The culture platform and the resulting fiber and cell networks.
Fig. 2: Maximum intensity–projected confocal micrographs showing immunofluorescent signals of cells.
Fig. 3: Images of critical steps during dissection and sample preparation.
Fig. 4: Image processing workflow.
Fig. 5: Neuron tree projected in 3D with descriptors of tree structure node classifications.
Fig. 6: Example strain mappings.
Fig. 7: Control viability data and representative projection.
Supplementary Figure 1: Mapping strains on tagged blebs.

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