Abstract
Microcracks in materials reflect their mechanical properties. The quantification of the number or orientation of such cracks is thus essential in many fields, including engineering and geology. In biology, cracks in soft tissues can reflect adhesion defects, and the analysis of their pattern can help to deduce the magnitude and orientation of tensions in organs and tissues. Here, we describe a semi-automatic method amenable to analyze cell separations occurring in the epidermis of Arabidopsis thaliana seedlings. Our protocol is applicable to any image exhibiting small cracks, and thus also adapted to the analysis of emerging cracks in animal tissues and materials.
Highlights
Microcracks are present in most materials; their number and extent generally increase when repeated stress is applied or when the temperature fluctuates, causing material fatigue and eventually, failure
Cracks can be observed in soft tissues, notably as a result of cell to cell adhesion defects
Cell Separation Image Analysis Pipeline (Image analysis script described in this protocol) Note: See “Installation procedure” in “Procedure” for the installation of Software 2 to 5
Summary
Microcracks are present in most materials; their number and extent generally increase when repeated stress is applied or when the temperature fluctuates, causing material fatigue and eventually, failure. Cracks can be observed in soft tissues, notably as a result of cell to cell adhesion defects. The contrast between the cells and the cracks is strong enough to detect and quantify cell separations After segmenting these cracks, a principal component analysis is performed on each of these segmented areas, yielding various information: area of the crack as well as its principal orientation (angle of the crack) and the shape anisotropy (derived from the eigen values and vectors calculated in the principal component analysis of the crack shape). Other staining method may be used on any types of tissues or materials, as long as the contrast is strong enough for the script to detect the cracks. Pandas (Data manipulation and analysis library) (https:// pandas.pydata.org/) d. Cell Separation Image Analysis Pipeline (Image analysis script described in this protocol) (https://github.com/sverger/Cell_separation_analysis) Note: See “Installation procedure” in “Procedure” for the installation of Software 2 to 5
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