Short communicationNovel image analysis methods for quantification of in situ 3-D tendon cell and matrix strain
Introduction
Tendons are load-bearing tissues that are essential for joint motion and stability. Macroscopic loads modulate cellular responses prompting an array of biological outcomes such as maintained homeostasis, degeneration, or repair. However, a major gap in our understanding of mechanotransduction pathways stems from the fact that the influence of macroscopic deformations on the microstructural response remains unknown. Our overarching hypothesis is that the unique relationship between extracellular matrix strain and cell deformation dictates biological outcomes. A first step towards addressing this hypothesis is the ability to characterize the local strain environment. Two-dimensional methods have been used to determine matrix strain by applying speckle patterns and photobleached lines to the surface (Andarawis-Puri et al., 2009, Cheng and Screen, 2007, Luyckx et al., 2014), or by tracking the planar movement of nuclei centroids (Arnoczky et al., 2002, Screen et al., 2004). Additionally, nuclear deformation methods continually identify the 2-D focal plane of maximum cross-sectional area to observe changes in aspect ratio (Arnoczky et al., 2002). Despite the value gained from established 2-D methods, 3-D methods are integral for capturing the complexity of the local strain environment that can arise from out-of-plane motion, particularly in the highly cellular, injured state. Therefore, the objectives of this study were (1) to assess the accuracy of digital volume correlation (DVC) to quantify 3-D matrix strain using images of the innate tendon microstructure, (2) to develop and validate a method for 3-D cell deformation and (3) to develop and validate a method for cell-matrix strain, a measure of the relationship between matrix strain and cell deformation.
Section snippets
Image acquisition and processing
Patellar tendons from C57BL/6 mice (n = 3) were stained with Hoechst 33258 (Thermo-Fisher) nucleic acid stain and nominally loaded to 100 g. Z-stack images (20×) through a depth of 50 µm were acquired using multiphoton microscopy for stained nuclei imaging (Fig. 1A) and second harmonic generation (SHG) imaging of the collagen fiber matrix (Fig. 1B). For the purpose of cell deformation and cell-matrix strain method development, cell nuclei images were assumed to represent those of cell
3-D matrix strain
For naïve tendon cell images (Fig. 1A), level of applied strain positively correlated with error in the X-direction (r = 1, p = .0004) and standard deviation within each sample (r = 1, p = .0004) (Fig. 6). In the Z-direction (r = 0.4286, p = .3536), however, there was no correlation between level of applied strain and error (Fig. 7A). Results for injured tendon cell images (Fig. 1C) in the X- (r = 0.9286, p = .0067) and Z-directions (r = 0, p > .999) were similar (Fig. 7C). In contrast, for SHG
Discussion
We developed image analysis methods for calculating 3-D matrix strain, 3-D cell deformation, and 3-D cell-matrix strain in tendon. This 3-D approach is unique because it considers out-of-plane motion, which can occur from misalignment with the uniaxial loading direction or anisotropy. 2-D methods have been used extensively to quantify strain transfer from the macro to microscales (Han et al., 2013, Upton et al., 2008), but many studies acknowledge that results are confounded by artifacts from
Conflict of interest
The authors have no conflict of interest.
Acknowledgements
This study was supported by grants from the NIH/NIAMS (AR052743 & AR068301). Imaging data was acquired through the Cornell University Biotechnology Resource Center with NIH S10OD018516 funding.
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