Mechanical strain enhances survivability of collagen micronetworks in the presence of collagenase: implications for load-bearing matrix growth and stability

Abstract

There has been great interest in understanding the methods by which collagen-based load-bearing tissue is constructed, grown and maintained in vertebrate animals. To date, the responsibility for this process has largely been placed with mesenchymal fibroblastic cells that are thought to fully control the morphology of load-bearing extracellular matrix (ECM). However, given clear limitations in the ability of fibroblastic cells to precisely place or remove single collagen molecules to sculpt tissue, we have hypothesized that the material itself must play a critical role in the determination of the form of structural ECM. We here demonstrate directly, using live, dynamic, differential interference contrast imaging, that mechanically strained networks of collagen fibrils, exposed to collagenase (Clostridium histolyticum), degrade preferentially. Specifically, unstrained fibrils are removed 'quickly', while strained fibrils persist significantly longer. The demonstration supports the idea that collagen networks are mechanosensitive in that they are stabilized by mechanical strain. Thus, collagen molecules (together with their complement enzymes) may comprise the basis of a smart, load-adaptive, structural material system. This concept has the potential to drastically simplify the assumed role of the fibroblast, which would need only to provide ECM molecules and mechanical force to sculpt collagenous tissue.

Figure 1.

(a) Schematic of the experimental setup used to carry out degradation of strained collagen under DIC microscopy. (b) Micropipette position and collagen gel in strained and unstrained form inside the microchamber. (c) Image of microchamber in situ. The design of the chamber permits manipulation of a small reaction volume.

Figure 2.

Contrast normalization and background noise removal. (a) Original histogram distribution in the image taken from the initially captured ROI. (b) Contrast enhancement is accomplished by stretching the lower value of the histogram to 0 and the higher value of the histogram to 255. (c) The width of the gamma line is kept constant about the mean value (brightness) of the histogram in all subsequent images. Thus, the contrast of all subsequent fibril edge strengths will be normalized to that of the initial fibrillar array. (d) The range of contrast noise in the histogram taken from a ‘fibril’-free area was typically subtracted from the histograms following edge detection. In this case, the noise floor was removed by ‘zeroing’ all pixel values below 32.

Figure 3.

Time-series DIC and edge-detected ROI during both gelation and degradation of collagen. (a–f) Larger image in each figure is the DIC of the entire field of view at 600×. The upper right image is a high magnification view of the ROI delineated by the white box to the left. The lower right image is the edge-detected signal, which is scaled to reflect the intensity of the DIC gradient. (g) Graph of the integration of the edge-detected ROI during the experiment. Each point on the plot represents the summation of all pixel intensities within the ROI. Because the pixel intensity is related to the diameter of a fibril in DIC (below the diffraction limit), each point on the plot is a scaled representation of the volume of fibrils within the focal plane in the ROI. (h) Transmission electron microscopy image of a quick-freeze, deep-etched gel sample from control (no pipettes) fibrillogenesis experiment, showing both banded and unbanded fibrils, along with a network of, presumably, much smaller fibrils. Mean fibril diameters are 121 nm (s.d.=18 nm) for banded fibrils and 64 nm (s.d.=11 nm) for unbanded fibrils. Scale bar, 20 μm (a–f); 500 nm (h); 200 nm ((h) inset).

Figure 4.

Representative plot showing quantification of edge loss against digestion time ΔT in control sample (no strain), where I_start is 95 per cent of (maximum edge detection intensity), I_finish is 10 per cent of and ΔT is the time (s) between. The small difference in the finishing times between the two unstrained ROIs within the same experiment is likely due to diffusion delay coupled with the inherent error in the optical edge-detection algorithm. Grey line, unstrained ROI1; black line, unstrained ROI2.

Figure 5.

DIC and edge-detected ROIs. (a) Intial strain on a heavily manipulated network of collagen fibrils. ROIs are strained (S) or unstrained (U). The translucent circle demarcates an area where collagen fibrils have been heavily compacted by our attempt to tension fibrils. The series of four boxes to the right of each large image represent: (upper left) high magnification of strained ROI, (upper right) corresponding detected edges, (lower left) high magnification of unstrained ROI and (lower right) corresponding edge-detected images. (b,c) Follow-on images showing the degradation sequence. Scale bar, 20 μm (a–c).

Figure 6.

DIC and edge-detected ROIs. (a) Initial strain on a gently manipulated network of collagen fibrils. ROIs are located under light tensile strain (S) or no observable strain (U). The four boxes to the right of each large image represent: (vertical boxes) high-magnification DIC and edge-detected signal, (horizontal boxes) high-magnification DIC and edge-detected signal. (b,c) Follow-on images in the sequence showing the pattern of degradation. Unstrained fibrils are removed significantly faster than fibrils loaded in tension. Scale bar, 20 μm (a–c).

Figure 7.

(a) Simulated fibril images (i) for diameters of 50, 150 and 250 nm and the result of the edge detection algorithm for each (ii). Note that the current edge-detection algorithm, in order to deal with noise, normalizes against a fibril-free image. The result of this normalization is a loss of some of the edge information, as can be seen by comparing detected edges with original images. (b) Normalized intensity versus fibril diameter. Note the linear relationship between intensity and diameter for 60–250 nm. (c) Normalized edge intensity and fibril radius in nanometres versus time during formation and enzymatic degradation of collagen fibrils (shown in figure 3).

Figure 8.

Representative plot showing quantification of edge loss against digestion time ΔT, where I_start is 95 per cent of (maximum edge detection), I_finish is 10 per cent of and ΔT is the time (s) between. Multiple analyses were completed to consider differences in digestion time based on I_start and I_finish of strained (S) and unstrained (U) fibrils. The residual strained fibril population that persists despite prolonged degradation is marked below 10 per cent . Grey line, strained; black line, unstrained.

Figure 9.

DIC images of the rapid degradation of the initially strained network shown in figure 2c. (a) Network of collagen fibrils after 3 min of exposure to bacterial collagenase. (b) After 8 min of exposure, fibrils loaded in tension are preserved while unloaded fibrils are preferentially removed from the field of view. Scale bar, 10μm (a,b).

Figure 10.

DIC and edge-detected ROIs in a similar experiment using MMP-8. (a) Initial strain on collagen fibrils formed between pipettes. ROIs are located as described previously, where S denotes a strained region and U denotes an unstrained region. The series of four boxes to the right of each large image are represented as described previously. Follow-on images (b,c) show the pattern of degradation as a function of time. These are preliminary unpublished results. Scale bar, 10 µm (a–c).

Figure 11.

DIC image showing what appears to be a substantial accumulation of assembled collagen fibrils in the area of applied tensile strain on the network between the pipettes. The increase in distance between the pipettes from the initial value was approximately 100 per cent. Scale bar, 20 µm.