cell–matrix mechanics in tendon fascicles and seeded collagen gels: implications for the multiscale design of biomaterials

Neil A. Duncan, Sabina B. Bruehlmann, Christopher J. Hunter, Xinxin Shao and Elizabeth J. Kelly

Computer Methods in Biomechanics and Biomedical Engineering, 2014, vol. 17, issue 1, 39-47

Abstract: Designing biomaterials to mimic and function within the complex mechanobiological conditions of connective tissues requires a detailed understanding of the micromechanical environment of the cell. The objective of our study was to measure the in situ cell–matrix strains from applied tension in both tendon fascicles and cell-seeded type I collagen scaffolds using laser scanning confocal microscopy techniques. Tendon fascicles and collagen gels were fluorescently labelled to simultaneously visualise the extracellular matrix and cell nuclei under applied tensile strains of 5%. There were significant differences observed in the micromechanics at the cell–matrix scale suggesting that the type I collagen scaffold did not replicate the pattern of native tendon strains. In particular, although the overall in situ tensile strains in the matrix were quite similar (∼2.5%) between the tendon fascicles and the collagen scaffolds, there were significant differences at the cell–matrix boundary with visible shear across cell nuclei of >1 μm measured in native tendon which was not observed at all in the collagen scaffolds. Similarly, there was significant non-uniformity of intercellular strains with relative sliding observed between cell rows in tendon which again was not observed in the collagen scaffolds where the strain environment was much more uniform. If the native micromechanical environment is not replicated in biomaterial scaffolds, then the cells may receive incorrect or mixed mechanical signals which could affect their biosynthetic response to mechanical load in tissue engineering applications. This study highlights the importance of considering the microscale mechanics in the design of biomaterial scaffolds and the need to incorporate such features in computational models of connective tissues.

Date: 2014
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DOI: 10.1080/10255842.2012.742075

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