Influence of multi-axial dynamic constraint on cell alignment and contractility in engineered tissues

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Abstract

In this study an experimental rig is developed to investigate the influence of tissue constraint and cyclic loading on cell alignment and active cell force generation in uniaxial and biaxial engineered tissues constructs. Addition of contractile cells to collagen hydrogels dramatically increases the measured forces in uniaxial and biaxial constructs under dynamic loading. This increase in measured force is due to active cell contractility, as is evident from the decreased force after treatment with cytochalasin D. Prior to dynamic loading, cells are highly aligned in uniaxially constrained tissues but are uniformly distributed in biaxially constrained tissues, demonstrating the importance of tissue constraints on cell alignment. Dynamic uniaxial stretching resulted in a slight increase in cell alignment in the centre of the tissue, whereas dynamic biaxial stretching had no significant effect on cell alignment. Our active modelling framework accurately predicts our experimental trends and suggests that a slightly higher (3%) total SF formation occurs at the centre of a biaxial tissue compared to the uniaxial tissue. However, high alignment of SFs and lateral compaction in the case of the uniaxially constrained tissue results in a significantly higher (75%) actively generated cell contractile stress, compared to the biaxially constrained tissue. These findings have significant implications for engineering of contractile tissue constructs.

Introduction

A growing interest in the biomechanical behaviour of cells seeded in 3D culture has emerged in recent years. Mechanical priming strategies have been developed in an ongoing drive to engineer tissues with increased functional viability (Baker et al., 2008; Berry et al., 2003; Billiar et al., 2005; Cummings et al., 2004; Isenberg and Tranquillo, 2003; Mauck et al., 2003, 2000; Seliktar et al., 2000). Previous studies demonstrate that the application of 3D substrate stretch can up-regulate gene expression, promote differentiation, cause cell orientation redistribution, increase proliferation, and increase extracellular matrix synthesis (Berry et al., 2003; Campbell et al., 2007; Foolen et al., 2014; Gabbay et al., 2006). Given that cells actively respond to loading in the 3D microenvironment, it is important to develop a fundamental mechanistic understanding of the effects of mechanical conditioning on 3D synthetic tissue constructs. Therefore, the development of a robust system that can apply different uniaxial and biaxial deformation regimes to engineered hydrogel constructs while measuring the active and passive force, as presented in the current study, can provide new insights into the link between tissue constraint and active force generation.

Stretching of 2D substrates containing semi-confluent cell monolayers reveals that stress fibres (SFs) exhibit stretch avoidance (Barron et al., 2007; Kaunas et al., 2005; Neidlinger-Wilke et al., 2001; Wang et al., 2001). Stretch avoidance has also been reported in 3D substrates (Foolen et al., 2014). However, it has been more commonly reported that SF orientations remain unchanged during cyclic deformation (Foolen et al., 2012; Gauvin et al., 2011a; Nieponice et al., 2007a; Wakatsuki and Elson, 2002; Wille et al., 2006; Zhao et al., 2013). Cell contractile forces have previously been measured in tissues subjected to uniaxial stretching (Wagenseil et al., 2004; Wakatsuki et al., 2001, 2000; Wille et al., 2006; Zhao et al., 2014, 2013). Biaxial stretching has been employed to characterize cellular and scaffold fibres deformations (Gilbert et al., 2006; Courtney et al., 2006; Stella et al., 2008). However, due to the significant technical challenge of tissue force measurement during dynamic biaxial stretching, the influence of constraint on dynamic force generation has not been reported to date. A study by Thavandiran et al. (2013) provides a quantitative comparison of cell alignment and stress fibre formation on biaxially and uniaxially statically constrained collagen gels. However, force measurement is not performed, so the influence of constraint and dynamic loading on cell contractility is not uncovered. The current study provides a key advance investigating the influence of tissue constraint and dynamic loading on cell contractility and cell alignment.

In this investigation a bespoke experimental system is developed for measurement of cell and tissues forces during biaxial and uniaxial dynamic stretching. In addition to measuring the evolution of cell and tissue force, cell alignment throughout biaxial and uniaxial tissues is also characterised. In order to interpret experimental measurements for uniaxially and biaxially loaded tissues, a novel thermodynamically motivated model for cell contractility and remodelling is combined with an anisotropic hyperelastic model of the collagen gel to simulate the uniaxial and biaxial experiments. Simulations accurately predict the alignment and contractility of cells in biaxial and uniaxial constrained tissues and reveal that actively generated cell stress is significantly higher in the case of uniaxial loading.

Section snippets

Sample preparation

Human cardiomyocytes (HCM) isolated from a 24 year old male donor were obtained from Promocell (C-12810 (lot number 4051303.1), Heidelerg, Germany). Cells were grown as per Promocell protocols. Cell passages between P8 and P12, with a split ratio of 1:2, were used for all experiments (cells were observed to become senescent at P14). One week after plating in T25 flasks cell monolayers were observed to reach 100% confluency. Cells were observed to be highly elongated and aligned with

Collagen-cell gel contraction

After gelling, the collagen-cell solution samples are incubated for 2 days before mechanical testing. During this 2-day period cells elongate and spread within the three-dimensional collagen matrix and endogenous force generated by SFs leads to gel contraction. In Fig. 2 a quantitative analysis of the deformation of uniaxial and biaxial tissues is shown. In uniaxial tissues the width of specific sections along the length are measured (Fig. 2-A). For each measurement a significant reduction from

Computational analysis

The experimental measurements presented above suggest that active cell contractility significantly contributes to the measured force for both biaxial and uniaxial tissues. Experiments also reveal significantly different patterns of cell alignment in uniaxial and biaxial tissue. However, the active stress generated by cells in uniaxial and biaxial tissues can only be parsed through a model framework that accounts for active cell contractility and alignment.

Finite element simulations (Abaqus,

Discussion

In this investigation we develop a novel experimental methodology that allows for the observation of cell alignment, while characterizing cell contractility through measurement of active force in both uniaxial and biaxial tissues under dynamic loading. We also implement a novel modelling framework to parse the relationship between active stress generation and cell alignment observed in our experiments. Our characterisation of the coupling between cell contractility and alignment in biaxial and

Author contributions

Patrick McGarry and Noel H. Reynolds designed the study.

Noel H. Reynolds and Eoin McEvoy performed the experiments.

Noel H. Reynolds, Patrick McGarry and Juan Alberto Panadero Pérez analysed the experimental data.

Noel H. Reynolds, Eoin McEvoy, Ryan J. Coleman and Patrick McGarry performed the computational analysis.

All authors contributed to the preparation of figures and writing of the manuscript.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

Funding was provided by Science Foundation Ireland (grants 18/ERCD/5481 and SFI/IP/1723). The authors would like to acknowledge the Irish Centre for High-End Computing (ICHEC) for provision of computational facilities and support. The authors thank Dr. Dimitrios Zeugolis for providing RTT collagen.

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