Abstract:

Biomechanical cues such as shear stress, stretching, compression, and matrix elasticity are vital in the establishment of next generation physiological in vitro tissue models. Matrix elasticity, for instance, is known to guide stem cell differentiation, influence healing processes and modulate extracellular matrix (ECM) deposition needed for tissue development and maintenance. To better understand the biomechanical effect of matrix elasticity on the formation of articular cartilage analogs in vitro, this study aims at assessing the redifferentiation capacity of primary human chondrocytes in three different hydrogel matrices of predefined matrix elasticities. The hydrogel elasticities were chosen to represent a broad spectrum of tissue stiffness ranging from very soft tissues with a Young's modulus of 1 kPa up to elasticities of 30 kPa, representative of the perichondral-space. In addition, the interplay of matrix elasticity and transforming growth factor beta-3 (TGF-β3) on the redifferentiation of primary human articular chondrocytes was studied by analyzing both qualitative (viability, morphology, histology) and quantitative (RT-qPCR, sGAG, DNA) parameters, crucial to the chondrotypic phenotype. Results show that fibrin hydrogels of 30 kPa Young's modulus best guide chondrocyte redifferentiation resulting in a native-like morphology as well as induces the synthesis of physiologic ECM constituents such as glycosaminoglycans (sGAG) and collagen type II. This comprehensive study sheds light onto the mechanobiological impact of matrix elasticity on formation and maintenance of articular cartilage and thus represents a major step toward meeting the need for advanced in vitro tissue models to study both re- and degeneration of articular cartilage.

Keywords: 3D cell culture; Young’s modulus; cartilage; chondrocytes; extracellular matrix; hydrogel.

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Stiffness Matters: Fine-Tuned Hydrogel Elasticity Alters Chondrogenic Redifferentiation

^{Faculty of Technical Chemistry, Institute of Applied Synthetic Chemistry and Institute of Chemical Technologies and Analytics, Vienna University of Technology, Vienna, Austria}

^{AUVA Research Centre, Ludwig Boltzmann Institute for Experimental and Clinical Traumatology, Vienna, Austria}

^{Competence Center MechanoBiology, Vienna, Austria}

^{Austrian Cluster for Tissue Regeneration, Vienna, Austria}

^{University Clinic of Dentistry, Medical University of Vienna, Vienna, Austria}

^{Department Life Science Engineering, University of Applied Sciences Technikum Wien, Vienna, Austria}

^{Division of Trauma-Surgery, Department of Orthopedics and Trauma-Surgery, Medical University of Vienna, Vienna, Austria}

Edited by: Miloslav Pekař, Brno University of Technology, Czechia

Reviewed by: Khoon Lim, University of Otago, Christchurch, New Zealand; Felix B. Engel, University Hospital Erlangen, Germany

*Correspondence: Sylvia Nürnberger, ta.ca.neiwinudem@regrebnreun.aivlys

Peter Ertl, ta.ca.neiwut@ltre.retep

^{These authors have contributed equally to this work}

This article was submitted to Biomaterials, a section of the journal Frontiers in Bioengineering and Biotechnology

Edited by: Miloslav Pekař, Brno University of Technology, Czechia

Reviewed by: Khoon Lim, University of Otago, Christchurch, New Zealand; Felix B. Engel, University Hospital Erlangen, Germany

Received 2019 Oct 22; Accepted 2020 Apr 3.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

Abstract

Biomechanical cues such as shear stress, stretching, compression, and matrix elasticity are vital in the establishment of next generation physiological in vitro tissue models. Matrix elasticity, for instance, is known to guide stem cell differentiation, influence healing processes and modulate extracellular matrix (ECM) deposition needed for tissue development and maintenance. To better understand the biomechanical effect of matrix elasticity on the formation of articular cartilage analogs in vitro, this study aims at assessing the redifferentiation capacity of primary human chondrocytes in three different hydrogel matrices of predefined matrix elasticities. The hydrogel elasticities were chosen to represent a broad spectrum of tissue stiffness ranging from very soft tissues with a Young’s modulus of 1 kPa up to elasticities of 30 kPa, representative of the perichondral-space. In addition, the interplay of matrix elasticity and transforming growth factor beta-3 (TGF-β3) on the redifferentiation of primary human articular chondrocytes was studied by analyzing both qualitative (viability, morphology, histology) and quantitative (RT-qPCR, sGAG, DNA) parameters, crucial to the chondrotypic phenotype. Results show that fibrin hydrogels of 30 kPa Young’s modulus best guide chondrocyte redifferentiation resulting in a native-like morphology as well as induces the synthesis of physiologic ECM constituents such as glycosaminoglycans (sGAG) and collagen type II. This comprehensive study sheds light onto the mechanobiological impact of matrix elasticity on formation and maintenance of articular cartilage and thus represents a major step toward meeting the need for advanced in vitro tissue models to study both re- and degeneration of articular cartilage.

Keywords: cartilage, chondrocytes, 3D cell culture, extracellular matrix, hydrogel, Young’s modulus

Abstract

Acknowledgments

The authors want to acknowledge Marian Fürsatz for primary human chondrocyte isolation and cultivation and Michaela Stainer for assisting in RNA isolation and RT-qPCR execution and analysis. Additionally, the authors want to recognize Stefan Baudis for assistance in oscillatory rheology and Elias Salzer for silk fibroin isolation. The graphical abstract (Figure 1) was created using BioRender.com.

Acknowledgments

Footnotes

Funding. This work was partly funded by the European Union’s INTERREG V-A AT-CZ programme (ATCZ133). The authors acknowledge TU Wien University Library for financial support through its Open Access Funding Program.

Footnotes

Click here for additional data file.^{(300K, TIF)}Click here for additional data file.^{(117K, TIF)}Click here for additional data file.^{(2.1M, TIF)}Click here for additional data file.^{(1.3M, TIF)}Click here for additional data file.^{(251K, TIF)}Click here for additional data file.^{(282K, TIF)}

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