New methods to study the composition and structure of the extracellular matrix in natural and bioengineered tissues

Abstract

The extracellular matrix (ECM) comprises a gel of numerous biopolymers that occurs in a multitude of biological tissues. The ECM provides the basic support and mechanical strength of skeletal tissue and is responsible for shape retention. At the same time, the ECM is responsible for the viscoelastic properties and the elasticity of soft tissues. As expected, there are several important diseases that affect and degenerate the ECM with severe consequences for its properties. Bioengineering is a promising approach to support the regenerative capacity of the body. Unfortunately, the biomechanical properties of bioengineered ECM often only poorly meet the standards of their native counterparts. Many bioengineered tissues are characterized by an increased glycosaminoglycan (GAG) but decreased collagen content. This leads to an enhanced water content that strongly alters the viscoelastic and thus the biomechanical properties. Therefore, compositional analysis is important to estimate the tissue quality. We will show that nuclear magnetic resonance (NMR) spectroscopy and soft-ionization mass spectrometry (MS) represent useful techniques for ECM research both in natural and bioengineered tissues. Both methods are strongly complimentary: while MS techniques such as matrix-assisted laser desorption and ionization (MALDI) are excellent and very sensitive analytical tools to determine the collagen and the GAG contents of tissues, NMR spectroscopy provides insight into the molecular architecture of the ECM, its dynamics and other important parameters such as the water content of the tissue as well as the diffusion of molecules within the ECM.

Keywords: :

• biomechanics
• collagen
• extracellular matrix
• glycosaminoglycans
• mass spectrometry
• nuclear magnetic resonance
• tissue engineering

Disclosure of Potential Conflicts of Interest

No potential conflicts of interest were disclosed.

Acknowledgments

This work was supported by the German Research Council (TRR 67 projects A2 and A6). We would like to thank our colleagues and coworkers for many useful hints regarding this review.