Preparation and characterization of tissue surrogates rich in extracellular matrix using the principles of macromolecular crowding
Zeugolis, Dimitrios I.
MetadataShow full item record
This item's downloads: 190 (view details)
Cited 3 times in Scopus (view citations)
Djalali-Cuevas, Adrian, Garnica-Galvez, Sergio, Rampin, Andrea, Gaspar, Diana, Skoufos, Ioannis, Tzora, Athina, Prassinos, Nikitas, Diakakis, Nikolaos, Zeugolis, Dimitrios I. (2019). Preparation and Characterization of Tissue Surrogates Rich in Extracellular Matrix Using the Principles of Macromolecular Crowding. In: Vigetti D., Theocharis A.D. (eds) The Extracellular Matrix. Methods in Molecular Biology, vol 1952, doi:10.1007/978-1-4939-9133-4_20
Tissue engineering by self-assembly allows for the fabrication of living tissue surrogates by taking advantage of the cell's inherent ability to produce and deposit tissue-specific extracellular matrix. However, the long culture periods required to build a tissue substitute in conducive to phenotypic drift in vitro microenvironments result in phenotype and function losses. Although several biophysical microenvironmental modulators (e.g., surface topography, substrate stiffness, mechanical stimulation) have been used to address these issues, slow extracellular matrix deposition remains a limiting factor in clinical translation and commercialization of such therapies. Macromolecular crowding is an alternative in vitro microenvironment modulator that has been shown to accelerate extracellular matrix deposition by several orders of magnitude, thereby decreasing culture periods required for the development of an implantable device, while maintaining cell phenotype and function. Herein, we provide protocols for the production of tissue surrogates rich in extracellular matrix from human dermal fibroblasts, equine tenocytes, and equine adipose-derived stem cells using the principles of macromolecular crowding and the subsequent characterization thereof by means of immunofluorescent staining and complementary fluorescence intensity analysis.