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Adv Mater. 2017 Mar;29(10). doi: 10.1002/adma.201603259. Epub 2016 Dec 19.

Linking the Transcriptional Landscape of Bone Induction to Biomaterial Design Parameters.

Author information

1
Department of Tissue Regeneration, University of Twente, Drienerlolaan 5, 7522, NB, Enschede, The Netherlands.
2
MERLN Institute for Technology-inspired Regenerative Medicine, Maastricht University, Universiteitssingel 40, 6229, ER, Maastricht, The Netherlands.
3
Xpand Biotechnology B.V, Professor Bronkhorstlaan 10, 3723, MB, Bilthoven, The Netherlands.

Abstract

New engineering possibilities allow biomaterials to serve as active orchestrators of the molecular and cellular events of tissue regeneration. Here, the molecular control of tissue regeneration for calcium phosphate (CaP)-based materials is established by defining the parameters critical for tissue induction and those are linked to the molecular circuitry controlling cell physiology. The material properties (microporosity, ion composition, protein adsorption) of a set of synthesized osteoinductive and noninductive CaP ceramics are parameterized and these properties are correlated to a transcriptomics profile of osteogenic cells grown on the materials in vitro. Using these data, a genetic network controlling biomaterial-induced bone formation is built. By isolating the complex material properties into single-parameter test conditions, it is verified that a subset of these genes is indeed controlled by surface topography and ions released from the ceramics, respectively. The gene network points to a decisive role for extracellular matrix deposition in osteoinduction by genes such as tenascin C and hyaluronic acid synthase 2, which are controlled by calcium and phosphate ions as well as surface topography. This work provides insight into the biomaterial composition and material engineering aspects of bone void filling and can be used as a strategy to explore the interface between biomaterials and tissue regeneration.

KEYWORDS:

biomaterials; bone-graft substitutes; gene networks; regenerative medicine; transcriptomics

PMID:
27991696
DOI:
10.1002/adma.201603259

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