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Mechanically-sensitive miRNAs bias human mesenchymal stem cell fate via mTOR signalling.


ABSTRACT: Mechanotransduction is a strong driver of mesenchymal stem cell (MSC) fate. In vitro, variations in matrix mechanics invoke changes in MSC proliferation, migration and differentiation. However, when incorporating MSCs within injectable, inherently soft hydrogels, this dominance over MSC response substantially limits our ability to couple the ease of application of hydrogels with efficiently directed MSC differentiation, especially in the case of bone generation. Here, we identify differential miRNA expression in response to varying hydrogel stiffness and RhoA activity. We show that modulation of miR-100-5p and miR-143-3p can be used to bias MSC fate and provide mechanistic insight by demonstrating convergence on mTOR signalling. By modulating these mechanosensitive miRNAs, we can enhance osteogenesis in a soft 3D hydrogel. The outcomes of this study provide new understanding of the mechanisms regulating MSC mechanotransduction and differentiation, but also a novel strategy with which to drive MSC fate and significantly impact MSC-based tissue-engineering applications.

SUBMITTER: Frith JE 

PROVIDER: S-EPMC5772625 | biostudies-literature | 2018 Jan

REPOSITORIES: biostudies-literature

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Mechanically-sensitive miRNAs bias human mesenchymal stem cell fate via mTOR signalling.

Frith Jessica E JE   Kusuma Gina D GD   Carthew James J   Li Fanyi F   Cloonan Nicole N   Gomez Guillermo A GA   Cooper-White Justin J JJ  

Nature communications 20180117 1


Mechanotransduction is a strong driver of mesenchymal stem cell (MSC) fate. In vitro, variations in matrix mechanics invoke changes in MSC proliferation, migration and differentiation. However, when incorporating MSCs within injectable, inherently soft hydrogels, this dominance over MSC response substantially limits our ability to couple the ease of application of hydrogels with efficiently directed MSC differentiation, especially in the case of bone generation. Here, we identify differential mi  ...[more]

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