Notch in mechanotransduction – from molecular mechanosensitivity to tissue mechanostasis

Oscar M. J. A. Stassen, Tommaso Ristori, Cecilia M. Sahlgren*

*Corresponding author for this work

Research output: Contribution to journalReview Article or Literature Reviewpeer-review

1 Citation (Scopus)

Abstract

Tissue development and homeostasis are controlled by mechanical cues. Perturbation of the mechanical equilibrium triggers restoration of mechanostasis through changes in cell behavior, while defects in these restorative mechanisms lead to mechanopathologies, for example, osteoporosis, myopathies, fibrosis or cardiovascular disease. Therefore, sensing mechanical cues and integrating them with the biomolecular cell fate machinery is essential for the maintenance of health. The Notch signaling pathway regulates cell and tissue fate in nearly all tissues. Notch activation is directly and indirectly mechanosensitive, and regulation of Notch signaling, and consequently cell fate, is integral to the cellular response to mechanical cues. Fully understanding the dynamic relationship between molecular signaling, tissue mechanics and tissue remodeling is challenging. To address this challenge, engineered microtissues and computational models play an increasingly large role. In this Review, we propose that Notch takes on the role of a ‘mechanostat’, maintaining the mechanical equilibrium of tissues. We discuss the reciprocal role of Notch in the regulation of tissue mechanics, with an emphasis on cardiovascular tissues, and the potential of computational and engineering approaches to unravel the complex dynamic relationship between mechanics and signaling in the maintenance of cell and tissue mechanostasis.
Original languageEnglish
Article numberjcs250738
Number of pages14
JournalJournal of Cell Science
Volume133
Issue number24
DOIs
Publication statusPublished - 21 Dec 2020
MoE publication typeA2 Review article in a scientific journal

Keywords

  • Notch signaling
  • Mechanotransduction
  • Engineered model systems
  • Computational modeling
  • Cardiovascular mechanics

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