YAP phosphorylation within integrin adhesions: insights from a computational model

Hamidreza Jafarinia, Lidan Shi, Haguy Wolfenson, Aurélie Carlier*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Mechanical and biochemical cues intricately activate Yes-associated protein (YAP), which is pivotal for the cellular responses to these stimuli. Recent findings reveal an unexplored role of YAP in influencing the apoptotic process. It has been shown that, on soft matrices, YAP is recruited to small adhesions, phosphorylated at Y357, and translocated into the nucleus triggering apoptosis. Interestingly, YAP Y357 phosphorylation is significantly reduced in larger mature focal adhesions on stiff matrices. Building upon these novel insights, we have developed a stochastic model to delve deeper into the complex dynamics of YAP phosphorylation within integrin adhesions. Our findings emphasize several key points: firstly, increasing the cytosolic diffusion rate of YAP correlates with higher levels of phosphorylated YAP (pYAP); secondly, increasing the number of binding sites and distributing them across the membrane surface, mimicking smaller adhesions, leads to higher pYAP levels, particularly at lower diffusion rates. Moreover, we show that the binding and release rate of YAP to adhesions as well as adhesion lifetimes significantly influence the size effect of adhesion-induced YAP phosphorylation. The results highlight the complex and dynamic interplay between adhesion lifetime, the rate of pYAP unbinding from adhesions, and dephosphorylation rates, collectively shaping overall pYAP levels. In summary, our work advances the understanding of YAP mechanotransduction and opens avenues for experimental validation.

Original languageEnglish
Pages (from-to)3658-3668
Number of pages11
JournalBiophysical Journal
Volume123
Issue number21
Early online date3 Sept 2024
DOIs
Publication statusPublished - 5 Nov 2024

Keywords

  • YAP phosphorylation
  • integrin adhesions
  • particle-based stochastic model

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