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CD44 and β1-integrin are both engaged in cell traction force generation in hyaluronic acid-rich extracellular matrices.

Brian C H CheungXingyu ChenHannah J DavisJoshua TothJeffrey E SegallVivek B ShenoyMingming Wu
Published in: bioRxiv : the preprint server for biology (2023)
Mechanical properties of the extracellular matrices (ECMs) critically regulate a number of important cell function including growth, differentiation and migration. Type I collagen and glycosaminoglycans (GAGs) are two primary components of ECMs that contribute to tissue mechanics with the collagen fiber network sustaining tension and GAGs withstanding compression. Collagen stiffness as well as its architecture are known to be important role players in cell-ECM mechanical interactions, however, much less is known about how GAGs within ECMs regulate cell force generation and invasion. Inspired by a recent theoretical work from the Shenoy lab that GAGs play important roles in cell - ECM interactions, we hereby present experimental studies on the role of hyaluronic acid (HA, an unsulfated GAG) in single tumor cell traction force generation within HA collagen cogels using a recently developed 3D cell traction force microscopy. Our work revealed that CD44, a cell surface adhesion receptor to HA, was engaged in cell traction force generation in conjunction with β1-integrin. Furthermore, we found that HA significantly modified the architecture and mechanics of the collagen fiber network, decreased tumor cells' propensity to remodel the collagen network, decreased traction force generation and transmission distance, and attenuated tumor invasion in agreement with theoretical predictions. Our findings highlighted the significance of CD44 and HA engagement in cell-ECM mechanical interactions, providing new insights on the mechanical model of cellular force transmission.
Keyphrases
  • single cell
  • cell therapy
  • single molecule
  • hyaluronic acid
  • stem cells
  • staphylococcus aureus
  • high throughput
  • social media
  • bone marrow
  • cell surface
  • binding protein
  • network analysis
  • candida albicans