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Helical self-assembly of a mucin segment suggests an evolutionary origin for von Willebrand factor tubules.

Gabriel JavittDeborah Fass
Published in: Proceedings of the National Academy of Sciences of the United States of America (2022)
The glycoprotein von Willebrand factor (VWF) contributes to hemostasis by stanching injuries in blood vessel walls. A distinctive feature of VWF is its assembly into long, helical tubules in endothelial cells prior to secretion. When VWF is released into the bloodstream, these tubules unfurl to release linear polymers that bind subendothelial collagen at wound sites, recruit platelets, and initiate the clotting cascade. VWF evolved from gel-forming mucins, the polymeric glycoproteins that coat and protect exposed epithelia. Despite the divergent function of VWF in blood vessel repair, sequence conservation and shared domain organization imply that VWF retained key aspects of the mucin bioassembly mechanism. Here, we show using cryo-electron microscopy that the ability to form tubules, a property hitherto thought to have arisen as a VWF adaptation to the vasculature, is a feature of the amino-terminal region of mucin. This segment of the human intestinal gel-forming mucin (MUC2) was found to self-assemble into tubules with a striking resemblance to those of VWF itself. To facilitate a comparison, we determined the residue-resolution structure of tubules formed by the homologous segment of VWF. The structures of the MUC2 and VWF tubules revealed the flexible joints and the intermolecular interactions required for tubule formation. Steric constraints in full-length MUC2 suggest that linear filaments, a previously observed supramolecular assembly form, are more likely than tubules to be the physiological mucin storage intermediate. Nevertheless, MUC2 tubules indicate a possible evolutionary origin for VWF tubules and elucidate design principles present in mucins and VWF.
Keyphrases
  • endothelial cells
  • machine learning
  • high resolution
  • gene expression
  • drug delivery
  • dna damage
  • deep learning
  • oxidative stress
  • dna methylation
  • multidrug resistant
  • klebsiella pneumoniae
  • energy transfer