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Investigating Receptor-ligand Systems of the Cellulosome with AFM-based Single-molecule Force Spectroscopy
Published on: December 20, 2013
Single-molecule force spectroscopy of ligand-receptor mechanics at extracellular vesicle biointerfaces
Sakurako Tani1, Reed Jacobson2, Sangdeuk Ha2
1Department of Physics, North Dakota State University, Fargo, ND 58108, USA. yongki.choi@ndsu.edu.
Abstract:
Extracellular vesicles (EVs) are nanoscale membrane-bound particles that present surface receptors for affinity capture, sensing, and targeted biointerface design. Although EV surface-marker expression is widely used to guide ligand selection, the molecular-scale rupture mechanics and force-dependent dissociation behavior of EV receptor-ligand interactions remain poorly understood. Here, atomic force microscopy-based single-molecule force spectroscopy and dynamic force spectroscopy are used to quantify ligand-accessible recognition, rupture-force distributions, and apparent Bell-Evans parameters for three pancreatic cancer-associated EV surface targets: integrins (ITG), epithelial cell adhesion molecule (EpCAM), and glypican-1 (GPC1). EVs derived from PANC-1 and hTERT-HPNE cells were compared as a model system. PANC-1 EVs exhibited higher particle concentrations and stronger ITG and GPC1 expression than HPNE EVs. AFM recognition maps showed markedly higher apparent ITG recognition and moderately higher GPC1 recognition on PANC-1 EVs, whereas EpCAM recognition was similar between the two EV preparations. Fixed-speed rupture-force distributions and loading-rate-dependent analysis revealed interaction-dependent differences in apparent rupture behavior. Across both EV preparations, EpCAM-antibody interactions tended to show higher apparent force-free off-rates than ITG-cRGD and GPC1-antibody interactions, while ITG and GPC1 were less clearly separated. Together with recognition mapping, these results demonstrate that ligand-accessible recognition and force-dependent rupture behavior provide complementary information about EV surface interactions.

