A Multiscale Molecular Dynamic Analysis Reveals the Effect of Sialylation on EGFR Clustering in a CRISPR/Cas9-Derived Model

Abstract

Bacterial and viral pathogens can modulate the glycosylation of key host proteins to facilitate pathogenesis by using various glycosidases, particularly sialidases. Epidermal growth factor receptor (EGFR) signaling is activated by ligand-induced receptor dimerization and oligomerization. Ligand binding induces conformational changes in EGFR, leading to clusters and aggregation. However, information on the relevance of EGFR clustering in the pattern of glycosylation during bacterial and viral invasion remains unclear. In this study, (1) we established CRISPR/Cas9-mediated GFP knock-in (EGFP-KI) HeLa cells expressing fluorescently tagged EGFR at close to endogenous levels to study EGF-induced EGFR clustering and molecular dynamics; (2) We studied the effect of sialylation on EGF-induced EGFR clustering and localization in live cells using a high content analysis platform and raster image correlation spectroscopy (RICS) coupled with a number and brightness (N&B) analysis; (3) Our data reveal that the removal of cell surface sialic acids by sialidase treatment significantly decreases EGF receptor clustering with reduced fluorescence intensity, number, and area of EGFR-GFP clusters per cell upon EGF stimulation. Sialylation appears to mediate EGF-induced EGFR clustering as demonstrated by the change of EGFR-GFP clusters in the diffusion coefficient and molecular brightness, providing new insights into the role of sialylation in EGF-induced EGFR activation; and (4) We envision that the combination of CRISPR/Cas9-mediated fluorescent tagging of endogenous proteins and fluorescence imaging techniques can be the method of choice for studying the molecular dynamics and interactions of proteins in live cells.

Keywords

• CRISPR/Cas9
• sialylation
• EGFR clustering
• dynamic molecular study
• number and brightness (N&B) analysis
• raster image correlation spectroscopy (RICS)