Back

Velcro-like mannose and slime-like sialic acid interactions guide self- adhesion and aggregation of virus N-glycan shields

Ogharandunkun, E.; Tewolde, W.; Damtae, E.; Wang, S.; Ivanov, A.; Kumari, N.; Nekhai, S.; Chandran, P.

2020-05-02 biophysics
10.1101/2020.05.01.072769 bioRxiv
Show abstract

The surfaces of cells and pathogens are covered with short polymers of sugars known as glycans. Complex N-glycans have a core of three mannose sugars, with distal repeats of N-acetylglucosamine and galactose sugars terminating with sialic acid (SA). Long-range slime-like and short-range Velcro-like self-adhesions were observed between SA and mannose residues, respectively, in ill-defined monolayers. We investigated if and how these adhesions translate when SA and mannose residues are presented in complex N-glycan shields on two pseudo-typed viruses brought together in force spectroscopy (FS). Slime-like adhesions were observed between the shields at higher ramp rates, whereas Velcro-like adhesions were observed at lower rates. The complex glycan shield appears penetrable at the lower ramp rates allowing the adhesion from the mannose core to be accessed; whereas the whole virus appears compressed at higher rates permitting only surface SA adhesions to be sampled. The slime-like and velcro-like adhesions were lost when SA and mannose, respectively, were cleaved with glycosidases. While virus self-adhesion in FS was modulated by glycan penetrability, virus self-aggregation in solution was only determined by the surface sugar. Mannose-terminal viruses self-aggregated in solution, while SA-terminal ones required Ca2+ ions to self-aggregate. Viruses with galactose or N-acetylglucosamine surfaces did not self-aggregate, irrespective of whether or not a mannose core was present below the N-acetylglucosamine surface. Well-defined rules appear to govern the self-adhesion and -aggregation of N-glycosylated surfaces, regardless of whether the sugars are presented in ill-defined monolayer, or N-glycan, or even polymer architecture.

Matching journals

The top 12 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.