Membrane-tethered mucin-like polypeptides sterically inhibit binding and slow fusion kinetics of influenza A virus

Significance Influenza A viruses cause tens of millions of cases of seasonal flu each year. Before a virus infects a host cell, it must first pass through a dense forest of sugar-bearing proteins called mucins. The basic mechanisms of how the virus navigates and chops down this forest of mucins remain up for debate, and many flu drugs target the interactions of the virus with mucin-like proteins. In this work, we make synthetic versions of mucins to create an artificial forest that can be tuned and modified at a molecular level to study how mucins impact influenza A virus binding and fusion. The mechanism(s) by which cell-tethered mucins modulate infection by influenza A viruses (IAVs) remain an open question. Mucins form both a protective barrier that can block virus binding and recruit IAVs to bind cells via the sialic acids of cell-tethered mucins. To elucidate the molecular role of mucins in flu pathogenesis, we constructed a synthetic glycocalyx to investigate membrane-tethered mucins in the context of IAV binding and fusion. We designed and synthesized lipid-tethered glycopolypeptide mimics of mucins and added them to lipid bilayers, allowing chemical control of length, glycosylation, and surface density of a model glycocalyx. We observed that the mucin mimics undergo a conformational change at high surface densities from a compact to an extended architecture. At high surface densities, asialo mucin mimics inhibited IAV binding to underlying glycolipid receptors, and this density correlated to the mucin mimic’s conformational transition. Using a single virus fusion assay, we observed that while fusion of virions bound to vesicles coated with sialylated mucin mimics was possible, the kinetics of fusion was slowed in a mucin density-dependent manner. These data provide a molecular model for a protective mechanism by mucins in IAV infection, and therefore this synthetic glycocalyx provides a useful reductionist model for studying the complex interface of host–pathogen interactions.