Structure of Merkel Cell Polyomavirus Capsid and Interaction with Its Glycosaminoglycan Attachment Receptor

默克尔细胞多瘤病毒衣壳的结构及其与其糖胺聚糖附着受体的相互作用

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作者:Niklas J Bayer, Dovile Januliene, Georg Zocher, Thilo Stehle, Arne Moeller, Bärbel S Blaum

Abstract

Merkel cell polyomavirus (MCPyV) is a human double-stranded DNA tumor virus. MCPyV cell entry is unique among members of the polyomavirus family as it requires the engagement of two types of glycans, sialylated oligosaccharides and sulfated glycosaminoglycans (GAGs). Here, we present crystallographic and cryo-electron microscopic structures of the icosahedral MCPyV capsid and analysis of its glycan interactions via nuclear magnetic resonance (NMR) spectroscopy. While sialic acid binding is specific for α2-3-linked sialic acid and mediated by the exposed apical loops of the major capsid protein VP1, a broad range of GAG oligosaccharides bind to recessed regions between VP1 capsomers. Individual VP1 capsomers are tethered to one another by an extensive disulfide network that differs in architecture from previously described interactions for other PyVs. An unusual C-terminal extension in MCPyV VP1 projects from the recessed capsid regions. Mutagenesis experiments show that this extension is dispensable for receptor interactions.IMPORTANCE The MCPyV genome was found to be clonally integrated in 80% of cases of Merkel cell carcinoma (MCC), a rare but aggressive form of human skin cancer, strongly suggesting that this virus is tumorigenic. In the metastasizing state, the course of the disease is often fatal, especially in immunocompromised individuals, as reflected by the high mortality rate of 33 to 46% and the low 5-year survival rate (<45%). The high seroprevalence of about 60% makes MCPyV a serious health care burden and illustrates the need for targeted treatments. In this study, we present the first high-resolution structural data for this human tumor virus and demonstrate that the full capsid is required for the essential interaction with its GAG receptor(s). Together, these data can be used as a basis for future strategies in drug development.

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