Dataset Information

Deciphering structural elements of mucin glycoprotein recognition.

ABSTRACT: Mucin glycoproteins present a complex structural landscape arising from the multiplicity of glycosylation patterns afforded by their numerous serine and threonine glycosylation sites, often in clusters, and with variations in respective glycans. To explore the structural complexities in such glycoconjugates, we used NMR to systematically analyze the conformational effects of glycosylation density within a cluster of sites. This allows correlation with molecular recognition through analysis of interactions between these and other glycopeptides, with antibodies, lectins, and sera, using a glycopeptide microarray. Selective antibody interactions with discrete conformational elements, reflecting aspects of the peptide and disposition of GalNAc residues, are observed. Our results help bridge the gap between conformational properties and molecular recognition of these molecules, with implications for their physiological roles. Features of the native mucin motifs impact their relative immunogenicity and are accurately encoded in the antibody binding site, with the conformational integrity being preserved in isolated glycopeptides, as reflected in the antibody binding profile to array components.

SUBMITTER: Borgert A

PROVIDER: S-EPMC3508731 | biostudies-literature | 2012 Jun

REPOSITORIES: biostudies-literature

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Deciphering structural elements of mucin glycoprotein recognition.

Borgert Andrew A Heimburg-Molinaro Jamie J Song Xuezheng X Lasanajak Yi Y Ju Tongzhong T Liu Mian M Thompson Pamela P Ragupathi Govind G Barany George G Smith David F DF Cummings Richard D RD Live David D

ACS chemical biology 20120409 6

Mucin glycoproteins present a complex structural landscape arising from the multiplicity of glycosylation patterns afforded by their numerous serine and threonine glycosylation sites, often in clusters, and with variations in respective glycans. To explore the structural complexities in such glycoconjugates, we used NMR to systematically analyze the conformational effects of glycosylation density within a cluster of sites. This allows correlation with molecular recognition through analysis of in ...[more]

PMID: 22444368

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Project description:UnlabelledThroughout the last 3 decades, Ebola virus (EBOV) outbreaks have been confined to isolated areas within Central Africa; however, the 2014 variant reached unprecedented transmission and mortality rates. While the outbreak was still under way, it was reported that the variant leading up to this outbreak evolved faster than previous EBOV variants, but evidence for diversifying selection was undetermined. Here, we test this selection hypothesis and show that while previous EBOV outbreaks were preceded by bursts of diversification, evidence for site-specific diversifying selection during the emergence of the 2014 EBOV clade is weak. However, we show strong evidence supporting an interplay between selection and correlated evolution (epistasis), particularly in the mucin-like domain (MLD) of the EBOV glycoprotein. By reconstructing ancestral structures of the MLD, we further propose a structural mechanism explaining how the substitutions that accumulated between 1918 and 1969 distorted the MLD, while more recent epistatic substitutions restored part of the structure, with the most recent substitution being adaptive. We suggest that it is this complex interplay between weak selection, epistasis, and structural constraints that has shaped the evolution of the 2014 EBOV variant.ImportanceThe role that selection plays in the emergence of viral epidemics remains debated, particularly in the context of the 2014 EBOV outbreak. Most critically, should such evidence exist, it is generally unclear how this relates to function and increased virulence. Here, we show that the viral lineage leading up to the 2014 outbreak underwent a complex interplay between selection and correlated evolution (epistasis) in a protein region that is critical for immune evasion. We then reconstructed the three-dimensional structure of this domain and showed that the initial mutations in this lineage deformed the structure, while subsequent mutations restored part of the structure. Along this mutational path, the first and last mutations were adaptive, while the intervening ones were epistatic. Altogether, we provide a mechanistic model that explains how selection and epistasis acted on the structural constraints that materialized during the 2014 EBOV outbreak.

Dataset Information

Deciphering structural elements of mucin glycoprotein recognition.

Publications

Deciphering structural elements of mucin glycoprotein recognition.

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