生物
计算生物学
冠状病毒
糖基化
Spike(软件开发)
病毒学
鸡传染性支气管炎病毒
聚糖
多序列比对
血清型
序列比对
进化动力学
遗传学
传输(电信)
病毒
系统发育树
序列分析
生物信息学
严重急性呼吸综合征冠状病毒2型(SARS-CoV-2)
序列(生物学)
肉毒神经毒素
序列母题
穗蛋白
鸡传染性支气管炎
作者
Heng Zhang,ZongXi HAN,Chuangchao Zou,Yihui Huang,Shiping Sun,Ouyang Peng,Usama Ashraf,Qiuping Xu,Yao Ge,Qixiang Kang,Xiuli Ma,Xinheng Zhang,Ye Zhao,X. Yang,Hongning Wang,Guozhong Zhang,Qingmei Xie,Mǎng Shī,Yongsen Ruan,Min Liao
摘要
Abstract Avian infectious bronchitis virus (IBV), a gammacoronavirus with substantial agricultural impact, offers a tractable model for dissecting coronavirus evolution. Here, we integrated 20 years of epidemiological surveillance with whole‐genome sequence analysis of 624 IBV strains, including 136 newly isolated field samples, to investigate the evolutionary and structural dynamics of N‐linked glycosylation at the spike protein. We identified three dominant glycosylation haplotypes defined by residues 51 and 77 of spike protein, which correlate with receptor‐binding interfaces, clinical phenotypes, and spatiotemporal transmission patterns. Molecular modeling and docking analyses provided insights into potential mechanistic links between glycan positioning and Neu5Acα2‐3Galβ1‐3GlcNAc receptor engagement. Complementing these findings, we developed a proof‐of‐concept machine learning model that shows potential for predicting clinical serotypes directly from the spike protein sequence, achieving high accuracy on a preliminary independent validation set. These findings support the use of glycosylation motifs as structural‐genomic markers and highlight the potential of sequence‐based serotype prediction. Our work establishes a scalable genomic‐structural framework that leverages glycosylation motifs and sequence features as evolutionary markers, providing a powerful approach for forecasting coronavirus adaptation and informing vaccine design and outbreak preparedness.
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