已入深夜,您辛苦了!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!祝你早点完成任务,早点休息,好梦!

Immune evasion and ACE2 binding affinity contribute to SARS-CoV-2 evolution

突变 生物 免疫系统 遗传学 谱系(遗传) 逃避(道德) 突变率 突变积累 免疫逃逸 抗体 基因
作者
Wentai Ma,Haoyi Fu,Fanchong Jian,Yunlong Cao,Mingkun Li
出处
期刊:Nature Ecology and Evolution [Nature Portfolio]
卷期号:7 (9): 1457-1466 被引量:56
标识
DOI:10.1038/s41559-023-02123-8
摘要

Mutations in the SARS-CoV-2 genome could confer resistance to pre-existing antibodies and/or increased transmissibility. The recently emerged Omicron subvariants exhibit a strong tendency for immune evasion, suggesting adaptive evolution. However, because previous studies have been limited to specific lineages or subsets of mutations, the overall evolutionary trajectory of SARS-CoV-2 and the underlying driving forces are still not fully understood. Here we analysed all open-access SARS-CoV-2 genomes (up to November 2022) and correlated the mutation incidence and fitness changes with the impacts of mutations on immune evasion and ACE2 binding affinity. Our results show that the Omicron lineage had an accelerated mutation rate in the RBD region, while the mutation incidence in other genomic regions did not change dramatically over time. Mutations in the RBD region exhibited a lineage-specific pattern and tended to become more aggregated over time, and the mutation incidence was positively correlated with the strength of antibody pressure. Additionally, mutation incidence was positively correlated with changes in ACE2 binding affinity, but with a lower correlation coefficient than with immune evasion. In contrast, the effect of mutations on fitness was more closely correlated with changes in ACE2 binding affinity than with immune evasion. Our findings suggest that immune evasion and ACE2 binding affinity play significant and diverse roles in the evolution of SARS-CoV-2.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
2秒前
3秒前
4秒前
多情捕完成签到,获得积分10
4秒前
小明是我完成签到,获得积分10
5秒前
科研通AI5应助cheng1chen采纳,获得10
6秒前
Hello应助qjw采纳,获得20
9秒前
13秒前
所所应助科研通管家采纳,获得10
13秒前
科目三应助科研通管家采纳,获得10
13秒前
大个应助科研通管家采纳,获得10
13秒前
fendy应助科研通管家采纳,获得10
13秒前
SciGPT应助科研通管家采纳,获得10
14秒前
华仔应助科研通管家采纳,获得10
14秒前
Yannik应助科研通管家采纳,获得10
14秒前
斯文败类应助科研通管家采纳,获得10
14秒前
14秒前
顾矜应助科研通管家采纳,获得10
14秒前
Lucas应助科研通管家采纳,获得10
14秒前
14秒前
俱乐部完成签到,获得积分10
15秒前
无花果应助新嘟采纳,获得10
16秒前
17秒前
帅气楼房发布了新的文献求助10
18秒前
18秒前
weisan发布了新的文献求助10
20秒前
cheng1chen发布了新的文献求助10
23秒前
24秒前
30秒前
xiongwenlei发布了新的文献求助10
30秒前
慕青应助聆风采纳,获得10
32秒前
褚雅诺发布了新的文献求助10
33秒前
平底锅攻击完成签到 ,获得积分10
33秒前
Min完成签到,获得积分20
33秒前
箫笛完成签到 ,获得积分10
34秒前
34秒前
34秒前
35秒前
35秒前
所所应助xiongwenlei采纳,获得10
36秒前
高分求助中
(禁止应助)【重要!!请各位详细阅读】【科研通的精品贴汇总】 10000
Building Quantum Computers 1000
Nucleophilic substitution in azasydnone-modified dinitroanisoles 500
Molecular Cloning: A Laboratory Manual (Fourth Edition) 500
Social Epistemology: The Niches for Knowledge and Ignorance 500
优秀运动员运动寿命的人文社会学因素研究 500
Encyclopedia of Mathematical Physics 2nd Edition 420
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 冶金 细胞生物学 免疫学
热门帖子
关注 科研通微信公众号,转发送积分 4241667
求助须知:如何正确求助?哪些是违规求助? 3775199
关于积分的说明 11855372
捐赠科研通 3430148
什么是DOI,文献DOI怎么找? 1882643
邀请新用户注册赠送积分活动 934582
科研通“疑难数据库(出版商)”最低求助积分说明 841083