An antibody-escape estimator for mutations to the SARS-CoV-2 receptor-binding domain.

An antibody-escape estimator for mutations to the SARS-CoV-2 receptor-binding domain.
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SARS-CoV-2 受体结合域突变的抗体逃逸估计器。

DOI:
10.1093/ve/veac021
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发表时间:
2022
期刊:
影响因子:
5.3
通讯作者:
--
中科院分区:
医学2区
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--
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严重急性呼吸道综合征冠状病毒2型(SARS-CoV-2)监测的一个关键目标是快速识别具有突变的病毒变种,这些突变会降低疫苗接种或感染引起的多克隆抗体的中和作用。不幸的是,新病毒变体的直接实验表征滞后于基于序列的鉴定。在这里,我们通过将深度突变扫描数据聚合到一个“逃逸估计器”中来帮助解决这一挑战,该估计器可以估计病毒刺突受体结合结构域突变的任意组合的抗原效应。该估计器可用于直观地可视化突变如何影响多克隆抗体识别,并对突变组合的预期抗原效应进行评分。这些分数与对SARS-CoV-2变体进行的中和试验相关,并强调了最近描述的Omicron变体的不祥抗原特性。估计器的交互式版本位于https://jbloomlab.github.io/SARS2_RBD_Ab_escape_maps/escape-calc/(最后一次访问是2022年3月11日),我们提供了一个用于批处理的Python模块。目前,该计算器主要使用武汉-Hu-1样疫苗接种或感染引起的抗体数据,因此预计最适合计算相对于早期SARS-CoV-2毒株的突变的免疫逃逸。
A key goal of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) surveillance is to rapidly identify viral variants with mutations that reduce neutralization by polyclonal antibodies elicited by vaccination or infection. Unfortunately, direct experimental characterization of new viral variants lags their sequence-based identification. Here we help address this challenge by aggregating deep mutational scanning data into an ‘escape estimator’ that estimates the antigenic effects of arbitrary combinations of mutations to the virus’s spike receptor-binding domain. The estimator can be used to intuitively visualize how mutations impact polyclonal antibody recognition and score the expected antigenic effect of combinations of mutations. These scores correlate with neutralization assays performed on SARS-CoV-2 variants and emphasize the ominous antigenic properties of the recently described Omicron variant. An interactive version of the estimator is at https://jbloomlab.github.io/SARS2_RBD_Ab_escape_maps/escape-calc/ (last accessed 11 March 2022), and we provide a Python module for batch processing. Currently the calculator uses primarily data for antibodies elicited by Wuhan-Hu-1-like vaccination or infection and so is expected to work best for calculating escape from such immunity for mutations relative to early SARS-CoV-2 strains.
DOI: 10.1038/s41467-021-24435-8
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影响因子: 16.6
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Greaney AJ;Starr TN;Barnes CO;Weisblum Y;Schmidt F;Caskey M;Gaebler C;Cho A;Agudelo M;Finkin S;Wang Z;Poston D;Muecksch F;Hatziioannou T;Bieniasz PD;Robbiani DF;Nussenzweig MC;Bjorkman PJ;Bloom JD
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发表时间: 2021-10
影响因子: 28.3
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通讯作者: Crowe JE Jr
DOI: 10.1109/tvcg.2016.2599030
发表时间: 2017-01-01
影响因子: 5.2
作者:
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通讯作者: Heer, Jeffrey
DOI: 10.1038/s41586-021-04005-0
发表时间: 2021-12
期刊: Nature
影响因子: 64.8
作者:
通讯作者: --