Suppr超能文献

从感染 SARS-CoV-2 的康复个体中快速分离出针对奥密克戎变异株的pan 中和抗体。

Rapid isolation of pan-neutralizing antibodies against Omicron variants from convalescent individuals infected with SARS-CoV-2.

机构信息

Antibody Research Platform, Chongqing International Institute for Immunology, Chongqing, China.

School of Pharmacy and Bioengineering, Chongqing University of Technology, Chongqing, China.

出版信息

Front Immunol. 2024 Mar 6;15:1374913. doi: 10.3389/fimmu.2024.1374913. eCollection 2024.

Abstract

INTRODUCTION

The emergence of SARS-CoV-2 Omicron subvariants has presented a significant challenge to global health, as these variants show resistance to most antibodies developed early in the pandemic. Therapeutic antibodies with potent efficacy to the Omicron variants are urgently demanded.

METHODS

Utilizing the rapid antibody discovery platform, Berkeley Lights Beacon, we isolated two monoclonal neutralizing antibodies, 2173-A6 and 3462-A4. These antibodies were isolated from individuals who recently recovered from Omicron infections.

RESULTS

Both antibodies, 2173-A6 and 3462-A4, demonstrated high affinity for the RBD and effectively neutralized pseudoviruses from various Omicron lineages, including BA.4/5, XBB.1.16, XBB.1.5, and EG.5.1. This neutralization was achieved through binding to identical or overlapping epitopes.

DISCUSSION

The use of the Beacon platform enabled the rapid isolation and identification of effective neutralizing antibodies within less than 10 days. This process significantly accelerates the development of novel therapeutic antibodies, potentially reducing the time required to respond to unknown infectious diseases in the future.

摘要

简介

SARS-CoV-2 奥密克戎亚变种的出现对全球健康构成了重大挑战,因为这些变种对大流行早期开发的大多数抗体表现出耐药性。迫切需要对奥密克戎变体具有强大疗效的治疗性抗体。

方法

我们利用快速抗体发现平台——伯克利之光 Beacon,从最近从奥密克戎感染中康复的个体中分离出两种单克隆中和抗体 2173-A6 和 3462-A4。

结果

两种抗体 2173-A6 和 3462-A4 均对 RBD 具有高亲和力,并能有效中和来自各种奥密克戎谱系的假病毒,包括 BA.4/5、XBB.1.16、XBB.1.5 和 EG.5.1。这种中和作用是通过与相同或重叠的表位结合实现的。

讨论

Beacon 平台的使用使得在不到 10 天的时间内快速分离和鉴定有效的中和抗体成为可能。这一过程显著加快了新型治疗性抗体的开发速度,可能会缩短未来应对未知传染病所需的时间。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a1b6/10950932/d3709b72d486/fimmu-15-1374913-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验