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肽微阵列与机器学习相结合,揭示了针对 SARS-CoV-2 具有中和能力的人抗体反应中的个体表位。

Peptide microarrays coupled to machine learning reveal individual epitopes from human antibody responses with neutralizing capabilities against SARS-CoV-2.

机构信息

Helmholtz Centre for Infection Research, Braunschweig, Germany.

Braunschweig Integrated Centre of Systems Biology (BRICS), Technische Universität Braunschweig, Braunschweig, Germany.

出版信息

Emerg Microbes Infect. 2022 Dec;11(1):1037-1048. doi: 10.1080/22221751.2022.2057874.

Abstract

The coronavirus SARS-CoV-2 is the causative agent for the disease COVID-19. To capture the IgA, IgG, and IgM antibody response of patients infected with SARS-CoV-2 at individual epitope resolution, we constructed planar microarrays of 648 overlapping peptides that cover the four major structural proteins S(pike), N(ucleocapsid), M(embrane), and E(nvelope). The arrays were incubated with sera of 67 SARS-CoV-2 positive and 22 negative control samples. Specific responses to SARS-CoV-2 were detectable, and nine peptides were associated with a more severe course of the disease. A random forest model disclosed that antibody binding to 21 peptides, mostly localized in the S protein, was associated with higher neutralization values in cellular anti-SARS-CoV-2 assays. For antibodies addressing the N-terminus of M, or peptides close to the fusion region of S, protective effects were proven by antibody depletion and neutralization assays. The study pinpoints unusual viral binding epitopes that might be suited as vaccine candidates

摘要

新型冠状病毒 SARS-CoV-2 是 COVID-19 疾病的病原体。为了在单个表位分辨率上捕获感染 SARS-CoV-2 的患者的 IgA、IgG 和 IgM 抗体反应,我们构建了包含 648 个重叠肽的平面微阵列,这些肽覆盖了四个主要的结构蛋白 S(刺突)、N(核衣壳)、M(膜)和 E(包膜)。将这些微阵列与 67 份 SARS-CoV-2 阳性和 22 份阴性对照样本的血清孵育。可以检测到针对 SARS-CoV-2 的特异性反应,并且有 9 个肽与疾病的更严重病程相关。随机森林模型显示,针对 S 蛋白的 21 个肽的抗体结合与细胞抗 SARS-CoV-2 测定中的更高中和值相关。对于针对 M 的 N 末端的抗体,或接近 S 的融合区域的肽,通过抗体耗竭和中和测定证明了保护作用。该研究确定了不寻常的病毒结合表位,这些表位可能适合作为疫苗候选物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f70d/9009950/842e3984a0a3/TEMI_A_2057874_F0001_OC.jpg

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