Suppr超能文献

SARS-CoV-2 的免疫反应性肽图谱。

Immunoreactive peptide maps of SARS-CoV-2.

机构信息

Center for Infection and Immunity, Mailman School of Public Health, Columbia University, New York, NY, USA.

Sun Yat-sen University, Guangzhou, Guangdong Province, China.

出版信息

Commun Biol. 2021 Feb 12;4(1):225. doi: 10.1038/s42003-021-01743-9.

Abstract

Serodiagnosis of SARS-CoV-2 infection is impeded by immunological cross-reactivity among the human coronaviruses (HCoVs): SARS-CoV-2, SARS-CoV-1, MERS-CoV, OC43, 229E, HKU1, and NL63. Here we report the identification of humoral immune responses to SARS-CoV-2 peptides that may enable discrimination between exposure to SARS-CoV-2 and other HCoVs. We used a high-density peptide microarray and plasma samples collected at two time points from 50 subjects with SARS-CoV-2 infection confirmed by qPCR, samples collected in 2004-2005 from 11 subjects with IgG antibodies to SARS-CoV-1, 11 subjects with IgG antibodies to other seasonal human coronaviruses (HCoV), and 10 healthy human subjects. Through statistical modeling with linear regression and multidimensional scaling we identified specific peptides that were reassembled to identify 29 linear SARS-CoV-2 epitopes that were immunoreactive with plasma from individuals who had asymptomatic, mild or severe SARS-CoV-2 infections. Larger studies will be required to determine whether these peptides may be useful in serodiagnostics.

摘要

血清学诊断 SARS-CoV-2 感染受到人类冠状病毒(HCoV)之间免疫交叉反应的阻碍:SARS-CoV-2、SARS-CoV-1、MERS-CoV、OC43、229E、HKU1 和 NL63。在这里,我们报告了对 SARS-CoV-2 肽的体液免疫反应的鉴定,这可能使我们能够区分 SARS-CoV-2 暴露和其他 HCoV 暴露。我们使用高密度肽微阵列和从通过 qPCR 确认的 50 名 SARS-CoV-2 感染患者在两个时间点采集的血浆样本,从 2004-2005 年采集的 11 名 SARS-CoV-1 IgG 抗体阳性患者、11 名其他季节性 HCoV IgG 抗体阳性患者和 10 名健康人类受试者采集的血浆样本。通过线性回归和多维标度的统计建模,我们确定了特定的肽,将这些肽重新组装以鉴定 29 个线性 SARS-CoV-2 表位,这些表位与无症状、轻度或重度 SARS-CoV-2 感染患者的血浆发生免疫反应。需要进行更大规模的研究来确定这些肽是否可用于血清学诊断。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3819/7881038/b3a76bd4fa22/42003_2021_1743_Fig1_HTML.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