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不同新冠病毒感染轨迹和新冠病毒变异株的免疫反应特征及表位图谱研究

Investigation of Immunoreactivity Profiles and Epitope Landscape in Divergent COVID-19 Trajectories and SARS-CoV-2 Variants.

作者信息

Bihani Surbhi, Ray Arka, Borishetty Dhanush, Tuckley Chaitanya, Salkar Akanksha, Acharjee Arup, Shrivastav Prithviraj, Shrivastav Om, Shastri Jayanthi, Agrawal Sachee, Duttagupta Siddhartha, Srivastava Sanjeeva

机构信息

Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Mumbai 400076, India.

Centre for Research in Nanotechnology and Science, Indian Institute of Technology Bombay, Mumbai 400076, India.

出版信息

J Proteome Res. 2025 Feb 7;24(2):762-776. doi: 10.1021/acs.jproteome.4c00791. Epub 2025 Jan 28.

Abstract

This study aimed to elucidate the complexity of the humoral immune response in COVID-19 patients with varying disease trajectories using a SARS-CoV-2 whole proteome peptide microarray chip. The microarray, containing 5347 peptides spanning the entire SARS-CoV-2 proteome and key variants of concern, was used to analyze IgG responses in 10 severe-to-recovered, 9 nonsevere-to-severe cases, and 10 control case (5 pre-pandemic and 5 SARS-CoV-2-negative) plasma samples. We identified 1151 IgG-reactive peptides corresponding to 647 epitopes, with 207 peptides being cross-reactive across 124 epitopes. Nonstructural protein 3 (nsp3) exhibited the highest number of total and unique epitopes, followed by the spike protein. nsp12 had the most number of cross-reactive epitopes. Peptides from the spike protein and nsps 2, 3, 5, and 13 were notably associated with recovery. Additionally, specific mutations in SARS-CoV-2 variants were found to alter peptide immunoreactivity, with some mutations (e.g., G142D, L452R, and N501Y) enhancing and others (e.g., R190S and E484 K) reducing immune recognition. These findings have critical implications for the development of diagnostics, vaccines, and therapeutics. Understanding the distribution of epitopes and the impact of viral mutations on antigenicity provides insights into immune evasion mechanisms, informing strategies for controlling COVID-19 and future coronavirus outbreaks.

摘要

本研究旨在使用SARS-CoV-2全蛋白质组肽微阵列芯片阐明不同疾病轨迹的COVID-19患者体液免疫反应的复杂性。该微阵列包含跨越整个SARS-CoV-2蛋白质组和关键关注变体的5347种肽,用于分析10例重症至康复患者、9例非重症至重症患者以及10例对照病例(5例大流行前和5例SARS-CoV-2阴性)血浆样本中的IgG反应。我们鉴定出了1151种与647个表位相对应的IgG反应性肽,其中207种肽在124个表位上具有交叉反应性。非结构蛋白3(nsp3)的总表位和独特表位数量最多,其次是刺突蛋白。nsp12的交叉反应性表位数量最多。来自刺突蛋白以及nsp2、3、5和13的肽与康复显著相关。此外,发现SARS-CoV-2变体中的特定突变会改变肽的免疫反应性,一些突变(如G142D、L452R和N501Y)增强免疫识别,而其他突变(如R190S和E484K)则降低免疫识别。这些发现对诊断、疫苗和治疗方法的开发具有至关重要的意义。了解表位的分布以及病毒突变对抗原性的影响有助于深入了解免疫逃逸机制,为控制COVID-19和未来冠状病毒爆发提供策略依据。

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