{"title":"Investigation of Immunoreactivity Profiles and Epitope Landscape in Divergent COVID-19 Trajectories and SARS-CoV-2 Variants.","authors":"Surbhi Bihani, Arka Ray, Dhanush Borishetty, Chaitanya Tuckley, Akanksha Salkar, Arup Acharjee, Prithviraj Shrivastav, Om Shrivastav, Jayanti Shastri, Sachee Agrawal, Siddhartha Duttagupta, Sanjeeva Srivastava","doi":"10.1021/acs.jproteome.4c00791","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":48,"journal":{"name":"Journal of Proteome Research","volume":" ","pages":""},"PeriodicalIF":3.8000,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Proteome Research","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1021/acs.jproteome.4c00791","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
引用次数: 0
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.
期刊介绍:
Journal of Proteome Research publishes content encompassing all aspects of global protein analysis and function, including the dynamic aspects of genomics, spatio-temporal proteomics, metabonomics and metabolomics, clinical and agricultural proteomics, as well as advances in methodology including bioinformatics. The theme and emphasis is on a multidisciplinary approach to the life sciences through the synergy between the different types of "omics".