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Richards KA, Changrob S, Thomas PG, Wilson PC, Sant AJ. Lack of memory recall in human CD4 T cells elicited by the first encounter with SARS-CoV-2. iScience 2024; 27:109992. [PMID: 38868209 PMCID: PMC11166706 DOI: 10.1016/j.isci.2024.109992] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2024] [Revised: 04/11/2024] [Accepted: 05/13/2024] [Indexed: 06/14/2024] Open
Abstract
The studies reported here focus on the impact of pre-existing CD4 T cell immunity on the first encounter with SARS-CoV-2. They leverage PBMC samples from plasma donors collected after a first SARS-CoV-2 infection, prior to vaccine availability and compared to samples collected prior to the emergence of SARS-CoV-2. Analysis of CD4 T cell specificity across the entire SARS-CoV-2 proteome revealed that the recognition of SARS-CoV-2-derived epitopes by CD4 memory cells prior to the pandemic are enriched for reactivity toward non-structural proteins conserved across endemic CoV strains. However, CD4 T cells after primary infection with SARS-CoV-2 focus on epitopes from structural proteins. We observed little evidence for preferential recall to epitopes conserved between SARS-CoV-2 and seasonal CoV, a finding confirmed through use of selectively curated conserved and SARS-unique peptides. Our data suggest that SARS-CoV-2 CD4 T cells elicited by the first infection are primarily established from the naive CD4 T cell pool.
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Affiliation(s)
- Katherine A. Richards
- David H. Smith Center for Vaccine Biology and Immunology, University of Rochester Medical Center, Department of Microbiology and Immunology, University of Rochester Medical Center, Rochester, NY 14642, USA
| | - Siriruk Changrob
- Drukier Institute for Children’s Health, Department of Pediatrics, Weill Cornell Medicine, New York, NY 10065, USA
| | - Paul G. Thomas
- Department of Immunology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
| | - Patrick C. Wilson
- Drukier Institute for Children’s Health, Department of Pediatrics, Weill Cornell Medicine, New York, NY 10065, USA
| | - Andrea J. Sant
- David H. Smith Center for Vaccine Biology and Immunology, University of Rochester Medical Center, Department of Microbiology and Immunology, University of Rochester Medical Center, Rochester, NY 14642, USA
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Filippi M, Demoliner M, Gularte JS, de Abreu Goes Pereira VM, da Silva MS, Girardi V, Hansen AW, Spilki FR. Relative frequency of genomic mutations in SARS-CoV-2 recovered from southern Brazilian cases of COVID-19 through the Gamma, Delta and Omicron waves. INFECTION, GENETICS AND EVOLUTION : JOURNAL OF MOLECULAR EPIDEMIOLOGY AND EVOLUTIONARY GENETICS IN INFECTIOUS DISEASES 2024; 120:105590. [PMID: 38574833 DOI: 10.1016/j.meegid.2024.105590] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/06/2023] [Revised: 03/28/2024] [Accepted: 03/31/2024] [Indexed: 04/06/2024]
Abstract
The presence of different mutations in the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genome can be related to changes in coronavirus disease (COVID-19) infection. Besides, these viral alterations associated with factors such as massive number of positive cases, vaccination and reinfections can be important in the viral evolution process. As well as, mutations found at low frequencies may have a more neutral action and consequently be less inclined to negative selection, facilitating their spread through the population. Related to that, we aimed to present mutations that are possibly relevant in the process of viral evolution found in 115 SARS-CoV-2 sequences from samples of individuals residing in the metropolitan region of Porto Alegre in the state of Rio Grande do Sul, Brazil. The genome from clinical samples was sequenced using High-Throughput Sequencing (HTS) and analyzed using a workflow to map reads and find variations/SNPs. The samples were separated into 3 groups considering the sample lineage. Of the total number of analyzed sequences, 35 were from the Gamma lineage, 35 from Delta and 45 from Omicron. Amino acid changes present in frequencies lower than 80% of the reads in the sequences were evaluated. 11 common mutations among the samples were found in the Gamma lineage, 1 in the ORF1ab gene, 7 in the S gene, 2 in the ORF6 gene and 1 in the ORF7a gene. While in the Delta lineage, a total of 11 mutations distributed in the ORF1ab, S, ORF7a and N genes, 2, 7, 1 and 1 mutation were found in each gene, respectively. And finally, in the Omicron, 16 mutations were identified, 2 in the ORF1ab gene, 12 in the S gene and 2 in the M gene. In conclusion, we emphasize that genomic surveillance can be a useful tool to assess how mutations play a key role in virus adaptation, and its process of susceptibility to new hosts showing the possible signs of viral evolution.
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Affiliation(s)
- Micheli Filippi
- Laboratório de Microbiologia Molecular, Departamento de Virologia, Universidade Feevale, Novo Hamburgo, Rio Grande do Sul, Brazil.
| | - Meriane Demoliner
- Laboratório de Microbiologia Molecular, Departamento de Virologia, Universidade Feevale, Novo Hamburgo, Rio Grande do Sul, Brazil
| | - Juliana Schons Gularte
- Laboratório de Microbiologia Molecular, Departamento de Virologia, Universidade Feevale, Novo Hamburgo, Rio Grande do Sul, Brazil
| | | | - Mariana Soares da Silva
- Laboratório de Microbiologia Molecular, Departamento de Virologia, Universidade Feevale, Novo Hamburgo, Rio Grande do Sul, Brazil
| | - Viviane Girardi
- Laboratório de Microbiologia Molecular, Departamento de Virologia, Universidade Feevale, Novo Hamburgo, Rio Grande do Sul, Brazil
| | - Alana Witt Hansen
- Laboratório de Microbiologia Molecular, Departamento de Virologia, Universidade Feevale, Novo Hamburgo, Rio Grande do Sul, Brazil
| | - Fernando Rosado Spilki
- Laboratório de Microbiologia Molecular, Departamento de Virologia, Universidade Feevale, Novo Hamburgo, Rio Grande do Sul, Brazil
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Yang G, Wang J, Sun P, Qin J, Yang X, Chen D, Zhang Y, Zhong N, Wang Z. SARS-CoV-2 epitope-specific T cells: Immunity response feature, TCR repertoire characteristics and cross-reactivity. Front Immunol 2023; 14:1146196. [PMID: 36969254 PMCID: PMC10036809 DOI: 10.3389/fimmu.2023.1146196] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Accepted: 03/01/2023] [Indexed: 03/12/2023] Open
Abstract
The devastating COVID-19 pandemic caused by SARS-CoV-2 and multiple variants or subvariants remains an ongoing global challenge. SARS-CoV-2-specific T cell responses play a critical role in early virus clearance, disease severity control, limiting the viral transmission and underpinning COVID-19 vaccine efficacy. Studies estimated broad and robust T cell responses in each individual recognized at least 30 to 40 SARS-CoV-2 antigen epitopes and associated with COVID-19 clinical outcome. Several key immunodominant viral proteome epitopes, including S protein- and non-S protein-derived epitopes, may primarily induce potent and long-lasting antiviral protective effects. In this review, we summarized the immune response features of immunodominant epitope-specific T cells targeting different SRAS-CoV-2 proteome structures after infection and vaccination, including abundance, magnitude, frequency, phenotypic features and response kinetics. Further, we analyzed the epitopes immunodominance hierarchy in combination with multiple epitope-specific T cell attributes and TCR repertoires characteristics, and discussed the significant implications of cross-reactive T cells toward HCoVs, SRAS-CoV-2 and variants of concern, especially Omicron. This review may be essential for mapping the landscape of T cell responses toward SARS-CoV-2 and optimizing the current vaccine strategy.
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Affiliation(s)
- Gang Yang
- Faculty of Life Science and Technology, Kunming University of Science and Technology, Kunming, China
- Guangzhou Laboratory, Guangzhou, China
- Department of Pulmonary and Critical Care Medicine, The First People’s Hospital of Yunnan Province, Kunming, China
| | - Junxiang Wang
- State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, China
| | - Ping Sun
- Faculty of Life Science and Technology, Kunming University of Science and Technology, Kunming, China
| | - Jian Qin
- Department of Pulmonary and Critical Care Medicine, The First People’s Hospital of Yunnan Province, Kunming, China
| | - Xiaoyun Yang
- Guangzhou Laboratory, Guangzhou, China
- State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, China
| | - Daxiang Chen
- Guangzhou Laboratory, Guangzhou, China
- State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, China
| | - Yunhui Zhang
- Department of Pulmonary and Critical Care Medicine, The First People’s Hospital of Yunnan Province, Kunming, China
| | - Nanshan Zhong
- Faculty of Life Science and Technology, Kunming University of Science and Technology, Kunming, China
- Guangzhou Laboratory, Guangzhou, China
- State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, China
| | - Zhongfang Wang
- Guangzhou Laboratory, Guangzhou, China
- State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, China
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Abbasian MH, Mahmanzar M, Rahimian K, Mahdavi B, Tokhanbigli S, Moradi B, Sisakht MM, Deng Y. Global landscape of SARS-CoV-2 mutations and conserved regions. J Transl Med 2023; 21:152. [PMID: 36841805 PMCID: PMC9958328 DOI: 10.1186/s12967-023-03996-w] [Citation(s) in RCA: 52] [Impact Index Per Article: 26.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Accepted: 02/15/2023] [Indexed: 02/27/2023] Open
Abstract
BACKGROUND At the end of December 2019, a novel strain of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) disease (COVID-19) has been identified in Wuhan, a central city in China, and then spread to every corner of the globe. As of October 8, 2022, the total number of COVID-19 cases had reached over 621 million worldwide, with more than 6.56 million confirmed deaths. Since SARS-CoV-2 genome sequences change due to mutation and recombination, it is pivotal to surveil emerging variants and monitor changes for improving pandemic management. METHODS 10,287,271 SARS-CoV-2 genome sequence samples were downloaded in FASTA format from the GISAID databases from February 24, 2020, to April 2022. Python programming language (version 3.8.0) software was utilized to process FASTA files to identify variants and sequence conservation. The NCBI RefSeq SARS-CoV-2 genome (accession no. NC_045512.2) was considered as the reference sequence. RESULTS Six mutations had more than 50% frequency in global SARS-CoV-2. These mutations include the P323L (99.3%) in NSP12, D614G (97.6) in S, the T492I (70.4) in NSP4, R203M (62.8%) in N, T60A (61.4%) in Orf9b, and P1228L (50.0%) in NSP3. In the SARS-CoV-2 genome, no mutation was observed in more than 90% of nsp11, nsp7, nsp10, nsp9, nsp8, and nsp16 regions. On the other hand, N, nsp3, S, nsp4, nsp12, and M had the maximum rate of mutations. In the S protein, the highest mutation frequency was observed in aa 508-635(0.77%) and aa 381-508 (0.43%). The highest frequency of mutation was observed in aa 66-88 (2.19%), aa 7-14, and aa 164-246 (2.92%) in M, E, and N proteins, respectively. CONCLUSION Therefore, monitoring SARS-CoV-2 proteomic changes and detecting hot spots mutations and conserved regions could be applied to improve the SARS-CoV-2 diagnostic efficiency and design safe and effective vaccines against emerging variants.
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Affiliation(s)
- Mohammad Hadi Abbasian
- Department of Medical Genetics, National Institute for Genetic Engineering and Biotechnology, Tehran, Iran
| | - Mohammadamin Mahmanzar
- Department of Quantitative Health Sciences, John A. Burns School of Medicine, University of Hawaii at Manoa, Honolulu, HI, 96813, USA
| | - Karim Rahimian
- Department of Bioinformatics, Institute of Biochemistry and Biophysics (IBB), University of Tehran, Tehran, Iran
| | - Bahar Mahdavi
- Department of Computer Science, Tarbiat Modares University, Tehran, Iran
| | - Samaneh Tokhanbigli
- Discipline of Pharmacy, Graduate School of Health, University of Technology Sydney, Sydney, Australia
| | - Bahman Moradi
- Department of Biology, Faculty of Sciences, Shahid Bahonar University of Kerman, Kerman, Iran
| | - Mahsa Mollapour Sisakht
- Department of Biochemistry, Erasmus University Medical Center, 2040, 3000 CA, Rotterdam, The Netherlands
| | - Youping Deng
- Department of Quantitative Health Sciences, John A. Burns School of Medicine, University of Hawaii at Manoa, Honolulu, HI, 96813, USA.
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Jin X, Liu X, Shen C. A systemic review of T-cell epitopes defined from the proteome of SARS-CoV-2. Virus Res 2023; 324:199024. [PMID: 36526016 PMCID: PMC9757803 DOI: 10.1016/j.virusres.2022.199024] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Revised: 12/10/2022] [Accepted: 12/12/2022] [Indexed: 12/15/2022]
Abstract
Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection remains in a global pandemic, and no eradicative therapy is currently available. Host T cells have been shown to play a crucial role in the antiviral immune protection and pathology in Coronavirus disease 2019 (COVID-19) patients; thus, identifying sufficient T-cell epitopes from the SARS-CoV-2 proteome can contribute greatly to the development of T-cell epitope vaccines and the precise evaluation of host SARS-CoV-2-specific cellular immunity. This review presents a comprehensive map of T-cell epitopes functionally validated from SARS-CoV-2 antigens, the human leukocyte antigen (HLA) supertypes to present these epitopes, and the strategies to screen and identify T-cell epitopes. To the best of our knowledge, a total of 1349 CD8+ T-cell epitopes and 790 CD4+ T-cell epitopes have been defined by functional experiments thus far, but most are presented by approximately twenty common HLA supertypes, such as HLA-A0201, A2402, B0702, DR15, DR7 and DR11 molecules, and 74-80% of the T-cell epitopes are derived from S protein and nonstructural protein. These data provide useful insight into the development of vaccines and specific T-cell detection systems. However, the currently defined T-cell epitope repertoire cannot cover the HLA polymorphism of major populations in an indicated geographic region. More research is needed to depict an overall landscape of T-cell epitopes, which covers the overall SARS-CoV-2 proteome and global patients.
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Affiliation(s)
- Xiaoxiao Jin
- Northern Jiangsu People's Hospital, Yangzhou, Jiangsu, China 225002; Department of Microbiology and Immunology, Medical School of Southeast University, Nanjing, Jiangsu, China 210009
| | - Xiaotao Liu
- Department of Microbiology and Immunology, Medical School of Southeast University, Nanjing, Jiangsu, China 210009
| | - Chuanlai Shen
- Department of Microbiology and Immunology, Medical School of Southeast University, Nanjing, Jiangsu, China 210009.
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Zhuang X, Zheng Y, Wei S, Zhai W, Song Q, Chen M, Xu Q, Fan Y, Zheng J. Can the nucleic acid Ct value of discharged patients infected with SARS-CoV-2 Omicron variant be 35?--A retrospective study on fluctuation of nucleic acid Ct values in SNIEC mobile cabin hospital. Front Cell Infect Microbiol 2022; 12:1059880. [PMID: 36601305 PMCID: PMC9806225 DOI: 10.3389/fcimb.2022.1059880] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2022] [Accepted: 12/05/2022] [Indexed: 12/23/2022] Open
Abstract
Objective To explore the meaning of cycle threshold (Ct) value fluctuation and the appropriateness of setting the discharge Ct value to 35, which is the current standard in Chinese guidelines. Method A retrospective study was conducted on 95 patients with Ct value fluctuation (Ct value below 35 on day 3; group A) and 97 patients with a normal discharge process (control; group B). Their clinical characteristics and follow-up data were collected. Results (1) There was no significant difference between the groups in age, gender distribution, number of vaccinations, initial ORF-Ct value, and initial N-Ct value. The proportion of patients complicated with chronic internal disorders, respiratory symptoms, and abnormal chest radiology in group A was significantly higher than that in group B. (2) Between the two groups, there was no significant difference in the ORF-Ct or N-Ct value on day 1, but the ORF-Ct and N-Ct values of group B on days 2 to 4 were significantly higher than those of group A. (3) There was no significant difference between the groups in the ORF-Ct value at discharge, but there was a significant difference in the N-Ct value at discharge. Seven days after discharge, almost 100% of the patients had been cured. The mean negative conversion interval of nucleic acid of the patients in group A was 14.5 ± 4.6 days, which was longer than that of the patients in group B (11.8 ± 4 days). (4) Logistic regression analysis showed that the ORF-Ct value on day 2 was the key factor influencing the Ct value fluctuation. Conclusion The fluctuation of Ct value is only a normal phenomenon in the recovery period of the disease, and there is no need for excessive intervention. It is reasonable to set the Ct value of the discharge standard to 35 and retest the nucleic acid on the 10th day after discharge for patients with underlying diseases or symptoms.
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Affiliation(s)
- Xu Zhuang
- Department of Obstetrics and Gynecology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Yu Zheng
- Department of Pulmonology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Shun Wei
- Department of Information Center, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Wei Zhai
- Department of Urology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Qixiang Song
- Department of Urology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Min Chen
- Nursing Department, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Qingrong Xu
- Department of Orthopaedics, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Yiling Fan
- Department of Neurosurgery, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China,*Correspondence: Yiling Fan, ; Junhua Zheng,
| | - Junhua Zheng
- Department of Urology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China,*Correspondence: Yiling Fan, ; Junhua Zheng,
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