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Zhang J, Yue C, Lin Y, Tian J, Guo Y, Zhang D, Guo Y, Ye B, Chai Y, Qi J, Zhao Y, Gao GF, Sun Z, Liu J. Uncommon P1 Anchor-featured Viral T Cell Epitope Preference within HLA-A*2601 and HLA-A*0101 Individuals. Immunohorizons 2024; 8:415-430. [PMID: 38885041 PMCID: PMC11220742 DOI: 10.4049/immunohorizons.2400026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2024] [Accepted: 05/09/2024] [Indexed: 06/20/2024] Open
Abstract
The individual HLA-related susceptibility to emerging viral diseases such as COVID-19 underscores the importance of understanding how HLA polymorphism influences peptide presentation and T cell recognition. Similar to HLA-A*0101, which is one of the earliest identified HLA alleles among the human population, HLA-A*2601 possesses a similar characteristic for the binding peptide and acts as a prevalent allomorph in HLA-I. In this study, we found that, compared with HLA-A*0101, HLA-A*2601 individuals exhibit distinctive features for the T cell responses to SARS-CoV-2 and influenza virus after infection and/or vaccination. The heterogeneous T cell responses can be attributed to the distinct preference of HLA-A*2601 and HLA-A*0101 to T cell epitope motifs with negative-charged residues at the P1 and P3 positions, respectively. Furthermore, we determined the crystal structures of the HLA-A*2601 complexed to four peptides derived from SARS-CoV-2 and human papillomavirus, with one structure of HLA-A*0101 for comparison. The shallow pocket C of HLA-A*2601 results in the promiscuous presentation of peptides with "switchable" bulged conformations because of the secondary anchor in the median portion. Notably, the hydrogen bond network formed between the negative-charged P1 anchors and the HLA-A*2601-specific residues lead to a "closed" conformation and solid placement for the P1 secondary anchor accommodation in pocket A. This insight sheds light on the intricate relationship between HLA I allelic allomorphs, peptide binding, and the immune response and provides valuable implications for understanding disease susceptibility and potential vaccine design.
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Affiliation(s)
- Jianing Zhang
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases (NITFID), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- NHC Key Laboratory of Biosafety, Research Unit of Adaptive Evolution and Control of Emerging Viruses, Chinese Academy of Medical Sciences, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Can Yue
- CAS Key Laboratory of Infection and Immunity, National Laboratory of Macromolecules, Institute of Biophysics, Chinese Academy of Sciences (CAS), Beijing, China
| | - Yin Lin
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases (NITFID), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- NHC Key Laboratory of Biosafety, Research Unit of Adaptive Evolution and Control of Emerging Viruses, Chinese Academy of Medical Sciences, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong Province, China
| | - Jinmin Tian
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases (NITFID), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- NHC Key Laboratory of Biosafety, Research Unit of Adaptive Evolution and Control of Emerging Viruses, Chinese Academy of Medical Sciences, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yuanyuan Guo
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases (NITFID), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- NHC Key Laboratory of Biosafety, Research Unit of Adaptive Evolution and Control of Emerging Viruses, Chinese Academy of Medical Sciences, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong Province, China
| | - Danni Zhang
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases (NITFID), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- NHC Key Laboratory of Biosafety, Research Unit of Adaptive Evolution and Control of Emerging Viruses, Chinese Academy of Medical Sciences, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yaxin Guo
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases (NITFID), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- NHC Key Laboratory of Biosafety, Research Unit of Adaptive Evolution and Control of Emerging Viruses, Chinese Academy of Medical Sciences, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Beiwei Ye
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases (NITFID), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- NHC Key Laboratory of Biosafety, Research Unit of Adaptive Evolution and Control of Emerging Viruses, Chinese Academy of Medical Sciences, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yan Chai
- CAS Key Laboratory of Pathogen Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences (CAS), Beijing, China
| | - Jianxun Qi
- CAS Key Laboratory of Pathogen Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences (CAS), Beijing, China
| | - Yingze Zhao
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases (NITFID), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- NHC Key Laboratory of Biosafety, Research Unit of Adaptive Evolution and Control of Emerging Viruses, Chinese Academy of Medical Sciences, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - George F. Gao
- CAS Key Laboratory of Pathogen Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences (CAS), Beijing, China
| | - Zeyu Sun
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Jun Liu
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases (NITFID), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- NHC Key Laboratory of Biosafety, Research Unit of Adaptive Evolution and Control of Emerging Viruses, Chinese Academy of Medical Sciences, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
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Ovens K, Naugler C. Preliminary evidence of different selection pressures on cancer cells as compared to normal tissues. Theor Biol Med Model 2012; 9:44. [PMID: 23146329 PMCID: PMC3503577 DOI: 10.1186/1742-4682-9-44] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2012] [Accepted: 11/03/2012] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND Cancer is characterized by both a high mutation rate as well as high rates of cell division and cell death. We postulate that these conditions will result in the eventual mutational inactivation of genes not essential to the survival of the cancer cell, while mutations in essential genes will be eliminated by natural selection leaving molecular signatures of selection in genes required for survival and reproduction. By looking for signatures of natural selection in the genomes of cancer cells, it should therefore be possible to determine which genes have been essential for the development of a particular cancer. METHODS We provide a proof of principle test of this idea by applying a test of neutrality (Nei-Gojobori Z-test of selection) to 139 cancer-related nucleotide sequences obtained from GenBank representing 46 cancer-derived genes. RESULTS Among cancer associated sequences, 10 genes showed molecular evidence of selection. Of these 10 genes, four showed molecular evidence of selection in non-cancer transcripts. Among non-cancer associated sequences, eight genes showed molecular evidence of selection, with four of these also showing selection in the cancer associated sequences. CONCLUSIONS These results provide preliminary evidence that the same genes may experience different selection pressures within normal and cancer tissues. Application of this technique could identify genes under unique selection pressure in cancer tissues and thereby indicate possible targets for therapeutic intervention.
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Affiliation(s)
- Katie Ovens
- Bachelor of Health Sciences Program, Faculty of Medicine, Room G503, O’Brien Centre for the BHSc, 3330 Hospital Drive NW, Calgary, AB T2N 4N1, Canada
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Paximadis M, Mathebula TY, Gentle NL, Vardas E, Colvin M, Gray CM, Tiemessen CT, Puren A. Human leukocyte antigen class I (A, B, C) and II (DRB1) diversity in the black and Caucasian South African population. Hum Immunol 2011; 73:80-92. [PMID: 22074999 DOI: 10.1016/j.humimm.2011.10.013] [Citation(s) in RCA: 48] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2011] [Revised: 09/05/2011] [Accepted: 10/03/2011] [Indexed: 01/24/2023]
Abstract
A cross-section of black and Caucasian South Africans (N = 302) were genotyped at high resolution (class I HLA-A, -B, -C and class II HLA-DRB1). Five new class I alleles (A*30:01:02, A*30:02:02, A*68:27, B*42:06, and B*45:07) and one new confirmatory allele (A*29:11) were identified in the black population. Alleles and haplotypes showed expected differences between the black and Caucasian populations, with the black population, on average, showing a broader spectrum of allele representation (less single allele dominance). The most prevalent alleles at the four loci in the black population were A*30:01, B*58:02, C*06:02, and DRB1*13:01 and in the Caucasian population were A*02:01:01, B*07:02:01, C*07:01, and DRB1*03:01. HLA-B, and HLA-C loci showed the strongest overall linkage disequilibrium (LD) and HLA-B/HLA-C two locus haplotypes also showed the strongest LD (D'(ij)) in both population groups. Bw allotype representation was similar between the two populations; however C allotypes differed significantly (C1 higher representation in Caucasians; C2 higher representation in blacks). HLA-A Supertype family phenotypic frequencies did not differ between the two populations, but four (B08, B27, B58, and B62) HLA-B Supertype families differed significantly. However, vaccine coverage estimation came close to 100% in both population groups, with inclusion of only four Supertype families (A1, A2, B7, B58).
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Affiliation(s)
- Maria Paximadis
- Centre for HIV and STIs, National Institute for Communicable Diseases, National Health Laboratory Services and the University of the Witwatersrand, Johannesburg, South Africa.
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Matthews PC, Adland E, Listgarten J, Leslie A, Mkhwanazi N, Carlson JM, Harndahl M, Stryhn A, Payne RP, Ogwu A, Huang KHG, Frater J, Paioni P, Kloverpris H, Jooste P, Goedhals D, van Vuuren C, Steyn D, Riddell L, Chen F, Luzzi G, Balachandran T, Ndung'u T, Buus S, Carrington M, Shapiro R, Heckerman D, Goulder PJR. HLA-A*7401-mediated control of HIV viremia is independent of its linkage disequilibrium with HLA-B*5703. JOURNAL OF IMMUNOLOGY (BALTIMORE, MD. : 1950) 2011; 186:5675-86. [PMID: 21498667 PMCID: PMC3738002 DOI: 10.4049/jimmunol.1003711] [Citation(s) in RCA: 47] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
The potential contribution of HLA-A alleles to viremic control in chronic HIV type 1 (HIV-1) infection has been relatively understudied compared with HLA-B. In these studies, we show that HLA-A*7401 is associated with favorable viremic control in extended southern African cohorts of >2100 C-clade-infected subjects. We present evidence that HLA-A*7401 operates an effect that is independent of HLA-B*5703, with which it is in linkage disequilibrium in some populations, to mediate lowered viremia. We describe a novel statistical approach to detecting additive effects between class I alleles in control of HIV-1 disease, highlighting improved viremic control in subjects with HLA-A*7401 combined with HLA-B*57. In common with HLA-B alleles that are associated with effective control of viremia, HLA-A*7401 presents highly targeted epitopes in several proteins, including Gag, Pol, Rev, and Nef, of which the Gag epitopes appear immunodominant. We identify eight novel putative HLA-A*7401-restricted epitopes, of which three have been defined to the optimal epitope. In common with HLA-B alleles linked with slow progression, viremic control through an HLA-A*7401-restricted response appears to be associated with the selection of escape mutants within Gag epitopes that reduce viral replicative capacity. These studies highlight the potentially important contribution of an HLA-A allele to immune control of HIV infection, which may have been concealed by a stronger effect mediated by an HLA-B allele with which it is in linkage disequilibrium. In addition, these studies identify a factor contributing to different HIV disease outcomes in individuals expressing HLA-B*5703.
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Affiliation(s)
- Philippa C Matthews
- Department of Paediatrics, University of Oxford, Oxford OX1 3SY, United Kingdom
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