Evidence map›Paper›PMID 38885041›Full record

ArticleImmunoHorizons2024

Uncommon P1 Anchor-featured Viral T Cell Epitope Preference within HLA-A*2601 and HLA-A*0101 Individuals.

Jianing Zhang, Can Yue, Yin Lin, Jinmin Tian, Yuanyuan Guo, Danni Zhang, Yaxin Guo, Beiwei Ye, Yan Chai, Jianxun Qi and 4 more

Abstract read
In one paragraph

Article in ImmunoHorizons, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Jianing ZhangNational 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.
Can YueCAS Key Laboratory of Infection and Immunity, National Laboratory of Macromolecules, Institute of Biophysics, Chinese Academy of Sciences (CAS), Beijing, China.
Yin LinNational 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.
Jinmin TianNational 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.
Yuanyuan GuoNational 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.
Danni ZhangNational 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.
Yaxin GuoNational 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.ORCID 0000-0002-4690-8212
Beiwei YeNational 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.
Yan ChaiCAS Key Laboratory of Pathogen Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences (CAS), Beijing, China.ORCID 0000-0002-1912-3620
Jianxun QiCAS Key Laboratory of Pathogen Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences (CAS), Beijing, China.ORCID 0000-0002-9358-4732
Yingze ZhaoNational 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.
George F GaoCAS Key Laboratory of Pathogen Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences (CAS), Beijing, China.ORCID 0000-0002-3869-615X
Zeyu SunState 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 LiuNational 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.ORCID 0000-0001-9388-3671

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

COVID-19Epitopes, T-LymphocyteSARS-CoV-2AllelesHLA-A1 AntigenHLA-A AntigensHumansPeptidesEpitopes, T-LymphocyteHLA-A*01:01 antigenHLA-A1 AntigenHLA-A AntigensPeptides

Identifiers

PMID38885041
PMCPMC11220742

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.