SARS-CoV-2 Omicron subvariants evolved to promote further escape from MHC-I recognition

  1. Miyu Moriyama
  2. Carolina Lucas
  3. Valter Silva Monteiro
  4. Yale SARS-CoV-2 Genomic Surveillance Initiative
  5. Akiko Iwasaki

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Abstract

SARS-CoV-2 variants of concern (VOCs) possess mutations that confer resistance to neutralizing antibodies within the Spike protein and are associated with breakthrough infection and reinfection. By contrast, less is known about the escape from CD8 + T cell-mediated immunity by VOC. Here, we demonstrated that all SARS-CoV-2 VOCs possess the ability to suppress MHC I expression. We identified several viral genes that contribute to the suppression of MHC I expression. Notably, MHC-I upregulation was strongly inhibited after SARS-CoV-2 infection in vivo . While earlier VOCs possess similar capacity as the ancestral strain to suppress MHC I, Omicron subvariants exhibit a greater ability to suppress surface MHC-I expressions. Collectively, our data suggest that, in addition to escape from neutralizing antibodies, the success of Omicron subvariants to cause breakthrough infection and reinfection may in part be due to its optimized evasion from T cell recognition.

Significance

Numerous pathogenic viruses have developed strategies to evade host CD8 + T cell-mediated clearance. Here, we demonstrated that SARS-CoV-2 encodes multiple viral factors that can modulate MHC-I expression in the host cells. We found that MHC-I upregulation was strongly suppressed during SARS-CoV-2 infection in vivo . Notably, the Omicron subvariants showed an enhanced ability to suppress MHC-I compared to the original strain and the earlier SARS-CoV-2 variants of concern (VOCs). Our results point to the inherently strong ability of SARS-CoV-2 to hinder MHC-I expression and demonstrated that Omicron subvariants have evolved an even more optimized capacity to evade CD8 T cell recognition.

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  1. ScreenIT

    SciScore for 10.1101/2022.05.04.490614: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Staining antibodies are as follows (Hu Fc Block Pure Fc1.3216 (BD, Cat# 564220), APC anti-HLA-ABC (Thermofisher, Cat# 17- 9983-42), APC/Cy7 anti-HLA-DR (BioLegend, Cat# 307618), PE anti- DYKDDDDK Tag (BioLegend, Cat# 637309), AF488 anti-SARS-CoV-2 Spike S1 Subunit (R&D Systems,Cat# FAB105403G), FITC anti-Influenza A NP (Thermofisher, Cat# MA1-7322), PE anti-mouse CD45 (BioLegend, Cat# 109808), BV421 anti-mouse CD31 (BioLegend, Cat# 102423), APC anti-mouse EpCAM (BioLegend, Cat# 118213), PerCP/Cy5.5 anti-H-2Kb/H-2Db (BioLegend,Cat# 114620)).
    anti-HLA-ABC
    suggested: (Thermo Fisher Scientific Cat# 17-9983-41, RRID:AB_10753773)
    anti-HLA-DR
    suggested: (BioLegend Cat# 307618, RRID:AB_493586)
    anti-SARS-CoV-2
    suggested: None
    anti-Influenza
    suggested: (Thermo Fisher Scientific Cat# MA1-7322, RRID:AB_1017747)
    anti-H-2Kb/H-2Db
    suggested: (BioLegend Cat# 114620, RRID:AB_2750200)
    Recombinant DNA
    SentencesResources
    Plasmids: pDONR207-SARS-CoV-2 E (#141273), pDONR207-SARS-CoV-2 M (#141274), pDONR207-SARS-CoV-2 ORF7a (#141276), pDONR223-SARS-CoV-2 ORF7b (#141277), pDONR223-SARS-CoV-2 ORF8 (#141278) were purchased from addgene (Kim et al., 2020) and used as templates for construction of plasmids expressing SARS-CoV-2 viral proteins.
    pDONR207-SARS-CoV-2
    suggested: None
    pDONR223-SARS-CoV-2
    suggested: None
    For HIV Nef expressing plasmid construction, NL4-3-dE-EGFP (kindly provided by Dr. Ya-Chi Ho) was used as a template.
    NL4-3-dE-EGFP
    suggested: None
    For construction of plasmids expressing SARS-CoV viral proteins, oligonucleotides corresponding to both strands of SARS-CoV Tor2 (GenBank accession: NC_004718.3) ORF8a and ORF8b containing XhoI and BamHI sites at the 5’ and 3’ ends were synthesized (IDT) and cloned into XhoI-BamHI site of c-Flag pcDNA3 vector.
    pcDNA3
    suggested: RRID:Addgene_15475)
    Software and Algorithms
    SentencesResources
    To investigate the prevalence of amino acid mutations, we downloaded up to 965 sequences of each lineage and aligned the ORF8 nucleotide sequences using Jalview software (http://www.jalview.org/) (Waterhouse et al. Bioinformatics. 2009) by MUSCLE algorithm (Edgar RC.
    Jalview
    suggested: (Jalview, RRID:SCR_006459)
    MUSCLE
    suggested: (MUSCLE, RRID:SCR_011812)
    FlowJo software (Tree Star) was used for the data analysis.
    FlowJo
    suggested: (FlowJo, RRID:SCR_008520)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    Results from scite Reference Check: We found no unreliable references.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. Version published to 10.1101/2022.05.04.490614 on bioRxiv