Dissecting CD8+ T cell pathology of severe SARS-CoV-2 infection by single-cell epitope mapping

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Abstract

The current COVID-19 pandemic represents a global challenge. A better understanding of the immune response against SARS-CoV-2 is key to unveil the differences in disease severity and to develop future vaccines targeting novel SARS-CoV-2 variants. Feature barcode technology combined with CITE-seq antibodies and DNA-barcoded peptide-MHC I Dextramer reagents enabled us to identify relevant SARS-CoV-2-derived epitopes and compare epitope-specific CD8 + T cell populations between mild and severe COVID-19. We identified a strong CD8 + T cell response against an S protein-derived epitope. CD8 + effector cells in severe COVID-19 displayed hyperactivation, T cell exhaustion and were missing characteristics of long-lived memory T cells. We identify A*0101 WTAGAAAYY as an immunogenic CD8 + T cell epitope with the ability to drive clonal expansion. We provide an in-depth characterization of the CD8 + T cell-mediated response to SARS-CoV-2 infection which will be relevant for the development of molecular and targeted therapies and potential adjustments of vaccination strategies.

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  1. SciScore for 10.1101/2021.03.03.432690: (What is this?)

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

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Antibodies
    SentencesResources
    SARS-CoV-2 antibody testing: To exclude healthy controls with a previous SARS-CoV-2 infection, we tested the subjects for SARS-CoV-2-specific IgG antibodies by performing the Euroimmun anti-SARS-CoV-2 ELISA (IgG) (EUROIMMUN, Lübeck, Germany)
    SARS-CoV-2-specific IgG
    suggested: None
    anti-SARS-CoV-2 ELISA ( IgG
    suggested: None
    The Dextramer reagent pool was incubated with the samples for 10 minutes at 4°C, followed by a 30 minute incubation with the TotalSeq-C antibody pool and 5 μl of a PE/Cyanine7 anti-human CD8 antibody (BioLegend) at 4°C.
    TotalSeq-C
    suggested: None
    anti-human CD8
    suggested: None
    Software and Algorithms
    SentencesResources
    After de-multiplexing using the MiSeq Reporter software (Illumina Inc.), the analysis of the read sequences was performed by a Visual Basic-based in-house software (NGSSequence Analyser, Institute of Transplantation Diagnostics and Cell Therapeutics (ITZ), University Hospital of Düsseldorf, Düsseldorf, Germany) approach considering quality control values and high coverage to automate data analysis.
    MiSeq Reporter
    suggested: None
    Bulk sequencing data analysis: Bulk-seq data analysis was carried out using the ShortRead package64 in R version 3.6.3.
    ShortRead
    suggested: (ShortRead, RRID:SCR_006813)
    Downstream analysis was conducted with Seurat version 4.065 in R version 4.0.3.
    Seurat
    suggested: (SEURAT, RRID:SCR_007322)
    Transcription factor activities with FDR < 5% or an absolute normalized enrichment score > 2.5 between the active mild and severe condition were visualized with pheatmap.
    pheatmap
    suggested: (pheatmap, RRID:SCR_016418)
    Supplementary Fig. 3A is referred to for all PROGENy pathway activities per condition.
    PROGENy
    suggested: (PROGENY, RRID:SCR_006647)
    For the active mild and severe conditions, interactions with the T cell activating (NKG2D, NKG2C:CD94, CD94:NKG2E, and CLEC2B)31,73,74 and inhibiting receptors (NKG2A:CD94, KIR3DL2, KIR2DL3, KIR2DL1, and KLRB1)75 were visualized with the circlize package76.
    circlize
    suggested: (circlize, RRID:SCR_002141)
    Briefly, CrossTalkeR constructs representations of the ligand-receptor networks for each condition, where the edges of the network are weighted by the number of interactions and the sum of weights of the interaction-pairs obtained by CellPhoneDB.
    CellPhoneDB
    suggested: (CellPhoneDB, RRID:SCR_017054)
    Slingshot was run on the UMAP embedding of the remaining clusters and the CD8+ TN population was designated as the root.
    Slingshot
    suggested: (Slingshot, RRID:SCR_017012)
    Clonal expansion of the uniquely WTAGAAAYY-binding cells across pseudotime were visualized as scatter plots for the SLEC and MPEC lineages using stat_smooth (method = loess) from the ggplot2 package.
    ggplot2
    suggested: (ggplot2, RRID:SCR_014601)
    Gene set enrichment analysis together with estimation of pathway signaling and transcription factor activity was computed as described above.
    Gene set enrichment analysis
    suggested: (Gene Set Enrichment Analysis, RRID:SCR_003199)
    The viral genome of the German SARS-CoV-2 isolate (accession MT270101) was added to the human GRCh38 genome and STAR (runmode genomeGenerate)85 was run to create a joint reference genome.
    STAR
    suggested: (STAR, RRID:SCR_015899)

    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: We detected the following sentences addressing limitations in the study:
    However, limitations are imposed on the ability to detect viral RNA by the tool, including low viral load in immune cells and sparsity of scRNA-seq data57. Viral infection of the CD8+ T cells could therefore not be ruled out. Weak evidence supporting this hypothesis was the significant enrichment of genes associated with “viral gene expression” in the SLEC lineage during severe COVID-19 (Fig. 3D). Assuming viral infection is a contributing factor in observed changes in JAK-STAT signaling and in CD8+ T cell differentiation in severe COVID-19, it remains unclear why viral infection leads to severe disease in some individuals, while others only develop mild symptoms. One possible explanation for the difference in disease progression of COVID-19 could be the significant downregulation of IFITM3 in severe COVID19. Downregulation of the IFN-stimulated gene was still pertained despite increased JAK-STAT signaling in the WTAGAAAYY epitope-binding TEM1 cells in the severe group compared to mild COVID-19. As previously described, IFITM proteins have been implicated in the restriction of SARS-CoV-1 cellular entry43 and baseline expression of IFITM3 has been shown to determine the susceptibility to influenza A virus infection41,42. It is therefore possible that in individuals who develop only mild COVID-19, a higher baseline expression of IFITM3 restricts cellular entry into CD8+ T cells, therefore leading to reduced viral loads and less impairment of JAK-STAT signaling compared to sever...

    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.

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