Antigenic determinants of SARS-CoV-2-specific CD4+ T cell lines reveals M protein-driven dysregulation of interferon signaling
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ABSTRACT:
PROVIDER: PRJNA831830 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR18913533.fastq.gz | Fastqsanger.gz | |||
| SRR18913534.fastq.gz | Fastqsanger.gz | |||
| SRR18913535.fastq.gz | Fastqsanger.gz | |||
| SRR18913536.fastq.gz | Fastqsanger.gz | |||
| SRR18913537.fastq.gz | Fastqsanger.gz |
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Project description:We generated CD4+ T cell lines (TCLs) reactive to either SARSCoV-2 spike (S) or membrane (M) proteins from unexposed naïve T cells from six healthy donor volunteers to understand in fine detail whether the S and M structural proteins have intrinsic differences in driving antigen-specific CD4+ T cell responses. Having shown that each of the TCLs were antigen-specific and antigen-reactive, single cell mRNA analyses demonstrated that SARS-CoV-2 S and M proteins drive strikingly distinct molecular signatures. Whereas the S-specific responses are transcriptionally similar from those responses induced by other viral antigens (e.g. CMV), the M protein-specific CD4+ TCLs have a transcriptomic signature that indicate a marked suppression of interferon signaling, characterized by a downregulation of the genes encoding ISG15, IFITM1, IFI6, MX1, STAT1, OAS1, IFI35, IFIT3 and IRF7 (a molecular signature which is not dissimilar to that found in severe COVID-19). Our study suggests a potential link between the antigen specificity of the SARS-CoV-2-reactive CD4+ T cells and the development of specific sets of adaptive immune responses. Moreover, the balance between T cells of significantly different specificities may be the key to understand how CD4+ T cell dysregulation can determine the clinical outcomes of COVID-19.
2022-06-02 | GSE201463 | GEO
Project description:We generated CD4+ T cell lines (TCLs) reactive to either SARS-CoV-2 spike (S) or membrane (M) proteins from unexposed naïve T cells from six healthy donor volunteers to understand in fine detail whether the S and M structural proteins have intrinsic differences in driving antigen-specific CD4+ T cell responses. Having shown that each of the TCLs were antigen-specific and antigen-reactive, single cell mRNA analyses demonstrated that SARS-CoV-2 S and M proteins drive strikingly distinct molecular signatures. Whereas the S-specific CD4+ T cell transcriptional signature showed a marked upregulation of CCL1, CD44, IL17RB, TNFRSF18 (GITR) and IGLC3 genes, in general their overall transcriptome signature was more similar to CD4+ T cell responses induced by other viral antigens (e.g. CMV). However, the M protein-specific CD4+ TCLs have a transcriptomic signature that indicate a marked suppression of interferon signaling, characterized by a downregulation of the genes encoding ISG15, IFITM1, IFI6, MX1, STAT1, OAS1, IFI35, IFIT3 and IRF7 (a molecular signature which is not dissimilar to that found in severe COVID-19). Our study suggests a potential link between the antigen specificity of the SARS-CoV-2-reactive CD4+ T cells and the development of specific sets of adaptive immune responses. Moreover, the balance between T cells of significantly different specificities may be the key to understand how CD4+ T cell dysregulation can determine the clinical outcomes of COVID-19.
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Project description:Presentation of antigenic peptides by MHCI is central to cellular immune responses against viral pathogens. While adaptive immune responses versus SARS-CoV-2 can be of critical importance to both recovery and vaccine efficacy, how protein antigens from this pathogen are processed inside the cell to generate antigenic peptides is largely unknown. Here, we analyzed the proteolytic processing of 315 overlapping precursor peptides spanning the entire sequence of the S1 spike glycoprotein of SARS-CoV-2, by three key enzymes for the generation ofthat generate antigenic peptides, namely intracellular aminopeptidases ERAP1, ERAP2 and IRAP. Each All enzymes generated shorter peptides with sequences suitable for binding onto HLA alleles, but with marked differences corresponding to distinct specificity fingerprints. ERAP1 was the most efficient in generating peptides 8-11 residues long, the optimal length for HLA binding, while IRAP was the least efficient. The combination of ERAP1 with ERAP2 was largely highly destructive and greatly reduced limited peptides the variability of peptide sequences availableproduced for HLA-binding. Less than 710% of computationally predicted epitopes were found to be produced by enzymatic trimming experimentally, suggesting that proteolytic aminopeptidase processing may constitute a significant filter to successful epitope presentation. These experimentally generated putative epitopes could be prioritized for SARS-CoV-2 immunogenicity studies and vaccine design. We furthermore propose that this in vitro trimming approach could constitute a general filtering method to enhance the prediction robustness of predicting for viral antigenic epitopes.
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