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1.
Preprint em Inglês | bioRxiv | ID: ppbiorxiv-478564

RESUMO

Human immunoglobulin heavy chain (IGH) locus on chromosome 14 includes more than 40 functional copies of the variable gene (IGHV), which, together with the joining genes (IGHJ), diversity genes (IGHD), constant genes (IGHC) and immunoglobulin light chains, code for antibodies that identify and neutralize pathogenic invaders as a part of the adaptive immune system. Because of its highly repetitive sequence composition, the IGH locus has been particularly difficult to assemble or genotype through the use of standard short read sequencing technologies. Here we introduce ImmunoTyper-SR, an algorithmic method for genotype and CNV analysis of the germline IGHV genes using Illumina whole genome sequencing (WGS) data. ImmunoTyper-SR is based on a novel combinatorial optimization formulation that aims to minimize the total edit distance between reads and their assigned IGHV alleles from a given database, with constraints on the number and distribution of reads across each called allele. We have validated ImmunoTyper-SR on 12 individuals with Illumina WGS data from the 1000 Genomes Project, whose IGHV allele composition have been studied extensively through the use of long read and targeted sequencing platforms, as well as nine individuals from the NIAID COVID Consortium who have been subjected to WGS twice. We have then applied ImmunoTyper-SR on 585 samples from the NIAID COVID Consortium to investigate associations between distinct IGHV alleles and anti-type I IFN autoantibodies which have been linked to COVID-19 severity.

2.
Preprint em Inglês | medRxiv | ID: ppmedrxiv-22269491

RESUMO

We generated CD4+ T cell lines (TCLs) reactive to either SARSCoV-2 spike (S) or membrane (M) proteins from unexposed naive 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 virtually indistinguishable 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.

3.
Preprint em Inglês | medRxiv | ID: ppmedrxiv-21263853

RESUMO

Pediatric COVID-19 (pCOVID-19) is rarely severe, however a minority of SARS-CoV-2-infected children may develop MIS-C, a multisystem inflammatory syndrome with significant morbidity. In this longitudinal multi-institutional study, we used multi-omics to identify novel time- and treatment-related immunopathological signatures in children with COVID-19 (n=105) and MIS-C (n=76). pCOVID-19 was characterized by enhanced type I IFN responses, and MIS-C by type II IFN- and NF-{kappa}B dependent responses, matrisome activation, and increased levels of Spike protein. Reduced levels of IL-33 in pCOVID-19, and of CCL22 in MIS-C suggested suppression of Th2 responses. Expansion of TRBV11-2 T-cell clonotypes in MIS-C was associated with inflammation and signatures of T-cell activation, and was reversed by glucocorticoids. The association of MIS-C with the combination of HLA A*02, B*35, C*04 alleles suggests genetic susceptibility. MIS-C B cells showed higher mutation load. Use of IVIG was identified as a confounding factor in the interpretation of autoantibody levels.

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