Biology subjects

Chisanga, D.

Publications and source records attributed to Chisanga, D..

2 recordsLinked to original sources

bioRxiv2026

Unconventional presentation of an immunodominant HLA-DR15-restricted nephritogenic proteinase 3 epitope implicated in vasculitis

Proteinase 3 (PR3) anti-neutrophil cytoplasmic antibody (ANCA)-associated vasculitis is associated with HLA-DR15, implicating HLA-DR15-restricted CD4 T cell autoimmunity in the disease. However, the PR3 epitopes presented by HLA-DR15 and the autoreactive CD4 T cell responses they elicit are undefined. Using humanized hPR3.DR15+ mice, we identified PR3216-231 as an immunodominant human PR3-derived CD4 T cell epitope presented by HLA-DR15. Immunopeptidomic profiling confirmed the natural processing and HLA-DR15-restricted presentation of PR3216-231. Structural analyses of HLA-DR15-PR3216-231 complexes revealed an unconventional mode of HLA class II antigen presentation, in which a 10 amino acid peptide core occupies the 9 amino acid binding groove, causing a central kink in the bound peptide. PR3216-231-specific CD4 T cells from both hPR3.DR15+ mice and patients with PR3-ANCA-associated vasculitis exhibited convergent T cell receptor features, and patients with active vasculitis displayed a clonally expanded, PR3216-231-specific CD4 TCR repertoire. Immunization of hPR3.DR15 mice with PR3216-231 induced cell-mediated glomerulonephritis characterized by increased renal infiltration of CD4 T cells and macrophages together with segmental glomerular necrosis. These findings identify a nephritogenic PR3-derived CD4 T cell epitope presented by HLA-DR15 in ANCA-associated vasculitis and define a new extended core binding pattern, broadening our understanding of HLA class II peptide presentation.

immunology↗

bioRxiv2021

Impact of gene annotation choice on the quantification of RNA-seq data

RNA sequencing is currently the method of choice for genome-wide profiling of gene expression. A popular approach to quantify expression levels of genes from RNA-seq data is to map reads to a reference genome and then count mapped reads to each gene. Gene annotation data, which include chromosomal coordinates of exons for tens of thousands of genes, are required for this quantification process. There are several major sources of gene annotations that can be used for quantification, such as Ensembl and RefSeq databases. However, there is very little understanding of the effect that the choice of annotation has on the accuracy of gene expression quantification in an RNA-seq analysis. In this paper, we present results from our comparison of Ensembl and RefSeq human annotations on their impact on gene expression quantification using a benchmark RNA-seq dataset generated by the SEquencing Quality Control (SEQC) consortium. We show that the use of RefSeq gene annotation models led to better quantification accuracy, based on the correlation with ground truths including expression data from >800 real-time PCR validated genes, known titration ratios of gene expression and microarray expression data. We also found that the recent expansion of the RefSeq annotation has led to a decrease in its annotation accuracy. Finally, we demonstrated that the RNA-seq quantification differences observed between different annotations were not affected by the use of different normalization methods.

bioinformatics↗