Behçet's disease risk-variant HLA-B51/ERAP1-Hap10 alters human CD8 T cell immunity.

OBJECTIVES: The endoplasmic reticulum aminopeptidase (ERAP1) haplotype Hap10 encodes for a variant allotype of the endoplasmic reticulum (ER)-resident peptide-trimming aminopeptidase ERAP1 with low enzymatic activity. This haplotype recessively confers the highest risk for Behçet's diseases (BD) currently known, but only in carriers of HLA-B*51, the classical risk factor for the disease. The mechanistic implications and biological consequences of this epistatic relationship are unknown. Here, we aimed to determine its biological relevance and functional impact. METHODS: We genotyped and immune phenotyped a cohort of 26 untreated Turkish BD subjects and 22 healthy donors, generated CRISPR-Cas9 ERAP1 KOs from HLA-B*51 + LCL, analysed the HLA class I-bound peptidome for peptide length differences and assessed immunogenicity of genome-edited cells in CD8 T cell co-culture systems. RESULTS: Allele frequencies of ERAP1-Hap10 were similar to previous studies. There were frequency shifts between antigen-experienced and naïve CD8 T cell populations of carriers and non-carriers of ERAP1-Hap10 in an HLA-B*51 background. ERAP1 KO cells showed peptidomes with longer peptides above 9mer and significant differences in their ability to stimulate alloreactive CD8 T cells compared with wild-type control cells. CONCLUSIONS: We demonstrate that hypoactive ERAP1 changes immunogenicity to CD8 T cells, mediated by an HLA class I peptidome with undertrimmed peptides. Naïve/effector CD8 T cell shifts in affected carriers provide evidence of the biological relevance of ERAP1-Hap10/HLA-B*51 at the cellular level and point to an HLA-B51-restricted process. Our findings suggest that variant ERAP1-Hap10 partakes in BD pathogenesis by generating HLA-B51-restricted peptides, causing a change in immunodominance of the ensuing CD8 T cell response.

Flow Plex-A tool for unbiased comprehensive flow cytometry data analysis.

INTRODUCTION: The information content of multiparametric flow cytometry experiments is routinely underexploited given the paucity of adequate tools for unbiased comprehensive data analysis that can be applied successfully and independently by immunologists without computational training. METHODS: We aimed to develop a tool that allows straightforward access to the entire information content of any given flow cytometry panel for immunologists without special computational expertise. We used a data analysis approach which accounts for all mathematically possible combinations of markers in a given panel, coded the algorithm and applied the method to mined and self-generated data sets. RESULTS: We developed Flow Plex, a straightforward computational tool that allows unrestricted access to the information content of a given flow cytometry panel, enables classification of human samples according to distinct immune phenotypes, such as different forms of autoimmune uveitis, acute myeloid leukemia vs "healthy", "old" vs "young", and facilitates the identification of cell populations with potential biologic relevance to states of disease and health. CONCLUSIONS: We provide a tool that allows immunologists and other flow cytometry users with limited bioinformatics skills to extract comprehensive, unbiased information from flow cytometry data sets.