Hierarchical Bayesian mixture modelling for antigen-specific T-cell subtyping in combinatorially encoded flow cytometry studies.

Novel uses of automated flow cytometry technology for measuring levels of protein markers on thousands to millions of cells are promoting increasing need for relevant, customized Bayesian mixture modelling approaches in many areas of biomedical research and application. In studies of immune profiling in many biological areas, traditional flow cytometry measures relative levels of abundance of marker proteins using fluorescently labeled tags that identify specific markers by a single-color. One specific and important recent development in this area is the use of combinatorial marker assays in which each marker is targeted with a probe that is labeled with two or more fluorescent tags. The use of several colors enables the identification of, in principle, combinatorially increasingly numbers of subtypes of cells, each identified by a subset of colors. This represents a major advance in the ability to characterize variation in immune responses involving larger numbers of functionally differentiated cell subtypes. We describe novel classes of Markov chain Monte Carlo methods for model fitting that exploit distributed GPU (graphics processing unit) implementation. We discuss issues of cellular subtype identification in this novel, general model framework, and provide a detailed example using simulated data. We then describe application to a data set from an experimental study of antigen-specific T-cell subtyping using combinatorially encoded assays in human blood samples. Summary comments discuss broader questions in applications in immunology, and aspects of statistical computation.

Conditional ligands for Asian HLA variants facilitate the definition of CD8+ T-cell responses in acute and chronic viral diseases.

Conditional ligands have enabled the high-throughput production of human leukocyte antigen (HLA) libraries that present defined peptides. Immunomonitoring platforms typically concentrate on restriction elements associated with European ancestry, and such tools are scarce for Asian HLA variants. We report 30 novel irradiation-sensitive ligands, specifically targeting South East Asian populations, which provide 93, 63, and 79% coverage for HLA-A, -B, and -C, respectively. Unique ligands for all 16 HLA types were constructed to provide the desired soluble HLA product in sufficient yield. Peptide exchange was accomplished for all variants as demonstrated by an ELISA-based MHC stability assay. HLA tetramers with redirected specificity could detect antigen-specific CD8(+) T-cell responses against human cytomegalovirus, hepatitis B (HBV), dengue virus (DENV), and Epstein-Barr virus (EBV) infections. The potential of this population-centric HLA library was demonstrated with the characterization of seven novel T-cell epitopes from severe acute respiratory syndrome coronavirus, HBV, and DENV. Posthoc analysis revealed that the majority of responses would be more readily identified by our unbiased discovery approach than through the application of state-of-the-art epitope prediction. This flow cytometry-based technology therefore holds considerable promise for monitoring clinically relevant antigen-specific T-cell responses in populations of distinct ethnicity.