Dataset Information

Flow Cytometric Clinical Immunomonitoring Using Peptide-MHC Class II Tetramers: Optimization of Methods and Protocol Development.

ABSTRACT: With the advent of novel strategies to induce tolerance in autoimmune and autoimmune-like conditions, clinical trials of antigen-specific tolerizing immunotherapy have become a reality. Besides safety, it will be essential to gather mechanistic data on responding CD4+ T cells to assess the effects of various immunomodulatory approaches in early-phase trials. Peptide-MHC class II (pMHCII) multimers are an ideal tool for monitoring antigen-specific CD4+ T cell responses in unmanipulated cells directly ex vivo. Various protocols have been published but there are reagent and assay limitations across laboratories that could hinder their global application to immune monitoring. In this methodological analysis, we compare protocols and test available reagents to identify sources of variability and to determine the limitations of the tetramer binding assay. We describe a robust pMHCII flow cytometry-based assay to quantify and phenotype antigen-specific CD4+ T cells directly ex vivo from frozen peripheral blood mononuclear cell samples, which we suggest should be tested across various laboratories to standardize immune-monitoring results.

SUBMITTER: Jansen DTSL

PROVIDER: S-EPMC5786526 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Flow Cytometric Clinical Immunomonitoring Using Peptide-MHC Class II Tetramers: Optimization of Methods and Protocol Development.

Jansen Diahann T S L DTSL Ramnoruth Nishta N Loh Khai L KL Rossjohn Jamie J Reid Hugh H HH Nel Hendrik J HJ Thomas Ranjeny R

Frontiers in immunology 20180122

With the advent of novel strategies to induce tolerance in autoimmune and autoimmune-like conditions, clinical trials of antigen-specific tolerizing immunotherapy have become a reality. Besides safety, it will be essential to gather mechanistic data on responding CD4<sup>+</sup> T cells to assess the effects of various immunomodulatory approaches in early-phase trials. Peptide-MHC class II (pMHCII) multimers are an ideal tool for monitoring antigen-specific CD4<sup>+</sup> T cell responses in un ...[more]

PMID: 29403492

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Project description:Major Histocompatibility Complex (MHC) class I molecules enable cytotoxic T lymphocytes to destroy virus-infected or cancerous cells, thereby preventing disease progression. MHC class I molecules provide a snapshot of the contents of a cell by binding to protein fragments arising from intracellular protein turnover and presenting these fragments at the cell surface. Competing fragments (peptides) are selected for cell-surface presentation on the basis of their ability to form a stable complex with MHC class I, by a process known as peptide optimization. A better understanding of the optimization process is important for our understanding of immunodominance, the predominance of some T lymphocyte specificities over others, which can determine the efficacy of an immune response, the danger of immune evasion, and the success of vaccination strategies. In this paper we present a dynamical systems model of peptide optimization by MHC class I. We incorporate the chaperone molecule tapasin, which has been shown to enhance peptide optimization to different extents for different MHC class I alleles. Using a combination of published and novel experimental data to parameterize the model, we arrive at a relation of peptide filtering, which quantifies peptide optimization as a function of peptide supply and peptide unbinding rates. From this relation, we find that tapasin enhances peptide unbinding to improve peptide optimization without significantly delaying the transit of MHC to the cell surface, and differences in peptide optimization across MHC class I alleles can be explained by allele-specific differences in peptide binding. Importantly, our filtering relation may be used to dynamically predict the cell surface abundance of any number of competing peptides by MHC class I alleles, providing a quantitative basis to investigate viral infection or disease at the cellular level. We exemplify this by simulating optimization of the distribution of peptides derived from Human Immunodeficiency Virus Gag-Pol polyprotein.

Dataset Information

Flow Cytometric Clinical Immunomonitoring Using Peptide-MHC Class II Tetramers: Optimization of Methods and Protocol Development.

Publications

Flow Cytometric Clinical Immunomonitoring Using Peptide-MHC Class II Tetramers: Optimization of Methods and Protocol Development.

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