Dataset Information

A Simple and Rapid Method for Quality Control of Major Histocompatibility Complex-Peptide Monomers by Flow Cytometry.

ABSTRACT: Major histocompatibility complex (MHC) multimers are essential tools in T cell immunomonitoring, which are employed both in basic and clinical research, as well as for assessing clinical samples during therapy. The generation of MHC monomers loaded with synthetic peptides is an elaborate and time-consuming process. It would be beneficial to assess the quality of these monomers prior to downstream applications. In this technical note, we describe a novel flow cytometry-based, cell-free, quick, and robust assay to check the quality of MHC monomers directly after refolding or after long-term storage.

SUBMITTER: Chandran PA

PROVIDER: S-EPMC5296342 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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A Simple and Rapid Method for Quality Control of Major Histocompatibility Complex-Peptide Monomers by Flow Cytometry.

Chandran P Anoop PA Heidu Sonja S Zelba Henning H Schmid-Horch Barbara B Rammensee Hans-Georg HG Pascolo Steve S Gouttefangeas Cécile C

Frontiers in immunology 20170208

Major histocompatibility complex (MHC) multimers are essential tools in T cell immunomonitoring, which are employed both in basic and clinical research, as well as for assessing clinical samples during therapy. The generation of MHC monomers loaded with synthetic peptides is an elaborate and time-consuming process. It would be beneficial to assess the quality of these monomers prior to downstream applications. In this technical note, we describe a novel flow cytometry-based, cell-free, quick, an ...[more]

PMID: 28228758

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Project description:BACKGROUND:Identification of antigenic peptide epitopes is an essential prerequisite in T cell-based molecular vaccine design. Computational (sequence-based and structure-based) methods are inexpensive and efficient compared to experimental approaches in screening numerous peptides against their cognate MHC alleles. In structure-based protocols, suited to alleles with limited epitope data, the first step is to identify high-binding peptides using docking techniques, which need improvement in speed and efficiency to be useful in large-scale screening studies. We present pDOCK: a new computational technique for rapid and accurate docking of flexible peptides to MHC receptors and primarily apply it on a non-redundant dataset of 186 pMHC (MHC-I and MHC-II) complexes with X-ray crystal structures. RESULTS:We have compared our docked structures with experimental crystallographic structures for the immunologically relevant nonameric core of the bound peptide for MHC-I and MHC-II complexes. Primary testing for re-docking of peptides into their respective MHC grooves generated 159 out of 186 peptides with C? RMSD of less than 1.00 Å, with a mean of 0.56 Å. Amongst the 25 peptides used for single and variant template docking, the C? RMSD values were below 1.00 A for 23 peptides. Compared to our earlier docking methodology, pDOCK shows upto 2.5 fold improvement in the accuracy and is ~60% faster. Results of validation against previously published studies represent a seven-fold increase in pDOCK accuracy. CONCLUSIONS:The limitations of our previous methodology have been addressed in the new docking protocol making it a rapid and accurate method to evaluate pMHC binding. pDOCK is a generic method and although benchmarks against experimental structures, it can be applied to alleles with no structural data using sequence information. Our outcomes establish the efficacy of our procedure to predict highly accurate peptide structures permitting conformational sampling of the peptide in MHC binding groove. Our results also support the applicability of pDOCK for in silico identification of promiscuous peptide epitopes that are relevant to higher proportions of human population with greater propensity to activate T cells making them key targets for the design of vaccines and immunotherapies.

Project description:Manual analysis of flow cytometry data and subjective gate-border decisions taken by individuals continue to be a source of variation in the assessment of antigen-specific T cells when comparing data across laboratories, and also over time in individual labs. Therefore, strategies to provide automated analysis of major histocompatibility complex (MHC) multimer-binding T cells represent an attractive solution to decrease subjectivity and technical variation. The challenge of using an automated analysis approach is that MHC multimer-binding T cell populations are often rare and therefore difficult to detect. We used a highly heterogeneous dataset from a recent MHC multimer proficiency panel to assess if MHC multimer-binding CD8+ T cells could be analyzed with computational solutions currently available, and if such analyses would reduce the technical variation across different laboratories. We used three different methods, FLOw Clustering without K (FLOCK), Scalable Weighted Iterative Flow-clustering Technique (SWIFT), and ReFlow to analyze flow cytometry data files from 28 laboratories. Each laboratory screened for antigen-responsive T cell populations with frequency ranging from 0.01 to 1.5% of lymphocytes within samples from two donors. Experience from this analysis shows that all three programs can be used for the identification of high to intermediate frequency of MHC multimer-binding T cell populations, with results very similar to that of manual gating. For the less frequent populations (<0.1% of live, single lymphocytes), SWIFT outperformed the other tools. As used in this study, none of the algorithms offered a completely automated pipeline for identification of MHC multimer populations, as varying degrees of human interventions were needed to complete the analysis. In this study, we demonstrate the feasibility of using automated analysis pipelines for assessing and identifying even rare populations of antigen-responsive T cells and discuss the main properties, differences, and advantages of the different methods tested.

Dataset Information

A Simple and Rapid Method for Quality Control of Major Histocompatibility Complex-Peptide Monomers by Flow Cytometry.

Publications

A Simple and Rapid Method for Quality Control of Major Histocompatibility Complex-Peptide Monomers by Flow Cytometry.

Similar Datasets

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