Automated Analysis of Flow Cytometry Data to Reduce Inter-Lab Variation in the Detection of Major Histocompatibility Complex Multimer-Binding T Cells.

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.

Dextramer reagents are effective tools for quantifying CMV antigen-specific T cells from peripheral blood samples.

The enumeration of antigen-specific T cells is increasingly relevant in clinical and research settings. This information is useful for evaluating immune responses to treatment, monitoring the efficacy of anticancer vaccines, and for detecting self-reactive T cells in autoimmune disorders. Quantifying antigen-specific T cells can be accomplished via IFNγ ELISpot assay, the measurement of intracellular cytokine production by flow cytometry, or by lymphocyte proliferation assays in response to antigen. While robust, these technologies are labor-intensive and can take several days to obtain results. New technology has led to more powerful tools for quickly and accurately measuring antigen-specific T cells by flow cytometry via fluorescently-labeled TCR-specific multimers. In this study, we evaluated the use of an assay based on Dextramer reagents for enumerating cytomegalovirus (CMV) antigen-specific T cells (CASTs). Assay performance characteristics were assessed by establishing Dextramers' sensitivity (median=0.4; range=0.1-1.4 CASTs µl(-1) ), determining their specificity (100%), evaluating assay robustness with different leukocyte sources and assay reproducibility via interlaboratory and interinstrument investigations. Furthermore, the levels of CASTs in 95 peripheral blood samples from 62 unique blood and marrow transplants recipients correlated well between Dextramers and Tetramers (R(2) =0.9042).