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

Multidimensional analysis of the frequencies and rates of cytokine secretion from single cells by quantitative microengraving

The large diversity of cells that comprise the human immune system requires methods that can resolve the individual contributions of specific subsets to an immunological response. Microengraving is process that uses a dense, elastomeric array of microwells to generate microarrays of proteins secreted from large numbers of individual live cells ([similar]10⁴–10⁵ cells/assay). In this paper, we describe an approach based on this technology to quantify the rates of secretion from single immune cells. Numerical simulations of the microengraving process indicated an operating regime between 30 min–4 h that permits quantitative analysis of the rates of secretion. Through experimental validation, we demonstrate that microengraving can provide quantitative measurements of both the frequencies and the distribution in rates of secretion for up to four cytokines simultaneously released from individual viable primary immune cells. The experimental limits of detection ranged from 0.5 to 4 molecules/s for IL-6, IL-17, IFNγ, IL-2, and TNFα. These multidimensional measures resolve the number and intensities of responses by cells exposed to stimuli with greater sensitivity than single-parameter assays for cytokine release. We show that cells from different donors exhibit distinct responses based on both the frequency and magnitude of cytokine secretion when stimulated under different activating conditions. Primary T cells with specific profiles of secretion can also be recovered after microengraving for subsequent expansion in vitro. These examples demonstrate the utility of quantitative, multidimensional profiles of single cells for analyzing the diversity and dynamics of immune responses in vitro and for identifying rare cells from clinical samples.National Institute of Allergy and Infectious Diseases (U.S.) (Award no. 5U19AI050864-07)National Institute of Allergy and Infectious Diseases (U.S.) (Award no. F32AI651003)National Institute of Allergy and Infectious Diseases (U.S.) (Award no. U19AI070352)National Institute of Allergy and Infectious Diseases (U.S.) (Award no. U19AI046130)National Institute of Allergy and Infectious Diseases (U.S.) (Award no. P01AI045757)National Institute of Neurological Disorders and Stroke (U.S.) (Jacob Javits Merit Award (NS2427))Massachusetts Institute of Technology (Texaco- Mangelsdorf Career Development Professor

Guidelines for the use of flow cytometry and cell sorting in immunological studies (second edition)

These guidelines are a consensus work of a considerable number of members of the immunology and flow cytometry community. They provide the theory and key practical aspects of flow cytometry enabling immunologists to avoid the common errors that often undermine immunological data. Notably, there are comprehensive sections of all major immune cell types with helpful Tables detailing phenotypes in murine and human cells. The latest flow cytometry techniques and applications are also described, featuring examples of the data that can be generated and, importantly, how the data can be analysed. Furthermore, there are sections detailing tips, tricks and pitfalls to avoid, all written and peer-reviewed by leading experts in the field, making this an essential research companion