Reproducible detection of antigen-specific T cells and Tregs via standardized and automated activation-induced marker assay workflows

Abstract

Activation-induced marker (AIM) assays are a promising tool to track antigen-specific T cells, but methodological heterogeneity between research groups hinders their clinical utility. To evaluate AIM assay reproducibility, we conducted a multi-site study of SARS-CoV-2 and cytomegalovirus AIMs. We found inherent variability in AIM assays and optimized approaches to enhance reproducibility, including a standardized workflow to minimize technical variability and a generalizable Box-Cox transformation-based statistical method to optimize calculation of AIM stimulation responses. We further standardized AIM data analysis through development of automated flow cytometric gating software, which had superior reproducibility compared to manual analysis. We also characterized antigen-specific Tregs, finding that gating on a combination of CD134, CD137, FOXP3 and HELIOS optimally detects antigen-specific cells. The combined methodology results in a high degree of reproducibility within and between research groups and provides a comprehensive foundation from which standardized AIM assays can be implemented across diverse scientific and clinical settings. MOTIVATIONReliable detection of antigen-specific T cells is critical to understand immune responses to infection and vaccination, and has translational potential to monitor T cell responses across diverse clinical settings. Activation-induced marker (AIM) assays offer a variety of advantages over methods such as ELISPOT and tetramers, but are limited by methodological heterogeneity between research groups and a lack of standardized protocols. As such, the degree to which AIM assay results are reproducible is unknown. Key variables such as cell source, media, stimulation time, marker selection for CD4+ T cells, CD8+ T cells and regulatory T cells; as well as data analysis parameters such as flow cytometric gating strategies and mathematical correction for background AIM+ frequencies in unstimulated control samples, have not been rigorously studied. To address this, we comprehensively characterized variability in AIM assays, including within and between operators and across multiple research centres, and sought to optimize a standard AIM workflow to enhance reproducibility at both the experimental and analytical levels.