Maximizing Insights, Minimizing Animal Testing: A Framework for Validating Multiparametric Single-Cell Cytokine Analysis Panels

Abstract

Intracellular cytokine labeling combined with high-parametric flow cytometry offers substantial promise in elucidating the nuanced effector functions of cells. However, the establishment of complex multicolor panels is often laborious and the importance of validation processes may be underestimated in research practice. This raises the risk of prematurely translating multicolor panels into in vivo studies. Alternatively, researchers may resort to animal disease models to procure cytokine-producing cells. Both scenarios raise ethical concerns as they entail the potential for unnecessary animal suffering without yielding novel insights into immunobiology. Here, we perform multicolor panel optimization and validation without the need for stressful animal testing. We designed two spectral flow cytometry panels for cytokine expression analyses across mouse immune and joint cells. Animal testing was replaced by stimulated co-cultures of T cells, splenocytes, and fibroblast-like synoviocytes. These cultures were used for multicolor labeling experiments. Our method proved suitable for validating the two cytometry panels, as it provided a complex cellular environment in which a variety of cytokine-producing populations were identified. In summary, we here present a blueprint for the quality control of single-cell cytokine assays by cell culture and further introduce multicolor panels that can be employed for studies on inflammatory or infectious diseases.