Experimental and data processing workflow for large-scale immune monitoring studies by mass cytometry
Mass cytometry is a powerful large-scale immune monitoring technology. It requires a careful experimental and analytical design to ensure a maximal data quality. Here I present an experimental protocol for whole blood analysis together with an r-based data analysis pipeline, which ensures the minimization of the experimental artifacts and batch effects, while ensuring data reproducibility. Whole blood samples are fixed and frozen for the phenotyping study just upon drawing or after stimulation. Thus, this protocol is particularly suitable for multiday, multicenter and retrospective studies.
Paulina Rybakowska held her Master’s degrees in Molecular Biology from University of Warsaw. She received a strong immunology background during a two-year internship in the laboratory of Umesh Deshmukh at the University of Virginia, Charlottesville and Oklahoma Medical Research foundation, Oklahoma City, as a scholar of the Visiting Research Graduate Traineeship Program (VRGTP). Currently, she is a PhD student at Marta Alarcón-Riquelme´s laboratory at GENYO (Centre for Genomics and Oncological Research). Her main interests are systemic autoimmune diseases and the application of single-cell technologies like flow and mass cytometry to immune monitoring studies. As an EMBO scholar she spent half a year at the Yvan Saeys laboratory in Ghent (Belgium), where she received training in programming and high dimensional cytometry data analysis.
Retrospective studies, automated data preprocessing, whole blood immunophenotyping, reference sample