ABSTRACT
Flow cytometry enables the sequential determination of calcium levels in millions of stimulated lymphocytes over a short period of time. Current algorithms available are not suitable for the statistical analysis of this large amount of data. The authors aimed to develop a robust algorithm that fits a function to median values of measured data and provides an opportunity for statistical comparison between different calcium-flux measurements. The alteration of calcium signal was monitored in CD4+ cells loaded with calcium binding fluorescent dyes and stimulated with phytohemagglutinin; the alteration of calcium signal was monitored for 10 minutes. The authors also reanalyzed published calcium-flux data of CD3+ cells and Jurkat cells stimulated with different concentrations of anti-CD3 and thapsigargin. The authors fitted different functions to the medians of data per time unit and identified hormesis function as the best fitting one. On the basis of the optimally fitting function, the authors calculated the most relevant biological descriptors such as starting value, peak, time to reach the maximum, and time to reach 50% of maximum before and after the peak. Statistically significant differences in cell activation kinetics at different stimulatory concentrations were also demonstrated. This approach enables us to characterize the kinetics and distribution of calcium-flux data derived by flow cytometry and may be a reliable tool for the characterization of lymphocyte activation (for details see: http://calciumflux.intralab.eu).