The magnitude of an adaptive immune response is controlled by the interplay of lymphocyte quiescence, proliferation and apoptosis. How lymphocytes integrate receptor-mediated signals influencing these cell fates is a fundamental problem for understanding this complex system. A model of the lymphocyte that reveals how stochastic parameters can be regulated by internal and external signals to generate many potential adaptive immune responses has been developed, built on an internal mechanistic unit called the cyton. The cyton model incorporates intrinsic variability of otherwise identical cells as an essential requirement for the regulation of cell numbers. Independent probability distributions are used to describe the time for cells to undergo their first division, their time to die before first division and the time before subsequent divisions or death. The limitation of the number of divisions that cells can undergo, or “division destiny”, is taken into account by a progressor fraction distribution.
Experimentally, flow cytometry is a powerful tool for monitoring the progress of cells participating in an immune reaction. The tracking dye CFSE together with immunofluorescence and viability markers provide a readout of proliferation, differentiation and death.
We report here a robust method for fitting division tracking data by implementing the cyton model as a computer program called CytonCalculator. This program allows user adjustment of the model parameters while graphically comparing the model prediction with experimental proliferating cell numbers per division state at multiple time points. These numbers are extracted from flow cytometry data using the Weasel flow cytometry data analysis program. CytonCalculator can also seek a best fit to the data by using Levenberg-Marquardt fitting methods. This process is illustrated for experimental data from SIINFEKL-stimulated CD8-positive OT1 cells.
CytonCalculator is to be made freely available to the research community.