  Activation of naive CD8 T-cells can lead to the generation of multiple
effector and memory subsets. Multiple parameters associated with activation
conditions are involved in generating this diversity that is associated with
heterogeneous molecular contents of activated cells. Although naive cell
polarisation upon antigenic stimulation and the resulting asymmetric division
are known to be a major source of heterogeneity and cell fate regulation, the
consequences of stochastic uneven partitioning of molecular content upon
subsequent divisions remain unclear yet. Here we aim at studying the impact of
uneven partitioning on molecular-content heterogeneity and then on the immune
response dynamics at the cellular level. To do so, we introduce a multiscale
mathematical model of the CD8 T-cell immune response in the lymph node. In the
model, cells are described as agents evolving and interacting in a 2D
environment while a set of differential equations, embedded in each cell,
models the regulation of intra and extracellular proteins involved in cell
differentiation. Based on the analysis of in silico data at the single cell
level, we 1 show that immune response dynamics can be explained by the
molecular-content heterogeneity generated by uneven partitioning at cell
division. In particular, uneven partitioning acts as a regulator of cell
differentiation and induces the emergence of two coexisting sub-populations of
cells exhibiting antagonistic fates. We show that the degree of unevenness of
molecular partitioning, along all cell divisions, affects the outcome of the
immune response and can promote the generation of memory cells.
