A systems immunology perspective on germinal center reaction dynamics

Adaptive immunity recognizes and responds to pathogens via B and T cells across cellular and humoral branches. Humoral immunity is mediated by B cells, which encounter antigens and differentiate into antibody-secreting plasma cells. Germinal centers (GCs) play a central role in humoral immunity by supporting B cell proliferation, diversification, and selection during affinity maturation or the GC reaction. In this thesis, we use computational multiscale modeling to understand germinal center reaction dynamics.
An agent-based model (ABM) was used to simulate GC cellular behavior, extended with probabilistic antigen (Ag) collection mechanisms to investigate how receptor-antigen binding kinetics influence B cell selection. Additionally, we used the model to explore how antigen concentration affects antibody affinity and binding kinetics. Furthermore, we integrated a core gene regulatory network (BCL6, IRF4, BLIMP1) into the ABM via ordinary differential equations in each B cell to simulate plasma cell differentiation and examine asymmetric cell division.
Using this kinetic model, we found that binding kinetics might influence B cell selection. Moreover, antigen concentration affects both the number and affinity of GC output cells. The multiscale model shows that affinity-based CD40 signaling, combined with asymmetric B cell division, drives a shift from memory B cell to plasma cell production. Findings demonstrate that cell fate decisions are unlikely to be governed solely by asymmetric antigen division and that BLIMP1 plays a more pivotal role.
Finally, we contributed to improving computational reproducibility by developing ENCORE (ENhancing COmputational REsearch), a framework partially informed by our experiences during this work.