Search

The relationship between biological research and mathematical modeling is complex, critical, and vital. In this review, we summarize the results of the collaboration between two laboratories, exploring the interaction between mathematical modeling and wet-lab immunology. During this collaboration several aspects of the immune defence against viral infections were investigated, focusing primarily on the subject of heterologous immunity. In this manuscript, we emphasize the topics where computational simulations were applied in conjunction with experiments, such as immune attrition, the growing and shrinking of cross-reactive T cell repertoires following repeated infections, the short and long-term effects of cross-reactive immunological memory, and the factors influencing the appearance of new clonal specificities. For each topic, we describe how the mathematical model used was adapted to answer specific biological questions, and we discuss the hypotheses that were generated by simulations. Finally, we propose rules for testing hypotheses that emerge from model experimentation in the wet lab, and vice-versa. [ABSTRACT FROM AUTHOR]

Heterologous immunity is a common phenomenon present in all infections. Most of the time it is beneficial, mediating protective immunity, but in some individuals that have the wrong crossreactive response it leads to a cascade of events that result in severe immunopathology. Infections have been associated with autoimmune diseases such as diabetes, multiple sclerosis and lupus erythematosis, but also with unusual autoimmune like pathologies where the immune system appears dysregulated, such as, sarcoidosis, colitis, panniculitis, bronchiolitis obliterans, infectious mononucleosis and even chronic fatigue syndrome. Here we review the evidence that to better understand these autoreactive pathologies it requires an evaluation of how T cells are regulated and evolve during sequential infections with different pathogens under the influence of heterologous immunity. [ABSTRACT FROM AUTHOR]

The present study uses the agent-based model IMMSIM to simulate immune responses to a viral infection, with a focus on the impact of preformed memory (homologous and heterologous) on the quality and the efficacy of the response. The in machina results confirm the observed thwarting of new, naïïve responses exerted by cross-reacting memory, but they also reveal that the competitive inhibition is made possible by the different time frame used by the primary and the secondary response, a well-known fact, epitomized by the interval of about 75 time steps between their peaks. This novel finding justifies the depression of naïïve responses and the long-term consequences it could bring about and the role of memory as a player in a survival of the fittest game. [ABSTRACT FROM AUTHOR]