A methodological approach for using High-Level Petri Nets to model the immune system response

Background: Mathematical and computational models showed to be a very important support tool for thecomprehension of the immune system response against pathogens. Models and simulations allowed to studythe immune system behavior, to test biological hypotheses about diseases and infection dynamics, and toimprove and optimize novel and existing drugs and vaccines.Continuous models, mainly based on differential equations, usually allow to qualitatively study the system but lack indescription; conversely discrete models, such as agent based models and cellular automata, permit to describe in detailentities properties at the cost of losing most qualitative analyses. Petri Nets (PN) are a graphical modeling tool developedto model concurrency and synchronization in distributed systems. Their use has become increasingly marked also thanksto the introduction in the years of many features and extensions which lead to the born of “high level” PN.Results: We propose a novel methodological approach that is based on high level PN, and in particular on Colored PetriNets (CPN), that can be used to model the immune system response at the cellular scale. To demonstrate the potentialityof the approach we provide a simple model of the humoral immune system response that is able of reproducing someof the most complex well-known features of the adaptive response like memory and specificity features.Conclusions: The methodology we present has advantages of both the two classical approaches based oncontinuous and discrete models, since it allows to gain good level of granularity in the description of cellsbehavior without losing the possibility of having a qualitative analysis. Furthermore, the presented methodology basedon CPN allows the adoption of the same graphical modeling technique well known to life scientists that use PN for themodeling of signaling pathways. Finally, such an approach may open the floodgates to the realization of multi scalemodels that integrate both signaling pathways (intra cellular) models and cellular (population) models built upon thesame technique and software.