Gene regulatory network modeling of macrophage polarization supports the continuum hypothesis of phenotype differentiation states

Macrophages derived from monocyte precursors undergo specific polarization processes being influenced by the local tissue environment: classically-activated (M1) macrophages, showing a pro-inflammatory activity affecting effector cells in Th1 cellular immune responses; and alternatively-activated (M2) macrophages, with anti-inflammatory functions, involved in immunosuppression and tissue repair. At least three distinctive subsets of M2 macrophages, i.e. M2a, M2b and M2c, are characterized in the literature based on their eliciting molecular signals. The triggering and polarization of macrophages is attained through numerous, interweaved signaling pathways. To depict the logical relations among the genes involved in macrophage polarization, we utilized a computational modeling methodology, viz. Boolean modeling of gene regulation. We combined experimental data/knowledge from the literature to build a logical gene regulation network model driving macrophage polarization to M1, M2a, M2b and M2c phenotypes. Exploiting the GINsim software we studied the network dynamics under different settings and perturbations to comprehend how they affect cell polarization. Simulations of the network model, enacting the most significant biological conditions, showed consistency with the experimentally observed behaviour of in vivo macrophages. The model could properly replicate the polarization toward the four main phenotypes as well as to numerous hybrid phenotypes, known to be experimentally associated to physiological and pathological conditions. We speculate that shifts among different phenotypes in our model mimic the hypothetical continuum of macrophage polarization, with M1 and M2 being the poles of a continuous succession of states. Our simulations also suggest that anti-inflammatory macrophages are more resilient to shift to the pro-inflammatory phenotype.