Castiglione Filippo, Tieri Paolo, Palma Alessandro, Jarrah Abdul Salam
Institute for Applied Computing, National Research Council of Italy, Via dei Taurini 19, Rome, 00185, Italy.
Department of Biology, University of Tor Vergata, Via della ricerca scientifica 1, Rome, 00133, Italy.
BMC Bioinformatics. 2016 Dec 22;17(Suppl 19):506. doi: 10.1186/s12859-016-1363-4.
Macrophages cover a major role in the immune system, being the most plastic cell yielding several key immune functions.
Here we derived a minimalistic gene regulatory network model for the differentiation of macrophages into the two phenotypes M1 (pro-) and M2 (anti-inflammatory).
To test the model, we simulated a large number of such networks as in a statistical ensemble. In other words, to enable the inter-cellular crosstalk required to obtain an immune activation in which the macrophage plays its role, the simulated networks are not taken in isolation but combined with other cellular agents, thus setting up a discrete minimalistic model of the immune system at the microscopic/intracellular (i.e., genetic regulation) and mesoscopic/intercellular scale.
We show that within the mesoscopic level description of cellular interaction and cooperation, the gene regulatory logic is coherent and contributes to the overall dynamics of the ensembles that shows, statistically, the expected behaviour.
巨噬细胞在免疫系统中发挥着主要作用，是具有多种关键免疫功能的最具可塑性的细胞。
在此，我们推导了一个简约的基因调控网络模型，用于巨噬细胞分化为两种表型M1（促炎）和M2（抗炎）。
为了测试该模型，我们在统计系综中模拟了大量此类网络。换句话说，为了实现获得巨噬细胞发挥作用的免疫激活所需的细胞间串扰，模拟网络并非孤立考虑，而是与其他细胞因子相结合，从而在微观/细胞内（即基因调控）和介观/细胞间尺度上建立了一个离散的简约免疫系统模型。
我们表明，在细胞相互作用与合作的介观水平描述中，基因调控逻辑是连贯的，并有助于整体集合体的动力学，从统计学上看，该集合体表现出预期行为。
