Statistical ensemble of gene regulatory networks of macrophage differentiation

BMC Bioinformatics. 2016 Dec 22;17(Suppl 19):506. doi: 10.1186/s12859-016-1363-4.

Abstract

Background: Macrophages cover a major role in the immune system, being the most plastic cell yielding several key immune functions.

Methods: Here we derived a minimalistic gene regulatory network model for the differentiation of macrophages into the two phenotypes M1 (pro-) and M2 (anti-inflammatory).

Results: 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.

Conclusions: 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.

Keywords: Agent-based modelling; Gene regulatory network; Macrophage differentiation; Multiscale modelling.

MeSH terms

  • Cell Differentiation*
  • Gene Expression Regulation
  • Gene Regulatory Networks*
  • Humans
  • Macrophages / cytology*
  • Macrophages / metabolism*
  • Models, Statistical*
  • Systems Biology / methods*