Statistical ensemble of gene regulatory networks of macrophage differentiation.
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.
Institute for Applied Computing, National Research Council of Italy, Via dei Taurini 19, Rome, 00185, Italy. f.castiglione@iac.cnr.it.
Filippo
F
Castiglione
Institute for Applied Computing, National Research Council of Italy, Via dei Taurini 19, Rome, 00185, Italy.
Paolo
P
Tieri
Department of Biology, University of Tor Vergata, Via della ricerca scientifica 1, Rome, 00133, Italy.
Alessandro
A
Palma
Department of Mathematics and Statistics, American University of Sharjah, P.O.Box 26666, Sharjah, UAE.
Abdul Salam
AS
Jarrah
D002454:Cell Differentiation; D005786:Gene Expression Regulation; D053263:Gene Regulatory Networks; D006801:Humans; D008264:Macrophages / Q000166:cytology* / Q000378:metabolism*; D015233:Models, Statistical; D049490:Systems Biology / Q000379:methods*
Agent-based modelling; Gene regulatory network; Macrophage differentiation; Multiscale modelling