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Updated: Jul 1, 2026

Investigation of Macrophage Polarization Using Bone Marrow Derived Macrophages
Published on: June 23, 2013
Identification of proteins regulating phenotype-associated genes of M2 macrophages: a bioinformatic analysis
E A Antropova1, I V Yatsyk1, P S Demenkov1
1Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia.
Abstract:
Macrophages are immune system cells that perform various, often opposing, functions in the organism depending on the incoming microenvironment signals. This is possible due to the plasticity of macrophages, which allows them to radically alter their phenotypic characteristics and gene expression profiles, as well as return to their original, non-activated state. Depending on the inductors acting on the cell, macrophages are activated into various functional states. There are five main phenotypes of activated macrophages: M1, M2a, M2b, M2c, and M2d. Although the amount of genome-wide transcriptomic and proteomic data showing differences between major macrophage phenotypes and non-activated macrophages (M0) is rapidly growing, questions regarding the mechanisms regulating gene and protein expression profiles in macrophages of different phenotypes still remain. We compiled lists of proteins associated with the macrophage phenotypes M1, M2a, M2b, M2c, and M2d (phenotype-associated proteins) and analyzed the data on potential mediators of macrophage polarization. Furthermore, using the computational system ANDSystem, we conducted a search and analysis of the relationships between potential regulatory proteins and the genes encoding the proteins associated with the M2 group phenotypes, obtaining estimates of the statistical significance of these relationships. The results indicate that the differences in the M2a, M2b, M2c, and M2d macrophage phenotypes may be attributed to the regulatory effects of the proteins JUN, IL8, NFAC2, CCND1, and YAP1. The expression levels of these proteins vary among the M2 group phenotypes, which in turn leads to different levels of gene expression associated with specific phenotypes.

