Simulations of naïve and KLA-activated macrophage plasma membrane models

Macrophages (MAs), which play vital roles in human immune responses and lipid metabolisms, are implicated in the development and progression of atherosclerosis, a major contributor to cardiovascular diseases. Specifically, the abnormal lipid metabolism of oxidized low-density lipids (oxLDLs) in MAs is believed to be a crucial factor. However, the precise mechanism by which the MA membrane contributes to this altered lipid metabolism remains unclear. Lipidomic studies have revealed significant differences in membrane composition between various MA phenotypes. This study serves to provide and characterize complex realistic computational models for naive (M0) and Kdo2-lipid A-activated (M1) state MA. Analyses of surface area per lipid (SA/lip), area compressibility modulus (KA), carbon-hydrogen order parameter (SCH), electron density profile (EDP), tilt angles, two-dimension radial distribution functions (2D RDFs), mean squared displacement (MSD), hydrogen bonds (Hbonds), lipid clustering, and lipid wobble were conducted for both models. Results indicate that the M1 state MA membrane is more tightly packed, with increased chain order across lipid species, and forms PSM-DOPG-CHOL and PSM-SLPC-CHOL clusters. Importantly, the bilayer thicknesses reported for the models are in good agreement with experimental data for the thicknesses of transmembrane regions for MA integral proteins. These findings validate the described models as physiologically accurate for future computational studies of MA membranes and their residing proteins.

Automated summary

Macrophage membranes in the activated state are more tightly packed, exhibit increased chain order across lipid species, and form specific lipid clusters. These findings provide physiologically accurate models for future computational studies of macrophage membranes and their proteins.