Modeling Lipid Vesicles’ Dynamic Response to Osmotic Pressure to Quantify Small-Molecule Transport

Abstract

Lipid membrane permeability is fundamental for cellular homeostasis, signaling, and drug transport. Experimental methods exist to characterize it, from cell-based assays to more reproducible artificial, filter-supported systems. Although they closely mimic physiological environments, these assays pose challenges for quantitative analysis. Simpler models, such as supported lipid bilayers and liposomes, offer better control of experimental variables and membrane composition, making them suitable for detailed physicochemical investigations. The dynamic response of unilamellar lipid vesicles to osmotic pressure can be monitored via fluorescence spectroscopy, exploiting specific fluorophores, or label-free, by light scattering, which are among the most commonly used techniques. Proper analysis of the results allows the determination of permeant species’ permeability coefficients. A numerical algorithm was developed to simulate label-free liposome swelling/shrinking assays by explicitly considering the permeant’s water/membrane partition equilibrium and diffusion through the lipid membrane, besides the elastic properties of the latter. Optical density kinetics were collected for gradients of potassium chloride and a series of molecules with different permeability coefficients. The simulation code (adaptable also to fluorescence data) was iteratively coupled to a least-squares curve-fitting script to retrieve the permeability coefficient. The algorithm proved reliable, yielding results consistent with the literature. It represents both an analysis method and a useful screening tool, as shown by a series of numerical experiments. The study demonstrated a remarkable difference in sensitivity between swelling and shrinking directions. Although foreseen by theory, this system response asymmetry is not always included in other models, whereas it can make a great difference and must be considered when setting up experiments.