Tunable Membrane Potential Reconstituted in Giant Vesicles Promotes Permeation of Cationic Peptides at Nanomolar Concentrations.
Ontology highlight
ABSTRACT: We investigate the influence of membrane potential on the permeation of cationic peptides. Therefore, we employ a microfluidic chip capable of capturing giant unilamellar vesicles (GUVs) in physical traps and fast exchange of chemical compounds. Control experiments with calcein proved that the vesicle membranes' integrity is not affected by the physical traps and applied shear forces. Combined with fluorescence correlation spectroscopy, permeation of fluorescently labeled peptides across vesicle membranes can be measured down to the nanomolar level. With the addition of a lipophilic ruthenium(II) complex Ru(C17)22+, GUVs consisting of mixed acyl phospholipids are prepared with a negative membrane potential, resembling the membrane asymmetry in cells. The membrane potential serves as a driving force for the permeation of cationic cell-penetrating peptides (CPPs) nonaarginine (Arg9) and the human immunodeficiency virus trans-activator of transcription (TAT) peptide already at nanomolar doses. Hyperpolarization of the membrane by photo-oxidation of Ru(C17)22+ enhances permeation significantly from 55 to 78% for Arg9. This specific enhancement for Arg9 (cf. TAT) is ascribed to the higher affinity of the arginines to the phosphoserine head groups. On the other hand, permeation is decreased by introducing an additional negative charge in close proximity to the N-terminal arginine residue when changing the fluorophore. In short, with the capability to reconstitute membrane potential as well as shear stress, our system is a suitable platform for modeling the membrane permeability of pharmaceutics candidates. The results also highlight the membrane potential as a major cause of discrepancies between vesicular and cellular studies on CPP permeation.
SUBMITTER: Lin CC
PROVIDER: S-EPMC6420060 | biostudies-literature | 2018 Dec
REPOSITORIES: biostudies-literature
ACCESS DATA