Abstract
Supported lipid bilayers (SLBs) are crucial model membrane platforms to study the structure and dynamics of cellular membranes. Vesicle fusion (VF) is one of the most widely used approaches to forming SLBs, though it suffers from compositional limitations and substrate compatibility constraints. The solvent-assisted lipid bilayer (SALB) technique enables the possibility of forming SLBs using a wider range of membrane compositions and substrate platforms through organic-solvent-mediated bilayer assembly, yet questions remain regarding structural equivalence and potential organic solvent incorporation effects. Using neutron reflectometry (NR), we systematically compare the structure and composition of phosphatidylcholine-based SLBs formed by either VF or SALB methodologies. SALB conditions were optimized for NR solid/liquid cells, and structural characterization revealed comparable bilayer architectures between the two formation methods, although some changes in the lipid acyl chain thickness were observed. SALBs showed up to 99.2 ± 0.9% surface coverage using ultrapure water for solvent exchange, but the reproducibility of the method was poor. Enhanced-contrast NR using either deuterated lipids or solvents allowed for the quantitative detection of residual organic solvent incorporation of the SALBs, which was up to 3.3 ± 0.9 vol.% in the tail regions. Making use of 1 mM CaCl(2) during solvent exchange substantially improved SALB reproducibility, reducing coverage variability from 21-30 to 2 vol.%. Validation studies using the antimicrobial peptide melittin demonstrated that membrane-peptide interactions proceeded according to established mechanisms, with peptide incorporation of 18 vol.% for the low-coverage (69.7 ± 0.8%) SALB. The quantified solvent incorporation levels and small changes in acyl chain layer thickness in the SALBs must be considered when interpreting protein-membrane interaction studies, which suggests that validation of the SALB methodology for membrane research applications requires assessment on a case by case basis.