Nanoscale Features of Tunable Bacterial Outer Membrane Models Revealed by Correlative Microscopy

The rise of antibiotic resistance is a growing worldwide human health issue, with major socioeconomic implications. An understanding of the interactions occurring at the bacterial membrane is crucial for the generation of new antibiotics. Supported lipid bilayers (SLBs) made from reconstituted lipid vesicles have been used to mimic these membranes, but their utility has been restricted by the simplistic nature of these systems. A breakthrough in the field has come with the use of outer membrane vesicles derived from Gram-negative bacteria to form SLBs, thus providing a more physiologically relevant system. These complex bilayer systems hold promise but have not yet been fully characterized in terms of their composition, ratio of natural to synthetic components, and membrane protein content. Here, we use correlative atomic force microscopy (AFM) with structured illumination microscopy (SIM) for the accurate mapping of complex lipid bilayers that consist of a synthetic fraction and a fraction of lipids derived from Escherichia coli outer membrane vesicles (OMVs). We exploit the high resolution and molecular specificity that SIM can offer to identify areas of interest in these bilayers and the enhanced resolution that AFM provides to create detailed topography maps of the bilayers. We are thus able to understand the way in which the two different lipid fractions (natural and synthetic) mix within the bilayers, and we can quantify the amount of bacterial membrane incorporated into the bilayer. We prove the system's tunability by generating bilayers made using OMVs engineered to contain a green fluorescent protein (GFP) binding nanobody fused with the porin OmpA. We are able to directly visualize protein-protein interactions between GFP and the nanobody complex. Our work sets the foundation for accurately understanding the composition and properties of OMV-derived SLBs to generate a high-resolution platform for investigating bacterial membrane interactions for the development of next-generation antibiotics.