Native Pulmonary Surfactant Membranes in Mice Show Coexistence of Two Different Phases in Bilayers and Monolayers: When the Lipid Composition can Predict the Structural Phase Segregations

Abstract

Pulmonary surfactant is a surface active material composed both of lipids (aprox. 90% by weight) and proteins (aprox. 10%) produced by type II pneumocyte cells in the alveoli. This tension-active material forms a unique air-liquid interface at the alveolar cell surface that reduces surface tension close to 0 mN/m and maintains lung volumes and alveolar homeostasis at the end of the expiration. There are four pulmonary surfactant proteins (SP-A, -B, -C and -D). SP-A and -D have an important role in the immunological response against pathogens. The particular lipid composition of the lung surfactant suggests that surfactant mono- and bi-layer-based structures could exhibit lateral phase segregation at physiological temperatures. This work shows that in native pulmonary surfactant membranes a close lipid compositional study is crucial to understand the structure and biophysical function of these complex mixtures. Observing Giant Unilamellar Vesicles under conventional and two-photon excitation microscopy allow us to characterize and quantify the coexistence of two fluid-like phases in the wild-type (wt) native pulmonary surfactant membranes and a gel/fluid-like segregation pattern in the Knocked-out protein D (KOD) membranes. The atomic force microscopy studies of supported Langmuir-Blodgett bilayers and monolayers at different surface pressure show the same phase pattern before the collapse surface pressure of native pulmonary surfactant (∼40mN/m). Above this surface pressure different protruded structures can be observed arising from the more fluid phases. A closer look at the lipid composition reveals a higher content of saturated phospholipid species in the KOD native pulmonary surfactant membranes. This last finding explain the coexistence phenomena observed and allow us to conclude that the pulmonary surfactant segregation pattern could be predicted by an accurate lipid compositional study.