RESUMO
Lateral lipid heterogeneity (i.e., raft formation) in biomembranes plays a functional role in living cells. Three-component mixtures of low- and high-melting lipids plus cholesterol offer a simplified experimental model for raft domains in which a liquid-disordered (Ld) phase coexists with a liquid-ordered (Lo) phase. Using such models, we recently showed that cryogenic electron microscopy (cryo-EM) can detect phase separation in lipid vesicles based on differences in bilayer thickness. However, the considerable noise within cryo-EM data poses a significant challenge for accurately determining the membrane phase state at high spatial resolution. To this end, we have developed an image-processing pipeline that utilizes machine learning (ML) to predict the bilayer phase in projection images of lipid vesicles. Importantly, the ML method exploits differences in both the thickness and molecular density of Lo compared to Ld, which leads to improved phase identification. To assess accuracy, we used artificial images of phase-separated lipid vesicles generated from all-atom molecular dynamics simulations of Lo and Ld phases. Synthetic ground-truth data sets mimicking a series of compositions along a tieline of Ld + Lo coexistence were created and then analyzed with various ML models. For all tieline compositions, we find that the ML approach can correctly identify the bilayer phase with >90% accuracy, thus providing a means to isolate the intensity profiles of coexisting Ld and Lo phases, as well as accurately determine domain-size distributions, number of domains, and phase-area fractions. The method described here provides a framework for characterizing nanoscopic lateral heterogeneities in membranes and paves the way for a more detailed understanding of raft properties in biological contexts.
RESUMO
We describe a method for investigating lateral membrane heterogeneity using cryogenic electron microscopy (cryo-EM) images of liposomes. The method takes advantage of differences in the thickness and molecular density of ordered and disordered phases that are resolvable in phase contrast cryo-EM. Compared to biophysical techniques like FRET or neutron scattering that yield ensemble-averaged information, cryo-EM provides direct visualization of individual vesicles and can therefore reveal variability that would otherwise be obscured by averaging. Moreover, because the contrast mechanism involves inherent properties of the lipid phases themselves, no extrinsic probes are required. We explain and discuss various complementary analyses of spatially resolved thickness and intensity measurements that enable an assessment of the membrane's phase state. The method opens a window to nanodomain structure in synthetic and biological membranes that should lead to an improved understanding of lipid raft phenomena.
Assuntos
Microscopia Crioeletrônica , Lipossomos , Microscopia Crioeletrônica/métodos , Lipossomos/química , Bicamadas Lipídicas/química , Microdomínios da Membrana/ultraestrutura , Microdomínios da Membrana/química , Microdomínios da Membrana/metabolismo , Lipídeos de Membrana/química , Separação de FasesRESUMO
Model asymmetric bilayers are useful for studying the coupling between lateral and transverse lipid organization. Here, we used calcium-induced hemifusion to create asymmetric giant unilamellar vesicles (aGUVs) for exploring the phase behavior of 16:0-PC/16:1-PC/Cholesterol, a simplified model for the mammalian plasma membrane. Symmetric GUVs (sGUVs) were first prepared using a composition that produced coexisting liquid-disordered and liquid-ordered phases visible by confocal fluorescence microscopy. The sGUVs were then hemifused to a supported lipid bilayer (SLB) composed of uniformly mixed 16:1-PC/Cholesterol. The extent of outer leaflet exchange was quantified in aGUVs in two ways: (1) from the reduction in fluorescence intensity of a lipid probe initially in the sGUV ("probe exit"); or (2) from the gain in intensity of a probe initially in the SLB ("probe entry"). These measurements revealed a large variability in the extent of outer leaflet exchange in aGUVs within a given preparation, and two populations with respect to their phase behavior: a subset of vesicles that remained phase separated, and a second subset that appeared uniformly mixed. Moreover, a correlation between phase behavior and extent of asymmetry was observed, with more strongly asymmetric vesicles having a greater probability of being uniformly mixed. We also observed substantial overlap between these populations, an indication that the uncertainty in measured exchange fraction is high. We developed models to determine the position of the phase boundary (i.e., the fraction of outer leaflet exchange above which domain formation is suppressed) and found that the phase boundaries determined separately from probe-entry and probe-exit data are in good agreement. Our models also provide improved estimates of the compositional uncertainty of individual aGUVs. We discuss several potential sources of uncertainty in the determination of lipid exchange from fluorescence measurements.
RESUMO
The organelles of eukaryotic cells maintain distinct protein and lipid compositions required for their specific functions. The mechanisms by which many of these components are sorted to their specific locations remain unknown. While some motifs mediating subcellular protein localization have been identified, many membrane proteins and most membrane lipids lack known sorting determinants. A putative mechanism for sorting of membrane components is based on membrane domains known as lipid rafts, which are laterally segregated nanoscopic assemblies of specific lipids and proteins. To assess the role of such domains in the secretory pathway, we applied a robust tool for synchronized secretory protein traffic (RUSH, Retention Using Selective Hooks) to protein constructs with defined affinity for raft phases. These constructs consist solely of single-pass transmembrane domains (TMDs) and, lacking other sorting determinants, constitute probes for membrane domain-mediated trafficking. We find that while raft affinity can be sufficient for steady-state PM localization, it is not sufficient for rapid exit from the endoplasmic reticulum (ER), which is instead mediated by a short cytosolic peptide motif. In contrast, we find that Golgi exit kinetics are highly dependent on raft affinity, with raft preferring probes exiting the Golgi ~2.5-fold faster than probes with minimal raft affinity. We rationalize these observations with a kinetic model of secretory trafficking, wherein Golgi export can be facilitated by protein association with raft domains. These observations support a role for raft-like membrane domains in the secretory pathway and establish an experimental paradigm for dissecting its underlying machinery.
Assuntos
Retículo Endoplasmático , Complexo de Golgi , Microdomínios da Membrana , Transporte Proteico , Retículo Endoplasmático/metabolismo , Complexo de Golgi/metabolismo , Microdomínios da Membrana/metabolismo , Via Secretória , Humanos , Cinética , Membrana Celular/metabolismo , Proteínas de Membrana/metabolismo , Células HeLaRESUMO
Cell membranes are responsible for a range of biological processes that require interactions between lipids and proteins. While the effects of lipids on proteins are becoming better understood, our knowledge of how protein conformational changes influence membrane dynamics remains rudimentary. Here, we performed experiments and computer simulations to study the dynamic response of a lipid membrane to changes in the conformational state of pH-low insertion peptide (pHLIP), which transitions from a surface-associated (SA) state at neutral or basic pH to a transmembrane (TM) α-helix under acidic conditions. Our results show that TM-pHLIP significantly slows down membrane thickness fluctuations due to an increase in effective membrane viscosity. Our findings suggest a possible membrane regulatory mechanism, where the TM helix affects lipid chain conformations, and subsequently alters membrane fluctuations and viscosity.