We report on the normal and lateral forces between controlled-density mono- and bilayers of phospholipid co-adsorbed onto hydrophobic and hydrophilic solid supports, respectively. Interactions between 1,2-dioleoyl-sn-glycero-3-phosphocholine layers were measured using an atomic force microscope. Notable features of the normal force curves (barrier heights and widths) were found to correlate with the thickness and density of the supported lipid layers. The friction and normal force curves were also found interrelated. Thus, very low friction values were measured as long as the supported layer(s) resisted the normal pressure of the tip. However, as the applied load exceeded the critical value needed for puncturing the layers, the friction jumped to values close to those recorded between bare surfaces. The lipid layers were self-healing between measurements, but a significant hysteresis was observed in the force curves measured on approach and retraction, respectively. The study shows the potential of using atomic force microscopy for lipid layer characterization both with respect to structure and interactions. It further shows the strong lubricating effect of adsorbed lipid layers and how this varies with surface density of lipids. The findings may have important implications for the issue of joint lubrication.

The surface specific technique vibrational sum frequency spectroscopy has been applied to in situ studies of the degradation of Langmuir monolayers of 1, 2-diacyl-phosphocholines with various degrees of unsaturation in the aliphatic chains. To monitor the degradation of the phospholipids, the time-dependent change of the monolayer area at constant surface pressure and the sum frequency intensity of the vinyl CH stretch at the carbon-carbon double bonds were measured. The data show a rapid degradation of monolayers of phospholipids carrying unsaturated aliphatic chains compared to the stable lipids carrying fully saturated chains when exposed to the ambient laboratory air. In addition, the degradation of the phospholipids can be inhibited by purging the ambient air with nitrogen. This instability may be attributed to spontaneous degradation by oxidation mediated by various reactive species in the air. To further elucidate the process of lipid oxidation in biological membranes artificial Langmuir monolayers probed by a surface specific spectroscopic technique as in this study can serve as a model system for studying the degradation/oxidation of cell membrane constituents.

Raster image correlation spectroscopy (RICS) is a fluorescence image analysis method for extracting the mobility, concentration, and stoichiometry of diffusing fluorescent molecules from confocal image stacks. The method works by calculating a spatial correlation function for each image and analyzing the average of those by model fitting. Rules of thumb exist for RICS image acquisitioning, yet a rigorous theoretical approach to predict the accuracy and precision of the recovered parameters has been lacking. We outline explicit expressions to reveal the dependence of RICS results on experimental parameters. In terms of imaging settings, we observed that a twofold decrease of the pixel size, e.g., from 100 to 50 nm, decreases the error on the translational diffusion constant (D) between three- and fivefold. For D = 1 μm2 s−1, a typical value for intracellular measurements, ∼25-fold lower mean-squared relative error was obtained when the optimal scan speed was used, although more drastic improvements were observed for other values of D. We proposed a slightly modified RICS calculation that allows correcting for the significant bias of the autocorrelation function at small (≪50 × 50 pixels) sizes of the region of interest. In terms of sample properties, at molecular brightness E = 100 kHz and higher, RICS data quality was sufficient using as little as 20 images, whereas the optimal number of frames for lower E scaled pro rata. RICS data quality was constant over the nM–μM concentration range. We developed a bootstrap-based confidence interval of D that outperformed the classical least-squares approach in terms of coverage probability of the true value of D. We validated the theory via in vitro experiments of enhanced green fluorescent protein at different buffer viscosities. Finally, we outline robust practical guidelines and provide free software to simulate the parameter effects on recovery of the diffusion coefficient. 

We introduce a new, to our knowledge, numerical model based on spectral methods for analysis of fluorescence recovery after photobleaching data. The model covers pure diffusion and diffusion and binding (reaction-diffusion) with immobile binding sites, as well as arbitrary bleach region shapes. Fitting of the model is supported using both conventional recovery-curve-based estimation and pixel-based estimation, in which all individual pixels in the data are utilized. The model explicitly accounts for multiple bleach frames, diffusion (and binding) during bleaching, and bleaching during imaging. To our knowledge, no other fluorescence recovery after photobleaching framework incorporates all these model features and estimation methods. We thoroughly validate the model by comparison to stochastic simulations of particle dynamics and find it to be highly accurate. We perform simulation studies to compare recovery-curve-based estimation and pixel-based estimation in realistic settings and show that pixel-based estimation is the better method for parameter estimation as well as for distinguishing pure diffusion from diffusion and binding. We show that accounting for multiple bleach frames is important and that the effect of neglecting this is qualitatively different for the two estimation methods. We perform a simple experimental validation showing that pixel-based estimation provides better agreement with literature values than recovery-curve-based estimation and that accounting for multiple bleach frames improves the result. Further, the software developed in this work is freely available online.

The effects of electrostatic interactions and obstruction by the microstructure on probe diffusion were determined in positively charged hydrogels. Probe diffusion in fine-stranded gels and solutions of ?-lactoglobulin at pH 3.5 was determined using fluorescence recovery after photobleaching (FRAP) and binding, which is widely used in biophysics. The microstructures of the ?-lactoglobulin gels were characterized using transmission electron microscopy. The effects of probe size and charge (negatively charged Na2-fluorescein (376Da) and weakly anionic 70kDa FITC-dextran), probe concentration (50 to 200 ppm), and ?-lactoglobulin concentration (9% to 12% w/w) on the diffusion properties and the electrostatic interaction between the negatively charged probes and the positively charged gels or solutions were evaluated. The results show that the diffusion of negatively charged Na2-fluorescein is strongly influenced by electrostatic interactions in the positively charged ?-lactoglobulin systems. A linear relationship between the pseudo-on binding rate constant and the ?-lactoglobulin concentration for three different probe concentrations was found. This validates an important assumption of existing biophysical FRAP and binding models, namely that the pseudo-on binding rate constant equals the product of the molecular binding rate constant and the concentration of the free binding sites. Indicators were established to clarify whether FRAP data should be analyzed using a binding-diffusion model or an obstruction-diffusion model.