Interactions and diffusion in fine-stranded β-lactoglobulin gels determined via FRAP and binding

SMART FRAP: a robust and quantitative FRAP analysis method for phase separation

We propose SMART FRAP, a robust FRAP quantitative analysis method that is insensitive to either the shape or size of the bleached region. It can not only accurately and quantitatively determine the diffusion coefficient, but also provide other essential properties of phase separation that are unobtainable by other methods.

Dynamics of small molecules within the F127 PEO-PPO-PEO triblock copolymer gel and sol phases studied at the molecular scale

Triplet excited states of guest molecules with different hydrophobicities were used to probe the association and dissociation dynamics of these guests with F127 micelles in the gel and sol phases. The dynamics probed was on a longer length scale than amenable with fluorescence techniques, but at a shorter length scale than probed in translational diffusion studies. The mobility of the guests at the molecular scale showed that subtle changes in the guest's structure affect the guest's release time from the micelles, where the structural features of the guest are more important than the phase, gel vs. sol, of the system.

Switchable β-lactoglobulin (BLG) adsorption on protein resistant oligo (ethylene glycol) (OEG) self-assembled monolayers (SAMs)

HYPOTHESIS

Although protein adsorption at an interface is very common and important in biology and biotechnology, it is still not fully understood - mainly due to the intricate balance of forces that ultimately control it. In food processing (and medicine), controlling and manipulating protein adsorption, as well as avoiding protein adsorption (biofilm formation or membrane fouling) by the production of protein-resistant surfaces is of substantial interest. A major factor conferring resistance towards protein adsorption to a surface is the presence of tightly bound water molecules, as is the case in oligo ethylene glycol (OEG)-terminated self-assembled monolayers (SAMs). Due to strong attractive protein-protein and protein-surface interactions observed in systems containing trivalent salt ions, we hypothesize that these conditions may lead to a breakdown of protein resistance in OEG SAMs.

EXPERIMENTS

We studied the adsorption behavior of BLG in the presence of a lanthanum(III) chloride (LaCl₃) at concentrations of 0, 0.1, 0.8 and 5.0 mM on normally protein resistant triethylene glycol-termianted (EG3) SAMs on a gold surface. We used quartz-crystal microbalance with dissipation (QCM-D) and neutron reflectivity (NR) to characterize the morphology of the interfacial region of the SAM.

FINDINGS

We demonstrate that the protein resistance of the EG3 SAM breaks down beyond a threshold salt concentration c^∗ and mirrors the bulk behaviour of this system, showing reduced adsorption beyond a second critical salt concentration c^∗∗. These results demonstrate for the first time the controlled switching of the protein-resistant properties of this type of SAM by the addition of trivalent salt.

DeepFRAP: Fast fluorescence recovery after photobleaching data analysis using deep neural networks

Conventional analysis of fluorescence recovery after photobleaching (FRAP) data for diffusion coefficient estimation typically involves fitting an analytical or numerical FRAP model to the recovery curve data using non-linear least squares. Depending on the model, this can be time consuming, especially for batch analysis of large numbers of data sets and if multiple initial guesses for the parameter vector are used to ensure convergence. In this work, we develop a completely new approach, DeepFRAP, utilizing machine learning for parameter estimation in FRAP. From a numerical FRAP model developed in previous work, we generate a very large set of simulated recovery curve data with realistic noise levels. The data are used for training different deep neural network regression models for prediction of several parameters, most importantly the diffusion coefficient. The neural networks are extremely fast and can estimate the parameters orders of magnitude faster than least squares. The performance of the neural network estimation framework is compared to conventional least squares estimation on simulated data, and found to be strikingly similar. Also, a simple experimental validation is performed, demonstrating excellent agreement between the two methods. We make the data and code used publicly available to facilitate further development of machine learning-based estimation in FRAP. LAY DESCRIPTION: Fluorescence recovery after photobleaching (FRAP) is one of the most frequently used methods for microscopy-based diffusion measurements and broadly used in materials science, pharmaceutics, food science and cell biology. In a FRAP experiment, a laser is used to photobleach fluorescent particles in a region. By analysing the recovery of the fluorescence intensity due to the diffusion of still fluorescent particles, the diffusion coefficient and other parameters can be estimated. Typically, a confocal laser scanning microscope (CLSM) is used to image the time evolution of the recovery, and a model is fit using least squares to obtain parameter estimates. In this work, we introduce a new, fast and accurate method for analysis of data from FRAP. The new method is based on using artificial neural networks to predict parameter values, such as the diffusion coefficient, effectively circumventing classical least squares fitting. This leads to a dramatic speed-up, especially noticeable when analysing large numbers of FRAP data sets, while still producing results in excellent agreement with least squares. Further, the neural network estimates can be used as very good initial guesses for least squares estimation in order to make the least squares optimization convergence much faster than it otherwise would. This provides for obtaining, for example, diffusion coefficients as soon as possible, spending minimal time on data analysis. In this fashion, the proposed method facilitates efficient use of the experimentalist's time which is the main motivation to our approach. The concept is demonstrated on pure diffusion. However, the concept can easily be extended to the diffusion and binding case. The concept is likely to be useful in all application areas of FRAP, including diffusion in cells, gels and solutions.

A Highly Accurate Pixel-Based FRAP Model Based on Spectral-Domain Numerical Methods

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.

Interplay between flow and diffusion in capillary alginate hydrogels

Alginate gels with naturally occurring macroscopic capillaries have been used as a model system to study the interplay between laminar flow and diffusion of nanometer-sized solutes in real time. Calcium alginate gels that contain homogeneously distributed parallel-aligned capillary structures were formed by external addition of crosslinking ions to an alginate sol. The effects of different flow rates (0, 1, 10, 50 and 100 μl min(-1)) and three different probes (fluorescein, 10 kDa and 500 kDa fluorescein isothiocyanate-dextran) on the diffusion rates of the solutes across the capillary wall and in the bulk gel in between the capillaries were investigated using confocal laser scanning microscopy. The flow in the capillaries was produced using a syringe pump that was connected to the capillaries via a tube. Transmission electron microscopy revealed an open aggregated structure close to the capillary wall, followed by an aligned network layer and the isotropic network of the bulk gel. The most pronounced effect was observed for the 1 nm-diameter fluorescein probe, for which an increase in flow rate increased the mobility of the probe in the gel. Fluorescence recovery after photobleaching confirmed increased mobility close to the channel, with increasing flow rate. Mobility maps derived using raster image correlation spectroscopy showed that the layer with the lowest mobility corresponded to the anisotropic layer of ordered network chains. The combination of microscopy techniques used in the present study elucidates the flow and diffusion behaviors visually, qualitatively and quantitatively, and represents a promising tool for future studies of mass transport in non-equilibrium systems.

Complex Coacervate Core Micelles with Spectroscopic Labels for Diffusometric Probing of Biopolymer Networks

We present the design, preparation, and characterization of two types of complex coacervate core micelles (C3Ms) with cross-linked cores and spectroscopic labels and demonstrate their use as diffusional probes to investigate the microstructure of percolating biopolymer networks. The first type consists of poly(allylamine hydrochloride) (PAH) and poly(ethylene oxide)-poly(methacrylic acid) (PEO-b-PMAA), labeled with ATTO 488 fluorescent dyes. We show that the size of these probes can be tuned by choosing the length of the PEO-PMAA chains. ATTO 488-labeled PEO113-PMAA15 micelles are very bright with 18 dye molecules incorporated into their cores. The second type is a (19)F-labeled micelle, for which we used PAH and a (19)F-labeled diblock copolymer tailor-made from poly(ethylene oxide)-poly(acrylic acid) (mPEO79-b-PAA14). These micelles contain approximately 4 wt % of (19)F and can be detected by (19)F NMR. The (19)F labels are placed at the end of a small spacer to allow for the necessary rotational mobility. We used these ATTO- and (19)F-labeled micelles to probe the microstructures of a transient gel (xanthan gum) and a cross-linked, heterogeneous gel (κ-carrageenan). For the transient gel, sensitive optical diffusometry methods, including fluorescence correlation spectroscopy, fluorescence recovery after photobleaching, and super-resolution single nanoparticle tracking, allowed us to measure the diffusion coefficient in networks with increasing density. From these measurements, we determined the diameters of the constituent xanthan fibers. In the heterogeneous κ-carrageenan gels, bimodal nanoparticle diffusion was observed, which is a signpost of microstructural heterogeneity of the network.

Fluorescence recovery after photobleaching in material and life sciences: putting theory into practice

Fluorescence recovery after photobleaching (FRAP) is a versatile tool for determining diffusion and interaction/binding properties in biological and material sciences. An understanding of the mechanisms controlling the diffusion requires a deep understanding of structure–interaction–diffusion relationships. In cell biology, for instance, this applies to the movement of proteins and lipids in the plasma membrane, cytoplasm and nucleus. In industrial applications related to pharmaceutics, foods, textiles, hygiene products and cosmetics, the diffusion of solutes and solvent molecules contributes strongly to the properties and functionality of the final product. All these systems are heterogeneous, and accurate quantification of the mass transport processes at the local level is therefore essential to the understanding of the properties of soft (bio)materials. FRAP is a commonly used fluorescence microscopy-based technique to determine local molecular transport at the micrometer scale. A brief high-intensity laser pulse is locally applied to the sample, causing substantial photobleaching of the fluorescent molecules within the illuminated area. This causes a local concentration gradient of fluorescent molecules, leading to diffusional influx of intact fluorophores from the local surroundings into the bleached area. Quantitative information on the molecular transport can be extracted from the time evolution of the fluorescence recovery in the bleached area using a suitable model. A multitude of FRAP models has been developed over the years, each based on specific assumptions. This makes it challenging for the non-specialist to decide which model is best suited for a particular application. Furthermore, there are many subtleties in performing accurate FRAP experiments. For these reasons, this review aims to provide an extensive tutorial covering the essential theoretical and practical aspects so as to enable accurate quantitative FRAP experiments for molecular transport measurements in soft (bio)materials.

Controlling drug delivery kinetics from mesoporous titania thin films by pore size and surface energy

The osseointegration capacity of bone-anchoring implants can be improved by the use of drugs that are administrated by an inbuilt drug delivery system. However, to attain superior control of drug delivery and to have the ability to administer drugs of varying size, including proteins, further material development of drug carriers is needed. Mesoporous materials have shown great potential in drug delivery applications to provide and maintain a drug concentration within the therapeutic window for the desired period of time. Moreover, drug delivery from coatings consisting of mesoporous titania has shown to be promising to improve healing of bone-anchoring implants. Here we report on how the delivery of an osteoporosis drug, alendronate, can be controlled by altering pore size and surface energy of mesoporous titania thin films. The pore size was varied from 3.4 nm to 7.2 nm by the use of different structure-directing templates and addition of a swelling agent. The surface energy was also altered by grafting dimethylsilane to the pore walls. The drug uptake and release profiles were monitored in situ using quartz crystal microbalance with dissipation (QCM-D) and it was shown that both pore size and surface energy had a profound effect on both the adsorption and release kinetics of alendronate. The QCM-D data provided evidence that the drug delivery from mesoporous titania films is controlled by a binding-diffusion mechanism. The yielded knowledge of release kinetics is crucial in order to improve the in vivo tissue response associated to therapeutic treatments.

Diffusion of macromolecules in self-assembled cellulose/hemicellulose hydrogels

Cellulose hydrogels are extensively applied in many biotechnological fields and are also used as models for plant cell walls. We synthesised model cellulosic hydrogels containing hemicelluloses, as a biomimetic of plant cell walls, in order to study the role of hemicelluloses on their mass transport properties. Microbial cellulose is able to self-assemble into composites when hemicelluloses, such as xyloglucan and arabinoxylan, are present in the incubation media, leading to hydrogels with different nano and microstructures. We investigated the diffusivities of a series of fluorescently labelled dextrans, of different molecular weight, and proteins, including a plant pectin methyl esterase (PME), using fluorescence recovery after photobleaching (FRAP). The presence of xyloglucan, known to be able to crosslink cellulose fibres, confirmed by scanning electron microscopy (SEM) and (13)C NMR, reduced mobility of macromolecules of molecular weight higher than 10 kDa, reflected in lower diffusion coefficients. Furthermore PME diffusion was reduced in composites containing xyloglucan, despite the lack of a particular binding motif in PME for this polysaccharide, suggesting possible non-specific interactions between PME and this hemicellulose. In contrast, hydrogels containing arabinoxylan coating cellulose fibres showed enhanced diffusivity of the molecules studied. The different diffusivities were related to the architectural features found in the composites as a function of polysaccharide composition. Our results show the effect of model hemicelluloses in the mass transport properties of cellulose networks in highly hydrated environments relevant to understanding the role of hemicelluloses in the permeability of plant cell walls and aiding design of plant based materials with tailored properties.

Probe diffusion in phase-separated bicontinuous biopolymer gels

Probe diffusion was determined in phase separated bicontinuous gels prepared by acid-induced gelation of the whey protein isolate-gellan gum system. The topological characterization of the phase-separated gel systems is achieved by confocal microscopy and the diffusion measurements are performed using pulsed field gradient (PFG) NMR and fluorescence recovery after photo-bleaching (FRAP). These two techniques gave complementary information about the mass transport at different time- and length scales, PFG NMR provided global diffusion rates in the gel systems, while FRAP enabled the measurements of diffusion in different phases of the phase-separated gels. The results revealed that the phase-separated gel with the largest characteristic wavelength had the fastest diffusion coefficient, while the gel with smaller microstructures had a slower probe diffusion rate. By using the diffusion data obtained by FRAP and the structural data from confocal microscopy, modelling through the lattice-Boltzmann framework was carried out to simulate the global diffusion and verify the validity of the experimental measurements. With this approach it was found that discrepancies between the two experimental techniques can be rationalized in terms of probe distribution between the different phases of the system. The combination of different techniques allowed the determination of diffusion in a phase-separated biopolymer gel and gave a clearer picture of this complex system. We also illustrate the difficulties that can arise if precautions are not taken to understand the system-probe interactions.