Diffusion Of Proteins Research Articles

Comparative study of SARS-CoV-2 infection in different cell types: Biophysical-computational approach to the role of potential receptors

Cellular susceptibility to SARS-CoV-2 infection in the respiratory tract has been associated with the ability of the virus to interact with potential receptors on the host membrane. We have modeled viral dynamics by simulating various cellular systems and artificial conditions, including macromolecular crowding, based on experimental and transcriptomic data to infer parameters associated with viral growth and predict cell susceptibility. We have accomplished this based on the type, number and level of expression of the angiotensin-converting enzyme 2 (ACE2), transmembrane serine 2 (TMPRSS2), basigin2 (CD147), FURIN protease, neuropilin 1 (NRP1) or other less studied candidate receptors such as heat shock protein A5 (HSPA5) and angiotensin II receptor type 2 (AGTR2). In parallel, we studied the effect of simulated artificial environments on the accessibility to said proposed receptors. In addition, viral kinetic behavior dependent on the degree of cellular susceptibility was predicted. The latter was observed to be more influenced by the type of proteins and expression level, than by the number of potential proteins associated with the SARS CoV-2 infection. We predict a greater theoretical propensity to susceptibility in cell lines such as NTERA-2, SCLC-21H, HepG2 and Vero6, and a lower theoretical propensity in lines such as CaLu3, RT4, HEK293, A549 and U-251MG. An important relationship was observed between expression levels, protein diffusivity, and thermodynamically favorable interactions between host proteins and the viral spike, suggesting potential sites of early infection other than the lungs. This research is expected to stimulate future quantitative experiments and promote systematic investigation of the effect of crowding presented here.

Time and space generalized diffusion equation on graph/networks

Normal and anomalous diffusion are ubiquitous in many complex systems [1]. Here, we define a time and space generalized diffusion equation (GDE), which uses fractional-time derivatives and transformed d-path Laplacian operators on graphs/networks. We find analytically the solution of this equation and prove that it covers the regimes of normal, sub- and superdiffusion as a function of the two parameters of the model. We extend the GDE to consider a system with temporal alternancy of normal and anomalous diffusion which can be observed for instance in the diffusion of proteins along a DNA chain. We perform computational experiments on a one-dimensional system emulating a linear DNA chain. It is shown that a subdiffusive-superdiffusive alternant regime allows the diffusive particle to explore more slowly small regions of the chain with a faster global exploration, than a subdiffusive-subdiffusive regime. Therefore, an alternancy of sliding (subdiffusive) with hopping and intersegmental transfer (superdiffusive) mechanisms show important advances for protein-DNA interactions.

Phenolic Acids in Red Wine Interact Directly with the Protein Fraction of Saliva

Wine-evoked astringency is usually associated with interactions between proanthocyanidins and salivary proteins. Limited information exists about interaction of other wine phenolic compounds with saliva. This study assessed the ability of single phenolic acids and mixes of phenolic acids to interact with salivary protein. Protein diffusion on cellulose membranes and protein precipitation assays were conducted. Single phenolic acids (PA), excepting tannic acid (T), showed concentrationdependent reduction of the area of diffusion of the diffusible salivary protein. PAs were weak precipitants of the salivary protein but strong inducers of soluble PA-salivary protein complexes. T precipitated non-diffusible salivary proteins without effect on the diffusible protein. Compared to single PAs, mixes of gallic acid (G) and PAs showed similar effects regarding inhibition of protein diffusion and formation of soluble PA-protein complexes. Contrarily, T interfered with both effects of PAs. It is concluded that PAs interact directly and diversely with the salivary protein and thence may cause astringency

Multiscale relaxation dynamics and diffusion of myelin basic protein in solution studied by quasielastic neutron scattering.

We report an analysis of high-resolution quasielastic neutron scattering spectra from Myelin Basic Protein (MBP) in solution, comparing the spectra at three different temperatures (283, 303, and 323K) for a pure D2O buffer and a mixture of D2O buffer with 30% of deuterated trifluoroethanol (TFE). Accompanying experiments with dynamic light scattering and Circular Dichroism (CD) spectroscopy have been performed to obtain, respectively, the global diffusion constant and the secondary structure content of the molecule for both buffers as a function of temperature. Modeling the decay of the neutron intermediate scattering function by the Mittag-Leffler relaxation function, ϕ(t) = Eα(-(t/τ)α) (0 < α < 1), we find that trifluoroethanol slows down the relaxation dynamics of the protein at 283K and leads to a broader relaxation rate spectrum. This effect vanishes with increasing temperature, and at 323K, its relaxation dynamics is identical in both solvents. These results are coherent with the data from dynamic light scattering, which show that the hydrodynamic radius of MBP in TFE-enriched solutions does not depend on temperature and is only slightly smaller compared to the pure D2O buffer, except for 283K, where it is much reduced. In accordance with these observations, the CD spectra reveal that TFE induces essentially a partial transition from β-strands to α-helices, but only a weak increase in the total secondary structure content, leaving about 50% of the protein unfolded. The results show that MBP is for all temperatures and in both buffers an intrinsically disordered protein and that TFE essentially induces a reduction in its hydrodynamic radius and its relaxation dynamics at low temperatures.

Microstructure and biomolecules mobility of human milk fat globules by fluorescence recovery after photobleaching with confocal scanning laser microscope

This work demonstrates the use of fluorescence recovery after photobleaching (FRAP) for direct measurement of the microstructure and biomolecules mobility of human milk fat globules (HMFGs). In particular, five fluorescent probes (three types), Nile Red, Rh-DOPE, NBD-PC, NBD-SM, and Nile Blue, were evaluated in a Confocal scanning laser microscope combined with FRAP for the detection of the molecular diffusion of neutral lipids, polar lipids and membrane proteins in HMFGs. Mobile fraction (Mf), half-life recovery time (t1/2) and diffusion coefficient (K) were calculated from the FRAP recovery curve of five fluorescent molecules. The Mf of fluorescent probes labeled neutral lipids, polar lipids, membrane proteins, phosphatidylcholine, sphingomyelin, and on HMFGs were 63%, 18%, 45%, 28% and 5%, respectively. The recovery times of fluorescent molecules labeled with membrane biomolecules were longer as the size of the milk fat globules decreased and the photobleaching area increased. This method was applied to the HMFG membrane cytoplasmic remnants (CR) region showing a similar trend and much higher fluorescence intensity to the membrane region, which suggests that CR might contain multiple layers of membrane lipids.

Interfacial rheology of sodium caseinate/high acyl gellan gum complexes: Stabilizing oil-in-water emulsions

In this work, the effects of pH and high acyl gellan gum concentration on the adsorption kinetics and interfacial dilatational rheology of sodium caseinate/high acyl gellan gum (CN/HG) complexes were investigated using a pendant drop tensiometer. In addition, stability related properties including interfacial protein concentration, droplet charge, size, microstructure and creaming index of emulsions were studied at different HG concentration (0–0.2 wt%) and pH values (4, 5.5 and 7). The results showed that HG adsorbed onto the CN mainly through electrostatic interactions which could lead to increase the interfacial pressure (π), rates of protein diffusion (kdiff), and molecular penetration (kp). The CN/HG complexes formed thick adsorption layers around the oil droplets which significantly increased the surface dilatational modulus with the increasing HG concentration. The CN/HG complexes appeared to form more elastic interfacial films after a long-term adsorption time compared with CN alone, which could reduce the droplet coalescence and thus prevented the growth of emulsion droplets. All four phosphorylated proteins of CN (αs1-, αs2-, β-, and κ-casein) were adsorbed at the oil-water (O/W) interface as confirmed by sodium dodecyl sulphate polyacrylamide gel electrophoresis (SDS-PAGE), and surface protein coverage increased progressively with increasing HG concentration at pH 5.5, but decreased at pH 7. The CN/HG stabilized emulsions at pH 5.5 revealed the higher net charges and smaller z-average diameters than those at pH 4 and pH 7. This study provides valuable information on the use of CN/HG complexes to improve the stability and texture of food emulsions.

A Protocol for Studying Transcription Factor Dynamics Using Fast Single-Particle Tracking and Spot-On Model-Based Analysis.

Single-particle tracking (SPT) makes it possible to directly observe single protein diffusion dynamics in living cells over time. Thus, SPT has emerged as a powerful method to quantify the dynamics of nuclear proteins such as transcription factors (TFs). Here, we provide a protocol for conducting and analyzing SPT experiments with a focus on fast tracking ("fastSPT") of TFs in mammalian cells. First, we explore how to engineer and prepare cells for SPT experiments. Next, we examine how to optimize SPT experiments by imaging at low densities to minimize tracking errors and by using stroboscopic excitation to minimize motion-blur. Next, we discuss how to convert raw SPT data into single-particle trajectories. Finally, we illustrate how to analyze these trajectories using the kinetic modeling package Spot-On. We discuss how to use Spot-On to fit histograms of displacements and extract useful information such as the fraction of TFs that are bound and freely diffusing, and their associated diffusion coefficients.

Investigating protein diffusivities in diluted hyaluronic acid solutions using dynamic light scattering.

This study aimed to investigate the diffusivities of lysozyme (LYS), ovalbumin (OVA), and hyaluronic acid (HA) in buffered solvents using dynamic light scattering (DLS). For protein/solvent and HA/solvent binary systems, the diffusion coefficients of protein or HA were obtained from autocorrelation function (ACF) curve fitting. Whereas, for protein/HA/solvent ternary systems, the two eigenvalues of the mutual diffusion coefficient matrix were obtained from ACF curve fitting. The results of binary systems showed that at low ionic strength, the diffusion coefficients of protein and HA increased linearly with concentration; at high ionic strength, the diffusion coefficients of OVA and LYS were independent on protein concentration; for HA, the positive linear relationship between diffusion coefficient and concentration existed at high and low ionic strengths, but the slope at high ionic strength was smaller compared to that at low ionic strength. For OVA/HA/solvent ternary systems, the sum of two eigenvalues (D1DLS + D2DLS) was slightly smaller compared to (DOVA + DHA), where DOVA and DHA were the diffusion coefficients in their binary systems. On the contrary, for LYS/HA/solvent ternary systems, (D1DLS + D2DLS) were significantly smaller than (DLYS + DHA) and the diffusion coefficients in binary and ternary systems exhibited an opposite trend with respect to ionic strength change. The DLS and MD simulation results indicated strong attractive intermolecular interaction existed between LYS and HA molecules, especially at low ionic strength. By using DLS, it was possible to characterize the diffusion coefficients of diluted protein/HA binary and ternary systems.

Potential utilization of glycerol as crosslinker in starch films for application in Regenerative Dentistry

Periodontal disease results in damage to dental insertion apparatus. Regenerative procedures are proposed to replace lost structures in the context of guided tissue regeneration (GTR), guided bone regeneration (GBR) techniques and frequently associate bone substitutes with physical barriers aiming at greater longevity and improvement of aesthetic pattern. This study evaluates the possibility of using glycerol as a starch films modifying agent, acting as a cross-linking agent, without compromising its plasticizing effect. Biodegradable cassava starch films were prepared incorporating glycerol at concentrations of 0, 15, 20, 30 and 40% aiming application at dental regenerative procedures. The characterization of films by microscopy (SEM), thermal analysis (DSC), spectroscopic (UV / Vis., FTIR, XRD), mechanical (Traction), and analysis of protein swelling, degradation and diffusion and physiological temperature) showed that the incorporation of glycerol in up to 20% attributed to the films a plasticizer character and in higher concentrations, conferred a greater interaction of glycerol (crosslinking) with the starch chains and a degradation time that allows the physical barrier in RTG and ROG. The films presented mechanical resistance, malleability and permissiveness to protein diffusion in the in vitro assays, which meet the current attributes that guide the use of these resources in biomaterials.

Weak correlation between fluctuations in protein diffusion inside bacteria

A weak correlation between the diffusion-exponent fluctuations and the temperature fluctuations is discussed based on recent experimental observations for protein diffusion inside bacteria. Its existence is shown to be essential for describing the statistical properties of the fluctuations. It is also quantified how largely the fluctuations are modulated by the weak correlation.

A deep learning-based approach to model anomalous diffusion of membrane proteins: the case of the nicotinic acetylcholine receptor.

We present a concatenated deep-learning multiple neural network system for the analysis of single-molecule trajectories. We apply this machine learning-based analysis to characterize the translational diffusion of the nicotinic acetylcholine receptor at the plasma membrane, experimentally interrogated using superresolution optical microscopy. The receptor protein displays a heterogeneous diffusion behavior that goes beyond the ensemble level, with individual trajectories exhibiting more than one diffusive state, requiring the optimization of the neural networks through a hyperparameter analysis for different numbers of steps and durations, especially for short trajectories (<50 steps) where the accuracy of the models is most sensitive to localization errors. We next use the statistical models to test for Brownian, continuous-time random walk and fractional Brownian motion, and introduce and implement an additional, two-state model combining Brownian walks and obstructed diffusion mechanisms, enabling us to partition the two-state trajectories into segments, each of which is independently subjected to multiple analysis. The concatenated multi-network system evaluates and selects those physical models that most accurately describe the receptor's translational diffusion. We show that the two-state Brownian-obstructed diffusion model can account for the experimentally observed anomalous diffusion (mostly subdiffusive) of the population and the heterogeneous single-molecule behavior, accurately describing the majority (72.5 to 88.7% for α-bungarotoxin-labeled receptor and between 73.5 and 90.3% for antibody-labeled molecules) of the experimentally observed trajectories, with only ~15% of the trajectories fitting to the fractional Brownian motion model.

Subdiffusive-Brownian crossover in membrane proteins: a generalized Langevin equation-based approach

In this work, we propose a generalized Langevin equation-based model to describe the lateral diffusion of a protein in a lipid bilayer. The memory kernel is represented in terms of a viscous (instantaneous) and an elastic (noninstantaneous) component modeled through a Dirac δ function and a three-parameter Mittag-Leffler type function, respectively. By imposing a specific relationship between the parameters of the three-parameter Mittag-Leffler function, the different dynamical regimes—namely ballistic, subdiffusive, and Brownian, as well as the crossover from one regime to another—are retrieved. Within this approach, the transition time from the ballistic to the subdiffusive regime and the spectrum of relaxation times underlying the transition from the subdiffusive to the Brownian regime are given. The reliability of the model is tested by comparing the mean-square displacement derived in the framework of this model and the mean-square displacement of a protein diffusing in a membrane calculated through molecular dynamics simulations.

Preparation of camellia oil pickering emulsion stabilized by glycated whey protein isolate and chitooligosaccharide: Effect on interfacial behavior and emulsion stability

Camellia oil has a high content of unsaturated fatty acids and active ingredients, but it is unstable during production, storage, and application. Camellia oil Pickering emulsions were prepared by utilizing electrostatic complex of glycosylated whey protein isolate (gWPI) and chitooligosaccharide (COS) as the emulsifier can be used as an effective carrier system. The effects of pH level and biomass concentration on polymer interaction and emulsion stability were systematically studied. The emulsion's interfacial properties and rheological behavior were studied by using an interfacial tensiometer and a rheometer, respectively. The mass ratio of 1:1 (1%) and pH 5.0 were the optimal conditions for protein–COS interactions. Compared with WPI-COS, the content of absorbed protein in the O/W interface of gWPI-COS increased, and the diffusion (kdiff) and rearrangement (kR) rates of proteins in the O/W interface of the gWPI/gWPI-COS significantly improved according to the rheokinetics of protein adsorption at the oil/water interface. Moreover, a higher viscoelasticity in the WPI/gWPI-COS stabilized the emulsion system. Subsequent studies on the stability of the emulsion also showed that the Pickering emulsions stabilized by gWPI–COS had better thermal stability, oxidative stability, resistance to oscillatory shear than gWPI/WPI or WPI-COS emulsion.

NOBIAS: Analyzing anomalous diffusion in single-molecule tracks with nonparametric Bayesian inference.

Single particle tracking (SPT) enables the investigation of biomolecular dynamics at a high temporal and spatial resolution in living cells, and the analysis of these SPT datasets can reveal biochemical interactions and mechanisms. Still, how to make the best use of these tracking data for a broad set of experimental conditions remains an analysis challenge in the field. Here, we develop a new SPT analysis framework: NOBIAS (NOnparametric Bayesian Inference for Anomalous Diffusion in Single-Molecule Tracking), which applies nonparametric Bayesian statistics and deep learning approaches to thoroughly analyze SPT datasets. In particular, NOBIAS handles complicated live-cell SPT data for which: the number of diffusive states is unknown, mixtures of different diffusive populations may exist within single trajectories, symmetry cannot be assumed between the x and y directions, and anomalous diffusion is possible. NOBIAS provides the number of diffusive states without manual supervision, it quantifies the dynamics and relative populations of each diffusive state, it provides the transition probabilities between states, and it assesses the anomalous diffusion behavior for each state. We validate the performance of NOBIAS with simulated datasets and apply it to the diffusion of single outer-membrane proteins in Bacteroides thetaiotaomicron. Furthermore, we compare NOBIAS with other SPT analysis methods and find that, in addition to these advantages, NOBIAS is robust and has high computational efficiency and is particularly advantageous due to its ability to treat experimental trajectories with asymmetry and anomalous diffusion.

Rapid ensemble measurement of protein diffusion and probe blinking dynamics in cells

We present a fluorescence fluctuation image correlation analysis method that can rapidly and simultaneously measure the diffusion coefficient, photoblinking rates, and fraction of diffusing particles of fluorescent molecules in cells. Unlike other image correlation techniques, we demonstrated that our method could be applied irrespective of a nonuniformly distributed, immobile blinking fluorophore population. This allows us to measure blinking and transport dynamics in complex cell morphologies, a benefit for a range of super-resolution fluorescence imaging approaches that rely on probe emission blinking. Furthermore, we showed that our technique could be applied without directly accounting for photobleaching. We successfully employed our technique on several simulations with realistic EMCCD noise and photobleaching models, as well as on Dronpa-C12-labeled β-actin in living NIH/3T3 and HeLa cells. We found that the diffusion coefficients measured using our method were consistent with previous literature values. We further found that photoblinking rates measured in the live HeLa cells varied as expected with changing excitation power.

Utility of TPP-manufactured biophysical restrictions to probe multiscale cellular dynamics

Biophysical restrictions regulate protein diffusion, nucleus deformation, and cell migration, which are all universal and important processes for cells to perform their biological functions. However, current technologies addressing these multiscale questions are extremely limited. Herein, through two-photon polymerization (TPP), we present the precise, low-cost, and multiscale microstructures (micro-fences) as a versatile investigating platform. With nanometer-scale printing resolution and multiscale scanning capacity, TPP is capable of generating micro-fences with sizes of 0.5–1000 μm. These micro-fences are utilized as biophysical restrictions to determine the fluidity of supported lipid bilayers (SLB), to investigate the restricted diffusion of Src family kinase protein Lck on SLB, and also to reveal the mechanical bending of cell nucleus and T cell climbing ability. Taken together, the proposed versatile and low-cost micro-fences have great potential in probing the restricted dynamics of molecules, organelles, and cells to understand the basics of physical biology.Graphic abstract

Toward High Spatially Resolved Proteomics Using Expansion Microscopy.

Expansion microscopy (EM) is an emerging approach for morphological examination of biological specimens at nanoscale resolution using conventional optical microscopy. To achieve physical separation of cell structures, tissues are embedded in a swellable polymer and expanded several fold in an isotropic manner. This work shows the development and optimization of physical tissue expansion as a new method for spatially resolved large-scale proteomics. Herein we established a novel method to enlarge the tissue section to be compatible with manual microdissection on regions of interest and MS-based proteomic analysis. A major issue in expansion microscopy is the loss of protein information during the mechanical homogenization phase due to the use of proteinase K. For isotropic expansion, different homogenization agents were investigated, both to maximize protein identification and to minimize protein diffusion. Best results were obtained with SDS for homogenization. Using our modified protocol, we were able to enlarge a tissue section more than 3-fold and identified up to 655 proteins from 1 mm in size after expansion, equivalent to 330 μm in their real size corresponding thus to an average of 260 cells. This approach can be performed easily without any expensive sampling instrument. We demonstrated the compatibility of sample preparation for expansion microscopy and proteomic study in a spatial context.

The Role of pH and Ionic Strength in the Attraction-Repulsion Balance of Fibrinogen Interactions.

Fibrinogen (Fg) self-assembly is sensitive to the physicochemical properties of an environment like pH and ionic strength. These parameters tune the direction and strength of noncovalent physical driving forces determining protein intermolecular interactions. The attraction-repulsion balance in intermolecular interactions of the multidomain protein Fg at pH values 3.5, 7.4, and 9.5 and varying ionic strengths of the water medium has been analyzed by the complex diffusive approach, proposed by us previously. The concentration dependence of protein collective diffusion was analyzed within the phenomenological approach, based on the frictional formalism of nonequilibrium thermodynamics proposed by H. Vink. The analysis of protein diffusion data has shown the fundamental difference in the physical nature and direction of interaction forces between protein molecules at different conditions. The paired interaction potential of protein molecules was characterized in terms of second virial coefficients and Hamaker constants within the Deryaguin-Landau-Verwey-Overbeek theory and the "porous" colloid particle model. Our results indicated the maximum Hamaker constant and dominance of the van der Waals attraction between Fg molecules at pH 7.4. The increase in pH up to 9.5 results in the zero values of the second virial coefficient and Hamaker constant, corresponding to the full reciprocal compensation for electrostatic repulsion and van der Waals attraction. In the acidic medium (pH 3.5), the strong electrostatic repulsion substantially exceeds the van der Waals attraction. A high ionic strength is characterized by a significant decrease of all intermolecular interactions, which is expressed in almost zero values of virial coefficients and the Hamaker constant. Thus, it is experimentally shown that the physiological conditions of the Fg environment (pH 7.4 and slight ionic strength) provide a high probability for peak physical attraction between fibrinogen molecules, which is used in nature to facilitate blood clotting.

Fast Leaps between Millisecond Confinements Govern Ase1 Diffusion along Microtubules

Diffusion is the most fundamental mode of protein translocation within cells. Confined diffusion of proteins along the electrostatic potential constituted by the surface of microtubules, although modeled meticulously in molecular dynamics simulations, has not been experimentally observed in real-time. Here, interferometric scattering microscopy is used to directly visualize the movement of the microtubule-associated protein Ase1 along the microtubule surface at nanometer and microsecond resolution. Millisecond confinements of Ase1 and fast leaps between these positions of dwelling preferentially occurring along the microtubule protofilaments are resolved, revealing Ase1's mode of diffusive translocation along the microtubule's periodic surface. The derived interaction potential closely matches the tubulin-dimer periodicity and the distribution of the electrostatic potential on the microtubule lattice. It is anticipated that mapping the interaction landscapes for different proteins on microtubules, finding plausible energetic barriers of different positioning and heights, can provide valuable insights into regulating the dynamics of essential cytoskeletal processes, such as intracellular cargo trafficking, cell division, and morphogenesis, all of which rely on diffusive translocation of proteins along microtubules.

Impact of DNA sequences on DNA ‘opening’ by the Rad4/XPC nucleotide excision repair complex

Rad4/XPC recognizes diverse DNA lesions to initiate nucleotide excision repair (NER). However, NER propensities among lesions vary widely and repair-resistant lesions are persistent and thus highly mutagenic. Rad4 recognizes repair-proficient lesions by unwinding (‘opening’) the damaged DNA site. Such ‘opening’ is also observed on a normal DNA sequence containing consecutive C/G’s (CCC/GGG) when tethered to Rad4 to prevent protein diffusion. However, it was unknown if such tethering-facilitated DNA ‘opening’ could occur on any DNA or if certain structures/sequences would resist being ‘opened’. Here, we report that DNA containing alternating C/G’s (CGC/GCG) failed to be opened even when tethered; instead, Rad4 bound in a 180°-reversed manner, capping the DNA end. Fluorescence lifetime studies of DNA conformations in solution showed that CCC/GGG exhibits local pre-melting that is absent in CGC/GCG. In MD simulations, CGC/GCG failed to engage Rad4 to promote ‘opening’ contrary to CCC/GGG. Altogether, our study illustrates how local sequences can impact DNA recognition by Rad4/XPC and how certain DNA sites resist being ‘opened’ even with Rad4 held at that site indefinitely. The contrast between CCC/GGG and CGC/GCG sequences in Rad4-DNA recognition may help decipher a lesion’s mutagenicity in various genomic sequence contexts to explain lesion-determined mutational hot and cold spots.