Mean squared displacement from fluorescence correlation spectroscopy

Polymer Microarray with Tailored Morphologies through Condensed Droplet Polymerization for High-Resolution Optical Imaging Applications

Nature-inspired functional surfaces with micro- and nanoscale features have garnered interest for potential applications in optics, imaging, and sensing. Traditional fabrication methods, such as lithography and self-assembly, face limitations in versatility, scalability, and morphology control. This study introduces an innovative technology, condensed droplet polymerization (CDP), for fabricating polymeric micro- and nano-dome arrays (PDAs) with readily tunable geometric properties-a challenging feat for conventional methods. The CDP process leverages free-radical polymerization in condensed monomer droplets, allowing rapid production of PDAs with targeted sizes, radii of curvature, and surface densities by manipulating a key synthesis parameter: the temperature of a filament array that activates initiators. This work systematically unravels its effects on polymerization kinetics, viscoelastic properties of the polymerizing droplets, and geometric characteristics of the PDAs. Utilizing in situ digital microscope, this work reveals the morphological evolution of the PDAs during the process. The resulting PDAs exhibit distinct optical properties, including magnification that enables high-resolution imaging beyond the diffraction limit of conventional microscopes. This work demonstrates the ability to magnify and focus light, enhancing imaging of subwavelength structures and biological specimens. This work advances the understanding of polymerization mechanisms in nano-sized reactors (i.e., droplets) and paves the way for developing compact optical imaging and sensing technologies.

Enzymatic Reaction Enhanced Diffusion Accelerates Cargo Transport through Micro/Nano-Channels

Energy conversion and transfer of enzyme-catalyzed reactions at molecular level are an interesting and challenging scientific topic that helps understanding biological processes in nature. In this study, it is demonstrated that enzyme-catalyzed reactions can enhance diffusion of surrounding molecules and thus accelerate cargo transport within 1D micro/nanochannels. Specifically, urease is immobilized on the inner walls of silica micro/nano-tubes to construct bio-catalytically active micro/nanochannels. The catalytic reaction inside the channels drives a variety of cargoes, including small dye molecules, polymers, and rigid nanoparticles (e.g., quantum dots, QDs), to pass through these micro/nanochannels much faster than they will by free diffusion. The enhanced diffusion of molecular species inside the channels is validated by direct observation of the Brownian motion of tracer particles, and further confirmed by significantly enhanced Raman intensity of reporter molecules. Finite element and Brownian dynamics simulations provide a theoretical understanding of these experimental observations. Furthermore, the effect of the channels' size on the diffusion enhancement is examined. The acceleration effect of the cargo transport through these enzymatically active micro/nanochannels can be turned on or off via chemical activators or inhibitors. This study provides valuable insights on the design of biomimetic channels capable of controlled and efficient transmembrane transport.

Colloidal Shear-Thickening Fluids Using Variable Functional Star-Shaped Particles: A Molecular Dynamics Study

Complex colloidal fluids, depending on constituent shapes and packing fractions, may have a wide range of shear-thinning and/or shear-thickening behaviors. An interesting way to transition between different types of such behavior is by infusing complex functional particles that can be manufactured using modern techniques such as 3D printing. In this paper, we perform 2D molecular dynamics simulations of such fluids with infused star-shaped functional particles, with a variable leg length and number of legs, as they are infused in a non-interacting fluid. We vary the packing fraction (ϕ) of the system, and for each different system, we apply shear at various strain rates, turning the fluid into a shear-thickened fluid and then, in jammed state, rising the apparent viscosity of the fluid and incipient stresses. We demonstrate the dependence of viscosity on the functional particles’ packing fraction and we show the role of shape and design dependence of the functional particles towards the transition to a shear-thickening fluid.

Ammonia Sensing Performance of Polyaniline-Coated Polyamide 6 Nanofibers

To understand the properties of polyaniline (PANI), aim gas, and the interaction between them in PANI-based gas sensors and help us to design sensors with better properties, direct calculations with molecular dynamics (MD) simulations were done in this work. Polyamide 6/polyaniline (PA6/PANI) nanofiber ammonia gas sensors were studied as an example here, and the structural, morphological, and ammonia sensing properties (to 50-250 ppm ammonia) of PA6/PANI nanofibers were tested and evaluated by scanning electron microscopy, Fourier transform infrared spectroscopy, and a homemade test system. The PA6/PANI nanofibers were prepared by in situ polymerization of aniline with electrospun PA6 nanofibers as templates and hydrochloric acid (HCl) as a doping agent for PANI, and the sensors show rapid response, ideal selectivity, and acceptable repeatability. Then, complementary molecular dynamics simulations were performed to understand how ammonia molecules interact with HCl-doped PANI chains, thus providing insights into the molecular-level details of the ammonia sensing performances of this system. Results of the radial distribution functions and mean square displacement analysis of the MD simulations were consistent with the dedoping mechanism of the PANI chains.

Direct Single Molecule Imaging of Enhanced Enzyme Diffusion

Recent experimental results have shown that enzymes can diffuse faster when they are in the presence of their reactants (substrate). This faster diffusion has been termed enhanced diffusion. Fluorescence correlation spectroscopy (FCS), which has been employed as the only method to make these measurements, relies on analyzing the fluctuations in fluorescence intensity to measure the diffusion coefficient of particles. Recently, artifacts in FCS measurements due to its sensitivity to environmental conditions have been evaluated, calling prior enhanced diffusion results into question. It behooves us to adopt complementary and direct methods to measure the mobility of enzymes. Herein, we use a technique of direct single molecule imaging to observe the diffusion of individual enzymes in solution. This technique is less sensitive to intensity fluctuations and deduces the diffusion coefficient directly based on the trajectory of the enzyme. Our measurements recapitulate that enzyme diffusion is enhanced in the presence of its substrate and find that the relative increase in diffusion of a single enzyme is even higher than those previously reported using FCS. We also use this complementary method to test if the total enzyme concentration affects the relative increase in diffusion and if the enzyme oligomerization state changes during its catalytic turnover. We find that the diffusion increase is independent of the total concentration of enzymes and the presence of substrate does not change the oligomerization state of enzymes.

Anomalous Diffusion in Inverted Variable-Lengthscale Fluorescence Correlation Spectroscopy

Using fluorescence correlation spectroscopy (FCS) to distinguish between different types of diffusion processes is often a perilous undertaking because the analysis of the resulting autocorrelation data is model dependant. Two recently introduced strategies, however, can help move toward a model-independent interpretation of FCS experiments: 1) the obtention of correlation data at different length scales and 2) their inversion to retrieve the mean-squared displacement associated with the process under study. We use computer simulations to examine the signature of several biologically relevant diffusion processes (simple diffusion, continuous-time random walk, caged diffusion, obstructed diffusion, two-state diffusion, and diffusing diffusivity) in variable-length-scale FCS. We show that, when used in concert, length-scale variation and data inversion permit us to identify non-Gaussian processes and, regardless of Gaussianity, to retrieve their mean-squared displacement over several orders of magnitude in time. This makes unbiased discrimination between different classes of diffusion models possible.

Fluorescence Correlation Spectroscopy with Photobleaching Correction in Slowly Diffusing Systems

Fluorescence correlation spectroscopy (FCS) is a powerful tool to quantitatively study the diffusion of fluorescently labeled molecules. It allows in principle important questions of macromolecular transport and supramolecular aggregation in living cells to be addressed. However, the crowded environment inside the cells slows diffusion and limits the reservoir of labeled molecules, causing artifacts that arise especially from photobleaching and limit the utility of FCS in these applications. We present a method to compute the time correlation function from weighted photon arrival times, which compensates computationally during the data analysis for the effect of photobleaching. We demonstrate the performance of this method using numerical simulations and experimental data from model solutions. Using this technique, we obtain correlation functions in which the effect of photobleaching has been removed and in turn recover quantitatively accurate mean-square displacements of the fluorophores, especially when deviations from an ideal Gaussian excitation volume are accounted for by using a reference calibration correlation function. This allows quantitative FCS studies of transport processes in challenging environments with substantial photobleaching like in living cells in the future.

Spatiotemporal mapping of diffusion dynamics and organization in plasma membranes

Imaging fluorescence correlation spectroscopy (FCS) and the related FCS diffusion law have been applied in recent years to investigate the diffusion modes of lipids and proteins in membranes. These efforts have provided new insights into the membrane structure below the optical diffraction limit, new information on the existence of lipid domains, and on the influence of the cytoskeleton on membrane dynamics. However, there has been no systematic study to evaluate how domain size, domain density, and the probe partition coefficient affect the resulting imaging FCS diffusion law parameters. Here, we characterize the effects of these factors on the FCS diffusion law through simulations and experiments on lipid bilayers and live cells. By segmenting images into smaller 7  ×  7 pixel areas, we can evaluate the FCS diffusion law on areas smaller than 2 µm and thus provide detailed maps of information on the membrane structure and heterogeneity at this length scale. We support and extend this analysis by deriving a mathematical expression to calculate the mean squared displacement (MSD_ACF) from the autocorrelation function of imaging FCS, and demonstrate that the MSD_ACF plots depend on the existence of nanoscopic domains. Based on the results, we derive limits for the detection of domains depending on their size, density, and relative viscosity in comparison to the surroundings. Finally, we apply these measurements to bilayers and live cells using imaging total internal reflection FCS and single plane illumination microscopy FCS.