Mean square displacement analysis of single-particle trajectories with localization error: Brownian motion in an isotropic medium

Bending the rules: Molecular dynamics of hydroxylated sphingolipid membranes with 2-hydroxyoleic acid

In this study, we introduce a novel method for quantifying the mechanical properties of lipid membranes-bending rigidity (κ), Gaussian rigidity (κG), and surface tension (γ) using molecular dynamics (MD) simulations. Our approach is applied to membranes incorporating 2-hydroxyoleic acid (2OHOA), a synthetic oleic acid derivative currently under clinical investigation for its anticancer properties. 2OHOA modifies the plasma membrane composition in cancer cells and activates sphingomyelin synthase 1 (SMS1), an enzyme critical for maintaining sphingolipid levels in the plasma membrane. This research focuses on how the integration of 2OHOA into ceramide and sphingomyelin alters the mechanical and biophysical properties of these membranes. We employed MD simulations to analyze structural parameters such as lipid area, volume, and bilayer thickness. Additionally, by constructing a system of linear equations based on the Helfrich-Seifert model, we estimated the mechanical properties of hydroxylated versus non-hydroxylated membranes. Our findings reveal significant membrane rigidity and curvature changes due to hydroxylation, affecting membrane-protein interactions and cellular processes like vesiculation. This work provides critical insights into the molecular mechanisms by which hydroxylation influences membrane elasticity, with implications for both fundamental biophysics and therapeutic applications in cancer treatment.

Mechanical properties of Staphylococcus aureus and Pseudomonas aeruginosa dual-species biofilms grown in chronic wound-based models

Wound infections become chronic due to biofilm formation by pathogenic bacteria; two such pathogens are Staphylococcus aureus and Pseudomonas aeruginosa. These bacteria are known to form polymicrobial biofilms in wounds, which exhibit increased colonization rates, enhanced chronicity, and greater resistance to treatment. Previously, the impacts of a wound bed environment on the mechanical properties of P. aeruginosa biofilms have been explored, and in this work the role of a wound bed environment in the viscoelasticity and microstructure of polymicrobial biofilms is characterized. We hypothesize that common wound bed proteins mediate interactions between S. aureus and P. aeruginosa to enable the formation of more elastic and stiff biofilms. Growth media with varying protein content as well as additional collagen, a protein associated with a wound extracellular matrix, were utilized to test our hypothesis. Microrheology indicates that both P. aeruginosa and S. aureus form relatively stiffer single-species biofilms in a wound environment with collagen. S. aureus produced stiffer biofilms in the presence of collagen, regardless of other wound proteins, likely due to its interactions with collagen. When both species were grown together in wound-like media, synergistic effects led to stiffer dual-species biofilms compared to their single-species forms. Under all growth conditions, collagen significantly contributed to stiffening P. aeruginosa/S. aureus dual-species biofilms, suggesting that it mediates complex interspecies interactions. High-resolution imaging and analysis revealed that collagen also influenced the microstructures of P. aeruginosa/S. aureus dual-species biofilms. In media containing wound proteins and collagen, S. aureus clusters were larger and exhibited more complex shapes. These results indicate that the wound bed environment not only provides improved antibacterial resistance due to cooperative interactions, but also improved mechanical protection, which impact common treatment methods like debridement.

Colloidal transport in periodic potentials: the role of modulated-crowding

The transport properties of colloids in external potentials are often studied at low concentrations to avoid particle-particle interactions. However, the impact of concentration on colloidal dynamics under external potentials has received limited attention. We examine the effect of concentration on the diffusivity of a quasi-2D colloidal dispersion subjected to a light-induced sinusoidal potential (interference fringes). By measuring particle diffusivity perpendicular to the fringes at various concentrations and laser powers, we find how the particle transport is governed by concentration and the structural organization induced by the external potential. Specifically, we introduce the concept of modulated-crowding for this physical scenario and characterize its influence on the long-time self-diffusion coefficient. These findings are confirmed using Brownian dynamics simulations.

Suppressing parasitic flow in membraneless diffusion-based microfluidic gradient generators

Diffusion-based microfluidic gradient generators (DMGGs) are essential for various in vitro studies due to their ability to provide a convection-free concentration gradient. However, these systems, often referred to as membrane-based DMGGs, exhibit delayed gradient formation due to the incorporated flow-resistant membrane. This limitation substantially hinders their application in dynamic and time-sensitive studies. Here, we accelerate the gradient response in DMGGs by removing the membrane and implementing new geometrical configurations to compensate for the membrane's role in suppressing parasitic flows. We introduce these novel configurations into two microfluidic designs: the H-junction and the Y-junction. In the H-junction design, parasitic flow is redirected through a bypass channel following the gradient region. The Y-junction design features a shared discharge channel that allows converging discharge flow streams, preventing the buildup of parasitic pressure downstream of the gradient region. Using hydraulic circuit analysis and fluid dynamics simulations, we demonstrate the effectiveness of the H-junction and Y-junction designs in suppressing parasitic pressure flows. These computational results, supported by experimental data from particle image velocimetry, confirm the capability of our designs to generate a highly stable, accurate, and convection-free gradient with rapid formation. These advantages make the H-junction and Y-junction designs ideal experimental platforms for a wide range of in vitro studies, including drug testing, cell chemotaxis, and stem cell differentiation.

Subcellular dynamics in unicellular parasites

Bioimaging has made tremendous advances in this century. Innovations in high- and super-resolution microscopy are well established, and live-cell imaging is extensively used to gain an overview of dynamic processes. But the combination of high spatial and temporal resolution necessary to capture intracellular dynamics is rarely achieved. Further, efficient software pipelines - that can handle the recorded data and allow comprehensive analyses - are being developed but lag behind other technical innovations in applicability for broad groups of researchers. Especially in parasites, which offer great potential for studying subcellular dynamics, the possibilities have only begun to be probed. In all cases, the complete description of dynamic molecular movement in 3D space remains a challenging necessity.

Deep eutectic solvent pretreatment of oil palm biomass: Promoted lignin pyrolysis and enzymatic digestibility of solid residues

Herein, choline chloride/oxalic acid (ChCl/OA) and choline chloride/oxalic acid/ethylene glycol (ChCl/OA/EG) pretreatments of oil palm empty fruit bunches (EFB) and mesocarp fibers (MSF) were conducted to achieve protection of the lignin structure, while improving the enzymatic efficiency of the solid residues. Under the operating conditions of 90 °C and 6 h, ChCl/OA/EG demonstrated a higher lignin extraction selectivity and obtained solid residues with higher hemicellulose content compared to ChCl/OA. The digestibility of glucan and xylan in solid residues obtained using ChCl/OA/EG achieved 98.56 % and 95.63 %, respectively, for EFB and 75.95 % and 88.60 %, for MSF. Uncondensed lignin enriched with 71.79-81.61 % of β-O-4 bonds was obtained from EFB and MSF using ChCl/OA/EG. 2D HSQC NMR and the density functional theory calculation confirmed that substituting the lignin Cα position by ethylene glycol changed the local potentials of the β-O-4 bonds, impeding the attack of protons (H+). The higher β-O-4 linkage content in ChCl/OA/EG-Ls led to the formation of several oxygenated alkyl methoxy phenols and alkyl methoxy phenols were promoted during the pyrolysis. Moreover, molecular dynamics simulations showed that the main factor affecting lignin extraction and dissolution in this study was the diffusion coefficient of lignin in DESs.

Super-photostable organic dye for long-term live-cell single-protein imaging

Organic dyes play a crucial role in live-cell imaging because of their advantageous properties, such as photostability and high brightness. Here we introduce a super-photostable and bright organic dye, Phoenix Fluor 555 (PF555), which exhibits an order-of-magnitude longer photobleaching lifetime than conventional organic dyes without the requirement of any anti-photobleaching additives. PF555 is an asymmetric cyanine structure in which, on one side, the indole in the conventional Cyanine-3 is substituted with 3-oxo-quinoline. PF555 provides a powerful tool for long-term live-cell single-molecule imaging, as demonstrated by the imaging of the dynamic single-molecule interactions of the epidermal growth factor receptor with clathrin-coated structures on the plasma membrane of a live cell under physiological conditions.

Precisely controlled colloids: a playground for path-wise non-equilibrium physics

We investigate path-wise observables in experiments on driven colloids in a periodic light field to dissect selected intricate transport features, kinetics, and transition-path time statistics out of thermodynamic equilibrium. These observables directly reflect the properties of individual paths in contrast to the properties of an ensemble of particles, such as radial distribution functions or mean-squared displacements. In particular, we present two distinct albeit equivalent formulations of the underlying stochastic equation of motion, highlight their respective practical relevance, and show how to interchange between them. We discuss conceptually different notions of local velocities and interrogate one- and two-sided first-passage and transition-path time statistics in and out of equilibrium. Our results reiterate how path-wise observables may be employed to systematically assess the quality of experimental data and demonstrate that, given sufficient control and sampling, one may quantitatively verify subtle theoretical predictions.

3D real-time single particle tracking using two-photon fluorescence from bright dye-based organic nanoparticles

This paper addresses the use of ultrabright dye-based fluorescent organic nanoparticles in a 3D single-particle tracking two-photon microscopy setup. The nanoparticles consist of an assembly of quadrupolar dyes, presenting a large two-photon absorption cross-section. They exhibit low photobleaching, crucial for long-term tracking, and their high brightness allows nanometer localization precision. Their small size compared to previously used nonlinear inorganic nanocrystals, stable structure at physiological temperature, and adjustable optical properties make them promising tools for further biological research. This study highlights their potential to track dynamic processes with precision and stability, paving the way for exploring cellular processes at the nanoscale.

Nanodomains and Their Temperature Dependence in a Phosphonium-Based Ionic Liquid: A Single-Molecule Tracking Study

Ionic liquids (ILs) exhibit a unique nanoscale structure (i.e., nanodomains) characterized by their organization into distinct domains. We present evidence of nanodomains in trihexyl(tetradecyl)phosphonium chloride, [P66614][Cl], using single-molecule tracking (SMT) and the maximum entropy method (MEM) to analyze single-molecule trajectories. The diffusion properties of ATTO 647N were assessed as the temperature of [P66614][Cl] increased from 20 °C (4020 cP), 35 °C (1239 cP), 45 °C (599 cP) to 50 °C (439 cP). The MEM analysis revealed a distinct two-population distribution of diffusion coefficients representing nanodomains in [P66614][Cl] at 20 °C (4020 cP). The slow population accounts for 16%, with a diffusion coefficient of 0.104 μm2/s, while the fast population constitutes 84% with a diffusion coefficient of 0.634 μm2/s. Two diffusing populations were also measured for the chemically different probes ATTO 647N, DiD, and Nile Blue chloride in [P66614][Cl] at 20 °C. In contrast, only a single fast population was measured in [P66614][Cl] at 50 °C. At a similar viscosity (640 cP) but a lower temperature of 20 °C, trihexyl(tetradecyl)phosphonium bis[(trifluoromethyl)-sulfonyl]imide, [P66614][NTf2], also showed only a single diffusing population. The elimination of the slow population and the presence of a single diffusing population in [P66614][Cl] as the temperature increases and the viscosity decreases is consistent with liquid-liquid phase separation (LLPS) as a mechanism of nanodomain formation. In addition, the measurement of two diffusing populations for three fluorophores with different chemical structures is also consistent with a physical mechanism, and not a chemical mechanism, for nanodomain formation.

Simulation Study on Diffusion and Local Structure of CH4, CO2, SO2, and H2O Mixtures into Double-Layers Graphene

Graphene has been widely studied as an ideal material for the adsorption and separation. In this work, we used molecular dynamics simulations to investigate the evolution of diffusion and local structure of CH4, CO2, SO2, and H2O mixtures into double-layers graphene under seven different interlayer spacings and four different CO2 concentrations. The results showed that the adsorption of CH4 and CO2 molecules on the graphene surface weakened with increased interlayer spacing. The diffusion capacities of CH4 and CO2 in the mixed system were significantly improved by increasing the interlayer spacing. In interlayer spacings ranging from 5 to 10 nm, the diffusion capacities of each component varied significantly in the order CH4 > CO2 ≫ H2O > SO2. Compared with CH4 and CO2, the local structures of SO2 and H2O were more affected by the interlayer spacing. Larger interlayer spacings or higher CO2 concentrations were advantageous for the formation of stronger hydrogen bond structures between H2O molecules. When the CO2 concentrations were between 10% and 20% and the interlayer spacing of graphene was 8 nm, the graphene structure exhibited the best adsorption and separation effects on CH4 and other components.

Microrheology of gemini surfactants at interfaces and in solutions in the dilute and semidilute regimes

Gemini surfactants are ideal systems to study a wide range of rheological behaviours in soft matter, showing fascinating analogies with living polymers and polyelectrolytes. By only changing the concentration, the shear viscosity can vary by 7 orders of magnitude in the bulk when transitioning through the semidilute regime. In order to elucidate on the intrinsic shear viscosity profile at the interface in soft matter systems manifesting various concentration regimes and morphological transitions, we performed microrheology and adsorption experiments under a wide range of experimental conditions. The surface shear viscosity has been characterized by passive microrheology, tracking Brownian particles trapped at the air-solution interface, under particle wetting conditions precisely characterized by interferometry. We observe that a steep increase in bulk shear viscosity as a function of the concentration does not translate at the interface, which may show a negative surface shear viscosity. By comparing macrorheology and microrheology, we measure significant differences both at the interface and in the bulk in the semidilute regime, where wormlike micelles start to entangle. The disparity in rheological measurements can be attributed to notable depletion effects near both the air-solution and particle-solution interfaces.

Long-Range Three-Dimensional Tracking of Nanoparticles Using Interferometric Scattering Microscopy

Tracking nanoparticle movement is highly desirable in many scientific areas, and various imaging methods have been employed to achieve this goal. Interferometric scattering (iSCAT) microscopy has been particularly successful in combining very high spatial and temporal resolution for tracking small nanoparticles in all three dimensions. However, previous works have been limited to an axial range of only a few hundred nanometers. Here, we present a robust and efficient measurement and analysis strategy for three-dimensional tracking of nanoparticles at high speed and with nanometer precision. After discussing the principle of our approach using synthetic data, we showcase the performance of the method by tracking gold nanoparticles with diameters ranging from 10 to 80 nm in water, demonstrating an axial tracking range from 4 μm for the smallest particles up to over 30 μm for the larger ones. We point out the limitations and robustness of our system across various noise levels and discuss its promise for applications in cell biology and material science, where the three-dimensional motion of nanoparticles in complex media is of interest.

Slowed Singlet Exciton Fission Enhances Triplet Exciton Transport in Select Perylenediimide Crystals

Singlet fission (SF) materials used in light-harvesting devices must not only efficiently produce spin-triplet excitons but also transport them to an energy acceptor. N,N'-Bis(2-phenylethyl)-3,4,9,10-perylenedicarboximide (EP-PDI) is a promising SF chromophore due to its photostability, large extinction coefficient, and high triplet yield, but the energy transport mechanisms in EP-PDI solids are minimally understood. Herein, we use transient absorption microscopy to directly characterize exciton transport in EP-PDI crystals. We find evidence for singlet-mediated transport in which pairs of triplet excitons undergo triplet fusion (TF), producing spin-singlet excitons that rapidly diffuse. This interchange of singlet and triplet excitons shuttles triplets as far as 205 nm within the first 500 ps after photoexcitation. This enhanced transport comes at a cost, however, as it necessitates favoring triplet recombination and thus requires fine-tuning of SF dynamics to balance triplet yields with triplet transport lengths. Through numerical modeling, we predict tuning the ratio of SF and TF rate constants, kSF/kTF, to between 1.9 and 3.8 allows for an optimized triplet transport length (425-563 nm) with minimal loss (7-10%) in triplet yield. Interestingly, by adjusting the size of EP-PDI crystals, we find that we can subtly tune their crystal structure and thereby alter their SF and TF rates. By slowing SF within small EP-PDI crystals, we are able to boost their triplet transport length by ∼20%. Although counterintuitive, our work suggests slowing SF by introducing moderate structural distortions can be preferential when optimizing triplet exciton transport, provided singlet exciton transport is not significantly hindered.

Shifts in keratin isoform expression activate motility signals during wound healing

Keratin intermediate filaments confer structural stability to epithelial tissues, but the reason this simple mechanical function requires a protein family with 54 isoforms is not understood. During skin wound healing, a shift in keratin isoform expression alters the composition of keratin filaments. If and how this change modulates cellular functions that support epidermal remodeling remains unclear. We report an unexpected effect of keratin isoform variation on kinase signal transduction. Increased expression of wound-associated keratin 6A, but not of steady-state keratin 5, potentiated keratinocyte migration and wound closure without compromising mechanical stability by activating myosin motors to increase contractile force generation. These results substantially expand the functional repertoire of intermediate filaments from their canonical role as mechanical scaffolds to include roles as isoform-tuned signaling scaffolds that organize signal transduction cascades in space and time to influence epithelial cell state.

Amino acid-dependent phase equilibrium and material properties of tetrapeptide condensates

The rules of how amino acids dictate the physical properties of biomolecular condensates are still incomplete. Here, we study condensates formed by tetrapeptides of the form XXssXX. Eight peptides form four types of condensates at different concentrations and pHs: droplets (X = F, L, M, P, V, and A), amorphous dense liquids (X = L, M, P, V, and A), amorphous aggregates (X = W), and gels (X = I, V, and A). The peptides exhibit differences in phase equilibrium and material properties, including a 368-fold range in the threshold concentration for phase separation and a 3,856-fold range in viscosity. All-atom molecular dynamics simulations provide physical explanations of these results. The present work also reveals widespread critical behaviors-including critical slowing down manifested by amorphous dense liquids and critical scaling obeyed by fusion speed-with broad implications for condensate functions.

Anomalous diffusion of active Brownian particles in responsive elastic gels: Nonergodicity, non-Gaussianity, and distributions of trapping times

Understanding actual transport mechanisms of self-propelled particles (SPPs) in complex elastic gels-such as in the cell cytoplasm, in in vitro networks of chromatin or of F-actin fibers, or in mucus gels-has far-reaching consequences. Implications beyond biology/biophysics are in engineering and medicine, with a particular focus on microrheology and on targeted drug delivery. Here, we examine via extensive computer simulations the dynamics of SPPs in deformable gellike structures responsive to thermal fluctuations. We treat tracer particles comparable to and larger than the mesh size of the gel. We observe distinct trapping events of active tracers at relatively short times, leading to subdiffusion; it is followed by an escape from meshwork-induced traps due to the flexibility of the network, resulting in superdiffusion. We thus find crossovers between different transport regimes. We also find pronounced nonergodicity in the dynamics of SPPs and non-Gaussianity at intermediate times. The distributions of trapping times of the tracers escaping from "cages" in our quasiperiodic gel often reveal the existence of two distinct timescales in the dynamics. At high activity of the tracers these timescales become comparable. Furthermore, we find that the mean waiting time exhibits a power-law dependence on the activity of SPPs (in terms of their Péclet number). Our results additionally showcase both exponential and nonexponential trapping events at high activities. Extensions of this setup are possible, with the factors such as anisotropy of the particles, different topologies of the gel network, and various interactions between the particles (also of a nonlocal nature) to be considered.

Fluorogenic RNA-based biomaterials for imaging and tracking the cargo of extracellular vesicles

Extracellular vesicles (EVs), or exosomes, play important roles in physiological and pathological cellular communication and have gained substantial traction as biological drug carriers. EVs contain both short and long non-coding RNAs that regulate gene expression and epigenetic processes. To fully capitalize on the potential of EVs as drug carriers, it is important to study and understand the intricacies of EV function and EV RNA-based communication. Here we developed a genetically encodable RNA-based biomaterial, termed EXO-Probe, for tracking EV RNAs. The EXO-Probe comprises an EV-loading RNA sequence (EXO-Code), fused to a fluorogenic RNA Mango aptamer for RNA imaging. This fusion construct allowed the visualization and tracking of EV RNA and colocalization with markers of multivesicular bodies; imaging RNA within EVs, and non-destructive quantification of EVs. Overall, the new RNA-based biomaterial provides a useful and versatile means to interrogate the role of EVs in cellular communication via RNA trafficking to EVs and to study cellular sorting decisions. The system will also help lay the foundation to further improve the therapeutic efficacy of EVs as drug carriers.

Label free tracking to quantify nanoparticle diffusion through biological media

Nanotechnology is a rapidly evolving field and has been extensively studied in biological applications. An understanding of the factors that influence nanoparticle diffusion in biofluids can aid in the development of diverse technologies. The development of real-time, label-free tracking technologies would allow the expansion of current knowledge of the diffusion and activity of nanoparticles. Fluorescence-based microscopy is one of the most widespread tools to monitor and track nanoparticle dynamics; however, the influence of fluorescent tags on diffusion and biological activity is still unclear. In this study, we experimentally determined the diffusion coefficient of gold nanoparticles using a label-free, optical tracking technique and evaluated the influence of protein concentration, charge and diameter on nanoparticle diffusion through biological media. We dispersed positively- and negatively-charged nanoparticles with diameters varying from 10 to 100 nm in a common cell culture media with different concentrations of serum proteins. Our results show that dynamic protein interactions influence nanoparticle diffusion in the range of serum concentrations tested. Experimental regimes to obtain quantitative information on the factors that influence the dynamics of nanoparticles in biological media have been developed.

The relationship between nanoscale genome organization and gene expression in mouse embryonic stem cells during pluripotency transition

During early development, gene expression is tightly regulated. However, how genome organization controls gene expression during the transition from naïve embryonic stem cells to epiblast stem cells is still poorly understood. Using single-molecule microscopy approaches to reach nanoscale resolution, we show that genome remodeling affects gene transcription during pluripotency transition. Specifically, after exit from the naïve pluripotency state, chromatin becomes less compacted, and the OCT4 transcription factor has lower mobility and is more bound to its cognate sites. In epiblast cells, the active transcription hallmark, H3K9ac, decreases within the Oct4 locus, correlating with reduced accessibility of OCT4 and, in turn, with reduced expression of Oct4 nascent RNAs. Despite the high variability in the distances between active pluripotency genes, distances between Nodal and Oct4 decrease during epiblast specification. In particular, highly expressed Oct4 alleles are closer to nuclear speckles during all stages of the pluripotency transition, while only a distinct group of highly expressed Nodal alleles are in close proximity to Oct4 when associated with a nuclear speckle in epiblast cells. Overall, our results provide new insights into the role of the spatiotemporal genome remodeling during mouse pluripotency transition and its correlation with the expression of key pluripotency genes.

Trajectory Analysis in Single-Particle Tracking: From Mean Squared Displacement to Machine Learning Approaches

Single-particle tracking is a powerful technique to investigate the motion of molecules or particles. Here, we review the methods for analyzing the reconstructed trajectories, a fundamental step for deciphering the underlying mechanisms driving the motion. First, we review the traditional analysis based on the mean squared displacement (MSD), highlighting the sometimes-neglected factors potentially affecting the accuracy of the results. We then report methods that exploit the distribution of parameters other than displacements, e.g., angles, velocities, and times and probabilities of reaching a target, discussing how they are more sensitive in characterizing heterogeneities and transient behaviors masked in the MSD analysis. Hidden Markov Models are also used for this purpose, and these allow for the identification of different states, their populations and the switching kinetics. Finally, we discuss a rapidly expanding field-trajectory analysis based on machine learning. Various approaches, from random forest to deep learning, are used to classify trajectory motions, which can be identified by motion models or by model-free sets of trajectory features, either previously defined or automatically identified by the algorithms. We also review free software available for some of the analysis methods. We emphasize that approaches based on a combination of the different methods, including classical statistics and machine learning, may be the way to obtain the most informative and accurate results.

Robust Quantification of Live-Cell Single-Molecule Tracking Data for Fluorophores with Different Photophysical Properties

High-speed single-molecule tracking in live cells is becoming an increasingly popular method for quantifying the spatiotemporal behavior of proteins in vivo. The method provides a wealth of quantitative information, but users need to be aware of biases that can skew estimates of molecular mobilities. The range of suitable fluorophores for live-cell single-molecule imaging has grown substantially over the past few years, but it remains unclear to what extent differences in photophysical properties introduce biases. Here, we tested two fluorophores with entirely different photophysical properties, one that photoswitches frequently between bright and dark states (TMR) and one that shows exceptional photostability without photoswitching (JFX650). We used a fusion of the Escherichia coli DNA repair enzyme MutS to the HaloTag and optimized sample preparation and imaging conditions for both types of fluorophore. We then assessed the reliability of two common data analysis algorithms, mean-square displacement (MSD) analysis and Hidden Markov Modeling (HMM), to estimate the diffusion coefficients and fractions of MutS molecules in different states of motion. We introduce a simple approach that removes discrepancies in the data analyses and show that both algorithms yield consistent results, regardless of the fluorophore used. Nevertheless, each dye has its own strengths and weaknesses, with TMR being more suitable for sampling the diffusive behavior of many molecules, while JFX650 enables prolonged observation of only a few molecules per cell. These characterizations and recommendations should help to standardize measurements for increased reproducibility and comparability across studies.

Highly sensitive volumetric single-molecule imaging

Volumetric subcellular imaging has long been essential for studying structures and dynamics in cells and tissues. However, due to limited imaging speed and depth of field, it has been challenging to perform live-cell imaging and single-particle tracking. Here we report a 2.5D fluorescence microscopy combined with highly inclined illumination beams, which significantly reduce not only the image acquisition time but also the out-of-focus background by ∼2-fold compared to epi-illumination. Instead of sequential z-scanning, our method projects a certain depth of volumetric information onto a 2D plane in a single shot using multi-layered glass for incoherent wavefront splitting, enabling high photon detection efficiency. We apply our method to multi-color immunofluorescence imaging and volumetric super-resolution imaging, covering ∼3-4 µm thickness of samples without z-scanning. Additionally, we demonstrate that our approach can substantially extend the observation time of single-particle tracking in living cells.

Molecular dynamics simulation and experimental verification of the effects of vinyl silicone oil viscosity on the mechanical properties of silicone rubber foam

The molecular motion trajectories of silicone rubber foam (SRF) at various vinyl silicone oil viscosities were studied via molecular dynamics (MD) simulation from the perspective of all atomic molecules. The influence of different viscosities of vinyl silicone oil on interaction, compatibility, and aggregation degree of molecules was determined based on the mean square displacement, diffusion coefficient, binding energy, solubility parameter, radial distribution function, and radius of gyration. The mechanical properties of the SRF were also experimentally verified. Results revealed that as the viscosity of vinyl silicone oil increased, the mean square displacement, fractional free volume, diffusion coefficient, and solubility parameter of the system decreased, whereas its larger radius of gyration increased. Moreover, the radial distribution function showed a weaker relative interaction between molecular chains. The calculated binding energy demonstrated that the system had better compatibility at a viscosity of 0.45 Pa s. This study provided a deeper insight into the relation between the viscosity of vinyl silicone oil and mechanical properties of the SRF. As the viscosity of vinyl silicone oil increased, the changing trend in MD simulation results of elastic modulus, shear modulus, bulk modulus, and Poisson's ratio was consistent with the experimental results. The MD simulations can promote theoretical predictions and scientific basis for the design of the SRF with desired performances.

Overstretching alveolar epithelial type II cells decreases surfactant secretion via actin polymerization and intracellular trafficking alteration

Pulmonary surfactant is essential for maintaining proper lung function. Alveolar epithelial type II (AE2) cells secrete surfactants via lamellar bodies (LBs). In tidal loading during each breath, the physiological cyclic stretching of AE2 cells promotes surfactant secretion. Excessive stretching inhibits surfactant secretion, which is considered to contribute to the development of lung damage. However, its precise mechanism remains unknown. This study tested whether actin polymerization and intracellular transport are required for pulmonary surfactant secretion and the association of actin polymerization and transport in identical human AE2-derived A549 cells using live-cell imaging, not in the bulk cells population. We found that overstretching approximately doubled actin polymerization into filaments (F-actin) and suppressed LB secretion by half in the fluorescent area ratio, compared with physiological stretching (F-actin: 1.495 vs 0.643 (P < 0.01); LB: 0.739 vs 0.332 (P < 0.01)). An inhibitor of actin polymerization increased LB secretion. Intracellular tracking using fluorescent particles revealed that cyclic stretching shifted the particle motion perpendicularly to the direction of stretching according to the orientation of the F-actin (proportion of perpendicular axis motion prior particle: 0h 40.12 % vs 2h 63.13 % (P < 0.01)), and particle motion was restricted over time in the cells subjected to overstretching, indicating that overstretching regulates intracellular transport dynamics (proportion of stop motion particle: 0h 1.01 % vs 2h 11.04 % (P < 0.01)). These findings suggest that overstretching changes secretion through the cytoskeleton: overstretching AE2 cells inhibits pulmonary surfactant secretion, at least through accelerating actin polymerization and decreasing intracellular trafficking, and the change in actin orientation would modulate intracellular trafficking.

Axial de-scanning using remote focusing in the detection arm of light-sheet microscopy

Rapid, high-resolution volumetric imaging without moving heavy objectives or disturbing delicate samples remains challenging. Pupil-matched remote focusing offers a promising solution for high NA systems, but the fluorescence signal's incoherent and unpolarized nature complicates its application. Thus, remote focusing is mainly used in the illumination arm with polarized laser light to improve optical coupling. Here, we introduce a novel optical design that can de-scan the axial focus movement in the detection arm of a microscope. Our method splits the fluorescence signal into S and P-polarized light, lets them pass through the remote focusing module separately, and combines them with the camera. This allows us to use only one focusing element to perform aberration-free, multi-color, volumetric imaging without (a) compromising the fluorescent signal and (b) needing to perform sample/detection-objective translation. We demonstrate the capabilities of this scheme by acquiring fast dual-color 4D (3D space + time) image stacks with an axial range of 70 μm and camera-limited acquisition speed. Owing to its general nature, we believe this technique will find its application in many other microscopy techniques that currently use an adjustable Z-stage to carry out volumetric imaging, such as confocal, 2-photon, and light sheet variants.

Expanding the Palette of SWIR Emitting Nanoparticles Based on Au Nanoclusters for Single-Particle Tracking Microscopy

Single-molecule localization microscopy has proved promising to unravel the dynamics and molecular architecture of thin biological samples down to nanoscales. For applications in complex, thick biological tissues shifting single-particle emission wavelengths to the shortwave infrared (SWIR also called NIR II) region between 900 to 2100 nm, where biological tissues are more transparent is key. To date, mainly single-walled carbon nanotubes (SWCNTs) enable such applications, but they are inherently 1D objects. Here, 0D ultra-small luminescent gold nanoclusters (AuNCs, <3 nm) and ≈25 nm AuNC-loaded-polymeric particles that can be detected at the single-particle level in the SWIR are presented. Thanks to high brightness and excellent photostability, it is shown that the dynamics of the spherical polymeric particles can be followed at the single-particle level in solution at video rates for minutes. We compared single particle tracking of AuNC-loaded-polymeric particles with that of SWCNT diffusing in agarose gels demonstrating the specificity and complementarity of diffusion properties of these SWIR-emitting nano-objects when exploring a complex environment. This extends the library of photostable SWIR emitting nanomaterials to 0D nano-objects of variable size for single-molecule localization microscopy in the second biological window, opening unprecedented possibilities for mapping the structure and dynamics of complex biological systems.

Amino Acid-Dependent Material Properties of Tetrapeptide Condensates

Condensates formed by intrinsically disordered proteins mediate a myriad of cellular processes and are linked to pathological conditions including neurodegeneration. Rules of how different types of amino acids (e.g., π-π pairs) dictate the physical properties of biomolecular condensates are emerging, but our understanding of the roles of different amino acids is far from complete. Here we studied condensates formed by tetrapeptides of the form XXssXX, where X is an amino acid and ss represents a disulfide bond along the backbone. Eight peptides form four types of condensates at different concentrations and pH values: droplets (X = F, L, M, P, V, A); amorphous dense liquids (X = L, M, P, V, A); amorphous aggregates (X = W), and gels (X = I, V, A). The peptides exhibit enormous differences in phase equilibrium and material properties, including a 368-fold range in the threshold concentration for phase separation and a 3856-fold range in viscosity. All-atom molecular dynamics simulations provide physical explanations of these results. The present work also reveals widespread critical behaviors, including critical slowing down manifested by the formation of amorphous dense liquids and critical scaling obeyed by fusion speed, with broad implications for condensate function.

Impact of temporal resolution in single particle tracking analysis

Temporal resolution is a key parameter in the observation of dynamic processes, as in the case of single molecules motions visualized in real time in two-dimensions by wide field (fluorescence) microscopy, but a systematic investigation of its effects in all the single particle tracking analysis steps is still lacking. Here we present tools to quantify its impact on the estimation of diffusivity and of its distribution using one of the most popular tracking software for biological applications on simulated data and movies. We found important shifts and different widths for diffusivity distributions, depending on the interplay of temporal sampling conditions with various parameters, such as simulated diffusivity, density of spots, signal-to-noise ratio, lengths of trajectories, and kind of boundaries in the simulation. We examined conditions starting from the ones of experiments on the fluorescently labelled receptor p75NTR, a relatively fast-diffusing membrane receptor (diffusivity around 0.5-1 µm2/s), visualized by TIRF microscopy on the basal membrane of living cells. From the analysis of the simulations, we identified the best conditions in cases similar to these ones; considering also the experiments, we could confirm a range of values of temporal resolution suitable for obtaining reliable diffusivity results. The procedure we present can be exploited in different single particle/molecule tracking applications to find an optimal temporal resolution.

Transfer of polarity information via diffusion of Wnt ligands in C. elegans embryos

Different signaling mechanisms concur to ensure robust tissue patterning and cell fate instruction during animal development. Most of these mechanisms rely on signaling proteins that are produced, transported, and detected. The spatiotemporal dynamics of signaling molecules are largely unknown, yet they determine signal activity's spatial range and time frame. Here, we use the Caenorhabditis elegans embryo to study how Wnt ligands, an evolutionarily conserved family of signaling proteins, dynamically organize to establish cell polarity in a developing tissue. We identify how Wnt ligands, produced in the posterior half of the embryos, spread extracellularly to transmit information to distant target cells in the anterior half. With quantitative live imaging and fluorescence correlation spectroscopy, we show that Wnt ligands diffuse through the embryo over a timescale shorter than the cell cycle, in the intercellular space, and outside the tissue below the eggshell. We extracted diffusion coefficients of Wnt ligands and their receptor Frizzled and characterized their co-localization. Integrating our different measurements and observations in a simple computational framework, we show how fast diffusion in the embryo can polarize individual cells through a time integration of the arrival of the ligands at the target cells. The polarity established at the tissue level by a posterior Wnt source can be transferred to the cellular level. Our results support a diffusion-based long-range Wnt signaling, which is consistent with the dynamics of developing processes.

Left-right Myosin-Is, Myosin1C, and Myosin1D exhibit distinct single molecule behaviors on the plasma membrane of Drosophila macrophages

Left-right (LR) asymmetry is crucial for animal development, particularly in Drosophila where LR-asymmetric morphogenesis of organs hinges on cellular-level chirality, termed cell chirality. In this species, two class I myosins, Myosin1D (Myo1D), and Myosin1C (Myo1C), respectively determine dextral (wild type) and sinistral (mirror image) cell chirality. Previous studies demonstrated Myo1D's ability to propel F-actin in leftward circles during in vitro gliding assays, suggesting its mechanochemical role in defining dextral chirality. Conversely, Myo1C propels F-actin without exhibiting LR-directional preference in this assay, suggesting at other properties governing sinistral chirality. Given the interaction of Myo1D and Myo1C with the membrane, we hypothesized that differences in their membrane behaviors might be critical in dictating their dextral or sinistral activities. In this study, employing single-molecule imaging analyses, we investigated the dynamic behaviors of Myo1D and Myo1C on the plasma membrane. Our findings revealed that Myo1C exhibits a significantly greater proportion of slow-diffusing population compared to Myo1D. Importantly, this characteristic was contingent upon both head and tail domains of Myo1C. The distinct diffusion patterns of Myo1D and Myo1C did not exert mutual influence on each other. This divergence in membrane diffusion between Myo1D and Myo1C may be crucial for dictating cell and organ chirality.

Keratin isoform shifts modulate motility signals during wound healing

Keratin intermediate filaments form strong mechanical scaffolds that confer structural stability to epithelial tissues, but the reason this function requires a protein family with 54 isoforms is not understood. During skin wound healing, a shift in keratin isoform expression alters the composition of keratin filaments. How this change modulates cellular function to support epidermal remodeling remains unclear. We report an unexpected effect of keratin isoform variation on kinase signal transduction. Increased expression of wound-associated keratin 6A, but not of steady-state keratin 5, potentiated keratinocyte migration and wound closure without compromising epidermal stability by activating myosin motors. This pathway depended on isoform-specific interaction between intrinsically disordered keratin head domains and non-filamentous vimentin shuttling myosin-activating kinases. These results substantially expand the functional repertoire of intermediate filaments from their canonical role as mechanical scaffolds to include roles as isoform-tuned signaling scaffolds that organize signal transduction cascades in space and time to influence epithelial cell state.

Axial de-scanning using remote focusing in the detection arm of light-sheet microscopy

The ability to image at high speeds is necessary for biological imaging to capture fast-moving or transient events or to efficiently image large samples. However, due to the lack of rigidity of biological specimens, carrying out fast, high-resolution volumetric imaging without moving and agitating the sample has been a challenging problem. Pupil-matched remote focusing has been promising for high NA imaging systems with their low aberrations and wavelength independence, making it suitable for multicolor imaging. However, owing to the incoherent and unpolarized nature of the fluorescence signal, manipulating this emission light through remote focusing is challenging. Therefore, remote focusing has been primarily limited to the illumination arm, using polarized laser light to facilitate coupling in and out of the remote focusing optics. Here, we introduce a novel optical design that can de-scan the axial focus movement in the detection arm of a microscope. Our method splits the fluorescence signal into S and P-polarized light, lets them pass through the remote focusing module separately, and combines them with the camera. This allows us to use only one focusing element to perform aberration-free, multi-color, volumetric imaging without (a) compromising the fluorescent signal and (b) needing to perform sample/detection-objective translation. We demonstrate the capabilities of this scheme by acquiring fast dual-color 4D (3D space + time) image stacks with an axial range of 70 μm and camera-limited acquisition speed. Owing to its general nature, we believe this technique will find its application in many other microscopy techniques that currently use an adjustable Z-stage to carry out volumetric imaging, such as confocal, 2-photon, and light sheet variants.

A Biophysics Toolbox for Reliable Data Acquisition and Processing in Integrated Force-Confocal Fluorescence Microscopy

Integrated single-molecule force-fluorescence spectroscopy setups allow for simultaneous fluorescence imaging and mechanical force manipulation and measurements on individual molecules, providing comprehensive dynamic and spatiotemporal information. Dual-beam optical tweezers (OT) combined with a confocal scanning microscope form a force-fluorescence spectroscopy apparatus broadly used to investigate various biological processes, in particular, protein:DNA interactions. Such experiments typically involve imaging of fluorescently labeled proteins bound to DNA and force spectroscopy measurements of trapped individual DNA molecules. Here, we present a versatile state-of-the-art toolbox including the preparation of protein:DNA complex samples, design of a microfluidic flow cell incorporated with OT, automation of OT-confocal scanning measurements, and the development and implementation of a streamlined data analysis package for force and fluorescence spectroscopy data processing. Its components can be adapted to any commercialized or home-built dual-beam OT setup equipped with a confocal scanning microscope, which will facilitate single-molecule force-fluorescence spectroscopy studies on a large variety of biological systems.

Macromolecular interactions and geometrical confinement determine the 3D diffusion of ribosome-sized particles in live Escherichia coli cells

The crowded bacterial cytoplasm is comprised of biomolecules that span several orders of magnitude in size and electrical charge. This complexity has been proposed as the source of the rich spatial organization and apparent anomalous diffusion of intracellular components, although this has not been tested directly. Here, we use biplane microscopy to track the 3D motion of self-assembled bacterial Genetically Encoded Multimeric nanoparticles (bGEMs) with tunable size (20 to 50 nm) and charge (-2160 to +1800 e) in live Escherichia coli cells. To probe intermolecular details at spatial and temporal resolutions beyond experimental limits, we also developed a colloidal whole-cell model that explicitly represents the size and charge of cytoplasmic macromolecules and the porous structure of the bacterial nucleoid. Combining these techniques, we show that bGEMs spatially segregate by size, with small 20-nm particles enriched inside the nucleoid, and larger and/or positively charged particles excluded from this region. Localization is driven by entropic and electrostatic forces arising from cytoplasmic polydispersity, nucleoid structure, geometrical confinement, and interactions with other biomolecules including ribosomes and DNA. We observe that at the timescales of traditional single molecule tracking experiments, motion appears sub-diffusive for all particle sizes and charges. However, using computer simulations with higher temporal resolution, we find that the apparent anomalous exponents are governed by the region of the cell in which bGEMs are located. Molecular motion does not display anomalous diffusion on short time scales and the apparent sub-diffusion arises from geometrical confinement within the nucleoid and by the cell boundary.

Transcription factor exchange enables prolonged transcriptional bursts

Single-molecule imaging inside living cells has revealed that transcription factors (TFs) bind to DNA transiently, but a long-standing question is how this transient binding is related to transcription activation. Here, we devised a microscopy method to simultaneously measure transient TF binding at a single locus and the effect of these binding events on transcription. We show that DNA binding of the yeast TF Gal4 activates transcription of a target gene within a few seconds, with at least ∼20% efficiency and with a high initiation rate of ∼1 RNA/s. Gal4 DNA dissociation decreases transcription rapidly. Moreover, at a gene with multiple binding sites, individual Gal4 molecules only rarely stay bound throughout the entire burst but instead frequently exchange during a burst to increase the transcriptional burst duration. Our results suggest a mechanism for enhancer regulation in more complex eukaryotes, where TF cooperativity and exchange enable robust and responsive transcription regulation.

Targeted Single Particle Tracking with Upconverting Nanoparticles

Single particle tracking (SPT) is a powerful technique for real-time microscopic visualization of the movement of individual biomolecules within or on the surface of living cells. However, SPT often suffers from the suboptimal performance of the photon-emitting labels used to tag the biomolecules of interest. For example, fluorescent dyes have poor photostability, while quantum dots suffer from blinking that hampers track acquisition and interpretation. Upconverting nanoparticles (UCNPs) have recently emerged as a promising anti-Stokes luminescent label for SPT. In this work, we demonstrated targeted SPT using UCNPs. For this, we synthesized 30 nm diameter doped UCNPs and coated them with amphiphilic polymers decorated with polyethylene glycol chains to make them water-dispersible and minimize their nonspecific interactions with cells. Coated UCNPs highly homogeneous in brightness (as confirmed by a single particle investigation) were functionalized by immunoglobulin E (IgE) using a biotin-streptavidin strategy. Using these IgE-UCNP SPT labels, we tracked high-affinity IgE receptors (FcεRI) on the membrane of living RBL-2H3 mast cells at 37 °C in the presence and absence of antigen and obtained good agreement with the literature. Moreover, we used the FcεRI-IgE receptor-antibody system to directly compare the performance of UCNP-based SPT labels to organic dyes (AlexaFluor647) and quantum dots (QD655). Due to their photostability as well as their backgroundless and continuous luminescence, SPT trajectories obtained with UCNP labels are no longer limited by the photophysics of the label but only by the dynamics of the system and, in particular, the movement of the label out of the field of view and/or focal plane.

Intranasal CRMP2-Ubc9 inhibitor regulates Na V 1.7 to alleviate trigeminal neuropathic pain

ABSTRACT

Dysregulation of voltage-gated sodium Na V 1.7 channels in sensory neurons contributes to chronic pain conditions, including trigeminal neuropathic pain. We previously reported that chronic pain results in part from increased SUMOylation of collapsin response mediator protein 2 (CRMP2), leading to an increased CRMP2/Na V 1.7 interaction and increased functional activity of Na V 1.7. Targeting this feed-forward regulation, we developed compound 194 , which inhibits CRMP2 SUMOylation mediated by the SUMO-conjugating enzyme Ubc9. We further demonstrated that 194 effectively reduces the functional activity of Na V 1.7 channels in dorsal root ganglia neurons and alleviated inflammatory and neuropathic pain. Here, we used a comprehensive array of approaches, encompassing biochemical, pharmacological, genetic, electrophysiological, and behavioral analyses, to assess the functional implications of Na V 1.7 regulation by CRMP2 in trigeminal ganglia (TG) neurons. We confirmed the expression of Scn9a , Dpysl2 , and UBE2I within TG neurons. Furthermore, we found an interaction between CRMP2 and Na V 1.7, with CRMP2 being SUMOylated in these sensory ganglia. Disrupting CRMP2 SUMOylation with compound 194 uncoupled the CRMP2/Na V 1.7 interaction, impeded Na V 1.7 diffusion on the plasma membrane, and subsequently diminished Na V 1.7 activity. Compound 194 also led to a reduction in TG neuron excitability. Finally, when intranasally administered to rats with chronic constriction injury of the infraorbital nerve, 194 significantly decreased nociceptive behaviors. Collectively, our findings underscore the critical role of CRMP2 in regulating Na V 1.7 within TG neurons, emphasizing the importance of this indirect modulation in trigeminal neuropathic pain.

Membrane lipids drive formation of KRAS4b-RAF1 RBDCRD nanoclusters on the membrane

The oncogene RAS, extensively studied for decades, presents persistent gaps in understanding, hindering the development of effective therapeutic strategies due to a lack of precise details on how RAS initiates MAPK signaling with RAF effector proteins at the plasma membrane. Recent advances in X-ray crystallography, cryo-EM, and super-resolution fluorescence microscopy offer structural and spatial insights, yet the molecular mechanisms involving protein-protein and protein-lipid interactions in RAS-mediated signaling require further characterization. This study utilizes single-molecule experimental techniques, nuclear magnetic resonance spectroscopy, and the computational Machine-Learned Modeling Infrastructure (MuMMI) to examine KRAS4b and RAF1 on a biologically relevant lipid bilayer. MuMMI captures long-timescale events while preserving detailed atomic descriptions, providing testable models for experimental validation. Both in vitro and computational studies reveal that RBDCRD binding alters KRAS lateral diffusion on the lipid bilayer, increasing cluster size and decreasing diffusion. RAS and membrane binding cause hydrophobic residues in the CRD region to penetrate the bilayer, stabilizing complexes through β-strand elongation. These cooperative interactions among lipids, KRAS4b, and RAF1 are proposed as essential for forming nanoclusters, potentially a critical step in MAP kinase signal activation.

Caveolae disassemble upon membrane lesioning and foster cell survival

Repair of lesions in the plasma membrane is key to sustaining cellular homeostasis. Cells maintain cytoplasmic as well as membrane-bound stores of repair proteins that can rapidly precipitate at the site of membrane lesions. However, little is known about the origins of lipids and proteins for resealing and repair of the plasma membrane. Here we study the dynamics of caveolar proteins after laser-induced lesioning of plasma membranes of mammalian C2C12 tissue culture cells and muscle cells of intact zebrafish embryos. Single-molecule diffusivity measurements indicate that caveolar clusters break up into smaller entities after wounding. Unlike Annexins and Dysferlin, caveolar proteins do not accumulate at the lesion patch. In caveolae-depleted cavin1a knockout zebrafish embryos, lesion patch formation is impaired, and injured cells show reduced survival. Our data suggest that caveolae disassembly releases surplus plasma membrane near the lesion to facilitate membrane repair after initial patch formation for emergency sealing.

Einstein-Stokes relation for small bubbles at the nanoscale

As the physicochemical properties of ultrafine bubble systems are governed by their size, it is crucial to determine the size and distribution of such bubble systems. At present, the size or size distribution of nanometer-sized bubbles in suspension is often measured by either dynamic light scattering or the nanoparticle tracking analysis. Both techniques determine the bubble size via the Einstein-Stokes equation based on the theory of the Brownian motion. However, it is not yet clear to which extent the Einstein-Stokes equation is applicable for such ultrafine bubbles. In this work, using atomic molecular dynamics simulation, we evaluate the applicability of the Einstein-Stokes equation for gas nanobubbles with a diameter less than 10 nm, and for a comparative analysis, both vacuum nanobubbles and copper nanoparticles are also considered. The simulation results demonstrate that the diffusion coefficient for rigid nanoparticles in water is found to be highly consistent with the Einstein-Stokes equation, with slight deviation only found for nanoparticle with a radius less than 1 nm. For nanobubbles, including both methane and vacuum nanobubbles, however, large deviation from the Einstein-Stokes equation is found for the bubble radius larger than 3 nm. The deviation is attributed to the deformability of large nanobubbles that leads to a cushioning effect for collision-induced bubble diffusion.

Temperature-Induced Restructuring of Mycolic Acid Bilayers Modeling the Mycobacterium tuberculosis Outer Membrane: A Molecular Dynamics Study

The emergence of new drug-resistant strains of the tuberculosis pathogen Mycobacterium tuberculosis (Mtb) is a new challenge for modern medicine. Its resistance capacity is closely related to the properties of the outer membrane of the Mtb cell wall, which is a bilayer membrane formed by mycolic acids (MAs) and their derivatives. To date, the molecular mechanisms of the response of the Mtb outer membrane to external factors and, in particular, elevated temperatures have not been sufficiently studied. In this work, we consider the temperature-induced changes in the structure, ordering, and molecular mobility of bilayer MA membranes of various chemical and conformational compositions. Using all-atom long-term molecular dynamics simulations of various MA membranes, we report the kinetic parameters of temperature-dependent changes in the MA self-diffusion coefficients and conformational compositions, including the apparent activation energies of these processes, as well as the characteristic times of ordering changes and the features of phase transitions occurring over a wide range of elevated temperatures. Understanding these effects could be useful for the prevention of drug resistance and the development of membrane-targeting pharmaceuticals, as well as in the design of membrane-based materials.

Deep learning assisted single particle tracking for automated correlation between diffusion and function

Sub-cellular diffusion in living systems reflects cellular processes and interactions. Recent advances in optical microscopy allow the tracking of this nanoscale diffusion of individual objects with an unprecedented level of precision. However, the agnostic and automated extraction of functional information from the diffusion of molecules and organelles within the sub-cellular environment, is labor-intensive and poses a significant challenge. Here we introduce DeepSPT, a deep learning framework to interpret the diffusional 2D or 3D temporal behavior of objects in a rapid and efficient manner, agnostically. Demonstrating its versatility, we have applied DeepSPT to automated mapping of the early events of viral infections, identifying distinct types of endosomal organelles, and clathrin-coated pits and vesicles with up to 95% accuracy and within seconds instead of weeks. The fact that DeepSPT effectively extracts biological information from diffusion alone illustrates that besides structure, motion encodes function at the molecular and subcellular level.

Transformation of Diffusion and Local Structure of CH4 , CO2 , SO2 and H2 O Mixtures in Graphene Under Wide Temperature and Pressure Range: A Molecular Dynamics Simulation Study

As a material with high specific surface area and excellent chemical stability, graphene exhibited remarkable adsorption and separation performance as well as a wide range of potential applications. The graphene layer played a significant role in influencing gas transmission. In this study, we employed molecular dynamics simulation to investigate the diffusion characteristics and local structures of a mixed system consisting of CH4 , CO2 , SO2 and H2 O. Additionally, we further examined the transformation of the behavior of these mixtures within graphene layers. The order of diffusion coefficients of the four molecules without graphene was H2 O>SO2 >CO2 ≫CH4 . However, in the double-layer graphene, the order changed to CH4 >CO2 ≫H2 O>SO2 . Higher temperatures and lower pressures were found to facilitate gas diffusion. Temperature and pressure had great effects on the local structures of CH4 , CO2 and SO2 , while their impact on H2 O was limited due to the extensive network of hydrogen bonds formed by H2 O molecules. The statistical results of average coordination number revealed that CH4 tended to aggregate with itself, whereas CO2 and SO2 exhibited a tendency to aggregate with H2 O. The graphene structure enhanced the separation and transportation of CH4 from mixed systems.

Brownian Diffusion of Hexagonal Boron Nitride Nanosheets and Graphene in Two Dimensions

Two-dimensional (2D) nanomaterials have numerous interesting chemical and physical properties that make them desirable building blocks for the manufacture of macroscopic materials. Liquid-phase processing is a common method for forming macroscopic materials from these building blocks including wet-spinning and vacuum filtration. As such, assembling 2D nanomaterials into ordered functional materials requires an understanding of their solution dynamics. Yet, there are few experimental studies investigating the hydrodynamics of disk-like materials. Herein, we report the lateral diffusion of hexagonal boron nitride nanosheets (h-BN and graphene) in aqueous solution when confined in 2-dimensions. This was done by imaging fluorescent surfactant-tagged nanosheets and visualizing them by using fluorescence microscopy. Spectroscopic studies were conducted to characterize the interactions between h-BN and the fluorescent surfactant, and atomic force microscopy (AFM) was conducted to characterize the quality of the dispersion. The diffusion data under different gap sizes and viscosities displayed a good correlation with Kramers' theory. We propose that the yielded activation energies by Kramers' equation express the magnitude of the interaction between fluorescent surfactant tagged h-BN and glass because the energies remain constant with changing viscosity and decrease with increasing confinement size. The diffusion of graphene presented a similar trend with similar activation energy as the h-BN. This relationship suggests that Kramers' theory can also be applied to simulate the diffusion of other 2D nanomaterials.

Using NMR diffusion data to validate MD models of disordered proteins: Test case of N-terminal tail of histone H4

MD simulations can provide uniquely detailed models of intrinsically disordered proteins (IDPs). However, these models need careful experimental validation. The coefficient of translational diffusion Dtr, measurable by pulsed field gradient NMR, offers a potentially useful piece of experimental information related to the compactness of the IDP's conformational ensemble. Here, we investigate, both experimentally and via the MD modeling, the translational diffusion of a 25-residue N-terminal fragment from histone H4 (N-H4). We found that the predicted values of Dtr, as obtained from mean-square displacement of the peptide in the MD simulations, are largely determined by the viscosity of the MD water (which has been reinvestigated as a part of our study). Beyond that, our analysis of the diffusion data indicates that MD simulations of N-H4 in the TIP4P-Ew water give rise to an overly compact conformational ensemble for this peptide. In contrast, TIP4P-D and OPC simulations produce the ensembles that are consistent with the experimental Dtr result. These observations are supported by the analyses of the 15N spin relaxation rates. We also tested a number of empirical methods to predict Dtr based on IDP's coordinates extracted from the MD snapshots. In particular, we show that the popular approach involving the program HYDROPRO can produce misleading results. This happens because HYDROPRO is not intended to predict the diffusion properties of highly flexible biopolymers such as IDPs. Likewise, recent empirical schemes that exploit the relationship between the small-angle x-ray scattering-informed conformational ensembles of IDPs and the respective experimental Dtr values also prove to be problematic. In this sense, the first-principle calculations of Dtr from the MD simulations, such as demonstrated in this work, should provide a useful benchmark for future efforts in this area.

Noise-cancellation algorithm for simulations of Brownian particles

We investigate the usage of a recently introduced noise-cancellation algorithm for Brownian simulations to enhance the precision of measuring transport properties such as the mean-square displacement or the velocity-autocorrelation function. The algorithm is based on explicitly storing the pseudorandom numbers used to create the randomized displacements in computer simulations and subtracting them from the simulated trajectories. The resulting correlation function of the reduced motion is connected to the target correlation function up to a cross-correlation term. Using analytical theory and computer simulations, we demonstrate that the cross-correlation term can be neglected in all three systems studied in this paper. We further expand the algorithm to Monte Carlo simulations and analyze the performance of the algorithm and rationalize that it works particularly well for unbounded, weakly interacting systems in which the precision of the mean-square displacement can be improved by orders of magnitude.

Single-Molecule Fluorescence Microscopy in Sensory Cilia of Living Caenorhabditis elegans

Intracellular transport of organelles and biomolecules is vital for several cellular processes. Single-molecule fluorescence microscopy can illuminate molecular aspects of the dynamics of individual biomolecules that remain unresolved in ensemble experiments. For example, studying single-molecule trajectories of moving biomolecules can reveal motility properties such as velocity, diffusivity, location and duration of pauses, etc. We use single-molecule imaging to study the dynamics of microtubule-based motor proteins and their cargo in the primary cilia of living C. elegans. To this end, we employ standard fluorescent proteins, an epi-illuminated, widefield fluorescence microscope, and primarily open-source software. This chapter describes the setup we use, the preparation of samples, a protocol for single-molecule imaging in primary cilia of C. elegans, and data analysis.

Rotational and translational drags of a Janus particle close to a wall and a lipid membrane

HYPOTHESIS

Measuring rotational and translational Brownian motion of single spherical particles reveals dissipations due to the interaction between the particle and the environment.

EXPERIMENTS

In this article, we show experiments where the in-plane translational and the two rotational drag coefficients of a single spherical Brownian particle can be measured. These particle drags are functions of the particle size and of the particle-wall distance, and of the viscous dissipations at play. We measure drag coefficients for Janus particles close to a solid wall and close to a lipid bilayer membrane.

FINDINGS

For a particle close to a wall, we show that according to hydrodynamic models, particle-wall distance and particle size can be determined. For a particle partially wrapped by lipid membranes, in absence of strong binding interactions, translational and rotational drags are significantly larger than the ones of non-wrapped particles. Beside the effect of the membrane viscosity, we show that dissipations in the deformed membrane cap region strongly contribute to the drag coefficients.

Deep learning assisted single particle tracking for automated correlation between diffusion and function

Sub-cellular diffusion in living systems reflects cellular processes and interactions. Recent advances in optical microscopy allow the tracking of this nanoscale diffusion of individual objects with an unprecedented level of precision. However, the agnostic and automated extraction of functional information from the diffusion of molecules and organelles within the sub-cellular environment, is labor-intensive and poses a significant challenge. Here we introduce DeepSPT, a deep learning framework to interpret the diffusional 2D or 3D temporal behavior of objects in a rapid and efficient manner, agnostically. Demonstrating its versatility, we have applied DeepSPT to automated mapping of the early events of viral infections, identifying distinct types of endosomal organelles, and clathrin-coated pits and vesicles with up to 95% accuracy and within seconds instead of weeks. The fact that DeepSPT effectively extracts biological information from diffusion alone indicates that besides structure, motion encodes function at the molecular and subcellular level.