Anomalous diffusion of proteins due to molecular crowding

Can Electroactive Tracer Molecules Reveal Viscoelastic Structure by Measuring Non-Fickian Diffusion?

We find that viscous and viscoelastic fluids are distinguishable by gauging Non-Fickian diffusion of dissolved electroactive molecules. Typically, such fluids are differentiated by measuring the mean-squared-displacement <Δr2> of embedded tracer particles (~1 μm) diffusing over time (t). From the relationship <Δr2>=6Dtα (D=particle diffusivity), log plots of <Δr2>vs.tα reveal regimes encoded in the slope α. For Fickian diffusion α=1, whereas α<1 and α>1, indicate Non-Fickian sub- and super-diffusion, respectively. Here, we electrolyzed redox reporters as molecular tracers in selected fluids. The current (I) relationship I ∝ ${\propto }$ v1/2 (v=scan-rate) was recast as I2vs.1/tα to introduce α as Non-Fickian quantifier in log plots. When viscosity increased at high concentration of small-molecules, D for the redox reporter declined but α remained constant at ~1 (Fickian). In contrast, both D and α(<1) decreased in viscoelastic hydrogels confirming a molecular sub-diffusive regime. These results agree with particle microrheology on the same fluid types using optical methods that are inapplicable to molecules. By quantifying Non-Fickian diffusion of electroactive molecular tracers, our method can uncover diffusion-structure relationships to identify regulators in neurodegenerative liquid-solid transitions of protein aggregates. Unlike tracer particles, the diffusivity of tracer molecules is controlled by the applied potential and electrode size.

Quasi-Diffusion Imaging: Application to Ultra-High b-Value and Time-Dependent Diffusion Images of Brain Tissue

We demonstrate that quasi-diffusion imaging (QDI) is a signal representation that extends towards the negative power law regime. We evaluate QDI for in vivo human and ex vivo fixed rat brain tissue acrossb $$ b $$ -value ranges from 0 to 25,000 s mm-2, determine whether accurate parameter estimates can be acquired from clinically feasible scan times and investigate their diffusion time-dependence. Several mathematical properties of the QDI representation are presented. QDI describes diffusion magnetic resonance imaging (dMRI) signal attenuation by two fitting parameters within a Mittag-Leffler function (MLF). We present its asymptotic properties at low and highb $$ b $$ -values and define the inflection point (IP) above which the signal tends to a negative power law. To show that QDI provides an accurate representation of dMRI signal, we apply it to two human brain datasets (Dataset 1:0 ≤ b ≤ 15,000 $$ 0\le b\le \mathrm{15,000} $$ s mm-2; Dataset 2:0 ≤ b ≤ 17,800 $$ 0\le b\le \mathrm{17,800} $$  s mm-2) and an ex vivo fixed rat brain (Dataset 3:0 ≤ b ≤ 25,000 $$ 0\le b\le \mathrm{25,000} $$  s mm-2, diffusion times17.5 ≤ ∆ ≤ 200 $$ 17.5\le \Delta \le 200 $$  ms). A clinically feasible 4b $$ b $$ -value subset of Dataset 1 (0 ≤ b ≤ 15,000 $$ 0\le b\le \mathrm{15,000} $$  s mm-2) is also analysed (acquisition time 6 min and 16 s). QDI showed excellent fits to observed signal attenuation, identified signal IPs and provided an apparent negative power law. Stable parameter estimates were identified upon increasing the maximumb $$ b $$ -value of the fitting range to near and above signal IPs, suggesting QDI is a valid signal representation within in vivo and ex vivo brain tissue across largeb $$ b $$ -value ranges with multiple diffusion times. QDI parameters were accurately estimated from clinically feasible shorter data acquisition, and time-dependence was observed with parameters approaching a Gaussian tortuosity limit with increasing diffusion time. In conclusion, QDI provides a parsimonious representation of dMRI signal attenuation in brain tissue that is sensitive to tissue microstructural heterogeneity and cell membrane permeability.

Highly Optimized Simulation of Atomic Resolution Cell-Like Protein Environment

Computational approaches can provide details of molecular mechanisms in a crowded environment inside cells. Protein docking predicts stable configurations of molecular complexes, which correspond to deep energy minima. Systematic docking approaches, such as those based on fast Fourier transform (FFT), also map the entire intermolecular energy landscape by determining the position and depth of the full spectrum of the energy minima. Such mapping allows speeding up simulations by precalculating the intermolecular energy values. Our earlier study combined FFT docking with the Monte Carlo protocol, enabling simulation of cell-size, crowded protein systems with seconds, and longer trajectories at atomic resolution, several orders of magnitude longer than those achievable by alternative approaches. In this study, we present a further drastic extension of the modeling capabilities by parallelized implementation of the simulation protocol. The procedure was applied to a panel of Death Fold Domains that form nucleated polymers in human innate immune signaling, recapitulating their homooligomerization tendencies and providing insights into the molecular mechanisms of polymer nucleation. The parallelized protocol allows extension of the simulation trajectories by orders of magnitude beyond the previously reported implementation, reaching into the uncharted territory of atomic resolution simulation of cell-sized systems.

A macroscopically homogeneous lipid phase exhibits leaflet-specific lipid diffusion in a glass-supported lipid bilayer

Lipid bilayer is a building block of cellular membranes. Understanding the physicochemical properties of a lipid bilayer and their composition dependence is thus inevitable to infer the biological functions of lipids in cellular membranes. Here, we performed leaflet-specific lipid diffusion analysis to study the structural and dynamical properties of lipids on glass-supported lipid bilayers composed of dioleoyl phosphatidylcholine, dipalmitoyl phosphatidylcholine and cholesterol, especially focusing on the regions where a macroscopically homogeneous phase was observed in the ternary phase diagram. The data showed that the interleaflet coupling and the effect of the solid support were highly dependent on the lipid/cholesterol compositions. We also found a distinctive feature of leaflet-specific lipid diffusion in the region near the critical point. This observation was discussed in terms of the nanoscale heterogeneity.

Application of a UV-vis spectrometer to investigate the effect of dissolution media on the diffusivity of small molecules and proteins

To date, the commonly used methods for diffusion coefficient measurements have some hurdles that prevent them from being widely applied in pharmaceutical laboratories. This study aimed to modify a method developed by di Cagno et al. based on the use of a UV-Vis spectrometer and apply the method to investigate the effect of dissolution media on the diffusivity of small molecules and proteins. A total of five small molecules and two proteins in different aqueous media and polymer solutions were investigated in this study. By attaching a 3D-printed cover with an open slit to a standard UV-Vis cuvette, the incident UV light could only pass through the open slit to measure the local drug concentration. During the diffusion experiment, drug molecules diffused from the cuvette bottom to the slit. According to the concentration measured as a function of time, diffusion coefficient was calculated based on Fick's law of diffusion using the analytical and numerical approaches. As a result, diffusion coefficients could be accurately measured with high reproducibility. The results also suggested that different media could affect the diffusion coefficients of small molecules by < 10% and proteins by < 15%. Since the UV-Vis spectrometer is a routine instrument, this method can potentially be employed by many pharmaceutical laboratories for diffusion coefficient measurements.

Quest for space: Tenacity of DNA, Protein, and Lipid macromolecules in intracellular crowded environment

The biochemical processes in the cellular milieu involving biomacromolecular interaction usually occur in crowded and heterogeneous environments, impacting their structure, stability, and reactivity. The crowded environment in vivo is typically ignored for experimental investigations since the studies get complex due to intracellular biophysical interactions between nucleic acids, proteins, cellular membranes, and various cations/anions present in the cell. Thus, being a ubiquitous property of all cells, studying those biophysical aspects affecting biochemical processes under realistically crowded conditions is of prime importance. Crowders or crowding agents are usually exploited to mimic the in vivo conditions on interacting with such genomic species, revealing structural and functional changes resulting from excluded volume and soft interactions. In the last few years, studies including crowders of varied sizes have gained attention concerning the consequences of crowding agents on biomolecular structural transitions and stability. This review comprehensively summarizes macromolecular crowding, emphasizing the biophysical effects and contribution of soft interactions in the heterogeneous cellular environment.

Simulation Studies of Dynamical Heterogeneity in a Dense Two-Dimensional Dimer-Solvent System with Obstacles

A coarse-grained model of a two-dimensional colloidal suspension was designed. The model was athermal and, in addition, a lattice approximation was introduced. It consisted of solvent (monomer) molecules, dimer molecules, and immobile impenetrable obstacles that introduced additional heterogeneity into the system. Dynamic properties were determined by a Monte Carlo simulation using the dynamic lattice liquid simulation algorithm. It is shown that there is a range of obstacle concentrations in which different diffusion characteristics were observed for dimers and solvents. In the system studied, it is possible to define the ranges of concentrations of individual components (solvent, dimers, and obstacles), in which the nature of the movement of dimers and solvents is different (normal diffusion vs. subdiffusion). The ratio of diffusion coefficients of solvent molecules and dimers for short times does not depend on the concentration of obstacles, while for long times, the ratio increases but remains independent of the concentration of the dimer.

Mechanobiology of 3D cell confinement and extracellular crowding

Cells and tissues are often under some level of confinement, imposed by the microenvironment and neighboring cells, meaning that there are limitations to cell size, volume changes, and fluid exchanges. 3D cell culture, increasingly used for both single cells and organoids, inherently impose levels of confinement absent in 2D systems. It is thus key to understand how different levels of confinement influences cell survival, cell function, and cell fate. It is well known that the mechanical properties of the microenvironment, such as stiffness and stress relaxation, are important in activating mechanosensitive pathways, and these are responsive to confinement conditions. In this review, we look at how low, intermediate, and high levels of confinement modulate the activation of known mechanobiology pathways, in single cells, organoids, and tumor spheroids, with a specific focus on 3D confinement in microwells, elastic, or viscoelastic scaffolds. In addition, a confining microenvironment can drastically limit cellular communication in both healthy and diseased tissues, due to extracellular crowding. We discuss potential implications of extracellular crowding on molecular transport, extracellular matrix deposition, and fluid transport. Understanding how cells sense and respond to various levels of confinement should inform the design of 3D engineered matrices that recapitulate the physical properties of tissues.

Macromolecular crowding effects on protein dynamics

Macromolecular crowding experiments bridge the gap between in-vivo and in-vitro studies by mimicking some of the cellular complexities like high viscosity and limited space, while still manageable for experiments and analysis. Macromolecular crowding impacts all biological processes and is a focus of contemporary research. Recent reviews have highlighted the effect of crowding on various protein properties. One of the essential characteristics of protein is its dynamic nature; however, how protein dynamics get modulated in the crowded milieu has been largely ignored. This article discusses how protein translational, rotational, conformational, and solvation dynamics change under crowded conditions, summarizing key observations in the literature. We emphasize our research on microsecond conformational and water dynamics in crowded milieus and their impact on enzymatic activity and stability. Lastly, we provided our outlook on how this field might move forward in the future.

Structure and Dynamics of Water in Polysaccharide (Alginate) Solutions and Gels Explained by the Core-Shell Model

In both biological and engineered systems, polysaccharides offer a means of establishing structural stiffness without altering the availability of water. Notable examples include the extracellular matrix of prokaryotes and eukaryotes, artificial skin grafts, drug delivery materials, and gels for water harvesting. Proper design and modeling of these systems require detailed understanding of the behavior of water confined in pores narrower than about 1 nm. We use molecular dynamics simulations to investigate the properties of water in solutions and gels of the polysaccharide alginate as a function of the water content and polymer cross-linking. We find that a detailed understanding of the nanoscale dynamics of water in alginate solutions and gels requires consideration of the discrete nature of water. However, we also find that the trends in tortuosity, permeability, dielectric constant, and shear viscosity can be adequately represented using the "core-shell" conceptual model that considers the confined fluid as a continuum.

Deciphering the intracellular forces shaping mitochondrial motion

We propose a novel quantitative method to explore the forces affecting mitochondria within living cells in an almost non-invasive fashion. This new tool enables the detection of localized mechanical impulses on these organelles that occur amidst the stationary fluctuations caused by the thermal jittering in the cytoplasm. Recent experimental evidence shows that the action of mechanical forces has important effects on the dynamics, morphology and distribution of mitochondria in cells. In particular, their crosstalk with the cytoskeleton has been found to alter these organelles function; however, the mechanisms underlying this phenomenon are largely unknown. Our results highlight the different functions that cytoskeletal networks play in shaping mitochondrial dynamics. This work presents a novel technique to extend our knowledge of how the impact of mechanical cues can be quantified at the single organelle level. Moreover, this approach can be expanded to the study of other organelles or biopolymers.

Anomalous mass diffusion in a binary mixture and Rayleigh-Bénard instability

The onset of the Rayleigh-Bénard instability in a horizontal fluid layer is investigated by assuming the fluid as a binary mixture and the concentration buoyancy as the driving force. The focus of this study is on the anomalous diffusion phenomenology emerging when the mean squared displacement of molecules in the diffusive random walk is not proportional to time, as in the usual Fick's diffusion, but it is proportional to a power of time. The power-law model of anomalous diffusion identifies subdiffusion when the power-law index is smaller than unity, while it describes superdiffusion when the power-law index is larger than unity. This study reconsiders the stability analysis of the Rayleigh-Bénard problem by extending the governing equations to include the anomalous diffusion.

The Influence of Local Constraints on Solvent Motion in Polymer Materials

The influence of obstacles in the form of polymer chains on the diffusion of a low-molecular-weight solvent was the subject of this research. Studies were performed by computer simulations. A Monte Carlo model-the Dynamic Lattice Liquid algorithm-based on the idea of cooperative movements was used. The tested materials were polymer networks with an ideal structure (with a uniform mesh size) and real, irregular networks (with a non-uniform mesh size) obtained numerically by copolymerization. The diffusion of the solvent was analyzed in systems with a polymer concentration that did not exceed 16%. The influence of the polymer concentration and macromolecular architecture structure on the mobility and character of the motion of the solvent was discussed. The influence of irregular network morphology on solvent dynamics appeared to be significantly stronger than that of regular networks and star-like polymers.

Diffusion of proteins in crowded solutions studied by docking-based modeling

The diffusion of proteins is significantly affected by macromolecular crowding. Molecular simulations accounting for protein interactions at atomic resolution are useful for characterizing the diffusion patterns in crowded environments. We present a comprehensive analysis of protein diffusion under different crowding conditions based on our recent docking-based approach simulating an intracellular crowded environment by sampling the intermolecular energy landscape using the Markov Chain Monte Carlo protocol. The procedure was extensively benchmarked, and the results are in very good agreement with the available experimental and theoretical data. The translational and rotational diffusion rates were determined for different types of proteins under crowding conditions in a broad range of concentrations. A protein system representing most abundant protein types in the E. coli cytoplasm was simulated, as well as large systems of other proteins of varying sizes in heterogeneous and self-crowding solutions. Dynamics of individual proteins was analyzed as a function of concentration and different diffusion rates in homogeneous and heterogeneous crowding. Smaller proteins diffused faster in heterogeneous crowding of larger molecules, compared to their diffusion in the self-crowded solution. Larger proteins displayed the opposite behavior, diffusing faster in the self-crowded solution. The results show the predictive power of our structure-based simulation approach for long timescales of cell-size systems at atomic resolution.

Extreme dependence of dynamics on concentration in highly crowded polyelectrolyte solutions

Charge-carrying species, such as polyelectrolytes, are vital to natural and synthetic processes that rely on their dynamic behavior. Through single-particle tracking techniques, the diffusivity of individual polyelectrolyte chains and overall system viscosity are determined for concentrated polylysine solutions. These studies show scaling dependences of D ~ c-6.1 and η ~ c7.2, much stronger than theoretical predictions, drawing the applicability of power law fits into question. Similar trends are observed in concentrated solutions prepared at various pH and counterion conditions. These hindered system dynamics appear universal to polyelectrolyte systems and are attributed to the large effective excluded volumes of polyelectrolyte chains inducing glassy dynamics. The framework of the Vrentas-Duda free-volume theory is used to compare polyelectrolyte and neutral systems. Supported by this theory, excluding counterion mass from total polymer mass results in all environmental conditions collapsing onto a common trendline. These results are applicable to crowded biological systems, such as intracellular environments where protein mobility is strongly inhibited.

Distinct Sub- to Superdiffuse Insulin Granule Transport Behaviors in β-Cells Are Strongly Affected by Granule Age

Intracellular transport is a complex process that is difficult to describe by a single general model for motion. Here, we study the transport of insulin containing vesicles, termed granules, in live MIN6 cells. We characterize how the observed heterogeneity is affected by different intracellular factors by constructing a MIN6 cell line by CRISPR-CAS9 that constitutively expresses mCherry fused to insulin and is thus packaged in granules. Confocal microscopy imaging and single particle tracking of the granule transport provide long trajectories of thousands of single granule trajectories for statistical analysis. Mean squared displacement (MSD), angle correlation distribution, and step size distribution analysis allowed identifying five distinct granule transport subpopulations, from nearly immobile and subdiffusive to run-pause and superdiffusive. The subdiffusive subpopulation recapitulates the subordinated random walk we reported earlier (Tabei, 2013; ref 18). We show that the transport characteristics of the five subpopulations have a strong dependence on the age of insulin granules. The five subpopulations also reflect the effect of local microtubule and actin networks on transport in different cellular regions. Our results provide robust metrics to clarify the heterogeneity of granule transport and demonstrate the roles of microtubule versus actin networks with granule age since initial packaging in the Golgi.

Freestanding bilayer microscope for single-molecule imaging of membrane proteins

Integral membrane proteins (IMPs) constitute a large fraction of organismal proteomes, playing fundamental roles in physiology and disease. Despite their importance, the mechanisms underlying dynamic features of IMPs, such as anomalous diffusion, protein-protein interactions, and protein clustering, remain largely unknown due to the high complexity of cell membrane environments. Available methods for in vitro studies are insufficient to study IMP dynamics systematically. This publication introduces the freestanding bilayer microscope (FBM), which combines the advantages of freestanding bilayers with single-particle tracking. The FBM, based on planar lipid bilayers, enables the study of IMP dynamics with single-molecule resolution and unconstrained diffusion. This paper benchmarks the FBM against total internal reflection fluorescence imaging on supported bilayers and is used here to estimate ion channel open probability and to examine the diffusion behavior of an ion channel in phase-separated bilayers. The FBM emerges as a powerful tool to examine membrane protein/lipid organization and dynamics to understand cell membrane processes.

Diffusive lensing as a mechanism of intracellular transport and compartmentalization

While inhomogeneous diffusivity has been identified as a ubiquitous feature of the cellular interior, its implications for particle mobility and concentration at different length scales remain largely unexplored. In this work, we use agent-based simulations of diffusion to investigate how heterogeneous diffusivity affects the movement and concentration of diffusing particles. We propose that a nonequilibrium mode of membrane-less compartmentalization arising from the convergence of diffusive trajectories into low-diffusive sinks, which we call 'diffusive lensing,' is relevant for living systems. Our work highlights the phenomenon of diffusive lensing as a potentially key driver of mesoscale dynamics in the cytoplasm, with possible far-reaching implications for biochemical processes.

Corneal fibrosis: From in vitro models to current and upcoming drug and gene medicines

Fibrotic diseases are characterised by myofibroblast differentiation, uncontrolled pathological extracellular matrix accumulation, tissue contraction, scar formation and, ultimately tissue / organ dysfunction. The cornea, the transparent tissue located on the anterior chamber of the eye, is extremely susceptible to fibrotic diseases, which cause loss of corneal transparency and are often associated with blindness. Although topical corticosteroids and antimetabolites are extensively used in the management of corneal fibrosis, they are associated with glaucoma, cataract formation, corneoscleral melting and infection, imposing the need of far more effective therapies. Herein, we summarise and discuss shortfalls and recent advances in in vitro models (e.g. transforming growth factor-β (TGF-β) / ascorbic acid / interleukin (IL) induced) and drug (e.g. TGF-β inhibitors, epigenetic modulators) and gene (e.g. gene editing, gene silencing) therapeutic strategies in the corneal fibrosis context. Emerging therapeutical agents (e.g. neutralising antibodies, ligand traps, receptor kinase inhibitors, antisense oligonucleotides) that have shown promise in clinical setting but have not yet assessed in corneal fibrosis context are also discussed.

Dissipative systems fractionally coupled to a bath

Quantum diffusion is a major topic in condensed-matter physics, and the Caldeira-Leggett model has been one of the most successful approaches to study this phenomenon. Here, we generalize this model by coupling the bath to the system through a Liouville fractional derivative. The Liouville fractional Langevin equation is then derived in the classical regime, without imposing a non-Ohmic macroscopic spectral function for the bath. By investigating the short- and long-time behavior of the mean squared displacement, we show that this model is able to describe a large variety of anomalous diffusion. Indeed, we find ballistic, sub-ballistic, and super-ballistic behavior for short times, whereas for long times, we find saturation and sub- and super-diffusion.

Contribution of different macromolecules to the diffusion of a 40 nm particle in Escherichia coli

Due to the high concentration of proteins, nucleic acids, and other macromolecules, the bacterial cytoplasm is typically described as a crowded environment. However, the extent to which each of these macromolecules individually affects the mobility of macromolecular complexes, and how this depends on growth conditions, is presently unclear. In this study, we sought to quantify the crowding experienced by an exogenous 40 nm fluorescent particle in the cytoplasm of E. coli under different growth conditions. By performing single-particle tracking measurements in cells selectively depleted of DNA and/or mRNA, we determined the contribution to crowding of mRNA, DNA, and remaining cellular components, i.e., mostly proteins and ribosomes. To estimate this contribution to crowding, we quantified the difference of the particle's diffusion coefficient in conditions with and without those macromolecules. We found that the contributions of the three classes of components were of comparable magnitude, being largest in the case of proteins and ribosomes. We further found that the contributions of mRNA and DNA to crowding were significantly larger than expected based on their volumetric fractions alone. Finally, we found that the crowding contributions change only slightly with the growth conditions. These results reveal how various cellular components partake in crowding of the cytoplasm and the consequences this has for the mobility of large macromolecular complexes.

Concentration-Dependent Diffusion of Monoclonal Antibodies: Underlying Mechanisms of Anomalous Diffusion

The development, storage, transport, and subcutaneous delivery of highly concentrated monoclonal antibody formulations pose significant challenges due to the high solution viscosity and low diffusion of the antibody molecules in crowded environments. These issues often stem from the self-associating behavior of the antibody molecules, potentially leading to aggregation. In this work, we used a dissipative particle dynamics-based coarse-grained model to investigate the diffusion behavior of IgG1 antibody molecules in aqueous solutions with 15 and 32 mM NaCl and antibody concentrations ranging from 10 to 400 mg/mL. We determined the coarse-grained interaction parameters by matching the calculated structure factor with the computational and experimental data from the literature. Our results indicate Fickian diffusion for antibody concentrations of 10 and 25 mg/mL and anomalous diffusion for concentrations exceeding 50 mg/mL. The anomalous diffusion was observed for ∼0.33 to 0.4 μs, followed by Fickian diffusion for all antibody concentrations. We observed a strong linear correlation between the diffusion behavior of the antibody molecules (diffusion coefficient D and anomalous diffusion exponent α) and the amount of aggregates present in the solution and between the amount of aggregates and the Coulomb interaction energy. The investigation of underlying mechanisms for anomalous diffusion revealed that in crowded environments at high antibody concentrations, the attractive interaction between electrostatically complementary regions of the antibody molecules could further bring the neighboring molecules closer to one another, ultimately resulting in aggregate formation. Further, the Coulomb attraction can continue to draw more molecules together, forming larger aggregates.

Activity-induced diffusion recovery in crowded colloidal suspensions

We show that the forces generated by active enzyme molecules are strong enough to influence the dynamics of their surroundings under artificial crowded environments. We measured the behavior of polymer microparticles in a quasi-two-dimensional system under aqueous environment, at various area fraction values of particles. In the presence of enzymatic activity, not only was the diffusion of the suspended particles enhanced at shorter time-scales, but the system also showed a transition from subdiffusive to diffusive dynamics at longer time-scale limits. Similar observations were also recorded with enzyme-functionalized microparticles. Brownian dynamics simulations have been performed to support the experimental observations.

Shaping active matter from crystalline solids to active turbulence

Active matter drives its constituent agents to move autonomously by harnessing free energy, leading to diverse emergent states with relevance to both biological processes and inanimate functionalities. Achieving maximum reconfigurability of active materials with minimal control remains a desirable yet challenging goal. Here, we employ large-scale, agent-resolved simulations to demonstrate that modulating the activity of a wet phoretic medium alone can govern its solid-liquid-gas phase transitions and, subsequently, laminar-turbulent transitions in fluid phases, thereby shaping its emergent pattern. These two progressively emerging transitions, hitherto unreported, bring us closer to perceiving the parallels between active matter and traditional matter. Our work reproduces and reconciles seemingly conflicting experimental observations on chemically active systems, presenting a unified landscape of phoretic collective dynamics. These findings enhance the understanding of long-range, many-body interactions among phoretic agents, offer new insights into their non-equilibrium collective behaviors, and provide potential guidelines for designing reconfigurable materials.

Influence of Cigarette Aerosol in Alpha-Synuclein Oligomerization and Cell Viability in SH-SY5Y: Implications for Parkinson's Disease

Although cigarette aerosol exposure is associated with various adverse health issues, its impact on Parkinson's disease (PD) remains elusive. Here, we investigated the effect of cigarette aerosol extract (CAE) on SH-SY5Y cells for the first time, both with and without α-synuclein (α-Syn) overexpression. We found that α-Syn aggravates CAE-induced cell death, oxidative stress, and mitochondrial dysfunction. Fluorescence cross-correlation spectroscopy (FCCS) revealed a dual distribution of α-Syn within the cells, with homogeneous regions indicative of monomeric α-Syn and punctated regions, suggesting the formation of oligomers. Moreover, we observed colocalization of α-Syn oligomers with lysosomes along with a reduction in autophagy activity. These findings suggest that α-Syn overexpression exacerbates CAE-induced intracellular cytotoxicity, mitochondrial dysfunction, and autophagy dysregulation, leading to elevated cell mortality. Our findings provide new insights into the pathogenic mechanisms linking exposure to cigarette aerosols with neurodegenerative diseases.

Multifractal spectral features enhance classification of anomalous diffusion

Anomalous diffusion processes, characterized by their nonstandard scaling of the mean-squared displacement, pose a unique challenge in classification and characterization. In a previous study [Mangalam et al., Phys. Rev. Res. 5, 023144 (2023)2643-156410.1103/PhysRevResearch.5.023144], we established a comprehensive framework for understanding anomalous diffusion using multifractal formalism. The present study delves into the potential of multifractal spectral features for effectively distinguishing anomalous diffusion trajectories from five widely used models: fractional Brownian motion, scaled Brownian motion, continuous-time random walk, annealed transient time motion, and Lévy walk. We generate extensive datasets comprising 10^{6} trajectories from these five anomalous diffusion models and extract multiple multifractal spectra from each trajectory to accomplish this. Our investigation entails a thorough analysis of neural network performance, encompassing features derived from varying numbers of spectra. We also explore the integration of multifractal spectra into traditional feature datasets, enabling us to assess their impact comprehensively. To ensure a statistically meaningful comparison, we categorize features into concept groups and train neural networks using features from each designated group. Notably, several feature groups demonstrate similar levels of accuracy, with the highest performance observed in groups utilizing moving-window characteristics and p varation features. Multifractal spectral features, particularly those derived from three spectra involving different timescales and cutoffs, closely follow, highlighting their robust discriminatory potential. Remarkably, a neural network exclusively trained on features from a single multifractal spectrum exhibits commendable performance, surpassing other feature groups. In summary, our findings underscore the diverse and potent efficacy of multifractal spectral features in enhancing the predictive capacity of machine learning to classify anomalous diffusion processes.

Molecular Crowding: The History and Development of a Scientific Paradigm

It is now generally accepted that macromolecules do not act in isolation but "live" in a crowded environment, that is, an environment populated by numerous different molecules. The field of molecular crowding has its origins in the far 80s but became accepted only by the end of the 90s. In the present issue, we discuss various aspects that are influenced by crowding and need to consider its effects. This Review is meant as an introduction to the theme and an analysis of the evolution of the crowding concept through time from colloidal and polymer physics to a more biological perspective. We introduce themes that will be more thoroughly treated in other Reviews of the present issue. In our intentions, each Review may stand by itself, but the complete collection has the aspiration to provide different but complementary perspectives to propose a more holistic view of molecular crowding.

Beyond microtubules: The cellular environment at the endoplasmic reticulum attracts proteins to the nucleus, enabling nuclear transport

All proteins are translated in the cytoplasm, yet many, including transcription factors, play vital roles in the nucleus. While previous research has concentrated on molecular motors for the transport of these proteins to the nucleus, recent observations reveal perinuclear accumulation even in the absence of an energy source, hinting at alternative mechanisms. Here, we propose that structural properties of the cellular environment, specifically the endoplasmic reticulum (ER), can promote molecular transport to the perinucleus without requiring additional energy expenditure. Specifically, physical interaction between proteins and the ER impedes their diffusion and leads to their accumulation near the nucleus. This result explains why larger proteins, more frequently interacting with the ER membrane, tend to accumulate at the perinucleus. Interestingly, such diffusion in a heterogeneous environment follows Chapman's law rather than the popular Fick's law. Our findings suggest a novel protein transport mechanism arising solely from characteristics of the intracellular environment.

Coherent light scattering from cellular dynamics in living tissues

This review examines the biological physics of intracellular transport probed by the coherent optics of dynamic light scattering from optically thick living tissues. Cells and their constituents are in constant motion, composed of a broad range of speeds spanning many orders of magnitude that reflect the wide array of functions and mechanisms that maintain cellular health. From the organelle scale of tens of nanometers and upward in size, the motion inside living tissue is actively driven rather than thermal, propelled by the hydrolysis of bioenergetic molecules and the forces of molecular motors. Active transport can mimic the random walks of thermal Brownian motion, but mean-squared displacements are far from thermal equilibrium and can display anomalous diffusion through Lévy or fractional Brownian walks. Despite the average isotropic three-dimensional environment of cells and tissues, active cellular or intracellular transport of single light-scattering objects is often pseudo-one-dimensional, for instance as organelle displacement persists along cytoskeletal tracks or as membranes displace along the normal to cell surfaces, albeit isotropically oriented in three dimensions. Coherent light scattering is a natural tool to characterize such tissue dynamics because persistent directed transport induces Doppler shifts in the scattered light. The many frequency-shifted partial waves from the complex and dynamic media interfere to produce dynamic speckle that reveals tissue-scale processes through speckle contrast imaging and fluctuation spectroscopy. Low-coherence interferometry, dynamic optical coherence tomography, diffusing-wave spectroscopy, diffuse-correlation spectroscopy, differential dynamic microscopy and digital holography offer coherent detection methods that shed light on intracellular processes. In health-care applications, altered states of cellular health and disease display altered cellular motions that imprint on the statistical fluctuations of the scattered light. For instance, the efficacy of medical therapeutics can be monitored by measuring the changes they induce in the Doppler spectra of livingex vivocancer biopsies.

Information Transmission via Molecular Communication in Astrobiological Environments

The ubiquity of information transmission via molecular communication between cells is comprehensively documented on Earth; this phenomenon might even have played a vital role in the origin(s) and early evolution of life. Motivated by these considerations, a simple model for molecular communication entailing the diffusion of signaling molecules from transmitter to receiver is elucidated. The channel capacity C (maximal rate of information transmission) and an optimistic heuristic estimate of the actual information transmission rate ℐ are derived for this communication system; the two quantities, especially the latter, are demonstrated to be broadly consistent with laboratory experiments and more sophisticated theoretical models. The channel capacity exhibits a potentially weak dependence on environmental parameters, whereas the actual information transmission rate may scale with the intercellular distance d as ℐ ∝ d-4 and could vary substantially across settings. These two variables are roughly calculated for diverse astrobiological environments, ranging from Earth's upper oceans (C ∼ 3.1 × 103 bits/s; ℐ ∼ 4.7 × 10-2 bits/s) and deep sea hydrothermal vents (C ∼ 4.2 × 103 bits/s; ℐ ∼ 1.2 × 10-1 bits/s) to the hydrocarbon lakes and seas of Titan (C ∼ 3.8 × 103 bits/s; ℐ ∼ 2.6 × 10-1 bits/s).

Multiple diffusive behaviors of the random walk in inhomogeneous environments

Anomalous diffusive behaviors are observed in highly inhomogeneous but relatively stable environments such as intracellular media and are increasingly attracting attention. In this paper we develop a coupled continuous-time random walk model in which the waiting time is power-law coupled with the local environmental diffusion coefficient. We provide two forms of the waiting time density, namely, a heavy-tailed density and an exponential density. For different waiting time densities, anomalous diffusions with the diffusion exponent between 0 and 2 and Brownian yet non-Gaussian diffusion can be realized within the present model. The diffusive behaviors are analyzed and discussed by deriving the mean-squared displacement and probability density function. In addition we derive the effective jump length density corresponding to the decoupled form to help distinguish the diffusion types. Our model unifies two kinds of anomalous diffusive behavior with different characteristics in the same inhomogeneous environment into a theoretical framework. The model interprets the random motion of particles in a complex inhomogeneous environment and reproduces the experimental results of different biological and physical systems.

Enhanced functionalities of immune cells separated by a microfluidic lattice: assessment based on holotomography

The isolation of white blood cells (WBCs) from whole blood constitutes a pivotal process for immunological studies, diagnosis of hematologic disorders, and the facilitation of immunotherapy. Despite the ubiquity of density gradient centrifugation in WBC isolation, its influence on WBC functionality remains inadequately understood. This research employs holotomography to explore the effects of two distinct WBC separation techniques, namely conventional centrifugation and microfluidic separation, on the functionality of the isolated cells. We utilize three-dimensional refractive index distribution and time-lapse dynamics to analyze individual WBCs in-depth, focusing on their morphology, motility, and phagocytic capabilities. Our observations highlight that centrifugal processes negatively impact WBC motility and phagocytic capacity, whereas microfluidic separation yields a more favorable outcome in preserving WBC functionality. These findings emphasize the potential of microfluidic separation techniques as a viable alternative to traditional centrifugation for WBC isolation, potentially enabling more precise analyses in immunology research and improving the accuracy of hematologic disorder diagnoses.

Entropy Production in a Fractal System with Diffusive Dynamics

We study the entropy production in a fractal system composed of two subsystems, each of which is subjected to an external force. This is achieved by using the H-theorem on the nonlinear Fokker-Planck equations (NFEs) characterizing the diffusing dynamics of each subsystem. In particular, we write a general NFE in terms of Hausdorff derivatives to take into account the metric of each system. We have also investigated some solutions from the analytical and numerical point of view. We demonstrate that each subsystem affects the total entropy and how the diffusive process is anomalous when the fractal nature of the system is considered.

Heterogeneous anomalous transport in cellular and molecular biology

It is well established that a wide variety of phenomena in cellular and molecular biology involve anomalous transport e.g. the statistics for the motility of cells and molecules are fractional and do not conform to the archetypes of simple diffusion or ballistic transport. Recent research demonstrates that anomalous transport is in many cases heterogeneous in both time and space. Thus single anomalous exponents and single generalised diffusion coefficients are unable to satisfactorily describe many crucial phenomena in cellular and molecular biology. We consider advances in the field ofheterogeneous anomalous transport(HAT) highlighting: experimental techniques (single molecule methods, microscopy, image analysis, fluorescence correlation spectroscopy, inelastic neutron scattering, and nuclear magnetic resonance), theoretical tools for data analysis (robust statistical methods such as first passage probabilities, survival analysis, different varieties of mean square displacements, etc), analytic theory and generative theoretical models based on simulations. Special emphasis is made on high throughput analysis techniques based on machine learning and neural networks. Furthermore, we consider anomalous transport in the context of microrheology and the heterogeneous viscoelasticity of complex fluids. HAT in the wavefronts of reaction-diffusion systems is also considered since it plays an important role in morphogenesis and signalling. In addition, we present specific examples from cellular biology including embryonic cells, leucocytes, cancer cells, bacterial cells, bacterial biofilms, and eukaryotic microorganisms. Case studies from molecular biology include DNA, membranes, endosomal transport, endoplasmic reticula, mucins, globular proteins, and amyloids.

Fractional and scaled Brownian motion on the sphere: The effects of long-time correlations on navigation strategies

We analyze fractional Brownian motion and scaled Brownian motion on the two-dimensional sphere S^{2}. We find that the intrinsic long-time correlations that characterize fractional Brownian motion collude with the specific dynamics (navigation strategies) carried out on the surface giving rise to rich transport properties. We focus our study on two classes of navigation strategies: one induced by a specific set of coordinates chosen for S^{2} (we have chosen the spherical ones in the present analysis), for which we find that contrary to what occurs in the absence of such long-time correlations, nonequilibrium stationary distributions are attained. These results resemble those reported in confined flat spaces in one and two dimensions [Guggenberger et al. New J. Phys. 21, 022002 (2019)1367-263010.1088/1367-2630/ab075f; Vojta et al. Phys. Rev. E 102, 032108 (2020)2470-004510.1103/PhysRevE.102.032108]; however, in the case analyzed here, there are no boundaries that affect the motion on the sphere. In contrast, when the navigation strategy chosen corresponds to a frame of reference moving with the particle (a Frenet-Serret reference system), then the equilibrium distribution on the sphere is recovered in the long-time limit. For both navigation strategies, the relaxation times toward the stationary distribution depend on the particular value of the Hurst parameter. We also show that on S^{2}, scaled Brownian motion, distinguished by a time-dependent diffusion coefficient with a power-scaling, is independent of the navigation strategy finding a good agreement between the analytical calculations obtained from the solution of a time-dependent diffusion equation on S^{2}, and the numerical results obtained from our numerical method to generate ensemble of trajectories.

Deubiquitination Detection of p53 Protein in Living Cells by Fluorescence Cross-Correlation Spectroscopy

Deubiquitination is a reverse post-translational modification of ubiquitination and plays significant roles in various signal transduction cascades and protein stability. The p53 is a very important tumor-suppressor protein and closely implicates more than 50% of human cancers. Although extracellular studies on the deubiquitination of p53 were reported, the process of p53 deubiquitination in living cells due to the shortage of an efficient in situ method for single living cells is still not clear. In this study, we described an in situ method for studying p53 deubiquitination in living cells by combining fluorescence cross-correlation spectroscopy with a fluorescent protein labeling technique. We first constructed the stable cell line expressing EGFP-Ub-p53-mCherry as the substrate of p53 deubiquitination. Then, we established a method for in situ monitoring of the deubiquitination of p53 in living cells. Based on the amplitudes of fluorescence correlation spectroscopy and fluorescence cross-correlation spectroscopy curves from living cells, we obtained the deubiquitination percentage for evaluating the level of p53 protein deubiquitination. Furthermore, we studied the effects of ubiquitin structures on p53 deubiquitination in living cells and found that the C-terminal Gly75-Gly76 motif of ubiquitin is a key location for p53 deubiquitination and the deubiquitination cannot occur when ubiquitin lacks the C-terminal Gly75-Gly76 motif. Our results documented that the developed strategy is an efficient method for in situ study of deubiquitination of proteins in living cells.

Protein translational diffusion as a way to detect intermolecular interactions

In this work, we analyze the information on the protein intermolecular interactions obtained from macromolecular diffusion. We have shown that the most hopeful results are given by our approach based on analysis of protein translational self-diffusion and collective diffusion obtained by dynamic light scattering and pulsed-field gradient NMR (PFG NMR) spectroscopy with the help of Vink's approach to analyze diffusion motion of particles by frictional formalism of non-equilibrium thermodynamics and the usage of the Derjaguin-Landau-Verwey-Overbeek (DLVO) theory of colloid particles interactions in electrolyte solutions. Early we have shown that integration of Vink's theory with DLVO provides a reliable basis for uniform interpreting of PFG NMR and DLS experiments on concentration dependence of diffusion coefficients. Basic details of theoretical and mathematical procedures and a broad analysis of experimental attestation of proposed conception on proteins of various structural form, size, and shape are presented. In the present review, the main capabilities of our approach obtain the details of intermolecular interactions of proteins with different shapes, internal structures, and mass. The universality of Vink's approach is experimentally shown, which gives the appropriate description of experimental results for proteins of complicated structure and shape.

Local and Large-Scale Conformational Dynamics in Unfolded Proteins and IDPs. I. Effect of Solvent Viscosity and Macromolecular Crowding

Protein/solvent interactions largely influence protein dynamics, particularly motions in unfolded and intrinsically disordered proteins (IDPs). Here, we apply triplet-triplet energy transfer (TTET) to investigate the coupling of internal protein motions to solvent motions by determining the effect of solvent viscosity (η) and macromolecular crowding on the rate constants of loop formation (kc) in several unfolded polypeptide chains including IDPs. The results show that the viscosity dependence of loop formation depends on amino acid sequence, loop length, and co-solute size. Below a critical size (rc), co-solutes exert a maximum effect, indicating that under these conditions microviscosity experienced by chain motions matches macroviscosity of the solvent. rc depends on chain stiffness and reflects the length scale of the chain motions, i.e., it is related to the persistence length. Above rc, the effect of solvent viscosity decreases with increasing co-solute size. For co-solutes typically used to mimic cellular environments, a scaling of kc ∝ η-0.1 is observed, suggesting that dynamics in unfolded proteins are only marginally modulated in cells. The effect of solvent viscosity on kc in the small co-solute limit (below rc) increases with increasing chain length and chain flexibility. Formation of long and very flexible loops exhibits a kc ∝ η-1 viscosity dependence, indicating full solvent coupling. Shorter and less flexible loops show weaker solvent coupling with values as low as kc ∝ η-0.75 ± 0.02. Coupling of formation of short loops to solvent motions is very little affected by amino acid sequence, but solvent coupling of long-range loop formation is decreased by side chain sterics.

Simulation Study on the Mechanism of Intermediate Subdiffusion of Diffusive Particles in Crowded Systems

The intermediate subdiffusion of diffusive particles in crowded systems is studied for two model systems: the continuous time random walk (CTRW) model and the obstruction-binding model. For the CTRW model with an arbitrarily given longest waiting time τmax, we find that the diffusive particle exhibits subdiffusion below τmax and recovers normal diffusion above τmax. For the obstruction-binding model with randomly distributed attractive obstacles, the diffusion of the diffusive particle is dependent on the binding energy and the density of obstacles. Interestingly, diffusion curves for different binding strengths can be overlapped by rescaling the simulation time, indicating that the diffusive particle in the obstruction-binding model can change from the intermediate subdiffusion to the normal diffusion at a long-term simulation scale. The results of the two model systems show that the diffusive particles only exhibit intermediate subdiffusion below the longest waiting time. Therefore, long timescale subdiffusion would only be observed in the CTRW model with an infinitely long waiting time and in the obstruction-binding model with an infinitely large binding strength.

Combined SPT and FCS methods reveal a mechanism of RNAP II oversampling in cell nuclei

Gene expression orchestration is a key question in fundamental and applied research. Different models for transcription regulation were proposed, yet the dynamic regulation of RNA polymerase II (RNAP II) activity remains a matter of debate. To improve our knowledge of this topic, we investigated RNAP II motility in eukaryotic cells by combining single particle tracking (SPT) and fluorescence correlation spectroscopy (FCS) techniques, to take advantage of their different sensitivities in order to analyze together slow and fast molecular movements. Thanks to calibrated samples, we developed a benchmark for quantitative analysis of molecular dynamics, to eliminate the main potential instrumental biases. We applied this workflow to study the diffusion of RPB1, the catalytic subunit of RNAP II. By a cross-analysis of FCS and SPT, we could highlight different RPB1 motility states and identifyed a stationary state, a slow diffusion state, and two different modes of subdiffusion. Interestingly, our analysis also unveiled the oversampling by RPB1 of nuclear subdomains. Based on these data, we propose a novel model of spatio-temporal transcription regulation. Altogether, our results highlight the importance of combining microscopy approaches at different time scales to get a full insight into the real complexity of molecular kinetics in cells.

Increased intracellular crowding during hyperosmotic stress

Hyperosmotic stress activates in live cells numerous processes and also promotes intracellular protein/RNA aggregation and phase separation. However, the time course and the extent of these changes remain largely uncharacterized. To investigate dynamic changes in intracellular macromolecular crowding (MMC) induced by hyperosmotic stress in live cells, we used fluorescence lifetime imaging microscopy and fluorescence correlation spectroscopy (FCS) to quantify changes in the local environment by measuring the fluorescence lifetime and the diffusion of the monomeric enhanced green fluorescent protein (eGFP), respectively. Real-time monitoring of eGFP fluorescence lifetime showed that a faster response to environmental changes due to MMC is observed than when measuring the acceptor/donor emission ratio using the MMC-sensitive Förster resonance energy transfer sensor (GimRET). This suggests that eGFP molecular electronic states and/or collision frequency are affected by changes in the immediate surroundings due to MMC without requiring conformational changes as is the case for the GimRET sensor. Furthermore, eGFP diffusion assessed by FCS indicated higher intracellular viscosity due to increased MMC during hyperosmotic stress. Our findings reveal that changes in eGFP fluorescence lifetime and diffusion are early indicators of elevated intracellular MMC. Our approach can therefore be used to reveal in live cells short-lived transient states through which MMC builds over time, which could not be observed when measuring changes in other physical properties that occur at slower time scales.

Molecular Dynamics Studies of the Ho(III) Aqua-tris(dibenzoylmethane) Complex: Role of Water Dynamics

The seven-coordinate Ho(III) aqua-tris(dibenzoylmethane)(DBM) complex, referred to as Ho-(DBM)₃·H₂O, was first reported in the late 1960s. It has a threefold symmetric structure, with Ho at the center of three dibenzoylmethane ligands and hydrogen-bonded water to ligands. It is considered that the hydrogen bonds between the water molecule and the ligands surrounding Ho play an important role in the formation of its symmetrical structure. In this work, we developed new force-field parameters for classical molecular dynamics (CMD) simulations to theoretically elucidate the structure and dynamics of Ho-(DBM)₃·H₂O. To develop the force field, structural optimization and molecular dynamics were performed on the basis of ab initio calculations using the plane-wave pseudopotential method. The force-field parameters for CMD were then optimized to reproduce the data obtained from ab initio calculations. Validation of the developed force field showed good agreement with the experimental crystalline structure and ab initio data. The vibrational properties of water in Ho-(DBM)₃·H₂O were investigated by comparison with bulk liquid water. The vibrational motion of water was found to have a characteristic mode originating from stationary rotational motion along the c-axis of Ho(III) aqua-tris(dibenzoylmethane). Contrary to expectations, the hydrogen-bond dynamics of water in Ho-(DBM)₃·H₂O were found to be almost equivalent to those of bulk liquid water except for librational motion. This development route for force-field parameters for CMD and the establishment of water dynamics can advance the understanding of water-coordinated metal complexes with high coordination numbers such as Ho-(DBM)₃·H₂O.

In vivo monitoring of the ubiquitination of newly synthesized proteins in living cells by combining a click reaction with fluorescence cross-correlation spectroscopy (FCCS)

Newly synthesized proteins are closely related to a series of biological processes, including cell growth, differentiation, and signaling. The post-translational modifications (PTMs) of newly synthesized proteins help maintain normal cellular functions. Ubiquitination is one of the PTMs and plays a prominent role in regulating cellular functions. Although great progress has been made in studying the ubiquitination of newly synthesized proteins, the in vivo monitoring of the ubiquitination of newly synthesized proteins in living cells still remains challenging. In this study, we propose a new method for measuring the ubiquitination of newly synthesized proteins in living cells by combining a click reaction with fluorescence cross-correlation spectroscopy (FCCS). In this study, a puromycin derivative (Puro-TCO) and a fluorescence probe (Bodipy-TR-Tz) were synthesized, and then, the newly synthesized proteins in living cells were labelled with Bodipy-TR via the click reaction between Puro-TCO and Tz. Ubiquitin (Ub) in living cells was labelled with the enhanced green fluorescence protein (EGFP) by fusion using a gene engineering technique. FCCS was used to quantify the newly synthesized proteins with two labels (EGFP and Bodipy-TR) in living cells. After measurements, the cross-correlation (CC) value was used to evaluate the ubiquitination degree of proteins. Herein, we established a method for monitoring the ubiquitination of newly synthesized proteins with EGFP-Ub in living cells and studied the effects of the ubiquitin E1 enzyme inhibitor on newly synthesized proteins. Our preliminary results document that the combination of FCCS with a click reaction is an efficient strategy for studying the ubiquitination of newly synthesized proteins in vivo in living cells. This new method can be applied to basic research in protein ubiquitination and drug screening at the living-cell level.

The Role of Polymer Chain Stiffness and Guest Nanoparticle Loading in Improving the Glass Transition Temperature of Polymer Nanocomposites

The impact of polymer chain stiffness characterized by the bending modulus (k_θ) on the glass transition temperature (T_g) of pure polymer systems, as well as polymer nanocomposites (PNCs), is investigated using molecular dynamics simulations. At small k_θ values, the pure polymer system and respective PNCs are in an amorphous state, whereas at large k_θ values, both systems are in a semicrystalline state with a glass transition at low temperature. For the pure polymer system, T_g initially increases with k_θ and does not change obviously at large k_θ. However, the T_g of PNCs shows interesting behaviors with the increasing volume fraction of nanoparticles (f_NP) at different k_θ values. T_g tends to increase with f_NP at small k_θ, whereas it becomes suppressed at large k_θ.

Vast heterogeneity in cytoplasmic diffusion rates revealed by nanorheology and Doppelgänger simulations

The cytoplasm is a complex, crowded, actively driven environment whose biophysical characteristics modulate critical cellular processes such as cytoskeletal dynamics, phase separation, and stem cell fate. Little is known about the variance in these cytoplasmic properties. Here, we employed particle-tracking nanorheology on genetically encoded multimeric 40 nm nanoparticles (GEMs) to measure diffusion within the cytoplasm of individual fission yeast (Schizosaccharomyces pombe) cellscells. We found that the apparent diffusion coefficients of individual GEM particles varied over a 400-fold range, while the differences in average particle diffusivity among individual cells spanned a 10-fold range. To determine the origin of this heterogeneity, we developed a Doppelgänger simulation approach that uses stochastic simulations of GEM diffusion that replicate the experimental statistics on a particle-by-particle basis, such that each experimental track and cell had a one-to-one correspondence with their simulated counterpart. These simulations showed that the large intra- and inter-cellular variations in diffusivity could not be explained by experimental variability but could only be reproduced with stochastic models that assume a wide intra- and inter-cellular variation in cytoplasmic viscosity. The simulation combining intra- and inter-cellular variation in viscosity also predicted weak nonergodicity in GEM diffusion, consistent with the experimental data. To probe the origin of this variation, we found that the variance in GEM diffusivity was largely independent of factors such as temperature, the actin and microtubule cytoskeletons, cell-cyle stage, and spatial locations, but was magnified by hyperosmotic shocks. Taken together, our results provide a striking demonstration that the cytoplasm is not "well-mixed" but represents a highly heterogeneous environment in which subcellular components at the 40 nm size scale experience dramatically different effective viscosities within an individual cell, as well as in different cells in a genetically identical population. These findings carry significant implications for the origins and regulation of biological noise at cellular and subcellular levels.

Phenotyping polarization dynamics of immune cells using a lipid droplet-cell pairing microfluidic platform

The immune synapse is the tight contact zone between a lymphocyte and a cell presenting its cognate antigen. This structure serves as a signaling platform and entails a polarization of intracellular components necessary to the immunological function of the cell. While the surface properties of the presenting cell are known to control the formation of the synapse, their impact on polarization has not yet been studied. Using functional lipid droplets as tunable artificial presenting cells combined with a microfluidic pairing device, we simultaneously observe synchronized synapses and dynamically quantify polarization patterns of individual B cells. By assessing how ligand concentration, surface fluidity, and substrate rigidity impact lysosome polarization, we show that its onset and kinetics depend on the local antigen concentration at the synapse and on substrate rigidity. Our experimental system enables a fine phenotyping of monoclonal cell populations based on their synaptic readout.

The Fokker-Planck equation of the superstatistical fractional Brownian motion with application to passive tracers inside cytoplasm

By collecting from literature data experimental evidence of anomalous diffusion of passive tracers inside cytoplasm, and in particular of subdiffusion of mRNA molecules inside live Escherichia coli cells, we obtain the probability density function of molecules' displacement and we derive the corresponding Fokker-Planck equation. Molecules' distribution emerges to be related to the Krätzel function and its Fokker-Planck equation to be a fractional diffusion equation in the Erdélyi-Kober sense. The irreducibility of the derived Fokker-Planck equation to those of other literature models is also discussed.