Intracellular Diffusion Research Articles

Revealing membrane integrity and cell size from diffusion kurtosis time dependence.

The nonmonotonic dependence of diffusion kurtosis on diffusion time has been observed in biological tissues, yet its relation to membrane integrity and cellular geometry remains to be clarified. Here we establish and explain the characteristic asymmetric shape of the kurtosis peak. We also derive the relation between the peak time , when kurtosis reaches its maximum, and tissue parameters. The peak shape and its position qualitatively follow from the adiabatic extension of the Kärger model onto the case of intra-cellular diffusivity time-dependence. This intuition is corroborated by the effective medium theory-based calculation, as well as by Monte Carlo simulations of diffusion and exchange in randomly and densely packed spheres for various values of permeability, cell fractions and sizes, and intrinsic diffusivity. We establish that is proportional to the geometric mean of two characteristic time scales: extra-cellular correlation time (determined by cell size) and intra-cellular residence time (determined by membrane permeability). When exchange is barrier-limited, the peak shape approaches a universal scaling form determined by the ratio . Numerical simulations and theory provide an interpretation of a specific feature of kurtosis time-dependence, offering a potential biomarker for in vivo evaluation of pathology by disentangling the functional (permeability) and structural (cell size) integrity in tissues. This is relevant as the time-dependent diffusion cumulants are sensitive to pathological changes in membrane integrity and cellular structure in diseases, such as ischemic stroke, tumors, and Alzheimer's disease.

Intracellular diffusion in the cytoplasm increases with cell size in fission yeast.

Diffusion in the cytoplasm can greatly impact cellular processes, yet regulation of macromolecular diffusion remains poorly understood. There is increasing evidence that cell size affects the density and macromolecular composition of the cytoplasm. Here, we studied whether cell size affects diffusion at the scale of macromolecules tens of microns in diameter. We analyzed the diffusive motions of intracellular genetically-encoded multimeric 40 nm nanoparticles (cytGEMs) in the cytoplasm of the fission yeast Schizosaccharomyces pombe . Using cell size mutants, we showed that cytGEMs diffusion coefficients decreased in smaller cells and increased in larger cells. This increase in diffusion in large cells may be due to a decrease in the DNA-to-Cytoplasm ratio, as diffusion was not affected in large multinucleate cytokinesis mutants. In investigating the underlying causes of altered cytGEMs diffusion, we found that the proteomes of large and small cells exhibited size-specific changes, including the sub-scaling of ribosomal proteins in large cells. Comparison with a similar dataset from human cells revealed that features of size-dependent proteome remodeling were conserved. These studies demonstrate that cell size is an important parameter in determining the biophysical properties and the composition of the cytoplasm.

Nonthermal fluctuations accelerate biomolecular motors

AbstractIntracellular transport is essential for maintaining cellular function. This process is driven by different mechanisms in prokaryotic and eukaryotic cells. In small prokaryotic cells, diffusion is the primary means of transport, while larger eukaryotic cells also rely on active transport by molecular motors such as kinesin and dynein. Recently, it has become evident that, in addition to diffusion based on thermal fluctuations (Brownian motion), which was conventionally considered a diffusion mechanism within living cells, nonthermal fluctuations generated by metabolic activities play a crucial role in intracellular diffusion. Similarly, while molecular motors have been proposed to exploit thermal fluctuations in the environment following the direct observation and manipulation of single molecules, they have also been reported to utilize nonthermal fluctuations in recent years. This review begins with a brief overview of the historical knowledge of diffusive intracellular transport, which has been extended from the thermal fluctuations to the nonthermal fluctuations generated by metabolic activity. It then introduces recent findings on how nonthermal fluctuations accelerate the motion of molecular motors and discusses future perspectives on the general effects of these fluctuations on molecules in living cells.

Quantitative Comparison of Monomeric StayGold Variants Using Protein Nanocages in Living Cells.

To standardize comparison of fluorescent proteins and independently determine which monomeric StayGold variant is best for live microscopy, we analyzed fluorescent protein tagged I3-01 peptides that self-assemble into stable sixty subunit dodecahedrons inside live cells. We find mStayGold is 3-fold brighter and 3-fold more photostable compared with EGFP and superior to other monomeric variants in mammalian cytoplasm. In addition, analysis of intracellular nanocage diffusion confirms the monomeric nature of mStayGold.

Quantum Dot-Based Three-Dimensional Single-Particle Tracking Characterizes the Evolution of Spatiotemporal Heterogeneity in Necrotic Cells.

Cell death is a fundamental biological process with different modes including apoptosis and necrosis. In contrast to programmed apoptosis, necrosis was previously considered disordered and passive, but it is now being realized to be under regulation by certain biological pathways. However, the intracellular dynamics that coordinates with cellular structure changes during necrosis remains unknown, limiting our understanding of the principles of necrosis. Here, we characterized the spatiotemporal intracellular diffusion dynamics in cells undergoing necrosis, using three-dimensional single-particle tracking of quantum dots. We found temporally increased diffusion rates in necrotic cells and spatially enhanced diffusion heterogeneity in the cell periphery, which could be attributed to the reduced molecular crowding resulting from cell swelling and peripheral blebbing, respectively. Moreover, the three-dimensional intracellular diffusion transits from strong anisotropy to nearly isotropy, suggesting a remodeling of the cytoarchitecture that relieves the axial constraint on intracellular diffusion during necrosis. Our results reveal the remarkable alterations of intracellular diffusion dynamics and biophysical properties in necrosis, providing insight into the well-organized nonequilibrium necrotic cell death from a biophysical perspective.

Mechanism of Biological Transport and Transformation of Copper, Cadmium, and Zinc in Water by Chlorella

This study investigates the effectiveness of Chlorella vulgaris in treating copper, cadmium, and zinc in aqueous solutions; the aim of this study was to examine the effects of various factors on the adsorption capacity of Chlorella in water. This study explored the intra- and extracellular adsorption and accumulation patterns of copper (Cu(II)), cadmium (Cd(II)), and zinc (Zn(II)), revealing their molecular response mechanisms under the most suitable conditions. The adsorption capacity of Chlorella to Cu(II), Cd(II), and Zn(II) in water was 93.63%, 73.45%, and 85.41%, respectively. The adsorption mechanism for heavy metals is governed by both intracellular and extracellular diffusion, with intracellular absorption serving as a supplement and external uptake predominating. XRD, XPS, FTIR, SEM-EDX, and TEM-EDX analyses showed that there would be the formation of precipitates such as Cu2S, CuS2, CdS, and ZnSO4. The adsorption of Cu(II) involves its simultaneous reduction to Cu(I). Moreover, specific functional groups present on the cellular surface, such as amino, carboxyl, aldehyde, and ether groups, interact with heavy metal ions. In view of its efficient heavy metal adsorption capacity and biosafety, this study recommends Chlorella as a potential biosorbent for the bioremediation and environmental treatment of heavy metal contaminated water in the future.

A data-driven intravoxel mean diffusivities distribution approach for molecular classifications and MIB-1 prediction of gliomas.

Measuring non-parametric intravoxel mean diffusivity distributions (MDDs) using magnetic resonance imaging (MRI) is a sensitive method for detecting intracellular diffusivity changes during physiological alterations. Histological and molecular glioma classifications are essential for prognosis and treatment, with distinct water diffusion dynamics among subtypes. We developed a data-driven approach using a fully connected network (FCN) to enhance the speed and stability of calculating MDDs across varying SNRs, enable tumor microstructural mapping, and test its reliability in identifying MIB-1 labeling index (LI) levels and molecular status of gliomas. An FCN was trained to learn the mapping between the simulated diffusion decay curves and the ground truth MDDs. We performed 5 000 000 simulation curves with various diffusivity components and random SNR . Eighty percent of simulation curves were used for the FCN training, 10% for validation, and the others were external tests for the FCN performance evaluation. In vivo data were collected to evaluate its clinical reliability. One hundred one patients (44 years 14, 67 men) with gliomas and six healthy controls underwent a 3.0 T MRI examination with a spin echo-echo planar imaging (SE-EPI) diffusion-weighted imaging (DWI) sequence. The trained FCN was employed to calculate MDDs of each brain voxel by voxel. We used the Fuzzy C-means algorithm to cluster the MDDs of tumor voxels, facilitating the characterization of distinct glioma tissues. Quantitative assessments were conducted through sectional integrals of the MDDs, demarcated by six bands to derive signal fractions ( ) and diffusivities of the maximum peaks ( ). Cosine similarity scores (CSS) were used for MDD similarity. ANOVA and Mann-Whitney U test were used for difference analysis. Logistic regression and area under the receiver operator characteristic curve (AUC) were used for classification evaluation. The simulation results showed that the FCN-based MDD approach (FCN-MDD) achieved higher CSS than non-negative least squares-based MDD (NNLS-MDD). For in vivo data, the spectra of ET and NET obtained by FCN-MDD are more distinguishable than NNLS-MDD. Fraction maps delineate the characteristics of different tumor tissues (enhancing and non-enhancing tumor, edema, and necrosis). showed a positive and negative correlation with MIB-1 respectively ( , all ). The AUC of for predicting MIB-1 LI levels was 0.900 (95% CI, 0.826-0.974), versus 0.781 (0.677-0.886) of ADC. The highest AUC of isocitrate dehydrogenase (IDH) mutation status, assessed by a logistic regression model ( ) was 0.873 (95% CI, 0.802-0.944). The proposed FCN-MDD method was more robust to variations in SNR and less reliant on empirically set regularization values than the NNLS-MDD method. FCN-MDD also enabled qualitative and quantitative evaluation of the composition of gliomas.

Prenatal and childhood air pollution exposure, cellular immune biomarkers, and brain connectivity in early adolescents

IntroductionAmbient air pollution is a neurotoxicant with hypothesized immune-related mechanisms. Adolescent brain structural and functional connectivity may be especially vulnerable to ambient pollution due to the refinement of large-scale brain networks during this period, which vary by sex and have important implications for cognitive, behavioral, and emotional functioning. In the current study we explored associations between air pollutants, immune markers, and structural and functional connectivity in early adolescence by leveraging cross-sectional sex-stratified data from the Adolescent Brain Cognitive Development℠ Study®. MethodsPollutant concentrations of fine particulate matter, nitrogen dioxide, and ozone were assigned to each child's primary residential address during the prenatal period and childhood (9-10 years-old) using an ensemble-based modeling approach. Data collected at 11-13 years-old included resting-state functional connectivity of the default mode, frontoparietal, and salience networks and limbic regions of interest, intracellular directional and isotropic diffusion of available white matter tracts, and markers of cellular immune activation. Using partial least squares correlation, a multivariate data-driven method that identifies important variables within latent dimensions, we investigated associations between 1) pollutants and structural and functional connectivity, 2) pollutants and immune markers, and 3) immune markers and structural and functional connectivity, in each sex separately. ResultsAir pollution exposure was related to white matter intracellular directional and isotropic diffusion at ages 11–13 years, but the direction of associations varied by sex. There were no associations between pollutants and resting-state functional connectivity at ages 11–13 years. Childhood exposure to nitrogen dioxide was negatively correlated with white blood cell count in males. Immune biomarkers were positively correlated with white matter intracellular directional diffusion in females and both white matter intracellular directional and isotropic diffusion in males. Lastly, there was a reliable negative correlation between lymphocyte-to-monocyte ratio and default mode network resting-state functional connectivity in females, as well as a compromised immune marker profile associated with lower resting-state functional connectivity between the salience network and the left hippocampus in males. In post-hoc exploratory analyses, we found that the PLSC-identified white matter tracts and resting-state networks related to processing speed and cognitive control performance from the NIH Toolbox. ConclusionsWe identified novel links between childhood nitrogen dioxide and cellular immune activation in males, and brain network connectivity and immune markers in both sexes. Future research should explore the potentially mediating role of immune activity in how pollutants affect neurological outcomes as well as the potential consequences of immune-related patterns of brain connectivity in service of improved brain health for all.

A mathematical model on the propagation of tau pathology in neurodegenerative diseases.

A system of partial differential equations is developed to study the spreading of tau pathology in the brain for Alzheimer's and other neurodegenerative diseases. Two cases are considered with one assuming intracellular diffusion through synaptic activities or the nanotubes that connect the adjacent cells. The other, in addition to intracellular spreading, takes into account of the secretion of the tau species which are able to diffuse, move with the interstitial fluid flow and subsequently taken up by the surrounding cells providing an alternative pathway for disease spreading. Cross membrane transport of the tau species are considered enabling us to examine the role of extracellular clearance of tau protein on the disease status. Bifurcation analysis is carried out for the steady states of the spatially homogeneous system yielding the results that fast cross-membrane transport combined with effective extracellular clearance is key to maintain the brain's healthy status. Numerical simulations of the first case exhibit solutions of travelling wave form describing the gradual outward spreading of the pathology; whereas the second case shows faster spreading with the buildup of neurofibrillary tangles quickly elevated throughout. Our investigation thus indicates that the gradual progression of the intracellular spreading case is more consistent with the clinical observations of the development of Alzheimer's disease.

Accelerated, physics-inspired inference of skeletal muscle microstructure from diffusion-weighted MRI.

Muscle health is a critical component of overall health and quality of life. However, current measures of skeletal muscle health take limited account of microstructural variations within muscle, which play a crucial role in mediating muscle function. To address this, we present a physics-inspired, machine learning-based framework for the non-invasive estimation of microstructural organization in skeletal muscle from diffusion-weighted MRI (dMRI) in an uncertainty-aware manner. To reduce the computational expense associated with direct numerical simulations of dMRI physics, a polynomial meta-model is developed that accurately represents the input/output relationships of a high-fidelity numerical model. This meta-model is used to develop a Gaussian process (GP) model that provides voxel-wise estimates and confidence intervals of microstructure organization in skeletal muscle. Given noise-free data, the GP model accurately estimates microstructural parameters. In the presence of noise, the diameter, intracellular diffusion coefficient, and membrane permeability are accurately estimated with narrow confidence intervals, while volume fraction and extracellular diffusion coefficient are poorly estimated and exhibit wide confidence intervals. A reduced-acquisition GP model, consisting of one-third the diffusion-encoding measurements, is shown to predict parameters with similar accuracy to the original model. The fiber diameter and volume fraction estimated by the reduced GP model is validated via histology, with both parameters accurately estimated, demonstrating the capability of the proposed framework as a promising non-invasive tool for assessing skeletal muscle health and function.

Asymptotic analysis of particle cluster formation in the presence of anchoring sites

The aggregation or clustering of proteins and other macromolecules plays an important role in the formation of large-scale molecular assemblies within cell membranes. Examples of such assemblies include lipid rafts, and postsynaptic domains (PSDs) at excitatory and inhibitory synapses in neurons. PSDs are rich in scaffolding proteins that can transiently trap transmembrane neurotransmitter receptors, thus localizing them at specific spatial positions. Hence, PSDs play a key role in determining the strength of synaptic connections and their regulation during learning and memory. Recently, a two-dimensional (2D) diffusion-mediated aggregation model of PSD formation has been developed in which the spatial locations of the clusters are determined by a set of fixed anchoring sites. The system is kept out of equilibrium by the recycling of particles between the cell membrane and interior. This results in a stationary distribution consisting of multiple clusters, whose average size can be determined using an effective mean-field description of the particle concentration around each anchored cluster. In this paper, we derive corrections to the mean-field approximation by applying the theory of diffusion in singularly perturbed domains. The latter is a powerful analytical method for solving two-dimensional (2D) and three-dimensional (3D) diffusion problems in domains where small holes or perforations have been removed from the interior. Applications range from modeling intracellular diffusion, where interior holes could represent subcellular structures such as organelles or biological condensates, to tracking the spread of chemical pollutants or heat from localized sources. In this paper, we take the bounded domain to be the cell membrane and the holes to represent anchored clusters. The analysis proceeds by partitioning the membrane into a set of inner regions around each cluster, and an outer region where mean-field interactions occur. Asymptotically matching the inner and outer stationary solutions generates an asymptotic expansion of the particle concentration, which includes higher-order corrections to mean-field theory that depend on the positions of the clusters and the boundary of the domain. Motivated by a recent study of light-activated protein oligomerization in cells, we also develop the analogous theory for cluster formation in a three-dimensional (3D) domain. The details of the asymptotic analysis differ from the 2D case due to the contrasting singularity structure of 2D and 3D Green’s functions.Graphical abstract2D model of diffusion-based protein cluster formation in the presence of anchoring cites and particle recycling. a A set of N anchoring sites at positions xj\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\ extbf{x}}_j$$\\end{document}, j=1,…,N\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$j=1,\\ldots ,N$$\\end{document}, in a bounded domain Ω\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\Omega $$\\end{document}. b Diffusing particles accumulate at the anchoring sites resulting in the formation of particle aggregates or clusters Uj\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${{\\mathcal {U}}}_j$$\\end{document}. c The clusters are dynamically maintained by a combination of lateral diffusion outside the clusters and particle recycling

HssS activation by membrane heme defines a paradigm for two-component system signaling in Staphylococcus aureus.

Strict management of intracellular heme pools, which are both toxic and beneficial, is crucial for bacterial survival during infection. The human pathogen Staphylococcus aureus uses a two-component heme sensing system (HssRS), which counteracts environmental heme toxicity by triggering expression of the efflux transporter HrtBA. The HssS heme sensor is a HisKA-type histidine kinase, characterized as a membrane-bound homodimer containing an extracellular sensor and a cytoplasmic conserved catalytic domain. To elucidate HssS heme-sensing mechanism, a structural simulation of the HssS dimer based on Alphafold2 was docked with heme. In this model, a heme-binding site is present in the HssS dimer between the membrane and extracellular domains. Heme is embedded in the membrane bilayer with its two protruding porphyrin propionates interacting with two conserved Arg94 and Arg163 that are located extracellularly. Single substitutions of these arginines and two highly conserved phenylalanines, Phe25 and Phe128, in the predicted hydrophobic pocket limited the ability of HssS to induce HrtBA synthesis. Combination of the four substitutions abolished HssS activation. Wild-type (WT) HssS copurified with heme from Escherichia coli, whereas heme binding was strongly attenuated in the variants. This study gives evidence that exogenous heme interacts with HssS at the membrane/extracellular interface to initiate HssS activation and induce HrtBA-mediated heme extrusion from the membrane. This "gatekeeper" mechanism could limit intracellular diffusion of exogenous heme in S. aureus and may serve as a paradigm for how efflux transporters control detoxification of exogenous hydrophobic stressors.IMPORTANCEIn the host blood, pathogenic bacteria are exposed to the red pigment heme that concentrates in their lipid membranes, generating cytotoxicity. To overcome heme toxicity, Staphylococcus aureus expresses a membrane sensor protein, HssS. Activation of HssS by heme triggers a phosphotransfer mechanism leading to the expression of a heme efflux system, HrtBA. This detoxification system prevents intracellular accumulation of heme. Our structural and functional data reveal a heme-binding hydrophobic cavity in HssS within the transmembrane domains (TM) helices at the interface with the extracellular domain. This structural pocket is important for the function of HssS as a heme sensor. Our findings provide a new basis for the elucidation of pathogen-sensing mechanisms as a prerequisite to the discovery of inhibitors.

Conduction velocity, G-ratio, and extracellular water as microstructural characteristics of autism spectrum disorder.

The neuronal differences contributing to the etiology of autism spectrum disorder (ASD) are still not well defined. Previous studies have suggested that myelin and axons are disrupted during development in ASD. By combining structural and diffusion MRI techniques, myelin and axons can be assessed using extracellular water, aggregate g-ratio, and a new approach to calculating axonal conduction velocity termed aggregate conduction velocity, which is related to the capacity of the axon to carry information. In this study, several innovative cellular microstructural methods, as measured from magnetic resonance imaging (MRI), are combined to characterize differences between ASD and typically developing adolescent participants in a large cohort. We first examine the relationship between each metric, including microstructural measurements of axonal and intracellular diffusion and the T1w/T2w ratio. We then demonstrate the sensitivity of these metrics by characterizing differences between ASD and neurotypical participants, finding widespread increases in extracellular water in the cortex and decreases in aggregate g-ratio and aggregate conduction velocity throughout the cortex, subcortex, and white matter skeleton. We finally provide evidence that these microstructural differences are associated with higher scores on the Social Communication Questionnaire (SCQ) a commonly used diagnostic tool to assess ASD. This study is the first to reveal that ASD involves MRI-measurable in vivo differences of myelin and axonal development with implications for neuronal and behavioral function. We also introduce a novel formulation for calculating aggregate conduction velocity, that is highly sensitive to these changes. We conclude that ASD may be characterized by otherwise intact structural connectivity but that functional connectivity may be attenuated by network properties affecting neural transmission speed. This effect may explain the putative reliance on local connectivity in contrast to more distal connectivity observed in ASD.

Role of protein kinase A and A kinase anchoring proteins in buffering and compartmentation of cAMP signalling in human airway smooth muscle cells.

In human airway smooth muscle (hASM) cells, not all receptors stimulating cAMP production elicit the same effects. This can only be explained if cAMP movement throughout the cell is restricted, yet the mechanisms involved are not fully understood. Phosphodiesterases (PDEs) contribute to compartmentation of many cAMP responses, but PDE activity alone is predicted to be insufficient if cAMP is otherwise freely diffusible. We tested the hypothesis that buffering of cAMP by protein kinase A (PKA) associated with A kinase anchoring proteins (AKAPs) slows cAMP diffusion and that this contributes to receptor-mediated, compartmentalized responses. Raster image correlation spectroscopy (RICS) was used to measure intracellular cAMP diffusion coefficients and evaluate the contribution of PKA-AKAP interactions. Western blotting and immunocytochemistry were used to identify the AKAPs involved. RNA interference was used to down-regulate AKAP expression and determine its effects on cAMP diffusion. Compartmentalized cAMP responses were measured using fluorescence resonance energy transfer (FRET) based biosensors. Cyclic AMP movement was significantly slower than that of free-diffusion in hASM cells, and disrupting PKA-AKAP interactions significantly increased the diffusion coefficient. PKA associated with the outer mitochondrial membrane appears to play a prominent role in this effect. Consistent with this idea, knocking down expression of D-AKAP2, the primary mitochondrial AKAP, increased cAMP diffusion and disrupted compartmentation of receptor-mediated responses. Our results confirm that AKAP-anchored PKA contributes to the buffering of cAMP and is consequential in the compartmentation of cAMP responses in hASM cells.

Investigating exchange, structural disorder, and restriction in gray matter via water and metabolites diffusivity and kurtosis time-dependence

Abstract Water diffusion-weighted MRI is a very powerful tool for probing tissue microstructure, but disentangling the contribution of compartment-specific structural disorder from cellular restriction and inter-compartment exchange remains an open challenge. In this work, we use diffusion-weighted MR spectroscopy (dMRS) of water and metabolite as a function of diffusion time in vivo in mouse gray matter to shed light on: i) which of these concomitant mechanisms (structural disorder, restriction, and exchange) dominates the MR measurements and ii) with which specific signature. We report the diffusion time-dependence of water with excellent SNR conditions as provided by dMRS, up to a very long diffusion time (500 ms). Water kurtosis decreases with increasing diffusion time, showing the concomitant influence of both structural disorder and exchange. However, despite the excellent experimental conditions, we were not able to clearly identify the nature of the structural disorder (i.e., 1D versus 2D/3D short-range disorder). Measurements of purely intracellular metabolites diffusion time-dependence (up to 500 ms) show opposite behavior to water, with metabolites kurtosis increasing as a function of diffusion time. We show that this is a signature of diffusion restricted in the intracellular space, from which cellular microstructural features such as soma’s and cell projections’ size can be estimated. Finally, by comparing water and metabolite diffusion time-dependencies, we attempt to disentangle the effect of intra/extracellular exchange and structural disorder of the extracellular space (both impacting water diffusion only). Our results suggest a relatively short intra/extracellular exchange time (~1-50 ms) and short-range disorder (still unclear if 1D or 2D/3D) most likely coming from the extracellular compartment. This work provides novel insights to help interpret water diffusion-time dependent measurements in terms of the underlying microstructure of gray matter and suggests that diffusion-time dependent measurements of intracellular metabolites may offer a new way to quantify microstructural restrictions in gray matter.

Single-Molecule Diffusivity Quantification Unveils Ubiquitous Net Charge-Driven Protein-Protein Interaction.

Recent microscopy and nuclear magnetic resonance (NMR) studies have noticed substantial suppression of intracellular diffusion for positively charged proteins, suggesting an overlooked role of electrostatic attraction in nonspecific protein interactions in a predominantly negatively charged intracellular environment. Utilizing single-molecule detection and statistics, here, we quantify in aqueous solutions how protein diffusion, in the limit of low diffuser concentration to avoid aggregate/coacervate formation, is modulated by differently charged interactor proteins over wide concentration ranges. We thus report substantially suppressed diffusion when oppositely charged interactors are added at parts per million levels, yet unvaried diffusivities when same-charge interactors are added beyond 1%. The electrostatic attraction-driven suppression of diffusion is sensitive to the protein net charge states, as probed by varying the solution pH and ionic strength or chemically modifying the proteins and is robust across different diffuser-interactor pairs. By converting the measured diffusivities to diffuser diameters, we further show that in the limit of excess interactors, a positively charged diffuser molecule effectively drags along just one monolayer of negatively charged interactors, where further interactions stop. We thus unveil ubiquitous, net charge-driven protein-protein interactions and shed new light on the mechanism of charge-based diffusion suppression in living cells.

Measurement of the rotational relaxation time of intracellular water in dried yeast and Jurkat cells by near infrared spectroscopy

Molecular mobility of intracellular water is a crucial parameter in the study of the mechanism of desiccation tolerance. As one of the parameters that reflecting molecular mobility, the viscosity of intracellular water has been found intimately related with the protection of the phospholipid membrane because it quantifies the diffusion ability of water and mass in the intracellular environment. In this work we measured the intracellular water relaxation time, which can be translated into water viscosity, by using a previously established NIR-dielectric method to monitor the drying process of baker's yeast and Jurkat cells with different desiccation tolerance. We found that intracellular saccharide can significantly decrease the intracellular water viscosity. Also, the intracellular water diffusion coefficient obtained from this method were found in good agreement with other reports.

Antibiotic resistance and phage sensitivity of topical listeriosis pathogens

Relevance. The problem of listeriosis infection continues to be relevant in epizootology and epidemiology. Resistance to eradication of Listeria spp. due to the ability of the bacterium to adapt and persist in various environments, as well as its intracellular location and weak intracellular diffusion of some antibiotics. Listeriosis refers to saprozoonoses, listeria often seed food products. As a pathogen of animal origin, Listeria is of concern not only from the point of view of public health and biosafety of products, but also as a causative agent of animal disease, leading to serious economic losses. The haphazard use of antibiotics to combat listeriosis has led to a change in the background of drug sensitivity. The aim of the work was to determine the antibiotic resistance of topical listeria strains and their sensitivity to bacteriophages to substantiate the prospects of phage treatments in the fight against listeriosis infection.Methods. The methodology is based on routine bacteriological studies, spot tests and sensitivity determination by the disco-diffusion method with 132 Listeria spp pathogens.Results. Multiple antibiotic resistance to fosfomycin, meropenem, cefotaxime, bacitracin, tylosin, cephalexin, polymyxin-B, lincomycin, benzylpenicillin, cefpirom, cefaclor and other drugs was noted. Listeria phagolysis was established by bacteriophages of our collection Lm1 (97.70%), Lm2 (96.20%). These bacteriophages are deposited in the collection of the Federal Scientific Centre VIEV. Thus, the aim of the study was to expand knowledge about listeriosis bacteriophages and their use as an effective method of prevention, treatment and control of listeriosis infections in the food and livestock industry.

Oncolytic Virus‐Like Nanoparticles for Tumor‐Specific Gene Delivery

AbstractNucleic acid drugs are widely used in biomedical fields. However, one of the main challenges in vivo is to selectively deliver nucleic acid drugs to subcellular compartments. To solve this problem, an oncolytic virus‐like nanoparticle, OV@FN, is constructed that can directly deliver nucleic acids to the cytoplasm through membrane fusion in response to the slightly acidic environment of the tumor. OV@FN is composed of a nano‐core (NA‐Zn@G) that can accurately release nucleic acids in response to high concentrations of glutathione in the cytoplasm of tumor cells and a hybrid membrane vesicle (FN) expressing oncolytic virus fusion membrane glycoprotein (mVSV‐G). The study findings suggest that OV@FN efficiently and selectively delivers nucleic acids to the cytoplasm of tumor cells, as compared to normal cells. Importantly, FN effectively induces tumor cells to form a syncytium, thus promoting intracellular drug diffusion, and enhancing the gene therapy effect. In vivo gene silencing test shows that OVsiR@FN has a significant nucleic acid delivery performance. In the melanoma model, the OV3pdsR@FN shows remarkable tumor ablation ability and improves the immunosuppressive microenvironment of the tumor site. OV@FN offers a novel approach to designing gene delivery and tumor therapy platforms.

Interplay Between Intracellular Transport Dynamics and Liquid‒Liquid Phase Separation.

Liquid‒liquid phase separation (LLPS) is a ubiquitous process in which proteins, RNA, and biomolecules assemble into membrane-less compartments, playing important roles in many biological functions and diseases. The current knowledge on the biophysical and biochemical principles of LLPS is largely from in vitro studies; however, the physiological environment in living cells is complex and not at equilibrium. The characteristics of intracellular dynamics and their roles in physiological LLPS remain to be resolved. Here, by using single-particle tracking of quantum dots and dynamic monitoring of the formation of stress granules (SGs) in single cells, the spatiotemporal dynamics of intracellular transport in cells undergoing LLPS are quantified. It is shown that intracellular diffusion and active transport are both reduced. Furthermore, the formation of SG droplets contributes to increased spatial heterogeneity within the cell. More importantly, the study demonstrated that the LLPS of SGs can be regulated by intracellular dynamics in two stages: the reduced intracellular diffusion promotes SG assembly and the microtubule-associated transport facilitates SG coalescences. The work on intracellular dynamics not only improves the understanding of the mechanism of physiology phase separations occurring in nonequilibrium environments but also reveals an interplay between intracellular dynamics and LLPS.