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HYPOTHESIS: In order to understand the basic mechanisms affecting emulsion stability, the intrinsic dynamics of the drop population must be investigated. We hypothesize that transient ballistic motion can serve as a marker of interactions between drops. In 1G conditions, buoyancy-induced drop motion obscures these interactions. The microgravity condition onboard the International Space Station enable this investigation. EXPERIMENTS: We performed Diffusing Wave Spectroscopy (DWS) experiments in the ESA Soft Matter Dynamics (SMD) facility. We used Monte Carlo simulations of photon trajectory to support data analysis. The analysis framework was validated by ground-based characterizations of the initial drop size distribution (DSD) and the properties of the oil/water interface in the presence of surfactant. FINDINGS: We characterized the drop size distribution and found to be bi-disperse. Drop dynamics shows transient ballistic features at early times, reaching a stationary regime of primarily diffusion-dominated motion. This suggests different ageing mechanisms: immediately after emulsification, the main mechanism is coalescence or aggregation between small drops. However at later times, ageing proceeds via coalescence or aggregation of small with large drops in some emulsions. Our results elucidate new processes relevant to emulsion stability with potential impact on industrial processes on Earth, as well as enabling technologies for space exploration.

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The dynamics of a driven superconducting vortex lattice in a two-dimensional (2D) periodic potential of square symmetry is studied using Brownian dynamics simulations. The range and strength of the vortex-substrate interaction are taken to be of the same order as that of the vortex-vortex interaction. The matching effect in a driven vortex lattice in the presence of a periodic array of pinning centers refers to the enhanced resistance to the vortex lattice motion when the ratio of the number of vortices to the number of pinning centers (called the filling fraction) takes simple fractional values. In particular, one expects a pronounced matching effect when the filling fraction is one. Contrary to this expectation, a drop in the vortex lattice mobility is observed as the filling fraction is increased from value one. This anti-matching effect can be understood in terms of the structural change in the vortex lattice as the filling fraction is varied. The dip observed in vortex mobility as a function of temperature when the filling fraction equals one (Joseph T 2020PhysicaA556124737), is studied for other values of filling above and below one. The behavior is found to persist for other fillings as well and is associated with the melting of the vortex lattice. The temperature at which the lattice melts is found to increase with drive and explains the shift in the temperature at which mobility is a minimum, locally.

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Computational models of cells cannot be considered complete unless they include the most fundamental process of life, the replication of genetic material. In a recent study, we presented a computational framework to model systems of replicating bacterial chromosomes as polymers at 10 bp resolution with Brownian dynamics. This approach was used to investigate changes in chromosome organization during replication and extend the applicability of an existing whole-cell model (WCM) for a genetically minimal bacterium, JCVI-syn3A, to the entire cell cycle. To achieve cell-scale chromosome structures that are realistic, we modeled the chromosome as a self-avoiding homopolymer with bending and torsional stiffnesses that capture the essential mechanical properties of dsDNA in Syn3A. Additionally, the polymer interacts with ribosomes distributed according to cryo-electron tomograms of Syn3A. The polymer model was further augmented by computational models of loop extrusion by structural maintenance of chromosomes (SMC) protein complexes and topoisomerase action, and the modeling and analysis of multi-fork replication states.

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Active fluids composed of constituents that are constantly driven away from thermal equilibrium can support spontaneous currents and can be engineered to have unconventional transport properties. Here, we report the emergence of (meta)stable traveling bands in computer simulations of aligning circle swimmers. These bands are different from polar flocks and, through coupling phase with mass transport, induce a bulk particle current with a component perpendicular to the propagation direction, thus giving rise to a collective Hall (or Magnus) effect. Traveling bands require sufficiently small orbits and undergo a discontinuous transition into a synchronized state with transient polar clusters for large orbital radii. Within a minimal hydrodynamic theory, we show that the bands can be understood as nondispersive soliton solutions fully accounting for the numerically observed properties.

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Mucus forms the first defense line of human lungs, and as such hampers the efficient delivery of therapeutics to the underlying epithelium. This holds particularly true for genetic cargo such as CRISPR-based gene editing tools which cannot readily surmount the mucosal barrier. While lipid nanoparticles (LNPs) emerge as versatile non-viral gene delivery systems that can help overcome the delivery challenge, many knowledge gaps remain, especially for diseased states such as cystic fibrosis (CF). This study provides fundamental insights into Cas9 mRNA or ribonucleoprotein-loaded LNP-mucus interactions in healthy and diseased states by assessing the impact of the genetic cargo, mucin sialylation, mucin concentration, ionic strength, pH, and polyethylene glycol (PEG) concentration and nature on LNP diffusivity leveraging experimental approaches and Brownian dynamics (BD) simulations. Taken together, this study identifies key mucus and LNP characteristics that are critical to enabling a rational LNP design for transmucosal delivery.

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In crowded fluids, polymer segments can exhibit anomalous subdiffusion due to the viscoelasticity of the surrounding environment. Previous single-particle tracking experiments revealed that such anomalous diffusion in complex fluids (e.g., in bacterial cytoplasm) can be described by fractional Brownian motion (fBm). To investigate how the viscoelastic media affects the diffusive behaviors of polymer segments without resolving single crowders, we developed a novel fractional Brownian dynamics method to simulate the dynamics of polymers under confinement. In this work, instead of using Gaussian random numbers ("white Gaussian noise") to model the Brownian force as in the standard Brownian dynamics simulations, we introduce fractional Gaussian noise (fGn) in our homemade fractional Brownian dynamics simulation code to investigate the anomalous diffusion of polymer segments by using a simple "bottle-brush"-type polymer model. The experimental results of the velocity autocorrelation function and the exponent that characterizes the subdiffusion of the confined polymer segments can be reproduced by this simple polymer model in combination with fractional Gaussian noise (fGn), which mimics the viscoelastic media.

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Methylene blue has multiple antiviral properties against Severe Acute Respiratory Syndrome-related Coronavirus 2 (SARS-CoV-2). The ability of methylene blue to inhibit different stages of the virus life cycle, both in light-independent and photodynamic processes, is used in clinical practice. At the same time, the molecular aspects of the interactions of methylene blue with molecular components of coronaviruses are not fully understood. Here, we use Brownian dynamics to identify methylene blue binding sites on the SARS-CoV-2 envelope. The local lipid and protein composition of the coronavirus envelope plays a crucial role in the binding of this cationic dye. Viral structures targeted by methylene blue include the S and E proteins and negatively charged lipids. We compare the obtained results with known experimental data on the antiviral effects of methylene blue to elucidate the molecular basis of its activity against coronaviruses.

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Many phenomena observed in synthetic and biological colloidal suspensions are dominated by the static interaction energies and the hydrodynamic interactions that act both between individual particles and also between colloids and macroscopic interfaces. This calls for methods that allow precise measurements of the corresponding forces. One method used for this purpose is total internal reflection microscopy (TIRM), which has been employed for around three decades to measure in particular the interactions between a single particle suspended in a liquid and a solid surface. However, given the importance of the observable variables, it is crucial to understand the possibilities and limitations of the method. In this paper, we investigate the influence of technically unavoidable noise effects and an inappropriate choice of particle size and sampling time on TIRM measurement results. Our main focus is on the measurement of diffusion coefficients and drift velocities, as the influence of error sources on dynamic properties has not been investigated so far. We find that detector shot noise and prolonged sampling times may cause erroneous results in the steep parts of the interaction potential where forces of the order of pico-Newtons or larger act on the particle, while the effect of background noise is negligible below certain thresholds. Furthermore, noise does not significantly affect dynamic data but we find that lengthy sampling times and/or probe particles with too small a radius will cause issues. Most importantly, we observe that dynamic results are very likely to differ from the standard hydrodynamic predictions for stick boundary conditions due to partial slip.

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Computational models of cells cannot be considered complete unless they include the most fundamental process of life, the replication and inheritance of genetic material. By creating a computational framework to model systems of replicating bacterial chromosomes as polymers at 10 bp resolution with Brownian dynamics, we investigate changes in chromosome organization during replication and extend the applicability of an existing whole-cell model (WCM) for a genetically minimal bacterium, JCVI-syn3A, to the entire cell-cycle. To achieve cell-scale chromosome structures that are realistic, we model the chromosome as a self-avoiding homopolymer with bending and torsional stiffnesses that capture the essential mechanical properties of dsDNA in Syn3A. In addition, the conformations of the circular DNA must avoid overlapping with ribosomes identitied in cryo-electron tomograms. While Syn3A lacks the complex regulatory systems known to orchestrate chromosome segregation in other bacteria, its minimized genome retains essential loop-extruding structural maintenance of chromosomes (SMC) protein complexes (SMC-scpAB) and topoisomerases. Through implementing the effects of these proteins in our simulations of replicating chromosomes, we find that they alone are sufficient for simultaneous chromosome segregation across all generations within nested theta structures. This supports previous studies suggesting loop-extrusion serves as a near-universal mechanism for chromosome organization within bacterial and eukaryotic cells. Furthermore, we analyze ribosome diffusion under the influence of the chromosome and calculate in silico chromosome contact maps that capture inter-daughter interactions. Finally, we present a methodology to map the polymer model of the chromosome to a Martini coarse-grained representation to prepare molecular dynamics models of entire Syn3A cells, which serves as an ultimate means of validation for cell states predicted by the WCM.

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An extensive review of literature simulations of quiescent polymer melts is given, considering results that test aspects of the Rouse model in the melt. We focus on Rouse model predictions for the mean-square amplitudes ⟨(Xp(0))2⟩ and time correlation functions ⟨Xp(0)Xp(t)⟩ of the Rouse mode Xp(t). The simulations conclusively demonstrate that the Rouse model is invalid in polymer melts. In particular, and contrary to the Rouse model, (i) mean-square Rouse mode amplitudes ⟨(Xp(0))2⟩ do not scale as sin-2(pπ/2N), N being the number of beads in the polymer. For small p (say, p≤3) ⟨(Xp(0))2⟩ scales with p as p-2; for larger p, it scales as p-3. (ii) Rouse mode time correlation functions ⟨Xp(t)Xp(0)⟩ do not decay with time as exponentials; they instead decay as stretched exponentials exp(-αtß). ß depends on p, typically with a minimum near N/2 or N/4. (iii) Polymer bead displacements are not described by independent Gaussian random processes. (iv) For p≠q, ⟨Xp(t)Xq(0)⟩ is sometimes non-zero. (v) The response of a polymer coil to a shear flow is a rotation, not the affine deformation predicted by Rouse. We also briefly consider the Kirkwood-Riseman polymer model.

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The Rouse model is the foundational basis of much of modern polymer physics. The period alternative, the Kirkwood-Riseman model, is rarely mentioned in modern monographs. The models are qualitatively different. The models do not agree as to how many internal modes a polymer molecule has. In the Kirkwood-Riseman model, polymers in a shear field perform whole-body rotation; in the Rouse model, polymers respond to shear with an affine deformation. We use Brownian dynamics to show that the Kirkwood-Riseman model for chain motion is qualitatively correct. Contrary to the Rouse model, in shear flow, polymer coils rotate. Rouse modes are cross-correlated. The amplitudes and relaxation rates of Rouse modes depend on the shear rate. Several alternatives to Rouse modes as collective coordinates are discussed.

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Viral variants of concern continue to arise for SARS-CoV-2, potentially impacting both methods for detection and mechanisms of action. Here, we investigate the effect of an evolving spike positive charge in SARS-CoV-2 variants and subsequent interactions with heparan sulfate and the angiotensin converting enzyme 2 (ACE2) in the glycocalyx. We show that the positively charged Omicron variant evolved enhanced binding rates to the negatively charged glycocalyx. Moreover, we discover that while the Omicron spike-ACE2 affinity is comparable to that of the Delta variant, the Omicron spike interactions with heparan sulfate are significantly enhanced, giving rise to a ternary complex of spike-heparan sulfate-ACE2 with a large proportion of double-bound and triple-bound ACE2. Our findings suggest that SARS-CoV-2 variants evolve to be more dependent on heparan sulfate in viral attachment and infection. This discovery enables us to engineer a second-generation lateral-flow test strip that harnesses both heparin and ACE2 to reliably detect all variants of concern, including Omicron.

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We argue in favour of developing a comprehensive dynamical theory for rationalizing, predicting, designing, and machine learning nonequilibrium phenomena that occur in soft matter. To give guidance for navigating the theoretical and practical challenges that lie ahead, we discuss and exemplify the limitations of dynamical density functional theory (DDFT). Instead of the implied adiabatic sequence of equilibrium states that this approach provides as a makeshift for the true time evolution, we posit that the pending theoretical tasks lie in developing a systematic understanding of the dynamical functional relationships that govern the genuine nonequilibrium physics. While static density functional theory gives a comprehensive account of the equilibrium properties of many-body systems, we argue that power functional theory is the only present contender to shed similar insights into nonequilibrium dynamics, including the recognition and implementation of exact sum rules that result from the Noether theorem. As a demonstration of the power functional point of view, we consider an idealized steady sedimentation flow of the three-dimensional Lennard-Jones fluid and machine-learn the kinematic map from the mean motion to the internal force field. The trained model is capable of both predicting and designing the steady state dynamics universally for various target density modulations. This demonstrates the significant potential of using such techniques in nonequilibrium many-body physics and overcomes both the conceptual constraints of DDFT as well as the limited availability of its analytical functional approximations.

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The genomic DNA of bacteria occupies only a fraction of the cell called the nucleoid, although it is not bounded by any membrane and would occupy a volume hundreds of times larger than the cell in the absence of constraints. The two most important contributions to the compaction of the DNA coil are the cross-linking of the DNA by nucleoid proteins (like H-NS and StpA) and the demixing of DNA and other abundant globular macromolecules which do not bind to the DNA (like ribosomes). The present work deals with the interplay of DNA-bridging proteins and globular macromolecular crowders, with the goal of determining the extent to which they collaborate in organizing the nucleoid. In order to answer this question, a coarse-grained model was developed and its properties were investigated through Brownian dynamics simulations. These simulations reveal that the radius of gyration of the DNA coil decreases linearly with the effective volume ratio of globular crowders and the number of DNA bridges formed by nucleoid proteins in the whole range of physiological values. Moreover, simulations highlight the fact that the number of DNA bridges formed by nucleoid proteins depends crucially on their ability to self-associate (oligomerize). An explanation for this result is proposed in terms of the mean distance between DNA segments and the capacity of proteins to maintain DNA-bridging in spite of the thermal fluctuations of the DNA network. Finally, simulations indicate that non-associating proteins preserve a high mobility inside the nucleoid while contributing to its compaction, leading to a DNA/protein complex which looks like a liquid droplet. In contrast, self-associating proteins form a little deformable network which cross-links the DNA chain, with the consequence that the DNA/protein complex looks more like a gel.

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Lipid mesophases are being intensively studied as potential candidates for drug-delivery purposes. Extensive experimental characterization has unveiled a wide palette of release features depending on the nature of the host lipids and of the guest molecule, as well as on the environmental conditions. However, only a few simulation works have addressed the matter, which hampers a solid rationalization of the richness of outcomes observed in experiments. Particularly, to date, there are no theoretical works addressing the impact of hydropathy on the transport of a molecule within lipid mesophases, despite the significant fraction of hydrophobic molecules among currently-available drugs. Similarly, the high heterogeneity of water mobility in the nanoscopic channels within lipid mesophases has also been neglected. To fill this gap, we introduce here a minimal model to account for these features in a lamellar geometry, and systematically study the role played by hydropathy and water-mobility heterogeneity by Brownian-dynamics simulations. We unveil a fine interplay between the presence of free-energy barriers, the affinity of the drug for the lipids, and the reduced mobility of water in determining the net molecular transport. More in general, our work is an instance of how multiscale simulations can be fruitfully employed to assist experiments in release systems based on lipid mesophases.

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Indoor propagation of airborne diseases is yet poorly understood. Here, we theoretically study a microscopic model based on the motions of virus particles in a respiratory microdroplet, responsible for airborne transmission of diseases, to understand their indoor propagation. The virus particles are driven by a driving force that mimics force due to gushing of air by devices like indoor air conditioning along with the gravity. A viral particle within the droplet experiences viscous drag due to the droplet medium, force due to interfacial tension at the droplet boundary, the thermal forces and mutual interaction forces with the other viral particles. We use Brownian Dynamics (BD) simulations and scaling arguments to study the motion of the droplet, given by that of the center of mass of the viral assembly. The BD simulations show that in presence of the gravity force alone, the time the droplet takes to reach the ground level, defined by the gravitational potential energy being zero, from a vertical height H,tf∼γ-0.1 dependence, where γ is the interfacial tension. In presence of the driving force of magnitude F0 and duration τ0, the horizontal propagation length, Ymax from the source increase linearly with τ0, where the slope is steeper for larger F0. Our scaling analysis explains qualitatively well the simulation observations and show long-distance transmission of airborne respiratory droplets in the indoor conditions due to F0 ∼ nano-dyne.

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A rationally designed gold-functionalized surface capable of capturing a target protein is presented using the biotin-streptavidin pair as a proof-of-concept. We carried out multiscale simulations to shed light on the binding mechanism of streptavidin on four differently biotinylated surfaces. Brownian Dynamics simulations were used to reveal the preferred initial orientation of streptavidin over the surfaces, whereas classical molecular dynamics was used to refine the binding poses and to investigate the fundamental forces involved in binding, and the binding kinetics. We assessed the binding events and the stability of the streptavidin attachment through a quartz crystal microbalance with dissipation monitoring (QCM-D). The sensing element comprises of biotinylated polyethylene glycol chains grafted on the sensor's gold surface via thiol-Au chemistry. Finally, we compared the results from experiments and simulations. We found that the confined biotin moieties can specifically capture streptavidin from the liquid phase and provide guidelines on how to exploit the microscopic parameters obtained from simulations to guide the design of further biosensors with enhanced sensitivity.

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The three-dimensional architecture of chromosomes, their arrangement, and dynamics within cell nuclei are still subject of debate. Obviously, the function of genomes-the storage, replication, and transcription of genetic information-has closely coevolved with this architecture and its dynamics, and hence are closely connected. In this work a scale-bridging framework investigates how of the 30 nm chromatin fibre organizes into chromosomes including their arrangement and morphology in the simulation of whole nuclei. Therefore, mainly two different topologies were simulated with corresponding parameter variations and comparing them to experiments: The Multi-Loop-Subcompartment (MLS) model, in which (stable) small loops form (stable) rosettes, connected by chromatin linkers, and the Random-Walk/Giant-Loop (RW/GL) model, in which large loops are attached to a flexible non-protein backbone, were simulated for various loop and linker sizes. The 30 nm chromatin fibre was modelled as a polymer chain with stretching, bending and excluded volume interactions. A spherical boundary potential simulated the confinement to nuclei with different radii. Simulated annealing and Brownian Dynamics methods were applied in a four-step decondensation procedure to generate from metaphase decondensated interphase configurations at thermodynamical equilibrium. Both the MLS and the RW/GL models form chromosome territories, with different morphologies: The MLS rosettes result in distinct subchromosomal domains visible in electron and confocal laser scanning microscopic images. In contrast, the big RW/GL loops lead to a mostly homogeneous chromatin distribution. Even small changes of the model parameters induced significant rearrangements of the chromatin morphology. The low overlap of chromosomes, arms, and subchromosomal domains observed in experiments agrees only with the MLS model. The chromatin density distribution in CLSM image stacks reveals a bimodal behaviour in agreement with recent experiments. Combination of these results with a variety of (spatial distance) measurements favour an MLS like model with loops and linkers of 63 to 126 kbp. The predicted large spaces between the chromatin fibres allow typically sized biological molecules to reach nearly every location in the nucleus by moderately obstructed diffusion and is in disagreement with the much simplified assumption that defined channels between territories for molecular transport as in the Interchromosomal Domain (ICD) hypothesis exist and are necessary for transport. All this is also in agreement with recent selective high-resolution chromosome interaction capture (T2C) experiments, the scaling behaviour of the DNA sequence, the dynamics of the chromatin fibre, the diffusion of molecules, and other measurements. Also all other chromosome topologies can in principle be excluded. In summary, polymer simulations of whole nuclei compared to experimental data not only clearly favour only a stable loop aggregate/rosette like genome architecture whose local topology is tightly connected to the global morphology and dynamics of the cell nucleus and hence can be used for understanding genome organization also in respect to diagnosis and treatment. This is in agreement with and also leads to a general novel framework of genome emergence, function, and evolution.

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