Search

We numerically study three-dimensional colonies of nonmotile stress-responsive bacteria growing under confining isotropic pressure in a nutrient-rich environment. We develop a novel simulation method to demonstrate how imposing an external pressure leads to a denser aggregate and strengthens the mechanical interactions between bacteria. Unlike rigid confinements that prevent bacterial growth, confining pressure acts as a soft constraint and allows colony expansion with a nearly linear long-term population growth and colony size. Enhancing the mechanosensitivity reduces instantaneous bacterial growth rates and the overall colony size, though its impact is modest compared to pressure for our studied set of biologically relevant parameter values. The doubling time grows exponentially at low mechanosensitivity or pressure in our bacterial growth model. We provide an analytical estimate of the doubling time and develop a population dynamics model consistent with our simulations. Our findings align with previous experimental results for E. coli colonies under pressure. Understanding the growth dynamics of stress-responsive bacteria under mechanical stresses provides insight into their adaptive response to varying environmental conditions., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2025 The Author(s). Published by Elsevier Inc. All rights reserved.)

Understanding and controlling microbial adhesion is a critical challenge in biomedical research, given the profound impact of bacterial infections on global health. Many facets of bacterial adhesion, including the distribution of adhesion forces across the cell wall, remain poorly understood. While a recent 'patchy colloid' model has shed light on adhesion in Gram-negative Escherichia coli cells, a corresponding model for Gram-positive cells has been elusive. In this study, we employ single cell force spectroscopy to investigate the adhesion force of Staphylococcus aureus . Normally, only one contact point of the entire bacterial surface is measured. However, by using a sine-shaped surface and recording force-distance curves along a path perpendicular to the rippled structures, we can characterize almost a hemisphere of one and the same bacterium. This unique approach allows us to study a greater number of contact points between the bacterium and the surface compared to conventional flat substrata. Distributed over the bacterial surface, we identify sites of higher and lower adhesion, which we call 'patchy adhesion', reminiscent of the patchy colloid model. The experimental results show that only some cells exhibit particularly strong adhesion at certain locations. To gain a better understanding of these locations, a geometric model of the bacterial cell surface was created. The experimental results were best reproduced by a model that features a few (5-6) particularly strong adhesion sites (diameter about 250 nm) that are widely distributed over the cell surface. Within the simulated patches, the number of molecules or their individual adhesive strength is increased. A more detailed comparison shows that simple geometric considerations for interacting molecules are not sufficient, but rather strong angle-dependent molecule-substratum interactions are required. We discuss the implications of our results for the development of new materials and the design and analysis of future studies.

Intracellular vesicular transport along cytoskeletal filaments ensures targeted cargo delivery. Such transport is rarely unidirectional but rather bidirectional, with frequent directional reversals owing to the simultaneous presence of opposite-polarity motors. So far, it has been unclear whether such complex motility pattern results from the sole mechanical interplay between opposite-polarity motors or requires regulators. Here, we demonstrate that a minimal system, comprising purified Dynein-Dynactin-BICD2 (DDB) and kinesin-3 (KIF16B) attached to large unilamellar vesicles, faithfully reproduces in vivo cargo motility, including runs, pauses, and reversals. Remarkably, opposing motors do not affect vesicle velocity during runs. Our computational model reveals that the engagement of a small number of motors is pivotal for transitioning between runs and pauses. Taken together, our results suggest that motors bound to vesicular cargo transiently engage in a tug-of-war during pauses. Subsequently, stochastic motor attachment and detachment events can lead to directional reversals without the need for regulators., (© 2023. The Author(s).)

Migration of immune cells within the human body allows them to fulfill their main function of detecting pathogens. We present experimental evidence showing the optimality of the search strategy of these cells, which is of crucial importance to achieve an efficient immune response. We find that the speed and directional persistence of migrating dendritic cells in our in vitro experiments are highly correlated, which enables them to reduce their search time. We introduce theoretically a new class of random search optimization problems by minimizing the mean first-passage time (MFPT) with respect to the strength of the coupling between influential parameters. We derive an analytical expression for the MFPT in a confined geometry and verify that the correlated motion enhances the search efficiency if the mean persistence length is sufficiently shorter than the confinement size. Our correlated search optimization approach provides an efficient searching recipe and predictive power in a broad range of correlated stochastic processes.

The maintenance of intracellular processes, like organelle transport and cell division, depend on bidirectional movement along microtubules. These processes typically require kinesin and dynein motor proteins, which move with opposite directionality. Because both types of motors are often simultaneously bound to the cargo, regulatory mechanisms are required to ensure controlled directional transport. Recently, it has been shown that parameters like mechanical motor activation, ATP concentration and roadblocks on the microtubule surface differentially influence the activity of kinesin and dynein motors in distinct manners. However, how these parameters affect bidirectional transport systems has not been studied. Here, we investigate the regulatory influence of these three parameters using in vitro gliding motility assays and stochastic simulations. We find that the number of active kinesin and dynein motors determines the transport direction and velocity, but that variations in ATP concentration and roadblock density have no significant effect. Thus, factors influencing the force balance between opposite motors appear to be important, whereas the detailed stepping kinetics and bypassing capabilities of the motors only have a small effect., Competing Interests: Competing interestsThe authors declare no competing or financial interests., (© 2020. Published by The Company of Biologists Ltd.)

Bacterial adhesion to surfaces is a crucial step in initial biofilm formation. In a combined experimental and computational approach, we studied the adhesion of the pathogenic bacterium Staphylococcus aureus to hydrophilic and hydrophobic surfaces. We used atomic force microscopy-based single-cell force spectroscopy and Monte Carlo simulations to investigate the similarities and differences of adhesion to hydrophilic and hydrophobic surfaces. Our results reveal that binding to both types of surfaces is mediated by thermally fluctuating cell wall macromolecules that behave differently on each type of substrate: on hydrophobic surfaces, many macromolecules are involved in adhesion, yet only weakly tethered, leading to high variance between individual bacteria, but low variance between repetitions with the same bacterium. On hydrophilic surfaces, however, only few macromolecules tether strongly to the surface. Since during every repetition with the same bacterium different macromolecules bind, we observe a comparable variance between repetitions and different bacteria. We expect these findings to be of importance for the understanding of the adhesion behaviour of many bacterial species as well as other microorganisms and even nanoparticles with soft, macromolecular coatings, used e.g. for biological diagnostics.

In eukaryotic cells, KDEL receptors (KDELRs) facilitate the retrieval of endoplasmic reticulum (ER) luminal proteins from the Golgi compartment back to the ER. Apart from the well-documented retention function, recent findings reveal that the cellular KDELRs have more complex roles, e.g. in cell signalling, protein secretion, cell adhesion and tumorigenesis. Furthermore, several studies suggest that a sub-population of KDELRs is located at the cell surface, where they could form and internalize KDELR/cargo clusters after K/HDEL-ligand binding. However, so far it has been unclear whether there are species- or cell-type-specific differences in KDELR clustering. By comparing ligand-induced KDELR clustering in different mouse and human cell lines via live cell imaging, we show that macrophage cell lines from both species do not develop any clusters. Using RT-qPCR experiments and numerical analysis, we address the role of KDELR expression as well as endocytosis and exocytosis rates on the receptor clustering at the plasma membrane and discuss how the efficiency of directed transport to preferred docking sites on the membrane influences the exponent of the power-law distribution of the cluster size., Competing Interests: The authors have declared that no competing interests exist.

Within cells, vesicles and proteins are actively transported several micrometers along the cytoskeletal filaments. The transport along microtubules is propelled by dynein and kinesin motors, which carry the cargo in opposite directions. Bidirectional intracellular transport is performed with great efficiency, even under strong confinement, as for example in the axon. For this kind of transport system, one would expect generically cluster formation. In this Letter, we discuss the effect of the recently observed self-enhanced binding affinity along the kinesin trajectories on the microtubule. We introduce a stochastic lattice-gas model, where the enhanced binding affinity is realized via a floor field. From Monte Carlo simulations and a mean-field analysis we show that this mechanism can lead to self-organized symmetry breaking and lane formation that indeed leads to efficient bidirectional transport in narrow environments.

Class II hydrophobins are amphiphilic proteins produced by filamentous fungi. One of their typical features is the tendency to accumulate at the interface between an aqueous phase and a hydrophobic phase, such as the air-water interface. The kinetics of the interfacial self-assembly of wild-type hydrophobins HFBI and HFBII and some of their engineered variants at the air-water interface were measured by monitoring the accumulated mass at the interface via nondestructive ellipsometry measurements. The resulting mass vs time curves revealed unusual kinetics for a monolayer formation that did not follow a typical Langmuir-type of behavior but had a rather coverage-independent rate instead. Typically, the full surface coverage was obtained at masses corresponding to a monolayer. The formation of multilayers was not observed. Atomic force microscopy revealed formation and growth of non-fusing protein clusters at the interface. The mechanism of the adsorption was studied by varying the structure or charges of the protein or the ionic strength of the subphase, revealing that the lateral interactions between the hydrophobins play a role in their interfacial assembly. Additionally, a theoretical model was introduced to identify the underlying mechanism of the unconventional adsorption kinetics.

Long-range intracellular transport is facilitated by motor proteins, such as kinesin-1 and cytoplasmic dynein, moving along microtubules (MTs). These motors often work in teams for the transport of various intracellular cargos. Although transport by multiple kinesin-1 motors has been studied extensively in the past, collective effects of cytoplasmic dynein are less well understood. On the level of single molecules, mammalian cytoplasmic dynein is not active in the absence of dynactin and adaptor proteins. However, when assembled into a team bound to the same cargo, processive motility has been observed. The underlying mechanism of this activation is not known. Here, we found that in MT gliding motility assays the gliding velocity increased with dynein surface density and MT length. Developing a mathematical model based on single-molecule parameters, we were able to simulate the observed behavior. Integral to our model is the usage of an activation term, which describes a mechanical activation of individual dynein motors when being stretched by other motors. We hypothesize that this activation is similar to the activation of single dynein motors by dynactin and adaptor proteins.This article has an associated First Person interview with the first author of the paper., Competing Interests: Competing interestsThe authors declare no competing or financial interests., (© 2018. Published by The Company of Biologists Ltd.)

We present a coarse-grained model for stochastic transport of noninteracting chemical signals inside neuronal dendrites and show how first-passage properties depend on the key structural factors affected by neurodegenerative disorders or aging: the extent of the tree, the topological bias induced by segmental decrease of dendrite diameter, and the trapping probabilities in biochemical cages and growth cones. We derive an exact expression for the distribution of first-passage times, which follows a universal exponential decay in the long-time limit. The asymptotic mean first-passage time exhibits a crossover from power-law to exponential scaling upon reducing the topological bias. We calibrate the coarse-grained model parameters and obtain the variation range of the mean first-passage time when the geometrical characteristics of the dendritic structure evolve during the course of aging or neurodegenerative disease progression (a few disorders for which clear trends for the pathological changes of dendritic structure have been reported in the literature are chosen and studied). We prove the validity of our analytical approach under realistic fluctuations of structural parameters by comparison to the results of Monte Carlo simulations. Moreover, by constructing local structural irregularities, we analyze the resulting influence on transport of chemical signals and formation of heterogeneous density patterns. Because neural functions rely on chemical signal transmission to a large extent, our results open the possibility of establishing a direct link between the disease progression and neural functions., (Copyright © 2018 Biophysical Society. Published by Elsevier Inc. All rights reserved.)

We consider the exclusion process on a ring with time-dependent defective bonds at which the hopping rate periodically switches between zero and one. This system models main roads in city traffics, intersecting with perpendicular streets. We explore basic properties of the system, in particular dependence of the vehicular flow on the parameters of signalization as well as the system size and the car density. We investigate various types of the spatial distribution of the vehicular density, and show existence of a shock profile. We also measure waiting time behind traffic lights, and examine its relationship with the traffic flow.

Cytoskeletal motor proteins are involved in major intracellular transport processes which are vital for maintaining appropriate cellular function. When attached to cytoskeletal filaments, the motor exhibits distinct states of motility: active motion along the filaments, and pause phase in which it remains stationary for a finite time interval. The transition probabilities between motion and pause phases are asymmetric in general, and considerably affected by changes in environmental conditions which influences the efficiency of cargo delivery to specific targets. By considering the motion of individual non-interacting molecular motors on a single filament as well as a dynamic filamentous network, we present an analytical model for the dynamics of self-propelled particles which undergo frequent pause phases. The interplay between motor processivity, structural properties of filamentous network, and transition probabilities between the two states of motility drastically changes the dynamics: multiple transitions between different types of anomalous diffusive dynamics occur and the crossover time to the asymptotic diffusive or ballistic motion varies by several orders of magnitude. We map out the phase diagrams in the space of transition probabilities, and address the role of initial conditions of motion on the resulting dynamics.

Many cellular processes are tightly connected to the dynamics of microtubules (MTs). While in neuronal axons MTs mainly regulate intracellular trafficking, they participate in cytoskeleton reorganization in many other eukaryotic cells, enabling the cell to efficiently adapt to changes in the environment. We show that the functional differences of MTs in different cell types and regions is reflected in the dynamic properties of MT tips. Using plus-end tracking proteins EB1 to monitor growing MT plus-ends, we show that MT dynamics and life cycle in axons of human neurons significantly differ from that of fibroblast cells. The density of plus-ends, as well as the rescue and catastrophe frequencies increase while the growth rate decreases toward the fibroblast cell margin. This results in a rather stable filamentous network structure and maintains the connection between nucleus and membrane. In contrast, plus-ends are uniformly distributed along the axons and exhibit diverse polymerization run times and spatially homogeneous rescue and catastrophe frequencies, leading to MT segments of various lengths. The probability distributions of the excursion length of polymerization and the MT length both follow nearly exponential tails, in agreement with the analytical predictions of a two-state model of MT dynamics.

Transmembrane receptor clustering is a ubiquitous phenomenon in pro- and eukaryotic cells to physically sense receptor/ligand interactions and subsequently translate an exogenous signal into a cellular response. Despite that receptor cluster formation has been described for a wide variety of receptors, ranging from chemotactic receptors in bacteria to growth factor and neurotransmitter receptors in mammalian cells, a mechanistic understanding of the underlying molecular processes is still puzzling. In an attempt to fill this gap we followed a combined experimental and theoretical approach by dissecting and modulating cargo binding, internalization and cellular response mediated by KDEL receptors (KDELRs) at the mammalian cell surface after interaction with a model cargo/ligand. Using a fluorescent variant of ricin toxin A chain as KDELR-ligand (eGFP-RTA(H/KDEL)), we demonstrate that cargo binding induces dose-dependent receptor cluster formation at and subsequent internalization from the membrane which is associated and counteracted by anterograde and microtubule-assisted receptor transport to preferred docking sites at the plasma membrane. By means of analytical arguments and extensive numerical simulations we show that cargo-synchronized receptor transport from and to the membrane is causative for KDELR/cargo cluster formation at the mammalian cell surface.

The adhesion of pathogenic bacteria to surfaces is of immense importance for health care applications. Via a combined experimental and computational approach, we studied the initiation of contact in the adhesion process of the pathogenic bacterium Staphylococcus aureus. AFM force spectroscopy with single cell bacterial probes paired with Monte Carlo simulations enabled an unprecedented molecular investigation of the contact formation. Our results reveal that bacteria attach to a surface over distances far beyond the range of classical surface forces via stochastic binding of thermally fluctuating cell wall proteins. Thereby, the bacteria are pulled into close contact with the surface as consecutive proteins of different stiffnesses attach. This mechanism greatly enhances the attachment capability of S. aureus. It, however, can be manipulated by enzymatically/chemically modifying the cell wall proteins to block their consecutive binding. Our study furthermore reveals that fluctuations in protein density and structure are much more relevant than the exact form of the binding potential.

The motion of self-propelled particles is modeled as a persistent random walk. An analytical framework is developed that allows the derivation of exact expressions for the time evolution of arbitrary moments of the persistent walk's displacement. It is shown that the interplay of step length and turning angle distributions and self-propulsion produces various signs of anomalous diffusion at short time scales and asymptotically a normal diffusion behavior with a broad range of diffusion coefficients. The crossover from the anomalous short-time behavior to the asymptotic diffusion regime is studied and the parameter dependencies of the crossover time are discussed. Higher moments of the displacement distribution are calculated and analytical expressions for the time evolution of the skewness and the kurtosis of the distribution are presented.

We theoretically study the transport properties of self-propelled particles on complex structures, such as motor proteins on filament networks. A general master equation formalism is developed to investigate the persistent motion of individual random walkers, which enables us to identify the contributions of key parameters: the motor processivity, and the anisotropy and heterogeneity of the underlying network. We prove the existence of different dynamical regimes of anomalous motion, and that the crossover times between these regimes as well as the asymptotic diffusion coefficient can be increased by several orders of magnitude within biologically relevant control parameter ranges. In terms of motion in continuous space, the interplay between stepping strategy and persistency of the walker is established as a source of anomalous diffusion at short and intermediate time scales.

We find a statistical mechanism that can adjust orientations of intracellular filaments to cell geometry in the absence of organizing centers. The effect is based on random and isotropic filament (de-)polymerization dynamics and is independent of filament interactions and explicit regulation. It can be understood by an analogy to electrostatics and appears to be induced by the confining boundaries; for periodic boundary conditions, no orientational bias emerges. Including active transport of particles, the model reproduces experimental observations of vesicle accumulations in transected axons.

The microtubule (MT) network, an important part of the cytoskeleton, is constantly remodeled by alternating phases of growth and shrinkage of individual filaments. Plus-end tracking proteins (+TIPs) interact with the MT and in many cases alter its dynamics. Although it is established that some +TIPs modify MT dynamics by increasing rescues, the plus-end tracking mechanism is still under debate. We present a model for MT dynamics in which a rescue factor is dynamically added to the filament during growth. As a consequence, the filament shows aging behavior that should be experimentally accessible and thus allow one to exclude some hypothesized models regarding the inclusion of rescue factors at the MT plus end. This result is not limited to +TIPs and can be extended to any kind of mechanism shifting the parameters of dynamic instability. Additionally, we show that the cell geometry has a strong influence on the quantitative results., (Copyright © 2011 Biophysical Society. Published by Elsevier Inc. All rights reserved.)

We study the stationary properties as well as the nonstationary dynamics of the one-dimensional partially asymmetric exclusion process with position-dependent random hop rates. Relating the hop rates to an energy landscape the stationary current J is determined by the largest barrier in a finite system of L sites and the corresponding waiting time tau approximately J{-1} is related to the waiting time of a single random walker, tau_{rw} , as tau approximately tau_{rw}{1/2} . The current is found to vanish as J approximately L{-z2} , where z is the dynamical exponent of the biased single-particle Sinai walk. Typical stationary states are phase separated: At the largest barrier almost all particles queue at one side and almost all holes are at the other side. The high-density (low-density) region is divided into approximately L{1/2} connected parts of particles (holes) which are separated by islands of holes (particles) located at the subleading barriers (valleys). We also study nonstationary processes of the system, like coarsening and invasion. Finally we discuss some related models, where particles of larger size or multiple occupation of lattice sites is considered.

We consider the one-dimensional partially asymmetric zero-range process where the hopping rates as well as the easy direction of hopping are random variables. For this type of disorder there is a condensation phenomenon in the thermodynamic limit: the particles typically occupy one single site and the fraction of particles outside the condensate is vanishing. We use extreme value statistics and an asymptotically exact strong disorder renormalization group method to explore the properties of the steady state. In a finite system of L sites the current vanishes as J approximately L(-z), where the dynamical exponent, z, is exactly calculated. For 0 < z < 1 the transport is realized by N(a) approximately L(1-z) active particles, which move with a constant velocity, whereas for z > 1 the transport is due to the anomalous diffusion of a single Brownian particle. Inactive particles are localized at a second special site and their number in rare realizations is macroscopic. The average density profile of inactive particles has a width of xi approximately delta(-2) in terms of the asymmetry parameter delta. In addition to this, we have investigated the approach to the steady state of the system through a coarsening process and found that the size of the condensate grows as n(L) approximately t(1/(1+z)) for large times. For the unbiased model z is formally infinite and the coarsening is logarithmically slow.

Based on a detailed microscopic test scenario motivated by recent empirical studies of single-vehicle data, several cellular automaton models for traffic flow are compared. We find three levels of agreement with the empirical data: (1) models that do not reproduce even qualitatively the most important empirical observations, (2) models that are on a macroscopic level in reasonable agreement with the empirics, and (3) models that reproduce the empirical data on a microscopic level as well. Our results are not only relevant for applications, but also shed light on the relevant interactions in traffic flow.

We present a detailed analysis of single-vehicle data, which sheds some light on the microscopic interaction of the vehicles. Besides the analysis of free flow and synchronized traffic the data sets especially provide information about wide jams that persist for a long time. The data have been collected at a location far away from ramps and in the absence of speed limits, which allows a comparison with idealized traffic simulations. We also resolve some open questions concerning the time-headway distribution.

It is shown that the desire for smooth and comfortable driving is directly responsible for the occurrence of synchronized traffic in highway traffic. This desire goes beyond the avoidance of accidents, which so far has been the main focus of microscopic modeling and that is mainly responsible for the other two phases observed empirically, free flow and wide moving jams. These features have been incorporated into a microscopic model based on stochastic cellular automata by means of event-driven anticipation. The results of computer simulations are compared with empirical data. It turns out that anticipation effects are responsible for the stabilization of the traffic phases and even reproduce the empirically observed coexistence of wide moving jams with both free flow and synchronized traffic.

We study the effect of metastability onto boundary induced phase transitions in a driven lattice gas. The phase diagram for open systems, parameterized by the input and output rates, consists of two regions corresponding to the free flow and jammed phase. Both have been entirely characterized. The microscopic states in the high density phase are shown to have an interesting striped structure, which undergoes a coarsening process and survives in the thermodynamic limit.

The glass transition can be viewed simply as the point at which the viscosity of a structurally disordered liquid reaches a universal threshold value. But this is an operational definition that circumvents fundamental issues, such as whether the glass transition is a purely dynamical phenomenon. If so, ergodicity gets broken (the system becomes confined to some part of its phase space), but the thermodynamic properties of the liquid remain unchanged across the transition, provided they are determined as thermodynamic equilibrium averages over the whole phase space. The opposite view claims that an underlying thermodynamic phase transition is responsible for the pronounced slow-down in the dynamics at the liquid-glass boundary. Such a phase transition would trigger the dynamic standstill, and then be masked by it. Here we perform Monte Carlo simulations of a two-dimensional system of polydisperse hard disks far within its glassy phase. The approach allows for non-local moves in a way that preserves micro-reversibility. We find no evidence for a thermodynamic phase transition up to very high densities; the glass is thus indistinguishable from the liquid on purely thermodynamic grounds.

Teddy bear/doll clinics continue to offer a feasible, effective opportunity to reach the community's children and their health information needs. Many thanks to Sunny B. Lee, RN, BS (Swedish Covenant Hospital, Chicago), and Kathy Powell, RN, PhD, and Barb Pierce, RN, MS (Children's Hospital, Birmingham).