arXiv subjects

Joachim O. Rädler

Publications and source records attributed to Joachim O. Rädler.

12 recordsLinked to original sources

arXiv2026

Inferring three-body interactions in cell migration dynamics

In active matter and living matter, such as clusters of migrating cells, collective dynamics emerges from the underlying interactions. A common assumption of theoretical descriptions of collective cell migration is that these interactions are pairwise additive. It remains unclear, however, if the dynamics of groups of cells is solely determined by pairwise interactions, or if higher-order interaction terms come into play. To investigate this question, we use time-lapse microscopy to record the dynamics of three cells interacting together in a linear three-site geometry. We collect a large number of cellular trajectories and develop an inference scheme to infer both pairwise and potential three-body cell-cell interactions. Our results reveal evidence of three-body interactions in one of the two cell lines tested. However, these three-body interactions only introduce minor corrections to the overall dynamics. Our work provides a methodology to infer the existence of three-body interactions from trajectory data, and supports the commonly assumed pairwise nature of cell-cell interactions.

physics.bio-ph↗

arXiv2025

Self-organized homogenization of flow networks

From the vasculature of animals to the porous media making up batteries, the core task of flow networks is to transport solutes and perfuse all cells or media equally with resources. Yet, living flow networks have a key advantage over porous media: they are adaptive and self-organize their geometry for homogeneous perfusion throughout the network. Here, we show that also artificial flow networks can self-organize toward homogeneous perfusion by the versatile adaption of controlled erosion. Flowing a pulse of cleaving enzyme through a network patterned into an erodible hydrogel, with initial channels disparate in width, we observe a homogenization in channel resistances. Experimental observations are matched with numerical simulations of the diffusion-advection-sorption dynamics of an eroding enzyme within a network. Analyzing transport dynamics theoretically, we show that homogenization only occurs if the pulse of the eroding enzyme lasts longer than the time it takes any channel to equilibrate to the pulse concentration. The equilibration time scale derived analytically is in agreement with simulations. Lastly, we show both numerically and experimentally that erosion leads to the homogenization of complex networks containing loops. Erosion being an omnipresent reaction, our results pave the way for a very versatile self-organized increase in the performance of porous media.

physics.bio-ph↗

arXiv2024

Intrinsic cell-to-cell variance from experimental single-cell motility data

When analyzing the individual positional dynamics of an ensemble of moving objects, the extracted parameters that characterize the motion of individual objects, such as the mean-squared instantaneous velocity or the diffusivity, exhibit a spread that is due to the convolution of three different effects: i) Motion stochasticity, caused by the fluctuating environment and enhanced by limited observation time, ii) measurement errors that depend on details of the detection technique, and iii) the intrinsic parameter variance that characterizes differences between individual objects, the quantity of ultimate interest. We develop the theoretical framework to separate these effects using the generalized Langevin equation (GLE), which constitutes the most general description of active and passive dynamics, as it derives from the general underlying many-body Hamiltonian for the studied system without approximations. We apply our methodology to determine intrinsic cell-to-cell differences of living human breast-cancer cells, algae cells and, as a benchmark, size differences of passively moving polystyrene beads in water. We find algae and human breast-cancer cells to exhibit significant individual differences, reflected by the spreading of the intrinsic mean-squared instantaneous velocity over two orders of magnitude, which is remarkable in light of the genetic homogeneity of the investigated breast-cancer cells and highlights their phenotypical diversity. Quantification of the intrinsic variance of single-cell properties is relevant for infection biology, ecology and medicine and opens up new possibilities to estimate population heterogeneity on the single-organism level in a non-destructive manner. Our framework is not limited to motility properties but can be readily applied to general experimental time-series data.

physics.bio-ph↗

arXiv2023

Geometry-sensitive protrusion growth directs confined cell migration

The migratory dynamics of cells can be influenced by the complex micro-environment through which they move. It remains unclear how the motility machinery of confined cells responds and adapts to their micro-environment. Here, we propose a biophysical mechanism for a geometry-dependent coupling between cellular protrusions and the nucleus that leads to directed migration. We apply our model to geometry-guided cell migration to obtain insights into the origin of directed migration on asymmetric adhesive micro-patterns and the polarization enhancement of cells observed under strong confinement. Remarkably, for cells that can choose between channels of different size, our model predicts an intricate dependence for cellular decision making as a function of the two channel widths, which we confirm experimentally.

physics.bio-ph↗

arXiv2022

Geometry adaptation of protrusion and polarity dynamics in confined cell migration

Cell migration in confining physiological environments relies on the concerted dynamics of several cellular components, including protrusions, adhesions with the environment, and the cell nucleus. However, it remains poorly understood how the dynamic interplay of these components and the cell polarity determine the emergent migration behavior at the cellular scale. Here, we combine data-driven inference with a mechanistic bottom-up approach to develop a model for protrusion and polarity dynamics in confined cell migration, revealing how the cellular dynamics adapt to confining geometries. Specifically, we use experimental data of joint protrusion-nucleus migration trajectories of cells on confining micropatterns to systematically determine a mechanistic model linking the stochastic dynamics of cell polarity, protrusions, and nucleus. This model indicates that the cellular dynamics adapt to confining constrictions through a switch in the polarity dynamics from a negative to a positive, self-reinforcing feedback loop. Our model further reveals how this feedback loop leads to stereotypical cycles of protrusion-nucleus dynamics that drive the migration of the cell through constrictions. These cycles are disrupted upon perturbation of cytoskeletal components, indicating that the positive feedback is controlled by cellular migration mechanisms. Our data-driven theoretical approach therefore identifies polarity feedback adaptation as a key mechanism in confined cell migration.

physics.bio-ph↗

arXiv2020

Learning the dynamics of cell-cell interactions in confined cell migration

The migratory dynamics of cells in physiological processes, ranging from wound healing to cancer metastasis, rely on contact-mediated cell-cell interactions. These interactions play a key role in shaping the stochastic trajectories of migrating cells. While data-driven physical formalisms for the stochastic migration dynamics of single cells have been developed, such a framework for the behavioral dynamics of interacting cells still remains elusive. Here, we monitor stochastic cell trajectories in a minimal experimental cell collider: a dumbbell-shaped micropattern on which pairs of cells perform repeated cellular collisions. We observe different characteristic behaviors, including cells reversing, following and sliding past each other upon collision. Capitalizing on this large experimental data set of coupled cell trajectories, we infer an interacting stochastic equation of motion that accurately predicts the observed interaction behaviors. Our approach reveals that interacting non-cancerous MCF10A cells can be described by repulsion and friction interactions. In contrast, cancerous MDA-MB-231 cells exhibit attraction and anti-friction interactions, promoting the predominant relative sliding behavior observed for these cells. Based on these experimentally inferred interactions, we show how this framework may generalize to provide a unifying theoretical description of the diverse cellular interaction behaviors of distinct cell types.

physics.bio-ph↗

arXiv2019

Disentangling the Behavioural Variability of Confined Cell Migration

Cell-to-cell variability is inherent to numerous biological processes, including cell migration. Quantifying and characterizing the variability of migrating cells is challenging, as it requires monitoring many cells for long time windows under identical conditions. Here, we observe the migration of single human breast cancer cells (MDA-MB-231) in confining two-state micropatterns. To describe the stochastic dynamics of this confined migration, we employ a dynamical systems approach. We identify statistics to measure the behavioural variance of the migration, which significantly exceed those predicted by a population-averaged stochastic model. This additional variance can be explained by the combination of an 'aging' process and population heterogeneity. To quantify population heterogeneity, we decompose the cells into subpopulations of slow and fast cells, revealing the presence of distinct classes of dynamical systems describing the migration, ranging from bistable to limit cycle behaviour. Our findings highlight the breadth of migration behaviours present in cell populations.

physics.bio-ph↗

arXiv2015

Shear-induced unfolding and enzymatic cleavage of full-length VWF multimers

Proteolysis of the multimeric blood coagulation protein von Willebrand Factor (VWF) by ADAMTS13 is crucial for prevention of microvascular thrombosis. ADAMTS13 cleaves VWF within the mechanosensitive A2 domain, which is believed to open under shear flow. Here, we combine Fluorescence Correlation Spectroscopy (FCS) and a microfluidic shear cell to monitor real-time kinetics of full-length VWF proteolysis as a function of shear stress. For comparison, we also measure the Michaelis-Menten kinetics of ADAMTS13 cleavage of wild-type VWF in the absence of shear but partially denaturing conditions. Under shear, ADAMTS13 activity on full-length VWF arises without denaturing agent as evidenced by FCS and gel-based multimer analysis. In agreement with Brownian hydrodynamics simulations, we find a sigmoidal increase of the enzymatic rate as a function of shear at a threshold shear rate 5522/s. The same flow-rate dependence of ADAMTS13 activity we also observe in blood plasma, which is relevant to predict hemostatic dysfunction.

physics.bio-ph↗

arXiv2015

Emergence and Persistence of Collective Cell Migration on Small Circular Micropatterns

The spontaneous formation of vortices is a hallmark of collective cellular activity. Here, we study the onset and persistence of coherent angular motion (CAMo) as a function of the number of cells $N$ confined in circular micropatterns. We find that the persistence of CAMo increases with $N$ but exhibits a pronounced discontinuity accompanied by a geometric rearrangement of cells to a configuration containing a central cell. Computer simulations based on a generalized Potts model reproduce the emergence of vortex states and show in agreement with experiment that their stability depends on the interplay of spatial arrangement and internal polarization of neighboring cells. Hence, the distinct migrational states in finite size ensembles reveal significant insight into the local interaction rules guiding collective migration.

physics.bio-ph↗

arXiv2010

Timing and dynamics of single cell gene expression in the arabinose utilization system

The arabinose utilization system of E. coli displays a stochastic "all or nothing" response at intermediate levels of arabinose, where the population divides into a fraction catabolizing the sugar at a high rate (ON state) and a fraction not utilizing arabinose (OFF state). Here we study this decision process in individual cells, focusing on the dynamics of the transition from the OFF to the ON state. Using quantitative time-lapse microscopy, we determine the time delay between inducer addition and fluorescence onset of a GFP reporter. Through independent characterization of the GFP maturation process, we can separate the lag time caused by the reporter from the intrinsic activation time of the arabinose system. The resulting distribution of intrinsic time delays scales inversely with the external arabinose concentration, and is compatible with a simple stochastic model for arabinose uptake. Our findings support the idea that the heterogeneous timing of gene induction is causally related to a broad distribution of uptake proteins at the time of sugar addition.

q-bio.MN↗

arXiv2010

Development of anomalous diffusion among crowding proteins

In cell membranes, proteins and lipids diffuse in a highly crowded and heterogeneous landscape, where aggregates and dense domains of proteins or lipids obstruct the path of diffusing molecules. In general, hindered motion gives rise to anomalous transport, though the nature of the onset of this behavior is still under debate and difficult to investigate experimentally. Here, we present a systematic study where proteins bound to supported lipid membranes diffuse freely in two dimensions, but are increasingly hindered by the presence of other like proteins. In our model system, the surface coverage of the protein avidin on the lipid bilayer is well controlled by varying the concentration of biotinylated lipid anchors. Using fluorescence correlation spectroscopy (FCS), we measure the time correlation function over long times and convert it to the mean-square displacement of the diffusing proteins. Our approach allows for high precision data and a clear distinction between anomalous and normal diffusion. It enables us to investigate the onset of anomalous diffusion, which takes place when the area coverage of membrane proteins increases beyond approximately 5%. This transition region exhibits pronounced spatial heterogeneities. Increasing the packing fraction further, transport becomes more and more anomalous, manifested in a decrease of the exponent of subdiffusion.

cond-mat.soft↗

arXiv2010

Predictive Modeling of Non-Viral Gene Transfer

In non-viral gene delivery, the variance of transgenic expression stems from the low number of plasmids successfully transferred. Here, we experimentally determine Lipofectamine- and PEI-mediated exogenous gene expression distributions from single cell time-lapse analysis. Broad Poisson-like distributions of steady state expression are observed for both transfection agents, when used with synchronized cell lines. At the same time, co-transfection analysis with YFP- and CFP-coding plasmids shows that multiple plasmids are simultaneously expressed, suggesting that plasmids are delivered in correlated units (complexes). We present a mathematical model of transfection, where a stochastic, two-step process is assumed, with the first being the low-probability entry step of complexes into the nucleus, followed by the subsequent release and activation of a small number of plasmids from a delivered complex. This conceptually simple model consistently predicts the observed fraction of transfected cells, the cotransfection ratio and the expression level distribution. It yields the number of efficient plasmids per complex and elucidates the origin of the associated noise, consequently providing a platform for evaluating and improving non-viral vectors.

q-bio.QM↗