Biology subjects

Metzler, R.

Publications and source records attributed to Metzler, R..

11 recordsLinked to original sources

bioRxiv2026

Loop statistics and fountain geometry reveal effective two-sided cohesin extrusion and crowding-induced arm desynchronization

Cohesin-driven loop extrusion shapes chromosome organization, yet what determines loop lengths and coordination between the extruding arms in vivo remains unclear. Broad extrusion "fountains" in Hi-C maps point to arm desynchronization, whose physical origin is unknown. Here we develop a kinetic theory of extrusion through transient chromatin roadblocks and neighbouring cohesins. Roadblock abundance, lifetime and partial permeability, together with cohesin crowding, combine into an effective obstacle density that renormalizes processivity and sets the mean loop length. Full loop-length distributions reveal extrusion symmetry: one-sided extrusion remains exponential, whereas effectively two-sided extrusion can generate a finite-length peak. ChIA-PET and MNase HiChIP data match the two-sided predictions, disfavouring purely one-sided extrusion. Cohesin crowding further desynchronizes the arms while leaving a residual correlation approaching {rho}=1/4. Fountain anisotropy across three vertebrates yields correlations near this value, consistent with local cohesin crowding as a sufficient mechanism for fountain formation. Fits further reveal 30-100-kb cohesin-loading regions and, in Danio rerio, a loading width comparable to the extent of enhancer enrichment, motivating a model in which an enhancer-rich loading platform acts as a collective barrier sustaining outward extrusion toward surrounding promoters. Our framework shows how cohesin and roadblock kinetics jointly determine loop statistics, shape chromosome-contact patterns, and may facilitate enhancer-promoter search.

biophysics↗

bioRxiv2025

Exploring the bistable equilibrium of methylated CpG DNA recognition by the MBD2 protein

Methyl-CpG binding domain 2 (MBD2) is a critical epigenetic regulator that selectively binds methylated CpG dinucleotides, key marks controlling gene regulation and chromatin organization. Understanding the interactions and conformational dynamics underlying this high selectivity is essential to elucidate MBD2s regulatory role. Here, using extensive classical MD simulations totaling over 277 {micro}s, we explored the formation of the MBD2-mCpG recognition complex. By initially positioning MBD2 one base pair downstream of its target, we observed its transition to the target site within microseconds. Notably, upon binding, MBD2 adopts two distinct stable conformations: a primary state closely resembling the X-ray crystal structure, and a secondary state of reduced affinity that nevertheless retains comparable selectivity for mCpG. Our results establish S189 as a key macro-switch; loss of its interaction with the methylcytosine backbone shifts the equilibrium toward the secondary state. This is corroborated by MD simulations of the S189A mutant, which preferentially adopts the secondary state-like conformation. Complementary NMR experiments confirm that S189A mutation does not alter mCpG selectivity, while fluorescence polarization measurements reveals a reduced binding affinity, consistent with our MD simulations results. Together, these findings indicate that MBD2 binding to methylated CpG involves a bistable equilibrium, providing new insights into how high affinity and adaptability are balanced in epigenetic recognition. In a broader context, our findings suggest that such alternative bound-state equilibria may represent an inherent feature of specific protein-DNA complexes.

molecular biology↗

bioRxiv2025

The Organization of Serotonergic Fibers in the Pacific Angelshark Brain: Neuroanatomical and Supercomputing Analyses

Serotonergic axons (fibers) are a universal feature of all vertebrate brains. They form meshworks, typically quantified with regional density measurements, and appear to support neuroplasticity. The self-organization of this system remains poorly understood, partly because of the strong stochasticity of individual fiber trajectories. In an extension to our previous analyses of the mouse brain, serotonergic fibers were investigated in the brain of the Pacific angelshark (Squatina californica), a representative of a unique (ray-like) lineage of the squalomorph sharks. First, the fundamental cytoarchitecture of the angelshark brain was examined, including the expression of ionized calcium binding adaptor molecule 1 (Iba1, AIF-1) and the mesencephalic trigeminal nucleus. Second, serotonergic fibers were visualized with immunohistochemistry, which showed that fibers in the forebrain have the tendency to move toward the dorsal pallium and also accumulate at higher densities at pial borders. Third, a population of serotonergic fibers was modeled inside a digital model of the angelshark brain by using a supercomputing simulation. The simulated fibers were defined as sample paths of fractional Brownian motion (FBM), a continuous-time stochastic process. The results reproduced key features of serotonergic fiber densities in the telencephalon, a brain division with a considerable physical uniformity and no major "obstacles" (dense axon tracts). The study provides further evidence that serotonergic fibers can be successfully modeled as paths of a rigorously-defined stochastic process, and that a rich repertoire of self-organizing behaviors can be produced by axons that are inherently stochastic but also respond to external forces.

neuroscience↗

bioRxiv2024

Controlled pH Alteration Enables Guanine Accumulation and Drives Crystallization within Iridosomes

Many animals exhibit remarkable colors produced by the constructive interference of light reflected from arrays of intracellular guanine crystals. These systems are utilized for various purposes, including vision, camouflage, communication, and thermal regulation. Each guanine crystal forms within a membrane-bound organelle called an iridosome, where precise control over crystal formation occurs. While the presence of guanine crystals in iridosomes is well-documented, the mechanisms facilitating the accumulation of water-insoluble guanine and driving its crystallization remain unclear. Here, we employ advanced imaging and spectroscopy techniques to characterize the maturation of iridosomes in zebrafish iridophores during development. Using cryo-electron microscopy, we found that amorphous guanine accumulates in early-stage iridosomes. Synchrotron-based soft X-ray microscopy studies revealed that, unlike mature crystals, the accumulated guanine is initially in its protonated state. Live imaging with a pH sensor demonstrated that early-stage iridosomes are acidic and that their pH gradually approaches neutrality during maturation. Additionally, the application of a V-ATPase inhibitor reduced the acidity of iridosomes and significantly decreased crystal formation, suggesting the involvement of V-ATPase in regulating the organelle pH. Our findings reveal new insights into the molecular mechanisms facilitating guanine accumulation and crystallization within iridosomes, emphasizing the pivotal role of pH alternations in the precise formation of biogenic crystals.

cell biology↗

bioRxiv2023

Predicting the Distribution of Serotonergic Axons: A Supercomputing Simulation of Reflected Fractional Brownian Motion in a 3D-Mouse Brain Model

The self-organization of the brain matrix of serotonergic axons (fibers) remains an unsolved problem in neuroscience. The regional densities of this matrix have major implications for neuroplasticity, tissue regeneration, and the understanding of mental disorders, but the trajectories of single fibers are strongly stochastic and require novel conceptual and analytical approaches. In a major extension to our previous studies, we used a supercomputing simulation to model 1000 serotonergic fibers as paths of superdiffusive fractional Brownian motion (FBM), a continuous-time stochastic process. The fibers produced long walks in a complex, threedimensional shape based on the mouse brain and reflected at the outer (pial) and inner (ventricular) boundaries. The resultant regional densities were compared to the actual fiber densities in the corresponding neuroanatomically-defined regions. The relative densities showed strong qualitative similarities in the forebrain and midbrain, demonstrating the predictive potential of stochastic modeling in this system. The current simulation does not respect tissue heterogeneities, but can be further improved with novel models of multifractional FBM. The study demonstrates that serotonergic fiber densities can be strongly influenced by the geometry of the brain, with implications for brain development, plasticity, and evolution.

neuroscience↗

bioRxiv2021

Non-Gaussian, transiently anomalous and ergodic self-diffusion of flexible dumbbells in crowded two-dimensional environments: coupled translational and rotational motions

We employ Langevin-dynamics simulations to unveil non-Brownian and non-Gaussian center-of-mass self-diffusion of massive flexible dumbbell-shaped particles in crowded two-dimensional solutions. We also study the intra-dumbbell dynamics due to the relative motion of the two constituent elastically-coupled disks. Our main focus is on effects of the crowding fraction{phi} and the particle structure on the diffusion characteristics. We evaluate the time-averaged mean-squared displacement (TAMSD), the displacement probability-density function (PDF) and the displacement autocorrelation function (ACF) of the dimers. For the TAMSD at highly crowded conditions of dumbbells, e.g., we observe a transition from the short-time ballistic behavior, via an intermediate subdiffusive regime, to long-time Brownian-like spreading dynamics. The crowded system of dimers exhibits two distinct diffusion regimes distinguished by the scaling exponent of the TAMSD, the dependence of the diffusivity on{phi} , and the features of the displacement-ACF. We attribute these regimes to a crowding-induced transition from a viscous to a viscoelastic diffusion medium upon growing{phi} . We also analyze the relative motion in the dimers, finding that larger{phi} suppress their vibrations and yield strongly non-Gaussian PDFs of rotational displacements. For the diffusion coefficients D({phi}) of translational and rotational motion of the dumbbells an exponential decay with{phi} for weak and a power-law D({phi}) {propto} ({phi} -{phi}[*] )2.4 for strong crowding is found. A comparison of simulation results with theoretical predictions for D({phi}) is discussed and some relevant experimental systems are overviewed.

biophysics↗

bioRxiv2021

Adsorption of Lysozyme Into a Charged Confining Pore

Several applications arise from the confinement of proteins on surfaces since their stability and biological activity are enhanced. It is also known that the way a protein adsorbs on the surface is important for its biological function since its active sites should not be obstructed. In this study, the adsorption properties of hen egg-white Lysozyme, HEWL, into a negatively charged silica pore is examined employing a coarse-grained model and constant-pH Monte Carlo simulations. The role of electrostatic interactions is taken into account when including the Debye-HAijckel potentials into the C structure-based model. We evaluate the effects of pH, salt concentration, and pore radius on the protein preferential orientation and spatial distribution of its residues regarding the pore surface. By mapping the residues that stay closer to the pore surface, we find the increase of pH leads to orientational changes of the adsorbed protein when the solution pH gets closer to the HEWL isoelectric point. At these conditions, the pKa shift of these important residues caused by the adsorption into the charged confining surface results in a HEWL charge distribution that stabilizes the adsorption in the observed protein orientation. We compare our observations to the results of pKa shift for HEWL available in the literature and to some experimental data.

biophysics↗

bioRxiv2021

Inertia triggers nonergodicity of fractional Brownian motion

How related are the ergodic properties of the over- and underdamped Langevin equations driven by fractional Gaussian noise? We here find that for massive particles performing fractional Brownian motion (FBM) inertial effects not only destroy the stylized fact of the equivalence of the ensemble-averaged mean-squared displacement (MSD) to the time-averaged MSD (TAMSD) of overdamped or massless FBM, but also concurrently dramatically alter the values of the ergodicity breaking parameter (EB). Our theoretical results for the behavior of EB for underdamped ot massive FBM for varying particle mass m, Hurst exponent H, and trace length T are in excellent agreement with the findings of extensive stochastic computer simulations. The current results can be of interest for the experimental community employing various single-particle-tracking techniques and aiming at assessing the degree of nonergodicity for the recorded time series (studying e.g. the behavior of EB versus lag time). To infer FBM as a realizable model of anomalous diffusion for a set single-particle-tracking data when massive particles are being tracked, the EBs from the data should be compared to EBs of massive (rather than massless) FBM.

biophysics↗

bioRxiv2021

Time-averaging and emerging nonergodicity upon resetting of fractional Brownian motion and heterogeneous diffusion processes

How different are the results of constant-rate resetting of anomalous-diffusion processes in terms of their ensemble-averaged versus time-averaged mean-squared displacements (MSDs versus TAMSDs) and how does the process of stochastic resetting impact nonergodicity? These are the main questions addressed in this study. Specifically, we examine, both analytically and by stochastic simulations, the implications of resetting on the MSD-and TAMSD-based spreading dynamics of fractional Brownian motion (FBM) with a long-time memory, of heterogeneous diffusion processes (HDPs) with a power-law-like space-dependent diffusivity D(x) = D0 |x| {gamma}, and of their "combined" process of HDP-FBM. We find, i.a., that the resetting dynamics of originally ergodic FBM for superdiffusive choices of the Hurst exponent develops distinct disparities in the scaling behavior and magnitudes of the MSDs and mean TAMSDs, indicating so-called weak ergodicity breaking (WEB). For subdiffusive HDPs we also quantify the nonequivalence of the MSD and TAMSD, and additionally observe a new trimodal form of the probability density function (PDF) of particle displacements. For all three reset processes (FBM, HDPs, and HDP-FBM) we compute analytically and verify by stochastic computer simulations the short-time (normal and anomalous) MSD and TAMSD asymptotes (making conclusions about WEB) as well as the long-time MSD and TAMSD plateaus, reminiscent of those for "confined" processes. We show that certain characteristics of the reset processes studied are functionally similar, despite the very different stochastic nature of their nonreset variants. Importantly, we discover nonmonotonicity of the ergodicity breaking parameter EB as a function of the resetting rate r. For all the reset processes studied, we unveil a pronounced resetting-induced nonergodicity with a maximum of EB at intermediate r and EB [~] (1/r)-decay at large r values. Together with the emerging MSD-versus-TAMSD disparity, this pronounced r-dependence of the EB parameter can be an experimentally testable prediction. We conclude via discussing some implications of our results to experimental systems featuring resetting dynamics.

biophysics↗

bioRxiv2020

Model of ciprofloxacin subdiffusion in Pseudomonas aeruginosa biofilm formed in artificial sputum medium

We study theoretically and empirically ciprofioxacin antibiotic diffusion through a gel-like artificial sputum medium (ASM) mimicking physiological conditions typical for a cystic fibrosis layer, in which regions occupied by Pseudomonas aeruginosa bacteria are present. Our theoretical model is based on the subdiffusion-absorption equation with a fractional time derivative that describes molecules diffusion in a medium structured as Thompsons plumpudding model; the pudding background represents ASM and the plums represent the bacterial biofilm. We show that the process can be divided into three successive stages: (1) only antibiotic subdiffusion with constant biofilm parameters, (2) subdiffusion and absorption of antibiotic molecules with variable biofilm parameters, (3) subdiffusion and absorption in the medium but biofilm parameters are constant. Stage 2 is interpreted as the appearance of an intensive defence bulid-up of bacteria against the action of an antibiotic, in the stage 3 it is likely that the bacteria have been inactivated. Times at which stages change are determined from the experimentally obtained temporal evolution of the amount of substance that has diffused through the ASM with bacteria. Our analysis shows good agreement between experimental and our theoretical results.

biophysics↗

bioRxiv2019

Serotonergic Axons as Fractional Brownian Motion Paths: Insights into the Self-organization of Regional Densities

All vertebrate brains contain a dense matrix of thin fibers that release serotonin (5-hydroxytryptamine), a neurotransmitter that modulates a wide range of neural, glial, and vascular processes. Perturbations in the density of this matrix have been associated with a number of mental disorders, including autism and depression, but its self-organization and plasticity remain poorly understood. We introduce a model based on reflected Fractional Brownian Motion (FBM), a rigorously defined stochastic process, and show that it recapitulates some key features of regional serotonergic fiber densities. Specifically, we use supercomputing simulations to model fibers as FBM-paths in two-dimensional brain-like domains and demonstrate that the resultant steady state distributions approximate the fiber distributions in physical brain sections immunostained for the serotonin transporter (a marker for serotonergic axons in the adult brain). We suggest that this framework can support predictive descriptions and manipulations of the serotonergic matrix and that it can be further extended to incorporate the detailed physical properties of the fibers and their environment.

neuroscience↗