Biology subjects

Moeckel, C.

Publications and source records attributed to Moeckel, C..

7 recordsLinked to original sources

bioRxiv2026

Quantitative assessment of mesoscale cellular order and organization in the mouse hippocampus

The hippocampus is characterized by a stereotypical macroscopic structure, where the nuclei are densely and heterogeneously packed among different subregions of the hippocampus. Despite the fact that tissue-specific cellular organization has been implicated in neural function, it has been technically challenging to quantitatively analyze mesoscopic cellular organization in the hippocampus due to its high cellular density. To overcome this technical hurdle, we developed Computational Biophysical Histomorphometry Software (CBHS), an automated image-analysis pipeline, aimed at quantifying nuclear shape and the order of the cellular ensemble in high-density areas. When applied to the subfields of hippocampus, we found that denser regions, most notably the dentate gyrus, were the most positionally, but least orientationally ordered. Nuclear shape exhibited a dependence on the local environment in a packing-dependent manner. This association was cell-type specific, with neurons, but not astrocytes displaying nuclear shape that varied with neighbour proximity, although astrocytes demonstrated greater intrinsic shape variance. The results reveal the presence of reproducible mesoscale cell packing order in hippocampal tissue, and are consistent with a nucleus-driven mechanical coupling between neighbouring cells. The present study provides a quantitative framework with which to understand mesoscopic tissue organization, thus enabling the formulation of testable hypotheses for future investigation.

neuroscience↗

bioRxiv2025

Hierarchical Heterogeneities in Spatio-Temporal Dynamics of the Cytoplasm

The physical properties of the cytoplasm fundamentally constrain the dynamics and fidelity of cellular processes. Endogenous fluctuations carry signatures of these properties, yet how their collective dynamics across mesoscopic spatiotemporal scales relate to cytoplasmic heterogeneity and organization remains poorly understood. Here, we use differential dynamic microscopy (DDM) to quantify these fluctuations in eukaryotic cytoplasms. In Xenopus laevis egg extracts, we identify signatures of subdiffusive fractional Brownian motion (fBm) and non-Gaussian displacement distributions, consistent with a crowded, heterogeneous environment. We introduce an empirical model combining fBm with an inverse Gaussian diffusivity distribution, enabling robust estimation of fractional diffusivities and scaling exponents across conditions. Denser cytoplasm exhibits lower fractional diffusivity and scaling exponent, while energy addition induces non-stationary dynamics. Stabilization of microtubule networks introduces a secondary timescale, rationalized by a two-state fBm model separating cytosolic and network-associated contributions. In HeLa cells, the framework reveals comparable scaling exponents but lower diffusivities than in egg extract. Upon microtubule depolymerization, the dynamics become slower yet more Brownian-like. This highlights dual roles of the cytoskeleton as confinement but also as fluidizer of the cytoplasm. These results establish label-free DDM as an interpretable, collective, multiscale readout of how composition, activity, and cytoskeletal organization shape hierarchical cytoplasmic dynamics.

biophysics↗

bioRxiv2025

Viscoelastic characterization of cells in microfluidic channels with 3D hydrodynamic focusing

The viscoelastic nature of biological cells has emerged as an increasingly important research subject due to its relevance for cellular functions under physiological and pathological conditions. Advancements in microfluidics have made this technology a promising tool to study the viscoelasticity of cells. However, significant challenges remain, including the complex distribution of stresses acting on cells depending on the channel geometry, and the difficulty of keeping cells in the focal plane for imaging. Here, we report a new approach using hyperbolic channels for measuring cell viscoelasticity. A channel height much larger than the typical cell size minimized shear stresses so that normal stresses in the hyperbolic region dominated the stress distribution. Reducing the complexity of the stress-strain relationship allowed us to use polyacrylamide microgel beads to calibrate the stress curve. Additionally, we introduced 3D hydrodynamic focusing which enabled us to focus cells and microgel beads in the center of the channel. Finally, Kelvin-Voigt and power-law rheology models were employed to extract the mechanical properties of microgel beads and human leukemia HL60 cells. The measurement technique described here will help establish the viscoelastic properties of cells as an important readout in biophysical research in health and disease.

biophysics↗

bioRxiv2024

Characterization of hairpin loops and cruciforms across 118,065 genomes spanning the tree of life

Inverted repeats (IRs) can form alternative DNA secondary structures called hairpins and cruciforms, which have a multitude of functional roles and have been associated with genomic instability. However, their prevalence across diverse organismal genomes remains only partially understood. Here, we examine the prevalence of IRs across 118,065 complete organismal genomes. Our comprehensive analysis across taxonomic subdivisions reveals significant differences in the distribution, frequency, and biophysical properties of perfect IRs among these genomes. We identify a total of 29,589,132 perfect IRs and show a highly variable density across different organisms, with strikingly distinct patterns observed in Viruses, Bacteria, Archaea, and Eukaryota. We report IRs with perfect arms of extreme lengths, which can extend to hundreds of thousands of base pairs. Our findings demonstrate a strong correlation between IR density and genome size, revealing that Viruses and Bacteria possess the highest density, whereas Eukaryota and Archaea exhibit the lowest relative to their genome size. Additionally, the study reveals the enrichment of IRs at transcription start and termination end sites in prokaryotes and Viruses and underscores their potential roles in gene regulation and genome organization. Through a comprehensive overview of the distribution and characteristics of IRs in a wide array of organisms, this largest-scale analysis to date sheds light on the functional significance of inverted repeats, their contribution to genomic instability, and their evolutionary impact across the tree of life.

genomics↗

bioRxiv2024

Quadrupia: Derivation of G-quadruplexes for organismal genomes across the tree of life

G-quadruplex DNA structures exhibit a profound influence on essential biological processes, including transcription, replication, telomere maintenance, and genomic stability. These structures have demonstrably shaped organismal evolution. However, a comprehensive, organism-wide G-quadruplex map encompassing the diversity of life has remained elusive. Here, we introduce Quadrupia, the most extensive and well-characterized G-quadruplex database to date, facilitating the exploration of G-quadruplex structures across the evolutionary spectrum. Quadrupia has identified G-quadruplex sequences in 108,449 reference genomes, with a total of 140,181,277 G-quadruplexes. The database also hosts a collection of 319,784 G-quadruplex clusters of 20 or more members, annotated by taxonomic distributions, multiple sequence alignments, profile Hidden Markov Models and cross-references to G-quadruplex 3D structures. Examination of G-quadruplexes across functional genomic elements in different taxa indicates preferential orientation and positioning, with significant differences between individual taxonomic groups. For example, we find that G-quadruplexes in bacteria with a single replication origin display profound preference for the leading orientation. Finally, we experimentally validate the most frequently observed G-quadruplexes using CD-spectroscopy, UV melting, and fluorescent-based approaches. Quadrupia is publicly available through https://www.pavlopoulos-lab.org/quadrupia.

genomics↗

bioRxiv2024

Optical quantification of molecular interaction strength in protein condensates

Biomolecular condensates have been identified as a ubiquitous means of intracellular organization, exhibiting very diverse material properties. However, techniques to characterize these material properties and their underlying molecular interactions are scarce. Here, we introduce two optical techniques - Brillouin microscopy and quantitative phase imaging (QPI) - to address this scarcity. We establish Brillouin shift and linewidth as measures for average molecular interaction and dissipation strength, respectively, and we used QPI to obtain the protein concentration within the condensates. We monitored the response of condensates formed by FUS and by the low-complexity domain of hnRNPA1 (A1-LCD) to altering temperature and ion concentration. Conditions favoring phase separation increased Brillouin shift, linewidth, and protein concentration. In comparison to solidification by chemical crosslinking, the ion-dependent aging of FUS condensates had a small effect on the molecular interaction strength inside. Finally, we investigated how sequence variations of A1-LCD, that change the driving force for phase separation, alter the physical properties of the respective condensates. Our results provide a new experimental perspective on the material properties of protein condensates. Robust and quantitative experimental approaches such as the presented ones will be crucial for understanding how the physical properties of biological condensates determine their function and dysfunction.

biophysics↗

bioRxiv2023

Estimation of the mass density of biological matter from refractive index measurements

The quantification of physical properties of biological matter gives rise to novel ways of understanding functional mechanisms by utilizing models that explicitly depend on physical observables. One of the basic biophysical properties is the mass density (MD), which determines the degree of crowdedness. It impacts the dynamics in sub-cellular compartments and further plays a major role in defining the opto-acoustical properties of cells and tissues. As such, the MD can be connected to the refractive index (RI) via the well known Lorentz-Lorenz relation, which takes into account the polarizability of matter. However, computing the MD based on RI measurements poses a challenge as it requires detailed knowledge of the biochemical composition of the sample. Here we propose a methodology on how to account for a priori and a posteriori assumptions about the biochemical composition of the sample as well as respective RI measurements. To that aim, we employ the Biot mixing rule of RIs alongside the assumption of volume additivity to find an approximate relation of MD and RI. We use Monte-Carlo simulations as well as Gaussian propagation of uncertainty to obtain approximate analytical solutions for the respective uncertainties of MD and RI. We validate this approach by applying it to a set of well characterized complex mixtures given by bovine milk and intralipid emulsion. Further, we employ it to estimate the mass density of trunk tissue of living zebrafish (Danio rerio) larvae. Our results enable quantifying changes of mass density estimates based on variations in the a priori assumptions. This illustrates the importance of implementing this methodology not only for MD estimations but for many other related biophysical problems, such as mechanical measurements using Brillouin microscopy and transient optical coherence elastography.

biophysics↗