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arXiv2026

Osmotically Induced Shape Changes in Membrane Vesicles

We develop a self-consistent free-energy framework in which membrane shape and osmotic pressure are determined simultaneously in a finite reservoir by minimizing bending elasticity and solute entropy. Solute conservation makes osmotic pressure a thermodynamic variable rather than an externally prescribed parameter, producing a nonlinear coupling between membrane mechanics and solvent entropy. This coupling modifies the classical stability condition for spherical vesicles: instability emerges from global free-energy competition rather than the linear Helfrich stability criterion. The resulting critical pressures differ by orders of magnitude from Helfrich predictions and agree with simulations for small and large unilamellar vesicles. The framework is relevant to cellular environments involving biomolecular condensate confinement as well as synthetic vesicles and the development of osmotic-pressure-driven encapsulation platforms.

cond-mat.soft↗

arXiv2026

Thermal fluctuations set fundamental limits on ion channel function

Voltage-gated ion channels are essential for propagating signals in neurons. Each channel senses the local membrane potential created by nearby ions. Fluctuations in these ions introduce two fundamental noise sources: (i) shot noise, from the discreteness of ionic charge, and (ii) Johnson-Nyquist noise, from long-wavelength thermal fluctuations of the electric field. We show that, for an individual channel, shot noise dominates and sets an intrinsic limit to voltage sensing. On the $10$ $μ$s timescales relevant to channel gating, this limit corresponds to an accuracy of about $10$ mV -- close to measured channel sensitivities. When signals from many channels are aggregated, Johnson-Nyquist noise eventually overtakes shot noise and bounds the total information that can be sensed from the environment. This transition occurs at an ion channel density of $< 1$ channel/$μ$m$^2$ for slow signals and around $10^2-10^4$ channels/$μ$m$^2$ for signals with $10$ $μ$s timescales, both of which are within the range of experimentally-measured densities for somas and axon initial segments, respectively. These results provide design principles for single-channel architecture and collective sensing and suggest that neuronal computation is ultimately constrained by thermal fluctuations.

physics.bio-ph↗

arXiv2026

Building and maintaining a System of Intracellular Compartments

Organelle patterning and its heritability remain central mysteries in cell biology, highlighting the fundamental tension between genetic inheritance and self-assembly. Here, we explore the nonequilibrium assembly and emdedded size control of the Golgi cisternae and endosomes, amid a continuous flux of membrane traffic, within a stochastic framework of mechanochemical fusion-fission cycles that violate detailed balance. Using a dynamical systems approach, we identify distinct, robust regimes, ranging from fixed points to limit cycles with definite phase relations between cisternae. We identify these dynamical regimes with diverse phenotypes, from stable cisternae to periodic, cell-cycle-dependent dissolution/reassembly of cisternae to cisternal progression. We analyse its dynamic response to systematic perturbations or driving protocols and make definite predictions that may be tested experimentally. Our analysis reveals that the two competing models of Golgi organization - vesicular transport and cisternal progression - are, in fact, two phases of the same underlying nonequilibrium process. We see that cisternal size homeostasis is brought about by a size-dependent embedded control system driven by fusion-fission kernels. Finally, our framework offers a strategy for controlling cisternal number and chemical identity by modulating the interplay between glycosylation enzymes and membrane fission-fusion dynamics.

cond-mat.soft↗

arXiv2026

Neuronal electricality founded in murburn-thermodynamic principles: 1. Background and basic theoretical formulation

Trans-membrane ion-gradients and fluxes are central to conventional electrical activity in aerobic cells/organelles. The Murburn concept offers novel physico-chemical models for various metabolic, bioenergetic and electrophysiological phenomena. Here, we develop a foundational framework for neuronal electrical activity and axonal signal propagation using the electron-holding potential (EHP), a dimensionless field related logarithmically to electron chemical potential. By combining local redox relaxation dynamics with spatial transport driven by thermodynamic gradients, we derive a unified reaction-transport-relaxation equation that accounts for resting potential, excitability, waveform generation, and signal propagation within a single formalism. Nonlinear local redox kinetics yield a stable resting state and graded responses from a single scalar field; extending it to the two-variable excitable (FitzHugh Nagumo) form, a bistable reaction with a slow recovery variable, further yields a genuine threshold, all-or-none spikes, a refractory period and a propagating action potential. The framework accommodates known physiological variability of neurons and provides a direct bridge between metabolic/redox state and electrophysiology. This framework offers testable predictions for neuronal dynamics (such as velocity, waveform morphology, and environmental conditions) across biological systems. We derive and solve the equations to obtain the transmembrane potential as a function of time, and the neuronal conduction velocity as a function of parameters like ionic strength, temperature, axon diameter, myelination, and driving potential. In the second part of this work, we present comparative analyses, simulations, and experimental strategies for validation and falsification.

q-bio.NC↗

arXiv2026

Neuronal electricality founded in murburn-thermodynamic principles: 2. Comparisons, evidenced explanations, and predictions

The analyses presented herein demonstrate that neuronal electrical activity can be consistently interpreted as a manifestation of murburn redox-mediated electronic dynamics rather than as a process fundamentally driven by transmembrane ionic flux. By integrating comparison with established models, quantitative predictions, and diverse experimental observations, the murburn framework emerges as a unified and chemically grounded description of excitability. A key strength of the model lies in its predictive structure. Unlike phenomenological frameworks that rely on parameter fitting, the murburn formulation links measurable electrophysiological outputs: such as conduction velocity, waveform morphology, and threshold behavior; to physically interpretable variables including redox kinetics, transport efficiency, and environmental conditions. This enables direct experimental validation through perturbations in oxygen availability, redox balance, solvent properties, ionic strength, and external fields. Importantly, the framework extends beyond neurons to a broader class of excitable systems, including cardiac tissue, photoreceptors, and artificial redox-active materials, suggesting that excitability is a general physicochemical phenomenon rooted in reaction-transport dynamics. While the present work establishes the mid-scale dynamics of neuronal electricality, further developments are required to connect quantum-level electron transfer processes with macroscopic electrophysiological signals such as EEG and EMG. These extensions, along with targeted experimental tests, will determine the ultimate scope and applicability of the murburn paradigm.

q-bio.NC↗

arXiv2026

Statistical analysis of virion-cell interactions mediated by peptide nanofibrils and peptide amphiphiles using STEM tomography

Peptide nanofibrils (PNFs) and peptide amphiphiles (PAs) are promising tools for enhancing viral transduction and gene transfer. However, quantitative insight into how their supramolecular architecture governs virion-cell interactions is limited. Here, we introduce a framework for the acquisition, processing, and statistical analysis of scanning transmission electron microscopy (STEM) tomograms to objectively quantify peptide-virion-cell interactions. Using four transduction-enhancing peptides (D4, Vectofusin-1, palmitic acid-PA (pal-PA), and eicosapentaenoic-PA (eic-PA)), peptide aggregate morphology, interfacial contact areas, and the spatial organization of virions with respect to peptides and cells were analyzed using advanced geometric descriptors. All peptides efficiently captured virions, resulting in few free virions, but they differ in how strictly virions were spatially confined near the cell surface. These differences reflect alternative spatial organization strategies, which are likely crucial factors influencing transduction-enhancing efficacy. Our approach provides a novel, generalizable method to evaluate infection-enhancing nanomaterials and guides the rational design of next-generation peptide assemblies for therapeutic viral delivery.

physics.bio-ph↗

arXiv2026

Robust chemotaxis beyond sensing limits: signal, noise, and strategy

Bacterial chemotaxis has long been viewed as operating near the physical limits of sensing, as originally articulated by Berg and Purcell. Recent information-theoretic analyses challenge this view, suggesting that Escherichia coli uses only a small fraction of the information available in ligand arrival statistics to bias its motion. How should such low information efficiency be interpreted at the level of behavior? Here, I argue that chemotactic performance is shaped not only by information transmission and noise, but by the strategy of movement itself. Using simple scaling arguments and minimal models, I show how run-and-tumble chemotaxis can remain robust to noise through symmetry and temporal averaging, even when internal information processing is inefficient. Comparing bacterial and eukaryotic chemotaxis highlights how different sensing strategies convert physical limits into observable behavior. These considerations suggest that low information efficiency need not imply poor performance, but may instead reflect an evolved balance between robustness, simplicity, and function.

q-bio.CB↗

arXiv2026

Actin cross-linking organizes basal body patterning through anomalous diffusion transitions

Subcellular protein complexes and organelles exhibit diverse dynamic behaviors that reflect the mechanical constraints and organization of the intracellular environment. Although some structures follow classical Brownian motion, many display anomalous dynamics. The transitions between these regimes are increasingly recognized as critical for subcellular organization, yet how they influence pattern formation remains unclear. Here, we investigate the spatial arrangement of cilia on the apical surface of multiciliated cells (MCCs) in developing Xenopus laevis embryos, where coordinated ciliary beating depends on the precise organization of hundreds of centriole-derived basal bodies (BBs). Using quantitative confocal, high-resolution and high-speed TIRF imaging together with theoretical modeling, we show that BB trajectories undergo time-resolved transitions between diffusive and anomalous motion, with distinct regimes that correlate with apical surface expansion. During the early stages, actin remodeling facilitates the dispersal of BBs by providing a permissive, low-confinement environment. As development progresses, the actin network becomes increasingly cross-linked that constrains BB movement and promotes uniform spacing across the apical domain. Disruption of $α$-actinin-1, a major actin cross-linking protein, impairs the integrity of the apical actin meshwork, weakens BB confinement, and disrupts regular spatial patterning, ultimately compromising the arrangement of BBs required for proper cilia alignment. Together, we show that progressive apical actin cross-linking coordinates BB positioning and regulates their dynamic state, guiding the shift from diffusive to confined motion. This transition in dynamics enables the emergence of a uniform BB pattern, which in turn ensures the aligned deployment of motile cilia necessary for effective directional fluid flow.

cond-mat.soft↗

arXiv2026

Widespread quasi-steady state assumption in biological interaction modeling mischaracterizes system transitions

From molecular, cellular, to ecological systems, the modeling of biological processes often stands on the assumption that fast components immediately reach the equilibrium at each moment (quasi-steady state) and only slow components govern the relevant system dynamics. This quasi-steady state approximation (QSSA) simplifies the modeling but discards the effects of the relaxation towards each quasi-steady state. Unclear is the QSSA's suitability around the transition point, a specific condition where the system changes to a qualitatively different state. In this regard, we here derived a theoretical framework for the near-transition dynamics of biological systems, explicitly considering the relaxation processes overlooked by the QSSA. Numerical simulations verify our predictions for cellular decision-making, metabolic oscillations, and ecological cycles. Despite the extreme slowdown near the transition point, the QSSA alone misestimates the duration of the transition from one state to another. Moreover, the QSSA erroneously predicts the transition point itself for the onset of oscillations, while the relaxation dynamics facilitates or suppresses the oscillation onset with a counterintuitive time-delay effect. Common feedback interactions between biological components are pivotal to those relaxation effects. Our study provides an analytical foundation to understand the rich transient or rhythmic dynamics of interacting biological components near the transitions.

q-bio.QM↗

arXiv2026

An agent-based model of outer membrane biogenesis in Gram-negative bacteria

The outer membrane is the interface through which Gram-negative bacteria - a broad classification of organisms including \textit{Escherichia coli} and a number of deadly pathogens - interact with the environment. Two decades of work on the process of outer membrane biogenesis have led to the discovery of the components that mediate this process, and the characterisation of structure and function of these component parts of the bacterial cell machinery. However, neither current experimental methods, nor conventional molecular dynamics (MD) simulation approaches are capable of investigating this membrane machinery on the time scale of the cell division cycle. This leaves crucial questions unanswered, such as how this lipid-poor, largely static environment is organised to permit ongoing membrane growth. Here, we introduce a semi-quantitative agent-based model to explore the molecular-scale dynamics of Gram-negative outer membrane as it grows. Model simulations across a broad region of parameter space suggest that protein incorporation into the membrane by the $β$-barrel assembly machinery (BAM complex) is a process which is prone to stalling, and may take place only in short bursts. We also find suggestions that BAM complexes work collaboratively with each other, and with the lipopolysaccharide-inserting Lpt complex when in close proximity. The agent-based framework we introduce provides a means to assess and generate hypotheses on outer membrane biogenesis on previously inaccessible time scales.

q-bio.SC↗

arXiv2026

DNA Replication under Thermal, Chemical, and Genotoxic Stress

Eukaryotic DNA replication must remain robust under thermal, chemical, and genotoxic stress despite large fluctuations in replication dynamics. Here, we develop a lattice-based stochastic Monte Carlo framework for whole-genome replication in Saccharomyces cerevisiae at single base-pair resolution, incorporating probabilistic origin firing, replication fork-speed distributions, and a time-dependent limiting factor that governs the availability of cellular replication resources. The model is benchmarked quantitatively against experimental replication profiles before being applied to stress conditions, and reproduces diverse replication stress responses using only two effective parameters. Importantly, the analysis reveals that replication fork-speed heterogeneity underlies the emergence of Erlang-distributed S-phase durations and rare, anomalously prolonged replication events observed experimentally in Escherichia coli and human cell lines, while predicting similar behavior in S. cerevisiae. The framework further predicts non-monotonic thermal behavior, power-law scaling under hydroxyurea stress, and total replication-time dynamics under diverse genotoxic conditions.

physics.bio-ph↗

arXiv2026

Oscillating concentrations suppress condensate coarsening

Living cells utilize condensates to spatially concentrate molecules in response to dynamic signals. For instance, nuclear condensates respond to oscillations in transcription factor levels in the nucleoplasm, including those involved in repairing multiple DNA breaks. To understand how oscillating signals affect condensates, we analyze a theoretical model using numerical simulations and analytical theory. While passive dynamics would drive all molecules into a single condensate, we find that sufficiently fast oscillations stabilize multiple droplets, allowing control of their sizes. We thus reveal a new behavior of chemically active droplets, which could be exploited in synthetic applications.

physics.bio-ph↗

arXiv2026

Cell Division Changes Fate Decisions in a Genetic Toggle Switch

Gene regulatory networks govern cellular fate decisions through multistable dynamics. The genetic toggle switch is a canonical model of such behaviour; yet, the impact of cell division on its dynamics remains poorly understood. We derive analytical separatrices for a simplified Boolean toggle switch with and without division. We show that division can redirect trajectories with identical initial conditions to opposing stable states, and we define a region of disagreement where fate decisions are predicted incorrectly if division is neglected. Our results imply that division can fundamentally reshape fate boundaries in multistable regulatory networks.

q-bio.MN↗

arXiv2026

Aging induced structural alterations in SR-Mitochondria interaction in skeletal muscle: Emerging insights

Skeletal muscle undergo remarkable changes during aging including anatomical, ultrastructural, and moreover biochemical. The aging associated reduction of muscle mass, termed as sarcopenia, is a major factor in geriatric functional decline and frailty, contributing to the lowering of self-confidence. In an adult skeletal muscle fibers, sarcoplasmic reticulum (SR) and mitochondria exhibit most intricate and precise distribution along with the sarcolemmal (forming T-tubule), which is critical for muscle function. In healthy young muscle tissue, the close physical proximity of SR and mitochondrial membranes shows contacts called mitochondria-associated membranes (MAMs). Recent literature highlights the role of MAMs network in smooth functioning of muscle by regulating localization of Ca2+-signaling, lipid transport, and other signalling molecules like reactive oxygen species. Several tethering mechanisms are proposed to stabilize the MAMs network, the classical ones being the mitofusins (MFN1 and MFN2). Emerging consensus suggest that MAMs in the skeletal muscle facilitate accuracy of excitation-metabolic coupling ensuring spatial energy supply. However, upon aging the precision of SR and mitochondria co-localization as well as crosstalk seems to be affected. In this review, we have critically examined the current literature about MAMs network structure and function during health and diseases mainly from an aging perspective. We have further evaluated the role of exercise, nutritional, nutraceutical and pharmacological approaches in lowering MAMs loss in an effort to retard aging progression. Retention of skeletal muscle health and performance is a major factor in achieving the goal of healthy aging.

q-bio.SC↗

arXiv2026

Pathway variability, coat stiffening and mechanical adaptation during clathrin-mediated endocytosis

Clathrin assemblies in cells can persist as flat plaques, abort after partial invagination, or close into clathrin-coated vesicles, but the determinants of these different fates remain unresolved. To investigate the stochastic and complex dynamics of clathrin assemblies, we have developed a kinetic Monte Carlo simulation framework that couples individual clathrin agents to an adaptive continuum membrane. In this hybrid discrete-continuum description, the effective coat bending rigidity and the preferred coat curvature emerge during growth, rather than being prescribed as material parameters. Once connected, curved lattices stiffen from molecular bending modes to coat-level rigidities, because curvature changes require increased stretching or compression, while newly incorporated triskelia hardcode a history-dependent preferred curvature. An analytical theory for non-Euclidean elasticity identifies the relevant internal variables and predicts growth laws that are validated by the simulations. The same microscopic assembly rules yield flat, stalled, and closed coats through two sequential gates in the effective membrane-coat energy landscape. Comparisons with experimentally observed coat geometries and nanodissection-induced curvature changes agree with our theoretical predictions without any fitting parameters. The clathrin coat thus emerges as an adaptive assembly with prestress and memory, whose fate and material parameters reflect the environment in which it has been growing.

q-bio.SC↗

arXiv2026

Targeting DNA Methylation: New Paradigms and the Advent of Gene-Selective Tools

DNA methylation can function as a toxic alkylation reaction exploited by chemotherapeutic agents to induce cancer cell death. However, finely tuned DNA methylation plays a fundamental role in cellular physiology, particularly in the epigenetic regulation of gene expression. Once thought to act solely as a repressor of gene transcription, its functional role has since been elucidated as genomic locus-specific and deeply connected with other epigenetic factors. Following the clinical approval of DNA methyltransferase inhibitors, such as Azacitidine and Decitabine, for the treatment of haematological malignancies, considerable efforts have been devoted to developing pharmacological tools that modulate epigenetic DNA methylation. However, the lack of gene selectivity in these agents limits their therapeutic efficacy and increases off-target toxicity. Moreover, the non-gene-selective nature of current DNA methylation-targeting molecules fails to meet the standards required to discern the nuanced roles of DNA methylation across diverse pathophysiological contexts and genomic loci, particularly in an era where next-generation sequencing and omics technologies enable hi ghresolution epigenetic analyses. In this review, we examine the mechanisms and roles of DNA methylation in epigenetic regulation, evaluate the current landscape of DNA methylation modulators, from traditional DNMT inhibitors to cutting-edge CRISPR-dCas9 fusion systems and protein-protein interaction disruptors, and discuss their clinical relevance. Finally, we emphasise the need for precise, locus-specific tools to advance both cancer research and therapeutic strategies.

q-bio.SC↗

arXiv2026

Entropy-Driven Initiation and Cellular Uptake Mediated by Viscoelastic Cytoskeleton: A Kinetic Phase Diagram from Onsager Variational Principle

A fundamental question in receptor-mediated endocytosis remains unanswered: what initial driving force brings ligands and receptors into close proximity? While previous models assume pre-existing contact and overlook this initiation problem, we propose that entropic forces from nanoscale biomolecules in crowded cellular environments provide the essential driving mechanism. We develop a unified continuum model rooted in the Onsager variational principle, where engulfment depth serves as the generalized coordinate and the driving force derives from a free energy landscape of entropic, binding, membrane, and cytoskeleton contributions. The framework naturally incorporates: (i) entropy-driven adhesion as initiation; (ii) ligand-receptor binding as the sustaining force; (iii) membrane deformation via the Helfrich-Canham Hamiltonian; and (iv) cytoskeleton viscoelasticity through the elastic-viscoelastic correspondence principle. The kinetic phase diagram predicts a critical biomolecule concentration for initiation, a lower bound of ligand density for complete engulfment, a finite size window for engulfable particles, and an optimal virus radius of 30--60 nm that decreases with increasing binding energy. The Onsager solubility condition naturally yields the phase boundaries. The model exhibits asymptotic consistency with the classic Asakura-Oosawa result in the large-particle flat-surface limit. Stiffer cells lead to longer engulfment times and narrower size windows. Strikingly, the optimal size matches HIV-1 dimensions under physiologically realistic parameters. This work provides a variational foundation for cellular uptake with implications for virology, nanotechnology, and drug delivery.

cond-mat.soft↗

arXiv2026

The Origins of Transient Bimodality

Many dynamical systems exhibit diverse modes of behavior. In biology, such modes can represent individual or cell fates. While the emergence of multimodality is commonly studied, transient bimodality is much less well understood. Under transient bimodality, a system moving from a well-defined initial to a final state transiently undergoes a bifurcation into multiple probability modes. This noise-driven phenomenon can significantly impact processes such as cell differentiation and speciation in the presence of changing environmental conditions. We detail a theoretical approach for understanding transient bimodality connecting results from ecology, optics, chemical reaction networks and cell biology, propose a ``minimal model'' of transient bimodality and derive a general criterion for its presence. We show that fast-to-slow dynamics can lead to transient bimodality in addition to the well-known case of slow-to-fast dynamics. Finally, we discuss the role of transient bimodality across the scientific literature, with emphasis on biochemical kinetics and gene regulation.

q-bio.SC↗