q-bio.SC — Pith

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q-bio.SC 2026-06-30

Clathrin coats develop stiffness and memory from growth conditions

by Johannes H. H. Dreckhoff, Ulrich S. Schwarz +2 more

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

Simulations reveal how emergent properties create two gates that decide flat, stalled or closed fates and match experiments without fitting.

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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.

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q-bio.SC 2026-06-17

Aging blurs SR-mitochondria contacts in muscle

by Unmod Senapati, Barsha Priyadarshini Kar +2 more

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

Review links loss of precise membrane proximity to sarcopenia and weighs ways to keep the contacts intact.

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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.

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q-bio.MN 2026-06-16

Division redirects identical cells to opposite fates

by Charli Austin, Nikola Popovic +1 more

Cell Division Changes Fate Decisions in a Genetic Toggle Switch

Analytical separatrices reveal a region where omitting division yields wrong stable-state predictions.

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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.

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physics.bio-ph 2026-06-08

Fork speed variation produces Erlang S-phase times

by Chinmaya Pradhan, Bhakti Mehta +3 more

DNA Replication under Thermal, Chemical, and Genotoxic Stress

A yeast genome model shows that uneven replication speeds explain both average timing spreads and rare long events under stress.

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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.

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q-bio.SC 2026-06-02

Model finds BAM insertion stalls in short bursts

by Thomas Williams, James M. Osborne +3 more

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

Agent-based simulations of Gram-negative outer membrane growth suggest bursty protein incorporation and complex collaboration.

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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 $\beta$-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.

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cond-mat.dis-nn 2026-06-01

Particles accumulate at convergent filament orientations

by Owen Santoso, Elena Koslover

Localization of Active Particles on Random Arrays of Parallel Filaments

Random parallel filament arrays create effective traps for active particles that switch between diffusion and directed motion, strongest at

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Quenched disorder in the environment can fundamentally alter transport dynamics in both active and passive systems. We explore how disordered arrays of filaments govern the distribution of intermittently moving particles which switch between diffusive and processive transport. Motivated by the mixed-polarity arrangements of parallel microtubules observed in mammalian dendrites, we show that such arrays tend to result in localization of particles at regions of convergent filament orientation. In the rapid attachment-detachment limit, the disordered system can be described by a noisy one-dimensional effective energy landscape, whose structure is approximated by a random walk. The depth and width of wells on this landscape are expressed as a function of the transport kinetics and system geometry. Localization is shown to be strongest at intermediate run-lengths, where biased transport persists long enough to sense the quenched filament polarity but not so long as to facilitate escape from local traps. These results demonstrate robust localization of particles moving on random filament networks, highlighting the emergent spatial organization that arises from an interplay of active transport and quenched disorder.

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q-bio.QM 2026-05-28

Relaxation dynamics shift biological transition and oscillation points

by Pan-Jun Kim

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

The quasi-steady state assumption ignores these effects and gets transition durations and onset points wrong in models of cells, metabolism,

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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.

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cond-mat.soft 2026-05-18 2 theorems

Actin cross-linking confines basal bodies for uniform cilia pattern

by Raghavan Thiagarajan, Younes Farhangi Barooji +3 more

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

Progressive cross-linking restricts basal body motion from diffusive to confined, enabling even spacing needed for aligned motile cilia and

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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 $\alpha$-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.

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cond-mat.stat-mech 2026-05-08

Burst timing shapes vesicle signaling activation

by Jan Hauke, Julian B. Voits +1 more

Activation in Vesicle-Mediated Signaling Shaped by Batch Arrival Statistics

Different release patterns with identical average rates produce distinct times to reach activation thresholds through fluctuation effects.

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Vesicle-mediated secretion of ions or molecules is a central mechanism of cellular communication, for example in processes such as neurotransmission or hormone release. These events are inherently stochastic: vesicle fusions lead to bursts of variable sizes, releasing discrete packets of transmitters that are subsequently cleared or degraded. The dynamics break time-reversal symmetry due to the interplay of spontaneous bursts and continuous degradation. Using generating functions and a recursion relation, we derive an exact solution for the full time-dependent probability distribution of a general batch arrival-degradation model. This framework also enables a full analysis of first-passage times to a concentration threshold representing downstream activation. We show that activation kinetics are not determined by mean dynamics alone, but depend sensitively on the temporal statistics of arrival events, batch-size variability, and degradation. In particular, different arrival processes with identical mean rates can lead to qualitatively distinct first-passage behavior, reflecting the role of time-asymmetric fluctuations. We also discuss extensions incorporating vesicle depletion. Our results provide a transparent link between stochastic release dynamics and activation timing in vesicle-mediated signaling.

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q-bio.CB 2026-05-06 3 theorems

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

by Robert G. Endres

Symmetry and time averaging let bacteria perform well even when they use only a small fraction of available signal information.

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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.

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physics.bio-ph 2026-05-01

Peptides differ in virion confinement near cells

by Philipp Rieder, Julia La Roche +9 more

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

Statistical tomography shows alternative spatial strategies likely key to transduction success.

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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.

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cond-mat.soft 2026-04-15 2 theorems

Golgi organization models unified as phases of one nonequilibrium process

by Amit Kumar, Madan Rao

Building and maintaining a System of Intracellular Compartments

Fusion-fission cycles breaking detailed balance produce stable, cycling and progressing cisternae with embedded size control.

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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.

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physics.bio-ph 2026-04-06 2 theorems

Shot noise limits single ion channel voltage accuracy to 10 mV

by Jose M. Betancourt, Benjamin B. Machta

Thermal fluctuations set fundamental limits on ion channel function

Thermal fluctuations from discrete ions set a hard bound on 10 microsecond gating timescales close to observed performance.

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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 $10$ $\mu$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/$\mu$m$^2$ for slow signals and around $10^2-10^4$ channels/$\mu$m$^2$ for signals with $10$ $\mu$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.

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cond-mat.soft 2026-03-24 2 theorems

Actin polymerization can linearly destabilize cell membranes

by Kristiana Mihali, Dennis Wörthmüller +1 more

Mechanical stress induced by the polymerisation of an active gel near a surface

Hydrodynamic model maps how compressibility, friction and turnover produce stresses that amplify small surface corrugations.

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Actin flow in the cortical cytoskeleton underneath the cell membrane generates mechanical stresses that shape the cell surface. We study this mechanism using a hydrodynamic model of a compressible active gel polymerizing at the membrane and undergoing turnover. We determine how actin flow, density relaxation and friction of actin with the membrane generate stress on a corrugated membrane at the linear order in deformation. Analytical solutions in limiting regimes, combined with finite element methods in the general case, provide a map of normal and tangential stresses as functions of compressibility, interfacial friction and actin turnover, and determine the conditions under which actin polymerization can render the membrane linearly unstable. The non-linear regime is also briefly discussed.

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physics.bio-ph 2026-02-03 2 theorems

Balanced metabolite levels raise metabolic control but also heat loss

by Jumpei F. Yamagishi, Tetsuhiro S. Hatakeyama

Thermodynamic cost-controllability tradeoff in metabolic currency coupling

A simple model links equal abundances of ATP, GTP and related currencies to better independent regulation at higher thermodynamic cost.

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Cellular metabolism is globally regulated by various currency metabolites such as ATP, GTP, and NAD(P)H. These metabolites cycle between charged (high-energy) and uncharged (low-energy) states to mediate energy transfer. While distinct currency metabolites are associated with different metabolic functions, their charged and uncharged forms are generally interchangeable via biochemical reactions such as ${\rm ATP{\,+\,}GDP{\,\rightleftharpoons\,}ADP{\,+\,}GTP}$ and $\rm NADP^+{\,+\,}NADH{\,\rightleftharpoons\,}NADPH{\,+\,}NAD^+ $. Thus, their energetic states are generally coupled and influence each other, which would hinder the independent regulation of different currency metabolites. Despite the extensive knowledge of the molecular biology of individual currency metabolites, it remains poorly understood how the coordination of various coupled currency metabolites shapes metabolic regulation, efficiency, and ultimately the evolution of organisms. Here, we present a minimal theoretical model of metabolic currency coupling and reveal a fundamental tradeoff relationship between metabolic controllability and thermodynamic cost: increasing the capacity to independently regulate multiple currency metabolites generally requires comparable abundances of those metabolites, which in turn incurs a higher entropy production rate. The tradeoff suggests that in complex environments, organisms evolutionarily favor an equal abundance of currency metabolites to enhance metabolic controllability at the expense of a higher thermodynamic cost; conversely, in simple environments, organisms evolve to have imbalanced amounts of them to reduce heat dissipation. These considerations also offer a hypothesis regarding evolutionary trends in nucleotide-pool balance and genomic GC content.

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q-bio.SC 2025-12-01 2 theorems

Local monomer depletion enables actin network coexistence

by Valentin Wössner, Falko Ziebert +1 more

A theory for coexistence and selection of branched actin networks in a shared and finite pool of monomers

Negative feedback from shared pool competition leads to steady states or selection without extra regulators.

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Cellular actin structures are continuously turned over while keeping similar sizes. Since they all compete for a shared pool of actin monomers, the question arises how they can coexist in these dynamic steady states. Recently, the coexistence of branched actin networks with different densities growing in a shared and finite pool of purified proteins has been demonstrated in a biomimetic bead assay. However, theoretical work in the context of organelle size regulation has mainly been focused on linear architectures, such as single filaments and bundles, and thus is not able to explain this observation. Here we show theoretically that the local depletion of actin monomers caused by the growth of a branched network naturally gives rise to a negative feedback loop between network density and growth rate, and that this competition is captured by one central ordinary differential equation. A comprehensive bifurcation analysis shows that the theory leads to well-defined steady states even in the case of multiple networks sharing the same pool of monomers, without any need for specific molecular processes. Under increasing competition strength, coexistence is replaced by selection. We also show that our theory is in excellent agreement with spatiotemporal simulations, implemented in a finite element framework, and that local depletion even occurs in the presence of a large pool of non-polymerizable actin. In summary, our work suggests that local monomer depletion is the decisive and universal factor controlling growth of branched actin networks.

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cond-mat.soft 2025-03-27 2 theorems

Contractile stresses form heterochromatin droplets

by S. Alex Rautu, Alexandra Zidovska +2 more

Active Hydrodynamic Theory of Euchromatin and Heterochromatin

Hydrodynamic model links mechanical forces and transcription fluctuations to chromatin organization under nuclear confinement.

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The genome contains genetic information essential for cell's life. The genome's spatial organization inside the cell nucleus is critical for its proper function including gene regulation. The two major genomic compartments -- euchromatin and heterochromatin -- contain largely transcriptionally active and silenced genes, respectively, and exhibit distinct dynamics. In this work, we present a hydrodynamic framework that describes the large-scale behavior of euchromatin and heterochromatin, and accounts for the interplay of mechanical forces, active processes, and nuclear confinement. Our model shows contractile stresses from cross-linking proteins lead to the formation of heterochromatin droplets via mechanically driven phase separation. These droplets grow, coalesce, and in nuclear confinement, wet the boundary. Active processes, such as gene transcription in euchromatin, introduce non-equilibrium fluctuations that drive long-range, coherent motions of chromatin as well as the nucleoplasm, and thus alter the genome's spatial organization. These fluctuations also indirectly deform heterochromatin droplets, by continuously changing their shape. Taken together, our findings reveal how active forces, mechanical stresses and hydrodynamic flows contribute to the genome's organization at large scales and provide a physical framework for understanding chromatin organization and dynamics in live cells.

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cond-mat.soft 2024-12-30 Recognition

Asymptotics reveal voltage drops across nanodomains

by Frédéric Paquin-Lefebvre, Alejandro Barea Moreno +1 more

Voltage laws in nanodomains revealed by asymptotics and simulations of electro-diffusion equations

Narrow windows and curvature set local voltage via solutions of electro-diffusion equations.

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Characterizing the local voltage distribution within nanophysiological domains, driven by ionic currents through membrane channels, is crucial for studying cellular activity in modern biophysics, yet it presents significant experimental and theoretical challenges. Theoretically, the complexity arises from the difficulty of solving electro-diffusion equations in three-dimensional domains. Currently, there are no methods available for obtaining asymptotic computations or approximated solutions of nonlinear equations, and numerically, it is challenging to explore solutions across both small and large spatial scales. In this work, we develop a method to solve the Poisson-Nernst-Planck equations with ionic currents entering and exiting through two narrow, circular window channels located on the boundary. The inflow through the first window is composed of a single cation, while the outflow maintains a constant ionic density satisfying local electro-neutrality conditions. Employing regular expansions and Green's function representations, we derive the ionic profiles and voltage drops in both small and large charge regimes. We explore how local surface curvature and window channels size influence voltage dynamics and validate our theoretical predictions through numerical simulations, assessing the accuracy of our asymptotic computations. These novel relationships between current, voltage, concentrations and geometry can enhance the characterization of physiological behaviors of nanodomains.

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q-bio.CB 2024-08-27 2 theorems

Stiffness triggers hierarchical actin phase transitions

by Yuika Ueda, Shinji Deguchi

Hierarchical phase transitions as mechanical checkpoints of intracellular organization

A thermodynamic model shows energy-entropy thresholds act as checkpoints for cytoskeletal order during cell spreading.

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Living cells inherently reorganize their intracellular structures in response to mechanical cues from their environment. Among these responses, the formation of actin-based stress fibers exhibits a series of structural transitions depending on substrate stiffness: from disordered states on soft substrates, to partial alignment, and eventually to bundled formations as stiffness increases. While these transformations have been well documented in many cell types, the physical principles underlying their emergence remain elusive. Here, we observe identical stiffness-dependent actin reorganizations in senescent fibroblasts despite their diminished biochemical and metabolic activities, suggesting that physical constraints play a dominant role in the phenomenon. We then develop a statistical-mechanical framework to demonstrate that these changes arise through a hierarchy of threshold-dependent phase transitions dictated by energy-entropy competition. This formulation provides a thermodynamic basis for understanding how distinct cytoskeletal orders become favored under different mechanical regimes. We propose that these transitions serve as mechanical checkpoints that coordinate intracellular organization during G1-phase spreading. These findings reveal how mechanical cues guide distinct intracellular orders through a physically constrained hierarchy of transitions.

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physics.bio-ph 2024-04-11 Recognition

RanGEF near nuclear envelope raises nuclear Ran levels

by S. Alex Rautu, Alexandra Zidovska +1 more

Spatio-Temporal Dynamics of Nucleo-Cytoplasmic Transport

Model shows this position emerges from the transport cycle itself and increases nuclear content of Ran.

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Nucleocytoplasmic transport is essential for cellular function, presenting a canonical example of rapid molecular sorting inside cells. It consists of a coordinated interplay between import/export of molecules in/out the cell nucleus. Here, we investigate the role of spatio-temporal dynamics of the nucleocytoplasmic transport and its regulation. We develop a biophysical model that captures the main features of the nucleocytoplasmic transport, in particular, its regulation through the Ran cycle. Our model yields steady-state profiles for the molecular components of the Ran cycle, their relaxation times, as well as the nuclear-to-cytoplasmic molecule ratio. We show that these quantities are affected by their spatial dynamics and heterogeneity within the nucleus. Specifically, we find that the spatial nonuniformity of Ran Guanine Exchange Factor (RanGEF) - particularly its proximity to the nuclear envelope - increases the Ran content in the nucleus. We further show that RanGEF's accumulation near the nuclear envelope results from its intrinsic dynamics as a nuclear cargo, transported by the Ran cycle itself. Overall, our work highlights the critical role of molecular spatial dynamics in cellular processes, and proposes new avenues for theoretical and experimental inquiries into the nucleocytoplasmic transport.

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q-bio.SC 2022-07-11 Recognition

Stochastic model links ribosome-RNAP rates to TTC delay times

by Xiangting Li, Tom Chou

Stochastic dynamics and ribosome-RNAP interactions in Transcription-Translation Coupling

Delay distributions and protection metrics depend on elongation, pausing, and binding parameters.

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Under certain cellular conditions, transcription and mRNA translation in prokaryotes appear to be "coupled," in which the formation of mRNA transcript and production of its associated protein are temporally correlated. Such transcription-translation coupling (TTC) has been evoked as a mechanism that speeds up the overall process, provides protection during the transcription, and/or regulates the timing of transcript and protein formation. What molecular mechanisms underlie ribosome-RNAP coupling and how they can perform these functions have not been explicitly modeled. We develop and analyze a continuous-time stochastic model that incorporates ribosome and RNAP elongation rates, initiation and termination rates, RNAP pausing, and direct ribosome and RNAP interactions (exclusion and binding). Our model predicts how distributions of delay times depend on these molecular features of transcription and translation. We also propose additional measures for TTC: a direct ribosome-RNAP binding probability and the fraction of time the translation-transcription process is "protected" from attack by transcription-terminating proteins. These metrics quantify different aspects of TTC and differentially depend on parameters of known molecular processes. We use our metrics to reveal how and when our model can exhibit either acceleration or deceleration of transcription, as well as protection from termination. Our detailed mechanistic model provides a basis for designing new experimental assays that can better elucidate the mechanisms of TTC.

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q-bio.QM 2019-07-26 Recognition

Brightness analysis measures GPCR clusters despite uneven membranes

by Paolo Annibale, Martin J Lohse

Molecular Brightness analysis of GPCR oligomerization in the presence of spatial heterogeneity

It extracts oligomer states from fluorescence data even when proteins are distributed unevenly across the cell surface.

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Measuring the oligomerization of plasma membrane proteins is rife with biophysical and biomedical implications. This is particularly true for GPCRs, a large family of proteins representing the targets of over one third of all FDA approved medications. Over the last thirty years, fluorescence microscopy has been the leading approach to address this problem. However, in spite of a large number of studies and approaches, for most GPCRs the results have remained highly contentious, possibly due to the large spectrum of specific methods employed.

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physics.bio-ph 2019-07-16 Recognition

Filament lengths create optimal cargo trapping zones in cells

by Bryan Maelfeyt, Ajay Gopinathan

Cytoskeletal filament length controlled dynamic sequestering of intracellular cargo

Model shows residence time peaks at specific lengths, allowing tunable sequestration controlled by network geometry.

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The spatial localization or sequestering of motile cargo and their dispersal within cells is an important process in a number of physiological contexts. The morphology of the cytoskeletal network, along which active, motor-driven intracellular transport takes place, plays a critical role in regulating such transport phases. Here, we use a computational model to address the existence and sensitivity of dynamic sequestering and how it depends on the parameters governing the cytoskeletal network geometry, with a focus on filament lengths and polarization away or toward the periphery. Our model of intracellular transport solves for the time evolution of a probability distribution of cargo that is transported by passive diffusion in the bulk cytoplasm and driven by motors on explicitly rendered, polar cytoskeletal filaments with random orientations. We show that depending on the lengths and polarizations of filaments in the network, dynamic sequestering regions can form in different regions of the cell. Furthermore, we find that, for certain parameters, the residence time of cargo is non-monotonic with increasing filament length, indicating an optimal regime for dynamic sequestration that is potentially tunable via filament length. Our results are consistent with {\it in vivo} observations and suggest that the ability to tunably control cargo sequestration via cytoskeletal network regulation could provide a general mechanism to regulate intracellular transport phases.

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q-bio.SC 2019-07-11 2 theorems

Inhibitor must bind tightly for counter-counter defence to pay off

by Stefan Schuster, Jan Ewald +2 more

Optimizing defence, counter-defence and counter-counter defence in parasitic and trophic interactions -- A modelling study

A model based on toxin exposure time shows a binding threshold below which producing the inhibitor evolves instead of more toxin.

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In host-pathogen interactions, often the host (attacked organism) defends itself by some toxic compound and the parasite, in turn, responds by producing an enzyme that inactivates that compound. In some cases, the host can respond by producing an inhibitor of that enzyme, which can be considered as a counter-counter defence. An example is provided by cephalosporins, beta-lactamases and clavulanic acid (an inhibitor of beta-lactamases). Here, we tackle the question under which conditions it pays, during evolution, to establish a counter-counter defence rather than to intensify or widen the defence mechanisms. We establish a mathematical model describing this phenomenon, based on enzyme kinetics for competitive inhibition. We use an objective function based on Haber's rule, which says that the toxic effect is proportional to the time integral of toxin concentration. The optimal allocation of defence and counter-counter defence can be calculated in an analytical way despite the nonlinearity in the underlying differential equation. The calculation provides a threshold value for the dissociation constant of the inhibitor. Only if the inhibition constant is below that threshold, that is, in the case of strong binding of the inhibitor, it pays to have a counter-counter defence. This theoretical prediction accounts for the observation that not for all defence mechanisms, a counter-counter defence exists. Our results should be of interest for computing optimal mixtures of beta-lactam antibiotics and beta-lactamase inhibitors such as sulbactam, as well as for plant-herbivore and other molecular-ecological interactions and to fight antibiotic resistance in general.

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physics.bio-ph 2019-07-08 2 theorems

Two conditions let cells assemble many protein complexes reliably

by Pablo Sartori, Stanislas Leibler

Towards a theory of assembly of protein complexes: lessons from equilibrium statistical physics

Equilibrium model finds heterogeneous compositions and sparse sharing prevent chimeric errors.

abstract click to expand

Cellular functions are established through biological evolution, but are constrained by the laws of physics. For instance, the physics of protein folding limits the lengths of cellular polypeptide chains. Consequently, many cellular functions are carried out not by long, isolated proteins, but rather by multi-protein complexes. Protein complexes themselves do not escape physical constraints, one of the most important being the difficulty to assemble reliably in the presence of cellular noise. In order to lay the foundation for a theory of reliable protein complex assembly, we study here an equilibrium thermodynamic model of self-assembly that exhibits four distinct assembly behaviors: diluted protein solution, liquid mixture, "chimeric assembly" and "multifarious assembly". In the latter regime, different protein complexes can coexist without forming erroneous chimeric structures. We show that two conditions have to be fulfilled to attain this regime: (i) the composition of the complexes needs to be sufficiently heterogeneous, and (ii) the use of the set of components by the complexes has to be sparse. Our analysis of publicly available databases of protein complexes indicates that cellular protein systems might have indeed evolved so to satisfy both of these conditions.

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