High mobility group box-1 (HMGB1) is a damage-associated molecular pattern and a ligand for multiple immune receptors, including receptors for advanced glycation endproducts (RAGE) and toll-like receptor 4 (TLR4). Binding of HMGB1 to these receptors initiates inflammatory signaling cascades implicated in diseases such as septic shock, chronic inflammation, and autoimmune disorders. The spatial and molecular mechanisms underlying HMGB1-mediated receptor signaling at the plasma membrane remain poorly understood. Here, single-particle tracking was used to investigate the effects of extracellular HMGB1 on RAGE’s and TLR4’s diffusion properties in human embryonic kidney 293 (HEK293) cells. HMGB1 treatment reduced the Brownian diffusion coefficients by 27% and 24% for RAGE (with and without TLR4 co-expression, respectively) and by 40% and 21% for TLR4 (with and without RAGE co-expression, respectively). HMGB1 treatment reduced the size of the confined domains the receptors diffuse into and increased the number of times the two receptors came in close proximity. In contrast, HMGB1 had no detectable effect on the diffusion properties of an S391A RAGE mutant, which lacks the ability to recruit adapter proteins. Lipid diffusion measurements revealed that HMGB1 treatment decreases lipid membrane fluidity in all cell lines studied. Similarly, phalloidin staining revealed no detectable HMGB1-induced changes in actin organization in RAGE expressing cells. Functionally, HMGB1 treatment activated the extracellular signal-regulated kinase (ERK) (1/2) signaling pathway through both RAGE and TLR4, whereas ERK (1/2) and p38 MAPK activation by HMGB1 were abolished in cells expressing S391A RAGE. Together, these findings show that HMGB1 reduced confined receptor diffusion and increased nanoscale proximity while promoting MAPK signaling. This work sheds new light on the nanoscale regulation of innate immune receptors by HMGB1 and emphasizes membrane biophysics as one critical component of inflammatory signaling outcomes.
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- The following article is Open accessEffect of high mobility group box-1 on receptor for advanced glycation endproducts (RAGE) and toll-like receptor-4 (TLR4) diffusion and signaling
Sharifur Rahman et al 2026 Phys. Biol. 23 046005
View article, Effect of high mobility group box-1 on receptor for advanced glycation endproducts (RAGE) and toll-like receptor-4 (TLR4) diffusion and signalingPDF, Effect of high mobility group box-1 on receptor for advanced glycation endproducts (RAGE) and toll-like receptor-4 (TLR4) diffusion and signaling - The following article is Open accessGetting around the cell: physical transport in the intracellular world
Saurabh S Mogre et al 2020 Phys. Biol. 17 061003
View article, Getting around the cell: physical transport in the intracellular worldPDF, Getting around the cell: physical transport in the intracellular worldEukaryotic cells face the challenging task of transporting a variety of particles through the complex intracellular milieu in order to deliver, distribute, and mix the many components that support cell function. In this review, we explore the biological objectives and physical mechanisms of intracellular transport. Our focus is on cytoplasmic and intra-organelle transport at the whole-cell scale. We outline several key biological functions that depend on physically transporting components across the cell, including the delivery of secreted proteins, support of cell growth and repair, propagation of intracellular signals, establishment of organelle contacts, and spatial organization of metabolic gradients. We then review the three primary physical modes of transport in eukaryotic cells: diffusive motion, motor-driven transport, and advection by cytoplasmic flow. For each mechanism, we identify the main factors that determine speed and directionality. We also highlight the efficiency of each transport mode in fulfilling various key objectives of transport, such as particle mixing, directed delivery, and rapid target search. Taken together, the interplay of diffusion, molecular motors, and flows supports the intracellular transport needs that underlie a broad variety of biological phenomena.
- The following article is Open accessEcological dynamics of pro-tumor and anti-tumor teams in the tumor microenvironment
Vaibhav Anand et al 2026 Phys. Biol. 23 036005
View article, Ecological dynamics of pro-tumor and anti-tumor teams in the tumor microenvironmentPDF, Ecological dynamics of pro-tumor and anti-tumor teams in the tumor microenvironmentTumor growth occurs within a complex tumor microenvironment (TME) composed of many interacting cell types. However, the signs of tumor-immune interactions in this ecosystem are not random and possess a structure, the immune cell types in the TME tend to organize into two functional communities: a pro-tumor team and an anti-tumor team, each internally cooperative but mutually antagonistic, forming a two-team ecosystem. Quantitatively predicting the ecological outcomes of such interactions remains challenging due to cellular diversity and interaction variability, and the exact dynamical regimes accessible to such a two-team ecosystem remain unknown. Here, we model tumor-immune interactions as a structured ecosystem with two competing teams using a generalized Lotka–Volterra framework and analyze it using the cavity method. We derive phase diagrams that delineate when these two communities coexist, when one dominates, and how these outcomes depend on intra-team cooperation, cross-team inhibition, and ecological heterogeneity. Our work provides a foundation for understanding tumor-immune dynamics from a community ecology perspective.
- The following article is Open accessQuantitative models of photoreceptor metabolisms: implications for rod outer segment length, retinal glycolysis and choroidal blood flow
Christina Kiel et al 2026 Phys. Biol. 23 036006
View article, Quantitative models of photoreceptor metabolisms: implications for rod outer segment length, retinal glycolysis and choroidal blood flowPDF, Quantitative models of photoreceptor metabolisms: implications for rod outer segment length, retinal glycolysis and choroidal blood flowThe outer retina exhibits several distinctive physiological features, including continuous turnover of rod photoreceptor outer segments (OS), a strong reliance on aerobic glycolysis despite oxygen availability, and an unusually high rate of choroidal blood flow. The mechanistic links between these phenomena remain incompletely understood. Here, we present a quantitative reaction–diffusion model of energy metabolism in rod photoreceptors that connects metabolic supply and demand to OS length and daily shedding. Because rod OS lack mitochondria, ATP and glycolytic intermediates must be supplied by diffusion from the inner segment, where oxidative phosphorylation and the initial steps of glycolysis occur. We model the diffusion and consumption of ATP and fructose-1,6-bisphosphate along the OS and show that diffusion-limited energy supply constrains OS length. Using literature-derived parameters, the model accurately predicts observed OS lengths in mammals (∼28 µm) and amphibians (∼50 µm), explains diurnal variations in OS length and tip shedding at light onset, and provides a unified explanation for the coexistence of high glycolytic flux, low oxygen extraction, and high choroidal blood flow in the outer retina. The model generates experimentally testable predictions regarding metabolite gradients along the OS and offers a general framework for understanding how metabolic constraints shape cellular morphology and tissue-level physiology.
- The following article is Open accessRoadmap on emerging concepts in the physical biology of bacterial biofilms: from surface sensing to community formation
Gerard C L Wong et al 2021 Phys. Biol. 18 051501
View article, Roadmap on emerging concepts in the physical biology of bacterial biofilms: from surface sensing to community formationPDF, Roadmap on emerging concepts in the physical biology of bacterial biofilms: from surface sensing to community formationBacterial biofilms are communities of bacteria that exist as aggregates that can adhere to surfaces or be free-standing. This complex, social mode of cellular organization is fundamental to the physiology of microbes and often exhibits surprising behavior. Bacterial biofilms are more than the sum of their parts: single-cell behavior has a complex relation to collective community behavior, in a manner perhaps cognate to the complex relation between atomic physics and condensed matter physics. Biofilm microbiology is a relatively young field by biology standards, but it has already attracted intense attention from physicists. Sometimes, this attention takes the form of seeing biofilms as inspiration for new physics. In this roadmap, we highlight the work of those who have taken the opposite strategy: we highlight the work of physicists and physical scientists who use physics to engage fundamental concepts in bacterial biofilm microbiology, including adhesion, sensing, motility, signaling, memory, energy flow, community formation and cooperativity. These contributions are juxtaposed with microbiologists who have made recent important discoveries on bacterial biofilms using state-of-the-art physical methods. The contributions to this roadmap exemplify how well physics and biology can be combined to achieve a new synthesis, rather than just a division of labor.
- The following article is Open accessDiversity in biology: definitions, quantification and models
Song Xu et al 2020 Phys. Biol. 17 031001
View article, Diversity in biology: definitions, quantification and modelsPDF, Diversity in biology: definitions, quantification and modelsDiversity indices are useful single-number metrics for characterizing a complex distribution of a set of attributes across a population of interest. The utility of these different metrics or sets of metrics depends on the context and application, and whether a predictive mechanistic model exists. In this topical review, we first summarize the relevant mathematical principles underlying heterogeneity in a large population, before outlining the various definitions of ‘diversity’ and providing examples of scientific topics in which its quantification plays an important role. We then review how diversity has been a ubiquitous concept across multiple fields, including ecology, immunology, cellular barcoding experiments, and socioeconomic studies. Since many of these applications involve sampling of populations, we also review how diversity in small samples is related to the diversity in the entire population. Features that arise in each of these applications are highlighted.
- The following article is Open accessThe 2019 mathematical oncology roadmap
Russell C Rockne et al 2019 Phys. Biol. 16 041005
Whether the nom de guerre is Mathematical Oncology, Computational or Systems Biology, Theoretical Biology, Evolutionary Oncology, Bioinformatics, or simply Basic Science, there is no denying that mathematics continues to play an increasingly prominent role in cancer research. Mathematical Oncology—defined here simply as the use of mathematics in cancer research—complements and overlaps with a number of other fields that rely on mathematics as a core methodology. As a result, Mathematical Oncology has a broad scope, ranging from theoretical studies to clinical trials designed with mathematical models. This Roadmap differentiates Mathematical Oncology from related fields and demonstrates specific areas of focus within this unique field of research. The dominant theme of this Roadmap is the personalization of medicine through mathematics, modelling, and simulation. This is achieved through the use of patient-specific clinical data to: develop individualized screening strategies to detect cancer earlier; make predictions of response to therapy; design adaptive, patient-specific treatment plans to overcome therapy resistance; and establish domain-specific standards to share model predictions and to make models and simulations reproducible. The cover art for this Roadmap was chosen as an apt metaphor for the beautiful, strange, and evolving relationship between mathematics and cancer.
- The following article is Open accessUnraveling the role of exercise in cancer suppression: insights from a mathematical model
Jay Taylor et al 2025 Phys. Biol. 22 016002
View article, Unraveling the role of exercise in cancer suppression: insights from a mathematical modelPDF, Unraveling the role of exercise in cancer suppression: insights from a mathematical modelRecent experimental studies have shown that physical exercise has the potential to suppress tumor progression. Such suppression has been reported to be mediated by the exercise-induced activation of natural killer (NK) cells through the release of IL-6, a cytokine. Aimed at shedding light on how exercise-induced NK cell activation helps in the suppression of cancer, we developed a coarse-grained mathematical model based on a system of ordinary differential equations describing the interaction between IL-6, NK-cells, and tumor cells. The model is then used to study how exercise duration and exercise intensity affect tumor suppression. Our results show that increasing exercise intensity or increasing exercise duration leads to greater and sustained tumor suppression. Furthermore, multi-bout exercise patterns hold promise for improving cancer treatment strategies by adjusting exercise intensity and frequency. Thus, the proposed mathematical model provides insights into the role of exercise in tumor suppression and can be instrumental in guiding future experimental studies, potentially leading to more effective exercise interventions.
- The following article is Open accessMethods in quantitative biology—from analysis of single-cell microscopy images to inference of predictive models for stochastic gene expression
Luis U Aguilera et al 2025 Phys. Biol. 22 042001
View article, Methods in quantitative biology—from analysis of single-cell microscopy images to inference of predictive models for stochastic gene expressionPDF, Methods in quantitative biology—from analysis of single-cell microscopy images to inference of predictive models for stochastic gene expressionThe field of quantitative biology (q-bio) seeks to provide precise and testable explanations for observed biological phenomena by applying mathematical and computational methods. The central goals of q-bio are to (1) systematically propose quantitative hypotheses in the form of mathematical models, (2) demonstrate that these models faithfully capture a specific essence of a biological process, and (3) correctly forecast the dynamics of the process in new, and previously untested circumstances. Achieving these goals depends on accurate analysis and incorporating informative experimental data to constrain the set of potential mathematical representations. In this introductory tutorial, we provide an overview of the state of the field and introduce some of the computational methods most commonly used in q-bio. In particular, we examine experimental techniques in single-cell imaging, computational tools to process images and extract quantitative data, various mechanistic modeling approaches used to reproduce these quantitative data, and techniques for data-driven model inference and model-driven experiment design. All topics are presented in the context of additional online resources, including open-source Python notebooks and open-ended practice problems that comprise the technical content of the annual Undergraduate Quantitative Biology Summer School (UQ-Bio).
- The following article is Open accessCell–extracellular matrix dynamics
Andrew D Doyle et al 2022 Phys. Biol. 19 021002
The sites of interaction between a cell and its surrounding microenvironment serve as dynamic signaling hubs that regulate cellular adaptations during developmental processes, immune functions, wound healing, cell migration, cancer invasion and metastasis, as well as in many other disease states. For most cell types, these interactions are established by integrin receptors binding directly to extracellular matrix proteins, such as the numerous collagens or fibronectin. For the cell, these points of contact provide vital cues by sampling environmental conditions, both chemical and physical. The overall regulation of this dynamic interaction involves both extracellular and intracellular components and can be highly variable. In this review, we highlight recent advances and hypotheses about the mechanisms and regulation of cell–ECM interactions, from the molecular to the tissue level, with a particular focus on cell migration. We then explore how cancer cell invasion and metastasis are deeply rooted in altered regulation of this vital interaction.
- Steady-state thermal homeostasis model of heat generated and dissipated in the human retina
Christina Kiel and Alexander J E Foss 2026 Phys. Biol. 23 046008
View article, Steady-state thermal homeostasis model of heat generated and dissipated in the human retinaPDF, Steady-state thermal homeostasis model of heat generated and dissipated in the human retinaThe retina is both metabolically active and exposed to light, resulting in persistent heat generation. However, the quantitative contributions of metabolic and irradiative heat sources, and the mechanisms responsible for dissipating this thermal load, remain incompletely characterized. Here we develop a steady-state quantitative thermal balance model of the retina that integrates heat production from metabolic activity and light absorption with multiple heat dissipation pathways into a unified energy balance framework. Metabolic heat was estimated from reported ATP consumption rates under dark—and light-adapted conditions, while irradiative heat input was quantified based on environmental luminance, pupil size, and ocular optics. These inputs were incorporated into a lumped energy balance in the form of
, allowing calculation of the retinal temperature elevation relative to blood, . Heat dissipation pathways, including conduction to surrounding tissue, choroidal blood perfusion, convection, and radiation, were expressed as thermal conductances, and analyzed within the same framework, . Under sunlight, total retinal heat input reached approximately 10 mW, approximately threefold higher than at night. Despite this, the predicted steady-state retinal temperature elevation remained very small (∼10−3 K), suggesting that heat is dissipated highly efficiently. The analysis shows that conduction and choroidal blood perfusion dominate retinal heat removal under physiological conditions, whereas radiation and convection contribute negligibly. The results suggest that retinal heat redistribution via conduction plays a major role in retinal thermal homeostasis, whereas choroidal blood perfusion primarily contributes to subsequent systemic heat removal rather than acting as a dominant limiting mechanism itself. This analysis provides quantitative support for the long-standing hypothesis that the choroid functions as a heat sink for the retina. - Nonequilibrium temperature fluctuations as modulators of mitochondrial elastocapillary stability
Peyman Fahimi 2026 Phys. Biol. 23 046007
View article, Nonequilibrium temperature fluctuations as modulators of mitochondrial elastocapillary stabilityPDF, Nonequilibrium temperature fluctuations as modulators of mitochondrial elastocapillary stabilityRecent studies have suggested that under high or near-maximal mitochondrial respiratory activity, ion-translocating proteins within the inner mitochondrial membrane may generate transient nonequilibrium temperature fluctuations in the adjacent mitochondrial matrix and intermembrane space. Such nonequilibrium temperature fluctuations may, in principle, influence mitochondrial mechanics and morphology. Building on elastocapillary models of mitochondrial dynamics, we investigate whether these nonequilibrium temperature fluctuations can modulate the stability of mitochondrial tubules through temperature-dependent changes in effective membrane tension and elasticity. Our numerical analysis predicts that this effect is strongly threshold-dependent: in deeply unstable states, thermal modulation remains insufficient to restore stability, whereas closer to the threshold, temperature-dependent reduction of effective membrane tension can overcome temperature-dependent elastic softening, thereby increasing the elastocapillary number, suppressing unstable modes, and shifting mitochondria toward mechanically more stable tubular states. In other words, when mitochondria begin shifting toward fission-promoting states, elevated respiratory activity, which increases the magnitude and cumulative temporal occupancy of transient thermal perturbations, tends to shift the system back toward mechanical stability. However, when mitochondria are already far within the mechanically unstable regime, transient thermal activity is no longer sufficient to restore stability. This stabilizing regime is qualitatively consistent with experimental observations linking elevated oxidative phosphorylation to mitochondrial elongation, fusion, or hyperfusion rather than fragmentation.
- Dynamical modeling and bifurcation analysis of malaria transmission under synergistic control of Wolbachia-infected male release and chemical insecticides
Xinyu Wang et al 2026 Phys. Biol. 23 046006
View article, Dynamical modeling and bifurcation analysis of malaria transmission under synergistic control of Wolbachia-infected male release and chemical insecticidesPDF, Dynamical modeling and bifurcation analysis of malaria transmission under synergistic control of Wolbachia-infected male release and chemical insecticidesIn this article, we integrate the release of Wolbachia-carrying male mosquitoes with chemical insecticide spraying to formulate a coupled model that incorporates mosquito stage structure and malaria transmission dynamics. The model accounts for mating competition influenced by cytoplasmic incompatibility and employs a Holling-II type saturated release mechanism to dynamically match the release intensity of infected male mosquitoes with the density of wild mosquitoes. The study first verifies the positive invariance and boundedness of solutions of the model. It then derives the basic reproduction number, followed by the existence conditions and stability properties of equilibria. Subsequently, it reveals saddle-node bifurcation, forward bifurcation, backward bifurcation and their compound phenomena, thereby elucidating the abrupt dynamic changes near parameter thresholds of the system. Numerical simulations validate the theoretical results, quantify the regulatory effects of key parameters, and confirm that the combined strategy effectively suppresses mosquito population growth and interrupts malaria transmission through synergistic effects. The results illustrate that accurate tuning of critical parameters for the integrated control strategy and exploitation of synergism between Wolbachia and chemical insecticides can effectively modulate mosquito populations and block malaria transmission.
- The following article is Open accessEffect of high mobility group box-1 on receptor for advanced glycation endproducts (RAGE) and toll-like receptor-4 (TLR4) diffusion and signaling
Sharifur Rahman et al 2026 Phys. Biol. 23 046005
View article, Effect of high mobility group box-1 on receptor for advanced glycation endproducts (RAGE) and toll-like receptor-4 (TLR4) diffusion and signalingPDF, Effect of high mobility group box-1 on receptor for advanced glycation endproducts (RAGE) and toll-like receptor-4 (TLR4) diffusion and signalingHigh mobility group box-1 (HMGB1) is a damage-associated molecular pattern and a ligand for multiple immune receptors, including receptors for advanced glycation endproducts (RAGE) and toll-like receptor 4 (TLR4). Binding of HMGB1 to these receptors initiates inflammatory signaling cascades implicated in diseases such as septic shock, chronic inflammation, and autoimmune disorders. The spatial and molecular mechanisms underlying HMGB1-mediated receptor signaling at the plasma membrane remain poorly understood. Here, single-particle tracking was used to investigate the effects of extracellular HMGB1 on RAGE’s and TLR4’s diffusion properties in human embryonic kidney 293 (HEK293) cells. HMGB1 treatment reduced the Brownian diffusion coefficients by 27% and 24% for RAGE (with and without TLR4 co-expression, respectively) and by 40% and 21% for TLR4 (with and without RAGE co-expression, respectively). HMGB1 treatment reduced the size of the confined domains the receptors diffuse into and increased the number of times the two receptors came in close proximity. In contrast, HMGB1 had no detectable effect on the diffusion properties of an S391A RAGE mutant, which lacks the ability to recruit adapter proteins. Lipid diffusion measurements revealed that HMGB1 treatment decreases lipid membrane fluidity in all cell lines studied. Similarly, phalloidin staining revealed no detectable HMGB1-induced changes in actin organization in RAGE expressing cells. Functionally, HMGB1 treatment activated the extracellular signal-regulated kinase (ERK) (1/2) signaling pathway through both RAGE and TLR4, whereas ERK (1/2) and p38 MAPK activation by HMGB1 were abolished in cells expressing S391A RAGE. Together, these findings show that HMGB1 reduced confined receptor diffusion and increased nanoscale proximity while promoting MAPK signaling. This work sheds new light on the nanoscale regulation of innate immune receptors by HMGB1 and emphasizes membrane biophysics as one critical component of inflammatory signaling outcomes.
- Scaling of the Bicoid morphogen gradient: the effect of state dependent diffusion
Priya Chakraborty et al 2026 Phys. Biol. 23 046004
View article, Scaling of the Bicoid morphogen gradient: the effect of state dependent diffusionPDF, Scaling of the Bicoid morphogen gradient: the effect of state dependent diffusionThe mechanisms underlying the scaling of the Bicoid morphogen gradient in Drosophila with the embryo size is not clearly understood. We propose a model with a spatially varying diffusion coefficient along the anterior–posterior axis, that is proportional to the nearly periodic spatial distribution of the nucleo-cytoplasmic domains and alternating between regions of fast and slow diffusion. We postulate that for specific interpretation of the heterogeneous environment, where the space available for free diffusion within an energid is assumed to be proportional to the embryo size, a change in the embryo size can lead to a size-dependent scaling of the gradient lengthscale. We further study a two component model with slow and fast diffusing Bicoid, and identify this model to be equivalent to the heterogeneous diffusion model further postulating that the fast-state occupancy which is a measure of the fraction of time spent in the fast diffusing state, should also scale with the embryo size via the energid size. Finally, we incorporate nuclear shuttling into our model to understand the effect of shuttling on the gradient lengthscale and scaling with embryo size. We argue that for the particular case where the degradation within the nucleus is low, nuclear shuttling does not perturb the Bicoid gradient. Our study suggests that spatial heterogeneity is able to generate scaling, independent of nuclear trapping. This mechanism may act in conjunction with other biological processes, to yield the experimentally observed scaling behavior of the Bicoid gradient.
- Comparative thermodynamic and kinetic properties governing the nucleic acid interactions of CRISPR-Cas9 and Cas12a
Camila E Molina et al 2026 Phys. Biol. 23 021001
View article, Comparative thermodynamic and kinetic properties governing the nucleic acid interactions of CRISPR-Cas9 and Cas12aPDF, Comparative thermodynamic and kinetic properties governing the nucleic acid interactions of CRISPR-Cas9 and Cas12aClustered regularly interspaced short palindromic repeat-associated proteins (CRISPR-Cas) biochemistry has been leveraged for genome editing applications in biochemical research and therapeutics. CRISPR-Cas9 and CRISPR-Cas12a are the two most widely used RNA-guided endonucleases and while Cas9 and Cas12a have a shared function, both have unique biophysical properties that alter their specificity and efficiency. The thermodynamic and kinetic properties governing their molecular interactions, recognition and binding of target DNA, and R-loop formation can differ. In some cases, these critical biophysical metrics have not been resolved. Distinctions between Cas9 and Cas12a enzymes are also prevalent in RNA:DNA hybrid binding affinities, DNA localization relative to the preferred PAM site and the DNA cleavage mechanism. In this review, we examine the thermodynamic and kinetic properties of both endonucleases, focused on the nucleic acid interactions that confer specificity and function. Complementing this biophysical overview, we discuss case studies in disparate model organisms that compare the genome editing and fidelity of Cas9 and Cas12a.
- The following article is Open accessPhysical and chemical considerations for successful in vitro culture of rust fungi: challenges, insights and novel strategies
Sarah Sale et al 2026 Phys. Biol. 23 011002
View article, Physical and chemical considerations for successful in vitro culture of rust fungi: challenges, insights and novel strategiesPDF, Physical and chemical considerations for successful in vitro culture of rust fungi: challenges, insights and novel strategiesRust fungi cause significant economic and biodiversity losses worldwide, yet effective control strategies for them remain limited. A major challenge in identifying control targets is the inability to culture them through the different stages of their life cycle in the laboratory, thereby restricting their study. Current research suggests that a complex interplay of physical and chemical plant properties influences rust fungal infection, and successful culture protocols likely need to incorporate multiple aspects of the plant host environment into an artificial system. These include plant surface moisture, charge, hardness, hydrophobicity, topography, texture and chemical make-up. This review outlines key plant characteristics that influence infection by rust fungi, examines attempts to replicate these characteristics in vitro, and assesses the level of success. We conclude by proposing a potential culture approach that integrates inoculation methods, media composition, physical properties of media, chemical additives, and environmental conditions.
- The following article is Open accessCW ESR spectroscopy and protein spin labeling in membrane biology
Olamide Ishola et al 2026 Phys. Biol. 23 011001
View article, CW ESR spectroscopy and protein spin labeling in membrane biologyPDF, CW ESR spectroscopy and protein spin labeling in membrane biologyBiological membranes define cellular and organelle boundaries, and perform vital functions, providing transport, recognition, signaling, and interaction with other cells. These membranes are majorly composed of lipid bilayers and membrane proteins. Membrane proteins perform most membrane functions. Based on their localization, they are classified as integral and peripheral proteins. In this overview, we provide basic information about membrane proteins structure, conformational dynamics, and functions, and outline the methodologies used to produce highly-pure functional membrane proteins for in vitro biophysical characterizations based on selected examples. To this end, expression of membrane proteins in a host, their extraction, purification and reconstitution in model lipid bilayers are described. Further, biophysical approaches play key role in elucidation of the structure and function of membrane proteins. Our focus here is on the technique of continuous wave electron paramagnetic/spin resonance (CW ESR) spectroscopy applied to spin-labeled membrane proteins. We describe the basic principles of membrane proteins labeling with nitroxide spin labels (paramagnetic tags) and how the CW ESR can be successfully used in elucidating the conformational dynamics of such proteins. We describe the basic principles of the CW ESR technique. The capability of this technique to characterize physiologically relevant conformational dynamics of proteins is demonstrated using two examples of CW ESR studies on spin-labeled human Tau and influenza A M2 proteins. The method is highly suitable to study physiological structure-function relationships of a broad range of proteins, and to explain the malfunctional states of proteins linked to diseases. This review is directed to the broader biophysical community with interest in molecular biophysics of biological membranes.
- The following article is Open accessMethods in quantitative biology—from analysis of single-cell microscopy images to inference of predictive models for stochastic gene expression
Luis U Aguilera et al 2025 Phys. Biol. 22 042001
View article, Methods in quantitative biology—from analysis of single-cell microscopy images to inference of predictive models for stochastic gene expressionPDF, Methods in quantitative biology—from analysis of single-cell microscopy images to inference of predictive models for stochastic gene expressionThe field of quantitative biology (q-bio) seeks to provide precise and testable explanations for observed biological phenomena by applying mathematical and computational methods. The central goals of q-bio are to (1) systematically propose quantitative hypotheses in the form of mathematical models, (2) demonstrate that these models faithfully capture a specific essence of a biological process, and (3) correctly forecast the dynamics of the process in new, and previously untested circumstances. Achieving these goals depends on accurate analysis and incorporating informative experimental data to constrain the set of potential mathematical representations. In this introductory tutorial, we provide an overview of the state of the field and introduce some of the computational methods most commonly used in q-bio. In particular, we examine experimental techniques in single-cell imaging, computational tools to process images and extract quantitative data, various mechanistic modeling approaches used to reproduce these quantitative data, and techniques for data-driven model inference and model-driven experiment design. All topics are presented in the context of additional online resources, including open-source Python notebooks and open-ended practice problems that comprise the technical content of the annual Undergraduate Quantitative Biology Summer School (UQ-Bio).
- Effect of membrane tension on pore formation induced by antimicrobial peptides and other membrane-active peptides
Marzuk Ahmed et al 2025 Phys. Biol. 22 031001
View article, Effect of membrane tension on pore formation induced by antimicrobial peptides and other membrane-active peptidesPDF, Effect of membrane tension on pore formation induced by antimicrobial peptides and other membrane-active peptidesMembrane tension plays an important role in various aspects of the dynamics and functions of cells. Here, we review recent studies of the effect of membrane tension on pore formation in lipid bilayers and pore formation induced by membrane-active peptides (MAPs) including antimicrobial peptides (AMPs). For this purpose, the micropipette aspiration method using a patch of cell membrane/lipid bilayers and a giant unilamellar vesicle (GUV)/a total cell, and the application of osmotic pressure (Π) to suspensions of large unilamellar vesicles (LUVs) have been used. However, these conventional methods have some drawbacks for the investigation of the effect of membrane tension on the actions of MAPs such as AMPs. Recently, to overcome these drawbacks, a new Π method using GUVs has been developed. Here, we focus on this Π method as a new technique for revealing the effect of membrane tension on the MAPs-induced pore formation. Firstly, we review studies of the effect of membrane tension on pore formation in lipid bilayers as determined by conventional methods. Secondly, after a brief review of studies of the effect of Π on LUVs, we describe the estimation of membrane tension in GUVs induced by Π and the Π-induced pore formation. Thirdly, after a review of the effect of membrane tension on the MAPs-induced pore formation as obtained by the conventional methods, we describe an application of the Π method to studies of the effect of membrane tension on AMP-induced pore formation. Finally, we discuss the advantages of the Π method over conventional methods and consider future perspectives.
- Role of hydrodynamic interactions in chemotaxis of bacterial populations
Shawn D Ryan 2020 Phys. Biol. 17 016003
View article, Role of hydrodynamic interactions in chemotaxis of bacterial populationsPDF, Role of hydrodynamic interactions in chemotaxis of bacterial populationsHow bacteria sense local chemical gradients and decide to move has been a fascinating area of recent study. Chemotaxis of bacterial populations has been traditionally modeled using either individual-based models describing the motion of a single bacterium as a velocity jump process, or macroscopic PDE models that describe the evolution of the bacterial density. In these models, the hydrodynamic interaction between the bacteria is usually ignored. However, hydrodynamic interaction has been shown to induce collective bacterial motion and self-organization resulting in larger mesoscale structures. In this paper, the role of hydrodynamic interactions in bacterial chemotaxis is investigated by extending a hybrid computational model that incorporates hydrodynamic interactions and adding components from a classical velocity jump model. It is shown that by including hydrodynamic interactions, a suspension with a low initial volume fraction can exhibit locally high concentrations in bacterial aggregates. Also, it is shown that hydrodynamic interactions enhance the merging of the small aggregates into larger ones and lead to qualitatively different aggregate behavior than possible with pure chemotaxis models. Namely, differences in the shape, number, and dynamics of these emergent clusters.
- Stochastic models of polymerization-based axonal actin transport
Nilaj Chakrabarty and Peter Jung 2019 Phys. Biol. 16 056001
View article, Stochastic models of polymerization-based axonal actin transportPDF, Stochastic models of polymerization-based axonal actin transportRecent advances in live cell imaging of F-actin structures, combined with pulse-chase imaging and computational modeling have suggested that actin is transported along the axon via biased polymerization of metastable actin fibers (actin trails). This mechanism is distinct from motor driven polymer transport, such as for neurofilaments and can be best described as molecular hitchhiking, where G-actin molecules are intermittently incorporated into actin fibers which grow preferentially in the anterograde direction. In this paper, we discuss how various axonal and actin trail parameters like axon diameter, trail nucleation rates, basal G-actin concentration, and trail length influence the transport rate. These predictions can help guide future experiments to verify this novel protein transport mechanism. We introduce a simplified, analytically solvable model of actin transport which relates these parameters to experimentally measurable quantities. We also discuss why a simple diffusion-based transport mechanism cannot explain bulk actin transport in the axon.
- Evaluating single-particle tracking by photo-activation localization microscopy (sptPALM) in Lactococcus lactis
Sam P B van Beljouw et al 2019 Phys. Biol. 16 035001
View article, Evaluating single-particle tracking by photo-activation localization microscopy (sptPALM) in Lactococcus lactisPDF, Evaluating single-particle tracking by photo-activation localization microscopy (sptPALM) in Lactococcus lactisLactic acid bacteria (LAB) are frequently used in food fermentation and are invaluable for the taste and nutritional value of the fermentation end-product. To gain a better understanding of underlying biochemical and microbiological mechanisms and cell-to-cell variability in LABs, single-molecule techniques such as single-particle tracking photo-activation localization microscopy (sptPALM) hold great promises but are not yet employed due to the lack of detailed protocols and suitable assays.
Here, we qualitatively test various fluorescent proteins including variants that are photoactivatable and therefore suitable for sptPALM measurements in Lactococcus lactis, a key LAB for the dairy industry. In particular, we fused PAmCherry2 to dCas9 allowing the successful tracking of single dCas9 proteins, whilst the dCas9 chimeras bound to specific guide RNAs retained their gene silencing ability in vivo. The diffusional information of the dCas9 without any targets showed different mechanistic states of dCas9: freely diffusing, bound to DNA, or transiently interacting with DNA. The capability of performing sptPALM with dCas9 in L. lactis can lead to a better, general understanding of CRISPR-Cas systems as well as paving the way for CRISPR-Cas based interrogations of cellular functions in LABs.
- Random walker models for durotaxis
Charles R Doering et al 2018 Phys. Biol. 15 066009
Motile biological cells in tissue often display the phenomenon of durotaxis, i.e. they tend to move towards stiffer parts of substrate tissue. The mechanism for this behavior is not completely understood. We consider simplified models for durotaxis based on the classic persistent random walker scheme. We show that even a one-dimensional model of this type sheds interesting light on the classes of behavior cells might exhibit. Our results strongly indicate that cells must be able to sense the gradient of stiffness in order to show the effects observed in experiment. This is in contrast to the claims in recent publications that it is sufficient for cells to be more persistent in their motion on stiff substrates to show durotaxis: i.e. it would be enough to sense the value of the stiffness. We show that these cases give rise to extremely inefficient transport towards stiff regions. Gradient sensing is almost certainly the selected behavior.
- Nanoscale insight into silk-like protein self-assembly: effect of design and number of repeat units
Jamoliddin Razzokov et al 2018 Phys. Biol. 15 066010
View article, Nanoscale insight into silk-like protein self-assembly: effect of design and number of repeat unitsPDF, Nanoscale insight into silk-like protein self-assembly: effect of design and number of repeat unitsBy means of replica exchange molecular dynamics simulations we investigate how the length of a silk-like, alternating diblock oligopeptide influences its secondary and quaternary structure. We carry out simulations for two protein sizes consisting of three and five blocks, and study the stability of a single protein, a dimer, a trimer and a tetramer. Initial configurations of our simulations are β-roll and β-sheet structures. We find that for the triblock the secondary and quaternary structures upto and including the tetramer are unstable: the proteins melt into random coil structures and the aggregates disassemble either completely or partially. We attribute this to the competition between conformational entropy of the proteins and the formation of hydrogen bonds and hydrophobic interactions between proteins. This is confirmed by our simulations on the pentablock proteins, where we find that, as the number of monomers in the aggregate increases, individual monomers form more hydrogen bonds whereas their solvent accessible surface area decreases. For the pentablock β-sheet protein, the monomer and the dimer melt as well, although for the β-roll protein only the monomer melts. For both trimers and tetramers remain stable. Apparently, for these the entropy loss of forming β-rolls and β-sheets is compensated for in the free-energy gain due to the hydrogen-bonding and hydrophobic interactions. We also find that the middle monomers in the trimers and tetramers are conformationally much more stable than the ones on the top and the bottom. Interestingly, the latter are more stable on the tetramer than on the trimer, suggesting that as the number of monomers increases protein-protein interactions cooperatively stabilize the assembly. According to our simulations, the β-roll and β-sheet aggregates must be approximately equally stable.
- The following article is Open accessSpanning-tree thermostatistics of protein allostery: An exact Kirchhoff framework with application to oncogenic KRAS
Senguler Ciftci et al
View accepted manuscript, Spanning-tree thermostatistics of protein allostery: An exact Kirchhoff framework with application to oncogenic KRASPDF, Spanning-tree thermostatistics of protein allostery: An exact Kirchhoff framework with application to oncogenic KRASThis study introduces a statistical mechanical framework for allosteric communication in proteins based on the spanning-tree ensemble of residue contact networks. By representing Cα protein backbones as weighted graphs, we identify each spanning tree as a topological microstate. The canonical partition function is evaluated analytically via the determinant of the reduced weighted Kirchhoff (Laplacian) matrix, allowing for the derivation of global thermodynamic functions (including Helmholtz free energy, internal energy, entropy, and heat capacity) without stochastic sampling.
Allosteric channels between specific residue pairs are defined as sub-ensembles containing unique simple paths. Using the Burton-Pemantle theorem and the Moore-Penrose pseudoinverse of the graph Laplacian, we compute path probabilities and channel-specific thermodynamics. This methodology enables a decomposition of channel heat capacity into energetic and topological components and quantifies residue-level allosteric importance through fractional contributions to the channel partition function.
The framework was applied to the G12D mutation in KRAS, comparing wild-type (PDB: 6GOD) and mutant (PDB: 6GOF) structures. Results show that while global thermodynamic properties remain highly conserved across the tight structural superposition, channel-level analysis shows a substantial internal redistribution of allosteric importance among intermediate residues, highlighted by the primary 12–61 signaling axis and distal routes (including shifts in residues such as Q61 and F156). Operating on Cα backbone geometry, these topological shifts provide predictive hypotheses for subsequent molecular dynamics and experimental testing. Overall, this approach offers a rigorous, parameter-robust framework for understanding how point mutations perturb distal signaling networks.
- The following article is Open accessSpanning-tree thermostatistics of protein allostery: An exact Kirchhoff framework with application to oncogenic KRAS
Fatma Senguler Ciftci and Burak Erman 2026 Phys. Biol.
View article, Spanning-tree thermostatistics of protein allostery: An exact Kirchhoff framework with application to oncogenic KRASPDF, Spanning-tree thermostatistics of protein allostery: An exact Kirchhoff framework with application to oncogenic KRASThis study introduces a statistical mechanical framework for allosteric communication in proteins based on the spanning-tree ensemble of residue contact networks. By representing Cα protein backbones as weighted graphs, we identify each spanning tree as a topological microstate. The canonical partition function is evaluated analytically via the determinant of the reduced weighted Kirchhoff (Laplacian) matrix, allowing for the derivation of global thermodynamic functions (including Helmholtz free energy, internal energy, entropy, and heat capacity) without stochastic sampling.
Allosteric channels between specific residue pairs are defined as sub-ensembles containing unique simple paths. Using the Burton-Pemantle theorem and the Moore-Penrose pseudoinverse of the graph Laplacian, we compute path probabilities and channel-specific thermodynamics. This methodology enables a decomposition of channel heat capacity into energetic and topological components and quantifies residue-level allosteric importance through fractional contributions to the channel partition function.
The framework was applied to the G12D mutation in KRAS, comparing wild-type (PDB: 6GOD) and mutant (PDB: 6GOF) structures. Results show that while global thermodynamic properties remain highly conserved across the tight structural superposition, channel-level analysis shows a substantial internal redistribution of allosteric importance among intermediate residues, highlighted by the primary 12–61 signaling axis and distal routes (including shifts in residues such as Q61 and F156). Operating on Cα backbone geometry, these topological shifts provide predictive hypotheses for subsequent molecular dynamics and experimental testing. Overall, this approach offers a rigorous, parameter-robust framework for understanding how point mutations perturb distal signaling networks.
- The following article is Open accessEffect of high mobility group box-1 on receptor for advanced glycation endproducts (RAGE) and toll-like receptor-4 (TLR4) diffusion and signaling
Sharifur Rahman et al 2026 Phys. Biol. 23 046005
View article, Effect of high mobility group box-1 on receptor for advanced glycation endproducts (RAGE) and toll-like receptor-4 (TLR4) diffusion and signalingPDF, Effect of high mobility group box-1 on receptor for advanced glycation endproducts (RAGE) and toll-like receptor-4 (TLR4) diffusion and signalingHigh mobility group box-1 (HMGB1) is a damage-associated molecular pattern and a ligand for multiple immune receptors, including receptors for advanced glycation endproducts (RAGE) and toll-like receptor 4 (TLR4). Binding of HMGB1 to these receptors initiates inflammatory signaling cascades implicated in diseases such as septic shock, chronic inflammation, and autoimmune disorders. The spatial and molecular mechanisms underlying HMGB1-mediated receptor signaling at the plasma membrane remain poorly understood. Here, single-particle tracking was used to investigate the effects of extracellular HMGB1 on RAGE’s and TLR4’s diffusion properties in human embryonic kidney 293 (HEK293) cells. HMGB1 treatment reduced the Brownian diffusion coefficients by 27% and 24% for RAGE (with and without TLR4 co-expression, respectively) and by 40% and 21% for TLR4 (with and without RAGE co-expression, respectively). HMGB1 treatment reduced the size of the confined domains the receptors diffuse into and increased the number of times the two receptors came in close proximity. In contrast, HMGB1 had no detectable effect on the diffusion properties of an S391A RAGE mutant, which lacks the ability to recruit adapter proteins. Lipid diffusion measurements revealed that HMGB1 treatment decreases lipid membrane fluidity in all cell lines studied. Similarly, phalloidin staining revealed no detectable HMGB1-induced changes in actin organization in RAGE expressing cells. Functionally, HMGB1 treatment activated the extracellular signal-regulated kinase (ERK) (1/2) signaling pathway through both RAGE and TLR4, whereas ERK (1/2) and p38 MAPK activation by HMGB1 were abolished in cells expressing S391A RAGE. Together, these findings show that HMGB1 reduced confined receptor diffusion and increased nanoscale proximity while promoting MAPK signaling. This work sheds new light on the nanoscale regulation of innate immune receptors by HMGB1 and emphasizes membrane biophysics as one critical component of inflammatory signaling outcomes.
- The following article is Open accessQuantitative models of photoreceptor metabolisms: implications for rod outer segment length, retinal glycolysis and choroidal blood flow
Christina Kiel et al 2026 Phys. Biol. 23 036006
View article, Quantitative models of photoreceptor metabolisms: implications for rod outer segment length, retinal glycolysis and choroidal blood flowPDF, Quantitative models of photoreceptor metabolisms: implications for rod outer segment length, retinal glycolysis and choroidal blood flowThe outer retina exhibits several distinctive physiological features, including continuous turnover of rod photoreceptor outer segments (OS), a strong reliance on aerobic glycolysis despite oxygen availability, and an unusually high rate of choroidal blood flow. The mechanistic links between these phenomena remain incompletely understood. Here, we present a quantitative reaction–diffusion model of energy metabolism in rod photoreceptors that connects metabolic supply and demand to OS length and daily shedding. Because rod OS lack mitochondria, ATP and glycolytic intermediates must be supplied by diffusion from the inner segment, where oxidative phosphorylation and the initial steps of glycolysis occur. We model the diffusion and consumption of ATP and fructose-1,6-bisphosphate along the OS and show that diffusion-limited energy supply constrains OS length. Using literature-derived parameters, the model accurately predicts observed OS lengths in mammals (∼28 µm) and amphibians (∼50 µm), explains diurnal variations in OS length and tip shedding at light onset, and provides a unified explanation for the coexistence of high glycolytic flux, low oxygen extraction, and high choroidal blood flow in the outer retina. The model generates experimentally testable predictions regarding metabolite gradients along the OS and offers a general framework for understanding how metabolic constraints shape cellular morphology and tissue-level physiology.
- The following article is Open accessEcological dynamics of pro-tumor and anti-tumor teams in the tumor microenvironment
Vaibhav Anand et al 2026 Phys. Biol. 23 036005
View article, Ecological dynamics of pro-tumor and anti-tumor teams in the tumor microenvironmentPDF, Ecological dynamics of pro-tumor and anti-tumor teams in the tumor microenvironmentTumor growth occurs within a complex tumor microenvironment (TME) composed of many interacting cell types. However, the signs of tumor-immune interactions in this ecosystem are not random and possess a structure, the immune cell types in the TME tend to organize into two functional communities: a pro-tumor team and an anti-tumor team, each internally cooperative but mutually antagonistic, forming a two-team ecosystem. Quantitatively predicting the ecological outcomes of such interactions remains challenging due to cellular diversity and interaction variability, and the exact dynamical regimes accessible to such a two-team ecosystem remain unknown. Here, we model tumor-immune interactions as a structured ecosystem with two competing teams using a generalized Lotka–Volterra framework and analyze it using the cavity method. We derive phase diagrams that delineate when these two communities coexist, when one dominates, and how these outcomes depend on intra-team cooperation, cross-team inhibition, and ecological heterogeneity. Our work provides a foundation for understanding tumor-immune dynamics from a community ecology perspective.
- The following article is Open accessRobust chemotaxis beyond sensing limits: signal, noise, and strategy
Robert G Endres 2026 Phys. Biol. 23 036003
View article, Robust chemotaxis beyond sensing limits: signal, noise, and strategyPDF, Robust chemotaxis beyond sensing limits: signal, noise, and strategyBacterial 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.
- The following article is Open accessHow exercise scheduling affects IL-6-mediated tumor suppression: a fixed exercise volume perspective
Mary L DorChhuon et al 2026 Phys. Biol. 23 036002
View article, How exercise scheduling affects IL-6-mediated tumor suppression: a fixed exercise volume perspectivePDF, How exercise scheduling affects IL-6-mediated tumor suppression: a fixed exercise volume perspectiveRecent investigations into exercise-induced tumor suppression suggest that higher exercise frequency enhances tumor control when the total duration of exercise within a specified time window is not constrained. An equally compelling avenue for exploration is the effect of increased exercise frequency under the condition of a fixed total exercise duration within the same time frame. Using a mathematical model of IL-6-mediated interactions between natural killer cells and tumor cells, here we explore how different combinations of exercise and rest intervals–while maintaining a constant overall exercise volume–affect tumor suppression. Our results reveal a nonmonotonic tumor response and key metrics such as the time of maximum tumor suppression and the duration of tumor suppression are found to decrease with increasing exercise frequency. Interestingly, unlike earlier study where increasing exercise frequency leads to increase in tumor suppression, here we find that under fixed exercise volume constraints, increased frequency diminishes therapeutic efficacy of exercise, suggesting exercise bouts with longer duration are more effective in suppressing tumors. These findings highlight the importance of considering total exercise volume when designing exercise-based cancer interventions.
- The following article is Open accessBoth sides now: modeling motor regulation of microtubule length at both ends
Maria-Veronica Ciocanel and Bhargav R Karamched 2026 Phys. Biol. 23 036001
View article, Both sides now: modeling motor regulation of microtubule length at both endsPDF, Both sides now: modeling motor regulation of microtubule length at both endsMicrotubules are dynamic biopolymers whose lengths are continuously regulated by the concerted actions of polymerization, depolymerization, and motor-protein activity. While numerous mathematical models have explored the regulation of filament length, most have been formulated in the context of growth and shrinking at a single tip of a microtubule, effectively ignoring the mechanistic description of complex phenomena such as treadmilling. Here, we develop a multiscale model for microtubule length regulation that explicitly couples the kinetics of two classes of kinesin molecular motors to filament dynamics at both microtubule tips. Motor densities along the filament are modeled using one-dimensional parabolic partial differential equations. The microtubule length evolves dynamically through a shrinkage term that depends on motor density and which closes the system. In the adiabatic regime, where motor kinetics are fast relative to length dynamics, we derive a reduced model amenable to analytic study and identify simple parameter relationships distinguishing growth, disassembly, and treadmilling behavior. Numerical simulations of the full system reveal qualitatively distinct dynamical regimes and demonstrate how bidirectional motor transport modulates filament length distributions. We parametrize our model with both in vivo and in vitro data and thus lay the foundation for developing mathematical models yielding a better understanding of cytoskeleton dynamics in living cells.
- The following article is Open accessEncounter times of intermittently running particles
Lizzy Teryoshin et al 2026 Phys. Biol. 23 026010
View article, Encounter times of intermittently running particlesPDF, Encounter times of intermittently running particlesIntracellular processes often rely on the timely encounter of mobile reaction partners, including intermittently motor-driven organelles. The underlying cytoskeletal network presents a complex landscape that both directs particle movement and introduces quenched disorder through filament organization. We investigate the mean first encounter times for pairs of intermittently processive and diffusive particles, moving in two dimensions with and without a fixed filament network. In unstructured domains, increasing particle run-length enhances exploration of the domain, but tends to slow down the encounter times compared to equivalent diffusing particles. Encounters for long-running particles occur preferentially near the periphery, contrasting with bulk encounters for the purely diffusive case. When particles are unbiased in their runs along dense filament networks, encounters are shown to be well approximated by a continuum run-and-tumble model. For biased particles, regions of convergent filament orientation serve as traps that slow the overall spatial exploration but can allow for faster encounter rates by funneling particles into regions of reduced dimensionality. These findings provide a framework for estimating intracellular encounter kinetics, highlighting the role of key physical features such as the effective diffusivity, run times, and network architecture.
- The following article is Open accessAC electro-osmosis in bacterial communities with fluorescence-based electrophysiology measurements using exogeneous fluorophores
Victor Carneiro da Cunha Martorelli et al 2026 Phys. Biol. 23 026009
View article, AC electro-osmosis in bacterial communities with fluorescence-based electrophysiology measurements using exogeneous fluorophoresPDF, AC electro-osmosis in bacterial communities with fluorescence-based electrophysiology measurements using exogeneous fluorophoresSynthetic cationic fluorophores are widely used as probes to measure the membrane potentials of bacterial cells, eukaryotic cells, and organelles (such as mitochondria) in electrophysiology experiments and live/dead assays. We applied an external oscillating electric field to Escherichia coli using microelectrodes and observed that AC electro-osmosis caused fluorescence transients independent of bacterial electrophysiology, which could be mistaken for membrane depolarisation events. The fluorophores migrated within the microfluidic device in vortices, leading to concentration fluctuations manifested as dips in fluorescence. These fluorescent dips were universally present when using cationic fluorophores such as thioflavin-T, propidium iodide, Syto9, and Sytox Green, with or without E. coli present, whenever AC voltages were applied. Furthermore, we also demonstrate that fluorescence dips in dense bacterial communities can arise from AC electro-osmosis rather than ion-channel activity. This cautionary tale highlights how electrical stimulation experiments in microbial communities can yield misleading results if electrokinetic effects are not accounted for. We quantified the relaxation times of fluorophores under AC electro-osmosis, which depended on the community, the cells, and the dye used: PI showed the shortest relaxation time and Syto9 the longest. Removing cells resulted in longer relaxation times, and introducing dense communities did not significantly alter the relaxation times compared with single-cell experiments. Furthermore, fluorescently labelled DNA and fluorescent colloidal beads (30–130 nm) also exhibited fluorescence dips due to AC electro-osmosis, demonstrating that charged molecules and particles readily penetrate and accumulate within these assemblies. To our knowledge, this is the first study to characterise AC electro-osmosis in dense bacterial communities, revealing the high mobility of charged molecules in such systems and suggesting possible applications for enhancing antibiotic delivery.
- The following article is Open accessEffect of G4C2 repeat expansions on the motion of lysosomes inside neurites
Maria Mytiliniou et al 2026 Phys. Biol. 23 026008
View article, Effect of G4C2 repeat expansions on the motion of lysosomes inside neuritesPDF, Effect of G4C2 repeat expansions on the motion of lysosomes inside neuritesThe G4C2 hexanucleotide repeat expansion (HRE) in the c9orf72 locus is a mutation associated with amyotrophic lateral sclerosis. Recent evidence suggests a link with disrupted axonal trafficking in neurons. Here, using a neuronal-like cell line without or transfected with G4C2 repeats, we characterize the motion of lysosomes inside neurites. The neurites grew either aligned to patterned lines, or oriented freely on a 2D-substrate. Implementing time-resolved (local) mean squared displacement analysis lysosome trajectories were split into sub-diffusive, diffusive, and super-diffusive parts. Our results suggest that in the presence of the G4C2 repeats, lysosome trafficking is hampered, exhibiting overall decreased mean squared displacement and speed, more prominently inside aligned neurites. Moreover, a prominent effect in the super-diffusive drift velocity and diffusive motion diffusion coefficient was evident when the motion occurred inside aligned neurites. Trajectories which included super-diffusive motion, exhibited a varied ratio of anterograde/retrograde/neutral for both neurite geometries in the presence of G4C2 repeats but a similar velocity decrease for both directions in each neurite geometry. Our findings support the hypothesis that impaired axonal trafficking emerges in the presence of the G4C2 HRE, and demonstrate that this effect is more prominent when the neurites are aligned.
- Physical root–soil interactions
Evelyne Kolb et al 2017 Phys. Biol. 14 065004
Plant root system development is highly modulated by the physical properties of the soil and especially by its mechanical resistance to penetration. The interplay between the mechanical stresses exerted by the soil and root growth is of particular interest for many communities, in agronomy and soil science as well as in biomechanics and plant morphogenesis. In contrast to aerial organs, roots apices must exert a growth pressure to penetrate strong soils and reorient their growth trajectory to cope with obstacles like stones or hardpans or to follow the tortuous paths of the soil porosity. In this review, we present the main macroscopic investigations of soil-root physical interactions in the field and combine them with simple mechanistic modeling derived from model experiments at the scale of the individual root apex.
- The following article is Open accessCell–extracellular matrix dynamics
Andrew D Doyle et al 2022 Phys. Biol. 19 021002
The sites of interaction between a cell and its surrounding microenvironment serve as dynamic signaling hubs that regulate cellular adaptations during developmental processes, immune functions, wound healing, cell migration, cancer invasion and metastasis, as well as in many other disease states. For most cell types, these interactions are established by integrin receptors binding directly to extracellular matrix proteins, such as the numerous collagens or fibronectin. For the cell, these points of contact provide vital cues by sampling environmental conditions, both chemical and physical. The overall regulation of this dynamic interaction involves both extracellular and intracellular components and can be highly variable. In this review, we highlight recent advances and hypotheses about the mechanisms and regulation of cell–ECM interactions, from the molecular to the tissue level, with a particular focus on cell migration. We then explore how cancer cell invasion and metastasis are deeply rooted in altered regulation of this vital interaction.
- Boolean modeling in systems biology: an overview of methodology and applications
Rui-Sheng Wang et al 2012 Phys. Biol. 9 055001
View article, Boolean modeling in systems biology: an overview of methodology and applicationsPDF, Boolean modeling in systems biology: an overview of methodology and applicationsMathematical modeling of biological processes provides deep insights into complex cellular systems. While quantitative and continuous models such as differential equations have been widely used, their use is obstructed in systems wherein the knowledge of mechanistic details and kinetic parameters is scarce. On the other hand, a wealth of molecular level qualitative data on individual components and interactions can be obtained from the experimental literature and high-throughput technologies, making qualitative approaches such as Boolean network modeling extremely useful. In this paper, we build on our research to provide a methodology overview of Boolean modeling in systems biology, including Boolean dynamic modeling of cellular networks, attractor analysis of Boolean dynamic models, as well as inferring biological regulatory mechanisms from high-throughput data using Boolean models. We finally demonstrate how Boolean models can be applied to perform the structural analysis of cellular networks. This overview aims to acquaint life science researchers with the basic steps of Boolean modeling and its applications in several areas of systems biology.
- The middle lamella—more than a glue
M S Zamil and A Geitmann 2017 Phys. Biol. 14 015004
In plant tissues, cells are glued to each other by a pectic polysaccharide rich material known as middle lamella (ML). Along with many biological functions, the ML plays a crucial role in maintaining the structural integrity of plant tissues and organs, as it prevents the cells from separating or sliding against each other. The macromolecular organization and the material properties of the ML are different from those of the adjacent primary cell walls that envelop all plant cells and provide them with a stiff casing. Due to its nanoscale dimensions and the extreme challenge to access the structure for material characterization, the ML is poorly characterized in terms of its distinct material properties. This review explores the ML beyond its functionality as a gluing agent. The putative molecular interactions of constituent macromolecules within the ML and at the interface between ML and primary cell wall are discussed. The correlation between the spatiotemporal distribution of pectic polysaccharides in the different portions of the ML and the subcellular distribution of mechanical stresses within the plant tissue are analyzed.
- The following article is Open accessGetting around the cell: physical transport in the intracellular world
Saurabh S Mogre et al 2020 Phys. Biol. 17 061003
View article, Getting around the cell: physical transport in the intracellular worldPDF, Getting around the cell: physical transport in the intracellular worldEukaryotic cells face the challenging task of transporting a variety of particles through the complex intracellular milieu in order to deliver, distribute, and mix the many components that support cell function. In this review, we explore the biological objectives and physical mechanisms of intracellular transport. Our focus is on cytoplasmic and intra-organelle transport at the whole-cell scale. We outline several key biological functions that depend on physically transporting components across the cell, including the delivery of secreted proteins, support of cell growth and repair, propagation of intracellular signals, establishment of organelle contacts, and spatial organization of metabolic gradients. We then review the three primary physical modes of transport in eukaryotic cells: diffusive motion, motor-driven transport, and advection by cytoplasmic flow. For each mechanism, we identify the main factors that determine speed and directionality. We also highlight the efficiency of each transport mode in fulfilling various key objectives of transport, such as particle mixing, directed delivery, and rapid target search. Taken together, the interplay of diffusion, molecular motors, and flows supports the intracellular transport needs that underlie a broad variety of biological phenomena.
- The following article is Open accessThe 2019 mathematical oncology roadmap
Russell C Rockne et al 2019 Phys. Biol. 16 041005
Whether the nom de guerre is Mathematical Oncology, Computational or Systems Biology, Theoretical Biology, Evolutionary Oncology, Bioinformatics, or simply Basic Science, there is no denying that mathematics continues to play an increasingly prominent role in cancer research. Mathematical Oncology—defined here simply as the use of mathematics in cancer research—complements and overlaps with a number of other fields that rely on mathematics as a core methodology. As a result, Mathematical Oncology has a broad scope, ranging from theoretical studies to clinical trials designed with mathematical models. This Roadmap differentiates Mathematical Oncology from related fields and demonstrates specific areas of focus within this unique field of research. The dominant theme of this Roadmap is the personalization of medicine through mathematics, modelling, and simulation. This is achieved through the use of patient-specific clinical data to: develop individualized screening strategies to detect cancer earlier; make predictions of response to therapy; design adaptive, patient-specific treatment plans to overcome therapy resistance; and establish domain-specific standards to share model predictions and to make models and simulations reproducible. The cover art for this Roadmap was chosen as an apt metaphor for the beautiful, strange, and evolving relationship between mathematics and cancer.
- The following article is Open accessRoadmap on emerging concepts in the physical biology of bacterial biofilms: from surface sensing to community formation
Gerard C L Wong et al 2021 Phys. Biol. 18 051501
View article, Roadmap on emerging concepts in the physical biology of bacterial biofilms: from surface sensing to community formationPDF, Roadmap on emerging concepts in the physical biology of bacterial biofilms: from surface sensing to community formationBacterial biofilms are communities of bacteria that exist as aggregates that can adhere to surfaces or be free-standing. This complex, social mode of cellular organization is fundamental to the physiology of microbes and often exhibits surprising behavior. Bacterial biofilms are more than the sum of their parts: single-cell behavior has a complex relation to collective community behavior, in a manner perhaps cognate to the complex relation between atomic physics and condensed matter physics. Biofilm microbiology is a relatively young field by biology standards, but it has already attracted intense attention from physicists. Sometimes, this attention takes the form of seeing biofilms as inspiration for new physics. In this roadmap, we highlight the work of those who have taken the opposite strategy: we highlight the work of physicists and physical scientists who use physics to engage fundamental concepts in bacterial biofilm microbiology, including adhesion, sensing, motility, signaling, memory, energy flow, community formation and cooperativity. These contributions are juxtaposed with microbiologists who have made recent important discoveries on bacterial biofilms using state-of-the-art physical methods. The contributions to this roadmap exemplify how well physics and biology can be combined to achieve a new synthesis, rather than just a division of labor.
- Stochastic modelling of reaction–diffusion processes: algorithms for bimolecular reactions
Radek Erban and S Jonathan Chapman 2009 Phys. Biol. 6 046001
View article, Stochastic modelling of reaction–diffusion processes: algorithms for bimolecular reactionsPDF, Stochastic modelling of reaction–diffusion processes: algorithms for bimolecular reactionsSeveral stochastic simulation algorithms (SSAs) have recently been proposed for modelling reaction–diffusion processes in cellular and molecular biology. In this paper, two commonly used SSAs are studied. The first SSA is an on-lattice model described by the reaction–diffusion master equation. The second SSA is an off-lattice model based on the simulation of Brownian motion of individual molecules and their reactive collisions. In both cases, it is shown that the commonly used implementation of bimolecular reactions (i.e. the reactions of the form A + B → C or A + A → C) might lead to incorrect results. Improvements of both SSAs are suggested which overcome the difficulties highlighted. In particular, a formula is presented for the smallest possible compartment size (lattice spacing) which can be correctly implemented in the first model. This implementation uses a new formula for the rate of bimolecular reactions per compartment (lattice site).
- A physics perspective on collective animal behavior
Nicholas T Ouellette 2022 Phys. Biol. 19 021004
View article, A physics perspective on collective animal behaviorPDF, A physics perspective on collective animal behaviorThe dynamic patterns and coordinated motion displayed by groups of social animals are a beautiful example of self-organization in natural far-from-equilibrium systems. Recent advances in active-matter physics have enticed physicists to begin to consider how their results can be extended from microscale physical or biological systems to groups of real, macroscopic animals. At the same time, advances in measurement technology have led to the increasing availability of high-quality empirical data for the behavior of animal groups both in the laboratory and in the wild. In this review, I survey this available data and the ways that it has been analyzed. I then describe how physicists have approached synthesizing, modeling, and interpreting this information, both at the level of individual animals and at the group scale. In particular, I focus on the kinds of analogies that physicists have made between animal groups and more traditional areas of physics.
- The following article is Open accessApoptosis: its origin, history, maintenance and the medical implications for cancer and aging
Szymon Kaczanowski 2016 Phys. Biol. 13 031001
View article, Apoptosis: its origin, history, maintenance and the medical implications for cancer and agingPDF, Apoptosis: its origin, history, maintenance and the medical implications for cancer and agingProgrammed cell death is a basic cellular mechanism. Apoptotic-like programmed cell death (called apoptosis in animals) occurs in both unicellular and multicellular eukaryotes, and some apoptotic mechanisms are observed in bacteria. Endosymbiosis between mitochondria and eukaryotic cells took place early in the eukaryotic evolution, and some of the apoptotic-like mechanisms of mitochondria that were retained after this event now serve as parts of the eukaryotic apoptotic machinery. Apoptotic mechanisms have several functions in unicellular organisms: they include kin-selected altruistic suicide that controls population size, sharing common goods, and responding to viral infection. Apoptotic factors also have non-apoptotic functions. Apoptosis is involved in the cellular aging of eukaryotes, including humans. In addition, apoptosis is a key part of the innate tumor-suppression mechanism. Several anticancer drugs induce apoptosis, because apoptotic mechanisms are inactivated during oncogenesis. Because of the ancient history of apoptosis, I hypothesize that there is a deep relationship between mitochondrial metabolism, its role in aerobic versus anaerobic respiration, and the connection between apoptosis and cancer. Whereas normal cells rely primarily on oxidative mitochondrial respiration, most cancer cells use anaerobic metabolism. According to the Warburg hypothesis, the remodeling of the metabolism is one of the processes that leads to cancer. Recent studies indicate that anaerobic, non-mitochondrial respiration is particularly active in embryonic cells, stem cells, and aggressive stem-like cancer cells. Mitochondrial respiration is particularly active during the pathological aging of human cells in neurodegenerative diseases. According to the reversed Warburg hypothesis formulated by Demetrius, pathological aging is induced by mitochondrial respiration. Here, I advance the hypothesis that the stimulation of mitochondrial metabolism leads to pathological aging.
Journal resources
Journal information
- 2004-present
Physical Biology
doi: 10.1088/issn.1478-3975
Online ISSN: 1478-3975
Print ISSN: 1478-3967