The team assembled measurements from twenty-five eukaryotic species spanning yeasts, animals and plants, drawing on published images and new morphometric analyses of spindle length, spindle width and the dimensions of the metaphase plate, the equatorial plane where chromosomes line up before segregation. When they plotted metaphase plate width against genome size on logarithmic axes, the data collapsed onto a straight line, revealing a power law with an exponent of approximately one third. The correlation was remarkably tight, with an R-squared value of 0.94. In practical terms, this means that when the amount of DNA in a genome increases a thousand-fold, the width of the structure that accommodates it grows only about ten-fold. Sublinear scaling of this kind is a hallmark of geometric constraints, and it hinted at an underlying physical mechanism rather than a purely biochemical one.

The clue to that mechanism came from the geometry of the chromosomes themselves. Previous work had shown that condensed mitotic chromosomes maintain a roughly uniform chromatin density of around ninety megabase pairs per cubic micrometre across species. The new analysis extended this observation to the level of the entire metaphase plate: plate volume scaled almost linearly with genome size, with an exponent of 0.96, and the effective density of the plate was roughly constant across organisms. The plate also maintained a conserved shape, with a width-to-thickness aspect ratio of about 1.9. Crucially, chromosome number played almost no role in the scaling. Species with similar chromosome counts but different genome sizes had very different plate widths, while species with similar genome sizes but chromosome numbers ranging from six to forty-six had nearly identical plates. It is the total volume of chromatin, not how it is parcelled into individual chromosomes, that dictates spindle geometry.

To explain the one-third exponent, the researchers built a physical model of the spindle in which each chromosome is represented as a compressible elastic sphere, attached to microtubule bundles that extend between the two spindle poles. The microtubules, through their bending stiffness, push the chromosomes inward toward the spindle axis, while the chromosomes, packed tightly together in the metaphase plate, push back against one another through steric repulsion. The equilibrium between microtubule bending forces and interchromosome pushing forces determines the positions of the chromosomes and hence the width of the plate and the spindle. Because chromosome volume is proportional to genome size, the characteristic length of a chromosome grows with the cube root of the genome, and the model naturally predicts a power-law exponent close to the observed 0.33. When the model was calibrated on human spindle parameters and extrapolated across four orders of magnitude of genome size, it predicted an exponent of 0.37, in close agreement with the comparative data.

The model made a second, counterintuitive prediction: if the total volume of chromatin is held constant while the number of chromosomes is varied, the metaphase plate width should remain roughly constant. This was confirmed by comparing species with similar genome sizes but very different chromosome numbers. Conversely, when chromosome number increases at constant individual chromosome volume, meaning more total chromatin, the model predicted a power-law widening with an exponent of 0.43, and experiments matched this behaviour. The estimated interchromosome pushing forces were in the range of hundreds of piconewtons, comparable to the pulling forces that molecular motors and microtubule depolymerization exert at kinetochores, the protein structures that link chromosomes to spindle fibres.

Experimental tests followed four complementary strategies. First, the team generated polyploid human cells, including hypotetraploid and hypooctaploid derivatives of the non-transformed RPE1 line and the tumour-derived HCT116 line, using carefully designed protocols that prevented centriole overduplication so that cells divided with bipolar spindles. Metaphase plate width increased robustly with ploidy in every case, and cell-by-cell analysis using nuclear area as a proxy for ploidy yielded a power-law exponent of 0.29, matching the cross-species value. Second, the researchers exploited natural ploidy variation in patient-derived colorectal cancer organoids and found the same scaling relationship. Third, by acutely reactivating the motor protein CENP-E in cells whose chromosomes had been stranded at the spindle poles, they watched in real time as chromosomes entered the plate, and both plate width and chromatin density rose in step with the increasing chromosome number. Fourth, forcing cells into mitosis with an unreplicated genome, so that most chromatin remained uncondensed in the cytoplasm, produced spindles that were thirty-one percent thinner without any change in cell size.

Perhaps the most dramatic test involved physically squeezing the spindles. The team compressed metaphase cells with a soft agarose gel, reducing spindle height by roughly forty-four percent within a minute. If chromosomes truly push against one another, compressing the cell should squeeze the plate sideways, and that is exactly what happened: the metaphase plate widened by about thirty percent and thickened by about fifty percent, while spindle length stayed unchanged. The angle between the outermost microtubule bundles at the poles increased, consistent with the model’s prediction that microtubules pivot around freely jointed pole attachments. When the compression was released, the spindle partially recovered its original shape. Spindles with unreplicated genomes widened less under compression, as the model predicted for softer, smaller chromatin masses. Compressed cells took longer to complete metaphase, suggesting that excessive interchromosome pushing forces impede the machinery of division.

The study also clarified that spindle length and spindle width are governed by independent mechanisms. Acute depolymerization of microtubules with nocodazole collapsed spindle length by sixty-five percent within minutes but left spindle width and plate width untouched, showing that width is maintained by the mechanical properties of chromatin rather than by microtubule-generated forces. Osmotic shocks, which alter cytoplasmic density, compressed or relaxed the plate and spindle in ways that decoupled length from width. Perturbing dozens of microtubule-associated proteins changed spindle length by up to one hundred percent while shifting width by only about twenty percent. In meiosis, the picture held as well: metaphase I plates, carrying twice the chromatin of metaphase II, were twenty-three percent wider in human oocytes and thirty-three percent wider in mouse oocytes, with spindle length differing by no more than seven percent.

The implications reach well beyond basic cell biology. The authors propose that chromosome crowding explains why animal cells round up before dividing, creating space for the spindle, and why eukaryotes with larger genomes evolved open mitosis, in which the nuclear envelope disassembles. It may also explain why polyploid cells, common in the human liver and frequent in tumours, can divide at all: the spindle simply widens to accommodate the extra chromatin, and adapted polyploid cells enlarge their spindles further with a distinct transcriptional programme. In plants, whose spindles have unfocused poles and experience weaker compression forces, the mechanism may have facilitated the repeated whole-genome duplications that drive speciation. A single physical principle, chromosomes fighting for space in the metaphase plate, appears to underpin how life divides genomes large and small.

Subject of Research: Power-law scaling of mitotic spindle dimensions with genome size across eukaryotes, driven by interchromosome pushing forces from chromosome crowding at the metaphase plate

Article Title: Power-law scaling of mitotic spindles with genome sizes across eukaryotes is driven by chromosome crowding

Article References: Gudlin, L., Vukušić, K., Novak, M., Trupinić, M., Ljulj, M., Dundović, I., Petelinec, A., Petrušić, L., Hertel, A., van Ravesteyn, T., Trakala, M., Kops, G. J. P. L., Storchová, Z., Tambača, J., Pavin, N., & Tolić, I. M. (2026). Power-law scaling of mitotic spindles with genome sizes across eukaryotes is driven by chromosome crowding. Nature Cell Biology. https://doi.org/10.1038/s41556-026-02005-8

Image Credits: AI Generated

DOI: 10.1038/s41556-026-02005-8

Keywords: mitotic spindle, chromosome crowding, genome size, power-law scaling, metaphase plate, microtubules, polyploidy, cell division, biophysics, eukaryotes, meiosis, chromatin density

Snow algae are found on every continent, predominantly in polar and alpine settings. They are keystone primary producers, acting as terrestrial carbon sinks, facilitating nutrient cycling, shaping microbial communities and providing nutrition for higher organisms. But they also have a darker climatic significance: by darkening snow surfaces, they reduce albedo, the fraction of incoming solar radiation that snow reflects, and thereby accelerate melting. Snow algae have been shown to reduce snow albedo by up to 44 percent. In one Antarctic Peninsula study, albedo fell from 0.85 at algae-free control sites to 0.44 over green-dominated blooms and 0.65 over red ones, corresponding to roughly 40 percent and 20 percent reductions respectively. Despite this ecological weight, the mechanisms governing how snow algae migrate within snow remain poorly understood, which is precisely the gap the review sets out to fill.

The authors frame snow algae as biologically active particles within the framework of active matter physics, a class of non-equilibrium soft matter whose motion cannot be explained by equilibrium physics alone. Unlike passive particles, microalgae harvest energy from their environment and convert it into directed motion. Their propulsion comes from flagellar beating, a process in which adenosine triphosphate is converted to adenosine diphosphate, releasing energy that powers microtubule sliding within the flagella. The motile species examined in the review are typically biflagellated, and the symmetry and phase relationships of their two flagella produce distinctive swimming gaits, including the helical swimming pattern well characterised in the model freshwater alga Chlamydomonas reinhardtii, which the authors use as a proxy where snow algae data are lacking.

Scale matters enormously in this world. The review walks through the dimensionless Reynolds number, the ratio of inertial to viscous forces, to illustrate just how alien the algal fluid environment is. For Chlamydomonas reinhardtii, with a swimming speed of roughly 130 micrometres per second and a cell length of about 10 micrometres, the Reynolds number is around 1.3 times ten to the minus three. For a human swimmer it is about 1.7 times ten to the sixth, roughly a billion times larger. At such low Reynolds numbers, inertia is negligible and reciprocal strokes produce no net motion, which is why microalgae have evolved helical flagella and whip-like techniques to navigate. Any understanding of how algae move through snow must therefore begin with the physics of viscous-dominated swimming.

The snowpack itself is a dynamic, porous and evolving medium. Snow crystals, typically between half a millimetre and three millimetres across, are up to three orders of magnitude larger than the algae, which measure roughly 5 to 40 micrometres. Within the pack, crystals continuously metamorphose under temperature and pressure gradients, forming rounded grains in the upper layers and large depth hoar crystals at the base. In melting snow, where algae flourish, water films bind crystals into clusters. At the macroscopic scale, the algae follow a seasonal cycle: they overwinter as dormant cysts, germinate into green motile flagellated cells with the spring melt, migrate upward toward the surface in response to meltwater, light and released nutrients, and then transform back into non-motile, pigmented cysts. Field experiments on an Alaskan ice field suggest that at the peak of the growing season, actively resurfacing cells account for about 65 percent of surface algal abundance, with passive dispersal by wind, water and birds making up the remaining 35 percent.

At the microscopic scale, the story becomes subtler. Snow algae were long thought to inhabit the quasi-liquid layer, a thin film of liquid water that coats snow crystals even at sub-zero temperatures. But that layer is astonishingly thin, ranging from a few molecular layers, roughly 0.37 nanometres each, up to about 10 nanometres as temperature rises. Motile snow algae cells are six to twenty micrometres across, several orders of magnitude too large to swim within it. In non-melting snow, moreover, about 80 percent of the limited liquid water is held in menisci at crystal contact points. This size disparity suggests that active swimming within the quasi-liquid layer is unlikely, and helps explain why algal migration and bloom development peak during snowmelt, when larger interconnected water channels form. X-ray tomography of the red snow alga Sanguina nivaloides has shown that its dormant cysts occur only in the liquid water fraction of the snowpack, never inside ice grain cores.

Fluid flow within the pack adds another layer of physics. Preferential flow paths carry meltwater at speeds between 12 and 30 millimetres per second, far exceeding the reported mean swimming speed of the snow alga Chlamydomonas nivalis, a mere 0.061 millimetres per second. Whether algae can swim against such flows depends on the viscous diffusion timescale, which scales with the square of channel width divided by kinematic viscosity. In narrow channels or saturated capillary zones, where flow is effectively stagnant, algae can move independently of the bulk water. In wider channels they are likely transported passively by advection. The review also highlights interfacial pre-melting and thermal regelation as possible migration aids: when an algal cell is embedded in ice near its melting point, surface forces induce a thin melted film, and a temperature gradient can drive the cell toward warmer regions through cycles of melting and refreezing. Some Chlamydomonas species even produce ice-binding proteins that hinder ice crystal growth, and exopolymeric substances and antifreeze glycoproteins may further enhance survival and motility in icy conditions.

Much of the review is devoted to tactic behaviour, the biased swimming of cells toward or away from stimuli. Phototaxis is the best documented. Motile snow algae swim toward light at low to moderate intensities but switch to negative phototaxis above a critical threshold; in a Japanese alpine snowpack, motile cells ascended nearly to the surface during low-light hours and descended 10 to 20 centimetres when solar radiation peaked at up to 755 watts per square metre. Cell density at the surface was negatively correlated with solar radiation and air temperature, and because solute gradients showed no day-night variation, light rather than nutrients drove the migration. Intriguingly, some snow algal species lack eyespots yet still exhibit phototaxis, while close relatives with eyespots do not, raising questions about how light sensing works in snow, where reflections off countless crystals could produce confusing signals. Ultraviolet-B radiation, meanwhile, appears to act mainly as a physiological stressor that suppresses motility rather than as a directional cue.

Chemotaxis, gravitaxis, gyrotaxis and thermotaxis complete the picture, though each is far less understood in snow algae specifically. Snowpacks are oligotrophic, and laboratory experiments suggest phosphorus, rather than nitrogen, is the limiting nutrient for the snow alga Chloromonas typhlos, making phosphorus gradients a plausible but untested driver of chemotactic movement. Gravitaxis, the orientation of cells relative to gravity, remains debated between passive mechanisms such as bottom-heavy mass distribution and differential sedimentation, and active physiological sensing; mutant studies in Chlamydomonas point to active, membrane-excitability-dependent signalling. Gyrotaxis, the combination of gravitational and viscous torques in flowing fluid, has been shown experimentally to generate bioconvective patterns in snow algal suspensions, and may focus swimming algae into downward meltwater flows, accelerating their transport to the base of the pack. Thermotaxis has never been demonstrated in snow algae, though psychrophilic species show optimal swimming speeds below 10 degrees Celsius, in sharp contrast to mesophilic species that peak above 20 degrees.

The review closes with a call to arms. The seasonal cyst-to-flagellate cycle is broadly accepted, but the quantitative biophysics of how algae interact with quasi-liquid layers, navigate meltwater channels and respond to evolving snowpack structure remains undocumented. Filling these gaps, the authors argue, would improve predictions of snow algal blooms and their climatic consequences, refine hydrological and cryospheric models, advance our understanding of microswimmer behaviour in active matter physics, and even inform emerging biotechnologies, from low-temperature algal cultivation for astaxanthin production to medical microrobotics inspired by algal motility. The pink patches staining the world’s snowfields, it turns out, are not just a curiosity but a living laboratory for physics, ecology and climate science all at once.

Subject of Research: Biophysical mechanisms of snow algae motility and migration within snowpacks

Article Title: Reviews and syntheses: Snow algae on the move – biased motility and snowpack interaction from a biophysics perspective

Article References: de Vries, C. S., Sandells, M. J., Davey, M. P., Caldwell, G. S., & Croze, O. A. (2026). Reviews and syntheses: Snow algae on the move – biased motility and snowpack interaction from a biophysics perspective. Biogeosciences, 23(19), 6835-6855. https://doi.org/10.5194/bg-23-6835-2026

Image Credits: AI Generated

DOI: 10.5194/bg-23-6835-2026

Keywords: snow algae, biophysics, active matter, phototaxis, chemotaxis, gravitaxis, gyrotaxis, snowpack, albedo, cryosphere, microswimmers, flagella

Alpha-hemolysin is an exotoxin secreted by the bacterium Staphylococcus aureus. In its active form, the protein is built from 293 water-soluble amino acids that assemble into a heptameric pore, a seven-part barrel that punches through cell membranes. That structure, first resolved in crystallographic detail in the 1990s, has made alpha-hemolysin the workhorse of stochastic sensing: the first and still most widely used biological nanopore for detecting individual molecules. When a single pore is embedded in an artificial membrane bathed in electrolyte and a voltage is applied, a steady ionic current flows through the opening. When an analyte molecule wanders into the pore, it partially obstructs that current, producing a characteristic downward blip. Each blip corresponds to one molecule, and the pattern of blips over time carries information about the analyte’s identity and concentration.

In the new experiments, the team used monodisperse polyethylene glycol of molecular weight 1294, abbreviated PEG 1294, as the analyte. The experimental platform was a solvent-free planar lipid bilayer assembled by the classic Montal and Mueller technique: two monomolecular lipid films were apposed across a hole roughly 100 micrometers in diameter in a Teflon partition, forming a barrier that separated two identical compartments of a Teflon chamber. The synthetic lipid 1,2-diphytanoyl-sn-glycero-3-phosphocholine was used at 2 percent by weight in hexane, and the hole was pretreated with a dilute hexadecane solution to promote stable bilayer formation. Both compartments held a concentrated electrolyte of 4 molar potassium chloride buffered with 5 millimolar Tris-citric acid at pH 7.5. Alpha-hemolysin was added to one side, the cis side, at a concentration tuned so that exactly one pore inserted into the membrane.

The researchers then added PEG 1294 to the opposite, trans side at two concentrations, 400 and 1000 micromolar, and applied voltages ranging from +20 to +100 millivolts in 20 millivolt steps. Ionic currents were recorded with an Axopatch 200B amplifier in voltage clamp mode, using silver/silver chloride electrodes connected through agar salt bridges. The signals were low-pass filtered at 15 kilohertz and digitized at a sampling rate of 250 kilohertz, all at a controlled temperature of 25 degrees Celsius. Under these conditions, the current trace showed the textbook signature of stochastic sensing: stepwise transitions between a fully open level and a partially blocked level, each step corresponding to the entry or exit of a single PEG molecule from the pore lumen.

The novelty of the study lay not in the electrophysiology but in the analysis. Rather than focusing on conventional metrics such as event duration or blocking depth, the team turned to Lempel-Ziv complexity, a measure introduced in 1976 by Abraham Lempel and Jacob Ziv to quantify the randomness of finite sequences. The method works by converting a time series into a binary string: each data point is compared with the average of the entire series, receiving a 1 if it exceeds the average and a 0 if it falls below. The resulting string of ones and zeros is then scanned from left to right, and a counter increments every time a new, previously unseen substring appears. Finally, the counter is normalized by a theoretical upper bound, n divided by the base-2 logarithm of n, yielding a complexity value that ranges from 0 to 1 and is independent of sequence length.

The interpretation of this number is intuitive. A value close to 1 indicates a highly random, unpredictable signal with little internal self-similarity, while a value close to 0 indicates a repetitive, ordered series. Lempel-Ziv complexity has previously found applications in biomedical signal analysis, including studies of electroencephalogram background activity in Alzheimer’s disease patients and the detection of ventricular tachycardia and fibrillation in cardiac recordings. Applying it to nanopore data, however, allowed the researchers to ask a question that conventional event statistics cannot easily answer: how complex, in an information-theoretic sense, is the pattern of molecular blocking events?

The answer depended strongly on how much analyte was present. At the lower PEG concentration of 400 micromolar, complexity values were consistently lower than at 1000 micromolar, across every voltage tested. The full range of measured values stretched from a minimum of 0.45, recorded at 400 micromolar and +40 millivolts, to a maximum of 0.97, recorded at 1000 micromolar and +80 millivolts. The physical explanation is straightforward: higher analyte concentrations produce more frequent blocking events, filling the time series with rapid alternations between open and blocked states and pushing the complexity measure toward its upper limit. At lower concentrations, longer stretches of open-pore current dominate, and the signal becomes more ordered and less random.

To probe whether the apparent order at low concentration reflected genuine structure or simply sparse sampling, the researchers performed a clever control. They segmented the original time series recorded at 400 micromolar, shuffled the segments into a random order, and recalculated the complexity of the resulting randomized series. For every applied potential, the shuffled data yielded higher Lempel-Ziv values than the original recordings. This result is diagnostic: if the original series had already been maximally random, shuffling it would have changed nothing. The fact that randomization increased complexity means the unshuffled sequences contained residual structure, and that the biosensor’s output at low analyte concentration falls short of full stochastic behavior.

The team also compared series built exclusively from blocked periods with series built exclusively from unblocked periods, at both concentrations and all voltages. Statistical analysis using Student’s t-test, with a significance threshold of p less than 0.05, found no meaningful differences between the complexity of the blocked-only and unblocked-only series, nor between those segmented series and the original combined recordings. In other words, the complexity of the signal does not reside preferentially in either the moments when PEG occupies the pore or the intervals between occupations; the stochastic character is distributed across the entire record.

The broader implications reach into a long-standing debate in biology about the role of randomness. Molecular biology has traditionally leaned on deterministic principles, yet stochasticity is now recognized as a genuine feature of living systems rather than mere noise. Ion channel kinetics are widely treated as stochastic events, and some theorists argue that intrinsic randomness in the nervous system may even enable flexible decision-making. As the authors note, biological studies often lack the tools to distinguish chaotic, noisy, deterministic, and probabilistic behavior. Lempel-Ziv complexity offers one such tool. Their conclusion is nuanced: the alpha-hemolysin biosensor behaves in a purely stochastic fashion only at higher analyte concentrations, while at lower concentrations its stochasticity diminishes, though it can be mathematically restored by randomizing the event sequence. For engineers designing nanopore sensors, that finding matters, because the reliability of single-molecule detection depends on understanding when the digital current signature is truly random and when it carries hidden structure that smarter algorithms might exploit.

Subject of Research: Stochastic analysis of alpha-hemolysin nanopore ionic current blocking events using Lempel-Ziv complexity

Article Title: Analyzing alpha-hemolysin nanopore behavior using Lempel-Ziv complexity

Article References: Neves, G. F., Machado, D. C., Consoni, L. H. A., Costa, E. V. L., Carneiro, C. M. M., Rodrigues, C. G., & Nogueira, R. A. (2026). Analyzing alpha-hemolysin nanopore behavior using Lempel-Ziv complexity. Discover Chemistry, 3(1), Article 571. https://doi.org/10.1007/s44371-026-01022-8

Image Credits: AI Generated

DOI: 10.1007/s44371-026-01022-8

Keywords: alpha-hemolysin, nanopore, Lempel-Ziv complexity, stochastic sensing, polyethylene glycol, ion channel, planar lipid bilayer, biosensor, information theory, single-molecule detection, biophysics, stochasticity

The award citation highlights Tanner’s discoveries elucidating the biophysical determinants of organ-specific metastasis in a living animal. That phrasing captures a question that has long frustrated cancer researchers: why do tumor cells shed from a primary growth settle and flourish in some organs while failing in others? The prevailing view in oncology has shifted over recent decades from a purely biochemical picture, in which chemical signals and genetic mutations govern the spread of cancer, toward a more integrated framework in which physical forces, tissue architecture, and mechanical properties of the cellular microenvironment play decisive roles. Tanner’s work sits squarely at the heart of this shift, and the Biophysical Society’s decision to honor it underscores how central physics has become to modern cancer research.

Metastasis remains the deadliest phase of cancer, responsible for the majority of cancer-related deaths worldwide. For a tumor cell to seed a new colony in a distant organ, it must complete an extraordinary sequence of steps: detach from the primary tumor, invade surrounding tissue, enter the circulation or lymphatic system, survive the punishing shear stresses of blood flow, arrest in a small vessel of a distant organ, exit into the new tissue, and finally adapt to an unfamiliar microenvironment well enough to proliferate. Each of these steps imposes distinct physical demands on the cell, from squeezing through narrow gaps to withstanding fluid forces to remodeling the stiffness of the tissue around it. Understanding which of these physical hurdles determine success or failure is essential for predicting and ultimately preventing deadly spread.

Organ-specific metastasis adds another layer of complexity. Clinicians have observed for more than a century that different cancers display characteristic patterns of spread: some tumors preferentially colonize the liver, others the lung, bone, or brain. Stephen Paget’s celebrated seed and soil hypothesis, proposed in 1889, framed the problem in agricultural terms, suggesting that tumor cells, like seeds, can only grow in congenial soil. Modern research has enriched that metaphor with molecular detail, identifying chemokine signaling, extracellular matrix composition, and organ-specific stromal cells as contributors to the soil’s fertility. What has been harder to capture is the physical dimension of the soil: how the stiffness, topology, fluid dynamics, and mechanical stresses of a given organ filter and shape arriving tumor cells. Studying these factors requires tools that can probe living tissue at multiple scales simultaneously, precisely the kind of methodological territory in which biophysics excels.

Tanner’s recognition by the Biophysical Society reflects the value of approaching these questions with the quantitative rigor of a physicist. Investigating biophysical determinants in a living animal, rather than in simplified cell culture dishes, is a demanding methodological choice. Cell culture allows exquisite control and measurement, but it strips away the fluid shear of the bloodstream, the three-dimensional architecture of organs, the immune system, and the mechanical heterogeneity of real tissue. Animal models preserve that complexity but make precise physical measurement far more difficult. Bridging the two requires innovative imaging strategies, engineered model systems that recapitulate key features of organs, and analytical frameworks capable of linking single-cell behavior to tissue-level outcomes. Researchers who accomplish this bridging are rare, and the award’s emphasis on work performed in a living animal signals how highly the community values that integration.

The significance of this line of research extends well beyond fundamental understanding. If the physical properties of an organ microenvironment help determine whether disseminated tumor cells take hold, then those properties become potential therapeutic targets. Approaches that modify tissue stiffness, interfere with mechanotransduction signaling pathways by which cells sense and respond to mechanical cues, or alter the physical interactions between tumor cells and their surroundings could complement existing treatments aimed at genetic and biochemical vulnerabilities. Moreover, physical measurements of the microenvironment might one day serve as predictive biomarkers, helping clinicians assess a patient’s risk of metastasis to particular organs and tailor surveillance and intervention accordingly. Work of the kind Tanner has pursued lays the groundwork for such translational possibilities by identifying which physical variables matter most.

Bárány Award recipients are chosen for outstanding contributions to biophysics at a career stage before senior rank, making the prize a marker of exceptional early trajectory. The award honors the legacies of Michael and Kate Bárány, whose own contributions to muscle biophysics exemplified the discipline’s tradition of explaining biological function through physical principles. In recognizing Tanner, the Society continues that tradition while also highlighting the expanding scope of biophysics itself. Once concentrated on problems such as protein structure, membrane dynamics, and muscle contraction, the field now encompasses the mechanics of cancer, the physics of morphogenesis, and the quantitative analysis of intact organisms. The Society, founded in 1958, describes its mission as leading a global community working at the interface of the physical and life sciences across all levels of complexity, and its roughly 6,000 members teach and conduct research in universities, laboratories, government agencies, and industry around the world.

The announcement also offered a vivid portrait of Tanner as a scientist. BPS President Karen Fleming of Johns Hopkins University described her as an innovative thinker and a fearless experimentalist, adding that Tanner has established herself as a world leader in the research community that investigates the impact of physical properties on complex biological processes within tissue and within intact organisms. The characterization is notable for its emphasis on fearlessness. Experiments that probe physical forces inside living animals demand technical ingenuity and a tolerance for systems that resist the tidy controls of the physics laboratory. The praise from the Society’s president suggests that Tanner’s willingness to tackle biology at its most complicated and least controllable has been central to her standing in the field.

The February 2027 meeting in Philadelphia will bring together thousands of biophysicists for a program spanning molecular, cellular, and organismal scales, and the award lecture that accompanies the Bárány honor will give Tanner a prominent platform to describe her findings to that audience. For the broader cancer research community, the recognition serves as a reminder that the physical sciences are no longer peripheral to oncology. The spread of cancer through the body is, at its core, a problem of cells navigating a physical world: deforming through confined spaces, sensing the rigidity of the ground beneath them, enduring the rush of blood, and remodeling the architecture of the tissues they invade. By illuminating the biophysical determinants of organ-specific metastasis in living animals, Tanner’s work addresses one of the most consequential questions in medicine with the tools of physics, and the 2027 Michael and Kate Bárány Award marks both her achievements and the growing conviction that understanding cancer requires understanding its physics.

Subject of Research: Biophysical mechanisms of organ-specific cancer metastasis recognized by the 2027 Michael and Kate Bárány Award

Article Title: Kandice Tanner to receive 2027 Michael and Kate Bárány Award

Article References: Kandice Tanner to receive 2027 Michael and Kate Bárány Award. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: Kandice Tanner, Biophysical Society, Bárány Award, metastasis, biophysics, National Cancer Institute, organ-specific metastasis, tumor microenvironment, mechanobiology, cancer research, living animal models, scientific award

The research, led by Alexandra Zidovska, an associate professor in NYU’s Department of Physics, addresses a gap that has persisted since the completion of the Human Genome Project. That monumental effort, launched in 1990 after decades of genetic breakthroughs, delivered a sequence of the human genome, but the physical rules governing how that genome is organized inside the cell nucleus remain an active and unsettled area of research. Among the unanswered questions is the role of gravity, a constant mechanical stress on everything that lives. To probe it, Zidovska and her colleagues reasoned, gravity must be removed as a factor, which is precisely what their custom-built laboratory apparatus was designed to do.

The stakes of the question are considerable. The human genome is a one-dimensional sequence encoded in roughly two meters of DNA molecules, packed with extraordinary efficiency into three dimensions inside a cell nucleus barely 10 micrometers across, about the width of a silk fiber. This compact hierarchical structure is directly linked to genomic function, and deviations from it can contribute to human diseases, including cancer, as well as developmental afflictions. But the physical principles that maintain this organization are not well understood, and it has remained unknown whether gravity contributes to preserving it, or whether its absence might induce genomic aberrations.

To find out, the NYU team designed and built a random positioning machine tailored for imaging the human genome in live cells. The device rotates dishes of living cells along two independent axes, following a three-dimensional rotational path that averages out the direction of the gravitational vector, producing a simulated microgravity, a condition of weightlessness created on Earth. The principle resembles that of the larger machines astronauts use in their training. A crucial preparatory step was the elimination of air bubbles from the cell cultures, since even small bubbles can interfere with delicate measurements during rotation.

Rotation alone, however, introduces a confounding problem. Turning a dish of cells through three dimensions inevitably stirs the surrounding fluid, generating flows that do not exist in genuine zero gravity outside Earth. Previous studies of simulated microgravity have often been obscured by such flows and by the cell aggregates they can induce. The researchers therefore developed novel 3D rotational algorithms that not only simulated microgravity but minimized fluid flow generation, and they created additional algorithms to investigate, separately, what flows themselves do to cells and their genomes. Together, these advances sharply reduced both fluid motions and cell clumping, allowing the team to isolate the effects of weightlessness from the artifacts of the simulation.

The experimental design then became a matter of careful comparison. The scientists exposed one set of cells to simulated microgravity with minimized flows, another to strong fluid flows, and a control group to neither condition, each exposure lasting 24 hours. They then deployed sophisticated imaging techniques, recording streams of images for detailed physical analysis. The measurements tracked changes in cell shape and volume, the shape and volume of the cell nucleus, the nuclear envelope, the genome itself, and the nucleolus, the largest liquid condensate within the nucleus. The team specifically examined changes in the genome’s organization and dynamics, as well as any DNA damage induced by the simulated conditions.

The results paint a picture of remarkable resilience, with telling exceptions. Cells exposed to flows became elongated in shape, but cells in simulated microgravity kept their form. The volume of the cell nucleus increased after exposure to weightlessness, indicating that on Earth gravity normally acts to diminish it. Despite that change in volume, the thickness and structure of the nuclear envelope, the membrane that encases the genome, remained unchanged, suggesting gravity has minimal influence on those architectural traits. Most strikingly, the genome itself maintained its physiological organization and motions throughout the day-long exposure to simulated microgravity, and the technique produced no detectable DNA damage, whereas exposure to flows did damage DNA. The nucleolus became smoother after exposure to either condition.

Our data show that the genome, its organization, and dynamics are incredibly robust and seem unaffected by gravity, or lack thereof, after 24 hours, Zidovska observed. In the same way, she noted, the results suggest that the physical organization of the human genome may undergo minimal changes in outer space during comparable timescales. The subtlety of the changes, however, comes with a caveat that the researchers themselves emphasize: small perturbations could amplify over time and eventually affect cell physiology, and longer exposures, particularly in the space environment where actual DNA damage occurs, could produce effects not seen in a single day of simulation.

The findings arrive at a moment of renewed ambition in human spaceflight, with plans for extended missions to the Moon and Mars raising urgent questions about how the body copes with weightlessness. How will the human genome be affected in outer space, Zidovska asked in describing the motivation for the work. By demonstrating that the genome’s organization and dynamics withstand a day of weightlessness on Earth, the study offers reassurance for short-duration exposures while framing the longer-term questions that future experiments, and future astronauts, will need to answer. It also provides the scientific community with a validated toolkit, combining imaging-compatible microgravity simulation with flow-suppressing algorithms, for disentangling gravitational effects from mechanical artifacts in cell biology.

Beyond its implications for space travel, the work speaks to a more fundamental mystery: the physics of the genome. Understanding which external forces shape, or fail to shape, the two meters of DNA coiled inside each of our cells touches on questions of disease, development, and the basic mechanics of life. The paper’s co-authors included Nikitas Kanellakopoulos, a doctoral student at NYU; undergraduates Manav Patel, Brandon Sato, and Melaina Lawrence; and Leif Ristroph, an associate professor at NYU’s Courant Institute School of Mathematics, Computing, and Data Science. The research was supported in part by grants from the National Science Foundation and the National Institutes of Health. For now, the message is one of quiet stability: the architecture of our genetic material, refined over billions of years, appears built to hold its shape whether it rests on Earth or floats among the stars, at least for a day.

Subject of Research: The effects of simulated microgravity and fluid flows on the organization, dynamics, and integrity of the human genome in living cells

Article Title: Scientists uncover gravity’s impact on the human genome

Article References: Scientists uncover gravity’s impact on the human genome. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: microgravity, human genome, cell nucleus, chromatin, DNA damage, nuclear envelope, nucleolus, random positioning machine, space biology, biophysics, Science Advances, New York University

Virus-like particles, often abbreviated as VLPs, are engineered or natural assemblies that mimic the architecture of true viruses but lack any genetic cargo and therefore cannot replicate or cause infection. They occupy a special place in modern biotechnology. Because they present the same repetitive protein lattice that the immune system encounters on a genuine viral surface, they are exceptionally potent platforms for vaccines, and several of the most successful immunizations in current use are built on VLP scaffolds. They are also widely used as delivery vehicles in gene therapy and as programmable nanocontainers in materials science. Understanding how these shells assemble is therefore not a purely academic question; it determines how efficiently such particles can be manufactured, how stable they are once formed, and how their surfaces can be modified for medical applications.

The central difficulty in studying self-assembly has always been one of scale and speed. A complete viral shell, or capsid, is typically built from sixty to several hundred copies of a single capsid protein, and the assembly reaction can pass through fleeting intermediates that exist for microseconds or less. Conventional structural biology techniques excel at determining the static structure of the finished particle. X-ray crystallography and cryo-electron microscopy can render the final capsid at near-atomic resolution, revealing the precise contacts that hold the shell together. But these methods average over enormous numbers of particles and freeze the ensemble at one point in its history. What they cannot easily show is the route by which the components travel from a disorganized solution of subunits to the finished, closed shell.

The new study addresses that gap by following the assembly reaction at the level of individual molecules. The researchers combined advanced single-particle imaging with time-resolved structural analysis, allowing them to observe the same population of virus-like particles as they progressed through distinct assembly stages. Rather than reconstructing a single averaged picture, the approach preserved the heterogeneity of the reaction, exposing the coexistence of half-formed intermediates, partially closed shells, and completed particles at any given moment. This heterogeneity is not noise; it is the physical signature of the assembly pathway itself, and capturing it is what makes a mechanistic reading of the process possible.

From these observations, a coherent picture of the assembly mechanism emerges. The capsid protein does not appear to be a passive brick that simply clicks into place wherever it collides with a growing shell. Instead, the experiments indicate that the subunit adopts distinct conformational states as it participates in the reaction, and that transitions between these states are coupled to the binding events that extend the shell. Early in assembly, small clusters of subunits nucleate the process, overcoming an energetic barrier that must be crossed before growth becomes favorable. Once a stable nucleus exists, the addition of further subunits proceeds rapidly, with each incoming protein locking into the lattice and, in doing so, preorganizing the binding surface for the next arrival.

This coupling between structure and binding is a hallmark of what biophysicists call a nucleation-and-growth mechanism, and it explains both the speed and the specificity of viral assembly. If subunits could bind indiscriminately, misassembled and malformed particles would dominate the reaction. Instead, the observed pathway funnels the components toward the correct geometry. The intermediate states captured in the study show that incorrect associations are either short-lived or structurally primed to convert into productive arrangements, so that the reaction is continually steered back onto the correct trajectory. The result is a yield of properly formed particles that would be the envy of any synthetic chemist, achieved without any external template or instruction beyond the information encoded in the protein sequence itself.

The energetic logic of the process is as important as its structural choreography. Capsid assembly must balance two opposing forces: the favorable contacts between subunits that drive the shell to grow, and the cost of conformational changes and electrostatic interactions that must be paid along the way. Too weak an attraction, and the reaction stalls before a nucleus forms. Too strong, and subunits aggregate irreversibly into useless clumps. The observations reported in Nature suggest that the virus-like particle sits at a finely tuned point between these extremes, with subunit binding affinities and conformational transitions calibrated so that assembly is both efficient and reversible enough to correct local errors. This principle of kinetically regulated, error-correcting self-assembly is one that researchers in nanotechnology have long tried to emulate in synthetic systems, and the direct structural evidence for how a biological assembly achieves it is likely to inform those efforts.

Beyond its fundamental interest, the study carries practical weight for biomedicine. Vaccine manufacturers producing VLP-based immunizations depend on assembly reactions that proceed with high yield and high uniformity, since misassembled particles can compromise both the potency and the safety profile of a product. A mechanistic understanding of the assembly pathway provides rational levers for optimization: adjusting solution conditions, protein sequence, or the presence of cofactors can shift the reaction toward faster nucleation, more stable intermediates, or improved final yield, depending on what the manufacturing process requires. Similarly, in gene therapy and drug delivery, where VLPs and related particles are engineered to encapsulate therapeutic cargo, the timing and coupling of assembly relative to cargo loading is a critical design parameter. The ability to see which intermediates form, and when, turns what has been a largely empirical optimization exercise into an evidence-guided engineering problem.

The work also illustrates a broader shift in structural biology. The field has traditionally been dominated by the determination of static, high-resolution structures of purified, stable states. Increasingly, however, the most pressing questions concern dynamics: how molecular machines move, how signaling proteins switch states, and how supramolecular assemblies build themselves. Methods that can resolve conformational heterogeneity and connect it to reaction progress are transforming those questions from matters of inference into matters of direct observation. In the case of virus-like particles, the application of such methods bridges a long-standing divide between virology, which has emphasized the architecture of mature viruses, and biophysics, which has modeled assembly largely through theory and simulation. Direct structural data on intermediates now provide the empirical anchor that theoretical models of self-assembly have needed.

The demonstration that a virus-like particle can be watched as it assembles, stage by stage, at molecular resolution closes one of the enduring gaps in the understanding of biological self-organization. The finished capsid, so elegant in its symmetry, is revealed not as a structure that simply exists but as the endpoint of a tightly controlled kinetic journey, one in which each subunit both responds to and shapes the assembly around it. For virologists, the findings deepen the picture of how the simplest biological entities achieve such remarkable reliability with so few components. For biotechnologists, they supply a mechanistic foundation for designing and producing the next generation of VLP-based vaccines, delivery vehicles, and nanomaterials. And for the wider study of molecular self-assembly, they offer a vivid reminder that the most sophisticated construction projects in the world are carried out, continuously and invisibly, by molecules following rules that science is only now learning to observe directly.

Subject of Research: Molecular-level observation of the self-assembly pathway of a virus-like particle

Article Title: Molecular-level observation of the self-assembly of a virus-like particle

Article References: Asor, R., Loewenthal, D., Melnyk, D., Tan, T. K., & Kukura, P. (2026). Molecular-level observation of the self-assembly of a virus-like particle. Nature, 657(8132), 653-660. https://doi.org/10.1038/s41586-026-10948-z

Image Credits: AI Generated

DOI: 10.1038/s41586-026-10948-z

Keywords: virus-like particle, self-assembly, capsid, virology, structural biology, biophysics, nucleation and growth, vaccines, nanotechnology, molecular imaging, Molecular-level, observation

The study, led by Jean-Baptiste Saulnier, Michèle Romanos, Jonathan Schrohe, Clémence Cuzin, Vincent Calvez and Tâm Mignot, and published in Nature Physics, combines high-resolution live microscopy with kinetic and agent-based modeling to dissect the mechanics of collective pattern formation. The work addresses one of the central questions in the physics of living systems: how do molecular-scale interactions between individual cells give rise to large-scale, organized patterns that span millimeters—an enormous distance by bacterial standards? Similar questions animate research on bird flocks, fish schools and human crowds, but bacteria offer a rare advantage: every single cell can be tracked, and the molecular machinery controlling its behavior can be genetically dissected.

Myxococcus xanthus is a predatory bacterium that hunts in packs. When nutrients are plentiful, cells glide across surfaces in loose, exploratory swarms, secreting extracellular polysaccharides that leave trail-like tracks in their wake. But when the swarm collides with a colony of prey organisms such as Escherichia coli, the hunters switch to a dramatic behavior called rippling. Cells organize into parallel crests that move back and forth, colliding periodically and then reversing, producing the visually striking wave patterns that gave the phenomenon its name. Earlier work established that rippling is a genuine predatory behavior associated with more efficient killing of prey, and that it emerges specifically in regions where prey density is high enough, yet the mechanism of the transition remained contested.

Previous theoretical explanations had proposed that rippling arises from cell–cell collisions: when two cells moving in opposite directions meet, they reverse, and repeated collisions somehow synchronize the population into traveling waves. Others emphasized intercellular chemical signaling through the C-signal pathway or the dynamics of the Frz chemosensory system, a bacterial relative of the chemotaxis circuits that guide E. coli toward nutrients. The new study cuts through this complexity. By carefully imaging single cells in both swarming and rippling fields, and by building mathematical models constrained by what the cells actually do, the researchers found that no exotic signaling mechanism is required to switch between the two patterns. Both emerge from the same two ingredients, operating under different local conditions.

The first ingredient is local alignment. M. xanthus cells do not simply move blindly; they tend to align their bodies with the orientation of neighboring cells and with the trails of extracellular matrix deposited on the surface. This alignment, reminiscent of the nematic ordering seen in liquid crystals, produces locally polarized domains in which large numbers of cells travel in the same direction. In swarming regions, cells follow self-deposited polysaccharide trails, forming a mesh-like network of intersecting streams. In rippling regions, where the prey-derived environment favors horizontal alignment, cells line up into ordered bands. The researchers quantified this alignment using nematic order parameters computed from single-cell trajectories, confirming that the degree and axis of alignment differ measurably between the two behavioral regimes.

The second ingredient is the reversal. M. xanthus cells periodically flip their polarity and swim in the opposite direction, a process controlled by the Frz system, which functions as a gated relaxation oscillator. Crucially, the team found that the timing of reversals is not fixed. Cells possess a tunable refractory period—the interval after a reversal during which another reversal cannot be triggered. This refractory period acts as a behavioral dial. When a cell becomes frustrated, pushing against its neighbors without making progress, the accumulation of mechanical congestion can trigger a reversal that lets it escape the traffic jam. The researchers directly measured this phenomenon, showing that the probability of reversal rises sharply with the degree of individual frustration, quantified as the mismatch between a cell’s target velocity and its actual displacement.

The beauty of the model lies in how the refractory period can be tuned to produce radically different collective outcomes. In dense prey regions, collisions between counter-propagating streams of aligned cells cause synchronized reversals: when two waves collide, most cells reverse at once, sending the waves back the way they came. The refractory period is short enough in this regime to permit the tight coupling that sustains periodic ripple waves. In swarming regions, by contrast, cells following trails rarely meet head-on opposition, and the reversal system instead serves to relieve congestion, keeping the mesh-like network flowing. One control parameter—the tunable delay in the reversal oscillator—thus supports two entirely different collective behaviors without any change in gene expression.

To test whether these ingredients were sufficient, the team constructed two complementary models. The first was a one-dimensional kinetic model in which cell populations moving right and left reverse upon collision, modified by an age-structured refractory period; it faithfully reproduced counter-propagating ripple waves. The second was a full two-dimensional agent-based simulation in which individual rods align with neighbors, deposit and follow extracellular matrix, and reverse when frustrated or after collision. Remarkably, this model not only reproduced swarming and rippling in isolation but also captured the coexistence of both patterns within a single colony. When the simulation was seeded with two fields of different local conditions, a sharp, stable boundary formed between the rippling domain and the swarming domain, and this interface persisted for the entire simulated period of hundreds of minutes.

Perhaps the most consequential claim of the study is that these dramatic pattern transitions can occur without changes in genetic regulation. The abstract environment—whether it favors trail-following or prey-aligned motion—effectively selects which of the two collective states the population adopts, and the same individual cells can migrate between the domains and switch behavior accordingly. Simulations in which a fraction of cells were rendered unable to reverse confirmed the central role of the reversal machinery in maintaining the boundary: non-reversing cells failed to respect the domain structure, while reversing cells sustained it. The authors propose that these stable spatial domains may in turn facilitate local differentiation, providing a physical scaffold for the multicellular development that M. xanthus famously undergoes when it builds fruiting bodies under starvation conditions.

Beyond its implications for microbiology, the work speaks to a broad physics audience interested in active matter and collective behavior. It demonstrates that a minimal set of rules—alignment plus congestion-responsive reversals governed by a tunable oscillator—can generate multiple stable macroscopic patterns and sharp transitions between them, a design principle that may recur in tissues, engineered microrobotic swarms and other collectives of self-propelled agents. It also offers a cautionary lesson about complexity: what looks like elaborate, centrally coordinated decision-making at the colony level can be an emergent consequence of simple, purely local interactions. For a soil bacterium with a genome no larger than that of many free-living microbes, the ability to switch between hunting strategies using nothing more than physics may be one of the secrets of its evolutionary success as a social predator.

Subject of Research: Pattern formation and behavioral transitions in predatory Myxococcus xanthus bacterial collectives

Article Title: Mechanisms of spatial pattern transition in motile bacterial collectives

Article References: Mechanisms of spatial pattern transition in motile bacterial collectives. (n.d.). https://doi.org/10.1038/s41567-026-03416-y

Image Credits: AI Generated

DOI: 10.1038/s41567-026-03416-y

Keywords: Myxococcus xanthus, bacterial swarming, rippling, collective behavior, active matter, pattern formation, cell reversal, Frz signaling, extracellular matrix, agent-based modeling, microbiology, biophysics