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bioRxiv2023

Protein condensate fusion mapping using Hippopede curve

Protein and nucleic acid condensation in cells has been a major focus of biophysical studies in recent years. Such droplets, condensates, or membraneless cellular organelles that form by condensation have been shown to behave like liquid or viscoelastic fluids. In vitro reconstitution of condensates of purified protein and nucleic acid have been used to better understand the phenomena, specifically to quantify the material properties of these condensates. One of the signature properties of a liquid-like condensate is the fusion of two round droplets into a larger droplet. Quantitative imaging and analysis of the fusion process can report the biophysical properties of the condensates, such as surface tension and viscosity in a non-invasive way. Here we take advantage of a model in soft matter physics, hippopede curves, to the condensate fusion problem to estimate these biophysical properties directly and compare the results with existing models in the field. In addition, this method approximates additional parameters such as the surface area and surface curvatures during the fusion process over time.

biophysics↗

bioRxiv2023

Quantifying fluorescence lifetime responsiveness of environment sensitive probes for membrane fluidity measurements

The structural diversity of different lipid species within the membrane defines its biophysical properties such as membrane fluidity, phase transition, curvature, charge distribution and tension. Environment-sensitive probes, which change their spectral properties in response to their surrounding milieu, have greatly contributed to our understanding of such biophysical properties. To realize the full potential of these probes and to avoid misinterpretation of their spectral responses, a detailed investigation of their fluorescence characteristics in different environments is necessary. Here, we examined fluorescence lifetime of two newly developed membrane order probes, NR12S and NR12A, in response to alterations in their environments such as degree of lipid saturation, cholesterol content, double bond position and configuration and phospholipid headgroup. As comparison, we investigated lifetime sensitivity of the membrane tension probe Flipper in these environments. Applying fluorescence lifetime imaging microscopy (FLIM) in both model membranes and biological membranes, all probes distinguished membrane phases by lifetime, but exhibited different lifetime sensitivities to varying membrane biophysical properties (e.g. cholesterol). While the lifetime of Flipper is particularly sensitive to membrane cholesterol content, NR12S and NR12A lifetime is moderately sensitive to both cholesterol content and lipid acyl chains. Moreover, all probes exhibit longer lifetimes at longer emission wavelengths in membranes of any complexity. This emission-wavelength dependency results in varying lifetime resolution at different spectral regions, highly relevant for FLIM data acquisition. Our data provides valuable insights on how to perform FLIM with these probes and highlights both their potential and limitations.

biophysics↗

bioRxiv2023

Connecting Chromatin Structures to Gene Regulation Using Dynamic Polymer Simulations

The transfer of regulatory information between distal loci on chromatin is thought to involve physical proximity, but key biophysical features of these contacts remain unclear. For instance, it is unknown how close and for how long two loci need to be in order to productively interact. The main challenge is that it is currently impossible to measure chromatin dynamics with high spatiotemporal resolution at scale. Polymer simulations provide an accessible and rigorous way to test biophysical models of chromatin regulation, yet there is a lack of simple and general methods for extracting the values of model parameters. Here we adapt the Nelder-Mead simplex optimization algorithm to select the best polymer model matching a given Hi-C dataset, using the MYC locus as an example. The models biophysical parameters predict a compartmental rearrangement of the MYC locus in leukemia, which we validate with single-cell measurements. Leveraging trajectories predicted by the model, we find that loci with similar Hi-C contact frequencies can exhibit widely different contact dynamics. Interestingly, the frequency of productive interactions between loci exhibits a non-linear relationship with their Hi-C contact frequency when we enforce a specific capture radius and contact duration. These observations are consistent with recent experimental observations and suggest that the dynamic ensemble of chromatin configurations, rather than average contact matrices, is required to fully predict productive long-range chromatin interactions.

biophysics↗

bioRxiv2023

The pathogenic p.N1662D SCN2A mutation reveals an essential molecular interaction for Nav1.2 channel inactivation

Mutations in the SCN2A gene encoding the Nav1.2 sodium channel can lead to neurodevelopmental disorders. We studied the N1662D variant associated with severe early-onset developmental and epileptic encephalopathy (DEE). The N1662D mutation almost completely prevented fast inactivation without affecting activation. The comparison of wild-type and N1662D channel structures suggested that the ambifunctional hydrogen bond formation between residues N1662 and Q1494 is essential for fast inactivation. Fast inactivation could also be prevented with engineered Q1494A or Q1494L Nav1.2 channel variants, whereas Q1494E or Q1494K variants resulted in incomplete inactivation and persistent current. Molecular dynamics simulations revealed a reduced affinity of the hydrophobic IFM-motif to its receptor site with N1662D and Q1494L variants relative to wild-type. These results demonstrate that the interactions between N1662 and Q1494 underpin the stability and the orientation of the inactivation gate and are essential for the development of fast inactivation. Six DEE-associated Nav1.2 variants, with mutations mapped to channel segments known to be implicated in fast inactivation were also evaluated. Remarkably, the L1657P variant also prevented fast inactivation and produced biophysical characteristics similar to N1662D, whereas the M1501V, M1501T, F1651C, P1658S, and A1659V variants resulted in biophysical properties that were consistent with gain-of-function and enhanced action potential firing of hybrid neurons in dynamic action potential clamp experiments. Paradoxically, low densities of N1662D or L1657P currents potentiated action potential firing, whereas increased densities resulted in sustained depolarization. The contribution of non-inactivating Nav1.2 channels to neuronal excitability may constitute a novel cellular mechanism in the pathogenesis of SCN2A-related DEE. SIGNIFICANCE STATEMENTSCN2A gene-related early-onset developmental and epileptic encephalopathy (EO-DEE) is a rare and severe disorder that manifests in early infancy and childhood. SCN2A mutations affecting the fast inactivation gating mechanism can cause altered voltage dependence and incomplete inactivation of the encoded Nav1.2 channel, leading to abnormal neuronal excitability. In this biophysical and clinical study of neuronal Nav1.2 variants, we identified amino acid residues that are critical for the stability and orientation of the inactivation gate during fast inactivation. Mutations of these residues prevent fast inactivation and may lead to EO-DEE via a novel pathophysiological mechanism. The results provide novel structural insights into the molecular mechanism of Nav1.2 channel fast inactivation and inform treatment strategies for SCN2A-related EO-DEE.

biophysics↗

bioRxiv2024

High-throughput analysis of membrane fluidity unveils a hidden dimension in immune cell states

Cell membranes undergo biophysical remodelling as an adaptation to the surroundings and to perform specific biological functions. However, the extent and relevance of such changes in human immune cells remain unknown, largely due to the lack of single-cell and multidimensional methodologies. Here, we apply a cytometry-based method to fill this gap by combining biophysical profiling with simultaneous analysis of immune cell markers. This platform reveals notable cell type-dependent plasma membrane order heterogeneity in immune cells. By sorting immune cells according to their membrane order and performing transcriptome and spatial surface proteome analyses together with functional tests, we show that plasma membrane order can be used to identify subsets of immune cells with distinct phenotypes and functional behaviours. Our findings demonstrate a broad heterogeneity of plasma membrane order in immune cells that will provide a more precise definition of immune cell states based on their biophysical properties in health and disease.

biophysics↗

bioRxiv2024

Cellular (de)coordination in gliding motility and plectoneme formation

2Cyanobacteria are key contributors to biogeochemical cycles through photosynthesis and carbon fixation. In filamentous, multicellular cyanobacteria these functions can be influenced through gliding motility, which enables filaments to localise in response to light and also form aggregates. Here, we use the aggregate forming species Fluctiforma draycotensis to study gliding motility dynamics in detail. We find that filaments move in curved and straight trajectories interspersed with re-orientation or reversal of direction. Most reversals take few seconds but some take substantially longer, resulting in a long-tailed distribution of stoppage times. Mean filament speeds range around a micron per second with a relatively uniform distribution against filament length, implying that all or fixed proportion of cells in a filament contribute to movement. We implement a biophysical model that can recapitulate these findings. Model simulations show that for filaments to reverse quickly, cells in a filament must achieve high coordination of the direction of the forces that they generate. To seek experimental support of this prediction, we track individual cells in a filament. This reveals that cells translational movement is fully coupled with their rotation along the long-axis of the filament, and that cellular movement remains coordinated throughout a reversal. For some filaments, especially longer ones, however, we also find that cellular coordination can be lost, and filaments can form buckles that can twist around themselves, resulting in plectonemes. The experimental findings and the biophysical model presented here will inform future studies of individual and collective filament movement. 1 Significance StatementCyanobacteria contribute to global oxygen production and carbon capture. Some cyanobacteria exist as multicellular filaments and display gliding motility that allows them to respond to light and to form aggregates, which influences their biological functions. Here, we study the dynamics of gliding motility. We find that filaments movement is interspersed with re-orientation or reversal of direction and that mean filament speed is mostly independent of filament length. We implement a biophysical model that predicts these features to relate to cells in a filament having high coordination of the direction of the forces that they generate. We find experimental support for this predicted cellular coordination, but also discover instances of longer filaments loosing coordination, resulting in buckling and entangling with other filaments.

biophysics↗

bioRxiv2024

Molecular dynamics simulations reveal molecular mechanisms for the gain and loss of function effects of four SCN2A variants

SCN2A gene disorders cover a wide range of medical conditions, from epileptic encephalopathies to neurodevelopmental disorders. The variants of these disorders, studied through electrophysiology, show complex behaviors that go beyond simple classification as either gain or loss of function. In our study, we simulated the biophysical effects of variants (R937C, V208E, S1336Y, and R853Q) to understand their impact. Our findings reveal that all these variants negatively affect the structural stability of the gene, with R937C being the most unstable. Specifically, R937C disrupts important charged interactions affecting sodium ion flow, while S1336Y introduces a new interaction that impacts the channels inactivation gate. Conversely, the variants V208E and R853Q, which are located in the voltage-sensing domains, have opposite effects: R853Q increases compactness and interaction, whereas V208E shows a decrease. Our computer-based method offers a scalable way to gain crucial insights into how genetic variants influence channel dysfunction and contribute to neurodevelopmental disorders. AUTHOR SUMMARYDespite numerous advancements in computational methods for predicting variant pathogenicity in the SCN2A gene, understanding the precise biophysical molecular mechanisms associated with each variant at the atomic level remains a challenge. Presently, variants are predominantly categorized as either gain or loss of function, often overlooking critical structural details associated with these variants. This study focuses on elucidating the molecular mechanisms linked to the four most common SCN2A variants using all-atom molecular dynamics simulations, employing three replicas for each system. Our findings offer insights into the potential mechanisms underlying these four variants, thereby providing explanations for the observed electrophysiological outcomes. This investigation significantly contributes to enhancing our comprehension of how SCN2A variants manifest in various diseases. It underscores the importance of unraveling the biophysical properties underlying potential disease mechanisms, which could potentially enhance diagnostic and therapeutic strategies for patients afflicted with SCN2A-related disorders.

biophysics↗

bioRxiv2024

Cellular flows initiate left-right patterning prior to laterality gene expression in amniotes

A bilateral body plan is predominant throughout the animal kingdom. Bilaterality of amniote embryos becomes recognizable as midline morphogenesis begins at gastrulation, bisecting an embryonic field into the left and right sides, and left-right asymmetry patterning follows. While a series of laterality genes expressed after the left-right compartmentalization has been extensively studied, the laterality patterning prior to and at the initiation of midline morphogenesis has remained unclear. Here, through a biophysical quantification in a high spatial and temporal resolution, applied to a chick model system, we show that a large-scale bilateral counter-rotating cellular flow, termed as polonaise movements, display left-right asymmetries in early gastrulation. This cell movement starts prior to the formation of the primitive streak (the earliest midline structure) and the subsequent appearance of Hensens node (the left-right organizer). The cellular flow speed and vorticity unravel the location and timing of the left-right asymmetries. The bilateral flows displayed a Right dominance after six hours since the start of cell movements. Mitotic arrest that diminishes primitive streak formation resulted in changes in the bilateral flow pattern, but the Right dominance persisted. Our data indicate that the left-right asymmetry in amniote gastrula becomes detectable earlier than suggested by current models, which assume that the asymmetric regulation of the laterality signals at the node leads to the left-right patterning. More broadly, our results suggest that physical processes can play an unexpected but significant role in influencing left-right laterality during embryonic development. Significance StatementBilaterians are defined by a bilaterally symmetrical body plan. Vertebrates exhibit external bilateral symmetry but display left-right (LR) asymmetry in their internal organs. Amniote embryos switch the patterning of internal organs from bilateral symmetry to LR-asymmetry. Using chick embryos as a model system, here we examined the initiation of LR symmetry breaking. Our biophysical approaches to quantify cellular flows inferred that LR symmetry breaking occurs before the formation of Hensens node, a LR organizer, which serves as a signaling center for LR patterning-gene programs. Our work demonstrates that quantitative biophysical parameters can help unravel the initiation of LR symmetry breaking, suggesting an involvement of physical mechanisms in this critical biological patterning process.

biophysics↗

bioRxiv2024

Martini without the twist: Unveiling a mechanically correct microtubule through bottom-up coarse-graining in Martini 3

Microtubules are essential cytoskeletal filaments involved in cell motility, division, and intracellular transport. These biomolecular assemblies can exhibit complex structural be-haviors influenced by various biophysical factors. However, simulating microtubule systems at the atomistic scale is challenging due to their large spatial scales. Here, we present an approach utilizing the Martini 3 Coarse-Grained (CG) model coupled with an appropriate elastic network to simulate microtubule-based systems accurately. By iteratively optimiz-ing the elastic network parameters, we matched the structural fluctuations of CG hetero-dimer building blocks to their atomistic counterparts. Our efforts culminated in a [~] 200nm microtubule built with [~] 6 million interaction-centers that could reproduce experimentally observed mechanical properties. Our aim is to employ these CG simulations to investigate specific biophysical phenomena at a microscopic level. These microscopic perspectives can provide valuable insights into the underlying mechanisms and contribute to our knowledge of microtubule-associated processes in cellular biology. With MARTINI 3 CG simulations, we can bridge the gap between computational efficiency and molecular detail, enabling in-vestigations into these biophysical processes over longer spatio-temporal scales with amino acid-level insights.

biophysics↗

bioRxiv2024

Functional properties of a disease mutation for migraine in Kv2.1/6.4 channels

Voltage-gated potassium (Kv) channels are integral to cellular excitability, impacting the resting membrane potential, repolarization, and shaping action potentials in neurons and cardiac myocytes. Structurally, Kv channels are homo or heterotetramers comprising four -subunits, each with six transmembrane segments (S1-S6). Silent Kv (KvS), includes Kv5.1, Kv6.1-6.4, Kv8.1-8.2, and Kv9.1-9.3, they do not form functional channels on their own but modulate the properties of heteromeric channels. Recent studies have identified the Kv6.4 subunit as a significant modulator within heteromeric channels, such as Kv2.16.4. The Kv2.16.4 heteromer exhibits altered biophysical properties, including a shift in voltage-dependent inactivation and a complex activation. Current genetic studies in migraine patients have revealed a single missense mutation in the Kv6.4 gene. The single missense mutation, L360P is in the highly conserved S4-S5 linker region. This study aims to demonstrate the biophysical effects of the L360P mutation in Kv2.1 6.4 channels with a fixed 2:2 stoichiometry, using monomeric (Kv2.1/6.4) and tandem dimer (Kv2.1_6.4) configurations. Our findings suggest that the L360P mutation significantly impacts the function and regulation of Kv2.1/6.4 channels, providing insights into the molecular mechanisms underlying channel dysfunction in migraine pathology. Statement of significanceThis study elucidates the biophysical properties of the Kv6.4 L360P mutation, providing insights into its role in Kv2.1 6.4 channel function. Given the high conservation of the leucine residue in the Kv channel family and its association with migraine, our findings have significant implications for understanding the molecular basis of migraine pathophysiology. By analyzing channels with a fixed 2:2 stoichiometry, we highlight the impact of the L360P mutation on channel gating and inactivation. This research advances the knowledge of the silent Kv6.4 channel mechanism and its role in pathophysiology.

biophysics↗

bioRxiv2024

Proton migration on biological membranes: Lipid phase, temperature, and composition dependence of proton transfer processes and membrane proton barrier

Biological membranes play a major role in diffusing protons on their surfaces between transmembrane protein complexes. The retention of protons on the membranes surface is commonly described by a membrane-associated proton barrier that determines the efficiency of protons escaping from surface to bulk, which correlates with the proton diffusion (PD) dimensionality at the membranes surface. Here, we explore the role of the membranes biophysical properties and its ability to accept a proton from a light-triggered proton donor situated on the membranes surface and to support PD around the probe. By changing lipid composition and temperature, while going through the melting point of the membrane, we directly investigate the role of the membrane phase in PD. We show that the proton transfer process from the proton donor to the membrane is more efficient in the liquid phase of the membrane than in the gel phase, with very low calculated activation energies that are also dependent on the lipid composition of the membrane. We further show that the liquid phase of the membrane allows higher dimensionalities (close to 3) of PD around the probe, indicating lower membrane proton barriers. In the gel phase, we show that the dimensionality of PD is lower, in some cases reaching values closer to 1, thus implying specific pathways for PD, which results in a higher proton recombination rate with the membrane-tethered probe. Computational simulations indicate that the change in PD between the two phases can be correlated to the membranes stiffness and looseness at each phase. Significance statementProton diffusion on the surface of biological membranes serves a vital role in migrating protons into bioenergetic systems. Here, we explore how the biophysical properties of the membrane determine proton migration and proton retention on the surface of the membrane, i.e., the membrane proton barrier. We show that the membrane phase, which is also influenced by lipid composition, has a crucial role in the proton circuity of biological membranes. We found that the gel phase reduces the proton diffusion dimensionality and that the proton barrier is determined by lipid composition. Our results highlight the complexity of proton migration on the surface of biological membranes and the associated biophysical parameters that influence the proton diffusion process.

biophysics↗

bioRxiv2025

Evolution of a fuzzy ribonucleoprotein complex in viral assembly

Previously we showed that the genetic diversity of SARS-CoV-2 nucleocapsid (N) protein explores a wide range of biophysical properties facilitated by non-local impact of point mutations to its intrinsically disordered regions (Nguyen et al., 2024). This includes modulation of self-association, such as the creation of a de novo binding interface through the P13L mutation characteristic of Omicron variants. In the present work we focus on the key function of N condensing viral RNA into ribonucleoprotein particles (RNPs) for viral assembly. Lacking high-resolution structural information, biochemical and biophysical approaches have revealed architectural principles of RNPs, which involve cooperative interactions of several protein-protein and protein-RNA interfaces, initiated through oligomerization of conserved transient helices in the central disordered linker of N. Here we study the impact of defining N-protein mutations in variants of concern on RNP formation, using biophysical tools, a virus-like particle assay, and reverse genetics experiments. We find convergent evolution in repeated, independent introduction of amino acid substitutions strengthening existing binding interfaces, compensating for other substitutions that promote viral replication but decrease RNP stability. Furthermore, we show that the P13L mutation of Omicron variants enhances RNP assembly and increases viral fitness. Overall, our data reveal RNP complexes to be highly variable not only in sequence and conformations, but also in thermodynamic and kinetic stability, with its pleomorphism affecting basic architectural principles. We hypothesize that the formation of polydisperse, fuzzy N-RNA clusters with multiple distributed weak binding interfaces optimizes reversible RNA condensation, while supporting host adaptation and allowing for a large sequence space to be explored.

biophysics↗

bioRxiv2019

Importance of Matrix-dimensionality in Regulating the Bone Marrow Hematopoietic Cells Pool

In bone marrow, hematopoietic stem cells (HSCs) and multiple hematopoietic progenitor cells (HPCs) cooperate to differentiate and replenish blood and immune cells. It has long been recognized bone marrow niche parameters interact with hematopoietic stem and progenitor cells (HSPCs) and additional work is required to study niche physical signals controlling cell behavior. Here we presented that important biophysical signals, stiffness and dimensionality, regulating expansion of bone marrow HSPCs. Mice bone marrow derived progenitor cells were cultured in collagen I hydrogel in vitro. We found stiffer 3D matrix promoted the expansion of lineage negative (Lin-) progenitor cells and Lin-Sca-1+c-kit+ (LSK) HSPCs compared to softer hydrogel. Compared with cells cultured in 2D environment, 3D embedded construct had significant advantage on HSPCs expansion, accompanied by increases on myeloid and lymphoid lineage fractions. Bright changes on gene expression were subsequently discovered. According to these data, we concluded that culture matrix dimensionality is an important factor to regulate the behavior of subpopulations in hematopoietic cell pool, which should be considered in attempts to illuminate HSCs fate decision in vitro.\n\nStatement of SignificanceWe would like to submit the enclosed manuscript entitled \"Importance of Niche-dimensionality in Regulating the Bone Marrow Hematopoietic Cells Pool\", which we wish to be considered for publication in Biophysical Journal. Studies about the interaction between HSCs and factors provided by their microenvironment is largely focus on pure perspective of biology. But biophysical factors affecting HSC fate and behavior needs to be further explore. Herein we found ex vivo culture dimensionality affected HSPC expansion. Cell surface marker detection and mRNA expression analysis predicted the changes on myeloid and lymphoid lineage fractions. We hope niche physical signals which we identified will be considered to design HSC biomimetic niches in clinical applications. And we believe that our study will make it interesting to general readers. We deeply appreciate your consideration of our manuscript, and we look forward to receiving comments from the reviewers.

biophysics↗

bioRxiv2019

Molecular Mechanism of Action of Mitochondrial Therapeutic SS-31 (Elamipretide): Membrane Interactions and Effects on Surface Electrostatics

Mitochondrial dysfunction includes heritable diseases, acquired pathologies, and age-related declines in health. Szeto-Schiller (SS) peptides comprise a class of amphipathic tetrapeptides that have demonstrated efficacy in treating a wide array of mitochondrial disorders, and are believed to target mitochondrial membranes due to their enrichment in the anionic phospholipid cardiolipin (CL). However, little is known regarding how SS peptides interact with or alter the physical properties of lipid bilayers. In this study, we have analyzed the interactions of the lead compound SS-31 (Elamipretide) with model and mitochondrial membranes using biophysical and computational approaches. Our results show that this polybasic peptide partitions into the membrane interfacial region with affinity and binding density that are directly related to surface charge. SS-31 binding does not destabilize lamellar bilayers even at the highest binding concentrations; however, it does cause saturable alterations in lipid packing. Most notably, SS-31 modulates the surface electrostatic properties of model and mitochondrial membranes, which could play a significant role in the mitoprotective properties of this compound. As a proof of concept, we show that SS-31 alters ion distribution at the membrane interface with implications for maintaining mitochondrial membranes subject to divalent cation (calcium) stress. Taken together, these results support a mechanism of action in which SS peptides interact with lipid bilayers and alter the biophysical (primarily electrostatic) properties of mitochondrial membranes as their primary mechanism of action. Understanding this molecular mechanism is key to the development of future compound variants with enhanced efficacy.\n\nSignificanceSzeto-Schiller (SS) peptides are among the most promising therapeutic compounds for mitochondrial dysfunction. However, the molecular target(s) and the mechanism of action of SS peptides are poorly understood. In this study, we evaluate the interaction of the lead compound SS-31 (Elamipretide) with mitochondrial and synthetic model membranes using a host of biophysical techniques. Our results show that SS-31 membrane interaction is driven largely by the negative surface charge of mitochondrial membranes and that SS-31 alters lipid bilayer properties, most notably electrostatics at the membrane interface. This work supports a mechanism in which SS peptides act on a key physical property of mitochondrial membranes rather than with a specific protein complex, consistent with the exceptionally broad therapeutic efficacy of these compounds.

biophysics↗

bioRxiv2025

Mechanistic Interpretability of Fine-Tuned Protein Language Models for Nanobody Thermostability Prediction

MotivationWhile Protein Language Models (PLMs) fine-tuned on biophysical data achieve high predictive accuracy, the physical principles underlying their predictions remain obscure. Deciphering these representations offers a unique opportunity to not only interpret model decisions but also to discover novel biophysical insights governing protein properties. Here, we present a framework using Sparse Autoencoders (SAEs) to extract mechanistic knowledge from PLMs fine-tuned for nanobody thermo-stability. ResultsWe fine-tuned the ESM-2 model on the nanobody thermostability dataset, achieving superior performance compared to significantly larger state-of-the-art models. SAE analysis successfully decomposed the models dense embeddings into sparse, interpretable features without loss of predictive accuracy. We characterized these features through both global and local analyses. Global analysis revealed that stabilizing features predominantly activate on the molecular surface, optimizing charge distributions, whereas destabilizing features map to the hydrophobic core, reflecting packing defects. Local analysis identified specific interactions, including known factors like the VHH-tetrad and critical disulfide bonds, as well as novel stabilizing candidates. Free Energy Perturbation calculations confirmed that these novel candidates exhibit structural compatibility, avoiding the severe destabilization seen in neighboring residues. By revealing these multi-scale biophysical rules, our approach demonstrates that interpreting fine-tuned PLMs provides a physics-grounded guide for rational protein engineering. AvailabilityThe data and source code of the proposed method are available at GitHub (https://github.com/matsunagalab/paper_nanobody-thermostability-sae) and Zenodo (DOI: 10.5281/zenodo.18012027). ContactYasuhiro Matsunaga (ymatsunaga@riken.jp) Supplementary informationSupplementary data are available at Bioinformatics online.

biophysics↗

bioRxiv2026

Measurement intensification for antibody formulations: combined measurement of protein size, interactions, and viscosity by differential dynamic microscopy

High-throughput screening and optimization of high-value protein formulations requires intensified measurements to extract a wide range of properties using a small number of measurement techniques, small sample volumes, and short measurement times. We demonstrate how differential dynamic microscopy (DDM) can fill this need by measuring a broad range of key biophysical properties relevant to protein formulations from a single workflow on microliter-scale samples using label-free video optical microscopy. We show that the use of phase contrast imaging dramatically enhances measurement resolution for protein solutions at dilute and semidilute concentrations, enabling measurement of colloidal properties such as protein-protein interactions, protein size, aggregation, and solution viscosity from a single set of measurements. DDM measurements on a representative human immunoglobulin (IgG) system yield estimates for the hydrodynamic radius (Rh), second osmotic virial coefficient (B2), and hydrodynamic interaction (kd) that are consistent with independently measured values, validating the ability of DDM to extract these parameters from a single set of measurements. Observed trends in B2 with pH and ionic strength are consistent with the antibodys charge and screened electrostatics, demonstrating the ability of DDM to provide insight on protein-protein interactions. To show the utility of DDM as a "multitool" for quantifying multiple formulation properties from a single measurement, we use the results to test a predictive colloidal model for the solution viscosity, which is in fair agreement with measurements obtained using DDM-based microrheology. Combined with low sample requirements and short measurement times, DDM thus offers a high-throughput and efficient route to accelerate protein biophysics and formulation development. SIGNIFICANCE STATEMENTThe formulation of stable, high-concentration antibodies and other protein solutions requires extensive biophysical measurements that are often material- and time-intensive. We demonstrate that differential dynamic microscopy (DDM) provides a powerful alternative by providing rapid access to a broad range of industrially relevant colloidal properties from a single measurement on microliter-scale samples using conventional video optical microscopy. This capability makes DDM an attractive, low-resource approach for routine biomolecular formulation screening and optimization.

biophysics↗

bioRxiv2026

Rapid Bacterial Identification and Antibiotic Susceptibility Testing through Interferometry-based Surface Topography Measurement

Scientists have long classified organisms based on shared morphological characteristics. However, modern taxonomy, particularly for bacteria, is largely defined at the genetic level. Yet the information encoded in genetics propagates through many levels of biological organization: genes determine patterns of gene expression and protein production which, in turn, influence cellular physiology and behavior which, in turn, influence the collective morphology of growing populations. It is unclear how far up this hierarchy that the lower level taxonomic information remains preserved. Here, we show that bacterial genera can be identified from differences in the three-dimensional topographies of their growing populations. Using coherence-scanning white-light interferometry (WLI), which is capable of nanometer-resolution, we measure bacterial population topographies of 77 different clinical isolates representing four different genera. We then extract ten biophysically relevant features describing their surface structure. Using a simple machine-learning classifier, these topographic features identified bacterial genus with 97% accuracy, demonstrating that genus-level information remains present at the scale of population morphology. We hypothesize that these topographic "fingerprints" arise because differences in the underlying biophysics of bacterial growth propagate upward into measurable differences in population structure. To test this hypothesis, we performed biophysical simulations of bacterial population growth and applied our experimentally trained classifier directly to the resulting simulated topographies. By systematically modifying simulation parameters, we determined which changes were necessary to generate topographies classified as each of the experimentally observed genera. We find that a relatively small number of differences in cellular growth, cell-surface interactions, and initial conditions are sufficient to recreate the genus-associated differences observed experimentally, and we then show that using the topographic features from the simulations we can recover the underlying parameters used to simulate the topographies. Together, these results show that differences in lower-level bacterial behavior can propagate into distinct population-scale morphologies, and that taxonomic information can remain recoverable far above the molecular scale at which bacterial identity is conventionally defined.

biophysics↗

bioRxiv2026

Membrane structural properties in Staphylococcus aureus are tuned by the carotenoid 4,4'-diaponeurosporenoic acid

Staphylococcus aureus (S. aureus) is a clinically relevant pathogen capable of adapting its membrane composition in response to environmental stress. In this adaptive process, bacterial carotenoids play a crucial role. Although staphyloxanthin (STX) is the main carotenoid produced by the bacterium, S. aureus also synthesizes other pigmented intermediates that play an unknown role in regulating membrane biophysical properties. In this study, we purified 4,4-diaponeurosporenoic acid (4,4'-DNPA) from S. aureus carotenoid extracts and evaluated its effect on the thermotropic and biophysical properties of representative membrane models. The highly rigid triterpenoid 4,4'-DNPA is one of the last precursors in the biosynthesis of STX and is found in high concentrations in the stationary phase of S. aureus. Phase transition temperatures were determined using infrared spectroscopy, while interfacial hydration and hydrophobic core dynamics were investigated using fluorescence spectroscopy through Laurdan generalized polarization and DPH anisotropy. The results show that 4,4'-DNPA increases the main phase transition temperature of lipid bilayers in a concentration-dependent manner. This is in contrast to STX that decreases the transition temperature. This difference is consistent with the additional fatty acid present in STX that changes its effect on the phase behavior. Furthermore, 4,4'-DNPA reduced the interfacial hydration levels and restricted hydrophobic-core dynamics at higher concentrations, consistent with increased molecular order and stability. 4,4'-DNPA therefore complements STX in increasing membrane order and lipid packing. These findings support the notion that the production of bacterial carotenoids functions as a biophysical regulatory mechanism of lipid packing in S. aureus membranes.

biophysics↗