European Biophysics Journal

The primary question in this work is whether a turbidity trace contains more than one resolved kinetic event before any rate or aggregate-mass information is supplied. A blind, three-gate hierarchical Gompertz procedure applied to human interleukin-1 receptor antagonist (IL-1ra) at 53 {degrees}C in phosphate retained one phase at 1 and 2 mg/mL, but selected two phases at 5 and 10 mg/mL. Thus the first resolved multiphase behavior appears at the low protein concentration of 5 mg/mL. Source optical-rate markers were withheld until after selection. Those observed optical rates were then compared with blind-fit phase rates, and the same comparison was expressed on a conditional mass-equivalent scale using the published 5.3-fold Type-I/Type-II turbidity response ratio. A separate 50 {degrees}C citrate series (4, 6, 8, 10, and 14 mg/mL) also selected two phases in every retained trace; its printed Vmax values were used only as post-selection comparators. Finally, two challenging 40 {degrees}C high-concentration traces (180 and 200 mg/mL) were digitized from the instrument-output plot and each retained two phases. All three conditions are analyzed independently. Blind recognition is therefore the central result; the mass-equivalent conversion is a secondary, post-selection interpretation of optical phase rates. The absolute {micro}M/min scale remains conditional on an endpoint aggregate fraction measured elsewhere.

Surface plasmon resonance (SPR) and biolayer interferometry (BLI) are well-established label-free analytical technologies used to determine biomolecular interaction rates (ka, kd) and equilibrium constants (KD). While assays historically rely on multi-cycle kinetics (MCK), this approach requires intermediate surface regeneration, risking sensor degradation and increasing reagent consumption. Single-cycle kinetics (SCK) avoids regeneration by sequentially injecting increasing analyte concentrations. However, implementing SCK workflows on biosensor platforms like the OctetRR8 BLI instrument (Sartorius) remains a challenge due to the lack of built-in or online data analysis tools. To address this, we introduce SCKAnalyzer, a free, user-friendly web application designed for processing and fitting SCK datasets. SCKAnalyzer accepts column-based text files and native raw BLI data (.frd format) from Sartorius instruments, performing data pre-processing and non-linear fitting to a 1:1 interaction model. Additionally, it offers advanced simulation capabilities that allow variable association and dissociation durations across sequential injection steps, a feature absent in existing platforms such as BiacoreTMSimul8. The performance of SCKAnalyzer was experimentally validated using a 3-step SCK method (SCK3) for DNA/RNA duplex formation on a Biacore T200, as well as 4-step (SCK4) and 5-step (SCK5) methods for DNA/DNA duplex formation on an OctetRR8 BLI instrument. Binding parameters (ka, kd, KD) derived from SCKAnalyzer showed excellent agreement with values from established proprietary softwares such as Biacore T200 Evaluation Software v3.2.1 and BIAevaluation v4.1.1. SCKAnalyzer provides a practical alternative to MCK, reducing probe consumption and extending SCK utility across biosensor platforms. SCKAnalyzer is available at sck.iecb.u-bordeaux.fr (source code: github.com/synthaze/sckanalyzer).

Nile Red is widely used for the detection of microplastics because its fluorescence emission is sensitive to local polarity and can distinguish hydrophobic plastics from hydrophilic ones. The fluorescence of the molecular rotor, 9-(dicyanovinyl)-julolidine (DCVJ) is less sensitive to polarity but more to viscosity. DCVJ is less widely used for microplastic analysis, although it has been used to detect polystyrene nanobeads. Here, we compared these dyes with standard samples from the Hawaii Pacific University Polymer Kit 1.0 and confirmed that Nile Red, in general, was better for the detection and identification of microplastics. Fluorescence emission was analyzed using photography, as well as spectroscopy. The color and peak emission wavelength of some stained environmental microplastics were affected by additives. Raman spectroscopy was used to confirm the chemical identity of such samples. Although DCVJ emits green fluorescence on binding to some microplastics, a peak at 620 nm has been reported with polystyrene nanobeads, attributed to dimer/excimer formation. We confirmed this property and directly observed diffraction-limited spots using fluorescence microscopy, attributed to single or just a few nanobeads. Nile Red also stains polystyrene nanobeads and gave stronger signals than with DCVJ, but Nile Red was prone to false positives due to dye aggregation in aqueous solutions.

This study aimed to (1) develop an elasticity framework for the sprint force-velocity (F-V) relationship and (2) examine how maximal force (F_{0}), maximal velocity (v_{0}), and sprint distance modulate the four derived elasticity metrics, and (3) explore these elasticity metrics' interrelation. After modelling the F-V relationship differential equation, four elasticity metrics were defined as force elasticity (F_{e}), the elasticity of sprint time to F_{0}; velocity elasticity (v_{e}), the elasticity of sprint time to v_{0}; the force-velocity elasticity norm {(\mathrm{F}-\mathrm{V}}_{\mathrm{EN}}=\sqrt{F_{e}^{2}+v_{e}^{2}}), capturing the combined sprint time sensitivity to proportional changes in F_{0} and v_{0}; and the force-velocity elasticity ratio {(\mathrm{F}-\mathrm{V}}_{\mathrm{ER}}=F_{e}{\div v}_{e}), indicating which variable dominates the sprint time response. Model simulations showed that F_{e} decreased with rising F_{0} and increased with rising v_{0}, while v_{e} showed the opposite pattern. With increasing sprint distance, F_{e} decreased and v_{e} increased. Given its negligible effect on sprint time, ignoring air resistance yields a conservation law (2F_{e}+v_{e}\equiv 1), indicating that a gain in one elasticity metric necessarily diminishes the other in a fixed proportion. This framework also identifies a valley distance (d_{valley}) at {\mathrm{F}-\mathrm{V}}_{\mathrm{ER}}=2, where {\mathrm{F}-\mathrm{V}}_{\mathrm{EN}} is minimized (\sqrt{0.2}) and sprint time is least responsive to changes in F-V relationship variables. Empirical data confirmed that the two theoretical laws still hold approximately when air resistance is considered. By linking changes in F_{0} and v_{0} to sprint time across different distances, the elasticity framework provides a quantitative basis for estimating the theoretical sprint time response to documented changes in F-V relationship variables.

This paper presents and critically reviews the results of original and some literature based experimental studies conducted by the authors last years on the structural organization of DNA in dormant (starvation stress), anabiotic dormant (4 HR treatment) E. coli cells, as well as the K12 {Delta}dps strain, which lacks the Dps protein (Dps null E. coli). The experimental data includes small-angle synchrotron radiation diffraction (SAXS) and transmission electron microscopy (TEM) data. Synchrotron radiation diffraction experiments on K12{Delta}dps cells allowed us to conclude that peaks at 44.3, 22.1, and 14.8 angstrom resolutions are associated exclusively with ordered DNA organization. Peaks at 44.3, 22.1, and 14.8 angstrom resolutions are also observed for samples of dormant (starvation stress) cells and anabiotically dormant cells. Therefore, this ordered DNA organization also applies to samples of dormant and anabiotically dormant cells. A model is proposed that considers the ordered DNA organization in the cell as a cholesteric liquid crystal. The powder diffraction pattern calculated based on this model is compared with experimental small angle X ray scattering (SAXS) data obtained on Dps-null cell samples. The model completely reproduces the key features of the experimental diffraction pattern from Dps-null cell samples. Accordingly, the cholesteric liquid crystal model corresponds to DNA packaging in dormant and anabiotically dormant cells. Cholesteric liquid crystal ordering should be further considered in all models of cellular DNA packaging. To address the question of which structural organization of DNA predominates in the cell: the cholesteric liquid crystal or nanocrystalline or whether they coexist and fully manifest themselves under different external conditions, it is necessary to utilize the latest methodological advances in structural analysis.

Neutron scattering is a powerful technique to investigate atomic structures and molecular dynamics of proteins at the nano-scale. When it comes to dynamics, incoherent and coherent scattering respectively provide information on the single and collective dynamics of nuclei. In proteins, hydrogen has the highest incoherent cross-section, and it is common practice to overlook the contribution of coherent terms stemming from all nuclei. However, the fast collective dynamics of heavier nuclei could also be studied if coherent scattering and incoherent scattering were experimentally separated. The recent advent of polarized neutron spectroscopy with sufficient flux and energy resolution has made it possible, and opens new perspectives to investigate the relative importance of coherent scattering and the information it provides on biological samples. The present study reports on the use of polarized quasi-elastic neutron scattering (QENS) and the application of a minimalistic model adapted to both individual and collective dynamics. Using a perdeuterated green fluorescent protein as a model globular protein, the study provides an interpretation of the dynamical parameters obtained with QENS, and a comparative study of the Elastic Coherent and Incoherent Scattering Factor. Based on both experiments and calculations, we discuss the relative importance of distinct and self components of coherent scattering, which is often wrongly assumed to be representative of collective dynamics only. The results highlight the current impediments rendering complicated a straightforward analysis of fast collective dynamics in hydrated protein samples.

Humans tend to walk at speeds that minimize energy expenditure and time duration. While most walking experiments examine individuals in relative isolation, everyday locomotion frequently occurs in social contexts. We investigated whether walking speed is modulated in response to a social interaction during a cooperative task. Participants completed 96 randomized walking trials where they approached and retrieved boxes varying in distance (2.5-10 m) and mass (0-6.8 kg). Boxes either rested on the ground or were handed off by an experimenter, signaling prosocial effort benefitting the participant. Approach speed was measured with inertial measurement units placed at the feet and fit to a saturating exponential function of walking distance using a nonlinear mixed-effects regression model. Based on the energy-time optimization framework, we hypothesized that participants would approach more quickly when larger boxes were held at farther distances, to reduce energy and time costs of the experimenter, despite exerting more effort themselves. Participants walked 8.5% faster (1.29 m s-1 versus 1.19 m s-1; p = 3.85 x 10-6) when the largest box was held out by the experimenter versus left on the ground. However, the manner in which the box was held had no influence on approach speeds (p = 0.31). Exploratory analyses identified modest trends between experiment responses and individual characteristics, but none reached statistical significance. The findings suggest that locomotor decisions reflect not only an individuals own energy and time costs but also the perceived costs borne by others. This study demonstrates that social context can meaningfully influence walking behavior. Summary StatementHumans walk more quickly in response to the perceived energy and time others spend helping them, even at the cost of exerting more energy themselves.

Microplicae are ridge-like membrane projections that are prominent features of many epithelial surfaces, yet little is known about the principles governing their spatial organisation. Determining whether microplicae represent stochastic membrane folds or biologically organised surface architectures is essential for understanding their formation and functional roles. Here, differential interference contrast images of human buccal epithelial cells were analysed using quantitative image-processing approaches. Ridge networks were segmented and characterised using complementary measurements of characteristic wavelength, including medial-axis and nearest-neighbour Voronoi analyses, together with skeleton-based metrics describing network architecture. Analysis of n=100 buccal epithelial cells sampled from n=10 donors revealed a reproducible sub-micron characteristic wavelength. Mean medial-axis spacing was 0.511 {+/-} 0.042 {micro}m and mean Voronoi nearest-neighbour spacing was 0.588 {+/-} 0.057 {micro}m. Characteristic wavelength exhibited CV of between only 8.26% and 9.67% across the dataset. However, metrics describing network architecture, including ridge density, branching and connectivity, varied by up to 109%. Donor-level analysis reported the same overall trends, with conservation of the characteristic wavelength while network parameters had considerably greater variation. These findings identify a previously unrecognised organising principle of microplical architecture, suggesting that epithelial membrane organisation is regulated through conservation of an intrinsic geometric length scale while network topology remains comparatively free to remodel.

It is important to determine whether native state dynamics drive the misfolding and oligomerization of the prion protein, which are important events in prion disease, and how they are modulated by conformational conversion. Native (N) mouse prion protein (moPrP) is known to form small (OS) and large (OL) oligomers rich in {beta}-sheet, and in this study, photoinduced electron transfer-fluorescence correlation spectroscopy (PET-FCS) has been used to characterize intramolecular dynamics within individual monomeric units in both isolated OS and OL, as well as the diffusion properties of the oligomers. It is estimated that OS and OL comprise of about 15 and 55 monomeric units, respectively. Microsecond dynamics at each of the two regions that are the 1-3 and 2-3 interfaces of native protein are distinct in N, OS and OL, although they occur on very similar timescales. Analysis of the evolution of the distribution of diffusion times, determined using the maximum entropy method, indicates heterogeneity in the oligomerization reaction. Analysis of the change in the fluctuations which occur in two different timescales in the native state ensemble shows that they are damped more at the erstwhile 1-3 interface than the erstwhile 2-3 interface. The difference in the extent of damping at the erstwhile 1-3 and 2-3 interfaces can be explained on the basis of the structural changes known to occur across each region. The changes in dynamics occur concurrently in both regions, indicating that the structural changes accompanying conformational conversion also occur simultaneously during the oligomerization of moPrP.

Nanoplastic contamination is increasingly recognized as a biochemical stressor, yet the molecular determinants governing how polymer fragment size dictates protein-level interactions remain poorly understood. Here, we combine molecular docking and all-atom molecular dynamics simulations to characterize the interaction of polyethylene (PE) oligomers of increasing length (n = 3, 5, 7, and 14 repeat units) with human catalase, a tetrameric heme enzyme central to cellular antioxidant defense. Single-chain simulations reveal that short PE fragments (3-, 5-, and 7-mer) migrate from an initial domain-connector pose toward a heme-proximal, previously characterized inhibitor-binding site, whereas the 14-mer remains kinetically confined to a peripheral surface site, implicating short-chain PE as a potential catalase inhibitor. In multichain corona systems, backbone dynamics show a non-monotonic, chain-length-dependent destabilization, with the 3- and 5-mer inducing the greatest structural perturbation and the 14-mer best preserving native-like dynamics despite forming an extensive, percolating surface network across all four subunits. MM-PBSA free energy decomposition identifies van der Waals interactions as the dominant thermodynamic driver of binding, while electrostatic surface mapping indicates that cationic surface patches instead govern long-range spatial targeting of PE chains. These findings establish a framework linking nanoplastic fragment size to protein-level toxicity, with direct implications for assessing the biochemical risk of environmentally weathered polyethylene.

Residue-level coarse-grained simulations provide a powerful route for modeling biomolecular condensates over length and time scales that are difficult to access with atomistic molecular dynamics. Coarse-grained models have been shown to reproduce many aspects of equilibrium phase behavior. However, it remains unclear to what extent such models can reproduce the relative timescales of molecular dynamics. Here, we examine this question for complex coacervates with markedly different dynamics, formed by the highly acidic intrinsically disordered protein prothymosin with four cationic partners: linker histone H1, protamine, polylysine, and polyarginine. Coexistence simulations using a residue-level coarse-grained model reproduce key equilibrium observables from experiments, including dense-phase concentrations, ionic-strength-dependent phase behavior, and chain dimensions in the dense and dilute phases. Dynamics are accelerated in these simulations, but a composition-specific time-rescaling factor captures the ionic-strength dependence of chain reconfiguration times within a given complex coacervate. In contrast, time rescaling is not transferable between dense and dilute phases or across condensate compositions and can depend on the chosen observable. These results show that agreement with measured equilibrium observables does not imply a universally transferable timescale for conformational dynamics in residue-level coarse-grained simulations. However, we find that the required time rescaling strongly correlates with the interaction energy of the protein chains, suggesting that the missing frictional effects arise from protein-protein interactions rather than solely from protein-solvent interactions, reminiscent of internal friction. Our findings highlight the need to combine thermodynamic validation with kinetic calibration when interpreting chain relaxation, molecular diffusion, and material properties from residue-level coarse-grained simulations of biomolecular condensates.

We used simulations of short single stranded DNA (ssDNA) homopolymers, based on the sequence dependent Three Interaction Site (TIS) model, to calculate the persistence length (lp) in polyvalent cations. The TIS model accounts for stacking interactions and electrostatic interactions are treated using the Coulomb potential. We find that lp for dT30 (T is thymine) and dA30 (A is adenine) is quantitatively fit using [Formula] ([Formula] is the bare persistence length,{lambda} is a dimensionless constant, and{kappa} -1 is the inverse Debye length) in the divalent cations Mg2+ and Ca2+. The dependence of lp on{kappa} is surprising because it was derived for long flexible polyelectrolytes in which the charges interact via the Debye-Huckel potential. The [Formula] values are 0.4 nm and 1.1 nm for polyT and polyA, respectively. Strikingly, lp is almost independent of the tetravalent spermine concentration. There is no clear theoretical explanation although simulations suggest that the number of spermine molecules that bind to the ssDNA saturates at a small value. A qualitative picture, based on the restrictions of access to the phosphate groups due to volume exclusion of the anisotropic structure of Spm4+, rationalizes the simulation results. The predicted dependence of lp in spermine awaits experimental test.

A cell's ability to maintain its volume is a prerequisite for its essential physiological functions. Changes in extracellular osmolarity induce the flux of water and solutes across the cell and nuclear membrane and, therefore, alters cell and nuclear volumes. Here, we investigated the equilibrium and dynamic volumetric responses of cells and nuclei in adherent human hepatoma (HepG2) cell monolayers using live three-dimensional imaging. Through image segmentation, 3D reconstruction, and volume rendering, precise cell and nuclear volumes were quantified. We found that during hypoosmotic stress, cells swell and lose osmolytes through active volume regulation, and nuclei undergo greater relative expansion than cells. During hyperosmotic stress, we found that both cells and nuclei shrink rapidly, develop irregular morphologies and undergo passive volume regulation. Furthermore, we explored the osmotic responses in these cells by restoring isosmotic conditions following osmotic stress and found that nuclei returned to volumes greater than their initial isosmotic volume, whereas cytoplasmic volume returned to a value below its initial isosmotic volume following swelling. By fitting coupled transport models water and solute permeability estimates for both cells and nuclei were made from their dynamic responses to different anisosmotic media with and without the presence of permeating solutes dimethyl sulfoxide and ethylene glycol. Together, these quantitative measurements of cell, cytoplasm, and nuclear volumetric responses and associated transport parameters have important implications for understanding cell physiology and the mechanism of osmoregulation.

Biomolecular reactions are often composed of multiple stochastic, reversible and branched transition paths over intermediates, leading to rich dynamics. Single-molecule biophysics has revolutionized our view of biology by revealing the heterogeneity in realized paths and pointing to the importance of rare events. The recent development of high-throughput single-molecule biophysics techniques now allow to quantitatively study this heterogeneity and characterize even the rarest kinetic events. Processing, analyzing and modelling high-throughput single-molecule data has been the focus of several reports, but are often difficult to implement for non-experts. Here, we provide a guide to extract the most from transitions in single-molecule biophysics data using a first-passage time framework and maximum likelihood estimation. We specifically focused on parameter sweeps in systems with one or two characteristic timescales, and show how they can be analyzed in terms of a minimal kinetic model and its dependence on enzyme/substrate concentration, force and temperature. We introduce a general framework to perform data-driven modelling on single- and two-state models and illustrate it with concrete examples. We also provide programs with graphical user interfaces to perform such analysis on raw data, in the hope that it will empower experimental single-molecule biophysicists to extract the most out of their data.

Lipid membranes undergo liquid-liquid phase separation to form micron-scale domains. Several physical parameters affect this phase transition. For example, a decrease in temperature causes membranes to demix, as does an increase in hydrostatic pressure. However, measurements to determine how tension affects membrane phase separation have yielded conflicting results. Experiments that have applied osmotic pressure differences to a population of vesicles have reported an increase in the membrane's miscibility transition temperature. Conversely, experiments that have applied micropipette aspiration or substrate stretching to single membranes have reported a decrease. Here, we find that both osmotic pressure and micropipette aspiration can increase transition temperatures. We discuss how membrane pores and hidden areas in membranes present challenges to researchers seeking to quantitatively convert experimentally measured osmolarity differences into membrane tensions. We show that challenges of comparing data from different osmotic pressure experiments can be mitigated by renormalizing osmolarity differences, specifically by dividing by the exterior osmolarity. We discuss our results in the context of existing theoretical predictions and in light of four known effects of increasing tension on vesicle membranes: 1) a reduction in hidden area of tubes and aggregates, 2) a reduction in out-of-plane thermal fluctuations, 3) an increase in the area per lipid, and 4) the formation of pores. First, hidden area can explain why vesicles can sustain high osmolarity differences. Next, suppression of thermal fluctuations and increases in the area per lipid may account for shifts in miscibility transition temperatures. Finally, pores can explain time dependences. Overall, our results highlight the need for new theory and simulation that unify predictions of how transition temperatures vary over all four regimes of membrane tension.

ObjectiveThe complement regulatory protein CD59 has been shown to promote SNARE complex assembly, yet its interaction with vesicle-associated membrane protein 2 (VAMP2) remains poorly characterized. This study aims to identify the key domain in VAMP2 that mediates the CD59 interaction and to evaluate whether CD59 point mutations affect SNARE complex assembly. MethodsThe interaction between CD59 and VAMP2 was examined by immunofluorescence confocal microscopy and co-immunoprecipitation (co-IP). The effect of CD59 on SNARE complex assembly was assessed by co-expressing CD59 with the three core SNARE proteins (syntaxin-1, SNAP-25, and VAMP2) and detecting complex formation by western blotting. Four CD59 single-point mutants were generated and evaluated in SNARE assembly assays. AlphaFold3 was employed to predict the interaction between CD59 and individual VAMP2 domains (confidence threshold: ipTM + pTM [≥] 0.75). Truncated VAMP2 constructs were further characterized by molecular dynamics simulations and co-IP. Results(1) CD59 directly bound VAMP2 and promoted SNARE complex assembly without altering individual SNARE protein levels. (2) All four CD59 single-point mutants retained the ability to promote SNARE assembly at a level comparable to wild-type CD59, despite showing differential effects on binding stability in molecular dynamics simulations. (3) The proline-rich (P-rich) N-terminal domain of VAMP2 was identified as the key binding interface; its deletion abolished the CD59 interaction, whereas deletion of the SNARE motif did not. ConclusionCD59 promotes SNARE complex assembly through interaction with the P-rich N-terminal domain of VAMP2. The examined point mutations do not impair this function, suggesting that these sites may tolerate substitutions or that redundant contact residues maintain the interaction.

Amylose contributes to starch crystallinity, but the stability of packed amylose double helices in water at elevated temperature remains insufficiently characterized. Here, we used molecular dynamics simulations to test whether chain length affects the short-timescale stability of A-type amylose oligomers in water. Six systems differing in chain length (6, 12, or 24 glucose units per chain) and oligomer size (isolated double strand or dodecamer of six double strands) were simulated, and five independent 1-s production runs were analyzed for each simulated condition. Oligomers with six glucose units showed structural collapse accompanied by increased water penetration. By contrast, dodecamers with 12 or 24 glucose units largely retained packed double-helical organization over the simulated timescale, although fraying was observed at their ends. These results indicate that chain length and lateral packing strongly affect the early structural response of amylose-like crystalline segments in hot water. The present simulations do not establish the ultimate fate of longer oligomers at longer timescales, but they identify a relative stability difference that is relevant to molecular interpretations of hydration-driven disordering in starch.

Nanoplastic interactions with cell membranes can influence particle uptake, translocation, and biological effects, making their molecular description important for assessing the environmental and biological consequences of plastic pollution. However, molecular simulations generally represent nanoplastics using monodisperse polymer chains, whereas nanoplastics formed by environmental degradation are polydisperse. Here, we construct 4 nm polyethylene terephthalate (PET), polyethylene (PE), and polystyrene (PS) nanoparticles with lognormal molecular-weight distributions reported for degraded polymers, and with melt-like chain packing and entanglement. Using Martini coarse-grained molecular dynamics, we simulate their interactions for 10 microseconds with three lipid bilayers of increasing complexity. PE and PS insert rapidly and remain largely intact, whereas PET remains surface-associated and progressively releases individual chains. Fluid, polyunsaturated lipid environments undergo greater deformation and promote substantially more chain release, up to 56% of the chains for PET and 43% for PS. Release begins with the shortest chains and progressively extends to longer chains, while semicrystalline PE remains largely intact. In contrast, a size-matched monodisperse PS particle releases no chains and minimally perturbs the membrane. These results identify the molecular-weight distribution as a key determinant of nanoplastic-membrane interactions, and indicate that uniform model particles underestimate the release of polymer chains into biological membranes.

High-speed atomic force microscopy (HS-AFM) experiments provide unique insights into nanoscale biological processes by directly visualizing the surface topography dynamics of biomolecules, such as proteins, over extended periods of time and generating large imaging data sets. However, the lack of computational methods for automated data analysis has thus far limited the full utilization of these data for the quantitative understanding of single-molecule dynamic. Here, we present the AFM Analysis Arena (A3) within BioAFMviewer as a software platform for automated, high-throughput quantitative analysis of AFM topographic imaging data within a user-friendly interactive graphical interface, implementing a convenient workflow from raw HS-AFM (AFM) imaging to statistical analysis. In several applications to HS-AFM imaging data, we demonstrate methods of automatized molecule detection and dynamic tracking to highlight the available capacities, aiming to transform HS-AFM measurements from observations towards an analytical tool in nanoscale biology.

The rising incidence of invasive fungal diseases emphasizes the need for novel therapeutic strategies, including membrane-targeting antifungal agents, which require representative lipid models for detailed molecular-level studies. In this work, we propose a consensus quinary fungal plasma membrane model based on lipidomic literature data, specifically PC:PE:PI:PA:PS phospholipid model with ratio of 44:29:13:8:6. Using a bottom-up approach, we characterized the biophysical properties of this system - with particular emphasis on mechanical parameters such as bending rigidity and area compressibility - by combining molecular dynamics simulations with experimental flicker-noise and ATR-FTIR spectroscopies. Furthermore, we investigated the effect of two key non-phospholipid components: ergosterol and triacylglycerols. Biophysical analysis revealed that DPPI and its specific interactions with DSPS induced the most substantial deviations in baseline membrane parameters, particularly area per lipid, membrane thickness, and area compressibility, while DSPS influenced bending rigidity change and DLiPA primarily affected lipid packing defects. In addition, ergosterol and TGs were found to influence all of the investigated parameters to different degree. Notably, the overall biophysical profile of the proposed FPMM closely mimicked that of natural vesicles derived from yeast lipid extracts, establishing this model may provide a reliable platform for studying fungal membrane biophysics and lipid-targeting interactions.