Biophysical Journal

Although many of the proteins of secretory granules have been identified, little is known about their molecular organization and diffusion characteristics. Granule-plasma membrane fusion can only occur when proteins that enable fusion are present at the granule-plasma membrane contact. Thus, the mobility of granule membrane proteins may be an important determinant of fusion pore formation and expansion. To address this issue, we measured the mobility of (fluorophore-tagged) vesicle associated membrane protein 2 (VAMP2), synaptotagmin 1 (Syt1), and synaptotagmin 7 (Syt7) in chromaffin granule membranes in living chromaffin cells. We used a method that is not limited by standard optical resolution. A bright flash of strongly decaying evanescent field ([~]80 nm exponential decay constant) produced by total internal reflection (TIR) was used to photobleach GFP-labeled proteins in the granule membrane. Fluorescence recovery occurs as unbleached protein in the granule membrane distal from the glass interface diffuses into the more bleached proximal regions, thereby enabling the measurement of diffusion coefficients. The studies revealed that VAMP2, Syt1, and Syt7 are relatively immobile in chromaffin granules membranes with diffusion constants of [≤] 3 x 10-10 cm2/s. Utilizing these diffusion parameters and the known density of VAMP2 and Syt 1 on synaptic vesicles, we estimated the time required for these proteins to arrive at a nascent fusion site to be tens of milliseconds. We propose that the mobilities of secretory granule SNARE and Syt proteins, heretofore unappreciated factors, influence the kinetics of exocytosis and protein discharge. Significance StatementIn eukaryotic cells, secretory vesicles fuse with the plasma membrane to secrete chemical transmitters, hormones and proteins that enable diverse physiological functions including neurotransmission. Fusion proteins need to be assembled at the fusion site in sufficient number in order to enable membrane fusion. However, the diffusion characteristics of fusogenic proteins on secretory vesicles remained unknown. Here we used a novel method not limited by standard optical resolution to measure the diffusion of VAMP2 and synaptotagmins on chromaffin granule membranes. We found they have limited mobility. The time required for these proteins to reach the granule-plasma membrane contact site suggests that their limited mobility likely influences the kinetics of membrane fusion and subsequent fusion pore expansion.

The positively charged residues, arginine and lysine, of the S4 segments of voltage-sensitive ion channels repel each other with Coulomb forces inversely proportional to the mean channel dielectric permittivity {varepsilon}. Dipole moments induced at rest potential in the branched sidechains of leucine, isoleucine and valine lend high values of {varepsilon} to the channel. High {varepsilon} keeps electrostatic forces small at rest, leaving the channel in a compact conformation closed to ion conduction. On membrane depolarization beyond threshold, the repulsive forces between positive S4 charges increase greatly on a sharp decrease in {varepsilon} due to the collapse of induced dipoles, causing an expansion of the S4 segments, which drives the channel into activation. Model calculations based on helical S4 geometry, neglecting the small number of negative charges, provide estimates of electrostatic energy for different values of open-channel {varepsilon} and numbers of positive S4 charges. When the Shaker K+ channel is depolarized, the repulsion energy in each S4 segment increases from about 0.2 kcal/mol to about 120 kJ/mol (30 kcal/mol). The S4 expansions lengthen and widen the pore domain, expanding the hydrogen bonds of its helices, thus providing sites for permeant ions. Ion percolation via these sites produces the stochastic ion currents observed in activated channels. The model proposed, Channel Activation by Electrostatic Repulsion (CAbER), explains observed features of voltage-sensitive channel behavior and offers predictions that can be tested by experiment.\n\nSIGNIFICANCE STATEMENTScience walks on two legs, experiment and theory. Experiment provides the facts that theory seeks to explain; the predictions of a theoretical model are then tested in the laboratory.\n\nRigid adherence to an inadequate model can lead to stagnation of a field.\n\nThe way in which a protein molecule straddling a lipid membrane in a nerve or muscle fiber responds to a voltage change by allowing certain ions to cross it is currently modeled by simple devices such as gated pores, screws and paddles. Since molecules and everyday objects are worlds apart, these devices dont provide productive models of the way a voltage-sensitive ion channel is activated when the voltage across the resting membrane is eliminated in a nerve impulse. A change of paradigm is needed.\n\nLike all matter, ion channels obey the laws of physics. One such law says that positive charges repel other positive charges. Since each of these ion channels has four \"voltage sensors\" studded with positive charges, they store repulsion energy in a membrane poised to conduct an impulse. To see how that stored energy is released in activation, we must turn to condensed-state physics. Recent advances in materials called ferroelectric liquid crystals, with structures resembling those of voltage-sensitive ion channels, provide a bridge between physics and biology. This bridge leads to a new model, Channel Activation by Electrostatic Repulsion,\n\nThree amino acids scattered throughout the molecules have side chains split at their ends, which makes them highly sensitive to changing electric fields. The calculations that form the core of this report examine the effect of these branched-chain amino acids on the repulsions between the positive charges in the voltage sensors. The numbers tell us that the voltage sensors expand on activation, popping the ion channel into a porous structure through which specific ions are able to cross the membrane and so carry the nerve impulse along.\n\nThis model may someday enable us to learn more about diseases caused by mutations in voltage-sensitive ion channels. But for now, the ball is in the court of the experimentalists to test whether the predictions of this model are confirmed in the laboratory.

Lipid-ion channel interactions play a critical role in channel function and membrane structural organization. Despite this importance, the mechanisms behind the rearrangement of lipids around ion channels are still unclear. To investigate this, we conducted coarse grained (CG) molecular dynamics simulations of voltage gated sodium ion channels (NavAB) embedded in a ternary lipid bilayer composed of 1,2-dilinoleoyl-sn- glycero-3-phosphocholine (DIPC), 1,2-dipalmitoyl-sn-glycero- 3-phosphocholine (DPPC), and cholesterol (CHOL) at varying CHOL concentrations (6.62%, 17.62% and 30.00%). By analyzing lipid organization and membrane structure, we examined how membrane composition and channel state (activated and resting) influence lipid redistribution near the channel interface. Our key finding is a pronounced preference for DIPC for the channel vicinity, observed consistently for all CHOL concentrations and channel states. Our simulations reveal that hydrophobic mismatch dictates lipid sorting near NavABs. The hydrphobic thickness of the channel favors flexible DIPC lipids, which are packed efficiently around it, while excluding thicker DPPC lipids. This exclusion drives DPPC and cholesterol to form ordered domains farther from the channel interface. Mixing entropy analysis supports local lipid de-mixing near the channel, aligning with the emergence of phase-separated domains. Notably, the hydrophobic thickness of NavAB remained stable and in close agreement with the experimental values, indicating that lipid-specific properties drive reorganization near the channel. Overall, our findings demonstrate that hydrophobic mismatch is a key driver of lipid reorganization and domain formation around ion channels, regardless of CHOL concentration or channel conformational state.

Electrostatic interactions play a key role in protein structure function. There is a large family of mesoscopic protein channels whose selectivity is mainly controlled by the protein electrostatic properties and ion specific channel interactions play a minor role. The knowledge of the charge state of the ionizable residues over a wide pH range, often summarized in their pKa, stands as the most valuable information for structure-function studies of many protein channels. However, experimental pKa determination is a difficult task, typically accomplished using Nuclear Magnetic Resonance only in a limited number of membrane proteins. Thus, the pKa calculation is the most frequently used alternative. Constant pH Molecular Dynamics (CpHMD) simulation provides arguably the most accurate pKa prediction method in proteins containing many charged residues since it captures the coupling between conformational dynamics and residue protonation. Here we study the charge state of a general diffusion porin, OmpF, in which protons exert a crucial regulation of the channel discrimination of small inorganic ions as well as antibiotic translocation. We examine the pKa prediction using different methods, with the CpHMD simulations as benchmarking, and discuss the somewhat unusual titration of several acidic residues. The most widely used pKa prediction methods, though useful for globular proteins, fail to capture the specificities of channel proteins embedded in biological membranes. This is the first attempt we know to use CpHMD to study the pH- dependent charge of a large multiionic channel (with over three hundred ionizable residues) embedded in a lipid membrane.

The level of compaction of an intrinsically disordered protein may affect both its physical and biological properties, and can be probed via different types of biophysical experiments. Small-angle X-ray scattering (SAXS) probe the radius of gyration (Rg) whereas pulsed-field-gradient nuclear magnetic resonance (NMR) diffusion, fluorescence correlation spectroscopy and dynamic light scattering experiments can be used to determine the hydrodynamic radius (Rh). Here we show how to calculate Rg and Rh from a computationally-generated conformational ensemble of an intrinsically disordered protein. We further describe how to use a Bayesian/Maximum Entropy procedure to integrate data from SAXS and NMR diffusion experiments, so as to derive conformational ensembles in agreement with those experiments.

0.Synaptotagmin 7 (Syt-7) is part of the synaptotagmin protein family that regulates exocytotic lipid membrane fusion. Among the family, Syt-7 stands out by its membrane binding strength and stabilization of long-lived membrane fusion pores. Given that Syt-7 vesicles form long-lived fusion pores, we hypothesize that its interactions with the membrane stabilize the specific curvatures, thicknesses, and lipid compositions that support a metastable fusion pore. Using all-atom molecular dynamics simulations and FRET-based assays of Syt-7s membrane-binding C2 domains (C2A and C2B), we found that Syt-7 C2 domains sequester anionic lipids, are sensitive to cholesterol, thin membranes, and generate lipid membrane curvature by two competing, but related mechanisms. First, Syt-7 forms strong electrostatic contacts with the membrane, generating negative curvature stress. Second, Syt-7s calcium binding loops embed in the membrane surface, acting as a wedge to thin the membrane and induce positive curvature stress. These curvature mechanisms are linked by the protein insertion depth as well as the resulting protein tilt. Simplified quantitative models of the curvature-generating mechanisms link simulation observables to their membrane-reshaping effectiveness.

Lateral interactions can stabilize different EphA2 receptor assemblies in the plasma membrane in response to different ligands. Here we use two fluorescent techniques, Forster Resonance Energy Transfer (FRET) and Fluorescence Intensity Fluctuations (FIF) spectrometry, to investigate how mutations in the EphA2 transmembrane (TM) helix affect the association between full-length EphA2 molecules in the absence of ligand and in the presence of three ligands: ephrinA1-Fc, m-ephrinA1, and the YSA peptide. The EphA2 mutations we studied have been previously characterized in the context of the isolated EphA2 TM helix. Working with full-length EphA2, we observed modest effects of the mutations on receptor-receptor interaction. Our data do not support the currently accepted model of a switch between two discrete TM helix dimerization motifs corresponding to active or inactive receptor states. Instead, we propose that different dimeric/oligomeric arrangements of the EphA2 extracellular region couple to an ensemble of TM helix dimer interfaces. Plasticity in the arrangements of receptor tyrosine kinase TM helices in active dimers and oligomers may serve to facilitate the cross-phosphorylation of multiple tyrosines in different positions of the intracellular regions.

Single-event completion times, such as are estimated in viral entry, offer both promise and challenge to kinetic interpretation. The promise is that they are able to constrain underlying kinetic models much more efficiently than bulk kinetics, but the challenge is that completion times alone can incompletely determine complex reaction topologies. Gamma distributions or mechanistic models have often been used to estimate kinetic parameters for such data, but the gamma distribution relies on homogenous processes contributing to the rate-limiting behavior of the system. Here, we introduce hypoexponential analysis to estimate heterogeneous kinetic processes. We demonstrate that hypoexponential fitting can indeed estimate rate constants separated by 2-3 orders of magnitude. We then apply this approach to measurements of SARS-CoV-2 entry, showing that ACE2 reduces the number of rate-limiting steps but does not change the rates of these kinetic processes. We propose a kinetic model whereby SARS-CoV-2 entry is driven by a mixture of ACE2-accelerated and ACE2-independent spike protein activation events. Inferring such models requires the capability to detect heterogeneous kinetic processes, provided by robust estimation of hypoexponential distributions.

Cells rely on contractility to proliferate, and cancerous ones exhibit an increased glucose dependence. It is therefore hypothesized that glucose restriction can mitigate cancer cell proliferation by stunting their contractility. However, glucose-restriction studies have mostly been based on experiments that have yielded conflicting results; some cells become less contractile under glucose-restriction, intuitively, while, others become surprisingly more contractile. Active mechanistic modeling may prove fruitful in resolving these conflicts. In this study, we develop a model for glucose-mediated cell contractility to capture the mechanical implications of glucose restriction. The model is calibrated on cell contraction data taken from 2D-cultured glioma cells, laying on a collagen substrate. The model predicts the existence of a critical level of glucose restriction that must be exceeded for contractility to be affected, and this is validated by our experiments. Our model provides an initial step toward a fundamental understanding of the metabolic implications of cell contractility, particularly in the context of glucose restriction: an essential step in cancer studies. significanceThis study advances our understanding of how glucose restriction affects cancer cell contractility, an essential factor in cell proliferation. Our findings reveal that cells require severe glucose deprivation before exhibiting reduced contractility, highlighting a threshold response. This indicates that the cytoskeleton, a key structural component, remains active until a significant reduction in energy supply forces the cell into a lower energy state. These insights provide critical knowledge about the metabolic hierarchy within cells, contributing to the broader study of cancer metabolism and potential therapeutic strategies aimed at disrupting cellular energy pathways.

Experimental studies reveal that anionic lipid POPA and non-phospholipid cholesterol inhibit the gating of voltage-sensitive potassium (Kv) channels at 5-10% molar concentrations. Intriguingly, other anionic lipids similar to POPA, like POPG, have minimal impact on the gating of the same channels for reasons that remain obscure. Our long-timescale atomistic simulations show that POPA preferentially solvates the voltage sensor domains of Kv channels by direct electrostatic interactions between the positively charged arginine and negatively charged phosphate groups. Cholesterol solvates the voltage sensor domains through CH-{pi} interactions between the cholesterol rings and the aromatic side chains of phenylalanine and tyrosine residues. A continuum electromechanical model predicts that POPA lipids may restrict the vertical motion of voltage-sensor domain through direct electrostatic interactions, while cholesterol may oppose the radial motion of the pore domain of the channel by increasing the mechanical rigidity of the membrane. The electromechanical model predictions are consistent with measurements of the activation curves of Kv channels for various lipids. The atomistic simulations also suggest that the solvation due to POPG is much weaker likely due to its bigger head-group size. Thus the channel activity appears to be tied to the local lipid environment, allowing lipids to regulate channel gating in low concentrations.

Plant cytokinesis, a fundamental process of plant life, involves de novo formation of a cell plate that partitions the cytoplasm of the dividing cell. Cell plate formation is directed by orchestrated delivery, fusion of cytokinetic vesicles, and membrane maturation to the form the nascent cell wall by the timely deposition of polysaccharides such as callose, cellulose, and crosslinking glycans. In contrast to the role of endomembrane protein regulators the role of polysaccharides, in cell plate development is poorly understood. Callose, a {beta}-1-3 glucan polymer, is transiently accumulated during cell plate expansion to be replaced by cellulose in mature stages. Based on the severity of cytokinesis defects in the absence of callose, it has been proposed that it stabilizes this membrane network structure. However, there is currently no theory to understand its role in cytokinesis. Here we extend the Helfrich free energy model for membranes including a phenomenological spreading force as an "areal pressure" generated by callose and/or other polysaccharides. Regular cell plate development in the model is possible, with suitable bending modulus, for a two-dimensional late stage spreading force parameter of between 2-6pN/nm, an osmotic pressure difference of 2-10kPa, and spontaneous curvature between 0-0.04nm-1. With these conditions, stable membrane conformation sizes and morphologies emerge in concordance with stages of cell plate development. With no spreading force, the cell plate fails to mature properly, corroborating experimental observations of cytokinesis arrest in the absence of callose. To reach a nearly mature cell plate, our model requires the late stage onset that the spreading force coupled with a concurrent loss of spontaneous curvature. A simple model based upon production of callose as a quasi-two-dimensional self-avoiding polymer produces the correct phenomenological form of the spreading force, which will be further refined, since matching to our numbers requires an exceptionally high callose synthesis rate. Significance StatementPlant cell division features the development of a unique membrane network called the cell plate that matures to a cell wall which separates the two daughter cells. During cell plate development, callose, a {beta}-1-3 glucan polymer, is transiently synthesized at the cell plate only to be replaced by cellulose in mature stages. The role for this transient callose accumulation at the cell plate is unknown. It has been suggested that callose provides mechanical stability, as well as a spreading force that widens and expands tubular and fenestrated cell plate structures to aid the maturation of the cell plate. Chemical inhibition of callose deposition results in the failure of cell plate development supporting this hypothesis. This publication establishes the need for a spreading force in cell plate development using a biophysical model that predicts cell plate development in the presence and the absence of this force. Such models can potentially be used to decipher for the transition/maturation of membrane networks upon the deposition of polysaccharide polymers.

The deformation of cellular membranes regulates trafficking processes, such as exocytosis and endocytosis. Classically, the Helfrich continuum model is used to characterize the forces and mechanical parameters that cells tune to accomplish membrane shape changes. While this classical model effectively captures curvature generation, one of the core challenges in using it to approximate a biological process is selecting a set of mechanical parameters (including bending modulus and membrane tension) from a large set of reasonable values. We used the Helfrich model to generate a large synthetic dataset from a random sampling of realistic mechanical parameters and used this dataset to train machine learning models. These models produced promising results, accurately classifying model behavior and predicting membrane shape from mechanical parameters. We also note emerging methods in machine learning that can leverage the physical insight of the Helfrich model to improve performance and draw greater insight into how cells control membrane shape change.

Chemoreceptors are principal components of the bacterial sensory system that modulates cellular motility. They detect changes in the environment and transmit information to CheA histidine kinase, which ultimately controls cellular flagellar motors. The prototypical Tsr chemoreceptor in E. coli is a homodimer containing two principal functional modules: (i) a periplasmic ligand-binding domain and (ii) a cytoplasmic signaling domain. Chemoreceptor dimers are arranged into a trimer of dimers at the tip of the signaling domain comprising a minimal physical unit essential for enhancing the CheA activity several hundredfold. Trimers of dimers are arranged into highly ordered hexagon arrays at the cell pole; however, the mechanism underlying the trimer-of-dimer and higher order array formation remains unclear. Furthermore, molecular mechanisms of signal transduction that are likely to involve inter-dimer interactions are not fully understood. Here we apply all-atom, microsecond-time scale molecular dynamics simulations of the Tsr trimer of dimers atomic model in order to obtain further insight into potential interactions within the chemoreceptor signaling unit. We show extensive interactions between homodimers at the hairpin tip of the signaling domain, where strong hydrophobic interactions maintain binding. A subsequent zipping of homodimers is facilitated by electrostatic interactions, in particular by polar solvation energy and salt bridges that stabilize the final compact structure, which extends beyond the kinase interacting subdomain. Our study provides evidence that interdimer interactions within the chemoreceptor signaling domain are more complex than previously thought.

Fluorescence recovery after photobleaching (FRAP) is widely used to characterize diffusion in cells, but quantitative interpretation of the data in small prokaryotes requires explicitly accounting for cell geometry. While this has been successfully achieved for spherical and rod-shaped bacteria, analytical approaches developed in these cases are not directly applicable to cells with more complex morphologies. Here, we explore the application of FRAP to helical bacteria using simulations. We show that half-compartment FRAP experiments, where one-half of the cell is photobleached, provide a robust means of characterizing fast protein diffusion. To help with the practical implementation of this technique, we established the relationship between the diffusion coefficient and characteristic fluorescence recovery time as a function of cell length and helical parameters, and for two different ways of estimating the recovery time. As a first application, we report measurements of the diffusion coefficient of the fluorescent protein, mNeonGreen, in the helical bacterium Paramagnetospirillum magneticum AMB-1. We find it to be D = 4.9 {+/-} 2.2 {micro}m2 s-1 in isosmotic conditions, not significantly different from the value measured in Escherichia coli. Although developed for helical bacteria, including spirilla, spirochetes, and vibrios, our framework can readily be extended to cells or compartments with other geometries.

Intracellular transport by teams of molecular motors is an essential cell-biological process that ensures the proper distribution of organelles, and other materials within cells. These teams of motors cooperate and compete in complex ways to achieve desired transport velocity and runlength. In-vitro experiments have observed that coupling motors through a lipid membrane that mimics in vivo membrane-bound cargoes leads to a higher cargo velocity. However, the mechanisms behind this increase in lipid cargo velocity are unclear. Here we seek to understand these mechanisms using Brownian dynamics simulations. We show that an underlying heterogeneity in single motor velocity is essential for the increased velocity of lipid cargoes. Our simulations also show that while the runlengths of both rigid and lipid cargoes increase, and the velocities decrease, with an increase in the fraction of slower motors, lipid cargoes can travel faster and substantially further with the same degree of heterogeneity, suggesting functional advantages of motor velocity heterogeneity. Together, our work explains mechanisms behind previous experimental observations and generates new experimentally testable predictions on velocities and runlengths relevant for in vivo transport.

Antigen (Ag) crosslinking of immunoglobulin E-receptor (IgE-Fc{varepsilon}RI) complexes in mast cells and consequent coupling with Lyn tyrosine kinase in the plasma membrane inner leaflet stimulates transmembrane signaling to initiate allergic and inflammatory responses. As established previously, this coupling requires formation of liquid-ordered (Lo)-like regions (aka "rafts") around the nano-clustered receptors to facilitate lipid-based partitioning of Lyn via its membrane anchor, followed by receptor phosphorylation mediated by protein-protein interactions. Imaging fluorescence correlation spectroscopy (ImFCS) was previously used to measure diffusion of Lyn-EGFP and its lipid anchor PM-EGFP (both Lo-preferring) as well as EGFP-GG (inner leaflet lipid probe, liquid-disordered (Ld)-preferring) and showed that the membrane reorganized within 15 minutes after Ag addition. To quantify the transition kinetics between the resting and Ag-stimulated steady-states, we have now developed Boxcar ImFCS for time-resolved diffusion measurements on sub-minute scale. We found that Ag stimulation causes gradual diffusion decreases for Lyn-EGFP and PM-EGFP with distinctive half-times (t1/2) of 6.9 min and 12 min, respectively, showing that Lyns protein-based interactions accelerate its diffusional transition. Simultaneously, EGFP-GG gradually changes to faster diffusion with t1/2 = 9.4 min. In comparison, t1/2 = 5.0 min for recruitment of cytoplasmic Syk by phosphorylated Fc{varepsilon}RI, consistent with initiation of transmembrane signaling before global membrane reorganization and raft condensation is completed by large, stabilized Ag-IgE-Fc{varepsilon}RI clusters. Boxcar ImFCS extends the analytical power of ImFCS to reveal dynamic membrane processes that may accompany stimuli-receptor interactions and their sequalae. STATEMENT OF SIGNIFICANCEStimulated lipid reorganization and stabilization of liquid-ordered (Lo)- like regions ("rafts") in the plasma membrane inner leaflet are decisive for initiating IgE-receptor-mediated mast cell signaling. Here, we developed a new technique, termed Boxcar Imaging Fluorescence Correlation Spectroscopy, to determine the kinetics of raft stabilization after antigen binding and crosslinking IgE receptors. We provide one of the first characterizations of time-dependent raft condensation as stimulated in live cells. We envisage broad applications of this experimental strategy to quantitatively decipher intertwined processes of membrane phase-like separation and functional transmembrane signaling.

Microtubule-directed anti-cancer drugs, such as paclitaxel, vinblastine, and colchicine, disrupt cell mitosis through suppression of microtubule dynamics ("kinetic stabilization"). However, while the molecular mechanisms of paclitaxel and vinblastine act as pseudo- and true-kinetic stabilizers, respectively, the molecular mechanism of colchicine has remained enigmatic since it requires explanation of both the slow kinetics of the drug and suppression of microtubule dynamics. In this work, we applied an integrated multi-scale modeling-experimental approach to systematically characterize the microtubule targeting agent (MTA) colchicine. We found that colchicine stabilizes microtubule dynamics significantly both in vivo and in vitro in a time and concentration-dependent manner. Molecular modeling results suggest that tubulins binding pocket is accessible to the drug for only 15% of the simulation trajectory time in straight and 82% in curved conformation on average, confirming that colchicine mainly binds to free tubulin. Molecular dynamics simulations show that there are conformational changes at longitudinal and lateral residues of GTP-tubulin-colchicine compared to a lattice tubulin structure, explaining why further incorporation of tubulin dimers to a tubulin-colchicine complex at a protofilament tip is unfavorable. Thermokinetic modeling of microtubule assembly shows that colchicine bound at fractions as low as [~]0.008 to free tubulin can poison the ends of protofilaments with a Poisson distribution and thus, reduce the microtubule growth rate, while stabilizing the tubulin lateral bond and reducing the microtubule shortening rate, i.e. true kinetic stabilization. This study suggests new strategies for colchicine administration to improve the therapeutic window in the treatment of cancer and inflammatory diseases. Significance StatementColchicine is an ancient microtubule targeting agent (MTA) known to attenuate microtubule (MT) dynamics but its cancer treatment efficacy is often limited by lack of a detailed understanding of the drugs mechanism of action. The primary goal of this study was to perform a multi-scale systematic analysis of molecular mechanism of action of colchicine. The analysis indicates that unlike paclitaxel and vinblastine, colchicine poisons the ends of protofilaments of MTs at low fractions bound to tubulin, in a time-dependent manner. Our results suggest new insights into improvement of the clinical administration of colchicine and new colchicine-site inhibitors.

Amyloid aggregates are found in many neurodegenerative diseases including Huntingtons, Alzheimers, and prion diseases. The precise role of the aggregates in disease progression has been difficult to elucidate due to the diversity of aggregated states they can adopt. Here we study the formation of fibrils and oligomers by exon 1 of huntingtin protein. We show that the oligomer states are consistent with polymer micelles that are limited in size by the stretching entropy of the polyglutamine region. The model shows how the sequences flanking the amyloid core modulate aggregation behavior. The N17 region promotes aggregation through weakly attractive interactions, while the C38 tail opposes aggregation via steric repulsion. We also show that the energetics of cross-{beta} stacking by polyglutamine would produce fibrils with many alignment defects, but minor perturbations from the flanking sequences are sufficient to reduce the defects to the level observed in experiment. We conclude with a discussion of the implications of this model for other amyloid forming molecules.

Tip growth is a tightly regulated process that enables root hairs to explore their surroundings, enhancing plant development, particularly by improving nutrient uptake. While Lockharts viscoplastic framework is widely used to describe this process, it has received limited experimental validation. By integrating optical microscopy with a custom microplate-based rheometer, we created a novel protocol to simultaneously measure, for individual growing root hairs, both the reduction in growth rate and the instantaneous compression in response to a step in applied axial force. The observed growth rate reduction aligns remarkably with a 1D Lockhart viscoplastic model, experimentally validating this framework in tip-growing cells. Additionally, the instantaneous compression upon force application provided an in situ estimate of turgor pressure. Together, these measurements allowed us to determine, for the first time in Arabidopsis root hairs, two critical parameters: the yield turgor pressure and cell wall viscosity. Our approach--including the technique, protocol, and analytical framework--can be readily adapted to other tip-growing species and diverse experimental conditions (e.g., varying nutrient availability or osmotic stress). This opens new opportunities to explore cell wall mechanosensitivity and its role in adapting tip growth to environmental signals. Significance StatementPlant growth relies on their ability to anchor roots in soil and maximize nutrient uptake. This process partly depends on root hairs. These long tubular extensions develop from the root surface, exhibiting a highly directional growth process --tip growth. Understanding how root hair growth adapts to soil mechanics is crucial, especially with climate change and soil hardening. We present a novel, non-invasive technique to probe the mechanics of root hair walls--key to their growth. By applying a feedback-controlled force, we can investigate the effect of mechanical resistance on root hair growth while preventing buckling, thus accessing elusive cell wall features. This method holds broader significance, as tip-driven growth is also used by fungi and yeasts to colonize their environments.

Determining the permeability of lipid membranes to gases is important for understanding the biological mechanisms of gas transport. Experiments on model membranes have been used to determine the permeability of lipid bilayers in the absence of proteins. Previous measurements have used a number of different methods and obtained widely varying results. We have developed a microfluidic based microscopy assay that measures the rate of CO2 permeation in Giant Unilamellar Vesicles (GUVs), and we report permeability data for the POPC-cholesterol system. We find that cholesterol has a strong effect on permeability; bilayers containing high levels of cholesterol are an order of magnitude less permeable than bilayers without cholesterol, 9.9 {+/-} 1.0 x 10-4 cm/s vs. 9.6 {+/-} 1.4 x 10-3 cm/s. Statement of SignificanceDiffusion of dissolved gasses such as carbon dioxide through cell membranes is an important step in physiological processes. Key to understanding the behavior in cells is the measurement of gas diffusion through model lipid membranes, which isolates the effect of the lipids from other membrane components and allows for control of the composition. Previous measurements have yielded different results for the magnitude of gas transport, and have disagreed on the amount that cholesterol affects transport. The present study presents new data on gas transport across lipid mixtures containing cholesterol, and develops a microfluidic assay for gas transport that will enable further work.