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At least 145 records · Page 8Linked to original sources

bioRxiv2016

Melittin-induced alterations in morphology and deformability of human red blood cells using quantitative phase imaging techniques

Here, the actions of melittin, the active molecule of apitoxin or bee venom, were investigated on human red blood cells (RBCs) using quantitative phase imaging techniques. High-resolution realtime 3-D refractive index (RI) measurements and dynamic 2-D phase images of individual melittin-bound RBCs enabled in-depth examination of melittin-induced biophysical alterations of the cells. From the measurements, morphological, biochemical, and mechanical alterations of the RBCs were analyzed quantitatively. Furthermore, leakage of haemoglobin (Hb) inside the RBCs at high melittin concentration was also investigated.

biophysics↗

bioRxiv2017

Decoding sequence-level information to predict membrane protein expression

The expression of integral membrane proteins (IMPs) remains a major bottleneck in the characterization of this important protein class. IMP expression levels are currently unpredictable, which renders the pursuit of IMPs for structural and biophysical characterization challenging and inefficient. Experimental evidence demonstrates that changes within the nucleotide or amino-acid sequence for a given IMP can dramatically affect expression; yet these observations have not resulted in generalizable approaches to improved expression. Here, we develop a data-driven statistical predictor named IMProve, that, using only sequence information, increases the likelihood of selecting an IMP that expresses in E. coli. The IMProve model, trained on experimental data, combines a set of sequence-derived features resulting in an IMProve score, where higher values have a higher probability of success. The model is rigorously validated against a variety of independent datasets that contain a wide range of experimental outcomes from various IMP expression trials. The results demonstrate that use of the model can more than double the number of successfully expressed targets at any experimental scale. IMProve can immediately be used to identify favorable targets for characterization.

biophysics↗

bioRxiv2017

Temporal super-resolution in single-molecule experiments

Many time-resolved, single-molecule biophysics experiments seek to characterize the kinetics of biomolecular systems exhibiting dynamics that challenge the time resolution of the given technique. Here we present a general, computational approach to this problem that employs Bayesian inference to learn the underlying dynamics of such systems, even when they are much faster than the time resolution of the experimental technique being used. By accurately and precisely inferring rate constants, our Bayesian Inference for the Analysis of Sub-temporal-resolution Data (BIASD) approach effectively enables the experimenter to super-resolve the poorly resolved dynamics that are present in their data.

biophysics↗

bioRxiv2017

Soft drug-resistant ovarian cancer cells invade via two distinct mechanisms utilizing myosin IIB

The failure of chemotherapeutic drugs in treatment of various cancers is attributed to the acquisition of drug resistance. However, the invasion mechanisms of drug-resistant cancer cells remains incompletely understood. Here we address this question from a biophysical perspective by mapping the phenotypic alterations in ovarian cancer cells (OCCs) resistant to cisplatin and paclitaxel. We show that cisplatin-resistant (CisR), paclitaxel-resistant (PacR) and dual drug-resistant (i.e., resistant to both drugs) OCCs are softer and more contractile than drug-sensitive cells. Protease inhibition suppresses invasion of CisR cells but not of PacR and dual cells, suggesting protease-dependent mode of invasion in CisR cells and protease-independent mode in PacR and dual cells. Despite these differences, actomyosin contractility, mediated by the RhoA-ROCK2-Myosin IIB signaling pathway regulates both modes of invasion. Myosin IIB modulates matrix metalloproteinase-9 (MMP-9) secretion in CisR cells and nuclear squeezing in PacR and dual cells, thereby highlighting its importance as a potential therapeutic target for treatment of drug-resistant ovarian cancer cells.\n\nFinancial SupportAuthors acknowledge financial support from IIT Bombay Healthcare Initiative, CSIR andDepartment of Biotechnology (Govt. of India) (Grant # BT/PR14658/MED/31/107/2010).AK and BTwere supported by fellowships from UGC and CSIR respectively (Govt. of India).\n\nAuthors declare no competing financial interests\n\nAuthor contributions: AK, PR and SS designed the experiments. AK performed most of the experiments and analyzed the data.BT and SG developed drug resistant cell lines and did RT-PCR. MM performed western blot. AD performed AFM experiments. SD performed gelatin zymography. ABB, PM, AM and AD helped with live cell imaging experiments. AK and SS wrote the manuscript. All authors read and approved the final manuscript.\n\nSummary statement: This study identifies drug-specific differences in the modes of invasion utilized by ovarian cancer cells, and demonstrates the role of myosin IIB in regulating both modes of invasion.

biophysics↗

bioRxiv2017

Monod-Wyman-Changeux Analysis of Ligand-Gated Ion Channel Mutants

We present a framework for computing the gating properties of ligand-gated ion channel mutants using the Monod-Wyman-Changeux (MWC) model of allostery. We derive simple analytic formulas for key functional properties such as the leakiness, dynamic range, half-maximal effective concentration ([EC50]), and effective Hill coefficient, and explore the full spectrum of phenotypes that are accessible through mutations. Specifically, we consider mutations in the channel pore of nicotinic acetylcholine receptor (nAChR) and the ligand binding domain of a cyclic nucleotide-gated (CNG) ion channel, demonstrating how each mutation can be characterized as only affecting a subset of the biophysical parameters. In addition, we show how the unifying perspective offered by the MWC model allows us, perhaps surprisingly, to collapse the plethora of dose-response data from different classes of ion channels into a universal family of curves.

biophysics↗

bioRxiv2017

RNA Stores Tau Reversibly in Complex Coacervates

Non-membrane-bound organelles that behave like liquid droplets are widespread among eukaryotic cells. Their dysregulation appears to be a critical step in several neurodegenerative conditions. Here we report that tau protein, the primary constituent of Alzheimer neurofibrillary tangles, can form liquid droplets and therefore has the necessary biophysical properties to undergo liquid-liquid phase separation (LLPS) in cells. Consonant with the factors that induce LLPS, tau is an intrinsically disordered protein that complexes with RNA to form droplets. Uniquely, the pool of RNAs to which tau binds in living cells are tRNAs. This phase state of tau is held in an approximately 1:1 charge balance across the protein and the nucleic acid constituents, and can thus be maximal at different RNA:tau mass ratios depending on the biopolymer constituents involved. This feature is characteristic of complex coacervation. We furthermore show that the LLPS process is directly and sensitively tuned by salt concentration and temperature, implying it is modulated by both electrostatic interactions between the involved protein and nucleic acid constituents, as well as net changes in entropy. Despite the high protein concentration within the complex coacervate phase, tau is locally freely tumbling and capable of diffusing through the droplet interior. In fact, tau in the condensed phase state does not reveal any immediate changes in local protein packing, local conformations and local protein dynamics from that of tau in the dilute solution state. In contrast, the population of aggregation-prone tau as induced by the complexation with heparin is accompanied by large changes in local tau conformations and irreversible aggregation. However, prolonged residency within the droplet state eventually results in the emergence of detectable {beta}-sheet structures according to thioflavin-T assay. These findings suggest that the droplet state can incubate tau and pre-dispose the protein toward the formation of insoluble fibrils.

biophysics↗

bioRxiv2017

Calcium oscillations in wounded fibroblast monolayers are spatially regulated through substrate mechanics

The maintenance of tissue integrity is essential for the life of multicellular organisms. Healing of a skin wound is a paradigm for how various cell types localize and repair tissue perturbations in an orchestrated fashion. To investigate biophysical mechanisms associated with wound localization, we focus on a model system consisting of a fibroblast monolayer on an elastic substrate. We find that the creation of an edge in the monolayer causes cytosolic calcium oscillations throughout the monolayer. The oscillation frequency increases with cell density, which shows that wound-induced calcium oscillations occur collectively. Inhibition of myosin II reduces the number of oscillating cells, demonstrating a coupling between actomyosin activity and calcium response. The spatial distribution of oscillating cells depends on the stiffness of the substrate. For soft substrates with a Youngs modulus E ~ 360 Pa, oscillations occur on average within 0.2 mm distance from the wound edge. Increasing substrate stiffness leads to an average localization of oscillations away from the edge (up to ~0.6 mm). In addition, we use traction force microscopy to determine stresses between cells and substrate. We find that an increase of substrate rigidity leads to a higher traction magnitude. For E < ~2 kPa, the traction magnitude is strongly concentrated at the monolayer edge, while for E > ~8 kPa, traction magnitude is on average almost uniform beneath the monolayer. Thus, the spatial occurrence of calcium oscillations correlates with the cell-substrate traction. Overall, the experiments with fibroblasts demonstrate a collective, chemomechanical localization mechanism at the edge of a wound with a potential physiological role.

biophysics↗

bioRxiv2017

Deletion of the short N-terminal extension in OCP reveals the main site for the FRP binding

The photoactive Orange Carotenoid Protein (OCP) plays a central role in cyanobacterial photoprotection. Photoconversion entails significant structural rearrangements in OCP required for its binding to the phycobilisome to induce excitation energy dissipation, whereas the fluorescence recovery protein (FRP) is required for OCP detachment and restoration of phycobilisome fluorescence. Although key to understanding the whole reversible mechanism of photoprotection, the FRP binding site on OCP has been representing challenge since the discovery of FRP in 2010 and is currently unknown. OCP comprises two structural domains organized into a compact basic orange form due to specific protein-chromophore and inter-domain protein-protein interactions and interacts with FRP tightly only when photoactivated. As an important stabilizing element in the orange OCP, the short A-helix within the N-terminal extension (NTE) binds to OCPs C-terminal domain (CTD), but unfolds upon photoactivation and interferes with phycobilisome binding. By using an alloy of biochemical and biophysical techniques, here we demonstrate that the NTE shares specific structural and functional similarities with FRP and discover the main site of OCP-FRP interactions in the OCP-CTD.

biophysics↗

bioRxiv2017

Mechanisms of generation of membrane potential resonance in a neuron with multiple resonant ionic currents

Neuronal membrane potential resonance (MPR) is associated with subthreshold and network oscillations. A number of voltage-gated ionic currents can contribute to the generation or amplification of MPR, but how the interaction of these currents with linear currents contributes to MPR is not well understood. We explored this in the pacemaker PD neurons of the crab pyloric network. The PD neuron MPR is sensitive to blockers of H- (IH) and calcium-currents (ICa). We used the impedance profile of the biological PD neuron, measured in voltage clamp, to constrain parameter values of a conductance-based model using a genetic algorithm and obtained many optimal parameter combinations. Unlike most cases of MPR, in these optimal models, the values of resonant- (fres) and phasonant- (f{varphi}=0) frequencies were almost identical. Taking advantage of this fact, we linked the peak phase of ionic currents to their amplitude, in order to provide a mechanistic explanation the dependence of MPR on the ICa gating variable time constants. Additionally, we found that distinct pairwise correlations between ICa parameters contributed to the maintenance of fres and resonance power (QZ). Measurements of the PD neuron MPR at more hyperpolarized voltages resulted in a reduction of fres but no change in QZ. Constraining the optimal models using these data unmasked a positive correlation between the maximal conductances of IH and ICa. Thus, although IH is not necessary for MPR in this neuron type, it contributes indirectly by constraining the parameters of ICa.\n\nAuthor SummaryMany neuron types exhibit membrane potential resonance (MPR) in which the neuron produces the largest response to oscillatory input at some preferred (resonant) frequency and, in many systems, the network frequency is correlated with neuronal MPR. MPR is captured by a peak in the impedance vs. frequency curve (Z-profile), which is shaped by the dynamics of voltage-gated ionic currents. Although neuron types can express variable levels of ionic currents, they may have a stable resonant frequency. We used the PD neuron of the crab pyloric network to understand how MPR emerges from the interplay of the biophysical properties of multiple ionic currents, each capable of generating resonance. We show the contribution of an inactivating current at the resonant frequency in terms of interacting time constants. We measured the Z-profile of the PD neuron and explored possible combinations of model parameters that fit this experimentally measured profile. We found that the Z-profile constrains and defines correlations among parameters associated with ionic currents. Furthermore, the resonant frequency and amplitude are sensitive to different parameter sets and can be preserved by co-varying pairs of parameters along their correlation lines. Furthermore, although a resonant current may be present in a neuron, it may not directly contribute to MPR, but constrain the properties of other currents that generate MPR. Finally, constraining model parameters further to those that modify their MPR properties to changes in voltage range produces maximal conductance correlations.

biophysics↗

bioRxiv2017

Measuring Protein Binding to Lipid Vesicles by Fluorescence Cross-Correlation Spectroscopy

Fluorescence Correlation Spectroscopy (FCS) has been previously used to investigate peptide and protein binding to lipid membranes, as it allows for very low amounts of sample, short measurement times and equilibrium binding conditions. Labeling only one of the binding partners however comes with certain drawbacks, as it relies on identifying binding events by a change in diffusion coefficient. Since peptide and protein aggregation can obscure specific binding and since non-stoichiometric binding necessitates the explicit choice of a statistical distribution for the number of bound ligands, we additionally label the liposomes and perform dual-color Fluorescence Cross-Correlation Spectroscopy (dcFCCS). We develop a theoretical framework showing that dcFCCS amplitudes allow calculation of the degree of ligand binding and the concentration of unbound ligand, leading to a binding model-independent binding curve. As the degree of labeling of the ligands does not factor into the measured quantities, it is permissible to mix labeled and unlabeled ligand, thereby extending the range of usable protein concentrations and accessible dissociation constants KD. The total protein concentration, but not the fraction of labeled protein needs to be known. In this work, we apply our dcFCCS analysis scheme to Sar1p, a protein of the COPII complex, which binds major-minor-mix liposomes. A Langmuir isotherm model yields KD = (2.1{+/-}1.1)M as the single site dissociation constant. The dual-color FCCS framework presented here is highly versatile for biophysical analysis of binding interactions. It may be applied to many types of fluorescently labeled ligands and small diffusing particles, including nanodiscs and liposomes containing membrane protein receptors.

biophysics↗

bioRxiv2017

Polarization effects and the calibration of a donut beam axial optical tweezers for single-molecule force spectroscopy

Advances in light shaping techniques are leading to new tools for optical trapping and micromanipulation. For example, optical tweezers made from Laguerre-Gaussian or donut beams display an increased axial trap strength and can impart angular momentum to rotate a specimen. However, their application to precision, biophysical measurements remains limited as their are a number of challenges to applying this tool to optical force spectroscopy. One notable complication, not present when trapping with a Gaussian beam, is that the polarization of the trap light can significantly affect the tweezers strength as well as the precise location of the trap. In this article, we provide a practical implementation of a donut beam optical tweezers for applying axial forces. We show how to precisely calibrate the height of the optical trap above the coverslip surface while accounting for focal shifts in the trap position that arise due to radiation pressure, mismatches in the index of refraction, and polarization induced intensity variations.

biophysics↗

bioRxiv2017

Challenges in estimating the motility parameters of single processive motor proteins

Cytoskeletal motor proteins are essential to the function of a wide range of intracellular mechanosystems. The biophysical characterization of their movement along their filamentous tracks is therefore of large importance. Towards this end, single-molecule, in vitro stepping-motility assays are commonly used to determine motor velocity and run length. However, comparing results from such experiments has proved difficult due to influences from variations in the experimental conditions and the data analysis methods. Here, we investigate the movement of fluorescently-labeled, processive, dimeric motor proteins and propose a unified algorithm to correct the measurements for finite filament length as well as photobleaching. Particular emphasis is put on estimating the statistical errors associated with the proposed evaluation method as knowledge of these values is crucial when comparing measurements from different experiments. Testing our approach with simulated and experimental data from GFP-labeled kinesin-1 motors stepping along immobilized microtubules, we show (i) that velocity distributions should be fitted by a t location-scale probability density function rather than by a norm*al distribution, (ii) that the impossibility to measure events shorter than the image acquisition time needs to be accounted for, (iii) that the interaction time and run length of the motors can be estimated independent of the filament length distribution, and (iv) that the dimeric nature of the motors needs to be considered when correcting for photobleaching. Moreover, our analysis reveals that controlling the temperature during the experiments with a precision below 1 K is of importance. We believe, our method will not only improve the evaluation of experimental data, but will also allow for better statistical comparisons between different populations of motor proteins (e.g. with distinct mutations or linked to different cargos) and filaments (e.g. in distinct nucleotide states or with different posttranslational modifications).

biophysics↗

bioRxiv2017

Spontaneous Phase Separation of Cocultured Cell Mixtures In vitro

During Embryogenesis, cells undergo constant organizational remodelling. Biochemical and biophysical guidance cues act in tandem to guide migration and morphogenesis into distinct cellular patterns. It has been shown that various cell types will express different configurations of cellular adhesion molecules known as cadherins and integrins. Cocultured in vitro experiments have focused on revealing the extensive genetic expression profiles that modulate embryogenesis whilst overlooking the physical cell-cell and cell-substrate interactions that influence organization. We demonstrate that NIH3T3 and MDCK cells undergo a spontaneous phase separation when cocultured in vitro and that this phenomenon occurs through purely physical binding energies. A Monte Carlo simulation model of a mixture of cells with different cell-cell and cell-substrate binding energies reveals that the spontaneous phase separation occurs due to the minimization of interfacial free energy within the system. Cell-cell and cell-substrate binding plays a critical role in cell organization and is capable of phase separating different populations of cells in vitro.

biophysics↗

bioRxiv2017

Quantifying cell adhesion dynamics using a custom-made fluid shear device: experiments and model

Changes in cell-substrate adhesion are believed to signal the onset of cancer metastasis, but such changes must be quantified against background levels of intrinsic heterogeneity between cells. Variations in cell-substrate adhesion strengths can be probed through biophysical measurements of cell detachment from substrates upon the application of an external force. Here, we investigate, theoretically and experimentally, the detachment of cells adhered to substrates when these cells are subjected to fluid shear. We present a theoretical framework within which we calculate the fraction of detached cells as a function of shear stress for fast ramps as well as for the decay in the fraction of detached cells at fixed shear stress as a function of time. Using HEK and 3T3 fibroblast cells as experimental model systems, we extract characteristic force scales for cell adhesion as well as characteristic detachment times. We estimate force-scales of ~ 500 pN associated to a single focal contact, and characteristic time-scales of 190 [≤]{tau} [≤] 350s representing cell-spread-area dependent mean first passage times to the detached state at intermediate values of the shear stress. Variations in adhesion across cell types are especially prominent when cell detachment is probed by applying a time-varying shear stress. These methods can be applied to characterizing changes in cell adhesion in a variety of contexts, including metastasis.

biophysics↗

bioRxiv2017

Kinetic Machine Learning Unravels Ligand-Directed Conformational Change of μ Opioid Receptor

The Opioid Receptor (OR) is a G-Protein Coupled Receptor (GPCR) that mediates pain and is a key target for clinically administered analgesics. The current generation of prescribed opiates - drugs that bind to OR - engender dangerous side effects such as respiratory depression and addiction in part by stabilizing off-target conformations of the receptor. To determine both the key conformations of OR to atomic resolution as well as the transitions between them, long timescale molecular dynamics (MD) simulations were conducted and analyzed. These simulations predict new and potentially druggable metastable states that have not been observed by crystallography. We applied cutting edge algorithms (e.g., tICA and Transfer Entropy) to guide our analysis and distill the key events and conformations from simulation, presenting a transferrable and systematic analysis scheme. Our approach provides a complete, predictive model of the dynamics, structure of states, and structure-ligand relationships of OR with broad applicability to GPCR biophysics and medicinal chemistry.

biophysics↗

bioRxiv2017

A structural and kinetic link between membrane association and amyloid fibril formation of α-Synuclein

The protein -Synuclein (S) is linked to Parkinsons disease through its abnormal aggregation, which is thought to involve an interplay between cytosolic and membrane-bound forms of S. Therefore, better insights into the molecular determinants of membrane association and their implications for protein aggregation may help deciphering the pathogenesis of Parkinsons disease. Following previous studies using micelles and vesicles, we present a comprehensive study of S interaction with phospholipid bilayer nanodiscs. Using a combination of NMR - spectroscopic and complementary biophysical as well as computational methods we structurally and kinetically characterize S interaction with defined stable planar membranes in a quantitative and site-resolved way. We probe the role of S acetylation as well as membrane charge, plasticity and available surface area in modulating S membrane binding modes and directly link these findings to their consequences for S amyloid fibril formation.

biophysics↗

bioRxiv2017

The lamellipodium is a myosin independent mechanosensor

The ability of adherent cells to sense changes in the mechanical properties of their extracellular environments is critical to numerous aspects of their physiology. It has been well documented that cell attachment and spreading are sensitive to substrate stiffness. Here we demonstrate that this behavior is actually biphasic, with a transition that occurs around a Youngs modulus of [~]7 kPa. Furthermore, we demonstrate that, contrary to established assumptions, this property is independent of myosin II activity. Rather, we find that cell spreading on soft substrates is inhibited due to reduced nascent adhesion formation within the lamellipodium. Cells on soft substrates display normal leading edge protrusion activity, but these protrusions are not stabilized due to impaired adhesion assembly. Enhancing integrin-ECM affinity through addition of Mn2+ recovers nascent adhesion assembly and cell spreading on soft substrates. Using a computational model to simulate nascent adhesion assembly, we find that biophysical properties of the integrin-ECM bond are optimized to stabilize interactions above a threshold matrix stiffness that is consistent with the experimentally observations. Together these results suggest that myosin II-independent forces in the lamellipodium are responsible for mechanosensation by regulating new adhesion assembly, which in turn, directly controls cell spreading. This myosin II-independent mechanism of substrate stiffness sensing could potentially regulate a number of other stiffness sensitive processes.\n\nSignificance StatementCell physiology can be regulated by the mechanics of the extracellular environment. Here, we demonstrate that cell spreading is a mechanosensitive process regulated by weak forces generated at the cell periphery and independent of motor activity. We show that stiffness sensing depends on the kinetics of the initial adhesion bonds that are subjected to forces driven by protein polymerization. This work demonstrates how the binding kinetics of adhesion molecules are sensitively tuned to a range of forces that enable mechanosensation.

biophysics↗

bioRxiv2017

In silico mechanobiochemical modeling of morphogenesis in cell monolayers

Cell morphogenesis is a fundamental process involved in tissue formation. One of the challenges in the fabrication of living tissues in vitro is to recapitulate the complex morphologies of individual cells. Despite tremendous progress in understanding biophysical principles underlying tissue/organ morphogenesis at the organ level, little work has been done to understand morphogenesis at the cellular and microtissue level. In this work, we developed a 2D computational model for studying cell morphogenesis in monolayer tissues. The model is mainly composed of four modules: mechanics of cytoskeleton, cell motility, cell-substrate interaction, and cell-cell interaction. The model integrates the biochemical and mechanical activities within individual cells spatiotemporally. Finite element method (FEM) is used to model the irregular shapes of cells and to solve the resulting system of reaction-diffusion-stress equations. Automated mesh generation is used to handle the element distortion in FEM due to the large shape changes of the cells. The computer program can simulate tens to hundreds of cells interacting with each other and with the elastic substrate on desktop workstations efficiently. The simulations demonstrated that our computational model can be used to study cell polarization, single cell migration, durotaxis, and morphogenesis in cell monolayers.

biophysics↗