PaperPlayer biorxiv biophysics

Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.10.25.354480v1?rss=1

Authors: KAIZUKA, Y., Machida, R.

Abstract:

The chemical control of cell-cell interactions using synthetic materials is useful for a wide range of biomedical applications. Herein, we report a method to regulate cell adhesion and dispersion by introducing repulsive forces to live cell membranes. To induce repulsion, we tethered amphiphilic polymers, such as cholesterol-modified polyethylene glycol (PEG-CLS) to cell membranes. These amphiphilic polymers both bind to and dissociate rapidly from membranes and thus, enable the reversible coating of cells by mixing and washout without requiring genetic manipulation or chemical synthesis in the cells. We found that the repulsive forces introduced by these tethered polymers can induce cell detachment from a substrate and allow cell dispersion in a suspension, modulate the speed of cell migration, and improve the separation of cells from tissues. Our analyses showed that coating the cells with tethered polymers most likely generated two distinct repulsive forces, lateral tension and steric repulsion, on the surface, which can be tuned by altering the polymer size and density. We also modeled how these two forces can be generated in kinetically distinctive manners to explain the various responses of cells to the coating. Collectively, our observations and analyses show how we can mechanochemically regulate cell adhesion and dispersion and may contribute to the optimization of chemical coating strategies for regulating various types of cell-cell interacting systems.

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.10.26.354928v1?rss=1

Authors: Marzen, S., Duran, A.

Abstract:

Potassium voltage-gated (Kv) channels need to detect and respond to rapidly changing ionic concentrations in their environment. With an essential role in regulating electric signaling, they would be expected to be optimal sensors that evolved to predict the ionic concentrations. To explore these assumptions, we use statistical mechanics in conjunction with information theory to model how animal Kv channels respond to changes in potassium concentrations in their environment. By estimating mutual information in representative Kv channel types across a variety of environments, we find two things. First, under a wide variety of environments, there is an optimal gating current that maximizes mutual information between the sensor and the environment. Second, as Kv channels evolved, they have moved towards decreasing mutual information with the environment. This either suggests that Kv channels do not need to act as sensors of their environment or that Kv channels have other functionalities that interfere with their role as sensors of their environment.

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.10.26.354878v1?rss=1

Authors: Rapin, G., Caballero, N., Gaponenko, I., Ziegler, B., Rawleight, A., Moriggi, E., Giamarchi, T., Brown, S. A., Paruch, P.

Abstract:

Juxtacellular interactions play an essential but still not fully understood role in both normal tissue development and tumour invasion. Using proliferating cell fronts as a model system, we explore the effects of cell-cell interactions on the geometry and dynamics of these one-dimensional biological interfaces. We observe two distinct scaling regimes of the steady state roughness of in-vitro propagating Rat1 fibroblast cell fronts, suggesting different hierarchies of interactions at sub-cell lengthscales and at a lengthscale of 2--10 cells. Pharmacological modulation significantly affects the proliferation speed of the cell fronts, and those modulators that promote cell mobility or division also lead to the most rapid evolution of cell front roughness. By comparing our experimental observations to numerical simulations of elastic cell fronts with purely short-range interactions, we demonstrate that the interactions at few-cell lengthscales play a key role. Our methodology provides a simple framework to measure and characterise the biological effects of such interactions, and could be useful in tumour phenotyping.

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.10.26.355974v1?rss=1

Authors: Beyerle, E. R., Dinpajooh, M., Ji, H., von Hippel, P. H., Marcus, A. H., Guenza, M. G.

Abstract:

Regulatory protein access to the DNA duplex 'interior' depends on local DNA 'breathing' fluctuations, and the most fundamental of these are thermally-driven base stacking-unstacking interactions. The smallest DNA unit that can undergo such transitions is the dinucleotide, whose structural and dynamic properties are dominated by stacking, while the ion condensation, cooperative stacking and inter-base hydrogen-bonding, present in duplex DNA are not involved. We use dApdA to study stacking-unstacking at the dinucleotide level because the fluctuations observed are likely to resemble those of larger DNA molecules, but in the absence of constraints introduced by cooperativity are likely to be more pronounced, and thus more accessible to measurement. We study these fluctuations with a combination of Molecular Dynamics simulations on the microsecond timescale and Markov State Model analyses, and validate our results by calculations of circular dichroism (CD) spectra, with results that agree well with experiments. Our analyses show that the CD spectrum of dApdA is defined by two distinct chiral conformations that correspond, respectively, to a Watson-Crick form and a hybrid form with one base in a Hoogsteen configuration. We find also that ionic structure and water orientation around dApdA play important roles in controlling its breathing fluctuations.

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.10.26.355164v1?rss=1

Authors: Speiser, A., Müller, L.-R., Matti, U., Obara, C. J., Legant, W. R., Kreshuk, A., Macke, J. H., Ries, J., Turaga, S. C.

Abstract:

Single-molecule localization microscopy (SMLM) has had remarkable success in imaging cellular structures with nanometer resolution, but the need for activating only single isolated emitters limits imaging speed and labeling density. Here, we overcome this major limitation using deep learning. We developed DECODE, a computational tool that can localize single emitters at high density in 3D with highest accuracy for a large range of imaging modalities and conditions. In a public software benchmark competition, it outperformed all other fitters on 12 out of 12 data-sets when comparing both detection accuracy and localization error, often by a substantial margin. DECODE allowed us to take live-cell SMLM data with reduced light exposure in just 3 seconds and to image microtubules at ultra-high labeling density. Packaged for simple installation and use, DECODE will enable many labs to reduce imaging times and increase localization density in SMLM.

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.10.25.353904v1?rss=1

Authors: Li, F., Park, T. H., Sankin, G., Gilchrist, C., Liao, D., Chan, C. U., Mao, Z., Hoffman, B. D., Zhong, P.

Abstract:

Ultrasound or shockwave-induced cavitation is used therapeutically to stimulate neural and muscle tissue, but the mechanisms underlying this mechanotransduction are unclear. Intracellular calcium signaling is one of the earliest events in mechanotransduction. In this study, we investigate the mechanism of calcium signaling in individual HEK293T cells stimulated by single cavitation bubbles. Calcium responses are rare at cell-bubble distance that avoids membrane poration, even with overexpression of the mechanosensitive ion channel Piezo1, but could be increased in frequency to 42% of cells by attaching RGD beads to the apical surface of the cells. By using Piezo1 knockout and Piezo1-expressing cells, integrin-blocking antibodies, and inhibitors of P2X ion channels, key molecular players are identified in the RGD bead-enhanced calcium response: increased integrin ligation by substrate ECM triggers ATP release and activation of P2X-but not Piezo1-ion channels. These molecular players have not been examined previously in cavitation-induced calcium signaling. The resultant calcium influx causes dynamic changes in cell spread area. This approach to eliciting a calcium response with cavitation microbubbles without cell injury, and the uncovered mechanotransduction mechanism by which increased integrin-ligation mediates ATP release and calcium signaling will inform new strategies to stimulate tissues with ultrasound and shockwaves.

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.10.23.353110v1?rss=1

Authors: Kinz-Thompson, C. D., Ray, K. K., Gonzalez, R. L.

Abstract:

Biophysics experiments performed at single-molecule resolution contain exceptional insight into the structural details and dynamic behavior of biological systems. However, extracting this information from the corresponding experimental data unequivocally requires applying a biophysical model. Here, we discuss how to use probability theory to apply these models to single-molecule data. Many current single-molecule data analysis methods apply parts of probability theory, sometimes unknowingly, and thus miss out on the full set of benefits provided by this self-consistent framework. The full application of probability theory involves a process called Bayesian inference that fully accounts for the uncertainties inherent to single-molecule experiments. Additionally, using Bayesian inference provides a scientifically rigorous manner to incorporate information from multiple experiments into a single analysis and to find the best biophysical model for an experiment without the risk of overfitting the data. These benefits make the Bayesian approach ideal for analyzing any type of single-molecule experiment.

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.10.24.353318v1?rss=1

Authors: Wieder, M., Fass, J., Chodera, J. D.

Abstract:

The computation of tautomer rations of druglike molecules is enormously important in computer-aided drug discovery, as over a quarter of all approved drugs can populate multiple tautomeric species in solution. Unfortunately, accurate calculations of aqueous tautomer ratios---the degree to which these species must be penalized in order to correctly account for tautomers in modeling binding for computer-aided drug discovery---is surprisingly difficult. While quantum chemical approaches to computing aqueous tautomer ratios using continuum solvent models and rigid-rotor harmonic-oscillator thermochemistry are currently state of the art, these methods are still surprisingly inaccurate despite their enormous computational expense. Here, we show that a major source of this inaccuracy lies in the breakdown of the standard approach to accounting for quantum chemical thermochemistry using rigid rotor harmonic oscillator (RRHO) approximations, which are frustrated by the complex conformational landscape introduced by the migration of double bonds, creation of stereocenters, and introduction of multiple conformations separated by low energetic barriers induced by migration of a single proton. Using quantum machine learning (QML) methods that allow us to compute potential energies with quantum chemical accuracy at a fraction of the cost, we show how rigorous alchemical free energy calculations can be used to compute tautomer ratios in vacuum free from the limitations introduced by RRHO approximations. Furthermore, since the parameters of QML methods are tunable, we show how we can train these models to correct limitations in the underlying learned quantum chemical potential energy surface using free energies, enabling these methods to learn to generalize tautomer free energies across a broader range of predictions.

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.10.23.352955v1?rss=1

Authors: Echave, J.

Abstract:

Studying the effect of perturbations on protein structure is a basic approach in protein research. Important problems, such as predicting pathological mutations and understanding patterns structural evolution, have been addressed by computational simulations based on modelling mutations as forces and predicting deformations using the Linear Response Approximation. In single mutation-response scanning simulations, a sensitivity matrix is obtained by averaging deformations over point mutations. In double mutation-response scanning simulations, a compensation matrix is obtained by minimizing deformations over pairs of mutations. These very useful simulation-based methods may be too slow to deal with large supra-molecular complexes, such as a ribosome or a virus capsid, or large number of proteins, such as the human proteome, which limits their applicability. To address this issue, I derived analytical closed formulas to calculate the sensitivity and compensation matrices directly, without simulations. Here, I present these derivations and show that the resulting analytical methods are much faster than their simulation counterparts, and that where the simulation methods are approximate, the analytical methods are exact by design.

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.10.25.352823v1?rss=1

Authors: McCall, P. M., Kim, K., Fritsch, A. W., Iglesias-Artola, J. M., Jawerth, L. M., Wang, J., Ruer, M., Peychl, J., Poznyakovskiy, A., Guck, J., Alberti, S., Hyman, A. A., Brugues, J.

Abstract:

Many compartments in eukaryotic cells are protein-rich biomolecular condensates demixed from the cyto- or nucleoplasm. Although much has been learned in recent years about the integral roles condensates play in many cellular processes as well as the biophysical properties of reconstituted condensates, an understanding of their most basic feature, their composition, remains elusive. Here we combined quantitative phase microscopy (QPM) and the physics of sessile droplets to develop a precise method to measure the shape and composition of individual model condensates. This technique does not rely on fluorescent dyes or tags, which we show can significantly alter protein phase behavior, and requires 1000-fold less material than traditional label-free technologies. We further show that this QPM method measures the protein concentration in condensates to a 3-fold higher precision than the next best label-free approach, and that commonly employed strategies based on fluorescence intensity dramatically underestimate these concentrations by as much as 50-fold. Interestingly, we find that condensed-phase protein concentrations can span a broad range, with PGL3, TAF15(RBD) and FUS condensates falling between 80 and 500 mg/ml under typical in vitro conditions. This points to a natural diversity in condensate composition specified by protein sequence. We were also able to measure temperature-dependent phase equilibria with QPM, an essential step towards relating phase behavior to the underlying physics and chemistry. Finally, time-resolved QPM reveals that PGL3 condensates undergo a contraction-like process during aging which leads to doubling of the internal protein concentration coupled to condensate shrinkage. We anticipate that this new approach will enable understanding the physical properties of biomolecular condensates and their function.

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