PaperPlayer biorxiv biophysics

Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.10.28.359059v1?rss=1

Authors: Zhang, Z., Voegele, J., Mrazikova, K., Kruse, H., Cang, X., Woehnert, J., Krepl, M., Sponer, J.

Abstract:

Phosphorothioates (PTs) are important chemical modifications of the RNA backbone where a single non-bridging oxygen of the phosphate is replaced with a sulphur atom. PT can stabilize RNAs by protecting them from hydrolysis and is commonly used as tool to explore their function. It is, however, unclear what basic physical effects PT has on RNA stability and electronic structure. Here, we present Molecular Dynamics (MD) simulations, quantum mechanical (QM) calculations, and NMR spectroscopy measurements, exploring the effects of PT modifications in the structural context of the Neomycin-sensing riboswitch (NSR). The NSR is the smallest biologically functional riboswitch with a well-defined structure stabilized by a U-turn motif. Three of the signature interactions of the U-turn; an H-bond, an anion-{pi} interaction and a potassium binding site; are formed by RNA phosphates, making the NSR an ideal model for studying how PT affects RNA dynamics, stability, and interaction with solvent. By comparing with high-level QM calculations, we reveal the distinct physical properties of the individual interactions facilitated by the PT. The sulphur force-field parameters commonly employed in the literature do not reflect these distinctions, leading to unsatisfactory description of PT in simulations of the NSR. We show that it is not possible to accurately describe the PT interactions using one universal set of van der Waals sulphur parameters and provide suggestions for improving the force-field performance.

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.10.27.357186v1?rss=1

Authors: Pesce, L., Laurino, A., Gavryusev, V., Mazzamuto, G., Sancataldo, G., Scardigli, M., Roffilli, M., Silvestri, L., Costantini, I., Pavone, F. S.

Abstract:

We still lack a detailed map of the anatomical disposition of neurons in the human brain. A complete map would be an important step for deeply understanding the brain function, providing anatomical information useful to decipher the neuronal pattern in healthy and diseased conditions. Here, we present several important advances towards this goal, obtained by combining a new clearing method, advanced Light Sheet Microscopy and automated machine-learning based image analysis. We perform volumetric imaging of large sequentially stained human brain slices, labelled for two different neuronal markers NeuN and GAD67, discriminating the inhibitory population and reconstructing the brain connectivity.

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.10.26.356329v1?rss=1

Authors: Brandão, H. B., Ren, Z., Karaboja, X., Mirny, L. A., Wang, X.

Abstract:

The spatial organization of chromosomes by structural maintenance of chromosomes (SMC) complexes is vital to organisms from bacteria to humans. SMC complexes were recently found to be motors that extrude DNA loops. It remains unclear, however, what happens when multiple SMC complexes encounter one another in vivo on the same DNA, how encounters are resolved, or how interactions help organize an active genome. Here, we set up a crash-course track system to study what happens when SMC complexes encounter one another. Using the parS/ParB system, which loads SMC complexes in a targeted manner, we engineered the Bacillus subtilis chromosome to have multiple SMC loading sites. Chromosome conformation capture (Hi-C) analyses of over 20 engineered strains show an amazing variety of never-before-seen chromosome folding patterns. Polymer simulations indicate these patterns require SMC complexes to traverse past each other in vivo, contrary to the common assumption that SMC complexes mutually block each others extrusion activity. Our quantitative model of bypassing predicted that increasing the numbers of SMCs on the chromosome could overwhelm the bypassing mechanism, create SMC traffic jams, and lead to major chromosome reorganization. We validated these predictions experimentally. We posit that SMC complexes traversing one another is part of a larger phenomenon of bypassing large steric barriers which enables these loop extruders to spatially organize a functional and busy genome.

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.10.27.352633v1?rss=1

Authors: Shah, Z. H., Müller, M., Wang, T.-C., Scheidig, P. M., Schneider, A., Schüttpelz, M., Huser, T., Schenck, W.

Abstract:

Super-resolution structured illumination microscopy (SR-SIM) pro- vides an up to two-fold enhanced spatial resolution of fluorescently labeled samples. The reconstruction of high quality SR-SIM images critically depends on patterned illumination with high modulation contrast. Noisy raw image data, e.g. as a result of low excitation power or low exposure times, result in reconstruction artifacts. Here, we demonstrate deep-learning based SR-SIM image denoising that results in high quality reconstructed images. A residual encoding-decoding convolution neural network (RED-Net) was used to successfully denoise computationally reconstructed noisy SR-SIM images. We also demonstrate the entirely deep-learning based denoising and reconstruction of raw SIM images into high-resolution SR-SIM images. Both image reconstruction methods prove to be very robust against image reconstruction artifacts and generalize very well over various noise levels. The combination of computational reconstruction and subsequent denoising via RED-Net shows very robust performance during inference after training even if the microscope settings change.

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.10.27.357178v1?rss=1

Authors: Isomursu, A., Park, K.-Y., Hou, J., Bo, C., Shamsan, G., Fuller, B., Kasim, J., Mahmoodi, M. M., Lu, T. J., Genin, G. M., Xu, F., Lin, M., Distefano, M., Ivaska, J., Odde, D. J.

Abstract:

Durotaxis - the ability of cells to sense and migrate along stiffness gradients - is important for embryonic development and has been implicated in pathologies including fibrosis and cancer. Although cellular processes can sometimes turn toward softer environments, durotaxis at the level of cells has thus far been observed exclusively as migration from soft to stiff regions. The molecular basis of durotaxis, especially the factors that contribute to different durotactic behaviors in various cell types, are still inadequately understood. With the recent discovery of 'optimal stiffness,' where cells generate maximal traction forces on substrates in an intermediate stiffness range, we hypothesized that some migratory cells may be capable of moving away from stiff environments and toward matrix on which they can generate more traction. Combining hydrogel-based stiffness gradients, live-cell imaging, genetic manipulations, and computational modeling, we found that cells move preferentially toward their stiffness optimum for maximal force transmission. Importantly, we directly observed biased migration toward softer environments, i.e. 'negative durotaxis,' in human glioblastoma cells. This directional migration did not coincide with changes in FAK, ERK or YAP signaling, or with altered actomyosin contractility. Instead, integrin-mediated adhesion and motor-clutch dynamics alone are sufficient to generate asymmetric traction to drive both positive and negative durotaxis. We verified this mechanistically by applying a motor-clutch-based model to explain negative durotaxis in the glioblastoma cells and in neurites, and experimentally by switching breast cancer cells from positive to negative durotaxis via talin downregulation. Our results identify the likely molecular mechanisms of durotaxis, with a cell's contractile and adhesive machinery dictating its capacity to exert traction on mechanically distinct substrates, directing cell migration.

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.10.27.357350v1?rss=1

Authors: Gorgun, D., Lihan, M., Kapoor, K., Tajkhorshid, E.

Abstract:

Infection of human cells by the SARS-CoV2 relies on its binding to a specific receptor and subsequent fusion of the viral and host cell membranes. The fusion peptide (FP), a short peptide segment in the spike protein, plays a central role in the initial penetration of the virus into the host cell membrane, followed by the fusion of the two membranes. Here, we use an array of molecular dynamics (MD) simulations taking advantage of the Highly Mobile Membrane Mimetic (HMMM) model, to investigate the interaction of the SARS-CoV2 FP with a lipid bilayer representing mammalian cellular membranes at an atomic level, and to characterize the membrane-bound form of the peptide. Six independent systems were generated by changing the initial positioning and orientation of the FP with respect to the membrane, and each system was simulated in five independent replicas. In 60% of the simulations, the FP reaches a stable, membrane-bound configuration where the peptide deeply penetrated into the membrane. Clustering of the results reveals two major membrane binding modes, the helix-binding mode and the loop-binding mode. Taken into account the sequence conservation among the viral FPs and the results of mutagenesis studies establishing the role of specific residues in the helical portion of the FP in membrane association, we propose that the helix-binding mode represents more closely the biologically relevant form. In the helix-binding mode, the helix is stabilized in an oblique angle with respect to the membrane with its N-terminus tilted towards the membrane core. Analysis of the FP-lipid interactions shows the involvement of specific residues of the helix in membrane binding previously described as the fusion active core residues. Taken together, the results shed light on a key step involved in SARS-CoV2 infection with potential implications in designing novel inhibitors.

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.10.26.355891v1?rss=1

Authors: Mohammed, D., Chan, P. Y., Fredberg, J. J., Weitz, D. A.

Abstract:

The migration of tumorigenic epithelial cells is a critical step for metastatic breast cancer progression. Although the role of the extracellular matrix in breast cancer cell migration has been extensively described, the effect of osmotic stress on the migration of tumor breast epithelial cohorts remains unclear. Most of our understanding on the effect of osmotic stresses on cell migration comes from studies at the level of the single cell in isolation and does not take into account cell-cell interactions. Here, we study the impact of moderate osmotic stress on the migration of epithelial clusters composed of either non-tumorigenic or tumorigenic epithelial cells. We observe a decrease in migration distance and speed for non-tumorigenic epithelial cells but not for tumorigenic ones. To explain these differences, we investigate how osmotic stress impacts the mechanical properties of cell clusters and affects cell volumes. After application of osmotic stress renal epithelial cells become stiffer whereas non-tumorigenic and tumorigenic breast epithelial cells do not. In addition, tumorigenic cells are shown to be less sensitive to osmotic stress than non-tumorigenic cells, and this difference is associated with lower levels of E-cadherin expression. Using EGTA treatments, we confirm that the establishment of cell-cell adhesive interactions is a key component of the behavior of epithelial clusters in response to osmotic stress. This study provides evidence on the low sensitivity of tumorigenic epithelial clusters to moderate osmotic stress and highlights the importance of cadherin-based junctions in response to osmotic stress.

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.10.26.354753v1?rss=1

Authors: Saar, K. L., Morgunov, A. S., Qi, R., Arter, W. E., Krainer, G., Lee, A. A., Knowles, T.

Abstract:

Intracellular phase separation of proteins into biomolecular condensates is increasingly recognised as an important phenomenon for cellular compartmentalisation and regulation of biological function. Different hypotheses about the parameters that determine the tendency of proteins to form condensates have been proposed with some of them probed experimentally through the use of constructs generated by sequence alterations. To broaden the scope of these observations, here, we established an in silico strategy for understanding on a global level the associations between protein sequence and condensate formation, and used this information to construct machine learning classifiers for predicting liquid-liquid phase separation (LLPS) from protein sequence. Our analysis highlighted that LLPS-prone sequences are more disordered, hydrophobic and of lower Shannon entropy than sequences in the Protein Data Bank or the Swiss-Prot database, and have their disordered regions enriched in polar, aromatic and charged residues. Using these determining features together with neural network based word2vec sequence embeddings, we developed machine learning classifiers for predicting protein condensate formation. Our model, trained to distinguish LLPS-prone sequences from structured proteins, achieved high accuracy (93%; 25-fold cross-validation) and identified condensate forming sequences from external independent test data at 97% sensitivity. Moreover, in combination with a classifier that had developed a nuanced insight into the features governing protein phase behaviour by learning to distinguish between sequences of varying LLPS propensity, the sensitivity was supplemented with high specificity (approximated ROC-AUC of 0.85). These results provide a platform rooted in molecular principles for understanding protein phase behaviour. The predictor is accessible from https://deephase.ch.cam.ac.uk/ .

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.10.25.354381v1?rss=1

Authors: Honda, S., Minagawa, Y., Noji, H., Tabata, K. V.

Abstract:

Single-molecule experiments have been helping us to get deeper inside biological phenomena by illuminating how individual molecules actually work. Digital bioassay, in which analyte molecules are individually confined in small compartments to be analyzed, is an emerging technology in single-molecule biology and applies to various biological entities (e.g., cells and virus particles). However, digital bioassay is not compatible with multi-conditional or multi-parametric assays, hindering understanding of analytes. This is because current digital bioassay lacks a repeatable solution-exchange system that keeps analytes inside compartments. To address this challenge, we developed a new digital bioassay platform with easy solution exchanges, called multi-dimensional (MD) digital bioassay, and tested its quantitativity and utility. We immobilized single analytes in arrayed femtoliter (10-15 L) reactors and sealed them with airflow. The solution in each reactor was stable and showed no cross-talk via solution leakage for more than 2 h, and over 30 rounds of perfect solution exchanges were successfully performed. To show the utility of our system, we investigated neuraminidase inhibitor (NAI) sensitivity on single influenza A virus (IAV) particles in a multi-conditional assay. We proved that IAV particles show a heterogeneous response to the NAI. Further, to demonstrate multi-parametric assays, we examined the sensitivity of individual IAV particles or model enzyme molecules to two different inhibitors. Our results support that MD digital bioassay is a versatile platform to unveil heterogeneities of biological entities in unprecedented resolution.

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.10.26.354233v1?rss=1

Authors: Bravo, J. P. K., Bartnik, K., Venditti, L., Gail, E. H., Davidovich, C., Lamb, D. C., Tuma, R., Calabrese, A. N., Borodavka, A.

Abstract:

Rotavirus genomes are distributed between 11 distinct RNA segments, all of which are essential for virus replication. Stoichiometric genome segment selection and assembly is achieved through a series of sequence-specific, intersegment RNA-RNA interactions that are facilitated by the rotavirus RNA chaperone protein NSP2. The C-terminal region (CTR) of NSP2 has been proposed to play a role in rotavirus replication, although its mechanistic contribution to the RNA chaperone activity of NSP2 remained unknown. Here, we use single-molecule fluorescence assays to directly demonstrate that the CTR is required for promoting RNA-RNA interactions and that it limits the RNA unwinding activity of NSP2. Unexpectedly, hydrogen-deuterium exchange-mass spectrometry and UV-crosslinking data indicate that the CTR does not interact with RNA. However, removal of the CTR reduced the RNA release activity of NSP2, suggesting that the CTR is important for chaperone recycling. To further interrogate the role of the CTR, we determined cryo-EM structures of NSP2 and its ribonucleoprotein complexes. These reveal that although the CTR is ampholytic in nature, it harbours a highly conserved acidic patch that is poised towards bound RNA. Using a reverse genetics approach, we demonstrate that rotavirus mutants harbouring triple alanine mutations within the acidic patch failed to replicate, while mutations that preserve the charge of the CTR successfully restored viral replication. Together, our data suggest that the CTR reduces the accumulation of kinetically trapped NSP2-RNA complexes by accelerating RNA dissociation via charge repulsion, thus promoting efficient intermolecular RNA-RNA interactions during segment assembly.

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