Showing papers in "Biophysical Journal in 2022"

The roles of glycans in the SARS-CoV-2 spike protein

Abstract: The SARS-CoV-2 spike is a homotrimeric class I fusion protein covered in a sugar cloak made of 22 N-linked and at least 2 O-linked glycans per protomer. This sophisticated machinery is used by SARS-CoV-2 to infect human cells upon latching onto a specific molecular target, the angiotensin-converting enzyme 2 (ACE2). The deposition of the first cryo-EM structure of the SARS-CoV-2 spike protein in mid-February 2020 marked the beginning of our endeavor to fight COVID-19 using high-performance computing (HPC). In this contribution, I will present how we deployed in-silico modeling and all-atom molecular dynamics simulations to examine the roles of the SARS-CoV-2 spike's glycans in the context of viral infection. Our study revealed the look of the glycan shield in the microsecond timescales, showing different vulnerabilities according to the spike’s state and topological domain. Beyond shielding, we found three N-linked glycans at positions N165, N234, and N343 that are utilized by the spike as functional devices to transition to an attacking mode and infect the host cell. Overall, our simulations significantly advanced the understanding of the (many) roles of the SARS-CoV-2 spike’s glycan shield that go beyond camouflaging antigenic regions. Our work allowed thousands of scientists from all over the world to delve more into the intricacies of the fully glycosylated spike and to use our simulations (and those of others) for vaccine design and drug development purposes. The SARS-CoV-2 spike is a homotrimeric class I fusion protein covered in a sugar cloak made of 22 N-linked and at least 2 O-linked glycans per protomer. This sophisticated machinery is used by SARS-CoV-2 to infect human cells upon latching onto a specific molecular target, the angiotensin-converting enzyme 2 (ACE2). The deposition of the first cryo-EM structure of the SARS-CoV-2 spike protein in mid-February 2020 marked the beginning of our endeavor to fight COVID-19 using high-performance computing (HPC). In this contribution, I will present how we deployed in-silico modeling and all-atom molecular dynamics simulations to examine the roles of the SARS-CoV-2 spike's glycans in the context of viral infection. Our study revealed the look of the glycan shield in the microsecond timescales, showing different vulnerabilities according to the spike’s state and topological domain. Beyond shielding, we found three N-linked glycans at positions N165, N234, and N343 that are utilized by the spike as functional devices to transition to an attacking mode and infect the host cell. Overall, our simulations significantly advanced the understanding of the (many) roles of the SARS-CoV-2 spike’s glycan shield that go beyond camouflaging antigenic regions. Our work allowed thousands of scientists from all over the world to delve more into the intricacies of the fully glycosylated spike and to use our simulations (and those of others) for vaccine design and drug development purposes.

Assembly of model postsynaptic densities involves interactions auxiliary to stoichiometric binding

Abstract: The assembly of functional biomolecular condensates often involves liquid-liquid phase separation (LLPS) of proteins with multiple modular domains, which can be folded or conformationally disordered to various degrees. To understand the LLPS-driving domain-domain interactions, a fundamental question is how readily the interactions in the condensed phase can be inferred from interdomain interactions in dilute solutions. In particular, are the interactions leading to LLPS exclusively those underlying the formation of discrete interdomain complexes in homogeneous solutions? We address this question by developing a mean-field LLPS theory of two stoichiometrically constrained solute species. The theory is applied to the neuronal proteins SynGAP and PSD-95, whose complex coacervate serves as a rudimentary model for neuronal postsynaptic densities (PSDs). The predicted phase behaviors are compared with experiments. Previously, a three SynGAP/two PSD-95 ratio was determined for SynGAP/PSD-95 complexes in dilute solutions. However, when this 3:2 stoichiometry is uniformly imposed in our theory encompassing both dilute and condensed phases, the tie-line pattern of the predicted SynGAP/PSD-95 phase diagram differs drastically from that obtained experimentally. In contrast, theories embodying alternate scenarios postulating auxiliary SynGAP-PSD-95 as well as SynGAP-SynGAP and PSD-95-PSD-95 interactions, in addition to those responsible for stoichiometric SynGAP/PSD-95 complexes, produce tie-line patterns consistent with experiment. Hence, our combined theoretical-experimental analysis indicates that weaker interactions or higher-order complexes beyond the 3:2 stoichiometry, but not yet documented, are involved in the formation of SynGAP/PSD-95 condensates, imploring future efforts to ascertain the nature of these auxiliary interactions in PSD-like LLPS and underscoring a likely general synergy between stoichiometric, structurally specific binding and stochastic, multivalent “fuzzy” interactions in the assembly of functional biomolecular condensates.

Modeling bursty transcription and splicing with the chemical master equation.

Abstract: Splicing cascades that alter gene products posttranscriptionally also affect expression dynamics. We study a class of processes and associated distributions that emerge from models of bursty promoters coupled to directed acyclic graphs of splicing. These solutions provide full time-dependent joint distributions for an arbitrary number of species with general noise behaviors and transient phenomena, offering qualitative and quantitative insights about how splicing can regulate expression dynamics. Finally, we derive a set of quantitative constraints on the minimum complexity necessary to reproduce gene coexpression patterns using synchronized burst models. We validate these findings by analyzing long-read sequencing data, where we find evidence of expression patterns largely consistent with these constraints.

A vesicle microrheometer for high-throughput viscosity measurements of lipid and polymer membranes

Abstract: Viscosity is a key property of cell membranes that controls mobility of embedded proteins and membrane remodeling. Measuring it is challenging because existing approaches involve complex experimental designs and/or models, and the applicability of some is limited to specific systems and membrane compositions. As a result there is scarcity of data and the reported values for membrane viscosity vary by orders of magnitude for the same system. Here, we show how viscosity of bilayer membranes can be obtained from the transient deformation of giant unilamellar vesicles. The approach enables a non-invasive, probe-independent and high-throughput measurement of the viscosity of bilayers made of lipids or polymers with a wide range of compositions and phase state. Pure lipid and single-phase mixed bilayers are found to behave as Newtonian fluids with strain-rate independent viscosity, while phase-separated and diblock-copolymers systems exhibit shear-thinning in the explored range of strain rates 1-2000 $s^{-1}$. The results also reveal that electrically polarized bilayers can be significantly more viscous than charge-neutral bilayers. These findings suggest that biomembrane viscosity is a dynamic property that can be actively modulated not only by composition but also by membrane polarization, e.g., as in action potentials.

SARS-CoV-2 spike binding to ACE2 is stronger and longer ranged due to glycan interaction

Abstract: Highly detailed steered molecular dynamics simulations are performed on differently glycosylated receptor binding domains of the severe acute respiratory syndrome coronavirus-2 spike protein. The binding strength and the binding range increase with glycosylation. The interaction energy rises very quickly when pulling the proteins apart and only slowly drops at larger distances. We see a catch-slip-type behavior whereby interactions during pulling break and are taken over by new interactions forming. The dominant interaction mode is hydrogen bonds, but Lennard-Jones and electrostatic interactions are relevant as well.

RNA at the surface of phase-separated condensates impacts their size and number

Abstract: Although it is now recognized that specific RNAs and protein families are critical for the biogenesis of ribonucleoprotein (RNP) condensates, how these molecular constituents determine condensate size and morphology is unknown. To circumvent the biochemical complexity of endogenous RNP condensates, the use of programmable tools to reconstitute condensate formation with minimal constituents can be instrumental. Here we report a methodology to form RNA-containing condensates in living cells programmed to specifically recruit a single RNA species. Our bioengineered condensates are made of ArtiGranule scaffolds composed of an orthogonal protein that can bind to a specific heterologously expressed RNA. These scaffolds undergo liquid-liquid phase separation in cells and can be chemically controlled to prevent condensation or to trigger condensate dissolution. We found that the targeted RNAs localize at the condensate surface, either as isolated RNA molecules or as a homogenous corona of RNA molecules around the condensate. The recruitment of RNA changes the material properties of condensates by hardening the condensate body. Moreover, the condensate size scales with RNA surface density; the higher the RNA density is, the smaller and more frequent the condensates are. These results suggest a mechanism based on physical constraints, provided by RNAs at the condensate surface, that limit condensate growth and coalescence.

Comparative Molecular Dynamics Simulation Studies of Realistic Eukaryotic, Prokaryotic, and Archaeal Membranes

Abstract: The OPM (Orientation of Proteins in Membranes) database currently holds, classifies, and annotates around 14,000 three-dimensional structures of transmembrane and peripheral membrane proteins and peptides positioned with respect to membrane boundaries. Developing uniform templates of biological membranes with realistic native-like lipid composition would provide a convenient and accurate platform for researchers who simulate membrane-associated proteins and peptides in natural environments. In this study, for the first time, we performed the standardized molecular dynamic simulations and comparative analysis of structures and properties of 18 native-like membrane models.

The substrate import mechanism of the human serotonin transporter

Abstract: The serotonin transporter (SERT) initiates the reuptake of extracellular serotonin in the synapse to terminate neurotransmission. The cryogenic electron microscopy structures of SERT bound to ibogaine and the physiological substrate serotonin resolved in different states have provided a glimpse of the functional conformations at atomistic resolution. However, the conformational dynamics and structural transitions to intermediate states are not fully understood. Furthermore, the molecular basis of how serotonin is recognized and transported remains unclear. In this study, we performed unbiased microsecond-long simulations of the human SERT to investigate the structural dynamics to various intermediate states and elucidated the complete substrate import pathway. Using Markov state models, we characterized a sequential order of conformational-driven ion-coupled substrate binding and transport events and calculated the free energy barriers of conformation transitions associated with the import mechanism. We find that the transition from the occluded to inward-facing state is the rate-limiting step for substrate import and that the substrate decreases the free energy barriers to achieve the inward-facing state. Our study provides insights on the molecular basis of dynamics-driven ion-substrate recognition and transport of SERT that can serve as a model for other closely related neurotransmitter transporters.

Following the tracks: How transcription factor binding dynamics control transcription

Abstract: Transcription, the process of copying genetic information from DNA to messenger RNA, is regulated by sequence-specific DNA-binding proteins known as transcription factors (TFs). Recent advances in single-molecule tracking (SMT) technologies have enabled visualization of individual TF molecules as they diffuse and interact with the DNA in the context of living cells. These SMT studies have uncovered multiple populations of DNA-binding events characterized by their distinctive DNA residence times. In this perspective, we review recent insights into how these residence times relate to specific and non-specific DNA binding, as well as the contribution of TF domains on the DNA-binding dynamics. We discuss different models that aim to link transient DNA binding by TFs to bursts of transcription and present an outlook for how future advances in microscopy development may broaden our understanding of the dynamics of the molecular steps that underlie transcription activation.

Dedifferentiation alters chondrocyte nuclear mechanics during in vitro culture and expansion

Abstract: The biophysical features of a cell can provide global insights into diverse molecular changes, especially in processes like the dedifferentiation of chondrocytes. Key biophysical markers of chondrocyte dedifferentiation include flattened cellular morphology and increased stress-fiber formation. During cartilage regeneration procedures, dedifferentiation of chondrocytes during in vitro expansion presents a critical limitation to the successful repair of cartilage tissue. Our study investigates how biophysical changes of chondrocytes during dedifferentiation influence the nuclear mechanics and gene expression of structural proteins located at the nuclear envelope. Through an experimental model of cell stretching and a detailed spatial intranuclear strain quantification, we identified that strain is amplified and the distribution of strain within the chromatin is altered under tensile loading in the dedifferentiated state. Further, using a confocal microscopy image-based finite element model and simulation of cell stretching, we found that the cell shape is the primary determinant of the strain amplification inside the chondrocyte nucleus in the dedifferentiated state. Additionally, we found that nuclear envelope proteins have lower gene expression in the dedifferentiated state. This study highlights the role of cell shape in nuclear mechanics and lays the groundwork to design biophysical strategies for the maintenance and enhancement of the chondrocyte phenotype during cell expansion with a goal of successful cartilage tissue engineering.

Distribution of cholesterol in asymmetric membranes driven by composition and differential stress

Abstract: Many lipid membranes of eukaryotic cells are asymmetric, which means the two leaflets differ in at least one physical property, such as lipid composition or lateral stress. Maintaining this asymmetry is helped by the fact that ordinary phospholipids rarely transition between leaflets, but cholesterol is an exception: its flip-flop times are in the microsecond range, so that its distribution between leaflets is determined by a chemical equilibrium. In particular, preferential partitioning can draw cholesterol into a more saturated leaflet, and phospholipid number asymmetry can force it out of a compressed leaflet. Combining highly coarse-grained membrane simulations with theoretical modeling, we investigate how these two driving forces play against each other until cholesterol’s chemical potential is equilibrated. The theory includes two coupled elastic sheets and a Flory-Huggins mixing free energy with a χ parameter. We obtain a relationship between χ and the interaction strength between cholesterol and lipids in either of the two leaflets, and we find that it depends, albeit weakly, on lipid number asymmetry. The differential stress measurements under various asymmetry conditions agree with our theoretical predictions. Using the two kinds of asymmetries in combination, we find that it is possible to counteract the phospholipid number bias, and the resultant stress in the membrane, via the control of cholesterol mixing in the leaflets.

Myofibril orientation as a metric for characterizing heart disease

Abstract: Myocyte disarray is a hallmark of many cardiac disorders. However, the relationship between alterations in the orientation of individual myofibrils and myofilaments to disease progression has been largely underexplored. This oversight has predominantly been because of a paucity of methods for objective and quantitative analysis. Here, we introduce a novel, less-biased approach to quantify myofibrillar and myofilament orientation in cardiac muscle under near-physiological conditions and demonstrate its superiority as compared with conventional histological assessments. Using small-angle x-ray diffraction, we first investigated changes in myofibrillar orientation at increasing sarcomere lengths in permeabilized, relaxed, wild-type mouse myocardium from the left ventricle by assessing the angular spread of the 1,0 equatorial reflection (angle σ). At a sarcomere length of 1.9 μm, the angle σ was 0.23 ± 0.01 rad, decreased to 0.19 ± 0.01 rad at a sarcomere length of 2.1 μm, and further decreased to 0.15 ± 0.01 rad at a sarcomere length of 2.3 μm (p < 0.0001). Angle σ was significantly larger in R403Q, a MYH7 hypertrophic cardiomyopathy model, porcine myocardium (0.24 ± 0.01 rad) compared with wild-type myocardium (0.14 ± 0.005 rad; p < 0.0001), as well as in human heart failure tissue (0.19 ± 0.006 rad) when compared with nonfailing samples (0.17 ± 0.007 rad; p = 0.01). These data indicate that diseased myocardium suffers from greater myofibrillar disorientation compared with healthy controls. Finally, we showed that conventional, histology-based analysis of disarray can be subject to user bias and/or sampling error and lead to false positives. Our method for directly assessing myofibrillar orientation avoids the artifacts introduced by conventional histological approaches that assess myocyte orientation and only indirectly evaluate myofibrillar orientation, and provides a precise and objective metric for phenotypically characterizing myocardium. The ability to obtain excellent x-ray diffraction patterns from frozen human myocardium provides a new tool for investigating structural anomalies associated with cardiac diseases.

The physics of liquid-to-solid transitions in multi-domain protein condensates

Abstract: Many RNA-binding proteins (RBPs) that assemble into membraneless organelles have a common architecture including disordered prion-like domain (PLD) and folded RNA-binding domain (RBD). An enrichment of PLD within the condensed phase gives rise to formation, on longer time scales, of amyloid-like fibrils (aging). In this study, we employ coarse-grained Langevin dynamics simulations to explore the physical basis for the structural diversity in condensed phases of multi-domain RBPs. We discovered a highly cooperative first-order transition between disordered structures and an ordered phase whereby chains of PLD organize in fibrils with high nematic orientational order. An interplay between homodomain (PLD-PLD) and heterodomain (PLD-RBD) interactions results in variety of structures with distinct spatial architectures. Interestingly, the different structural phases also exhibit vastly different intracluster dynamics of proteins, with diffusion coefficients 5 times (disordered structures) to 50 times (ordered structures) lower than that of the dilute phase. Cooperativity of this liquid-solid transition makes fibril formation highly malleable to mutations or post-translational modifications. Our results provide a mechanistic understanding of how multi-domain RBPs could form assemblies with distinct structural and material properties.

Influence of the extracellular domain size on the dynamic behavior of membrane proteins

Abstract: The dynamic behavior of plasma membrane proteins mediates various cellular processes such as cellular motility, communication, and signaling. It is widely accepted that the dynamics of the membrane proteins is determined either by the interactions of the transmembrane domain with the surrounding lipids or by the interactions of the intracellular domain with cytosolic components such as cortical actin. Although initiation of different cellular signaling events at the plasma membrane has been attributed to the extracellular domain (ECD) properties recently, the impact of ECDs on the dynamic behavior of membrane proteins is rather unexplored. Here, we investigate how ECD properties influence protein dynamics in the lipid bilayer by reconstituting ECDs of different sizes or glycosylation in model membrane systems and analyzing ECD-driven protein sorting in lipid domains as well as protein mobility. Our data show that increasing the ECD mass or glycosylation leads to a decrease in ordered domain partitioning and diffusivity. Our data reconcile different mechanisms proposed for the initiation of cellular signaling by linking the ECD size of membrane proteins with their localization and diffusion dynamics in the plasma membrane.

DeepTracer-ID: De novo protein identification from cryo-EM maps

Abstract: The recent revolution in cryo-electron microscopy (cryo-EM) has made it possible to determine macromolecular structures directly from cell extracts. However, identifying the correct protein from the cryo-EM map is still challenging and often needs additional sequence information from other techniques, such as tandem mass spectrometry and/or bioinformatics. Here, we present DeepTracer-ID, a server-based approach to identify the candidate protein in a user-provided organism de novo from a cryo-EM map, without the need for additional information. Our method first uses DeepTracer to generate a protein backbone model that best represents the cryo-EM map, and this model is then searched against the library of AlphaFold2 predictions for all proteins in the given organism. This method is highly accurate and robust for high-resolution cryo-EM maps: in all 13 experimental maps tested blindly, DeepTracer-ID identified the correct proteins as the top candidates. Eight of the maps were of known structures, while the other five unpublished maps were validated by prior protein annotation and careful inspection of the model refined into the map. The program also showed promising results for both homomeric and heteromeric protein complexes. This platform is possible because of the recent breakthroughs in large-scale three-dimensional protein structure prediction.

ATP:Mg2+ shapes material properties of protein-RNA condensates and its partitioning of clients.

Abstract: Many cellular condensates are heterotypic mixtures of proteins and RNA formed in complex environments. Magnesium ions (Mg2+) and ATP can impact RNA folding, and local intracellular levels of these factors can vary significantly. However, the effect of ATP:Mg2+ on the material properties of protein-RNA condensates is largely unknown. Here, we use an in vitro condensate model of nucleoli, made from nucleophosmin 1 (NPM1) proteins and ribosomal RNA (rRNA), to study the effect of ATP:Mg2+. While NPM1 dynamics remain unchanged at increasing Mg2+ concentrations, the internal RNA dynamics dramatically slowed until a critical point, where gel-like states appeared, suggesting the RNA component alone forms a viscoelastic network that undergoes maturation driven by weak multivalent interactions. ATP reverses this arrest and liquefies the gel-like structures. ATP:Mg2+ also influenced the NPM1-rRNA composition of condensates and enhanced the partitioning of two clients: an arginine-rich peptide and a small nuclear RNA. By contrast, larger ribosome partitioning shows dependence on ATP:Mg2+ and can become reversibly trapped around NPM1-rRNA condensates. Lastly, we show that dissipative enzymatic reactions that deplete ATP can be used to control the shape, composition, and function of condensates. Our results illustrate how intracellular environments may regulate the state and client partitioning of RNA-containing condensates.

Red blood cell shape transitions and dynamics in time-dependent capillary flows

Abstract: The dynamics of single red blood cells (RBCs) determine microvascular blood flow by adapting their shape to the flow conditions in the narrow vessels. In this study, we explore the dynamics and shape transitions of RBCs on the cellular scale under confined and unsteady flow conditions using a combination of microfluidic experiments and numerical simulations. Tracking RBCs in a comoving frame in time-dependent flows reveals that the mean transition time from the symmetric croissant to the off-centered, non-symmetric slipper shape is significantly faster than the opposite shape transition, which exhibits pronounced cell rotations. Complementary simulations indicate that these dynamics depend on the orientation of the RBC membrane in the channel during the time-dependent flow. Moreover, we show how the tank-treading movement of slipper-shaped RBCs in combination with the narrow channel leads to oscillations of the cell's center of mass. The frequency of these oscillations depends on the cell velocity, the viscosity of the surrounding fluid, and the cytosol viscosity. These results provide a potential framework to identify and study pathological changes of RBC properties.

On the stability and layered organization of protein-DNA condensates.

Abstract: Multi-component phase separation is emerging as a key mechanism for the formation of biological condensates that play essential roles in signal sensing and transcriptional regulation. The molecular factors that dictate these condensates' stability and spatial organization are not fully understood, and it remains challenging to predict their microstructures. Using a near-atomistic, chemically accurate force field, we studied the phase behavior of chromatin regulators that are crucial for heterochromatin organization and their interactions with DNA. Our computed phase diagrams recapitulated previous experimental findings on different proteins. They revealed a strong dependence of condensate stability on the protein-DNA mixing ratio as a result of balancing protein-protein interactions and charge neutralization. Notably, a layered organization was observed in condensates formed by mixing HP1, histone H1, and DNA. This layered organization may be of biological relevance, as it enables cooperative DNA packaging between the two chromatin regulators: histone H1 softens the DNA to facilitate the compaction induced by HP1 droplets. Our study supports near-atomistic models as a valuable tool for characterizing the structure and stability of biological condensates.

Active chemo-mechanical feedbacks dictate the collective migration of cells on patterned surfaces.

Abstract: Recent evidence has demonstrated that, when cultured on micro-patterned surfaces, living cells can move in a coordinated manner and form distinct migration patterns, including flowing chain, suspended propagating bridge, rotating vortex, etc. However, the fundamental question of exactly how and why cells migrate in these fashions remains elusive. Here, we present a theoretical investigation to show that the tight interplay between internal cellular activities, such as chemo-mechanical feedbacks and polarization, and external geometrical constraints are behind these intriguing experimental observations. In particular, on narrow strip patterns, strongly force-dependent cellular contractility and intercellular adhesion were found to be critical for reinforcing the leading edge of the migrating cell monolayer and eventually result in the formation of suspended cell bridges flying over nonadhesive regions. On the other hand, a weak force-contractility feedback led to the movement of cells like a flowing chain along the adhesive strip. Finally, we also showed that the random polarity forces generated in migrating cells are responsible for driving them into rotating vortices on strips with width above a threshold value (~10 times the size of the cell).

Fast, accurate antibody structure prediction from deep learning on massive set of natural antibodies

Abstract: Antibodies have the capacity to bind a diverse set of antigens and have become critical therapeutics and diagnostic molecules. The binding of antibodies is facilitated by a set of six hypervariable loops that are diversified through genetic recombination and mutation. Accurate structural modeling of these loops is critical for rational design of antibodies, but remains an expensive, time-consuming endeavor using traditional experimental methods. Even with recent advances, accurate computational prediction of these hypervariable loops remains a challenge.

Modeling insights into SARS-CoV-2 respiratory tract infections prior to immune protection

Abstract: Mechanistic insights into human respiratory tract (RT) infections from SARS-CoV-2 can inform public awareness as well as guide medical prevention and treatment for COVID-19 disease. Yet the complexity of the RT and the inability to access diverse regions pose fundamental roadblocks to evaluation of potential mechanisms for the onset and progression of infection (and transmission). We present a model that incorporates detailed RT anatomy and physiology, including airway geometry, physical dimensions, thicknesses of airway surface liquids (ASLs), and mucus layer transport by cilia. The model further incorporates SARS-CoV-2 diffusivity in ASLs and best-known data for epithelial cell infection probabilities, and, once infected, duration of eclipse and replication phases, and replication rate of infectious virions. We apply this baseline model in the absence of immune protection to explore immediate, short-term outcomes from novel SARS-CoV-2 depositions onto the air-ASL interface. For each RT location, we compute probability to clear versus infect; per infected cell, we compute dynamics of viral load and cell infection. Results reveal that nasal infections are highly likely within 1–2 days from minimal exposure, and alveolar pneumonia occurs only if infectious virions are deposited directly into alveolar ducts and sacs, not via retrograde propagation to the deep lung. Furthermore, to infect just 1% of the 140 m2 of alveolar surface area within 1 week, either 103 boluses each with 106 infectious virions or 106 aerosols with one infectious virion, all physically separated, must be directly deposited. These results strongly suggest that COVID-19 disease occurs in stages: a nasal/upper RT infection, followed by self-transmission of infection to the deep lung. Two mechanisms of self-transmission are persistent aspiration of infected nasal boluses that drain to the deep lung and repeated rupture of nasal aerosols from infected mucosal membranes by speaking, singing, or cheering that are partially inhaled, exhaled, and re-inhaled, to the deep lung.

Membrane ruffling is a mechanosensor of extracellular fluid viscosity

Abstract: Throughout the body, cells are immersed in extracellular fluids (ECFs) that are typically orders of magnitude more viscous than water or culture medium. Changes in the viscosity of biological fluids are associated with physiological processes and diseases ranging from wound healing to cystic fibrosis to cancer. However, unlike the material properties of the extracellular matrix, the role of ECF viscosity has not been thoroughly studied. Here we characterize the cellular response to viscosity, which causes dramatic increases in cell area, traction force generation, and cell speed, and present a mechanism by which membrane ruffling acts as a mechanosensor of ECF viscosity.

rsRNASP: A residue-separation-based statistical potential for RNA 3D structure evaluation

Abstract: Knowledge-based statistical potentials have been shown to be rather effective in protein 3-dimensional (3D) structure evaluation and prediction. Recently, several statistical potentials have been developed for RNA 3D structure evaluation, while their performances are either still at a low level for the test datasets from structure prediction models or dependent on the "black-box" process through neural networks. In this work, we have developed an all-atom distance-dependent statistical potential based on residue separation for RNA 3D structure evaluation, namely rsRNASP, which is composed of short- and long-ranged potentials distinguished by residue separation. The extensive examinations against available RNA test datasets show that rsRNASP has apparently higher performance than the existing statistical potentials for the realistic test datasets with large RNAs from structure prediction models, including the newly released RNA-Puzzles dataset, and is comparable to the existing top statistical potentials for the test datasets with small RNAs or near-native decoys. In addition, rsRNASP is superior to RNA3DCNN, a recently developed scoring function through 3D convolutional neural networks. rsRNASP and the relevant databases are available to the public.

Systematic measurements of interleaflet friction in supported bilayers.

Abstract: When lipid membranes curve or are subjected to strong shear forces, the two apposed leaflets of the bilayer slide past each other. The drag that one leaflet creates on the other is quantified by the coefficient of interleaflet friction, b. Existing measurements of this coefficient range over several orders of magnitude, so we used a recently developed microfluidic technique to measure it systematically in supported lipid membranes. Fluid shear stress was used to force the top leaflet of a supported membrane to slide over the stationary lower leaflet. Here, we show that this technique yields a reproducible measurement of the friction coefficient and is sensitive enough to detect differences in friction between membranes made from saturated and unsaturated lipids. Adding cholesterol to saturated and unsaturated membranes increased interleaflet friction significantly. We also discovered that fluid shear stress can reversibly induce gel phase in supported lipid bilayers that are close to the gel-transition temperature.

Multiscale mechanobiology: coupling models of adhesion kinetics and nonlinear tissue mechanics.

Abstract: The mechanical behavior of tissues at the macroscale is tightly coupled to cellular activity at the microscale. Dermal wound healing is a prominent example of a complex system in which multiscale mechanics regulate restoration of tissue form and function. In cutaneous wound healing, a fibrin matrix is populated by fibroblasts migrating in from a surrounding tissue made mostly out of collagen. Fibroblasts both respond to mechanical cues, such as fiber alignment and stiffness, as well as exert active stresses needed for wound closure. Here, we develop a multiscale model with a two-way coupling between a microscale cell adhesion model and a macroscale tissue mechanics model. Starting from the well-known model of adhesion kinetics proposed by Bell, we extend the formulation to account for nonlinear mechanics of fibrin and collagen and show how this nonlinear response naturally captures stretch-driven mechanosensing. We then embed the new nonlinear adhesion model into a custom finite element implementation of tissue mechanical equilibrium. Strains and stresses at the tissue level are coupled with the solution of the microscale adhesion model at each integration point of the finite element mesh. In addition, solution of the adhesion model is coupled with the active contractile stress of the cell population. The multiscale model successfully captures the mechanical response of biopolymer fibers and gels, contractile stresses generated by fibroblasts, and stress-strain contours observed during wound healing. We anticipate that this framework will not only increase our understanding of how mechanical cues guide cellular behavior in cutaneous wound healing, but will also be helpful in the study of mechanobiology, growth, and remodeling in other tissues.

Cellular mechanics of wound formation in single cell layer under cyclic stretching

Abstract: Wounds can be produced when cells and tissues are subjected to excessive forces, for instance, under pathological conditions or nonphysiological loading. However, the cellular behaviors in the wound formation process are not clear. Here we tested the behaviors of wound formation in the epithelial layer with an in-suit uniaxial stretching device. We found that the wound often nucleates at the position where the cells are dividing. The polarization direction of cells near the wound is preferentially along the wound edge, whereas the cells far from the wound are preferentially perpendicular to the stretching direction. The larger the wound area is, the higher is the aspect ratio of the cells around the wound. Increasing the cell density will strengthen the cell layer. The higher the cell density is, the smaller is the area of the wounds, and the weaker is the effect of stretching on the polarization of the cells. Furthermore, we built a coarse-grained cell model that can explicitly consider the elasticity and viscoelasticity of cells, cell-cell interaction, and cell active stress, by which we simulated the wound formation process and quantitatively analyzed the force and stress fields in the cell layer, particularly around the wound. These analyses reveal the cellular mechanisms of wound formation behaviors in the cell layer under stretching and shed useful light on tissue engineering and regenerative medicine for biomedical applications.

Simulating the chromatin-mediated phase separation of model proteins with multiple domains

Abstract: We perform simulations of a system containing simple model proteins and a polymer representing chromatin. We study the interplay between protein-protein and protein-chromatin interactions, and the resulting condensates that arise due to liquid-liquid phase separation, or a via a “bridging-induced attraction” mechanism. For proteins that interact multivalently, we obtain a phase diagram which includes liquid-like droplets, droplets with absorbed polymer, and coated polymer regimes. Of particular interest is a regime where protein droplets only form due to interaction with the polymer; here, unlike a standard phase separating system, droplet density rather than size varies with the overall protein concentration. We also observe that protein dynamics within droplets slow down as chromatin is absorbed. If the protein-protein interactions have a strictly limited valence, fractal or gel-like condensates are instead observed. A specific example that inspired our model is heterochromatin protein 1, or HP1. Recent in vivo experiments have shown that HP1 exhibits similar droplet size buffering behavior as our simulations. Overall, our results provide biologically relevant insights into the general nature of protein-chromatin condensates in living cells.

Muscle active force-length curve explained by an electrophysical model of interfilament spacing.

Abstract: The active isometric force-length relation (FLR) of striated muscle sarcomeres is central to understanding and modeling muscle function. The mechanistic basis of the descending arm of the FLR is well explained by the decreasing thin:thick filament overlap that occurs at long sarcomere lengths. The mechanistic basis of the ascending arm of the FLR (the decrease in force that occurs at short sarcomere lengths), alternatively, has never been well explained. Because muscle is a constant-volume system, interfilament lattice distances must increase as sarcomere length shortens. This increase would decrease thin and thick-filament electrostatic interactions independently of thin:thick filament overlap. To examine this effect, we present here a fundamental, physics-based model of the sarcomere that includes filament molecular properties, calcium binding, sarcomere geometry including both thin:thick filament overlap and interfilament radial distance, and electrostatics. The model gives extremely good fits to existing FLR data from a large number of different muscles across their entire range of measured activity levels, with the optimized parameter values in all cases lying within anatomically and physically reasonable ranges. A local first-order sensitivity analysis (varying individual parameters while holding the values of all others constant) shows that model output is most sensitive to a subset of model parameters, most of which are related to sarcomere geometry, with model output being most sensitive to interfilament radial distance. This conclusion is supported by re-running the fits with only this parameter subset being allowed to vary, which increases fit errors only moderately. These results show that the model well reproduces existing experimental data, and indicate that changes in interfilament spacing play as central a role as changes in filament overlap in determining the FLR, particularly on its ascending arm.

Desmoglein 2 can undergo Ca2+-dependent interactions with both desmosomal and classical cadherins including E-cadherin and N-cadherin.

Abstract: Desmoglein (Dsg) 2 is a ubiquitously expressed desmosomal cadherin. Particularly, it is present in all cell types forming desmosomes, including epithelial cells and cardiac myocytes and is upregulated in the autoimmune skin disease pemphigus. Thus, we here characterized the binding properties of Dsg2 in more detail using atomic force microscopy (AFM). Dsg2 exhibits homophilic interactions and also heterophilic interactions with the desmosomal cadherin desmocollin (Dsc) 2, and further with the classical cadherins E-cadherin (E-Cad) and N-cadherin (N-Cad), which may be relevant for cross talk between desmosomes and adherens junctions in epithelia and cardiac myocytes. We found that all homo- and heterophilic interactions were Ca2+-dependent. All binding forces observed are in the same force range, i.e., 30 to 40 pN, except for the Dsg2/E-Cad unbinding force, which with 45 pN is significantly higher. To further characterize the nature of the interactions, we used tryptophan, a critical amino acid required for trans-interaction, and a tandem peptide (TP) designed to cross-link Dsg isoforms. TP was sufficient to prevent the tryptophan-induced loss of Dsg2 interaction with the desmosomal cadherins Dsg2 and Dsc2; however, not with the classical cadherins E-Cad and N-Cad, indicating that the interaction modes of Dsg2 with desmosomal and classical cadherins differ. TP rescued the tryptophan-induced loss of Dsg2 binding on living enterocytes, suggesting that interaction with desmosomal cadherins may be more relevant. In summary, the data suggest that the ubiquitous desmosomal cadherin Dsg2 enables the cross talk with adherens junctions by interacting with multiple binding partners with implications for proper adhesive function in healthy and diseased states.

Characterizing fenestration size in sodium channel subtypes and their accessibility to inhibitors

Abstract: Voltage-gated sodium channels (Nav) underlie the electrical activity of nerve and muscle cells. Humans have nine different subtypes of these channels, which are the target of small-molecule inhibitors commonly used to treat a range of conditions. Structural studies have identified four lateral fenestrations within the Nav pore module that have been shown to influence Nav pore blocker access during resting-state inhibition. However, the structural differences among the nine subtypes are still unclear. In particular, the dimensions of the four individual fenestrations across the Nav subtypes and their differential accessibility to pore blockers is yet to be characterized. To address this, we applied classical molecular dynamics simulations to study the recently published structures of Nav1.1, Nav1.2, Nav1.4, Nav1.5, and Nav1.7. Although there is significant variability in the bottleneck sizes of the Nav fenestrations, the subtypes follow a common pattern, with wider DI-II and DIII-IV fenestrations, a more restricted DII-III fenestration, and the most restricted DI-IV fenestration. We further identify the key bottleneck residues in each fenestration and show that the motions of aromatic residue sidechains govern the bottleneck radii. Well-tempered metadynamics simulations of Nav1.4 and Nav1.5 in the presence of the pore blocker lidocaine also support the DI-II fenestration being the most likely access route for drugs. Our computational results provide a foundation for future in vitro experiments examining the route of drug access to sodium channels. Understanding the fenestrations and their accessibility to drugs is critical for future analyses of diseases mutations across different sodium channel subtypes, with the potential to inform pharmacological development of resting-state inhibitors and subtype-selective drug design.