Biophysical journal最新文献

Traumatic brain injury (TBI) is an established risk factor for developing neurodegenerative disease. However, how TBI leads from acute injury to chronic neurodegeneration is limited to postmortem models. There is a lack of connections between in vitro and in vivo TBI models that can relate injury forces to both macroscale tissue damage and brain function at the cellular level. Needle-induced cavitation (NIC) is a technique that can produce small cavitation bubbles in soft tissues, which allows us to relate small strains and strain rates in living tissue to ensuing acute cell death, tissue damage, and tissue remodeling. Here, we applied NIC to mouse brain slices to create a new model of TBI with high spatial and temporal resolution. We specifically targeted the hippocampus, which is a brain region critical for learning and memory and an area in which injury causes cognitive pathologies in humans and rodent models. By combining NIC with patch-clamp electrophysiology, we demonstrate that NIC in the cornu ammonis 3 region of the hippocampus dynamically alters synaptic release onto cornu ammonis 1 pyramidal neurons in a cannabinoid 1 receptor-dependent manner. Further, we show that NIC induces an increase in extracellular matrix protein GFAP associated with neural repair that is mitigated by cannabinoid 1 receptor antagonism. Together, these data lay the groundwork for advanced approaches in understanding how TBI impacts neural function at the cellular level and the development of treatments that promote neural repair in response to brain injury.

TAR DNA binding protein 43 (TDP-43) is a nuclear RNA/DNA-binding protein with pivotal roles in RNA-related processes such as splicing, transcription, transport, and stability. The high binding affinity and specificity of TDP-43 toward its cognate RNA sequences (GU-rich) is mediated by highly conserved residues in its tandem RNA recognition motif (RRM) domains (aa: 104-263). Importantly, the loss of RNA binding to the tandem RRMs caused by physiological stressors and chemical modifications promotes cytoplasmic mislocalization and pathological aggregation of TDP-43. Despite the substantial implications of RNA binding in TDP-43 function and pathology, its precise effects on the intradomain stability, and conformational dynamics of the tandem RRMs is not properly understood. Here, we employed all-atom molecular dynamics (MD) simulations to assess the effect of RNA binding on the conformational landscape and intradomain stability of TDP-43 tandem RRMs. RNA limits the overall conformational space of the tandem RRMs and promotes intradomain stability through a combination of specific base stacking interactions and transient electrostatic interactions. In contrast, tandem RRMs exhibit a high intrinsic conformational plasticity in the absence of RNA, which, surprisingly, is accompanied by a tendency of RRM1 to adopt partially unfolded conformations. Overall, our simulations reveal how RNA binding dynamically tunes the structural and conformational landscape of TDP-43 tandem RRMs, contributing to physiological function and mitigating pathological aggregation.

Molecular dynamics (MD) simulation of biological processes has always been a challenging task due to the long timescales of the processes involved and the large amount of output data to handle. Markov state models (MSMs) have been introduced as a powerful tool in this area of research, as they provide a mechanistically comprehensible synthesis of the large amount of MD data and, at the same time, can be used to rapidly estimate experimental properties of biological processes. Herein, we propose a method for building MSMs of ion channel permeation from MD trajectories, which directly evaluates the current flowing through the channel from the model's transition matrix (T), which is crucial for comparing simulations and experimental data. This is achieved by including in the model a flux matrix that summarizes information on the charge moving across the channel between each pair of states of the MSM and can be used in conjunction with T to predict the ion current. A procedure to drastically reduce the number of states in the MSM while preserving the estimated ion current is also proposed. Applying the method to the KcsA channel returned an MSM with five states with significant equilibrium occupancy, capable of accurately reproducing the single-channel ion current from microsecond MD trajectories.

We demonstrate the use of multiscale polymer modeling to quantitatively predict DNA linear dichroism (LD) in shear flow. LD is the difference in absorption of light polarized along two perpendicular axes and has long been applied to study biopolymer structure and drug-biopolymer interactions. As LD is orientation dependent, the sample must be aligned in order to measure a signal. Shear flow via a Couette cell can generate the required orientation; however, it is challenging to separate the LD due to changes in polymer conformation from specific interactions, e.g., drug-biopolymer. In this study, we have applied a combination of Brownian dynamics and equilibrium Monte Carlo simulations to accurately predict polymer alignment, and hence flow LD, at modest computational cost. As the optical and conformational contributions to the LD can be explicitly separated, our findings allow for enhanced quantitative interpretation of LD spectra through the use of an in silico model to capture conformational changes. Our model requires no fitting and only five input parameters: the DNA contour length, persistence length, optical factor, solvent quality, and relaxation time, all of which have been well characterized in prior literature. The method is sufficiently general to apply to a wide range of biopolymers beyond DNA, and our findings could help guide the search for new pharmaceutical drug targets via flow LD.

Intrinsically disordered proteins (IDPs) often contain proline residues that undergo cis/trans isomerization. While molecular dynamics (MD) simulations have the potential to fully characterize the proline cis and trans subensembles, they are limited by the slow timescales of isomerization and force field inaccuracies. NMR spectroscopy can report on ensemble-averaged observables for both the cis-proline and trans-proline states, but a full atomistic characterization of these conformers is challenging. Given the importance of proline cis/trans isomerization for influencing the conformational sampling of disordered proteins, we employed a combination of all-atom MD simulations with enhanced sampling (metadynamics), NMR, and small-angle x-ray scattering (SAXS) to characterize the two subensembles of the ORF6 C-terminal region (ORF6_CTR) from SARS-CoV-2 corresponding to the proline-57 (P57) cis and trans states. We performed MD simulations in three distinct force fields: AMBER03ws, AMBER99SB-disp, and CHARMM36m, which are all optimized for disordered proteins. Each simulation was run for an accumulated time of 180-220 μs until convergence was reached, as assessed by blocking analysis. A good agreement between the cis-P57 populations predicted from metadynamic simulations in AMBER03ws was observed with populations obtained from experimental NMR data. Moreover, we observed good agreement between the radius of gyration predicted from the metadynamic simulations in AMBER03ws and that measured using SAXS. Our findings suggest that both the cis-P57 and trans-P57 conformations of ORF6_CTR are extremely dynamic and that interdisciplinary approaches combining both multiscale computations and experiments offer avenues to explore highly dynamic states that cannot be reliably characterized by either approach in isolation.

The epidermal growth factor receptor (EGFR) governs pivotal signaling pathways in cell proliferation and survival, with mutations implicated in numerous cancers. The organization of EGFR on the plasma membrane (PM) is influenced by the lipids and the cortical actin (CA) cytoskeleton. Despite the presence of a putative actin-binding domain (ABD) spanning 13 residues, a direct interaction between EGFR and CA has not been definitively established. While disrupting the cytoskeleton can impact EGFR behavior, suggesting a connection, the influence of the static actin cytoskeleton has been found to be indirect. Here, we investigate the potential interaction between EGFR and CA, as well as the extent to which CA regulates EGFR's distribution on the PM using SRRF'n'TIRF, a spatiotemporal super-resolution microscopy technique that provides sub-100 nm resolution and ms-scale dynamics from the same data set. To label CA, we constructed PMT-mEGFP-F-tractin, which combines an inner leaflet targeting domain PMT, fluorescent probe mEGFP, and the actin-binding protein F-tractin. In addition to EGFR-mEGFP, we included two control constructs: 1) an ABD deletion mutant, EGFRΔ^ABD-mEGFP serving as a negative control and 2) EGFR-mApple-F-tractin, where F-tractin is fused to the C-terminus of EGFR-mApple, serving as the positive control. We find that EGFR-mEGFP and EGFRΔ^ABD-mEGFP show similar membrane dynamics, implying that EGFR-mEGFP dynamics and organization are independent of CA. EGFR dynamics show CA dependence when F-tractin is anchored to the cytoplasmic tail. Together, our results demonstrate that EGFR does not directly interact with the CA in its resting and activated state.

Many animal cells that crawl on extracellular substrates exhibit durotaxis, i.e., directed migration toward stiffer substrate regions. This has implications in several biological processes including tissue development and tumor progression. Here, we introduce a phenomenological model for single-cell durotaxis that incorporates both elastic deformation-mediated cell-substrate interactions and the stochasticity of cell migration. Our model is motivated by a key observation in an early demonstration of durotaxis: a single, contractile cell at a sharp interface between a softer and a stiffer region of an elastic substrate reorients and migrates toward the stiffer region. We model migrating cells as self-propelling, persistently motile agents that exert contractile traction forces on their elastic substrate. The resulting substrate deformations induce elastic interactions with mechanical boundaries, captured by an elastic potential. The dynamics is determined by two crucial parameters: the strength of the cellular traction-induced boundary elastic interaction (A), and the persistence of cell motility (Pe). Elastic forces and torques resulting from the potential orient cells perpendicular (parallel) to the boundary and accumulate (deplete) them at the clamped (free) boundary. Thus, a clamped boundary induces an attractive potential that drives durotaxis, while a free boundary induces a repulsive potential that prevents antidurotaxis. By quantifying the steady-state position and orientation probability densities, we show how the extent of accumulation (depletion) depends on the strength of the elastic potential and motility. We compare and contrast crawling cells with biological microswimmers and other synthetic active particles, where accumulation at confining boundaries is well known. We define metrics quantifying boundary accumulation and durotaxis, and present a phase diagram that identifies three possible regimes: durotaxis, and adurotaxis with and without motility-induced accumulation at the boundary. Overall, our model predicts how durotaxis depends on cell contractility and motility, successfully explains some previous observations, and provides testable predictions to guide future experiments.

Hemolysis, including subclinical hemolysis, is a potentially severe complications of mechanical heart valves (MHVs), which leads to shortened red blood cell (RBC) lifespan and hemolytic anemia. Serious hemolysis is usually associated with structural deterioration and regurgitation. However, the shear stress in MHVs' narrow leakage slits is much lower than the shear stress threshold causing hemolysis and the mechanisms in this context remain largely unclear. This study investigated the hemolysis mechanism of RBCs in cell-size slits under high shear rates by establishing in vitro microfluidic devices and a coarse-grained molecular dynamics (CGMD) model, considering both fluid and structural effects simultaneously. Microfluidic experiments and computational simulation revealed six distinct dynamic states of RBC traversal through MHVs' microscale slits under various shear rates and slit sizes. It elucidated that RBC dynamic states were influenced by not only by fluid forces but significantly by the compressive force of slit walls. The variation of the potential energy of the cell membrane indicated its stretching, deformation, and rupture during traversal, corresponding to the six dynamic states. The maximum forces exerted on membrane by water particles and slit walls directly determined membrane rupture, serving as a critical determinant. This analysis helps in understanding the contribution of the slit walls to membrane rupture and identifying the threshold force that leads to membrane rupture. The hemolysis mechanism of traversing microscale slits is revealed to effectively explain the occurrences of hemolysis and subclinical hemolysis.

Measuring the compaction of a protein or complex is key to our understanding of the interactions within and between biomolecules. Experimentally, protein compaction is often probed either by estimating the radius of gyration (R_g) obtained from small-angle x-ray scattering (SAXS) experiments or the hydrodynamic radius (R_h) obtained, for example, by pulsed field gradient NMR (PFG NMR) spectroscopy. PFG NMR experiments generally report on the translational diffusion coefficient, which in turn can be used to estimate R_h using an internal standard to account for sample viscosity and uncertainty about the gradient strength. 1,4-Dioxane is one such commonly used internal standard, and the reference value of R_h is therefore important. We have revisited the basis for the commonly used reference value for the R_h of dioxane (2.12 Å) that is used to convert measured diffusion coefficients into a hydrodynamic radius. We followed the same approach that was used to establish the current reference value by measuring SAXS and PFG NMR data for a set of seven different proteins and using these as standards. Our analysis shows that the current R_h reference value for dioxane R_h is underestimated, and we instead suggest a new value of 2.27 ± 0.04 Å. Using this updated reference value results in a ∼7% increase in R_h values for proteins whose hydrodynamic radii have been measured by PFG NMR. These results are particularly important when the absolute value of R_h is of interest such as when determining or validating ensemble descriptions of intrinsically disordered proteins.