Biophysical journal最新文献

The flaviviral NS2B/NS3 protease is a conserved enzyme required for flavivirus replication. Its highly dynamic conformation poses major challenges but also offers opportunities for antiviral inhibition. Here, we established a nanopore tweezers-based platform to monitor NS2B/NS3 conformational dynamics in real time. Molecular simulations coupled with single-channel current recording measurements revealed that the protease could be captured in the middle of the ClyA nanopore lumen, stabilized mainly by dynamic electrostatic interactions. We designed a new Salmonella typhi ClyA nanopore with enhanced nanopore/protease interaction that can resolve the open and closed states at the single-molecule level for the first time. We demonstrated that the tailored ClyA could track the conformational transitions of the West Nile NS2B/NS3 protease and unravel the conformational energy landscape of various protease constructs through population and kinetic analysis. The new ClyA-protease platform paves a way to search for new allosteric inhibitors that target the NS2B and NS3 interface.

The dynamics of many macromolecular machines are characterized by chemically mediated structural changes that achieve large-scale functional deployment through local rearrangements of constitutive protein subunits. Motivated by recent high-resolution structural microscopy of a particular class of such machines, contractile injection systems (CISs), we construct a coarse-grained semianalytical model that recapitulates the geometry and bistability of CISs in terms of a minimal set of measurable physical parameters. We use this model to predict the size, shape, and speed of a dynamical actuation front that underlies contraction. Scaling laws for the velocity and physical extension of the contraction front are consistent with our numerical simulations and may be generally applicable to related systems.

Living cells are known to exhibit power-law viscoelastic responses and localized stress relaxation behaviors in the frequency spectrum. However, the precise interplay between molecular-scale cytoskeletal dynamics and macroscale dynamical rheological responses remains elusive. Here, we propose a mechanism-based general theoretical model showing that cytoskeleton dissociation generates a peak in the loss modulus as a function of frequency, while the cytoplasmic viscosity promotes its recovery, producing a subsequent trough. We define two characteristic frequencies (ω_c1 and ω_c2) related to the dissociation rate of crosslinkers and the viscosity of the cytoplasm, where the loss modulus 1) exhibits peak and trough values for ω_c1<ω_c2 and 2) monotonically increases with frequency for ω_c1>ω_c2. Furthermore, the characteristic frequency ω_c1 exhibits a biphasic stress-dependent behavior, with a local minimum at sufficiently high stress due to the stress-dependent dissociation rate. Moreover, the characteristic frequency ω_c2 evolves with age, following a power-law relationship. The predictions of the dissociation-based multiscale theoretical mechanical model align well with experimental observations. Our model provides a comprehensive description of the dynamical viscoelastic behaviors of cells and cell-like materials.

All living cells vibrate depending on metabolism. It has been hypothesized that vibrations are unique for a given phenotype and thereby suitable to diagnose cancer type and stage and to pre-assess the effectiveness of pharmaceutical treatments in real time. However, cells exhibit highly variable vibrational signals, can be subject to environmental noise, and may be challenging to differentiate, having so far limited the phenomenon's applicability. Here, we combined the sensitive method of force spectroscopy using optical tweezers with comprehensive statistical analysis. After data acquisition, the signal was decomposed into its spectral components via fast Fourier transform. Peaks were parameterized and subjected to principal-component analysis to perform an unbiased multivariate statistical evaluation. This method, which we term cell vibrational profiling (CVP), systematically assesses cellular vibrations. To validate the CVP technique, we conducted experiments on five U251 glioblastoma cells, using 8- to 10-μm polystyrene beads as a control for comparison. We collected raw data using optical tweezers, segmenting into 150+ 5-s intervals. Each segment was converted into power spectra representing a frequency resolution of 10,000 Hz for both cells and controls. U251 glioblastoma cells exhibited significant vibrations at 402.6, 1254.6, 1909.0, 2169.4, and 3462.8 Hz (p < 0.0001). This method was further verified with principal-component analysis modeling, which revealed that, in cell-cell comparisons using the selected frequencies, overlap frequently occurred, and clustering was difficult to discern. In contrast, comparison between cell-bead models showed that clustering was easily distinguishable. Our paper establishes CVP as an unbiased, comprehensive technique to analyze cell vibrations. This technique effectively differentiates between cell types and evaluates cellular responses to therapeutic interventions. Notably, CVP is a versatile, cell-agnostic technique requiring minimal sample preparation and no labeling or external interference. By enabling definitive phenotypic assessments, CVP holds promise as a diagnostic tool and could significantly enhance the evaluation of pharmaceutical treatments.

Cell-cell communication through direct contact, or juxtacrine signaling, is important in development, disease, and many areas of physiology. Synthetic forms of juxtacrine signaling can be precisely controlled and operate orthogonally to native processes, making them a powerful reductionist tool with which to address fundamental questions in cell-cell communication in vivo. Here, we investigate how cell-cell contact length and tissue growth dynamics affect juxtacrine signal responses through implementing a custom synthetic gene circuit in Drosophila wing imaginal discs alongside mathematical modeling to determine synthetic Notch (synNotch) activation patterns. We find that the area of contact between cells largely determines the extent of synNotch activation, leading to the prediction that the shape of the interface between signal-sending and signal-receiving cells will impact the magnitude of the synNotch response. Notably, synNotch outputs form a graded spatial profile that extends several cell diameters from the signal source, providing evidence that the response to juxtacrine signals can persist in cells as they proliferate away from source cells, or that cells remain able to communicate directly over several cell diameters. Our model suggests that the former mechanism may be sufficient, since it predicts graded outputs without diffusion or long-range cell-cell communication. Overall, we identify that cell-cell contact area together with output synthesis and decay rates likely govern the pattern of synNotch outputs in both space and time during tissue growth, insights that may have broader implications for juxtacrine signaling in general.

Influenza A virus particles assemble at the plasma membrane of infected cells. During assembly all components of the virus come together in a coordinated manner to deform the membrane into a protrusion eventually forming a new, membrane-enveloped virus. Here, we integrate recent molecular insights of this process, particularly concerning the structure of the matrix protein 1 (M1), within a theoretical framework describing the mechanics of virus assembly. Our model describes M1 polymerization and membrane protrusion formation, explaining why it is efficient for M1 to form long strands assembling into helices in filamentous virions. Eventually, we find how the architecture of M1 helices is controlled by physical properties of viral proteins and the host cell membrane. Finally, by considering the growth force and speed of viral filaments, we propose that the helical geometry of M1 strands might have evolved to optimize for fast and efficient virus assembly and growth.