European Biophysics Journal最新文献

Giant unilamellar vesicles (GUVs) are a powerful model system whose response to electric fields constitutes a strategy to directly assess membrane material properties. In the last few years, the field has advanced in both conceptual scope and experimental precision. Electric-field manipulation of GUVs remains a versatile platform for extracting membrane mechanical, electrical, and rheological properties with single-vesicle resolution, while increasingly extending from a diagnostic tool into an actuation mechanism. Here, we summarize classical electrodeformation and electroporation methodologies and review recent developments that push these approaches toward greater biological realism, including compound vesicles as nucleate-cell mimics, resting-membrane-potential- and ion-dependent poration, phase-transition electromechanics, and cytoskeleton-loaded, field-responsive membranes. We also discuss how electric fields are combined with other stimuli, such as light and biochemical cues, and repurposed to drive active, motile vesicle assemblies and to fabricate tailored lipid architectures at high throughput. We further highlight theoretical work on electromechanical coupling, membrane charging dynamics, and vesicle shape landscapes under electric stress. We close by outlining remaining challenges, from reproducibility across preparation protocols to bridging model membranes and living cells, and future opportunities for automated, high-throughput, and multimodal electromechanical studies of biomimetic membranes.

The structure of chromatin and its association mechanisms are studied using the biological membrane (BM) model with a formalism of electric and hydrophobic dipole interactions. This model establishes that hydrophobic moments attract each other, associating in parallel in a manner analogous to how phospholipids associate to form a biological membrane. The structure of DNA is reviewed as the stacking of the hydrophobic dipole moments of its bases in relation to their separation distances. Archaeal chromatin is revisited, which is associated with a structure resembling a continuous coil of DNA, in which each turn contains three protohistone dimers hydrophobically attached to it. A description follows of the hydrophobic association of histones H2A, H2B, H3, and H4, forming the well-known octamer, and its binding to two DNA strands that constitute the nucleosome. This association is nuanced with electrostatic interactions, highlighting the fundamental role of hydrophobic interactions. Simulated alternative forms of histone association are compared, and it is confirmed that the structure present in the nucleosome is the most energetically stable. This type of interaction is also the basis of the hydrophobic association mechanisms of nucleosome stacking, by the parallel alignment of their hydrophobic dipole moments. These associations in parallel stacks have variable strengths, depending on their specific sequence compositions. Also the role of histone H1 and linker DNAs is addressed in its mechanisms of joining the extensions of nucleosomal DNA to join another nucleosome.

Bax-interacting factor-1 (BIF-1), also known as endophilin B1 (SH3GLB1), is a membrane-associated protein involved in apoptosis, autophagy, and membrane dynamics. There is growing evidence of a context-dependent role in tumor biology, mainly associated with tumor-suppressive functions in several cancers. In this narrative review, we summarize current evidence regarding BIF-1 expression patterns and its functional relevance in cancer-related pathways. Downregulation of BIF-1 has been consistently reported in melanoma, breast cancer, prostate cancer, gastric carcinoma, colorectal cancer, urinary bladder cancer and gallbladder cancer, where reduced expression is associated with impaired apoptosis, altered autophagy and tumor progression, supporting its potential value as a tumor suppressor-associated biomarker. On the other hand, hepatocellular carcinoma shows a context-dependent expression pattern and inconsistent associations with clinical outcomes. Its clinical utility in these tumors is limited because diagnostic and prognostic significance has not been consistently demonstrated. Therapeutic studies suggest that modulation of BIF-1-related pathways could influence autophagy, apoptosis and cellular metabolism, implying indirect participation in cancer treatment strategies. In general, BIF-1 seems to be a potential biomarker linked to tumor suppression in various epithelial cancers, especially in melanoma, breast, and prostate cancers. However, it's clinical utility remains limited or appears variable in pancreatic ductal adenocarcinoma and Merkel cell carcinoma. These findings highlight the context-dependent role of BIF-1 in tumor biology.

Focal adhesion (FA) dynamics and cell migration depend sensitively on the mechanical properties of the extracellular matrix, yet substrate stiffness alone cannot account for the distinct behaviours observed on natural versus artificial materials. In this review, we synthesize experimental findings on cells interacting with collagen I matrices and viscoelastic hydrogels, and identify the key physical mechanisms that govern adhesion stability, turnover, and migratory efficiency. Collagen I substrates are characterized by structural anisotropy, spatial heterogeneity, and a broad spectrum of relaxation times, in contrast to the simplified and often isotropic response of artificial hydrogels. Based on these observations, we highlight the central role of interfacial slippage at the FA-substrate biointerface enabled by matrix remodelling and multi-timescale viscoelastic dissipation. We further discuss how cell-generated forces can induce collagen reorganization and surface tension gradients, potentially driving Marangoni-like flows that contribute to dynamic matrix redistribution. These processes collectively maintain adhesions in a state between stabilization and turnover, favourable for persistent migration. Finally, we consider the interplay between these mechanical mechanisms and mechanosensitive signalling, particularly involving Piezo1 ion channels. This perspective emphasizes that effective cell-matrix coupling arises from the ability of the substrate to dissipate and reorganize distribution of mechanical energy, rather than from stiffness alone.

Electrical impedance sensing offers a powerful, non-invasive method for real-time monitoring of cellular behaviour; with applications spanning immunology, cancer biology and drug discovery. Adoption of impedance-sensing approaches has been accelerated by the commercial availability of the ECIS, xCELLigence, ScioSpec and cellZscope platforms; however, the complexity and volume of impedance datasets produced has limited rigorous analysis. vascr, an open-source R-based toolkit designed to streamline the processing of impedance sensing datasets was created to facilitate rapid and simplified handling of cellular impedance sensing data. vascr can import multi-frequency data from multiple instrument manufacturers and includes robust analysis tools for resampling, outlier detection, and statistical testing using ANOVA and cross-correlation. Using the vascr workflow, impedance sensing data can be rapidly and robustly interpreted, allowing for real-time investigation of the effects of biological agents on cellular processes such as endothelial barrier integrity.

The plasma membrane hosts a diverse set of proteins whose attachment, detachment, and lateral diffusion give rise to complex spatiotemporal patterns that regulate essential cellular processes. In motile eukaryotic cells, localized protein patterns at the membrane control actin organization and thereby establish a front-rear axis that drives locomotion. While persistent migration following a chemotactic signal can be captured by deterministic reaction-diffusion models coupled to a phase-field description of cell shape, amoeboid motion in cells such as neutrophils and Dictyostelium discoideum is markedly more irregular and requires the inclusion of stochastic effects. Existing modeling approaches typically introduce external noise into pattern-forming mechanisms or, alternatively, although much less frequently, they account for intrinsic fluctuations arising from the small number of participating molecules. Here, we compare and connect these two complementary modeling strategies for membrane protein dynamics driving cell locomotion in Dictyostelium discoideum. We present a stochastic reaction-diffusion model coupled to a phase field, previously calibrated to experimental data, alongside a related formulation in which fluctuations emerge intrinsically from molecular discreteness. Through systematic numerical simulations, we characterize the resulting membrane patterns and dynamical behaviors. Our results test the hypothesis that externally imposed fluctuations can be effectively reduced to intrinsic noise derived from first principles. We highlight the critical role of temporal correlation, a key feature of the original phenomenological formulation, and contrast it with the behavior of internal fluctuations. Finally, we discuss the relative strengths, differences, and physical limitations of both stochastic approaches.