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Electrostatically driven double stranded (ds)DNA condensation is critical in regulating many biological processes, including bacteriophage and virus replication and the packaging of chromosomal DNA in sperm heads. Here we review single-molecule (SM) measurements of dsDNA condensed by cationic proteins, polypeptides, and small multivalent cations. Optical tweezers (OT) measurements of dsDNA collapsed by cationic condensing agents reveal a critical condensing force unique to each condensing agent that is tunable with condensing agent concentration and ionic strength.

The breast tumor microenvironment is composed of heterogeneous cell populations, including normal epithelial cells, cancer-associated fibroblasts, and tumor cells that lead collective cell invasion. Both leader tumor cells and CAFs are known to play important roles in tumor invasion across the collagen-rich stromal boundary. However, their individual abilities to utilize their cell-intrinsic protrusions and perform force-based collagen remodeling to collectively invade remain unclear. To compare collective invasion phenotypes of leader-like tumor cells and CAFs, we embedded spheroids composed of 4T1 tumor cells or mouse tumor-derived CAF cell lines within 3D collagen gels and analyzed their invasion and collagen deformation.

Mutations to WNT ligands in cancer are poorly understood. WNT ligands are a family of secreted proteins that trigger the activation of the WNT pathway with essential roles in cell development and carcinogenesis, particularly of the colorectal tract. Whilst the structure of WNT ligands has been elucidated, little is known about how mutations in these proteins affect colorectal cancer. Here we show that mutations in WNT ligands found in colorectal cancer show regional specificity and selectivity for particular conserved sequences.

Single-molecule spectroscopy combined with Förster resonance energy transfer (FRET) is widely used to quantify distance dynamics and distributions in biomolecules. Most commonly, measurements are interpreted using simple analytical relations between experimental observables and the underlying distance distributions. However, these relations make simplifying assumptions, such as a separation of timescales between inter-dye distance dynamics, fluorescence lifetimes, and dye reorientation, the validity of which is notoriously difficult to assess from experimental data alone.

Statement of Significance: We describe a novel system that can read out and control tension of a membrane patch in real time. It allows measuring tension-response relationships of force-gated ion channels without the need for hands-on data analysis, thereby accelerating data collection. We envision that the system can be alternatively used to read out and control membrane curvature, thereby additionally enabling the study of how protein function is affected by membrane geometry.

Deep learning based approaches are now widely used across biophysics to help automate a variety of tasks including image segmentation, feature selection, and deconvolution. However, the presence of multiple competing deep learning architectures, each with its own advantages and disadvantages, makes it challenging to select an architecture best suited for a specific application. As such, we present a comprehensive comparison of common models. Here, we focus on the task of segmentation assuming typical (often small) training dataset sizes available from biophysics experiments and compare the following four commonly used architectures: convolutional neural networks, U-Nets, vision transformers, and vision state space models.

We introduce a Discard-and-Restart molecular dynamics (MD) algorithm tailored for the sampling of realistic protein intermediate states. It aids computational structure-based drug discovery by reducing the simulation times to compute a "quick sketch" of folding pathways by up to 2000x. The algorithm iteratively performs short MD simulations and measures their proximity to a target state via a collective variable (CV) loss, which can be defined in a flexible fashion, locally or globally. Using the loss, if the trajectory proceeds toward the target, the MD simulation continues.

Recent global burden of disease studies have shown that bacterial infections are responsible for over 13 million deaths worldwide, or one in every eight deaths, each year. Enteric diarrheal infections, in particular, pose a significant challenge and strain on healthcare systems as many are difficult to address pharmaceutically, and thus, rely primarily on the patient’s own immune system and gut microbiome to fight the infection. Nonetheless, the specific mechanisms behind gut microbiome colonization resistance of enteric pathogens are not well-defined and microbiome diversity is difficult to represent and study experimentally.

The purpose of this review is to evaluate the current knowledge about the mechanisms by which mechanosensitive ion channels are activated by fluid shear stress in endothelial cells. We focus on three classes of endothelial ion channels that are most well studied for their sensitivity to flow and roles in mechanotransduction: inwardly-rectifying K+ channels, Piezo channels and TRPV channels. We also discuss the mechanisms by which these channels initiate and contribute to mechanosensitive signaling pathways.

SIGNIFICANCE: Cell cycle studies regularly use correlations between cell lengths at various cell cycle checkpoints to elucidate the underlying mechanisms. It is unclear whether length is a good proxy for cell volume. Indeed, studies in fission yeast showed that cell width fluctuations can influence the measured correlations, and make length and volume non-interchangeable. Using modeling and data analysis of Escherichia coli experimental data, we find that cell width fluctuations have negligible impact on the correlation structure of cell cycle variables. This implies that for bacteria such as E. coli, length and volume can often be used interchangeably. Our analysis suggests cell width is tightly regulated in E. coli, to an accuracy of ≈ 4% or 10 nm.

Small proteins can be challenging to study by single-particle cryo-EM techniques because they have low signal to noise ratios, making them difficult to identify and analyze. Here we investigated the use of Csp1, a small (54 kDa) tetrameric metal-binding protein, to act as a “bio-tag” to help overcome this problem. We find Csp1 is compact, stable, and exhibits enhanced electron scattering and excellent particle contrast in cryo-EM micrographs. As a result, we could determine the structure of Csp1 to 2.98 Å resolution using standard cryo-EM approaches.

Large unilamellar vesicles are popular membrane models for studying the impact of lipids and bilayer properties on the structure and function of transmembrane proteins. However, the functional reconstitution of transmembrane proteins in liposomes can be challenging, especially, if the hydrophobic thickness of the protein does not match the thickness of the lipid bilayer. Such hydrophobic mismatch causes protein aggregation and low yields during the reconstitution procedure, which are exacerbated in sterol-rich membranes featuring low membrane compressibility.