Despite the importance of speed in synaptic transmission, in many synapses, neurotransmitters bind to their receptors at rates that appear to be slower than the diffusion limit. This assessment is generally based on a comparison with the Smoluchowski limit rather than an independent experimental analysis. In many synapses, miniature excitatory postsynaptic currents (mEPSCs) are controlled by the interplay between binding to receptors and diffusion of the neurotransmitter out of the synaptic cleft. A model for mEPSCs that incorporates these features was used to evaluate published data showing that elevated viscosity increases mEPSC amplitude. With diffusion-limited binding, the model predicts that raising the viscosity will decrease the amplitude rather than increase it. Diffusion-independent binding predicts an increase that is larger than that observed. To explore the intermediate behavior between the diffusion-limited and diffusion-independent extremes, a general expression for intermolecular rates was used that depends on both collision frequency and intrinsic reactivity. This analysis yielded an estimate for collision frequency that is about an order of magnitude above the measured rate of association and an order of magnitude below the Smoluchowski limit.
Traction-force microscopy (TFM) has emerged as a widely used standard methodology to measure cell-generated traction forces and determine their role in regulating cell behavior. While TFM platforms have enabled many discoveries, their implementation remains limited due to complex experimental procedures, specialized substrates, and the ill-posed inverse problem whereby low-magnitude high-frequency noise in the displacement field severely contaminates the resulting traction measurements. Here, we introduce deep morphology traction microscopy (DeepMorphoTM), a deep-learning alternative to conventional TFM approaches. DeepMorphoTM first infers cell-induced substrate displacement solely from a sequence of cell shapes and subsequently computes cellular traction forces, thus avoiding the requirement of a specialized fiduciarily marked deformable substrate or force-free reference image. Rather, this technique drastically simplifies the overall experimental methodology, imaging, and analysis needed to conduct cell-contractility measurements. We demonstrate that DeepMorphoTM quantitatively matches conventional TFM results while offering stability against the biological variability in cell contractility for a given cell shape. Without high-frequency noise in the inferred displacement, DeepMorphoTM also resolves the ill-posedness of traction computation, increasing the consistency and accuracy of traction analysis. We demonstrate the accurate extrapolation across several cell types and substrate materials, suggesting robustness of the methodology. Accordingly, we present DeepMorphoTM as a capable yet simpler alternative to conventional TFM for characterizing cellular contractility in two dimensions.
Insulin levels in the blood oscillate with a variety of periods, including rapid (5-10 min), ultradian (50-120 min), and circadian (24 h). Oscillations of insulin are beneficial for lowering blood glucose and disrupted rhythms are found in people with type 2 diabetes and their close relatives. These in vivo secretion dynamics imply that the oscillatory activity of individual islets of Langerhans are synchronized, although the mechanism for this is not known. One mechanism by which islets may synchronize is negative feedback of insulin on whole-body glucose levels. In previous work, we demonstrated that a negative feedback loop with a small time delay, to account for the time required for islets to be exposed to a new glucose concentration in vivo, results in small 3-6 islet populations synchronizing to produce fast closed-loop oscillations. However, these same islet populations could also produce slow closed-loop oscillations with periods longer than the natural islet oscillation periods. Here, we investigate the origin of the slow oscillations and the bistability with the fast oscillations using larger islet populations (20-50 islets). In contrast to what was observed earlier, larger islet populations mainly synchronize to longer-period oscillations that are approximately twice the delay time used in the feedback loop. A mean-field model was also used as a proxy for a large islet population to uncover the underlying mechanism for the slow rhythm. The heterogeneous intrinsic oscillation periods of the islets interferes with this rhythm mechanism when islet populations are small, and is similar to adding noise to the mean-field model. Thus, the effect of a time delay in the glucose feedback mechanism is similar to other examples of time-delayed systems in biology and may be a viable mechanism for ultradian oscillations.
Proton transport across lipid membranes is one of the most fundamental reactions that make up living organisms. In vitro, however, the study of proton transport reactions can be very challenging due to limitations imposed by proton concentrations, compartment size, and unstirred layers as well as buffer exchange and buffer capacity. In this study, we have developed a proton permeation assay based on the microfluidic trapping of giant vesicles enclosing the pH-sensitive dye pyranine to address some of these challenges. Time-resolved fluorescence imaging upon a rapid pH shift enabled us to investigate the facilitated H+ permeation mediated by either a channel or a carrier. Specifically, we compared the proton transport rates as a function of different proton gradients of the channel gramicidin D and the proton carrier carbonyl cyanide-m-chlorophenyl hydrazone. Our results demonstrate the efficacy of the assay in monitoring proton transport reactions and distinguishing between a channel-like and a carrier-like mechanism. This groundbreaking result enabled us to elucidate the enigmatic mode of the proton permeation mechanism of the recently discovered natural fibupeptide lugdunin.
There have been a growing number of computational strategies to aid in the design of synthetic microbial consortia. A framework to identify regions in parametric space to maximize two essential properties, evenness and stability, is critical. In this study, we introduce DyMMM-LEAPS (dynamic multispecies metabolic modeling-locating evenness and stability in large parametric space), an extension of the DyMMM framework. Our method explores the large parametric space of genetic circuits in synthetic microbial communities to identify regions of evenness and stability. Due to the high computational costs of exhaustive sampling, we utilize adaptive sampling and surrogate modeling to reduce the number of simulations required to map the vast space. Our framework predicts engineering targets and computes their operating ranges to maximize the probability of the engineered community to have high evenness and stability. We demonstrate our approach by simulating five cocultures and one three-strain culture with different social interactions (cooperation, competition, and predation) employing quorum-sensing-based genetic circuits. In addition to guiding circuit tuning, our pipeline gives an opportunity for a detailed analysis of pockets of evenness and stability for the circuit under investigation, which can further help dissect the relationship between the two properties. DyMMM-LEAPS is easily customizable and can be expanded to a larger community with more complex interactions.
Dendritic cells (DCs) are antigen-presenting cells that reside in peripheral tissues and are responsible for initiating adaptive immune responses. As gatekeepers of the immune system, DCs need to continuously explore their surroundings, for which they can rapidly move through various types of connective tissue and basement membranes. DC motility has been extensively studied on flat 2D surfaces, yet the influences of a contextual 3D fibrous environment still need to be described. Using ECM-mimicking suspended fiber networks, we show how immature DCs (iDCs) engage in migratory cycles that allow them to transition from persistent migration to slow migratory states. For a subset of iDCs with high migratory potential, we report the organization of protrusions at the front of the cell body, which reverses upon treatment with inflammation agent PGE2. We identify an unusual migratory response to aligned fiber networks, whereby iDCs use filamentous protrusions to attach laterally and exert forces on fibers to migrate independent of fiber alignment. Increasing the fiber diameter from 200 to 500 nm does not significantly affect the migratory response; however, iDCs respond by forming denser actin bundles around larger diameters. Overall, the correlation between force-coupling and random migration of iDCs in aligned fibrous topography offers new insights into how iDCs might move in fibrous environments in vivo.
Skin barrier function is localized in its outermost layer, the stratum corneum (SC), which is comprised of corneocyte cells embedded in an extracellular lipid matrix containing ceramides (CERs), cholesterol (CHOL), and free fatty acids (FFAs). The unique structure and composition of this lipid matrix are important for skin barrier function. In this study, experiments and molecular dynamics simulation were combined to investigate the structural properties and phase behavior of mixtures containing nonhydroxy sphingosine CER (CER NS), CHOL, and FFA. X-ray scattering for mixtures with varying CHOL levels revealed the presence of the 5.4 nm short periodicity phase in the presence of CHOL. Bilayers in coarse-grained multilayer simulations of the same compositions contained domains with thicknesses of approximately 5.3 and 5.8 nm that are associated with elevated levels, respectively, of CER sphingosine chains with CHOL, and CER acyl chains with FFA chains. The prevalence of the thicker domain increased with decreasing CHOL content. This might correspond to a phase with ∼5.8 nm spacing observed by x-rays (other details unknown) in mixtures with lower CHOL content. Scissoring and stretching frequencies from Fourier transform infrared spectroscopy (FTIR) also indicate interaction between FFA and CER acyl chains and little interaction between CER acyl and CER sphingosine chains, which requires CER molecules to adopt a predominantly extended conformation. In the simulated systems, neighbor preferences of extended CER chains align more closely with the FTIR observations than those of CERs with hairpin ceramide chains. Both FTIR and atomistic simulations of reverse mapped multilayer membranes detect a hexagonal to fluid phase transition between 65 and 80°C. These results demonstrate the utility of a collaborative experimental and simulation effort in gaining a more comprehensive understanding of SC lipid membranes.