Biophysical journal最新文献

Voltage-gated ion channels allow ion flux across biological membranes in response to changes in the membrane potential. HCNL1 is a recently discovered voltage-gated ion channel that selectively conducts protons through its voltage-sensing domain (VSD), reminiscent of the well-studied depolarization-activated Hv1 proton channel. However, HCNL1 is activated by hyperpolarization, allowing the influx of protons, which leads to an intracellular acidification in zebrafish sperm. Zinc ions (Zn²⁺) are important cofactors in many proteins and essential for sperm physiology. Proton channels such as Hv1 and Otopetrin1 are inhibited by Zn²⁺. We investigated the effect of Zn²⁺ on heterologously expressed HCNL1 channels using electrophysiological and fluorometric techniques. Extracellular Zn²⁺ inhibits HCNL1 currents with an apparent half-maximal inhibition (IC₅₀) of 26 μM. Zn²⁺ slows voltage-dependent current kinetics, shifts the voltage-dependent activation to more negative potentials, and alters hyperpolarization-induced conformational changes of the voltage sensor. Our data suggest that extracellular Zn²⁺ inhibits HCNL1 currents by multiple mechanisms, including modulation of channel gating. Two histidine residues located at the extracellular side of the VSD might weakly contribute to Zn²⁺ coordination: mutants with either histidine replaced with alanine show modest shifts of the IC₅₀ values to higher concentrations. Interestingly, Zn²⁺ inhibits HCNL1 at even lower concentrations from the intracellular side (IC₅₀ ≈ 0.5 μM). A histidine residue at the intracellular end of S1 (position 50) is important for Zn²⁺ binding: much higher Zn²⁺ concentrations are required to inhibit the mutant HCNL1-H50A (IC₅₀ ≈ 106 μM). We anticipate that Zn²⁺ will be a useful ion to study the structure-function relationship of HCNL1 as well as the physiological role of HCNL1 in zebrafish sperm.

Under standard physiological conditions, budding relies on asymmetries, including differences in leaflet composition, area, and osmotic conditions, and involves large curvature changes in nanoscale lipid vesicles. So far, the combined impact of asymmetry and high curvatures on budding has remained unknown. Here, using the continuum elastic theory, the budding pathway is detailed under realistic conditions. The model enables a quantitative description of the budding process and the budded state of both ideally and nonideally mixed lipid nanoscale vesicles. It shows that budding is less favored in smaller vesicles but that lipid demixing can significantly reduce its energy barrier, and yet high compositional deviations of more than 7% between the bud and vesicle only occur with phase separation on the bud.

Embryonic development is orchestrated by the action of morphogens, which spread out from a local source and activate, in a field of target cells, different cellular programs based on their concentration gradient. Fibroblast growth factor 8 (Fgf8) is a morphogen with important functions in embryonic organizing centers. It forms a gradient in the extracellular space by free diffusion, interaction with the extracellular matrix (ECM), and receptor-mediated endocytosis. However, morphogen gradient regulation by ECM is still poorly understood. Here, we show that specific heparan sulfate proteoglycans (HSPGs) bind Fgf8 with different affinities directly in the ECM of living zebrafish embryos, thus affecting its diffusion and signaling. Using single-molecule fluorescence correlation spectroscopy, we quantify this binding in vivo, and find two different modes of interaction. First, reducing or increasing the concentration of specific HSPGs in the extracellular space alters Fgf8 diffusion and, thus, its gradient shape. Second, ternary complex formation of Fgf8 ligand with Fgf receptors and HSPGs at the cell surface requires HSPG attachment to the cell membrane. Together, our results show that graded Fgf8 morphogen distribution is achieved by constraining free Fgf8 diffusion through successive interactions with HSPGs at the cell surface and in ECM space.

Chromaffin cells of the adrenal medulla have an important role in the sympathetic stress response. They secrete catecholamines and other hormones into the bloodstream upon stimulation by the neurotransmitter pituitary adenylate cyclase-activating polypeptide (PACAP). PACAP causes a long-lasting and robust secretory response from chromaffin cells. However, the cellular mechanisms by which PACAP causes secretion remain unclear. Our previous work showed that the secretory response to PACAP relies on signaling through phospholipase C epsilon (PLCε). The objective of this study was to clarify the role of signaling events downstream of PLCε. Here, it is demonstrated that a brief exposure of chromaffin cells to PACAP caused diacylglycerol (DAG) production-a process that was dependent on PLCε activity. DAG then activated protein kinase C (PKC), prompting its redistribution to the plasma membrane. PKC activation was important for the increases in cytosolic Ca²⁺ and exocytosis that were evoked by PACAP. Indeed, pharmacological inhibition of PKC with NPC 15437, a competitive inhibitor of DAG binding, significantly disrupted the secretory response. NPC 15437 application also eliminated PACAP-stimulated effects on the readily releasable pool size, the Ca²⁺ sensitivity of granule fusion, and the voltage dependence of Ca²⁺ channel activation. Quantitative PCR revealed PKCβ, PKCε, and PKCμ to be highly expressed in the mouse chromaffin cell. Genetic knockdown of PKCβ and PKCε disrupted PACAP-evoked secretion, while knockdown of PKCμ had no measurable effect. This study highlights important roles for PKC signaling in a highly regulated pathway for exocytosis that is stimulated by PACAP.

We review empirical methods that can be used to provide physical descriptions of dynamic cellular processes during development and disease. Our focus will be nonspatial descriptions and the inference of underlying interaction networks including cell-state lineages, gene regulatory networks, and molecular interactions in living cells. Our overarching questions are: How much can we learn from just observing? To what degree is it possible to infer causal and/or precise mathematical relationships from observations? We restrict ourselves to data sets arising from only observations, or experiments in which minimal perturbations have taken place to facilitate observation of the systems as they naturally occur. We discuss analysis perspectives in order from those offering the least descriptive power but requiring the least assumptions such as statistical associations. We end with those that are most descriptive, but require stricter assumptions and more previous knowledge of the systems such as causal inference and dynamical systems approaches. We hope to provide and encourage the use of a wide array of options for quantitative cell biologists to learn as much as possible from their observations at all stages of understanding of their system of interest. Finally, we provide our own recipe of how to empirically determine quantitative relationships and growth laws from live-cell microscopy data, the resultant predictions of which can then be verified with perturbation experiments. We also include an extended supplement that describes further inference algorithms and theory for the interested reader.

The process of biological fate decision regulated by gene regulatory networks involves numerous complex dynamical interactions among many components. Mathematical modeling typically employed ordinary differential equations and steady-state analysis, which has yielded valuable quantitative insights. However, stable states predicted by theoretical models often fail to capture transient or metastable phenomena that occur during most observation periods in experimental or real biological systems. We attribute this discrepancy to the omission of dynamic processes of various complex interactions. Here, we demonstrate the influence of delays in gene regulatory steps and the timescales of the external induction on the dynamic processes of the fate decision in inducible bistable systems. We propose that steady-state parameters determine the landscape of fate decision. However, during the dynamic evolution along the landscape, the unequal delays of biochemical interactions as well as the timescale of external induction cause deviations in the differentiation trajectories, leading to the formation of new transient distributions that persist long term. Our findings emphasize the importance of considering dynamic processes in fate decision instead of relying solely on steady-state analysis. We provide insights into the interpretation of experimental phenomena and offer valuable guidance for future efforts in dynamical modeling and synthetic biology design.

Synaptic vesicle clusters or pools are functionally important constituents of chemical synapses. In the so-called reserve and the active pools, neurotransmitter-loaded synaptic vesicles (SVs) are stored and conditioned for fusion with the synaptic membrane and subsequent neurotransmitter release during synaptic activity. Vesicle clusters can be considered as so-called membraneless compartments, which form by liquid-liquid phase separation. Synapsin as one of the most abundant synaptic proteins has been identified as a major driver of pool formation. It has been shown to induce liquid-liquid phase separation and form condensates on its own in solution, but also has been shown to integrate vesicles into condensates in vitro. In this process, the intrinsically disordered region of synapsin is believed to play a critical role. Here, we first investigate the solution structure of synapsin and SVs separately by small-angle x-ray scattering. In the limit of low momentum transfer q, the scattering curve for synapsin gives clear indication for supramolecular aggregation (condensation). We then study mixtures of SVs and synapsin-forming condensates, aiming at the morphology and intervesicle distances, i.e., the structure of the condensates in solution. To obtain the structure factor S(q) quantifying intervesicle correlation, we divide the scattering curve of condensates by that of pure SV suspensions. Analysis of S(q) in combination with numerical simulations of cluster aggregation indicates a noncompact fractal-like vesicular fluid with rather short intervesicle distances at the contact sites.

Experimental studies of collective dynamics in lipid bilayers have been challenging due to the energy resolution required to observe these low-energy phonon-like modes. However, inelastic x-ray scattering (IXS) measurements-a technique for probing vibrations in soft and biological materials-are now possible with sub-meV resolution, permitting direct observation of low-energy, phonon-like modes in lipid membranes. Here, IXS measurements with sub-meV energy resolution reveal a low-energy optic-like phonon mode at roughly 3 meV in the liquid-ordered (L_o) and liquid-disordered phases of a ternary lipid mixture. This mode is only observed experimentally at momentum transfers greater than 5 nm^-1 in the L_o system. A similar gapped mode is also observed in all-atom molecular dynamics (MD) simulations of the same mixture, indicating that the simulations accurately represent the fast, collective dynamics in the L_o phase. Its optical nature and the Q range of the gap together suggest that the observed mode is due to the coupled motion of cholesterol-lipid pairs, separated by several hydrocarbon chains within the membrane plane. Analysis of the simulations provides molecular insight into the origin of the mode in transient, nanoscale substructures of hexagonally packed hydrocarbon chains. This nanoscale hexagonal packing was previously reported based on MD simulations and, later, by NMR measurements. Here, however, the integration of IXS and MD simulations identifies a new signature of the L_o substructure in the collective lipid dynamics, thanks to the recent confluence of IXS sensitivity and MD simulation capabilities.

Three analog solvatochromic probes, Laurdan, Prodan, and Acdan, are extensively used in the study of biological sciences. Their locations in lipid membranes vary greatly in depth, and their fluorescence responds to their surrounding environment based on their corresponding locations in the membrane. Utilizing the fluorescence lifetimes (τ) and emission peak positions (λ) acquired from the time-resolved emission spectrum, one can effectively determine the local lipid environment using the analytical approach, referred to as τ and λ plots. Herein, a τ and λ plot was created using the aforementioned probes to expand the analytical field according to their location. Furthermore, the solvent modeling method in the τ and λ plot was upgraded to artificially emulate the complex environment in lipid membranes by utilizing liquid paraffin and glycerol to assess the contribution of viscosity to each fluorescence distribution. According to the results from a series of solvent mixtures, the effect of solvent viscosity on lifetime values was confirmed in the short lifetime region (τ < 3 ns). However, it was impossible to emulate the longer than 4 ns lifetime values observed in lipid membranes containing 1,2-dipalmitoyl-sn-glycero-3-phosphocholine in the range of viscosity applied in this study. From the insight of the limiting anisotropy (r_∞), the τ and λ plot was divided into a solvent-like region with an isotropic environment (r_∞ < 0.15) and a region highly ordered enough to define it as an anisotropic environment (0.15 < r_∞) at τ = 4 ns. Also, the membrane-specific distribution was illustrated as 4 ns < τ and λ < 460 nm from this work. An updated analytical model was created to visualize multiple fluorescence components of each probe in six types of lipid bilayers, confirming the different distributions between these probes. Our results well illustrate the multiplicity of lipid environments modeled with solvent and ordered environments in each lipid bilayer system.

Solutions of the intrinsically disordered, low-complexity domain of the FUS protein (FUS-LC) undergo liquid-liquid phase separation (LLPS) below a temperature T_LLPS. To investigate whether local conformational distributions are detectably different in the homogeneous (i.e., single-phase) and phase-separated states of FUS-LC, we performed solid-state NMR (ssNMR) measurements on solutions that were frozen on submillisecond timescales after equilibration at temperatures well above (50°C) or well below (4°C) T_LLPS. Measurements were performed at 25 K with signal enhancements from dynamic nuclear polarization. Crosspeak patterns in two-dimensional ssNMR spectra of rapidly frozen solutions in which FUS-LC was uniformly ¹⁵N,¹³C labeled were found to be nearly identical for the two states. Similar results were obtained for solutions in which FUS-LC was labeled only at Thr, Tyr, and Gly residues, as well as solutions of a FUS construct in which five specific residues were labeled by ligation of synthetic and recombinant fragments. These experiments show that local conformational distributions are nearly the same in the homogeneous and phase-separated solutions, despite the much greater protein concentrations and more abundant intermolecular interactions within phase-separated, protein-rich "droplets." Comparison of the experimental results with simulations of the sensitivity of two-dimensional ssNMR crosspeaks to changes in populations of β strand-like conformations suggests that changes in conformational distributions are no larger than 5-10%.