Journal of General Physiology最新文献

This JGP study (Collaço et al. https://doi.org/10.1085/jgp.202413563) reveals that in addition to voltage-gated Ca2+ and K+ channels, ω-grammotoxin-SIA also inhibits voltage-gated Na+ channel currents.

Regulation of ion channel expression on the plasma membrane is a major determinant of neuronal excitability, and identifying the underlying mechanisms of this expression is critical to our understanding of neurons. Here, we present two orthogonal strategies to label extracellular sites of the ion channel TRPV1 that minimally perturb its function. We use the amber codon suppression technique to introduce a non-canonical amino acid (ncAA) with tetrazine click chemistry, compatible with a trans-cyclooctene coupled fluorescent dye. Additionally, by inserting the circularly permutated HaloTag (cpHaloTag) in an extracellular loop of TRPV1, we can incorporate a fluorescent dye of our choosing. Optimization of ncAA insertion sites was accomplished by screening residue positions between the S1 and S2 transmembrane domains with elevated missense variants in the human population. We identified T468 as a rapid labeling site (∼5 min) based on functional and biochemical assays in HEK293T/17 cells. Through adapting linker lengths and backbone placement of cpHaloTag on the extracellular side of TRPV1, we generated a fully functional channel construct, TRPV1exCellHalo, with intact wild-type gating properties. We used TRPV1exCellHalo in a single molecule experiment to track TRPV1 on the cell surface and validate studies that show decreased mobility of the channel upon activation. The application of these extracellular label TRPV1 (exCellTRPV1) constructs to track surface localization of the channel will shed significant light on the mechanisms regulating its expression and provide a general scheme to introduce similar modifications to other cell surface receptors.

Thermosensation requires the activation of a unique collection of ion channels and receptors that work in concert to transmit thermal information. It is widely accepted that transient receptor potential melastatin 8 (TRPM8) activation is required for normal cold sensing; however, recent studies have illuminated major roles for other ion channels in this important somatic sensation. In addition to TRPM8, other TRP channels have been reported to contribute to cold transduction mechanisms in diverse sensory neuron populations, with both leak- and voltage-gated channels being identified for their role in the transmission of cold signals. Whether the same channels that contribute to physiological cold sensing also mediate noxious cold signaling remains unclear; however, recent work has found a conserved role for the kainite receptor, GluK2, in noxious cold sensing across species. Additionally, cold-sensing neurons likely engage in functional crosstalk with nociceptors to give rise to cold pain. This Review will provide an update on our understanding of the relationship between various ion channels in the transduction and transmission of cold and highlight areas where further investigation is required.

Hypertrophic cardiomyopathy (HCM) is a genetic disease of the heart characterized by thickening of the left ventricle (LV), hypercontractility, and impaired relaxation. HCM is caused primarily by heritable mutations in sarcomeric proteins, such as β myosin heavy chain. Until recently, medications in clinical use for HCM did not directly target the underlying contractile changes in the sarcomere. Here, we investigate a novel small molecule, RLC-1, identified in a bovine cardiac myofibril high-throughput screen. RLC-1 is highly dependent on the presence of a regulatory light chain to bind to cardiac myosin and modulate its ATPase activity. In demembranated rat LV trabeculae, RLC-1 decreased maximal Ca2+-activated force and Ca2+ sensitivity of force, while it increased the submaximal rate constant for tension redevelopment. In myofibrils isolated from rat LV, both maximal and submaximal Ca2+-activated force are reduced by nearly 50%. Additionally, the fast and slow phases of relaxation were approximately twice as fast as DMSO controls, and the duration of the slow phase was shorter. Structurally, x-ray diffraction studies showed that RLC-1 moved myosin heads away from the thick filament backbone and decreased the order of myosin heads, which is different from other myosin inhibitors. In intact trabeculae and isolated cardiomyocytes, RLC-1 treatment resulted in decreased peak twitch magnitude and faster activation and relaxation kinetics. In conclusion, RLC-1 accelerated kinetics and decreased force production in the demembranated tissue, intact tissue, and intact whole cells, resulting in a smaller cardiac twitch, which could improve the underlying contractile changes associated with HCM.

ω-Grammotoxin-SIA (GrTX-SIA) was originally isolated from the venom of the Chilean rose tarantula and demonstrated to function as a gating modifier of voltage-gated Ca2+ (CaV) channels. Later experiments revealed that GrTX-SIA could also inhibit voltage-gated K+ (KV) channel currents via a similar mechanism of action that involved binding to a conserved S3-S4 region in the voltage-sensing domains (VSDs). Since voltage-gated Na+ (NaV) channels contain homologous structural motifs, we hypothesized that GrTX-SIA could inhibit members of this ion channel family as well. Here, we show that GrTX-SIA can indeed impede the gating process of multiple NaV channel subtypes with NaV1.6 being the most susceptible target. Moreover, molecular docking of GrTX-SIA onto NaV1.6, supported by a p.E1607K mutation, revealed the voltage sensor in domain IV (VSDIV) as being a primary site of action. The biphasic manner in which current inhibition appeared to occur suggested a second, possibly lower-sensitivity binding locus, which was identified as VSDII by using KV2.1/NaV1.6 chimeric voltage-sensor constructs. Subsequently, the NaV1.6p.E782K/p.E838K (VSDII), NaV1.6p.E1607K (VSDIV), and particularly the combined VSDII/VSDIV mutant lost virtually all susceptibility to GrTX-SIA. Together with existing literature, our data suggest that GrTX-SIA recognizes modules in NaV channel VSDs that are conserved among ion channel families, thereby allowing it to act as a comprehensive ion channel gating modifier peptide.

Skeletal muscle, the major processor of dietary glucose, stores it in myriad glycogen granules. Their numbers vary with cellular location and physiological and pathophysiological states. AI models were developed to derive granular glycogen content from electron-microscopic images of human muscle. Two UNet-type semantic segmentation models were built: "Locations" classified pixels as belonging to different regions in the cell; "Granules" identified pixels within granules. From their joint output, a pixel fraction pf was calculated for images from patients positive (MHS) or negative (MHN) to a test for malignant hyperthermia susceptibility. pf was used to derive vf, the volume fraction occupied by granules. The relationship vf (pf) was derived from a simulation of volumes ("baskets") containing virtual granules at realistic concentrations. The simulated granules had diameters matching the real ones, which were measured by adapting a utility devised for calcium sparks. Applying this relationship to the pf measured in images, vf was calculated for every region and patient, and from them a glycogen concentration. The intermyofibrillar spaces and the sarcomeric I band had the highest granular content. The measured glycogen concentration was low enough to allow for a substantial presence of non-granular glycogen. The MHS samples had an approximately threefold lower concentration (significant in a hierarchical test), consistent with earlier evidence of diminished glucose processing in MHS. The AI models and the approach to infer three-dimensional magnitudes from two-dimensional images should be adaptable to other tasks on a variety of images from patients and animal models and different disease conditions.

This Commentary discusses the implications of a recent JGP study (Ríos et al. https://www.doi.org/10.1085/jgp.202413595) demonstrating an AI model to quantify glycogen granules.