Opportunities and Challenges in Building a Spatiotemporal Multi-scale Model of the Human Pancreatic ß Cell.

The construction of a predictive model of an entire eukaryotic cell that describes its dynamic structure from atomic to cellular scales is a grand challenge at the intersection of biology, chemistry, physics, and computer science. Having such a model will open new dimensions in biological research and accelerate healthcare advancements. Developing the necessary experimental and modeling methods presents abundant opportunities for a community effort to realize this goal. Here, we present a vision for creation of a spatiotemporal multi-scale model of the pancreatic ß-cell, a relevant target for understanding and modulating the pathogenesis of diabetes.

Allosteric Coupling of Drug Binding and Intracellular Signaling in the A2A Adenosine Receptor.

Signaling across cellular membranes, the 826 human G protein-coupled receptors (GPCRs) govern a wide range of vital physiological processes, making GPCRs prominent drug targets. X-ray crystallography provided GPCR molecular architectures, which also revealed the need for additional structural dynamics data to support drug development. Here, nuclear magnetic resonance (NMR) spectroscopy with the wild-type-like A2A adenosine receptor (A2AAR) in solution provides a comprehensive characterization of signaling-related structural dynamics. All six tryptophan indole and eight glycine backbone 15N-1H NMR signals in A2AAR were individually assigned. These NMR probes provided insight into the role of Asp522.50 as an allosteric link between the orthosteric drug binding site and the intracellular signaling surface, revealing strong interactions with the toggle switch Trp 2466.48, and delineated the structural response to variable efficacy of bound drugs across A2AAR. The present data support GPCR signaling based on dynamic interactions between two semi-independent subdomains connected by an allosteric switch at Asp522.50.

Bayesian metamodeling of complex biological systems across varying representations.

Comprehensive modeling of a whole cell requires an integration of vast amounts of information on various aspects of the cell and its parts. To divide and conquer this task, we introduce Bayesian metamodeling, a general approach to modeling complex systems by integrating a collection of heterogeneous input models. Each input model can in principle be based on any type of data and can describe a different aspect of the modeled system using any mathematical representation, scale, and level of granularity. These input models are 1) converted to a standardized statistical representation relying on probabilistic graphical models, 2) coupled by modeling their mutual relations with the physical world, and 3) finally harmonized with respect to each other. To illustrate Bayesian metamodeling, we provide a proof-of-principle metamodel of glucose-stimulated insulin secretion by human pancreatic ß-cells. The input models include a coarse-grained spatiotemporal simulation of insulin vesicle trafficking, docking, and exocytosis; a molecular network model of glucose-stimulated insulin secretion signaling; a network model of insulin metabolism; a structural model of glucagon-like peptide-1 receptor activation; a linear model of a pancreatic cell population; and ordinary differential equations for systemic postprandial insulin response. Metamodeling benefits from decentralized computing, while often producing a more accurate, precise, and complete model that contextualizes input models as well as resolves conflicting information. We anticipate Bayesian metamodeling will facilitate collaborative science by providing a framework for sharing expertise, resources, data, and models, as exemplified by the Pancreatic ß-Cell Consortium.

Kinetic and data-driven modeling of pancreatic ß-cell central carbon metabolism and insulin secretion.

Pancreatic ß-cells respond to increased extracellular glucose levels by initiating a metabolic shift. That change in metabolism is part of the process of glucose-stimulated insulin secretion and is of particular interest in the context of diabetes. However, we do not fully understand how the coordinated changes in metabolic pathways and metabolite products influence insulin secretion. In this work, we apply systems biology approaches to develop a detailed kinetic model of the intracellular central carbon metabolic pathways in pancreatic ß-cells upon stimulation with high levels of glucose. The model is calibrated to published metabolomics datasets for the INS1 823/13 cell line, accurately capturing the measured metabolite fold-changes. We first employed the calibrated mechanistic model to estimate the stimulated cell's fluxome. We then used the predicted network fluxes in a data-driven approach to build a partial least squares regression model. By developing the combined kinetic and data-driven modeling framework, we gain insights into the link between ß-cell metabolism and glucose-stimulated insulin secretion. The combined modeling framework was used to predict the effects of common anti-diabetic pharmacological interventions on metabolite levels, flux through the metabolic network, and insulin secretion. Our simulations reveal targets that can be modulated to enhance insulin secretion. The model is a promising tool to contextualize and extend the usefulness of metabolomics data and to predict dynamics and metabolite levels that are difficult to measure in vitro. In addition, the modeling framework can be applied to identify, explain, and assess novel and clinically-relevant interventions that may be particularly valuable in diabetes treatment.

Structural basis for selectivity and diversity in angiotensin II receptors.

The angiotensin II receptors AT1R and AT2R serve as key components of the renin-angiotensin-aldosterone system. AT1R has a central role in the regulation of blood pressure, but the function of AT2R is unclear and it has a variety of reported effects. To identify the mechanisms that underlie the differences in function and ligand selectivity between these receptors, here we report crystal structures of human AT2R bound to an AT2R-selective ligand and to an AT1R/AT2R dual ligand, capturing the receptor in an active-like conformation. Unexpectedly, helix VIII was found in a non-canonical position, stabilizing the active-like state, but at the same time preventing the recruitment of G proteins or ß-arrestins, in agreement with the lack of signalling responses in standard cellular assays. Structure-activity relationship, docking and mutagenesis studies revealed the crucial interactions for ligand binding and selectivity. Our results thus provide insights into the structural basis of the distinct functions of the angiotensin receptors, and may guide the design of new selective ligands.

Assessment of scoring functions to rank the quality of 3D subtomogram clusters from cryo-electron tomography.

Cryo-electron tomography provides the opportunity for unsupervised discovery of endogenous complexes in situ. This process usually requires particle picking, clustering and alignment of subtomograms to produce an average structure of the complex. When applied to heterogeneous samples, template-free clustering and alignment of subtomograms can potentially lead to the discovery of structures for unknown endogenous complexes. However, such methods require scoring functions to measure and accurately rank the quality of aligned subtomogram clusters, which can be compromised by contaminations from misclassified complexes and alignment errors. Here, we provide the first study to assess the effectiveness of more than 15 scoring functions for evaluating the quality of subtomogram clusters, which differ in the amount of structural misalignments and contaminations due to misclassified complexes. We assessed both experimental and simulated subtomograms as ground truth data sets. Our analysis showed that the robustness of scoring functions varies largely. Most scores were sensitive to the signal-to-noise ratio of subtomograms and often required Gaussian filtering as preprocessing for improved performance. Two scoring functions, Spectral SNR-based Fourier Shell Correlation and Pearson Correlation in the Fourier domain with missing wedge correction, showed a robust ranking of subtomogram clusters without any preprocessing and irrespective of SNR levels of subtomograms. Of these two scoring functions, Spectral SNR-based Fourier Shell Correlation was fastest to compute and is a better choice for handling large numbers of subtomograms. Our results provide a guidance for choosing an accurate scoring function for template-free approaches to detect complexes from heterogeneous samples.

Crystal structure of misoprostol bound to the labor inducer prostaglandin E2 receptor.

Misoprostol is a life-saving drug in many developing countries for women at risk of post-partum hemorrhaging owing to its affordability, stability, ease of administration and clinical efficacy. However, misoprostol lacks receptor and tissue selectivities, and thus its use is accompanied by a number of serious side effects. The development of pharmacological agents combining the advantages of misoprostol with improved selectivity is hindered by the absence of atomic details of misoprostol action in labor induction. Here, we present the 2.5 Å resolution crystal structure of misoprostol free-acid form bound to the myometrium labor-inducing prostaglandin E2 receptor 3 (EP3). The active state structure reveals a completely enclosed binding pocket containing a structured water molecule that coordinates misoprostol's ring structure. Modeling of selective agonists in the EP3 structure reveals rationales for selectivity. These findings will provide the basis for the next generation of uterotonic drugs that will be suitable for administration in low resource settings.

Publisher Correction: Crystal structure of misoprostol bound to the labor inducer prostaglandin E2 receptor.

In the version of this article originally published, the present address for Petr Popov was incorrectly listed as 'Koltech Institute of Science & Technology, Moscow, Russia'. The correct present address is 'Skolkovo Institute of Science and Technology, Moscow, Russia'. The error has been corrected in the HTML and PDF versions of the paper.

NMR structure and dynamics of the agonist dynorphin peptide bound to the human kappa opioid receptor.

The structure of the dynorphin (1-13) peptide (dynorphin) bound to the human kappa opioid receptor (KOR) has been determined by liquid-state NMR spectroscopy. (1)H and (15)N chemical shift variations indicated that free and bound peptide is in fast exchange in solutions containing 1 mM dynorphin and 0.01 mM KOR. Radioligand binding indicated an intermediate-affinity interaction, with a Kd of ∼200 nM. Transferred nuclear Overhauser enhancement spectroscopy was used to determine the structure of bound dynorphin. The N-terminal opioid signature, YGGF, was observed to be flexibly disordered, the central part of the peptide from L5 to R9 to form a helical turn, and the C-terminal segment from P10 to K13 to be flexibly disordered in this intermediate-affinity bound state. Combining molecular modeling with NMR provided an initial framework for understanding multistep activation of a G protein-coupled receptor by its cognate peptide ligand.

Single-molecule view of basal activity and activation mechanisms of the G protein-coupled receptor ß2AR.

Binding of extracellular ligands to G protein-coupled receptors (GPCRs) initiates transmembrane signaling by inducing conformational changes on the cytoplasmic receptor surface. Knowledge of this process provides a platform for the development of GPCR-targeting drugs. Here, using a site-specific Cy3 fluorescence probe in the human ß2-adrenergic receptor (ß2AR), we observed that individual receptor molecules in the native-like environment of phospholipid nanodiscs undergo spontaneous transitions between two distinct conformational states. These states are assigned to inactive and active-like receptor conformations. Individual receptor molecules in the apo form repeatedly sample both conformations, with a bias toward the inactive conformation. Experiments in the presence of drug ligands show that binding of the full agonist formoterol shifts the conformational distribution in favor of the active-like conformation, whereas binding of the inverse agonist ICI-118,551 favors the inactive conformation. Analysis of single-molecule dwell-time distributions for each state reveals that formoterol increases the frequency of activation transitions, while also reducing the frequency of deactivation events. In contrast, the inverse agonist increases the frequency of deactivation transitions. Our observations account for the high level of basal activity of this receptor and provide insights that help to rationalize, on the molecular level, the widely documented variability of the pharmacological efficacies among GPCR-targeting drugs.

A clinical evaluation of the pharmacokinetics and pharmacodynamics of intravenous alfaxalone in cyclodextrin in male and female rats following a loading dose and constant rate infusion.

OBJECTIVE: To characterise, as a clinical study, the pharmacokinetics and pharmacodynamics and describe the hypnotic effect of the neurosteroid alfaxalone (3α-hydroxy-5 α-pregnane-11, 20-dione) formulated with 2-hydroxypropyl-ß-cyclodextrin in male and female rats. STUDY DESIGN: Prospective, experimental laboratory study. ANIMALS: A total of 12 (six male and six female) adult, aged-matched Sprague Dawley rats. METHODS: Surgery and instrumentation was performed under isoflurane anaesthesia in an oxygen/nitrous oxide mixture (1:2) and local anaesthetic infiltration. All animals received a loading dose (1.67 mg kg-1 minute-1) for 2.5 minutes followed by a constant rate infusion (0.75 mg kg-1 minute-1) for 120 minutes of alfaxalone. Isoflurane and nitrous oxide was discontinued 2.5 minutes after the alfaxalone infusion started. Cardiorespiratory variables (heart rate, respiratory rate, arterial blood pressure and end tidal carbon dioxide tension) and clinical signs of anaesthetic depth were evaluated throughout anaesthesia. Carotid artery blood samples were collected at strategic time points for blood gas analysis, haematology, biochemistry, and plasma concentrations of alfaxalone. Plasma samples were assayed using liquid chromatography-mass spectrometry. RESULTS: There were significant differences between the sexes for plasma clearance (p=0.0008), half-life (p=0.0268) and mean residence time (p=0.027). Mean arterial blood pressure was significantly higher in the male rats (p=0.0255). CONCLUSIONS AND CLINICAL RELEVANCE: This study confirms that alfaxalone solubilised in 2-hydroxypropyl-ß-cyclodextrin provides excellent total intravenous anaesthesia in rats. Sex-based differences in pharmacokinetics and pharmacodynamics were demonstrated and must be considered when designing biomedical research models using alfaxalone.

Clinical comparison of alfaxalone, ketamine and propofol following medetomidine and methadone in dogs.

OBJECTIVE: To compare the clinical effects of alfaxalone, ketamine and propofol in dogs following premedication with medetomidine and methadone. STUDY DESIGN: Prospective, 'blinded' and randomized clinical study. ANIMALS: A total of 75 male dogs presented for neutering at a charity clinic. METHODS: Dogs were allocated to be administered alfaxalone, ketamine or propofol following premedication with medetomidine (20 µg kg-1) and methadone (0.2 mg kg-1). Dogs were temperament scored prior to premedication. Quality of sedation, induction of anaesthesia, recovery and recovery environment were scored by simple descriptive scales. Physiological variables during anaesthesia were recorded. Continuous numerical data were analysed using analysis of variance with repeated measures as necessary. Nonparametric data were analysed using Kruskal-Wallis tests and multiple comparisons using Dunn's test. Statistical significance was set at p < 0.05. RESULTS: The mean (± standard deviation) dose of alfaxalone was 0.6 ± 0.2 mg kg-1, that for ketamine was 1.5 ± 0.7 mg kg-1 and that for propofol was 0.8 ± 0.3 mg kg-1. Alfaxalone inductions were significantly smoother compared to ketamine but not to propofol. Only one of 75 of the inductions was deemed poor. There were no differences in cardiopulmonary variables between groups except immediately after induction of anaesthesia. There were no differences in quality of recovery between groups. CONCLUSIONS AND CLINICAL RELEVANCE: All three induction agents provided reliable, predictable anaesthesia conditions that were clinically indistinguishable and ideal for teaching anaesthesia skills. The medetomidine and methadone premedication resulted in profound, heavy sedation and the quality of induction of anaesthesia was better with alfaxalone compared to ketamine. No significant difference in induction quality was detected between alfaxalone and proprofol or propofol and ketamine, and these findings are likely to be of limited clinical significance when choosing an induction agent.

Pilot study of long-term anaesthesia in broiler chickens.

OBJECTIVE: To provide stable anaesthesia of long duration in broiler chickens in order to perform a terminal caecal ligated loop procedure. STUDY DESIGN: Prospective experimental study. ANIMALS: Seven clinically healthy broiler chickens (Gallus domesticus) aged 27-36 days, weighing 884-2000 g. METHODS: Anaesthesia was induced and maintained with isoflurane in oxygen. All birds underwent intermittent positive pressure ventilation for the duration. End-tidal carbon dioxide, peripheral haemoglobin oxygen saturation, heart rate and oesophageal temperature were monitored continuously. All birds received intraosseous fluids. Butorphanol (2 mg kg(-1)) was administered intramuscularly at two hourly intervals. Euthanasia by parenteral pentobarbitone was performed at the end of procedure. RESULTS: Stable anaesthesia was maintained in four chickens for durations ranging from 435 to 510 minutes. One bird died and one was euthanized after 130 and 330 minutes, respectively, owing to surgical complications and another died from anaesthetic complication after 285 minutes. CONCLUSIONS AND CLINICAL RELEVANCE: Long-term, stable anaesthesia is possible in clinically healthy chickens, provided complications such as hypothermia and hypoventilation are addressed and vital signs are carefully monitored. There are no known previous reports describing monitored, controlled anaesthesia of this duration in chickens.

The G protein-biased κ-opioid receptor agonist RB-64 is analgesic with a unique spectrum of activities in vivo.

The hypothesis that functionally selective G protein-coupled receptor (GPCR) agonists may have enhanced therapeutic benefits has revitalized interest for many GPCR targets. In particular, although κ-opioid receptor (KOR) agonists are analgesic with a low risk of dependence and abuse, their use is limited by a propensity to induce sedation, motor incoordination, hallucinations, and dysphoria-like states. Several laboratories have produced a body of work suggesting that G protein-biased KOR agonists might be analgesic with fewer side effects. Although that has been an intriguing hypothesis, suitable KOR-selective and G protein-biased agonists have not been available to test this idea. Here we provide data using a G protein-biased agonist, RB-64 (22-thiocyanatosalvinorin A), which suggests that KOR-mediated G protein signaling induces analgesia and aversion, whereas ß-arrestin-2 signaling may be associated with motor incoordination. Additionally, unlike unbiased KOR agonists, the G protein-biased ligand RB-64 does not induce sedation and does not have anhedonia-like actions, suggesting that a mechanism other than G protein signaling mediates these effects. Our findings provide the first evidence for a highly selective and G protein-biased tool compound for which many, but not all, of the negative side effects of KOR agonists can be minimized by creating G protein-biased KOR agonists.

Identification of novel functionally selective κ-opioid receptor scaffolds.

The κ-opioid receptor (KOR)-dynorphin system has been implicated in the control of affect, cognition, and motivation, and is thought to be dysregulated in mood and psychotic disorders, as well as in various phases of opioid dependence. KOR agonists exhibit analgesic effects, although the adverse effects produced by some KOR agonists, including sedation, dysphoria, and hallucinations, have limited their clinical use. Interestingly, KOR-mediated dysphoria, assessed in rodents as aversion, has recently been attributed to the activation of the p38 mitogen-activated protein kinase pathway following arrestin recruitment to the activated KOR. Therefore, KOR-selective G protein-biased agonists, which do not recruit arrestin, have been proposed to be more effective analgesics, without the adverse effects triggered by the arrestin pathway. As an initial step toward identifying novel biased KOR agonists, we applied a multifaceted screening strategy utilizing both in silico and parallel screening approaches. We identified several KOR-selective ligand scaffolds with a range of signaling bias in vitro. The arylacetamide-based scaffold includes both G protein- and ß-arrestin-biased ligands, while the endogenous peptides and the diterpene scaffolds are G protein biased. Interestingly, we found scaffold screening to be more successful than library screening in identifying biased ligands. Many of the identified functionally selective ligands are potent selective KOR agonists that are reported to be active in the central nervous system. They therefore represent excellent candidates for in vivo studies aiming at determining the behavioral effects mediated by specific KOR-mediated signaling cascades.

Insulator-based dielectrophoresis-assisted separation of insulin secretory vesicles.

Organelle heterogeneity and inter-organelle contacts within a single cell contribute to the limited sensitivity of current organelle separation techniques, thus hindering organelle subpopulation characterization. Here, we use direct current insulator-based dielectrophoresis (DC-iDEP) as an unbiased separation method and demonstrate its capability by identifying distinct distribution patterns of insulin vesicles from INS-1E insulinoma cells. A multiple voltage DC-iDEP strategy with increased range and sensitivity has been applied, and a differentiation factor (ratio of electrokinetic to dielectrophoretic mobility) has been used to characterize features of insulin vesicle distribution patterns. We observed a significant difference in the distribution pattern of insulin vesicles isolated from glucose-stimulated cells relative to unstimulated cells, in accordance with maturation of vesicles upon glucose stimulation. We interpret the difference in distribution pattern to be indicative of high-resolution separation of vesicle subpopulations. DC-iDEP provides a path for future characterization of subtle biochemical differences of organelle subpopulations within any biological system.

Subcellular Feature-Based Classification of α and ß Cells Using Soft X-ray Tomography.

The dysfunction of α and ß cells in pancreatic islets can lead to diabetes. Many questions remain on the subcellular organization of islet cells during the progression of disease. Existing three-dimensional cellular mapping approaches face challenges such as time-intensive sample sectioning and subjective cellular identification. To address these challenges, we have developed a subcellular feature-based classification approach, which allows us to identify α and ß cells and quantify their subcellular structural characteristics using soft X-ray tomography (SXT). We observed significant differences in whole-cell morphological and organelle statistics between the two cell types. Additionally, we characterize subtle biophysical differences between individual insulin and glucagon vesicles by analyzing vesicle size and molecular density distributions, which were not previously possible using other methods. These sub-vesicular parameters enable us to predict cell types systematically using supervised machine learning. We also visualize distinct vesicle and cell subtypes using Uniform Manifold Approximation and Projection (UMAP) embeddings, which provides us with an innovative approach to explore structural heterogeneity in islet cells. This methodology presents an innovative approach for tracking biologically meaningful heterogeneity in cells that can be applied to any cellular system.

In situ structure of actin remodeling during glucose-stimulated insulin secretion using cryo-electron tomography.

Actin mediates insulin secretion in pancreatic ß-cells through remodeling. Hampered by limited resolution, previous studies have offered an ambiguous depiction as depolymerization and repolymerization. We report the in situ structure of actin remodeling in INS-1E ß-cells during glucose-stimulated insulin secretion at nanoscale resolution. After remodeling, the actin filament network at the cell periphery exhibits three marked differences: 12% of actin filaments reorient quasi-orthogonally to the ventral membrane; the filament network mainly remains as cell-stabilizing bundles but partially reconfigures into a less compact arrangement; actin filaments anchored to the ventral membrane reorganize from a "netlike" to a "blooming" architecture. Furthermore, the density of actin filaments and microtubules around insulin secretory granules decreases, while actin filaments and microtubules become more densely packed. The actin filament network after remodeling potentially precedes the transport and release of insulin secretory granules. These findings advance our understanding of actin remodeling and its role in glucose-stimulated insulin secretion.