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.

Loss of ZNF148 enhances insulin secretion in human pancreatic ß cells.

Insulin secretion from pancreatic ß cells is essential to the maintenance of glucose homeostasis. Defects in this process result in diabetes. Identifying genetic regulators that impair insulin secretion is crucial for the identification of novel therapeutic targets. Here, we show that reduction of ZNF148 in human islets, and its deletion in stem cell-derived ß cells (SC-ß cells), enhances insulin secretion. Transcriptomics of ZNF148-deficient SC-ß cells identifies increased expression of annexin and S100 genes whose proteins form tetrameric complexes involved in regulation of insulin vesicle trafficking and exocytosis. ZNF148 in SC-ß cells prevents translocation of annexin A2 from the nucleus to its functional place at the cell membrane via direct repression of S100A16 expression. These findings point to ZNF148 as a regulator of annexin-S100 complexes in human ß cells and suggest that suppression of ZNF148 may provide a novel therapeutic strategy to enhance insulin secretion.

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.

Soft X-ray tomography to map and quantify organelle interactions at the mesoscale.

Inter-organelle interactions are a vital part of normal cellular function; however, these have proven difficult to quantify due to the range of scales encountered in cell biology and the throughput limitations of traditional imaging approaches. Here, we demonstrate that soft X-ray tomography (SXT) can be used to rapidly map ultrastructural reorganization and inter-organelle interactions in intact cells. SXT takes advantage of the naturally occurring, differential X-ray absorption of the carbon-rich compounds in each organelle. Specifically, we use SXT to map the spatiotemporal evolution of insulin vesicles and their co-localization and interaction with mitochondria in pancreatic ß cells during insulin secretion and in response to different stimuli. We quantify changes in the morphology, biochemical composition, and relative position of mitochondria and insulin vesicles. These findings highlight the importance of a comprehensive and unbiased mapping at the mesoscale to characterize cell reorganization that would be difficult to detect with other existing methodologies.

A new visual design language for biological structures in a cell.

As part of a project to build a spatiotemporal model of the pancreatic ß-cell, we are creating an immersive experience called "World in a Cell" that can be used to integrate and create new educational tools. To do this, we have developed a new visual design language that uses tetrahedral building blocks to express the structural features of biological molecules and organelles in crowded cellular environments. The tetrahedral language enables more efficient animation and user interaction in an immersive environment.

The use of soft X-ray tomography to explore mitochondrial structure and function.

BACKGROUND: Mitochondria are cellular organelles responsible for energy production, and dysregulation of the mitochondrial network is associated with many disease states. To fully characterize the mitochondrial network's structure and function, a three-dimensional whole cell mapping technique is required. SCOPE OF REVIEW: This review highlights the use of soft X-ray tomography (SXT) as a relatively high-throughput approach to quantify mitochondrial structure and function under multiple cellular conditions. MAJOR CONCLUSIONS: The use of SXT opens the door for mapping cellular rearrangements during critical processes such as insulin secretion, stem cell differentiation, or disease progression. SXT provides unique information such as biochemical compositions or molecular densities of organelles and allows for unbiased, label-free imaging of intact whole cells. Mapping mitochondria in the context of the near-native cellular environment will reveal more information regarding mitochondrial network functions within the cell.

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.

Live-cell imaging of glucose-induced metabolic coupling of ß and α cell metabolism in health and type 2 diabetes.

Type 2 diabetes is characterized by ß and α cell dysfunction. We used phasor-FLIM (Fluorescence Lifetime Imaging Microscopy) to monitor oxidative phosphorylation and glycolysis in living islet cells before and after glucose stimulation. In healthy cells, glucose enhanced oxidative phosphorylation in ß cells and suppressed oxidative phosphorylation in α cells. In Type 2 diabetes, glucose increased glycolysis in ß cells, and only partially suppressed oxidative phosphorylation in α cells. FLIM uncovers key perturbations in glucose induced metabolism in living islet cells and provides a sensitive tool for drug discovery in diabetes.

Sevoflurane or isoflurane anaesthesia? A prospective, randomised blinded clinical trial in horses undergoing elective surgery.

BACKGROUND: Isoflurane is the only volatile anaesthetic agent licensed for equine use in the United Kingdom, but sevoflurane is also commonly used. The two agents have rarely been compared for use in clinical elective surgery. METHODS: This single centre, prospective, randomised, blinded clinical investigation recruited 101 healthy client owned horses undergoing elective surgery. Anaesthesia was standardised and horses randomly assigned to receive isoflurane (I) or sevoflurane (S) for maintenance of anaesthesia in 100% oxygen. Horses were ventilated to normocapnia and received intravenous fluid therapy and haemodynamic support with dobutamine to maintain mean arterial blood pressure above 60 mm Hg. Recovery was timed and video-recorded to allow offline evaluation by two experienced clinicians unaware of the volatile agent used. No post-anaesthetic sedation was administered. RESULTS: There was no significant difference between groups in terms of haemodynamic support required during anaesthesia nor in quality or duration of recovery. Inotropic support to maintain MAP above 60 mm Hg was required by 67 of 101 (67%) of horses. Five horses in the I group required additional ketamine or thiopentone to improve the plane of anaesthesia. CONCLUSIONS: Haemodynamic support needed during anaesthesia as well as the duration and quality of recovery were similar with isoflurane and sevoflurane.

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.

Visualizing insulin vesicle neighborhoods in ß cells by cryo-electron tomography.

Subcellular neighborhoods, comprising specific ratios of organelles and proteins, serve a multitude of biological functions and are of particular importance in secretory cells. However, the role of subcellular neighborhoods in insulin vesicle maturation is poorly understood. Here, we present single-cell multiple distinct tomogram acquisitions of ß cells for in situ visualization of distinct subcellular neighborhoods that are involved in the insulin vesicle secretory pathway. We propose that these neighborhoods play an essential role in the specific function of cellular material. In the regions where we observed insulin vesicles, a measurable increase in both the fraction of cellular volume occupied by vesicles and the average size (diameter) of the vesicles was apparent as sampling moved from the area near the nucleus toward the plasma membrane. These findings describe the important role of the nanometer-scale organization of subcellular neighborhoods on insulin vesicle maturation.

Visualizing subcellular rearrangements in intact ß cells using soft x-ray tomography.

Characterizing relationships between cell structures and functions requires mesoscale mapping of intact cells showing subcellular rearrangements following stimulation; however, current approaches are limited in this regard. Here, we report a unique application of soft x-ray tomography to generate three-dimensional reconstructions of whole pancreatic ß cells at different time points following glucose-stimulated insulin secretion. Reconstructions following stimulation showed distinct insulin vesicle distribution patterns reflective of altered vesicle pool sizes as they travel through the secretory pathway. Our results show that glucose stimulation caused rapid changes in biochemical composition and/or density of insulin packing, increased mitochondrial volume, and closer proximity of insulin vesicles to mitochondria. Costimulation with exendin-4 (a glucagon-like peptide-1 receptor agonist) prolonged these effects and increased insulin packaging efficiency and vesicle maturation. This study provides unique perspectives on the coordinated structural reorganization and interactions of organelles that dictate cell responses.

Biased Signaling of the G-Protein-Coupled Receptor ß2AR Is Governed by Conformational Exchange Kinetics.

G-protein-coupled receptors (GPCRs) mediate a wide range of human physiological functions by transducing extracellular ligand binding events into intracellular responses. GPCRs can activate parallel, independent signaling pathways mediated by G proteins or ß-arrestins. Whereas "balanced" agonists activate both pathways equally, "biased" agonists dominantly activate one pathway, which is of interest for designing GPCR-targeting drugs because it may mitigate undesirable side effects. Previous studies demonstrated that ß-arrestin activation is associated with transmembrane helix VII (TM VII) of GPCRs. Here, single-molecule fluorescence spectroscopy with the ß2-adrenergic receptor (ß2AR) in the ligand-free state showed that TM VII spontaneously fluctuates between one inactive and one active-like conformation. The presence of the ß-arrestin-biased agonist isoetharine prolongs the dwell time of TM VII in the active-like conformation compared with the balanced agonist formoterol, suggesting that ligands can induce signaling bias by modulating the kinetics of receptor conformational exchange.

Comparison of the effects of buprenorphine and methadone in combination with medetomidine followed by intramuscular alfaxalone for anaesthesia of cats undergoing ovariohysterectomy.

OBJECTIVES: The aim of this study was to compare the quality of anaesthesia and analgesia between methadone and buprenorphine in combination with medetomidine after induction with intramuscular (IM) alfaxalone in cats undergoing ovariohysterectomy. METHODS: Fifty-one female cats (American Society of Anesthesiologists status I-II), with a median age of 12 months (range 2-60 months), weighing a mean ± SD of 2.5 ± 0.5 kg, were recruited to the study. Cats were randomly allocated to receive medetomidine (600 µg/m2) and buprenorphine (180 µg/m2) (group MB) or medetomidine (500 µg/m2) and methadone (5 mg/m2) (group MM) IM. Anaesthesia was induced 15 mins later using alfaxalone (3 mg/kg) IM. Anaesthesia was maintained with isoflurane in oxygen. All cats received meloxicam preoperatively. Quality of premedication and induction and intraoperative physiological parameters were recorded. Atipamezole (50% of medetomidine dose) was administered at the end of surgery. Cats were assessed postoperatively by the same blinded observer using a simple descriptive scale, numeric rating scale, dynamic interactive visual analogue scale (DIVAS) and UNESP-Botucatu multidimensional composite pain scales, at 10, 20 and 30 mins post-extubation. Parametric and non-parametric data were compared using Student's t-test or Mann-Whitney U-tests, respectively. RESULTS: Forty-one cats completed the study. No significant differences were detected between groups before or during anaesthesia. No cats required rescue analgesia. DIVAS scores at 10 mins were significantly less in the MM group compared with the MB. No differences between groups at any other time points were detected using the four metrology instruments. CONCLUSIONS AND RELEVANCE: Both protocols provided good anaesthesia conditions for ovariohysterectomy in the cat.

Elucidating the active δ-opioid receptor crystal structure with peptide and small-molecule agonists.

Selective activation of the δ-opioid receptor (DOP) has great potential for the treatment of chronic pain, benefitting from ancillary anxiolytic and antidepressant-like effects. Moreover, DOP agonists show reduced adverse effects as compared to µ-opioid receptor (MOP) agonists that are in the spotlight of the current "opioid crisis." Here, we report the first crystal structures of the DOP in an activated state, in complex with two relevant and structurally diverse agonists: the potent opioid agonist peptide KGCHM07 and the small-molecule agonist DPI-287 at 2.8 and 3.3 Å resolution, respectively. Our study identifies key determinants for agonist recognition, receptor activation, and DOP selectivity, revealing crucial differences between both agonist scaffolds. Our findings provide the first investigation into atomic-scale agonist binding at the DOP, supported by site-directed mutagenesis and pharmacological characterization. These structures will underpin the future structure-based development of DOP agonists for an improved pain treatment with fewer adverse effects.

Federating Structural Models and Data: Outcomes from A Workshop on Archiving Integrative Structures.

Structures of biomolecular systems are increasingly computed by integrative modeling. In this approach, a structural model is constructed by combining information from multiple sources, including varied experimental methods and prior models. In 2019, a Workshop was held as a Biophysical Society Satellite Meeting to assess progress and discuss further requirements for archiving integrative structures. The primary goal of the Workshop was to build consensus for addressing the challenges involved in creating common data standards, building methods for federated data exchange, and developing mechanisms for validating integrative structures. The summary of the Workshop and the recommendations that emerged are presented here.

The lipid phase preference of the adenosine A2A receptor depends on its ligand binding state.

Giant unilamellar protein vesicles (GUPs) were formed with the adenosine A2A receptor (A2AR) incorporated in the lipid bilayer and protein partitioning into the liquid ordered and liquid disordered phases was observed. When no ligand is bound, A2AR partitions preferentially into the liquid disordered phase of GUPs, while ligand-bound A2AR partitions into the liquid ordered phase.