bioRxiv Science⌕ Search

bioRxiv · 10.1101/337113

Chromomycin A2 potently inhibits glucose-stimulated insulin secretion from pancreatic beta cells.

Abstract

Enhancers or inhibitors of insulin secretion could become therapeutics as well as lead to the identification of requisite {beta}-cell regulatory pathways and increase our understanding of pancreatic islet function. Toward this goal, we previously used an insulin-linked luciferase that is co-secreted with insulin in MIN6 {beta}-cells to perform a high-throughput natural product screen for chronic effects on glucose-stimulated insulin secretion. Using multiple phenotypic analyses, we identified that one of the top natural product hits, chromomycin A2 (CMA2), potently inhibited insulin secretion through at least three mechanisms: disruption of Wnt signaling, interfering with {beta}-cell gene expression, and suppression of triggering calcium (Ca2+) influx. Chronic treatment with CMA2 largely ablated glucose-stimulated insulin secretion even post-washout, but did not inhibit glucose-stimulated generation of ATP or Ca2+ influx. However, by using the KATP channel-opener diazoxide, we uncovered defects in depolarization-induced Ca2+ influx which may contribute to the suppressed secretory response. Glucose-responsive ERK1/2 and S6 phosphorylation were also disrupted by chronic CMA2 treatment. The FUSION bioinformatic database indicated that the phenotypic effects of CMA2 clustered with a number of Wnt/GSK3 pathway-related genes. Consistently, CMA2 decreased GSK3 phosphorylation and suppressed activation of a {beta}-catenin activity reporter. CMA2 and a related compound mithramycin are described to have DNA-interaction properties, possibly abrogating transcription factor binding to critical {beta}-cell gene promoters. We observed that CMA2, but not mithramycin, suppressed expression of PDX1 and UCN3. However, neither expression of INSI/II nor insulin content was affected by chronic CMA2. The mechanisms of CMA2-induced insulin secretion defects may involve components both proximal and distal to Ca2+ influx. Therefore, CMA2 is an example of a chemical that can simultaneously disrupt {beta}-cell function through both non-cytotoxic and cytotoxic mechanisms. Future applications of CMA2 and similar aureolic acid analogs for disease therapies should consider the potential impacts on pancreatic islet function.

Source connections

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Kalwat, M. A., Hwang, I. H., Macho, J., Grzemska, M., Yang, J. Z., McGlynn, K., MacMillan, J. B., Cobb, M. H.. 2018-06-04. Chromomycin A2 potently inhibits glucose-stimulated insulin secretion from pancreatic beta cells.. https://doi.org/10.1101/337113

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Cigarette smoke extract and palmitic acid exposed patient-derived iPS- RPE cells as a model for AMD

Purpose: Age-related macular degeneration (AMD) is a multifactorial disease in which dysfunction and loss of retinal pigment epithelial (RPE) cells contribute to disease progression. Besides genetics, cigarette smoking and high fat diet are important environmental and metabolic risk factors for AMD and are associated with RPE dysfunction. However, the effects of combined environmental and metabolic stress on AMD-derived RPE cells remain poorly understood. In this study, we used patient-derived induced pluripotent stem cell-derived RPE (iPSC-RPE) cells to examine the effects of cigarette smoke extract (CSE) and palmitic acid (PA) on RPE cell function. Methods: iPSCs derived from non-AMD and AMD donors were differentiated into RPE cells and characterized based on morphology, RPE-specific marker expression, polarity, gene expression, and barrier function. Mature iPSC-RPE cells were exposed to different concentrations of CSE and PA to determine experimental conditions. Cell death, epithelial-to-mesenchymal transition (EMT)-like morphological changes, stress-related gene expression, RPE polarity, TEER, VEGF-A and PEDF secretion, and intracellular lipid accumulation were then evaluated following CSE, PA, or combined CSE and PA exposure. Results: Differentiated iPSC-RPE cells developed typical pigmented, hexagonal morphology, expressed RPE-specific markers, and formed polarized monolayers. Both CSE and PA increased cell death in a dose-dependent manner in the control and AMD-iPSC-RPE, with AMD-iPSC-RPE exhibiting greater susceptibility, particularly those from patients with dry AMD. CSE and PA also induced also induced EMT-like morphological changes and increased the expression of ZEB1, NQO1, and IL8. Furthermore, CSE and PA disrupted the polarized distribution of ZO-1 and Best1, significantly reduced the polarity ratio, decreased PEDF and VEGF-A secretion and increased intracellular lipid accumulation. Combined CSE and PA treatment produced more pronounced effects than either treatment alone in AMD lines. Conclusions: AMD- iPSC-RPE cells, particularly those derived from dry AMD donors, exhibit increased susceptibility to environmental and metabolic stress. Exposure to CSE and PA revealed this vulnerability through alterations in cell survival, stress responses, epithelial morphology, polarity, secretory function, and intracellular lipid accumulation. These findings highlight the effects of CSE and lipid stress on RPE metabolism and underscore the utility of patient-derived iPSC-RPE cells as a model for investigating how environmental and metabolic factors contribute to RPE dysfunction and AMD pathogenesis.

cell biology↗

Structural Determinants of Ligand-Mediated Hmg2 Mallostery

The sterol pathway is a conserved eukaryotic process that produces essential metabolites. Hmg-CoA reductase (HMGR) is a key rate limiting enzyme of the sterol pathway and is the most successful clinical target for managing cholesterol levels. However, determination of the structural features that are essential for its regulation remains elusive. Because of the conservation between mammals and yeast, for many years we have studied the structural features of a yeast Hmg2 isozyme of HMGR. Hmg2 is regulated by the mevalonate pathway isoprenoid GGPP. GGPP acts similarly to an allosteric ligand and appears to bind to a specific site on Hmg2, causing Hmg2 to undergo reversible misfolding. Misfolded Hmg2 is then recognized by the protein quality control mechanism known as the HRD pathway. Due to its similarity to allosteric regulation we have termed this ligand-dependent misfolding mallostery. In this work, we systematically probe each residue of the Hmg2 lumenal domain as well as assess the transmembrane domain and lumenal domain as independent domains and use in vivo and in vitro techniques to assess what regions are important for GGPP response. We identified stabilizing mutations within each loop of the lumenal domain but did not find mutants that were completely unresponsive to GGPP. When assessing the transmembrane domain and lumenal domain as two independent structures, we found that only the transmembrane domain responded to GGPP specifically in vitro. Our results suggest that GGPP binding occurs within the Hmg2 transmembrane domain and that the loops in the lumenal domain are required for transducing a mallosteric response to GGPP. Taken together, these data suggest a new model of Hmg2 regulation.

cell biology↗

RELAY: Relational In-Context Learning for Cellular Perturbation Prediction

Cellular responses to perturbations vary across multiple experimental variables, such as perturbation identity, cell type, donor, and dose, defining a multidimensional condition space in which each measured population occupies one coordinate. Existing methods predict unmeasured conditions using explicit representations of these variable values, generalizing unseen values therefore depends on the availability and quality of such representations. We present RELAY, a relational in-context model that predicts unmeasured coordinates from measured responses at related coordinates. For each target, RELAY uses measured control--perturbed pairs from conditions that share one or more experimental variables with the target, such as the same perturbation in another cell type. The model receives only which variables are shared, not their values, and uses these demonstrations to predict the target response. We evaluate RELAY on chemical, genetic, and cytokine perturbation datasets under two settings: unseen combinations, where test values are individually observed during training but not in their target combinations, and unseen variable values, where test values are introduced only through context at inference. RELAY outperforms existing in-context methods on unseen variable values and supervised perturbation-prediction methods on unseen combinations. All resources will be open sourced, including code and data.

cell biology↗