Biology subjects

Kalwat, M. A.

Publications and source records attributed to Kalwat, M. A..

7 recordsLinked to original sources

bioRxiv2025

Unique and conserved endoplasmic reticulum stress responses in neuroendocrine cells

Endocrine cells are dedicated to the production and processing of hormones, from peptides to small molecules, to regulate key physiological processes, including glucose homeostasis and metabolism. Because of this relatively high productivity, endo-crine cells must handle a variety of stresses from oxidative stress to the unfolded protein response of the endoplasmic reticulum (UPRER). While much is known about the major pathways regulating the UPRER, the roles of endocrine cell type-specific, context-dependent, and time-dependent transcriptional changes are not well explored. To identify unique and shared responses to the UPRER across a subset of endocrine cell types, we tested representative lines for {beta}-cells (insulin), -cells (glucagon), {delta}-cells (somatostatin), X/A-cells (ghrelin), L-cells (glucagon-like peptide 1 (GLP1)), and thyrotropes (thyroid hormone and thyroglobulin). We exposed each cell type to the canonical ER stressor thapsigargin for 6 and 24 h, or vehicle for 24 h and performed mRNA sequencing. Analysis of the data showed all lines responded to thapsigargin. Comparisons of differentially expressed genes between each line revealed both shared and unique transcriptional signatures. These data represent a valuable mineable set of candidate genes that may have cell type-specific functions during the UPRER and have the potential to lead to a new understanding of how different endocrine cells mitigate or succumb to ER stress.

cell biology↗

bioRxiv2025

Identification of High-Risk Cells in Single-Cell Spatially Resolved Transcriptomics Data Using Deep Transfer Learning

SummaryThe examination of high-risk cells and regions in tissue samples from spatially resolved transcriptomics platforms offers meaningful insights into specific disease processes. For existing methods, while cell types or clusters can be identified and associated with disease attributes, individual cells are unable to be associated in the same manner. MethodDiag-nostic Evidence GAuge of Single-cells and spatial transcriptomics (DEGAS), solves the above problem by employing latent representations of gene expression data and domain adaptation to transfer disease attributes from patients to individual cells from single-cell RNA sequencing datasets. In this research, we present and evaluate DEGASs versatility in adapting to data arising from various single-cell spatially resolved transcriptomics (scSRT) platforms. DEGAS successfully identified high-risk cells and regions in liver hepatocellular carcinoma and skin cutaneous melanoma, which were validated through known markers. Additionally, DEGAS was applied to our newly generated Type II Diabetes Xenium dataset revealing high-risk cells within the tissue samples. Availability and ImplementationThe DEGAS software can be accessed at https://github.com/tsteelejohnson91/DEGAS. For the updated smoothing functions and associated codes, visit https://github.com/dchatter04/DEGAS-Spatial-Smoothing. Sources for the datasets reviewed are detailed in their respective sections. A description of some datasets, along with extra tables and figures, is provided in the Supplementary Materials file. Our newly generated Xenium data for Type II Diabetes can be found at https://doi.org/10.7303/syn68699752.

bioinformatics↗

bioRxiv2024

Target deconvolution of an insulin hypersecretion-inducer acting through VDAC1 with a distinct transcriptomic signature in beta-cells

Obesity, insulin resistance, and a host of environmental and genetic factors can drive hyperglycemia, causing {beta}-cells to compensate by increasing insulin production and secretion. In type 2 diabetes (T2D), {beta}-cells under these conditions eventually fail. Rare {beta}-cell diseases like congenital hyperinsulinism (HI) also cause inappropriate insulin secretion, and some HI patients develop diabetes. However, the mechanisms of insulin hypersecretion and how it causes {beta}-cell dysfunction are not fully understood. We previously discovered small molecules (e.g. SW016789) that cause insulin hypersecretion and lead to a loss in {beta}-cell function without cell death. Here, we uncover the protein target of SW016789 and provide the first time-course transcriptomic analysis of hypersecretory responses versus thapsigargin-mediated ER stress in {beta}-cells. In mouse MIN6 and human EndoC-{beta}H1 {beta}-cells, we identified and validated VDAC1 as a SW016789 target using photoaffinity proteomics, cellular thermal shift assays, siRNA, and small molecule inhibitors. SW016789 raises membrane potential to enhance Ca2+ influx, potentially through VDAC1. Chronically elevated intracellular Ca2+ appears to underpin the negative impacts of hypersecretion, as nifedipine protected against each small molecule hypersecretion inducer we tested. Using time- course RNAseq, we discovered that hypersecretion induced a distinct transcriptional pattern compared to ER stress. Clustering analyses led us to focus on ER-associated degradation (ERAD) as a potential mediator of the adaptive response. SW016789 reduced the abundance of ERAD substrate OS-9 and pharmacological inhibition of ERAD worsened {beta}-cell survival in response to hypersecretory stress. Changes in other ERAD components in MIN6 and EndoC-{beta}H1 at the protein level were minor with either SW016789 or thapsigargin. However, immunostaining for core ERAD components SEL1L, HRD1, and DERL3 in non-diabetic and T2D human pancreas revealed altered distributions of SEL1L/HRD1 and SEL1L/DERL3 rations in {beta}-cells of T2D islets, in alignment with altered ERAD in stressed {beta}-cells. We conclude that hypersecretory stimuli, including SW016789- mediated VDAC1 activation, cause enhanced Ca2+ influx and insulin release. Subsequent differential gene expression represents a {beta}-cell hypersecretory response signature that is reflected at the protein level for some, but not all genes. A better understanding of how {beta}-cells induce hypersecretion and the mechanisms of negative feedback on secretory rate may lead to the discovery of novel therapeutic targets for T2D and HI.

cell biology↗

bioRxiv2024

Identification of type 2 diabetes- and obesity-associated human β-cells using deep transfer learning

Diabetes affects >10% of adults worldwide and is caused by impaired production or response to insulin, resulting in chronic hyperglycemia. Pancreatic islet {beta}-cells are the sole source of endogenous insulin and our understanding of {beta}-cell dysfunction and death in type 2 diabetes (T2D) is incomplete. Single-cell RNA-seq data supports heterogeneity as an important factor in {beta}-cell function and survival. However, it is difficult to identify which {beta}-cell phenotypes are critical for T2D etiology and progression. Our goal was to prioritize specific disease-related {beta}-cell subpopulations to better understand T2D pathogenesis and identify relevant genes for targeted therapeutics. To address this, we applied a deep transfer learning tool, DEGAS, which maps disease associations onto single-cell RNA-seq data from bulk expression data. Independent runs of DEGAS using T2D or obesity status identified distinct {beta}-cell subpopulations. A singular cluster of T2D-associated {beta}-cells was identified; however, {beta}-cells with high obese-DEGAS scores contained two subpopulations derived largely from either non-diabetic or T2D donors. The obesity-associated non-diabetic cells were enriched for translation and unfolded protein response genes compared to T2D cells. We selected CDKN1C and DLK1 for validation by immunostaining in human pancreas sections from healthy and T2D donors. Both CDKN1C and DLK1 were heterogeneously expressed among {beta}-cells. CDKN1C was increased in {beta}-cells from T2D donors, in agreement with the DEGAS predictions, while DLK1 appeared depleted from T2D islets of some donors. In conclusion, DEGAS has the potential to advance our holistic understanding of the {beta}-cell transcriptomic phenotypes, including features that distinguish {beta}-cells in obese non-diabetic or lean T2D states. Future work will expand this approach to additional human islet omics datasets to reveal the complex multicellular interactions driving T2D.

bioinformatics↗

bioRxiv2022

Small molecule-mediated insulin hypersecretion induces transient unfolded protein response and loss of function in pancreatic islet beta cells

Pancreatic islet beta cells require a fine-tuned ER stress response for normal function; abnormal ER stress contributes to diabetes pathogenesis. Here, we identified a small molecule, SW016789, with time-dependent effects on beta cell ER stress and function. Acute treatment with SW016789 potentiated nutrient-induced calcium influx and insulin secretion, while chronic exposure to SW016789 transiently induced ER stress and shut down secretory function in a reversible manner. Distinct from the effects of thapsigargin, SW016789 did not affect beta cell viability or apoptosis, potentially due to a rapid induction of adaptive genes, weak signaling through the eIF2 kinase PERK, and lack of oxidative stress gene Txnip induction. We determined that SW016789 acted upstream of voltage-dependent calcium channels (VDCCs) and potentiated nutrient- but not KCl-stimulated calcium influx. Measurements of metabolomics, oxygen consumption rate, and G protein-coupled receptor signaling did not explain the potentiating effects of SW016789. In chemical co-treatment experiments we discovered synergy between SW016789 and activators of protein kinase C (PKC) and VDCCs, suggesting involvement of these pathways in the mechanism of action. Finally, chronically elevated calcium influx was required for the inhibitory impact of SW016789, as blockade of VDCCs protected human islets and MIN6 beta cells from hypersecretion-induced dysfunction. We conclude that beta cells undergoing this type of pharmacological hypersecretion have the capacity to suppress their function to mitigate ER stress and avoid apoptosis. These results have the potential to uncover beta cell ER stress mitigation factors and add support to beta cell rest strategies to preserve function.

cell biology↗

bioRxiv2018

BDNF/TrkB signaling in pancreatic islet beta cells

Adrenergic signaling is a well-known input into pancreatic islet function. Specifically, the insulin-secreting islet {beta} cell expresses the Gi/o-linked 2-adrenergic receptor, which upon activation suppresses insulin secretion. The use of adrenergic agonist epinephrine at micromolar doses may have supraphysiological effects. We found that pretreating {beta} cells with micromolar concentrations of epinephrine differentially inhibited activation of receptor tyrosine kinases. We chose TrkB as an example because of its relative sensitivity to the effects of epinephrine and due to its potential regulatory role in the {beta} cell. Our characterization of brain-derived neurotrophic factor (BDNF)-TrkB signaling in MIN6 {beta} cells showed that TrkB is activated by BDNF as expected, leading to canonical TrkB autophosphorylation and subsequent downstream signaling, as well as chronic effects on {beta} cell growth. Micromolar, but not nanomolar, concentrations of epinephrine blocked BDNF-induced TrkB autophosphorylation and downstream mitogen-activated protein kinase pathway activation, suggesting an inhibitory phenomenon at the receptor level. We determined epinephrine-mediated inhibition of TrkB activation to be Gi/o-dependent using pertussis toxin, arguing against an off-target effect of high dose epinephrine. Published data suggested that inhibition of potassium channels or phosphoinositide-3-kinase signaling may abrogate the negative effects of epinephrine, however these did not rescue TrkB signaling in our experiments. Taken together, these results show that 1) TrkB kinase signaling occurs in {beta} cells and 2) use of epinephrine in studies of insulin secretion requires careful consideration of concentration-dependent effects. BDNF-TrkB signaling in {beta} cells may underlie pro-survival or growth signaling and warrants further study.

cell biology↗

bioRxiv2018

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

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.

cell biology↗