ABSTRACT
Variants at the SLC30A8 locus are associated with type 2 diabetes (T2D) risk. The lead variant, rs13266634, encodes an amino acid change, Arg325Trp (R325W), at the C-terminus of the secretory granule-enriched zinc transporter, ZnT8. Although this protein-coding variant was previously thought to be the sole driver of T2D risk at this locus, recent studies have provided evidence for lowered expression of SLC30A8 mRNA in protective allele carriers. In the present study, we examined multiple variants that influence SLC30A8 allele-specific expression. Epigenomic mapping has previously identified an islet-selective enhancer cluster at the SLC30A8 locus, hosting multiple T2D risk and cASE associations, which is spatially associated with the SLC30A8 promoter and additional neighboring genes. Here, we show that deletion of variant-bearing enhancer regions using CRISPR-Cas9 in human-derived EndoC-ßH3 cells lowers the expression of SLC30A8 and several neighboring genes and improves glucose-stimulated insulin secretion. While downregulation of SLC30A8 had no effect on beta cell survival, loss of UTP23, RAD21, or MED30 markedly reduced cell viability. Although eQTL or cASE analyses in human islets did not support the association between these additional genes and diabetes risk, the transcriptional regulator JQ1 lowered the expression of multiple genes at the SLC30A8 locus and enhanced stimulated insulin secretion.
Subject(s)
Diabetes Mellitus, Type 2 , Enhancer Elements, Genetic , Insulin-Secreting Cells , Zinc Transporter 8 , Humans , Zinc Transporter 8/genetics , Zinc Transporter 8/metabolism , Insulin-Secreting Cells/metabolism , Diabetes Mellitus, Type 2/genetics , Diabetes Mellitus, Type 2/metabolism , Cell Survival/genetics , Genetic Variation , Insulin/metabolism , Cell LineABSTRACT
Liver kinase B1 (LKB1/STK11) is an important regulator of pancreatic ß-cell identity and function. Elimination of Lkb1 from the ß-cell results in improved glucose-stimulated insulin secretion and is accompanied by profound changes in gene expression, including the upregulation of several neuronal genes. The mechanisms through which LKB1 controls gene expression are, at present, poorly understood. Here, we explore the impact of ß cell-selective deletion of Lkb1 on chromatin accessibility in mouse pancreatic islets. To characterize the role of LKB1 in the regulation of gene expression at the transcriptional level, we combine these data with a map of islet active transcription start sites and histone marks. We demonstrate that LKB1 elimination from ß-cells results in widespread changes in chromatin accessibility, correlating with changes in transcript levels. Changes occurred in hundreds of promoter and enhancer regions, many of which were close to neuronal genes. We reveal that dysregulated enhancers are enriched in binding motifs for transcription factors (TFs) important for ß-cell identity, such as FOXA, MAFA or RFX6, and we identify microRNAs (miRNAs) that are regulated by LKB1 at the transcriptional level. Overall, our study provides important new insights into the epigenetic mechanisms by which LKB1 regulates ß-cell identity and function.
Subject(s)
Epigenesis, Genetic , Insulin-Secreting Cells , Protein Serine-Threonine Kinases , Animals , Insulin-Secreting Cells/metabolism , Mice , Protein Serine-Threonine Kinases/genetics , Protein Serine-Threonine Kinases/metabolism , MicroRNAs/genetics , MicroRNAs/metabolism , Mice, Knockout , AMP-Activated Protein Kinases/metabolism , AMP-Activated Protein Kinases/genetics , Promoter Regions, Genetic , Mice, Inbred C57BL , MaleABSTRACT
AIMS/HYPOTHESIS: People with type 2 diabetes are heterogeneous in their disease trajectory, with some progressing more quickly to insulin initiation than others. Although classical biomarkers such as age, HbA1c and diabetes duration are associated with glycaemic progression, it is unclear how well such variables predict insulin initiation or requirement and whether newly identified markers have added predictive value. METHODS: In two prospective cohort studies as part of IMI-RHAPSODY, we investigated whether clinical variables and three types of molecular markers (metabolites, lipids, proteins) can predict time to insulin requirement using different machine learning approaches (lasso, ridge, GRridge, random forest). Clinical variables included age, sex, HbA1c, HDL-cholesterol and C-peptide. Models were run with unpenalised clinical variables (i.e. always included in the model without weights) or penalised clinical variables, or without clinical variables. Model development was performed in one cohort and the model was applied in a second cohort. Model performance was evaluated using Harrel's C statistic. RESULTS: Of the 585 individuals from the Hoorn Diabetes Care System (DCS) cohort, 69 required insulin during follow-up (1.0-11.4 years); of the 571 individuals in the Genetics of Diabetes Audit and Research in Tayside Scotland (GoDARTS) cohort, 175 required insulin during follow-up (0.3-11.8 years). Overall, the clinical variables and proteins were selected in the different models most often, followed by the metabolites. The most frequently selected clinical variables were HbA1c (18 of the 36 models, 50%), age (15 models, 41.2%) and C-peptide (15 models, 41.2%). Base models (age, sex, BMI, HbA1c) including only clinical variables performed moderately in both the DCS discovery cohort (C statistic 0.71 [95% CI 0.64, 0.79]) and the GoDARTS replication cohort (C 0.71 [95% CI 0.69, 0.75]). A more extensive model including HDL-cholesterol and C-peptide performed better in both cohorts (DCS, C 0.74 [95% CI 0.67, 0.81]; GoDARTS, C 0.73 [95% CI 0.69, 0.77]). Two proteins, lactadherin and proto-oncogene tyrosine-protein kinase receptor, were most consistently selected and slightly improved model performance. CONCLUSIONS/INTERPRETATION: Using machine learning approaches, we show that insulin requirement risk can be modestly well predicted by predominantly clinical variables. Inclusion of molecular markers improves the prognostic performance beyond that of clinical variables by up to 5%. Such prognostic models could be useful for identifying people with diabetes at high risk of progressing quickly to treatment intensification. DATA AVAILABILITY: Summary statistics of lipidomic, proteomic and metabolomic data are available from a Shiny dashboard at https://rhapdata-app.vital-it.ch .
Subject(s)
Diabetes Mellitus, Type 2 , Humans , Diabetes Mellitus, Type 2/metabolism , Prospective Studies , C-Peptide , Proteomics , Insulin/therapeutic use , Biomarkers , Machine Learning , CholesterolABSTRACT
AIMS/HYPOTHESIS: Beta cells within the pancreatic islet represent a heterogenous population wherein individual sub-groups of cells make distinct contributions to the overall control of insulin secretion. These include a subpopulation of highly connected 'hub' cells, important for the propagation of intercellular Ca2+ waves. Functional subpopulations have also been demonstrated in human beta cells, with an altered subtype distribution apparent in type 2 diabetes. At present, the molecular mechanisms through which beta cell hierarchy is established are poorly understood. Changes at the level of the epigenome provide one such possibility, which we explore here by focusing on the imprinted gene Nnat (encoding neuronatin [NNAT]), which is required for normal insulin synthesis and secretion. METHODS: Single-cell RNA-seq datasets were examined using Seurat 4.0 and ClusterProfiler running under R. Transgenic mice expressing enhanced GFP under the control of the Nnat enhancer/promoter regions were generated for FACS of beta cells and downstream analysis of CpG methylation by bisulphite sequencing and RNA-seq, respectively. Animals deleted for the de novo methyltransferase DNA methyltransferase 3 alpha (DNMT3A) from the pancreatic progenitor stage were used to explore control of promoter methylation. Proteomics was performed using affinity purification mass spectrometry and Ca2+ dynamics explored by rapid confocal imaging of Cal-520 AM and Cal-590 AM. Insulin secretion was measured using homogeneous time-resolved fluorescence imaging. RESULTS: Nnat mRNA was differentially expressed in a discrete beta cell population in a developmental stage- and DNA methylation (DNMT3A)-dependent manner. Thus, pseudo-time analysis of embryonic datasets demonstrated the early establishment of Nnat-positive and -negative subpopulations during embryogenesis. NNAT expression is also restricted to a subset of beta cells across the human islet that is maintained throughout adult life. NNAT+ beta cells also displayed a discrete transcriptome at adult stages, representing a subpopulation specialised for insulin production, and were diminished in db/db mice. 'Hub' cells were less abundant in the NNAT+ population, consistent with epigenetic control of this functional specialisation. CONCLUSIONS/INTERPRETATION: These findings demonstrate that differential DNA methylation at Nnat represents a novel means through which beta cell heterogeneity is established during development. We therefore hypothesise that changes in methylation at this locus may contribute to a loss of beta cell hierarchy and connectivity, potentially contributing to defective insulin secretion in some forms of diabetes. DATA AVAILABILITY: The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD048465.
Subject(s)
CpG Islands , DNA Methylation , Insulin-Secreting Cells , Insulin-Secreting Cells/metabolism , Animals , Mice , CpG Islands/genetics , Nerve Tissue Proteins/metabolism , Nerve Tissue Proteins/genetics , Membrane Proteins/metabolism , Membrane Proteins/genetics , Mice, Transgenic , DNA Methyltransferase 3A/metabolism , Humans , Insulin/metabolism , Insulin Secretion/physiologyABSTRACT
The canonical model of glucose-induced increase in insulin secretion involves the metabolism of glucose via glycolysis and the citrate cycle, resulting in increased ATP synthesis by the respiratory chain and the closure of ATP-sensitive K+ (KATP) channels. The resulting plasma membrane depolarization, followed by Ca2+ influx through L-type Ca2+ channels, then induces insulin granule fusion. Merrins and colleagues have recently proposed an alternative model whereby KATP channels are controlled by pyruvate kinase, using glycolytic and mitochondrial phosphoenolpyruvate (PEP) to generate microdomains of high ATP/ADP immediately adjacent to KATP channels. This model presents several challenges. First, how mitochondrially generated PEP, but not ATP produced abundantly by the mitochondrial F1F0-ATP synthase, can gain access to the proposed microdomains is unclear. Second, ATP/ADP fluctuations imaged immediately beneath the plasma membrane closely resemble those in the bulk cytosol. Third, ADP privation of the respiratory chain at high glucose, suggested to drive alternating, phased-locked generation by mitochondria of ATP or PEP, has yet to be directly demonstrated. Finally, the approaches used to explore these questions may be complicated by off-target effects. We suggest instead that Ca2+ changes, well known to affect both ATP generation and consumption, likely drive cytosolic ATP/ADP oscillations that in turn regulate KATP channels and membrane potential. Thus, it remains to be demonstrated that a new model is required to replace the existing, mitochondrial bioenergetics-based model.
Subject(s)
Glucose , Insulin-Secreting Cells , KATP Channels , Insulin-Secreting Cells/metabolism , KATP Channels/metabolism , Glucose/metabolism , Humans , Animals , Adenosine Triphosphate/metabolism , Mitochondria/metabolism , Insulin/metabolism , Adenosine Diphosphate/metabolism , Models, Biological , Insulin Secretion/physiologyABSTRACT
Functional pancreatic islet beta cells are essential to ensure glucose homeostasis across species from zebrafish to humans. These cells show significant heterogeneity, and emerging studies have revealed that connectivity across a hierarchical network is required for normal insulin release. Here, we discuss current thinking and areas of debate around intra-islet connectivity, cellular hierarchies and potential "controlling" beta-cell populations. We focus on methodologies, including comparisons of different cell preparations as well as in vitro and in vivo approaches to imaging and controlling the activity of human and rodent islet preparations. We also discuss the analytical approaches that can be applied to live-cell data to identify and study critical subgroups of cells with a disproportionate role in control Ca2+ dynamics and thus insulin secretion (such as "first responders", "leaders" and "hubs", as defined by Ca2+ responses to glucose stimulation). Possible mechanisms by which this hierarchy is achieved, its physiological relevance and how its loss may contribute to islet failure in diabetes mellitus are also considered. A glossary of terms and links to computational resources are provided.
ABSTRACT
Human pluripotent stem cells (hPSCs) can differentiate into any kind of cell, making them an excellent alternative source of human pancreatic ß-cells. hPSCs can either be embryonic stem cells (hESCs) derived from the blastocyst or induced pluripotent cells (hiPSCs) generated directly from somatic cells using a reprogramming process. Here a video-based protocol is presented to outline the optimal culture and passage conditions for hPSCs, prior to their differentiation and subsequent generation of insulin-producing pancreatic cells. This methodology follows the six-stage process for ß-cell directed differentiation, wherein hPSCs differentiate into definitive endoderm (DE), primitive gut tube, posterior foregut fate, pancreatic progenitors, pancreatic endocrine progenitors, and ultimately pancreatic ß-cells. It is noteworthy that this differentiation methodology takes a period of 27 days to generate human pancreatic ß-cells. The potential of insulin secretion was evaluated through two experiments, which included immunostaining and glucose-stimulated insulin secretion.
Subject(s)
Induced Pluripotent Stem Cells , Insulin-Secreting Cells , Pluripotent Stem Cells , Humans , Cell Differentiation , PancreasABSTRACT
Introduction: Proinflammatory cytokines are implicated in pancreatic ß cell failure in type 1 and type 2 diabetes and are known to stimulate alternative RNA splicing and the expression of nonsense-mediated RNA decay (NMD) components. Here, we investigate whether cytokines regulate NMD activity and identify transcript isoforms targeted in ß cells. Methods: A luciferase-based NMD reporter transiently expressed in rat INS1(832/13), human-derived EndoC-ßH3, or dispersed human islet cells is used to examine the effect of proinflammatory cytokines (Cyt) on NMD activity. The gain- or loss-of-function of two key NMD components, UPF3B and UPF2, is used to reveal the effect of cytokines on cell viability and function. RNA-sequencing and siRNA-mediated silencing are deployed using standard techniques. Results: Cyt attenuate NMD activity in insulin-producing cell lines and primary human ß cells. These effects are found to involve ER stress and are associated with the downregulation of UPF3B. Increases or decreases in NMD activity achieved by UPF3B overexpression (OE) or UPF2 silencing raise or lower Cyt-induced cell death, respectively, in EndoC-ßH3 cells and are associated with decreased or increased insulin content, respectively. No effects of these manipulations are observed on glucose-stimulated insulin secretion. Transcriptomic analysis reveals that Cyt increases alternative splicing (AS)-induced exon skipping in the transcript isoforms, and this is potentiated by UPF2 silencing. Gene enrichment analysis identifies transcripts regulated by UPF2 silencing whose proteins are localized and/or functional in the extracellular matrix (ECM), including the serine protease inhibitor SERPINA1/α-1-antitrypsin, whose silencing sensitizes ß-cells to Cyt cytotoxicity. Cytokines suppress NMD activity via UPR signaling, potentially serving as a protective response against Cyt-induced NMD component expression. Conclusion: Our findings highlight the central importance of RNA turnover in ß cell responses to inflammatory stress.
Subject(s)
Diabetes Mellitus, Type 2 , Insulin-Secreting Cells , Insulins , Humans , Rats , Animals , RNA/metabolism , Insulin-Secreting Cells/metabolism , Cytokines/metabolism , Diabetes Mellitus, Type 2/metabolism , Nonsense Mediated mRNA Decay , Protein Isoforms/genetics , Protein Isoforms/metabolism , Insulins/metabolism , RNA-Binding Proteins/geneticsABSTRACT
Proinflammatory cytokines are implicated in pancreatic ß-cell failure in type 1 and type 2 diabetes and are known to stimulate alternative RNA splicing and the expression of Nonsense-Mediated RNA Decay (NMD) components. Here, we investigate whether cytokines regulate NMD activity and identify transcript isoforms targeted in ß-cells. A luciferase-based NMD reporter transiently expressed in rat INS1(832/13), human-derived EndoC-ßH3 or dispersed human islet cells is used to examine the effect of proinflammatory cytokines (Cyt) on NMD activity. Gain- or loss-of function of two key NMD components UPF3B and UPF2 is used to reveal the effect of cytokines on cell viability and function. RNA-sequencing and siRNA-mediated silencing are deployed using standard techniques. Cyt attenuate NMD activity in insulin-producing cell lines and primary human ß-cells. These effects are found to involve ER stress and are associated with downregulation of UPF3B. Increases or decreases in NMD activity achieved by UPF3B overexpression (OE) or UPF2 silencing, raises or lowers Cyt-induced cell death, respectively, in EndoC-ßH3 cells, and are associated with decreased or increased insulin content, respectively. No effects of these manipulations are observed on glucose-stimulated insulin secretion. Transcriptomic analysis reveals that Cyt increase alternative splicing (AS)-induced exon skipping in the transcript isoforms, and this is potentiated by UPF2 silencing. Gene enrichment analysis identifies transcripts regulated by UPF2 silencing whose proteins are localized and/or functional in extracellular matrix (ECM) including the serine protease inhibitor SERPINA1/α-1-antitrypsin, whose silencing sensitises ß-cells to Cyt cytotoxicity. Cytokines suppress NMD activity via UPR signalling, potentially serving as a protective response against Cyt-induced NMD component expression. Our findings highlight the central importance of RNA turnover in ß-cell responses to inflammatory stress.
ABSTRACT
Coordination of cellular activity through Ca2+ enables ß cells to secrete precise quantities of insulin. To explore how the Ca2+ response is orchestrated in space and time, we implement optogenetic systems to probe the role of individual ß cells in the glucose response. By targeted ß cell activation/inactivation in zebrafish, we reveal a hierarchy of cells, each with a different level of influence over islet-wide Ca2+ dynamics. First-responder ß cells lie at the top of the hierarchy, essential for initiating the first-phase Ca2+ response. Silencing first responders impairs the Ca2+ response to glucose. Conversely, selective activation of first responders demonstrates their increased capability to raise pan-islet Ca2+ levels compared to followers. By photolabeling and transcriptionally profiling ß cells that differ in their thresholds to a glucose-stimulated Ca2+ response, we highlight vitamin B6 production as a signature pathway of first responders. We further define an evolutionarily conserved requirement for vitamin B6 in enabling the Ca2+ response to glucose in mammalian systems.
Subject(s)
Calcium , Glucose , Insulin-Secreting Cells , Optogenetics , Zebrafish , Animals , Insulin-Secreting Cells/metabolism , Glucose/metabolism , Calcium/metabolism , Calcium SignalingABSTRACT
Despite recent therapeutic advances, achieving optimal glycaemic control remains a challenge in managing Type 2 Diabetes (T2D). Sodium-glucose co-transporter type 2 (SGLT2) inhibitors have emerged as effective treatments by promoting urinary glucose excretion. However, the full scope of their mechanisms extends beyond glycaemic control. At present, their immunometabolic effects remain elusive. To investigate the effects of SGLT2 inhibition or deletion, we compared the metabolic and immune phenotype between high fat diet-fed control, chronically dapagliflozin-treated mice and total-body SGLT2/Slc5a2 knockout mice. SGLT2 null mice exhibited superior glucose tolerance and insulin sensitivity compared to control or dapagliflozin-treated mice, independent of glycosuria and body weight. Moreover, SGLT2 null mice demonstrated physiological regulation of corticosterone secretion, with lowered morning levels compared to control mice. Systemic cytokine profiling also unveiled significant alterations in inflammatory mediators, particularly interleukin 6 (IL-6). Furthermore, unbiased proteomic analysis demonstrated downregulation of acute-phase proteins and upregulation of glutathione-related proteins, suggesting a role in the modulation of antioxidant responses. Conversely, IL-6 increased SGLT2 expression in kidney HK2 cells suggesting a role for cytokines in the effects of hyperglycemia. Collectively, our study elucidates a potential interplay between SGLT2 activity, immune modulation, and metabolic homeostasis.
ABSTRACT
Liver kinase B1 (LKB1/STK11) is an important regulator of pancreatic ß-cell identity and function. Elimination of Lkb1 from the ß-cell results in improved glucose-stimulated insulin secretion and is accompanied by profound changes in gene expression, including the upregulation of several neuronal genes. The mechanisms through which LKB1 controls gene expression are, at present, poorly understood. Here, we explore the impact of ß cell- selective deletion of Lkb1 on chromatin accessibility in mouse pancreatic islets. To characterize the role of LKB1 in the regulation of gene expression at the transcriptional level, we combine these data with a map of islet active transcription start sites and histone marks. We demonstrate that LKB1 elimination from ß-cells results in widespread changes in chromatin accessibility, correlating with changes in transcript levels. Changes occurred in hundreds of promoter and enhancer regions, many of which were close to neuronal genes. We reveal that dysregulated enhancers are enriched in binding motifs for transcription factors important for ß-cell identity, such as FOXA, MAFA or RFX6 and we identify microRNAs (miRNAs) that are regulated by LKB1 at the transcriptional level. Overall, our study provides important new insights into the epigenetic mechanisms by which LKB1 regulates ß-cell identity and function.
ABSTRACT
Mini-G proteins are engineered, thermostable variants of Gα subunits designed to stabilize G protein-coupled receptors (GPCRs) in their active conformations. Because of their small size and ease of use, they are popular tools for assessing GPCR behaviors in cells, both as reporters of receptor coupling to Gα subtypes and for cellular assays to quantify compartmentalized signaling at various subcellular locations. Here, we report that overexpression of mini-G proteins with their cognate GPCRs disrupted GPCR endocytic trafficking and associated intracellular signaling. In cells expressing the Gαs-coupled GPCR glucagon-like peptide 1 receptor (GLP-1R), coexpression of mini-Gs, a mini-G protein derived from Gαs, blocked ß-arrestin 2 recruitment and receptor internalization and disrupted endosomal GLP-1R signaling. These effects did not involve changes in receptor phosphorylation or lipid nanodomain segregation. Moreover, we found that mini-G proteins derived from Gαi and Gαq also inhibited the internalization of GPCRs that couple to them. Finally, we developed an alternative intracellular signaling assay for GLP-1R using a nanobody specific for active Gαs:GPCR complexes (Nb37) that did not affect GLP-1R internalization. Our results have important implications for designing methods to assess intracellular GPCR signaling.
Subject(s)
Glucagon-Like Peptide-1 Receptor , Protein Engineering , Receptors, G-Protein-Coupled , Signal Transduction , Humans , Glucagon-Like Peptide-1 Receptor/metabolism , Glucagon-Like Peptide-1 Receptor/genetics , Receptors, G-Protein-Coupled/metabolism , Receptors, G-Protein-Coupled/genetics , HEK293 Cells , Protein Engineering/methods , Endocytosis/physiology , Protein Transport , AnimalsABSTRACT
Introduction: Type 2 diabetes (T2D) onset, progression and outcomes differ substantially between individuals. Multi-omics analyses may allow a deeper understanding of these differences and ultimately facilitate personalised treatments. Here, in an unsupervised "bottom-up" approach, we attempt to group T2D patients based solely on -omics data generated from plasma. Methods: Circulating plasma lipidomic and proteomic data from two independent clinical cohorts, Hoorn Diabetes Care System (DCS) and Genetics of Diabetes Audit and Research in Tayside Scotland (GoDARTS), were analysed using Similarity Network Fusion. The resulting patient network was analysed with Logistic and Cox regression modelling to explore relationships between plasma -omic profiles and clinical characteristics. Results: From a total of 1,134 subjects in the two cohorts, levels of 180 circulating plasma lipids and 1195 proteins were used to separate patients into two subgroups. These differed in terms of glycaemic deterioration (Hazard Ratio=0.56;0.73), insulin sensitivity and secretion (C-peptide, p=3.7e-11;2.5e-06, DCS and GoDARTS, respectively; Homeostatic model assessment 2 (HOMA2)-B; -IR; -S, p=0.0008;4.2e-11;1.1e-09, only in DCS). The main molecular signatures separating the two groups included triacylglycerols, sphingomyelin, testican-1 and interleukin 18 receptor. Conclusions: Using an unsupervised network-based fusion method on plasma lipidomics and proteomics data from two independent cohorts, we were able to identify two subgroups of T2D patients differing in terms of disease severity. The molecular signatures identified within these subgroups provide insights into disease mechanisms and possibly new prognostic markers for T2D.
Subject(s)
Diabetes Mellitus, Type 2 , Insulin Resistance , Humans , Diabetes Mellitus, Type 2/metabolism , Proteomics , MultiomicsABSTRACT
Using 13C6 glucose labeling coupled to gas chromatography-mass spectrometry and 2D 1H-13C heteronuclear single quantum coherence NMR spectroscopy, we have obtained a comparative high-resolution map of glucose fate underpinning ß cell function. In both mouse and human islets, the contribution of glucose to the tricarboxylic acid (TCA) cycle is similar. Pyruvate fueling of the TCA cycle is primarily mediated by the activity of pyruvate dehydrogenase, with lower flux through pyruvate carboxylase. While the conversion of pyruvate to lactate by lactate dehydrogenase (LDH) can be detected in islets of both species, lactate accumulation is 6-fold higher in human islets. Human islets express LDH, with low-moderate LDHA expression and ß cell-specific LDHB expression. LDHB inhibition amplifies LDHA-dependent lactate generation in mouse and human ß cells and increases basal insulin release. Lastly, cis-instrument Mendelian randomization shows that low LDHB expression levels correlate with elevated fasting insulin in humans. Thus, LDHB limits lactate generation in ß cells to maintain appropriate insulin release.
Subject(s)
Insulin Secretion , Insulin-Secreting Cells , L-Lactate Dehydrogenase , Lactic Acid , Humans , Insulin-Secreting Cells/metabolism , Animals , L-Lactate Dehydrogenase/metabolism , Mice , Lactic Acid/metabolism , Glucose/metabolism , Insulin/metabolism , Isoenzymes/metabolism , Citric Acid Cycle , Mice, Inbred C57BL , MaleABSTRACT
Inducing apoptosis in different types of cancer cells is an effective therapeutic strategy. However, the success of existing chemotherapeutics can be compromised by tumor cell resistance and systemic off-target effects. Therefore, the discovery of pro-apoptotic compounds with minimal systemic side-effects is crucial. 14-3-3 proteins are molecular scaffolds that serve as important regulators of cell survival. Our previous study demonstrated that 14-3-3ζ can sequester BAD, a pro-apoptotic member of the BCL-2 protein family, in the cytoplasm and prevent its translocation to mitochondria to inhibit the induction of apoptosis. Despite being a critical mechanism of cell survival, it is unclear whether disrupting 14-3-3 protein:BAD interactions could be harnessed as a chemotherapeutic approach. Herein, we established a BRET-based high-throughput drug screening approach (Z'-score= 0.52) capable of identifying molecules that can disrupt 14-3-3ζ:BAD interactions. An FDA-approved drug library containing 1971 compounds was used for screening, and the capacity of identified hits to induce cell death was examined in NIH3T3-fibroblasts and colorectal cancer cell lines, HT-29 and Caco-2. Our in vitro results suggest that terfenadine, penfluridol, and lomitapide could be potentially repurposed for treating colorectal cancer. Moreover, our screening method demonstrates the feasibility of identifying pro-apoptotic agents that can be applied towards conditions where aberrant cell growth or function are key determinants of disease pathogenesis.