scholarly journals Characteristics of the New Insulin-Resistant Zebrafish Model

2021 ◽  
Vol 14 (7) ◽  
pp. 642
Author(s):  
Youn-Hee Nam ◽  
Isabel Rodriguez ◽  
Sung-Woo Shin ◽  
Ji-Heon Shim ◽  
Na-Woo Kim ◽  
...  
Keyword(s):  
Insulin Resistance ◽  
Drug Discovery ◽  
Pancreatic Islets ◽  
Drug Testing ◽  
Enrichment Analysis ◽  
Mapk Signaling ◽  
Pathway Enrichment Analysis ◽  
Rodent Models ◽  
Zebrafish Model ◽  
Insulin Resistant

Insulin resistance, which occurs when insulin levels are sufficiently high over a prolonged period, causing the cells to fail to respond normally to the hormone. As a system for insulin resistance and diabetes drug development, insulin-resistant rodent models have been clearly established, but there is a limitation to high-throughput drug screening. Recently, zebrafish have been identified as an excellent system for drug discovery and identification of therapeutic targets, but studies on insulin resistance models have not been extensively performed. Therefore, we aimed to make a rapid insulin-resistant zebrafish model that complements the existing rodent models. To establish this model, zebrafish were treated with 10 μM insulin for 48 h. This model showed characteristics of insulin-resistant disease such as damaged pancreatic islets. Then we confirmed the recovery of the pancreatic islets after pioglitazone treatment. In addition, it was found that insulin-resistant drugs have as significant an effect in zebrafish as in humans, and these results proved the value of the zebrafish insulin resistance model for drug selection. In addition, RNA sequencing was performed to elucidate the mechanism involved. KEGG pathway enrichment analysis of differentially expressed genes showed that insulin resistance altered gene expression due to the MAPK signaling and calcium signaling pathways. This model demonstrates the utility of the zebrafish model for drug testing and drug discovery in insulin resistance and diabetes.

scholarly journals Hepatic fat is a stronger correlate of key clinical and molecular abnormalities than visceral and abdominal subcutaneous fat in youth

2020 ◽  
Vol 8 (1) ◽  
pp. e001126
Author(s):  
Catherine E Cioffi ◽  
K M Venkat Narayan ◽  
Ken Liu ◽  
Karan Uppal ◽  
Dean P Jones ◽  
...  
Keyword(s):  
Insulin Resistance ◽  
Network Analysis ◽  
Subcutaneous Fat ◽  
Enrichment Analysis ◽  
Fat Distribution ◽  
Pathway Enrichment Analysis ◽  
Clinical Variables ◽  
Pathway Enrichment ◽  
Hepatic Fat ◽  
Integrative Network

IntroductionBody fat distribution is strongly associated with cardiometabolic disease (CMD), but the relative importance of hepatic fat as an underlying driver remains unclear. Here, we applied a systems biology approach to compare the clinical and molecular subnetworks that correlate with hepatic fat, visceral fat, and abdominal subcutaneous fat distribution.Research design and methodsThis was a cross-sectional sub-study of 283 children/adolescents (7–19 years) from the Yale Pediatric NAFLD Cohort. Untargeted, high-resolution metabolomics (HRM) was performed on plasma and combined with existing clinical variables including hepatic and abdominal fat measured by MRI. Integrative network analysis was coupled with pathway enrichment analysis and multivariable linear regression (MLR) to examine which metabolites and clinical variables associated with each fat depot.ResultsThe data divided into four communities of correlated variables (|r|>0.15, p<0.05) after integrative network analysis. In the largest community, hepatic fat was associated with eight clinical biomarkers, including measures of insulin resistance and dyslipidemia, and 878 metabolite features that were enriched predominantly in amino acid (AA) and lipid pathways in pathway enrichment analysis (p<0.05). Key metabolites associated with hepatic fat included branched-chain AAs (valine and isoleucine/leucine), aromatic AAs (tyrosine and tryptophan), serine, glycine, alanine, and pyruvate, as well as several acylcarnitines and glycerophospholipids (all q<0.05 in MLR adjusted for covariates). The other communities detected in integrative network analysis consisted of abdominal visceral, superficial subcutaneous, and deep subcutaneous fats, but no clinical variables, fewer metabolite features (280, 312, and 74, respectively), and limited findings in pathway analysis.ConclusionsThese data-driven findings show a stronger association of hepatic fat with key CMD risk factors compared with abdominal fats. The molecular network identified using HRM that associated with hepatic fat provides insight into potential mechanisms underlying the hepatic fat–insulin resistance interface in youth.

scholarly journals Comprehensive circRNA Expression Profile and Construction of circRNAs-Related ceRNA Network in a Mouse Model of Autism

2021 ◽  
Vol 11 ◽  
Author(s):  
Ji Wang ◽  
Zhongxiu Yang ◽  
Canming Chen ◽  
Yang Xu ◽  
Hongguang Wang ◽  
...  
Keyword(s):  
Signaling Pathway ◽  
Expression Profile ◽  
Enrichment Analysis ◽  
Notch Signaling Pathway ◽  
Mapk Signaling ◽  
Circular Rnas ◽  
Pathway Enrichment Analysis ◽  
Common Disease ◽  
Cerna Network

Autism is a common disease that seriously affects the quality of life. The role of circular RNAs (circRNAs) in autism remains largely unexplored. We aimed to detect the circRNA expression profile and construct a circRNA-based competing endogenous RNA (ceRNA) network in autism. Valproate acid was used to establish an in vivo model of autism in mice. A total of 1,059 differentially expressed circRNAs (477 upregulated and 582 downregulated) in autism group was identified by RNA sequencing. The expression of novel_circ_015779 and novel_circ_035247 were detected by real-time PCR. A ceRNA network based on altered circRNAs was established, with 9,715 nodes and 150,408 edges. Module analysis was conducted followed by GO and KEGG pathway enrichment analysis. The top three modules were all correlated with autism-related pathways involving “TGF-beta signaling pathway,” “Notch signaling pathway,” “MAPK signaling pathway,” “long term depression,” “thyroid hormone signaling pathway,” etc. The present study reveals a novel circRNA involved mechanisms in the pathogenesis of autism.

scholarly journals Uncovering the Mechanisms and Molecular Targets of Weibing Formula 1 against Gastritis: Coupling Network Pharmacology with GEO Database

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Ke Chen ◽  
Luojian Zhang ◽  
Zhen Qu ◽  
Feng Wan ◽  
Jia Li ◽  
...  
Keyword(s):  
Real Time ◽  
Signaling Pathway ◽  
Quantitative Pcr ◽  
Enrichment Analysis ◽  
Mapk Signaling ◽  
Gene Expression Omnibus ◽  
Network Pharmacology ◽  
Receptor Interaction ◽  
Pathway Enrichment Analysis ◽  
Real Time Quantitative Pcr

Weibing Formula 1, a classic traditional formula, has been widely used clinically to treat gastritis in recent years. However, the potential pharmacological mechanism of Weibing Formula 1 is still unclear to date. A network pharmacology-based strategy was performed to uncover the underlying mechanisms of Weibing Formula 1 against gastritis. Furthermore, we structured the drug-active ingredients-genes–disease network and PPI network of shared targets, and function enrichment analysis of these targets was carried out. Ultimately, Gene Expression Omnibus (GEO) datasets and real-time quantitative PCR were used to verify the related genes. We found 251 potential targets corresponding to 135 bioactive components of Weibing Formula 1. Then, 327 gastritis-related targets were known gastritis-related targets. Among which, 60 common targets were shared between potential targets of Weibing Formula 1 and known gastritis-related targets. The results of pathway enrichment analysis displayed that 60 common targets mostly participated in various pathways related to Toll-like receptor signaling pathway, MAPK signaling pathway, cytokine-cytokine receptor interaction pathway, chemokine signaling pathway, and apoptosis. Based on the GSE60427 dataset, 15 common genes were shared between differentially expressed genes and 60 candidate targets. The verification results of the GSE5081 dataset showed that except for DUOX2 and VCAM1, the other 13 genes were significantly upregulated in gastritis, which was consistent with the results in the GSE60427 dataset. More importantly, real-time quantitative PCR results showed that the expressions of PTGS2, MMP9, CXCL2, and CXCL8 were significantly upregulated and NOS2, EGFR, and IL-10 were downregulated in gastritis patients, while the expressions of PTGS2, MMP9, CXCL2, and CXCL8 were significantly downregulated and NOS2, EGFR, and IL-10 were upregulated after the treatment of Weibing Formula 1. PTGS2, NOS2, EGFR, MMP9, CXCL2, CXCL8, and IL-10 may be the important direct targets of Weibing Formula 1 in gastritis treatment. Our study revealed the mechanism of Weibing Formula 1 in gastritis from an overall and systematic perspective, providing a theoretical basis for further knowing and application of this formula in the future.

scholarly journals Global DNA methylation pattern involved in the modulation of differentiation potential of adipogenic and myogenic precursors in skeletal muscle of pigs

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Xin Zhang ◽  
Wenjuan Sun ◽  
Linjuan He ◽  
Liqi Wang ◽  
Kai Qiu ◽  
...  
Keyword(s):  
Skeletal Muscle ◽  
Dna Methylation ◽  
Signaling Pathway ◽  
Myogenic Differentiation ◽  
Enrichment Analysis ◽  
Mapk Signaling ◽  
Methylation Pattern ◽  
Pathway Enrichment Analysis ◽  
Differentiation Potential ◽  
Muscle Homeostasis

Abstract Background Skeletal muscle is a complex and heterogeneous tissue accounting for approximately 40% of body weight. Excessive ectopic lipid accumulation in the muscle fascicle would undermine the integrity of skeletal muscle in humans but endow muscle with marbling-related characteristics in farm animals. Therefore, the balance of myogenesis and adipogenesis is of great significance for skeletal muscle homeostasis. Significant DNA methylation occurs during myogenesis and adipogenesis; however, DNA methylation pattern of myogenic and adipogenic precursors derived from skeletal muscle remains unknown yet. Methods In this study, reduced representation bisulfite sequencing was performed to analyze genome-wide DNA methylation of adipogenic and myogenic precursors derived from the skeletal muscle of neonatal pigs. Integrated analysis of DNA methylation and transcription profiles was further conducted. Based on the results of pathway enrichment analysis, myogenic precursors were transfected with CACNA2D2-overexpression plasmids to explore the function of CACNA2D2 in myogenic differentiation. Results As a result, 11,361 differentially methylated regions mainly located in intergenic region and introns were identified. Furthermore, 153 genes with different DNA methylation and gene expression level between adipogenic and myogenic precursors were characterized. Subsequently, pathway enrichment analysis revealed that DNA methylation programing was involved in the regulation of adipogenic and myogenic differentiation potential through mediating the crosstalk among pathways including focal adhesion, regulation of actin cytoskeleton, MAPK signaling pathway, and calcium signaling pathway. In particular, we characterized a new role of CACNA2D2 in inhibiting myogenic differentiation by suppressing JNK/MAPK signaling pathway. Conclusions This study depicted a comprehensive landmark of DNA methylome of skeletal muscle-derived myogenic and adipogenic precursors, highlighted the critical role of CACNA2D2 in regulating myogenic differentiation, and illustrated the possible regulatory ways of DNA methylation on cell fate commitment and skeletal muscle homeostasis.

scholarly journals Circulating miR-583 and miR-663 Refer to ZHENG Differentiation in Chronic Hepatitis B

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Hui Zhang ◽  
Yan Guan ◽  
Yi-Yu Lu ◽  
Yi-Yang Hu ◽  
Shuang Huang ◽  
...  
Keyword(s):  
Chronic Hepatitis ◽  
Hepatitis B ◽  
Chronic Hepatitis B ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Deficiency Syndrome ◽  
Mapk Signaling ◽  
Pathway Enrichment Analysis ◽  
Roc Curve Analysis ◽  
Zheng Differentiation

Traditional Chinese medicine (TCM) ZHENG as the key pathological principle is to understand the human homeostasis and guide TCM treatment. Here, circulating microRNAs (miRNAs) were utilized to differentiate between ZHENGs including liver-gallbladder dampness-heat syndrome (LGDHS) and liver-kidney yin deficiency syndrome (LKYDS) in chronic hepatitis B (CHB). Sera samples of CHB patients with LGDHS (n=35), LKYDS (n=24), and healthy controls (Ctrls,n=21) were analyzed by microarray and real-time RT-PCR. Receiver-operator characteristic (ROC) curves were established to evaluate the levels of serum miRNA for discriminating LGDHS and LKYDS. The target genes of miRNAs were predicted by TargetScan. Gene Ontology (GO) and pathways were analyzed using DAVID tool. The results showed that 22 miRNAs were differentially expressed between LGDHS and LKYDS (fold change>2.0 andP<0.01). Circulating miR-583 and miR-663 were significantly higher (P<0.001) in CHB patients with LGDHS than those with LKYDS and Ctrls. ROC curve analysis revealed that miR-583 and miR-663 were sensitive and specific enough to distinguish LGDHS from LKYDS. Pathway enrichment analysis indicated that 354 putative targets for miR-583 and 68 putative targets for miR-663 were mainly involved in Axon guidance, Neurotrophin, and MAPK signaling pathway. miR-583 and miR-663 may be potential markers for ZHENG differentiation in CHB.

scholarly journals Exploring the Pharmacological Mechanism of Duhuo Jisheng Decoction in Treating Osteoporosis Based on Network Pharmacology

2021 ◽  
Vol 2021 ◽  
pp. 1-21
Author(s):  
Zhencheng Xiong ◽  
Can Zheng ◽  
Yanan Chang ◽  
Kuankuan Liu ◽  
Li Shu ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Signaling Pathway ◽  
Enrichment Analysis ◽  
Mapk Signaling ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Hub Genes ◽  
Active Compounds ◽  
Treatment Of Osteoporosis ◽  
Target Proteins

Objective. The purpose of this work is to study the mechanism of action of Duhuo Jisheng Decoction (DHJSD) in the treatment of osteoporosis based on the methods of bioinformatics and network pharmacology. Methods. In this study, the active compounds of each medicinal ingredient of DHJSD and their corresponding targets were obtained from TCMSP database. Osteoporosis was treated as search query in GeneCards, MalaCards, DisGeNET, Therapeutic Target Database (TTD), Comparative Toxicogenomics Database (CTD), and OMIM databases to obtain disease-related genes. The overlapping targets of DHJSD and osteoporosis were identified, and then GO and KEGG enrichment analysis were performed. Cytoscape was employed to construct DHJSD-compounds-target genes-osteoporosis network and protein-protein interaction (PPI) network. CytoHubba was utilized to select the hub genes. The activities of binding of hub genes and key components were confirmed by molecular docking. Results. 174 active compounds and their 205 related potential targets were identified in DHJSD for the treatment of osteoporosis, including 10 hub genes (AKT1, ALB, IL6, MAPK3, VEGFA, JUN, CASP3, EGFR, MYC, and EGF). Pathway enrichment analysis of target proteins indicated that osteoclast differentiation, AGE-RAGE signaling pathway in diabetic complications, Wnt signaling pathway, MAPK signaling pathway, PI3K-Akt signaling pathway, JAK-STAT signaling pathway, calcium signaling pathway, and TNF signaling pathway were the specifically major pathways regulated by DHJSD against osteoporosis. Further verification based on molecular docking results showed that the small molecule compounds (Quercetin, Kaempferol, Beta-sitosterol, Beta-carotene, and Formononetin) contained in DHJSD generally have excellent binding affinity to the macromolecular target proteins encoded by the top 10 genes. Conclusion. This study reveals the characteristics of multi-component, multi-target, and multi-pathway of DHJSD against osteoporosis and provides novel insights for verifying the mechanism of DHJSD in the treatment of osteoporosis.

scholarly journals Mechanism of quercetin therapeutic targets for Alzheimer disease and type 2 diabetes mellitus

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Guoxiu Zu ◽  
Keyun Sun ◽  
Ling Li ◽  
Xiuli Zu ◽  
Tao Han ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Kegg Pathway ◽  
Enrichment Analysis ◽  
Mapk Signaling ◽  
Pathway Enrichment Analysis ◽  
Ppi Network ◽  
Pathway Enrichment

AbstractQuercetin has demonstrated antioxidant, anti-inflammatory, hypoglycemic, and hypolipidemic activities, suggesting therapeutic potential against type 2 diabetes mellitus (T2DM) and Alzheimer’s disease (AD). In this study, potential molecular targets of quercetin were first identified using the Swiss Target Prediction platform and pathogenic targets of T2DM and AD were identified using online Mendelian inheritance in man (OMIM), DisGeNET, TTD, DrugBank, and GeneCards databases. The 95 targets shared among quercetin, T2DM, and AD were used to establish a protein–protein interaction (PPI) network, top 25 core genes, and protein functional modules using MCODE. Metascape was then used for gene ontology and kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analysis. A protein functional module with best score was obtained from the PPI network using CytoHubba, and 6 high-probability quercetin targets (AKT1, JUN, MAPK, TNF, VEGFA, and EGFR) were confirmed by docking simulations. Molecular dynamics simulation was carried out according to the molecular docking results. KEGG pathway enrichment analysis suggested that the major shared mechanisms for T2DM and AD include “AGE-RAGE signaling pathway in diabetic complications,” “pathways in cancer,” and “MAPK signaling pathway” (the key pathway). We speculate that quercetin may have therapeutic applications in T2DM and AD by targeting MAPK signaling, providing a theoretical foundation for future clinical research.

scholarly journals Elaborate the Mechanism of Ancient Classic Prescriptions (Erzhi Formula) in Reversing GIOP by Network Pharmacology Coupled with Zebrafish Verification

2022 ◽  
Vol 2022 ◽  
pp. 1-17
Author(s):  
Zhihui Cai ◽  
Huajun Wang ◽  
Jun Jiang ◽  
Shichang Xiao ◽  
Jianpeng Xiao ◽  
...  
Keyword(s):  
Signaling Pathway ◽  
Optical Density ◽  
Bone Mineralization ◽  
Enrichment Analysis ◽  
Akt Signaling ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Akt Signaling Pathway ◽  
Active Components ◽  
Zebrafish Model

Osteoporosis is a degenerative disease that endangers human health. At present, chemical drugs used for osteoporosis have serious side effects. Therefore, it is valuable to search herbs with high safety and good curative effect in antiosteoporosis. Erzhi formula (EZF), an ancient classic compound, has been reported to have a beneficial effect in antiosteoporosis, but its mechanism is unclear. In this paper, the active compounds of EZF were found in Systems Pharmacology Database, and gene targets related to osteoporosis were obtained in GeneCards. The GO functional and KEGG pathway enrichment analysis were performed by Metascape. The network of “components-targets-signal pathway” was constructed by Cytoscape. Next, molecular docking between the active components and hub genes related to the PI3K-Akt signaling pathway was conducted by Autodock. In the verification experiment, the zebrafish induced by prednisolone (PNSL) was used to reproduce glucocorticoid-induced osteoporosis (GIOP) model, and then the reversal effects of EZF were systematically evaluated according to the behavior, skull staining area, bone mineralization area (BMA), average optical density (AOD), and cumulative optical density (COD). Finally, it was shown that 24 components in EZF could regulate 39 common gene targets to exert antiosteoporosis effect. Besides, the main regulatory mechanisms of EZF were 4 signaling pathways: PI3K-Akt, JAK-STAT, AGE-RAGE, and cancer pathway. In PI3K-Akt signaling pathway, wedelolactone, dimethyl wedelolactone, specnuezhenide, ursolic acid, acacetin, beta-sitosterol, apigenin, and kaempferol can bind tightly with EGF, IL-2, and IL-4 genes. Compared with the model group, the moving distance, swimming speed, and cumulative swimming time of zebrafish in EZF group were significantly increased ( P < 0.05 ). Meanwhile, the BMA and COD of zebrafish were significantly improved after the intervention of EZF ( P < 0.05 ). In summary, the 24 components of EZF exert their antiosteoporosis effects by regulating 39 related gene targets, among which the PI3K signaling pathway is crucial. EZF can promote bone formation and reversed GIOP through “multicomponent/multitarget/multipathway” and the medium dose of EZF may be the most suitable concentration for the treatment of GIOP in zebrafish model.

scholarly journals Altered Transcription Factor Expression Responses to Exercise in Insulin Resistance

2021 ◽  
Vol 12 ◽  
Author(s):  
Rocio Zapata-Bustos ◽  
Jean Finlayson ◽  
Paul R. Langlais ◽  
Dawn K. Coletta ◽  
Moulun Luo ◽  
...  
Keyword(s):  
Insulin Resistance ◽  
Transcription Factor ◽  
Transcription Factors ◽  
Growth Factors ◽  
Enrichment Analysis ◽  
Rt Pcr ◽  
Post Exercise ◽  
Insulin Resistant ◽  
Exercise Muscle ◽  
Muscle Biopsies

PurposeInsulin resistant muscle is resistant to gene expression changes induced by acute exercise. This study was undertaken to identify transcription factors that differentially respond to exercise in insulin resistance. Candidate transcription factors were identified from analysis of 5′-untranslated regions (5′-UTRs) of exercise responsive genes and from analysis of the 5′-UTRs of genes coding for proteins that differ in abundance in insulin resistance.Research Design and MethodsTwenty participants took part in this study. Insulin sensitivity was assessed by an euglycemic clamp. Participants were matched for aerobic capacity and performed a single 48 min bout of exercise with sets at 70 and 90% of maximum heart rate. Muscle biopsies were obtained at resting conditions, 30 min and 24 h after exercise. Global proteomics analysis identified differentially abundant proteins in muscle. The 5′-UTRs of genes coding for significant proteins were subjected to transcription factor enrichment analysis to identify candidate transcription factors. Q-rt-PCR to determine expression of candidate transcription factors was performed on RNA from resting and post-exercise muscle biopsies; immunoblots quantified protein abundance.ResultsProteins involved in mitochondrial function, protein targeting and translation, and metabolism were among those significantly different between lean and obese groups. Transcription factor enrichment analysis of genes coding for these proteins revealed new candidate transcription factors to be evaluated along the previously identified factors. Q-rt-PCR analysis of RNA and immunoblot analysis from pre- and post-exercise muscle biopsies revealed several transcription and growth factors that had altered responses to exercise in insulin resistant participants. A significant increase (EGR3 and CTGF) and decrease (RELA and ATF2) in the mRNA expression of transcription and growth factors was found after exercise in the lean group, but not in the obese participants.ConclusionsThese results confirm findings of an association between insulin sensitivity and transcription factor mRNA response to exercise and show that obesity also may be a sufficient prerequisite for exercise resistance. Analysis of the muscle proteome together with determination of effects of exercise on expression of transcription factors suggests that abnormal responses of transcription factors to exercise may be responsible for differences in protein abundances in insulin resistant muscle.

scholarly journals Hyperinsulinemia induces insulin resistance and immune suppression via Ptpn6/Shp1 in zebrafish

2014 ◽  
Vol 222 (2) ◽  
pp. 229-241 ◽  
Author(s):  
Rubén Marín-Juez ◽  
Susanne Jong-Raadsen ◽  
Shuxin Yang ◽  
Herman P Spaink
Keyword(s):  
Insulin Resistance ◽  
Tyrosine Phosphatase ◽  
Large Population ◽  
High Dose ◽  
Zebrafish Model ◽  
Metabolic Switch ◽  
Insulin Metabolism ◽  
Insulin Resistant ◽  
Recombinant Insulin ◽  
High Insulin

Type 2 diabetes, obesity, and metabolic syndrome are pathologies where insulin resistance plays a central role, and that affect a large population worldwide. These pathologies are usually associated with a dysregulation of insulin secretion leading to a chronic exposure of the tissues to high insulin levels (i.e. hyperinsulinemia), which diminishes the concentration of key downstream elements, causing insulin resistance. The complexity of the study of insulin resistance arises from the heterogeneity of the metabolic states where it is observed. To contribute to the understanding of the mechanisms triggering insulin resistance, we have developed a zebrafish model to study insulin metabolism and its associated disorders. Zebrafish larvae appeared to be sensitive to human recombinant insulin, becoming insulin-resistant when exposed to a high dose of the hormone. Moreover RNA-seq-based transcriptomic profiling of these larvae revealed a strong downregulation of a number of immune-relevant genes as a consequence of the exposure to hyperinsulinemia. Interestingly, as an exception, the negative immune modulator protein tyrosine phosphatase nonreceptor type 6 (ptpn6) appeared to be upregulated in insulin-resistant larvae. Knockdown ofptpn6was found to counteract the observed downregulation of the immune system and insulin signaling pathway caused by hyperinsulinemia. These results indicate thatptpn6is a mediator of the metabolic switch between insulin-sensitive and insulin-resistant states. Our zebrafish model for hyperinsulinemia has therefore demonstrated its suitability for discovery of novel regulators of insulin resistance. In addition, our data will be very useful in further studies of the function of immunological determinants in a non-obese model system.

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