scholarly journals Identification of transcription factors MYC and C/EBPβ mediated regulatory networks in heart failure based on Gene Expression Omnibus datasets

2020 ◽  
Author(s):  
Haiwei Wang ◽  
Xinrui Wang ◽  
Liangpu Xu ◽  
Hua Cao
Keyword(s):  
Gene Expression ◽  
Heart Failure ◽  
Transcription Factors ◽  
Signaling Pathways ◽  
Signaling Pathway ◽  
Insulin Signaling ◽  
Regulatory Networks ◽  
Target Genes ◽  
Insulin Signaling Pathway ◽  
Failing Heart

Abstract Background: Heart failure is one of leading cause of death worldwide. However, the transcriptional profiling of heart failure is unclear. Moreover, the signaling pathways and transcription factors involving the heart failure development also are largely unknown. Using published Gene Expression Omnibus (GEO) datasets, in the present study, we aim to comprehensively analyze the differentially expressed genes in failing heart tissues, and identified the critical signaling pathways and transcription factors involving heart failure development. Methods: The transcriptional profiling of heart failure was identified from previously published gene expression datasets deposited in GSE5406, GSE16499 and GSE68316. The enriched signaling pathways and transcription factors were analyzed using Database for Annotation, Visualization and Integrated Discovery (DAVID) website and gene set enrichment analysis (GSEA) assay. The transcriptional networks were created by Cytoscape. Results: Compared with the normal heart tissues, 90 genes were particularly differentially expressed in failing heart tissues, and those genes were associated with multiple metabolism signaling pathways and insulin signaling pathway. Metabolism and insulin signaling pathway were both inactivated in failing heart tissues. Transcription factors MYC and C/EBPβ were both negatively associated with the expression profiling of failing heart tissues in GSEA assay. Moreover, compared with normal heart tissues, MYC and C/EBPβ were down regulated in failing heart tissues. Furthermore, MYC and C/EBPβ mediated downstream target genes were also decreased in failing heart tissues. MYC and C/EBPβ were positively correlated with each other. At last, we constructed MYC and C/EBPβ mediated regulatory networks in failing heart tissues, and identified the MYC and C/EBPβ target genes which had been reported involving the heart failure developmental progress. Conclusions: Our results suggested that metabolism pathways and insulin signaling pathway, transcription factors MYC and C/EBPβ played critical roles in heart failure developmental progress.

scholarly journals Identification of transcription factors MYC and C/EBPβ mediated regulatory networks in heart failure based on Gene Expression Omnibus datasets

2020 ◽  
Author(s):  
Haiwei Wang ◽  
Xinrui Wang ◽  
Liangpu Xu ◽  
Hua Cao
Keyword(s):  
Gene Expression ◽  
Heart Failure ◽  
Transcription Factors ◽  
Signaling Pathways ◽  
Signaling Pathway ◽  
Insulin Signaling ◽  
Regulatory Networks ◽  
Target Genes ◽  
Insulin Signaling Pathway ◽  
Failing Heart

Abstract Background: Heart failure is one of leading cause of death worldwide. However, the transcriptional profiling of heart failure is unclear. Moreover, the signaling pathways and transcription factors involving the heart failure development also are largely unknown. Using published Gene Expression Omnibus (GEO) datasets, in the present study, we aim to comprehensively analyze the differentially expressed genes in failing heart tissues, and identified the critical signaling pathways and transcription factors involving heart failure development.Methods: The transcriptional profiling of heart failure was identified from previously published gene expression datasets deposited in GSE5406, GSE16499 and GSE68316. The enriched signaling pathways and transcription factors were analyzed using Database for Annotation, Visualization and Integrated Discovery (DAVID) website and gene set enrichment analysis (GSEA) assay. The transcriptional networks were created by Cytoscape.Results: Compared with the normal heart tissues, 90 genes were particularly differentially expressed in failing heart tissues, and those genes were associated with multiple metabolism signaling pathways and insulin signaling pathway. Metabolism and insulin signaling pathway were both inactivated in failing heart tissues. Transcription factors MYC and C/EBPβ were both negatively associated with the expression profiling of failing heart tissues in GSEA assay. Moreover, compared with normal heart tissues, MYC and C/EBPβ were down regulated in failing heart tissues. Furthermore, MYC and C/EBPβ mediated downstream target genes were also decreased in failing heart tissues. MYC and C/EBPβ were positively correlated with each other. At last, we constructed MYC and C/EBPβ mediated regulatory networks in failing heart tissues, and identified the MYC and C/EBPβ target genes which had been reported involving the heart failure developmental progress.Conclusions: Our results suggested that metabolism pathways and insulin signaling pathway, transcription factors MYC and C/EBPβ played critical roles in heart failure developmental progress.

Identification of transcription factors MYC and C/EBPβ mediated regulatory networks in heart failure based on GEO dataset

2020 ◽  
Author(s):  
Haiwei Wang ◽  
Xinrui Wang ◽  
Liangpu Xu ◽  
Hua Cao
Keyword(s):  
Heart Failure ◽  
Transcription Factors ◽  
Signaling Pathways ◽  
Signaling Pathway ◽  
Insulin Signaling ◽  
Regulatory Networks ◽  
Target Genes ◽  
Transcriptional Profiling ◽  
Insulin Signaling Pathway ◽  
Failing Heart

Abstract Background: Heart failure is one of leading cause of death worldwide. However, the transcriptional profiling of heart failure is unclear. Moreover, the signaling pathways and transcription factors involving the heart failure development also are largely unknown. Using published Gene Expression Omnibus (GEO) datasets, in the present study, we aim to comprehensively analyze the differentially expressed genes in failing heart tissues, and identified the critical signaling pathways and transcription factors involving heart failure development. Methods: The transcriptional profiling of heart failure was identified from previously published gene expression datasets deposited in GSE5406, GSE16499 and GSE68316. The enriched signaling pathways and transcription factors were analyzed using DAVID website and gene set enrichment analysis (GSEA) assay. The transcriptional networks were created by Cytoscape. Results: Compared with the normal heart tissues, 90 genes were particularly differentially expressed in failing heart tissues, and those genes were associated with multiple metabolism signaling pathways and insulin signaling pathway. Metabolism and insulin signaling pathway were both inactivated in failing heart tissues. Transcription factors MYC and C/EBPβ were both negatively associated with the expression profiling of failing heart tissues in GSEA assay. Moreover, compared with normal heart tissues, MYC and C/EBPβ were down regulated in failing heart tissues. Furthermore, MYC and C/EBPβ mediated downstream target genes were also decreased in failing heart tissues. MYC and C/EBPβ were positively correlated with each other. At last, we constructed MYC and C/EBPβ mediated regulatory networks in failing heart tissues, and identified the MYC and C/EBPβ target genes which had been reported involving the heart failure developmental progress. Conclusions: Our results suggested that metabolism pathways and insulin signaling pathway, transcription factors MYC and C/EBPβ played critical roles in heart failure developmental progress.

scholarly journals Identification of transcription factors MYC and C/EBPβ mediated regulatory networks in heart failure

2019 ◽  
Author(s):  
Haiwei Wang ◽  
Xinrui Wang ◽  
Liangpu Xu ◽  
Hua Cao
Keyword(s):  
Heart Failure ◽  
Transcription Factor ◽  
Transcription Factors ◽  
Signaling Pathway ◽  
Insulin Signaling ◽  
Regulatory Networks ◽  
Target Genes ◽  
Transcriptional Profiling ◽  
Normal Heart ◽  
Developmental Progress

Abstract Background: Heart failure is one of leading cause of death worldwide. However, the transcriptional profiling of heart failure is unclear. Moreover, the signaling pathways and transcription factors involving the heart failure developmental progress also are largely unclear.Methods: The transcriptional profiling of heart failure was identified from integrated gene expression datasets. The enriched pathways and transcription factors were analyzed using DAVID and GSEA assay. The transcriptional networks were created by Cytoscape.Results: Compared with the normal heart tissues, we found 90 genes were particularly differentially expressed in heart failing tissues, and those genes were associated with multiple metabolism pathways and insulin signaling pathway. Metabolism and insulin signaling pathway were both inactivated in heart failing tissues. Transcription factors MYC and C/EBPβ were both negatively associated with the expression profiling of heart failing tissues in GSEA assay. Moreover, compared with normal heart tissues, MYC and C/EBPβ were down regulated in heart failing tissues. Furthermore, MYC and C/EBPβ mediated downstream target genes were decreased in heart failing tissues. MYC and C/EBPβ were positively correlated with each other. At last, we constructed the transcription factor MYC and C/EBPβ mediated regulatory networks in heart failing tissues, and identified the MYC and C/EBPβ target genes which had been reported involving the failure developmental progress by literature research. Conclusions: Our results suggested that transcription factor MYC and C/EBPβ played critical roles in heart failure developmental progress. And new heart failure treatments may be developed by targeting MYC and C/EBPβ.

scholarly journals Identifying genetic modulators of the connectivity between transcription factors and their transcriptional targets

2016 ◽  
Vol 113 (13) ◽  
pp. E1835-E1843 ◽  
Author(s):  
Mina Fazlollahi ◽  
Ivor Muroff ◽  
Eunjee Lee ◽  
Helen C. Causton ◽  
Harmen J. Bussemaker
Keyword(s):  
Gene Expression ◽  
Transcription Factors ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Target Genes ◽  
Regulation Of Gene Expression ◽  
Nonsynonymous Mutation ◽  
Gene Regulatory ◽  
Genetic Modulators

Regulation of gene expression by transcription factors (TFs) is highly dependent on genetic background and interactions with cofactors. Identifying specific context factors is a major challenge that requires new approaches. Here we show that exploiting natural variation is a potent strategy for probing functional interactions within gene regulatory networks. We developed an algorithm to identify genetic polymorphisms that modulate the regulatory connectivity between specific transcription factors and their target genes in vivo. As a proof of principle, we mapped connectivity quantitative trait loci (cQTLs) using parallel genotype and gene expression data for segregants from a cross between two strains of the yeast Saccharomyces cerevisiae. We identified a nonsynonymous mutation in the DIG2 gene as a cQTL for the transcription factor Ste12p and confirmed this prediction empirically. We also identified three polymorphisms in TAF13 as putative modulators of regulation by Gcn4p. Our method has potential for revealing how genetic differences among individuals influence gene regulatory networks in any organism for which gene expression and genotype data are available along with information on binding preferences for transcription factors.

839 HEPATITIS C VIRUS MODIFIES PROTEIN AND GENE EXPRESSION OF THE INSULIN SIGNALING PATHWAY IN VIVO AND IN VITRO

2012 ◽  
Vol 56 ◽  
pp. S327-S328
Author(s):  
M. Garcîa-Valdecasas ◽  
A. Rojas ◽  
J.A. Del ◽  
M. Romero-Gomez
Keyword(s):  
Gene Expression ◽  
Hepatitis C Virus ◽  
Hepatitis C ◽  
Signaling Pathway ◽  
Insulin Signaling ◽  
Insulin Signaling Pathway

scholarly journals The Role of Adenosine Monophosphate Activated Protein Kinase Alpha 1 (AMPK) in Gamma-Globin Regulation

Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 413-413
Author(s):  
Alicia Chang ◽  
Yankai Zhang ◽  
Nelda Itzep ◽  
Vivien A Sheehan
Keyword(s):  
Gene Expression ◽  
Western Blot ◽  
Signaling Pathway ◽  
Insulin Signaling ◽  
Globin Gene ◽  
Insulin Signaling Pathway ◽  
Gamma Globin ◽  
Compound C ◽  
Globin Gene Expression

Abstract Background: Fetal hemoglobin (HbF, α2g2) induction has long been an area of investigation, as it is known to reduce the clinical complications of sickle cell disease (SCD) and beta thalassemia. Progress in identifying novel HbF inducing strategies has been stymied by an incomplete understanding of gamma-globin regulation. We used natural genetic variation to identify novel genes and pathways associated with HbF levels in patients with SCD. Our whole exome sequencing analysis of 1290 samples from patients with SCD identified the insulin signaling pathway to be related to HbF regulation. Functional studies performed in hematopoietic stem and progenitor cells (HSPCs) from patients with SCD established that FOXO3 is a positive regulator of HbF, and that metformin, a FOXO3 and AMPK activator, can induce HbF (Zhang et al, Blood 2018). We hypothesized that other proteins in the insulin signaling pathway, particularly AMPK, a direct activator of FOXO3, may contribute to HbF regulation and be a potential target for pharmacologic induction of HbF. Objectives: We now seek to determine the role of AMPK and AMPK activators such as piceatannol in HbF regulation through functional studies in HSPCs from patients with SCD. Methods: HSPCs from 3 unique patients with SCD were transduced with AMPK shRNA on day 5 of two phase primary erythroid culture. AMPK, FOXO3, gamma and beta globin gene expression were measured by RT-qPCR and HbF by HPLC respectively on day 14 of culture. HSPCs from 3 unique patients with SCD were treated with AICAR, piceatannol at 12.5µM and metformin at 100 µM on day 7 of erythroid culture. Cell lysate was collected on day 14, and AMPK, FOXO3, gamma and beta globin gene expression and protein levels measured by RT-qPCR and western blot respectively. Levels of pAMPK, at Thr172, were quantified by western blot. 1 µM Compound C was added with piceatannol and with metformin in separate erythroid cultures on day 7, and the effect on gamma globin and phosphorylation of AMPK at Thr172 was measured on day 14 by RT-qPCR and western blot respectively. Results: 70% knockdown of AMPK resulted in a 50% decrease in HbF (p<0.01) and a three-fold reduction in gamma-globin expression (p<0.001). HSPCs treated with metformin or piceatannol exhibited a 2-3 fold rise in AMPK, FOXO3 and gamma globin gene expression (p<0.001). HSPCs treated with piceatannol and metformin showed an increase in pAMPK at Thr172, the activated form of AMPK. In the presence of a specific AMPK inhibitor, Compound C, metformin and piceatannol, no induction of gamma globin was observed (Figure 1), and pAMPK was reduced to untreated levels. Conclusions: Knockdown of AMPK in HSPCs reduces gamma globin expression and %HbF, supporting the role of AMPK in gamma globin regulation. Drugs known to activate AMPK, metformin and piceatannol, increase gamma globin in SCD patient derived HSPCs. Pharmacologic blockage of AMPK activity with Compound C results in reduction of HbF induction, and reduces the gamma globin induction of metformin and piceatannol to untreated levels. We therefore conclude that AMPK is a positive regulator of HbF, and that pharmacologic induction of HbF with metformin and piceatannol requires AMPK activity. Further work is needed to establish if FOXO3 and AMPK alone are instrumental in HbF regulation, or if other proteins in the insulin signaling pathway may play a role in HbF regulation. Disclosures No relevant conflicts of interest to declare.

scholarly journals Resveratrol stimulates microRNA expression during differentiation of bovine primary myoblasts

2021 ◽  
Author(s):  
Dan Hao ◽  
Xiao Wang ◽  
Xiaogang Wang ◽  
Bo Thomsen ◽  
Kaixing Qu ◽  
...  
Keyword(s):  
Signaling Pathway ◽  
Insulin Signaling ◽  
Target Genes ◽  
Group Versus ◽  
Enrichment Analysis ◽  
Treated Group ◽  
Insulin Signaling Pathway ◽  
Myoblast Differentiation ◽  
P Value ◽  
Go Terms

Background: Resveratrol (RSV), a phenolic compound, is present in many human dietary sources, such as peanuts, peanut butter, grapes skin, and grape wine. RSV has been widely known for its benefits on human health. Beef from cattle skeletal muscle is one of the main sources of protein for human consumption. Previous studies have also found that pork and chicken qualities are influenced by the feed supplementation with RSV. In addition, our previous study demonstrated the RSV effects on bovine myoblast differentiation using messenger RNA (mRNA) data. In this study, we mainly focused on the influences of RSV on microRNA (miRNA) expression. Method: We used 20 μM RSV to treat primary bovine myoblasts and extracted RNA for miRNA sequencing. After quality control and alignment for clean reads, we conducted quantification and analysis of differentially expressed (DE) miRNAs in the case (RSV-treated) group versus control (non-RSV treated) group. Next, we predicted the target genes for the DE miRNAs and analyzed them for the enrichments of Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Results: Finally, we identified 93 DE miRNAs (adjusted P-value < 0.05), of them 44 were upregulated and 49 were downregulated. Bta-miR-34c was the most significantly upregulated miRNA. In silico, prediction results indicated 1,869 target genes for the 93 DE miRNAs. GO enrichment analysis for the genes targeted by DE miRNAs revealed two significant GO terms (adjusted P-value < 0.05), in which the most significant one was stereocilium (GO:0032420). KEGG enrichment analysis showed five significant pathways, and the top significant KEGG pathway was the insulin signaling pathway (bta04910) (adjusted P-value < 0.05). Conclusions: This study provided an improved understanding of effects of RSV on primary bovine myoblast differentiation through the miRNA modulations. The results suggested that RSV could promote differentiation of primary bovine myoblast by stimulating the miRNA expressions. The target genes of DE miRNAs were significantly enriched in the insulin signaling pathway, thus potentially contributing to improving muscle leanness by increasing the energy metabolism.

scholarly journals Modulation of Renal Insulin Signaling Pathway and Antioxidant Enzymes with Streptozotocin-Induced Diabetes: Effects of Resveratrol

Medicina ◽  
2018 ◽  
Vol 55 (1) ◽  
pp. 3 ◽  
Author(s):  
Gökhan Sadi ◽  
Gamze Şahin ◽  
Aykut Bostanci
Keyword(s):  
Oxidative Stress ◽  
Gene Expression ◽  
Antioxidant Enzymes ◽  
Signaling Pathway ◽  
Insulin Signaling ◽  
Diabetic Rats ◽  
Insulin Signaling Pathway ◽  
Enzymatic Antioxidants ◽  
Gene And Protein Expression ◽  
Male Wistar Rats

Background and objectives: Diabetes mellitus is a disease of insulin deficiency or its inability of usage by the target tissues leading to impairment of carbohydrate, lipid, and protein metabolisms. Resveratrol, having robust anti-inflammatory and anti-oxidant properties, has a high potential to treat or prevent the pathogenesis of diseases. This study was conducted to reveal the relationship between diabetes-induced oxidative stress and tissue inflammation with changes in main enzymatic antioxidants (cat, sod, gpx, and gst) and the components of the insulin signaling pathway (insulin Rβ, irs-1, pi3k, akt, mtor) in kidney tissues. Additionally, the effects of resveratrol on these parameters were evaluated. Materials and Methods: Male Wistar rats were randomly divided into four groups; (1) control/vehicle; (2) control/20 mg/kg resveratrol; (3) diabetic/vehicle; (4) diabetic/20 mg/kg resveratrol. Gene and protein expressions of antioxidant enzymes and insulin signaling elements were evaluated in renal tissues. Results: Downregulation of antioxidant enzymes’ gene expression in the kidney tissues of diabetic rats was demonstrated and this situation was devoted partially to the reduced gene expression of nfκb. Moreover, the components of renal insulin signaling elements were upregulated at both gene and protein expression levels in diabetic rats, and resveratrol treatment decreased this sensitization towards the control state. Conclusion: Resveratrol partially improved diabetes-induced renal oxidative stress and inflammation due to healing action on renal antioxidant enzymes and insulin signaling pathway components.

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