Insulin degrading enzyme (IDE) is a major enzyme responsible for insulin degradation in the liver. The modulation of insulin degrading enzyme activity is hypothesized to be a link between T2DM and liver cancer. Results provide insight into role of IDE in proliferation and other cell functions.
Modulation of insulin degrading enzyme activity and liver cell proliferation.
Cell line
View SamplesThis SuperSeries is composed of the SubSeries listed below.
Transcriptome profile analysis reflects rat liver and kidney damage following chronic ultra-low dose Roundup exposure.
Sex, Specimen part
View SamplesGlyphosate-based herbicides (GBH) are the major pesticides used worldwide. Converging evidence suggests that GBH residues pose a particular risk to the kidneys and liver. However, the existence of biological effects with negative health implications at low environmentally relevant doses remains unresolved. A previous investigation addressed this issue, by conducting a 2-year feeding study, which included 10 female Sprague Dawley rats administered via drinking water with 0.1 ppb of a major Roundup formulation (50 ng/L glyphosate equivalent dilution). Hepatorenal toxicities, as well as urine and blood biochemistry disturbances at the 15th month of age were observed. In an effort to obtain molecular mechanistic insight into the underlying causes of these pathologies, we have carried out a transcriptome microarray analysis of the liver and kidneys from these same animals. The expression of 4224 and 4447 genes were found to be disturbed respectively in liver and kidney (p<0.01, q<0.08, fold change >1.1). Among the 1319 genes whose expression was altered in both tissues, 3 functional categories were over-represented. First, genes involved in mRNA splicing and small nucleolar RNA were mostly upregulated, suggesting disruption of normal spliceosome activity. Electron microscopic analysis of hepatocytes confirmed nucleolar structural disruption. Second, genes controlling chromatin structure (especially histone-lysine N-methyltransferases) were mostly upregulated. Third, genes related to respiratory chain complex I and the tricarboxylic acid cycle were mostly downregulated. The transcription factor networks that can account for these disruptions were centered on CREB1, ESR1, YY1, c-Myc and Oct3/4 activity, which are known to closely cooperate in the regulation of gene expression after hormonal stimulation. The analysis of pathways and toxicity processes showed that these disturbances in gene expression were representative of fibrosis, necrosis, phospholipidosis, mitochondrial membrane dysfunction and ischemia, which correlate with the pathologies observed at an anatomical and histological level. Our results suggest that new studies incorporating testing principles from endocrinology and developmental epigenetics need to be performed to investigate potential consequences of exposure to low dose, environmental levels of GBH and glyphosate.
Transcriptome profile analysis reflects rat liver and kidney damage following chronic ultra-low dose Roundup exposure.
Sex, Specimen part
View SamplesGlyphosate-based herbicides (GBH) are the major pesticides used worldwide. Converging evidence suggests that GBH residues pose a particular risk to the kidneys and liver. However, the existence of biological effects with negative health implications at low environmentally relevant doses remains unresolved. A previous investigation addressed this issue, by conducting a 2-year feeding study, which included 10 female Sprague Dawley rats administered via drinking water with 0.1 ppb of a major Roundup formulation (50 ng/L glyphosate equivalent dilution). Hepatorenal toxicities, as well as urine and blood biochemistry disturbances at the 15th month of age were observed. In an effort to obtain molecular mechanistic insight into the underlying causes of these pathologies, we have carried out a transcriptome microarray analysis of the liver and kidneys from these same animals. The expression of 4224 and 4447 genes were found to be disturbed respectively in liver and kidney (p<0.01, q<0.08, fold change >1.1). Among the 1319 genes whose expression was altered in both tissues, 3 functional categories were over-represented. First, genes involved in mRNA splicing and small nucleolar RNA were mostly upregulated, suggesting disruption of normal spliceosome activity. Electron microscopic analysis of hepatocytes confirmed nucleolar structural disruption. Second, genes controlling chromatin structure (especially histone-lysine N-methyltransferases) were mostly upregulated. Third, genes related to respiratory chain complex I and the tricarboxylic acid cycle were mostly downregulated. The transcription factor networks that can account for these disruptions were centered on CREB1, ESR1, YY1, c-Myc and Oct3/4 activity, which are known to closely cooperate in the regulation of gene expression after hormonal stimulation. The analysis of pathways and toxicity processes showed that these disturbances in gene expression were representative of fibrosis, necrosis, phospholipidosis, mitochondrial membrane dysfunction and ischemia, which correlate with the pathologies observed at an anatomical and histological level. Our results suggest that new studies incorporating testing principles from endocrinology and developmental epigenetics need to be performed to investigate potential consequences of exposure to low dose, environmental levels of GBH and glyphosate.
Transcriptome profile analysis reflects rat liver and kidney damage following chronic ultra-low dose Roundup exposure.
Sex, Specimen part
View SamplesSeveral different mechanisms have been proposed to explain the possible role of cranberries, cranberry juice, and cranberry extracts in inhibiting bacterial growth. In this report, we showed that Escherichia coli showed slower growth rate in response to the presence of cranberry juice in the growth media. By compareing the global transcript profiles, significant modulation of several genes of E. coli grown in LB broth with 10% cranberry juice were identified and provided identification of the potential mechanisms involved in the inhibitory effects of cranberry juice. The results presented clearly demonstrate that the inhibitory effect on bacterial growth observed in the presence of cranberry juice/extracts is primarily a result of the iron chelation capacity of PACs and direct disruption of metabolic enzymes. The results are discussed with a focus on the genes associated with iron chelation capability.
Impact of cranberry on Escherichia coli cellular surface characteristics.
No sample metadata fields
View SamplesAims: To assess the virulence of multiple Aeromonas spp. using two models, a neonatal mouse assay and a mouse intestinal cell culture.
Evaluating virulence of waterborne and clinical Aeromonas isolates using gene expression and mortality in neonatal mice followed by assessing cell culture's ability to predict virulence based on transcriptional response.
No sample metadata fields
View SamplesThe goal of this study was to identify transcriptional differences between varying combinations of Tet deletion clones following six days of LIF withdrawal. These libraries were generated from cells under normal culture conditions. Overall design: RNA-seq libraries were generated for 3 WT, 3 Tet1-/-, 2 Tet2-/-, DKO, and TKO clones. Sequencing was done on a Illumina NextSeq 500 for all paired end reads
Deletion of Tet proteins results in quantitative disparities during ESC differentiation partially attributable to alterations in gene expression.
Cell line, Subject, Time
View SamplesWe analyzed the generation of mouse gliomas following the overexpression of PDGF-B in embryonic neural progenitors. Comparison of our microarray data, with published gene expression data sets for many different murine neural cell types, revealed a closest relationship between our tumor cells and oligodendrocyte progenitor cells, confirming definitively that PDGF-B-induced gliomas are pure oligodendrogliomas.
PDGF-B induces a homogeneous class of oligodendrogliomas from embryonic neural progenitors.
No sample metadata fields
View SamplesThis SuperSeries is composed of the SubSeries listed below.
Integration Analysis of Three Omics Data Using Penalized Regression Methods: An Application to Bladder Cancer.
Specimen part
View SamplesOmics data integration is becoming necessary to investigate the still unknown genomic mechanisms of complex diseases. During the integration process, many challenges arise such as data heterogeneity, the smaller number of individuals in comparison to the number of parameters, multicollinearity, and interpretation and validation of results due to their complexity and lack of knowledge about biological mechanisms. To overcome some of these issues, innovative statistical approaches are being developed. In this work, we applied penalized regression methods (LASSO and ENET) to explore relationships between common genetic variants, DNA methylation and gene expression measured in bladder tumor samples and have proposed a permutation-based method to concomitantly assess significance and correct by multiple testing with the MaxT algorithm. The overall analysis flow consisted of three steps: (1) SNPs/CpGs were selected per each gene probe within 1Mb window upstream and downstream the gene; (2) LASSO and ENET were applied to assess the association between each expression probe and the selected SNPs/CpGs in three multivariable models (SNP, CPG, and Global models, the latter integrating SNPs and CPGs); and (3) the significance of each model was assessed using the permutation-based MaxT method. We identified 48 genes whom expression levels were associated with both SNPs and GPGs. Importantly, we replicated results for 36 (75%) of them in an independent data set (TCGA). We checked the performance of the proposed method with a simulation study and further supported our results with a biological interpretation based on an enrichment analysis. The approach we propose allows reducing computational time and is flexibly and easy to implement when analyzing several omics data. Our results highlight the importance of integrating omics data by applying appropriate statistical strategies to discover new insights into the complexity of disease genetic mechanisms.
Integration Analysis of Three Omics Data Using Penalized Regression Methods: An Application to Bladder Cancer.
Specimen part
View Samples