Gene/Protein Disease Symptom Drug Enzyme Compound
Pivot Concepts:   Target Concepts:
Query: EC:2.7.11.11 (AMPK)
 12,425 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

Nucleoplasmic RNA polymerase II (nucleosidetriphosphate:RNA nucleotidyltransferase, EC 2.7.7.6) from calfthymus is phosphorylated by homologous cyclic AMP-independent protein kinase (ATP:protein phosphotransferase, EC 2.7.1.37). Polyacrylamide gel electrophoresis of the 32P-labeled RNA polymerase II under non-denaturing conditions revealed that both forms of the enzyme were phosphorylated. Polyacrylamide gel electrophoresis of the 32P-labeled RNA polymerase II under denaturing conditions showed that the 25 000 dalton subunit was the phosphate acceptor subunit. Partial acid hydrolysis of the 32P-labeled RNA polymerase II followed by ion-exchange chromatography revealed serine and threonine as the [32P]phosphate acceptor amino acids. Phosphorylation of the RNA polymerase II was accompanied by a stimulation of enzymatic activity and was dependent upon the presence of ATP.
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PMID:Phosphorylation of calf thymus RNA polymerase II by nuclear cyclic 3',5'-AMP-independent protein kinase. 20 18

Purified RNA polymerase II from chicken leukemia cells was found to be an effective substrate for protein kinase C but not cAMP-dependent protein kinase. Protein kinase C catalyzed the incorporation of 1-2 mol of phosphate per mol of polymerase II and the reaction was totally calcium and lipid dependent. Electrophoresis studies revealed a time-dependent increase of phosphate incorporation into RNA polymerase II subunits of 220 KDa, 180 KDa and 150 KDa, with a preferential phosphorylation of the 180 KDa polypeptide. The phosphorylated enzyme has a preference for using single-stranded DNA as the template for transcription, including transcription of the single-stranded myb oncogene sequence. Phosphoamino acid analysis indicated that both serine and threonine residues were phosphorylated at equal amounts. Phosphorylation by protein kinase C increased the affinity of substrate-polymerase binding and the initial rate of RNA synthesis, suggesting a mechanism by which gene expression can be activated by protein kinase C.
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PMID:Protein kinase C phosphorylates leukemia RNA polymerase II. 347 67

Ssn6 (Cyc8) is a component of the yeast general corepressor Ssn6-Tup1 that inhibits the transcription of many diversely regulated genes. The corepressor does not interact directly with DNA but is recruited to different promoters through interactions with distinct pathway-specific, DNA-binding repressor proteins. Using yeast two-hybrid and GST chromatography interaction experiments, we have determined that Sfl1, a novel repressor protein, interacts directly with Ssn6, and in vivo repression data suggest that Sfl1 inhibits transcription by recruiting Ssn6-Tup1 via a specific domain in the Sfl1 protein. Sin4 and Srb10, components of specific RNA polymerase II sub-complexes that are required for Ssn6-Tup1 repression activity, are found to be required for Sfl1 repression function. These results indicate a possible mechanism for Sfl1-mediated repression via Ssn6-Tup1 and specific subunits of the RNA polymerase II holoenzyme. Electrophoretic mobility shift and chromatin immuno-precipitation assays demonstrate that Sfl1 is present at the promoters of three Ssn6-Tup1-repressible genes; namely, FLO11, HSP26, and SUC2. Sfl1 is known to interact with Tpk2, a cAMP-dependent protein kinase that negatively regulates Sfl1 function. Consistently, we show that phosphorylation by protein kinase A inhibits Sfl1 DNA binding in vitro, and that a tpk2Delta mutation increases the levels of Sfl1 protein associated with specific promoter elements in vivo. These data indicate a possible mechanism for regulating Sfl1-mediated repression through modulation of DNA binding by cAMP-dependent protein kinase-dependent phosphorylation. Taken together with previous data, these new observations suggest a link between cAMP signaling and Ssn6-Tup1-mediated transcriptional repression.
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PMID:Sfl1 functions via the co-repressor Ssn6-Tup1 and the cAMP-dependent protein kinase Tpk2. 1139 75

The Saccharomyces cerevisiae Ras proteins control cell growth by regulating the activity of the cAMP-dependent protein kinase (PKA). In this study, a genetic approach was used to identify cellular processes that were regulated by Ras/PKA signaling activity. Interestingly, we found that mutations affecting the C-terminal domain (CTD), of Rpb1p, the largest subunit of RNA polymerase II, were very sensitive to changes in Ras signaling activity. The Rpb1p CTD is a highly conserved, repetitive structure that is a key site of control during the production of a mature mRNA molecule. We found that mutations compromising the CTD were synthetically lethal with alterations that led to elevated levels of Ras/PKA signaling. Altogether, the data suggested that Ras/PKA activity was negatively regulating a protein that functioned in concert with the CTD during RNA pol II transcription. Consistent with this prediction, we found that elevated levels of Ras signaling caused growth and transcription defects that were very similar to those observed in mutants encoding an Rpb1p with a truncated CTD. In all, these data suggested that S. cerevisiae growth control and RNA pol II transcription might be coupled by using the Ras pathway to regulate CTD function.
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PMID:The C-terminal domain of the largest subunit of RNA polymerase II is required for stationary phase entry and functionally interacts with the Ras/PKA signaling pathway. 1203 76

The Ras signaling pathway in Saccharomyces cerevisiae controls cell growth via the cAMP-dependent protein kinase, PKA. Recent work has indicated that these effects on growth are due, in part, to the regulation of activities associated with the C-terminal domain (CTD) of the largest subunit of RNA polymerase II. However, the precise target of these Ras effects has remained unknown. This study suggests that Ras/PKA activity regulates the elongation step of the RNA polymerase II transcription process. Several lines of evidence indicate that Spt5p in the Spt4p/Spt5p elongation factor is the likely target of this control. First, the growth of spt4 and spt5 mutants was found to be very sensitive to changes in Ras/PKA signaling activity. Second, mutants with elevated levels of Ras activity shared a number of specific phenotypes with spt5 mutants and vice versa. Finally, Spt5p was efficiently phosphorylated by PKA in vitro. Altogether, the data suggest that the Ras/PKA pathway might be directly targeting a component of the elongating polymerase complex and that this regulation is important for the normal control of yeast cell growth. These data point out the interesting possibility that signal transduction pathways might directly influence the elongation step of RNA polymerase II transcription.
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PMID:The Ras/PKA signaling pathway may control RNA polymerase II elongation via the Spt4p/Spt5p complex in Saccharomyces cerevisiae. 1466 64

Macroautophagy/autophagy is a catabolic process that allows cells to adapt to environmental changes and maintain energy homeostasis. This multistep process is regulated at several levels, including transcriptionally regulating autophagy-related (ATG) gene expression through the action of transcription regulators. Very recently, Wen et al. and we have provided more evidence that two well-known transcription factors regulate different ATG genes to control either nonselective or selective forms of autophagy, respectively. Under nitrogen-starvation conditions, the Spt4-Spt5 complex derepresses ATG8 and ATG41 expression and upregulates bulk autophagy activity. By contrast, under glucose-starvation conditions, the Paf1 complex (the polymerase-associated factor 1 complex, Paf1C) specifically modulates expression of ATG11 and ATG32 to regulate mitophagy. These studies suggest the potential existence of other transcription regulators yet to be discovered that function in the regulation of diverse autophagy pathways.Abbreviations: AMPK: AMP-activated protein kinase; ATG: autophagy-related; NELF: negative elongation factor; Paf1C/PAF1C: polymerase-associated factor 1 complex; RNAP II: RNA polymerase II; Rpd3L: Rpd3 large complex.
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PMID:Old factors, new players: transcriptional regulation of autophagy. 3205 19

BACKGROUND The underlying mechanism of insulin resistance is complex; bioinformatics analysis is used to explore the mechanism based differential expression genes (DEGs) obtained from omics analysis. However, the expression and role of most DEGs involved in bioinformatics analysis are invalidated. This study aimed to disclose the mechanism of insulin resistance via bioinformatics analysis based on validated insulin resistance-related genes (IRRGs) collected from public disease-gene databases. MATERIAL AND METHODS IRRGs were collected from 4 disease databases including NCBI-Gene, CTD, RGD, and Phenopedia. GO and KEGG analysis of IRRGs were performed by DAVID. Then, the STRING database was employed to construct a protein-protein interaction (PPI) network of IRRGs. The module analysis and hub genes identification were carried out by MCODE and cytoHubba plugin of Cytoscape based on the primary PPI network, respectively. RESULTS A total of 1195 IRRGs were identified. Response to drug, hypoxia, insulin, positive regulation of transcription from RNA polymerase II promoter, cell proliferation, inflammatory response, negative regulation of apoptotic process, glucose homeostasis, cellular response to insulin stimulus, and aging were proposed as the crucial functions related to insulin resistance. Ten insulin resistance-related pathways included the pathways of insulin resistance, pathways in cancer, adipocytokine, prostate cancer, PI3K-Akt, insulin, AMPK, HIF-1, prolactin, and pancreatic cancer signaling pathway were revealed. INS, AKT1, IL-6, TP53, TNF, VEGFA, MAPK3, EGFR, EGF, and SRC were identified as the top 10 hub genes. CONCLUSIONS The current study presented a landscape view of possible underlying mechanism of insulin resistance by bioinformatics analysis based on validated IRRGs.
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PMID:Underlying Mechanism of Insulin Resistance: A Bioinformatics Analysis Based on Validated Related-Genes from Public Disease Databases. 3265 53

Background: Chemotherapy is one of the most common therapies used in the treatment of colorectal cancer (CRC), but chemoresistance inevitably occurs. It is challenging to obtain an immediate and accurate diagnosis of chemoresistance. The potential of circulating exosomal miRNAs as oxaliplatin-based chemoresistant biomarkers in CRC patients was investigated in this study. Methods: Plasma exosomal miRNAs in sensitive and resistant patients were analyzed by miRNA microarray analysis, followed by verification with a quantitative reverse-transcription polymerase chain reaction (RT-qPCR) assay in two independent cohorts. The diagnostic accuracy was determined by ROC curve analysis. Logistic regression analysis and Spearman's rank correlation test were also performed. Finally, bioinformatics was used to preliminarily explore the potential molecular mechanism of the selected miRNAs in chemoresistance. Results: miRNA microarray analysis identified four upregulated miRNAs and 20 downregulated miRNAs in chemoresistant patients compared to chemosensitive patients. Twelve markedly dysregulated miRNAs were selected for further investigation, of which six (miR-100, miR-92a, miR-16, miR-30e, miR-144-5p, and let-7i) were verified to be significantly and consistently dysregulated (>1.5-fold, P < 0.05). The combination of the six miRNAs had the highest AUC (0.825, 95% CI, 0.753-0.897). The expression level of these 6 miRNAs was not correlated with tumor location, stage, or chemotherapy program. Only miR-100 was significantly upregulated in low histological grade. GO analysis and KEGG pathway analysis showed that miRNAs were related to RNA polymerase II transcription and enriched in the PI3K-AKT signaling pathway, AMPK signaling pathway, and FoxO signaling pathway. Conclusions: We identified a panel of plasma exosomal miRNAs, containing miR-100, miR-92a, miR-16, miR-30e, miR-144-5p, and let-7i, that could significantly distinguish chemoresistant patients from chemosensitive patients. The detection of circulating exosomal miRNAs may serve as an effective way to monitor CRC patient responses to chemotherapy. Targeting these miRNAs may also be a promising strategy for CRC treatment.
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PMID:Plasma Exosomal miRNA Expression Profile as Oxaliplatin-Based Chemoresistant Biomarkers in Colorectal Adenocarcinoma. 3307 45