Determination and comparison of specific activity of the HIF-prolyl hydroxylases

AbstractHypoxia-inducible factor (HIF) is a transcriptional complex that is regulated by oxygen sensitive hydroxylation of its α subunits by the prolyl hydroxylases PHD1, 2 and 3. To better understand the role of these enzymes in directing cellular responses to hypoxia, we derived an assay to determine their specific activity in both native cell extracts and recombinant sources of enzyme. We show that all three are capable of high rates of catalysis, in the order PHD2=PHD3>PHD1, using substrate peptides derived from the C-terminal degradation domain of HIF-α subunits, and that each demonstrates similar and remarkable sensitivity to oxygen, commensurate with a common role in signaling hypoxia

Integrated analysis of microRNA and mRNA expression and association with HIF binding reveals the complexity of microRNA expression regulation under hypoxia.

BACKGROUND: In mammalians, HIF is a master regulator of hypoxia gene expression through direct binding to DNA, while its role in microRNA expression regulation, critical in the hypoxia response, is not elucidated genome wide. Our aim is to investigate in depth the regulation of microRNA expression by hypoxia in the breast cancer cell line MCF-7, establish the relationship between microRNA expression and HIF binding sites, pri-miRNA transcription and microRNA processing gene expression. METHODS: MCF-7 cells were incubated at 1% Oxygen for 16, 32 and 48 h. SiRNA against HIF-1α and HIF-2α were performed as previously published. MicroRNA and mRNA expression were assessed using microRNA microarrays, small RNA sequencing, gene expression microarrays and Real time PCR. The Kraken pipeline was applied for microRNA-seq analysis along with Bioconductor packages. Microarray data was analysed using Limma (Bioconductor), ChIP-seq data were analysed using Gene Set Enrichment Analysis and multiple testing correction applied in all analyses. RESULTS: Hypoxia time course microRNA sequencing data analysis identified 41 microRNAs significantly up- and 28 down-regulated, including hsa-miR-4521, hsa-miR-145-3p and hsa-miR-222-5p reported in conjunction with hypoxia for the first time. Integration of HIF-1α and HIF-2α ChIP-seq data with expression data showed overall association between binding sites and microRNA up-regulation, with hsa-miR-210-3p and microRNAs of miR-27a/23a/24-2 and miR-30b/30d clusters as predominant examples. Moreover the expression of hsa-miR-27a-3p and hsa-miR-24-3p was found positively associated to a hypoxia gene signature in breast cancer. Gene expression analysis showed no full coordination between pri-miRNA and microRNA expression, pointing towards additional levels of regulation. Several transcripts involved in microRNA processing were found regulated by hypoxia, of which DICER (down-regulated) and AGO4 (up-regulated) were HIF dependent. DICER expression was found inversely correlated to hypoxia in breast cancer. CONCLUSIONS: Integrated analysis of microRNA, mRNA and ChIP-seq data in a model cell line supports the hypothesis that microRNA expression under hypoxia is regulated at transcriptional and post-transcriptional level, with the presence of HIF binding sites at microRNA genomic loci associated with up-regulation. The identification of hypoxia and HIF regulated microRNAs relevant for breast cancer is important for our understanding of disease development and design of therapeutic interventions

A Novel Nomogram Model to Predict the Recurrence-Free Survival and Overall Survival of Hepatocellular Carcinoma

BackgroundTreatments for patients with early‐stage hepatocellular carcinoma (HCC) include liver transplantation (LT), liver resection (LR), radiofrequency ablation (RFA), and microwave ablation (MWA), are critical for their long-term survival. However, a computational model predicting treatment-independent prognosis of patients with HCC, such as overall survival (OS) and recurrence-free survival (RFS), is yet to be developed, to our best knowledge. The goal of this study is to identify prognostic factors associated with OS and RFS in patients with HCC and develop nomograms to predict them, respectively.MethodsWe retrospectively retrieved 730 patients with HCC from three hospitals in China and followed them up for 3 and 5 years after invasive treatment. All enrolled patients were randomly divided into the training cohort and the validation cohort with a 7:3 ratio, respectively. Independent prognostic factors associated with OS and RFS were determined by the multivariate Cox regression analysis. Two nomogram prognostic models were built and evaluated by concordance index (C-index), calibration curves, area under the receiver operating characteristics (ROC) curve, time-dependent area under the ROC curve (AUC), the Kaplan–Meier survival curve, and decision curve analyses (DCAs), respectively.ResultsPrognostic factors for OS and RFS were identified, and nomograms were successfully built. Calibration discrimination was good for both the OS and RFS nomogram prediction models (C-index: 0.750 and 0.746, respectively). For both nomograms, the AUC demonstrated outstanding predictive performance; the DCA shows that the model has good decision ability; and the calibration curve demonstrated strong predictive power. The nomograms successfully discriminated high-risk and low-risk patients with HCC associated with OS and RFS.ConclusionsWe developed nomogram survival prediction models to predict the prognosis of HCC after invasive treatment with acceptable accuracies in both training and independent testing cohorts. The models may have clinical values in guiding the selection of clinical treatment strategies

Global mRNA and Long Non-Coding RNA Expression in the Placenta and White Adipose Tissue of Mice Fed a High-Fat Diet During Pregnancy

Background/Aims: Gestational diabetes mellitus (GDM) is a common complication of pregnancy, but the mechanisms underlying the disorders remain unclear. The study aimed to identify mRNA and long non-coding RNA (lncRNA) profiles in placenta and gonadal fat of pregnant mice fed a high-fat diet and to investigate the transcripts and pathways involved in the development of gestational diabetes mellitus. Methods: Deep and broad transcriptome profiling was performed to assess the expression of mRNAs and lncRNAs in placenta and gonadal fat from 3 mice fed an HFD and chow during pregnancy. Then, differentially expressed mRNAs and lncRNAs were validated by quantitative real-time PCR. The function of the differentially expressed mRNAs was determined by pathway and Gene Ontology (GO) analyses, and the physical or functional relationships between the lncRNAs and the corresponding mRNAs were determined. Results: Our study revealed that 82 mRNAs and 52 lncRNAs were differentially expressed in the placenta of mice fed an HFD during pregnancy, and 202 mRNAs and 120 lncRNAs were differentially expressed in gonadal fat. GO and Kyoto Encyclopedia of Genes and Genomes pathway analyses revealed differentially expressed mRNAs of placenta were closely related to extracellular matrix interactions, digestion, adhesion, and metabolism, whereas the differentially expressed mRNAs in adipose tissue were related to metabolic and insulin signalling pathways. The gene network demonstrated that Actg2, Cnfn, Muc16, Serpina3k, NONMMUT068202, and NONMMUT068203, were the core of the network in placental tissue, and the genes Tkt, Acss2, and Elovl6 served as the core of the network in gonadal fat tissue. Conclusion: These newly identified key genes and pathways in mice might provide valuable information regarding the pathogenesis of GDM and might be used to improve early diagnosis, prevention, drug design, and clinical treatment

Assessing the Effect of Simultaneous Combining of Transcranial Direct Current Stimulation and Transcutaneous Auricular Vagus Nerve Stimulation on the Improvement of Working Memory Performance in Healthy Individuals

A previous study found that combining transcranial direct current stimulation (tDCS) and transcutaneous auricular vagus nerve stimulation (taVNS) could evoke significantly larger activation on a range of cortical and subcortical brain regions than the numerical summation of tDCS and taVNS effects. In this study, two within-subject experiments were employed to investigate its effects on working memory (WM). In experiment 1, the WM modulatory effects of tDCS over the left dorsolateral prefrontal cortex (DLPFC), taVNS, and simultaneous joint simulation of tDCS over the left DLPFC and taVNS (SJS-L) were compared among 60 healthy subjects. They received these three interventions between the baseline test and post-test in a random manner three times. In spatial 3-back task, there was a significant interaction between time and stimulations in the accuracy rate of matching trials (mACC, p=0.018). MACCs were significantly improved by SJS (p = 0.001) and taVNS (p = 0.045), but not by tDCS (p = 0.495). Moreover, 41 subjects in the SJS group showed improvement, which was significantly larger than that in the taVNS group (29 subjects) and tDCS group (26 subjects). To further investigate the generalization effects of SJS, 72 students were recruited in experiment 2. They received tDCS over the right DLPFC, taVNS, simultaneous joint simulation of tDCS over the right DLPFC and taVNS (SJS-R), and sham stimulation in a random manner four times. No significant results were found, but there was a tendency similar to experiment 1 in the spatial 3-back task. In conclusion, combining tDCS and taVNS might be a potential non-invasive neuromodulation technique which is worthy of study in future

Control of Cotton Fibre Elongation by a Homeodomain Transcription Factor GhHOX3

Cotton fibres are unusually long, single-celled epidermal seed trichomes and a model for plant cell growth, but little is known about the regulation of fibre cell elongation. Here we report that a homeodomain-leucine zipper (HD-ZIP) transcription factor, GhHOX3, controls cotton fibre elongation. GhHOX3 genes are localized to the 12th homoeologous chromosome set of allotetraploid cotton cultivars, associated with quantitative trait loci (QTLs) for fibre length. Silencing of GhHOX3 greatly reduces (\u3e80%) fibre length, whereas its overexpression leads to longer fibre. Combined transcriptomic and biochemical analyses identify target genes of GhHOX3 that also contain the L1-box cis-element, including two cell wall loosening protein genes GhRDL1 and GhEXPA1. GhHOX3 interacts with GhHD1, another homeodomain protein, resulting in enhanced transcriptional activity, and with cotton DELLA, GhSLR1, repressor of the growth hormone gibberellin (GA). GhSLR1 interferes with the GhHOX3–GhHD1 interaction and represses target gene transcription. Our results uncover a novel mechanism whereby a homeodomain protein transduces GA signal to promote fibre cell elongation

Whole-genome sequencing of native sheep provides insights into rapid adaptations to extreme environments

201