The transcriptional response driven by Hypoxia-inducible factor (HIF) is central to the adaptation to oxygen restriction. Hence, the complete identification of HIF targets is essential for understanding the cellular responses to hypoxia. Herein we describe a computational strategy based on the combination of phylogenetic footprinting and transcription profiling meta-analysis for the identification of HIF-target genes. Comparison of the resulting candidates with published HIF1a genome-wide chromatin immunoprecipitation indicates a high sensitivity (78%) and specificity (97.8%). To validate our strategy, we performed HIF1a chromatin immunoprecipitation on a set of putative targets. Our results confirm the robustness of the computational strategy in predicting HIF-binding sites and reveal several novel HIF targets, including RE1-silencing transcription factor co-repressor (RCOR2). In addition, mapping of described polymorphisms to the predicted HIF-binding sites identified several single-nucleotide polymorphisms (SNPs) that could alter HIF binding. As a proof of principle, we demonstrate that SNP rs17004038, mapping to a functional hypoxia response element in the macrophage migration inhibitory factor (MIF) locus, prevents induction of this gene by hypoxia. Altogether, our results show that the proposed strategy is a powerful tool for the identification of HIF direct targets that expands our knowledge of the cellular adaptation to hypoxia and provides cues on the inter-individual variation in this response.

When oxygen becomes limiting, cells reduce mitochondrial respiration and increase ATP production through anaerobic fermentation of glucose. The Hypoxia Inducible Factors (HIFs) play a key role in this metabolic shift by regulating the transcription of key enzymes of glucose metabolism. Here we show that oxygen regulates the expression of the muscle glycogen synthase (GYS1). Hypoxic GYS1 induction requires HIF activity and a Hypoxia Response Element within its promoter. GYS1 gene induction correlated with a significant increase in glycogen synthase activity and glycogen accumulation in cells exposed to hypoxia. Significantly, knockdown of either HIF1α or GYS1 attenuated hypoxia-induced glycogen accumulation, while GYS1 overexpression was sufficient to mimic this effect. Altogether, these results indicate that GYS1 regulation by HIF plays a central role in the hypoxic accumulation of glycogen. Importantly, we found that hypoxia also upregulates the expression of UTP:glucose-1-phosphate urydylyltransferase (UGP2) and 1,4-α glucan branching enzyme (GBE1), two enzymes involved in the biosynthesis of glycogen. Therefore, hypoxia regulates almost all the enzymes involved in glycogen metabolism in a coordinated fashion, leading to its accumulation. Finally, we demonstrated that abrogation of glycogen synthesis, by knock-down of GYS1 expression, impairs hypoxic preconditioning, suggesting a physiological role for the glycogen accumulated during chronic hypoxia. In summary, our results uncover a novel effect of hypoxia on glucose metabolism, further supporting the central importance of metabolic reprogramming in the cellular adaptation to hypoxia.

Low oxygen levels induce an adaptive response in cells through the activation of HIFs (hypoxia-inducible factors). These transcription factors are mainly regulated by a group of proline hydroxylases that, in the presence of oxygen, target HIF for degradation. The expression of two such enzymes, EGLN1 [EGL nine homologous protein 1, where EGL stands for egg laying defective (Caenorhabditis elegans gene)] and EGLN3, is induced by hypoxia through a negative feedback loop, and we have demonstrated recently that hypoxic induction of EGLN expression is HIF-dependent. In the present study, we have identified an HRE (hypoxia response element) in the region of the EGLN3 gene using a combination of bioinformatics and biological approaches. Initially, we isolated a number of HRE consensus sequences in a region of 40 kb around the human EGLN3 gene and studied their evolutionary conservation. Subsequently, we examined the functionality of the conserved HRE sequences in reporter and chromatin precipitation assays. One of the HREs, located within a conserved region of the first intron of the EGLN3 gene 12 kb downstream of the transcription initiation site, bound HIF in vivo. Furthermore, this sequence was able to drive reporter gene expression under conditions of hypoxia in an HRE-dependent manner. Indeed, we were able to demonstrate that HIF was necessary and sufficient to induce gene expression from this enhancer sequence.

Background and AimMicroRNAs are small non-coding RNAs that play important regulatory roles in a variety of biological processes, including complex metabolic processes, such as energy and lipid metabolism, which have been studied in the context of diabetes and obesity. Some particular microRNAs have recently been demonstrated to abundantly and stably exist in serum and to be potentially disease-specific. The aim of this profiling study was to characterize the expression of miRNA in serum samples of obese, nonobese diabetic and obese diabetic individuals to determine whether miRNA expression was deregulated in these serum samples and to identify whether any observed deregulation was specific to either obesity or diabetes or obesity with diabetes.Patients and MethodsThirteen patients with type 2 diabetes, 20 obese patients, 16 obese patients with type 2 diabetes and 20 healthy controls were selected for this study. MiRNA PCR panels were employed to screen serum levels of 739 miRNAs in pooled samples from these four groups. We compared the levels of circulating miRNAs between serum pools of each group. Individual validation of the twelve microRNAs selected as promising biomarkers was carried out using RT-qPCR.ResultsThree serum microRNAs, miR-138, miR-15b and miR-376a, were found to have potential as predictive biomarkers in obesity. Use of miR-138 or miR-376a provides a powerful predictive tool for distinguishing obese patients from normal healthy controls, diabetic patients, and obese diabetic patients. In addition, the combination of miR-503 and miR-138 can distinguish diabetic from obese diabetic patients.ConclusionThis study is the first to show a panel of serum miRNAs for obesity, and compare them with miRNAs identified in serum for diabetes and obesity with diabetes. Our results support the use of some miRNAs extracted from serum samples as potential predictive tools for obesity and type 2 diabetes.

The transcriptional response driven by Hypoxia-inducible factor (HIF) is central to the adaptation to oxygen restriction. Despite recent characterization of genome-wide HIF DNA binding locations and hypoxia-regulated transcripts in different cell types, the molecular bases of HIF target selection remain unresolved. Herein, we combined multi-level experimental data and computational predictions to identify sequence motifs that may contribute to HIF target selectivity. We obtained a core set of bona fide HIF binding regions by integrating multiple HIF1 DNA binding and hypoxia expression profiling datasets. This core set exhibits evolutionarily conserved binding regions and is enriched in functional responses to hypoxia. Computational prediction of enriched transcription factor binding sites identified sequence motifs corresponding to several stress-responsive transcription factors, such as activator protein 1 (AP1), cAMP response element-binding (CREB), or CCAAT-enhancer binding protein (CEBP). Experimental validations on HIF-regulated promoters suggest a functional role of the identified motifs in modulating HIF-mediated transcription. Accordingly, transcriptional targets of these factors are over-represented in a sorted list of hypoxia-regulated genes. Altogether, our results implicate cooperativity among stress-responsive transcription factors in fine-tuning the HIF transcriptional response.

Gene therapy to achieve in vivo secretion of recombinant anti-CD3 x anti-tumor bispecific antibodies in cancer patients is being explored as a strategy to counterbalance rapid renal elimination, thereby sustaining levels of bispecific antibodies in the therapeutic range. Here, we performed a comparative analysis between single- and two-chain configurations for anti-CD3 x anti-CEA (carcinoembryonic antigen) bispecific antibodies secreted by genetically-modified human cells. We demonstrate that tandem single-chain variable fragment (scFv) antibodies and two-chain diabodies are expressed as soluble secreted proteins with similar yields. However, we found significant differences in their biological functionality (i.e., antigen binding) and in their ability to induce non-specific T cell activation. Whereas single-chain tandem scFvs induced human T cell activation and proliferation in an antigen-independent manner, secreted two-chain diabodies exerted almost no proliferative stimulus when human T cells were cultured alone or in co-cultures with CEA negative cells. Thus, our data suggest that two-chain diabodies are preferable to single-chain tandem scFvs for immunotherapeutic strategies comprising in vivo secretion of bispecific antibodies aiming to recruit and activate anticancer specific lymphocytic effector T cells.

BackgroundIntegrating transcriptional profiles results in the identification of gene expression signatures that are more robust than those obtained for individual datasets. However, direct comparison of datasets derived from heterogeneous experimental conditions is not possible and their integration requires the application of specific meta-analysis techniques. The transcriptional response to hypoxia has been the focus of intense research due to its central role in tissue homeostasis and in prevalent diseases. Accordingly, a large number of studies have determined the gene expression profile of hypoxic cells. Yet, in spite of this wealth of information, little effort have been done to integrate these dataset to produce a robust hypoxic signature.ResultsWe applied a formal meta-analysis procedure to a dataset comprising 425 RNAseq samples derived from 42 individual studies including 33 different cell types, to derive a pooled estimate of the effect of hypoxia on gene expression. This approach revealed that a large proportion of the transcriptome (8556 genes out of 20888) is significantly regulated by hypoxia. However, only a small fraction of the differentially expressed genes (1265 genes, 15%) show an effect size that, according to comparisons to gene pathways known to be regulated by hypoxia, is likely to be biologically relevant. By focusing on genes ubiquitously expressed we identified a signature of 291 genes robustly and consistently regulated by hypoxia. Finally, by a applying a moderator analysis we found that endothelial cells show a characteristic gene expression pattern that is significantly different from other cell types.ConclusionBy the application of a formal meta-analysis to hypoxic gene profiles, we have developed a robust gene signature that characterizes the transcriptomic response to low oxygen. In addition to identifying a universal set of hypoxia-responsive genes, we found a set of genes whose regulation is cell-type specific and suggest a unique metabolic response of endothelial cells to reduced oxygen tension.

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