Rapamycin negatively impacts insulin signaling, glucose uptake and uncoupling protein-1 in brown adipocytes.

New onset diabetes after transplantation (NODAT) is a metabolic disorder that affects 40% of patients on immunosuppressive agent (IA) treatment, such as rapamycin (also known as sirolimus). IAs negatively modulate insulin action in peripheral tissues including skeletal muscle, liver and white fat. However, the effects of IAs on insulin sensitivity and thermogenesis in brown adipose tissue (BAT) have not been investigated. We have analyzed the impact of rapamycin on insulin signaling, thermogenic gene-expression and mitochondrial respiration in BAT. Treatment of brown adipocytes with rapamycin for 16h significantly decreased insulin receptor substrate 1 (IRS1) protein expression and insulin-mediated protein kinase B (Akt) phosphorylation. Consequently, both insulin-induced glucose transporter 4 (GLUT4) translocation to the plasma membrane and glucose uptake were decreased. Early activation of the N-terminal Janus activated kinase (JNK) was also observed, thereby increasing IRS1 Ser 307 phosphorylation. These effects of rapamycin on insulin signaling in brown adipocytes were partly prevented by a JNK inhibitor. In vivo treatment of rats with rapamycin for three weeks abolished insulin-mediated Akt phosphorylation in BAT. Rapamycin also inhibited norepinephrine (NE)-induced lipolysis, the expression of peroxisome proliferator-activated receptor γ coactivator 1α (PGC-1α) and uncoupling protein (UCP)-1 in brown adipocytes. Importantly, basal mitochondrial respiration, proton leak and maximal respiratory capacity were significantly decreased in brown adipocytes treated with rapamycin. In conclusion, we demonstrate, for the first time the important role of brown adipocytes as target cells of rapamycin, suggesting that insulin resistance in BAT might play a major role in NODAT development.

Genome-wide identification of hypoxia-inducible factor binding sites and target genes by a probabilistic model integrating transcription-profiling data and in silico binding site prediction.

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.

Formal Meta-Analysis of Hypoxic Gene Expression Profiles Reveals a Universal Gene Signature.

Integrating transcriptional profiles results in identifying gene expression signatures that are more robust than those obtained for individual datasets. However, a direct comparison of datasets derived from heterogeneous experimental conditions is problematic, hence their integration requires applying 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 prevalent diseases. Accordingly, many studies have determined the gene expression profile of hypoxic cells. Yet, despite this wealth of information, little effort has been made to integrate these datasets to produce a robust hypoxic signature. We applied a formal meta-analysis procedure to datasets comprising 430 RNA-seq samples from 43 individual studies including 34 different cell types, to derive a pooled estimate of the effect of hypoxia on gene expression in human cell lines grown ingin vitro. This approach revealed that a large proportion of the transcriptome is significantly regulated by hypoxia (8556 out of 20,888 genes identified across studies). 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. Overall, we have developed a robust gene signature that characterizes the transcriptomic response of human cell lines exposed to hypoxia in vitro by applying a formal meta-analysis to gene expression profiles.

Metformin reduces macrophage HIF1α-dependent proinflammatory signaling to restore brown adipocyte function in vitro.

Therapeutic potential of metformin in obese/diabetic patients has been associated to its ability to combat insulin resistance. However, it remains largely unknown the signaling pathways involved and whether some cell types are particularly relevant for its beneficial effects. M1-activation of macrophages by bacterial lipopolysaccharide (LPS) promotes a paracrine activation of hypoxia-inducible factor-1α (HIF1α) in brown adipocytes which reduces insulin signaling and glucose uptake, as well as ß-adrenergic sensitivity. Addition of metformin to M1-polarized macrophages blunted these signs of brown adipocyte dysfunction. At the molecular level, metformin inhibits an inflammatory program executed by HIF1α in macrophages by inducing its degradation through the inhibition of mitochondrial complex I activity, thereby reducing oxygen consumption in a reactive oxygen species (ROS)-independent manner. In obese mice, metformin reduced inflammatory features in brown adipose tissue (BAT) such as macrophage infiltration, proinflammatory signaling and gene expression, and restored the response to cold exposure. In conclusion, the impact of metformin on macrophages by suppressing a HIF1α-dependent proinflammatory program is likely responsible for a secondary beneficial effect on insulin-mediated glucose uptake and ß-adrenergic responses in brown adipocytes.

Identification of a functional hypoxia-responsive element that regulates the expression of the egl nine homologue 3 (egln3/phd3) gene.

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.

Functional comparison of single-chain and two-chain anti-CD3-based bispecific antibodies in gene immunotherapy applications.

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.

Serum circulating microRNA profiling for identification of potential type 2 diabetes and obesity biomarkers.

BACKGROUND AND AIM: MicroRNAs 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 METHODS: Thirteen 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. RESULTS: Three 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. CONCLUSION: This 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.

Cooperativity of stress-responsive transcription factors in core hypoxia-inducible factor binding regions.

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.

Hypoxia promotes glycogen accumulation through hypoxia inducible factor (HIF)-mediated induction of glycogen synthase 1.

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 HIF1alpha 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-alpha 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.