Estrogen-related receptor α (ERRα) : a novel target in type 2 diabetes

Recent studies have shown that reduced mitochondrial content and function in skeletal muscle are common features of type 2 diabetes. Here, we review the molecular mechanisms involved in the regulation of mitochondrial genes in skeletal muscle, focusing on a key transcriptional network consisting of ERRα and PGC-1α. We describe how knowledge of this transcriptional circuit can be translated to the development of novel therapies for type 2 diabetes

Oligonucleotides targeting TCF4 triplet repeat expansion inhibit RNA foci and mis-splicing in Fuchs\u27 dystrophy

Fuchs\u27 endothelial corneal dystrophy (FECD) is the most common repeat expansion disorder. FECD impacts 4% of U.S. population and is the leading indication for corneal transplantation. Most cases are caused by an expanded intronic CUG tract in the TCF4 gene that forms nuclear foci, sequesters splicing factors and impairs splicing. We investigated the sense and antisense RNA landscape at the FECD gene and find that the sense-expanded repeat transcript is the predominant species in patient corneas. In patient tissue, sense foci number were negatively correlated with age and showed no correlation with sex. Each endothelial cell has approximately 2 sense foci and each foci is single RNA molecule. We designed antisense oligonucleotides (ASOs) to target the mutant-repetitive RNA and demonstrated potent inhibition of foci in patient-derived cells. Ex vivo treatment of FECD human corneas effectively inhibits foci and reverses pathological changes in splicing. FECD has the potential to be a model for treating many trinucleotide repeat diseases and targeting the TCF4 expansion with ASOs represents a promising therapeutic strategy to prevent and treat FECD

Interpreting microarray experiments via co-expressed gene groups analysis

International audienceMicroarray technology produces vast amounts of data by measuring simultaneously the expression levels of thousands of genes under hundreds of biological conditions. Nowadays, one of the principal challenges in bioinformatics is the interpretation of huge data using different sources of information. We propose a novel data analysis method named CGGA (Co-expressed Gene Groups Analysis) that automatically finds groups of genes that are functionally enriched, i.e. have the same functional annotations, and are co- expressed. CGGA automatically integrates the information of microarrays, i.e. gene expression profiles, with the functional annotations of the genes obtained by the genome-wide information sources such as Gene Ontology (GO)1. By applying CGGA to well-known microarray experiments, we have identified the principal functionally enriched and co-expressed gene groups, and we have shown that this approach enhances and accelerates the interpretation of DNA microarray experiments

Energy Metabolism in Uncoupling Protein 3 Gene Knockout Mice

Uncoupling protein 3 (UCP3) is a member of the mitochondrial anion carrier superfamily. Based upon its high homology with UCP1 and its restricted tissue distribution to skeletal muscle and brown adipose tissue, UCP3 has been suggested to play important roles in regulating energy expenditure, body weight, and thermoregulation. Other postulated roles for UCP3 include regulation of fatty acid metabolism, adaptive responses to acute exercise and starvation, and prevention of reactive oxygen species (ROS) formation. To address these questions, we have generated mice lacking UCP3 (UCP3 knockout (KO) mice). Here, we provide evidence that skeletal muscle mitochondria lacking UCP3 are more coupled (i.e. increased state 3/state 4 ratio), indicating that UCP3 has uncoupling activity. In addition, production of ROS is increased in mitochondria lacking UCP3. This study demonstrates that UCP3 has uncoupling activity and that its absence may lead to increased production of ROS. Despite these effects on mitochondrial function, UCP3 does not seem to be required for body weight regulation, exercise tolerance, fatty acid oxidation, or cold-induced thermogenesis. The absence of such phenotypes in UCP3 KO mice could not be attributed to up-regulation of other UCP mRNAs. However, alternative compensatory mechanisms cannot be excluded. The consequence of increased mitochondrial coupling in UCP3 KO mice on metabolism and the possible role of yet unidentified compensatory mechanisms, remains to be determined

Energy Metabolism in Uncoupling Protein 3 Gene Knockout Mice

Uncoupling protein 3 (UCP3) is a member of the mitochondrial anion carrier superfamily. Based upon its high homology with UCP1 and its restricted tissue distribution to skeletal muscle and brown adipose tissue, UCP3 has been suggested to play important roles in regulating energy expenditure, body weight, and thermoregulation. Other postulated roles for UCP3 include regulation of fatty acid metabolism, adaptive responses to acute exercise and starvation, and prevention of reactive oxygen species (ROS) formation. To address these questions, we have generated mice lacking UCP3 (UCP3 knockout (KO) mice). Here, we provide evidence that skeletal muscle mitochondria lacking UCP3 are more coupled (i.e. increased state 3/state 4 ratio), indicating that UCP3 has uncoupling activity. In addition, production of ROS is increased in mitochondria lacking UCP3. This study demonstrates that UCP3 has uncoupling activity and that its absence may lead to increased production of ROS. Despite these effects on mitochondrial function, UCP3 does not seem to be required for body weight regulation, exercise tolerance, fatty acid oxidation, or cold-induced thermogenesis. The absence of such phenotypes in UCP3 KO mice could not be attributed to up-regulation of other UCP mRNAs. However, alternative compensatory mechanisms cannot be excluded. The consequence of increased mitochondrial coupling in UCP3 KO mice on metabolism and the possible role of yet unidentified compensatory mechanisms, remains to be determined

MCM-test: a fuzzy-set-theory-based approach to differential analysis of gene pathways

Abstract Background Gene pathway can be defined as a group of genes that interact with each other to perform some biological processes. Along with the efforts to identify the individual genes that play vital roles in a particular disease, there is a growing interest in identifying the roles of gene pathways in such diseases. Results This paper proposes an innovative fuzzy-set-theory-based approach, Multi-dimensional Cluster Misclassification test (MCM-test), to measure the significance of gene pathways in a particular disease. Experiments have been conducted on both synthetic data and real world data. Results on published diabetes gene expression dataset and a list of predefined pathways from KEGG identified OXPHOS pathway involved in oxidative phosphorylation in mitochondria and other mitochondrial related pathways to be deregulated in diabetes patients. Our results support the previously supported notion that mitochondrial dysfunction is an important event in insulin resistance and type-2 diabetes. Conclusion Our experiments results suggest that MCM-test can be successfully used in pathway level differential analysis of gene expression datasets. This approach also provides a new solution to the general problem of measuring the difference between two groups of data, which is one of the most essential problems in most areas of research

Hypoxia as a therapy for mitochondrial disease

Defects in the mitochondrial respiratory chain (RC) underlie a spectrum of human conditions, ranging from devastating inborn errors of metabolism to aging. We performed a genome-wide Cas9-mediated screen to identify factors that are protective during RC inhibition. Our results highlight the hypoxia response, an endogenous program evolved to adapt to limited oxygen availability. Genetic or small-molecule activation of the hypoxia response is protective against mitochondrial toxicity in cultured cells and zebrafish models. Chronic hypoxia leads to a marked improvement in survival, body weight, body temperature, behavior, neuropathology, and disease biomarkers in a genetic mouse model of Leigh syndrome, the most common pediatric manifestation of mitochondrial disease. Further preclinical studies are required to assess whether hypoxic exposure can be developed into a safe and effective treatment for human diseases associated with mitochondrial dysfunction.National Institute of Mental Health (U.S.) (Grant 5DP1-MH100706)National Institute of Mental Health (U.S.) (Grant 1R01-MH110049)National Institute of Neurological Diseases and Stroke (U.S.) (Grant 5R01DK097768-03

Computation of significance scores of unweighted Gene Set Enrichment Analyses

<p>Abstract</p> <p>Background</p> <p>Gene Set Enrichment Analysis (GSEA) is a computational method for the statistical evaluation of sorted lists of genes or proteins. Originally GSEA was developed for interpreting microarray gene expression data, but it can be applied to any sorted list of genes. Given the gene list and an arbitrary biological category, GSEA evaluates whether the genes of the considered category are randomly distributed or accumulated on top or bottom of the list. Usually, significance scores (p-values) of GSEA are computed by nonparametric permutation tests, a time consuming procedure that yields only estimates of the p-values.</p> <p>Results</p> <p>We present a novel dynamic programming algorithm for calculating exact significance values of unweighted Gene Set Enrichment Analyses. Our algorithm avoids typical problems of nonparametric permutation tests, as varying findings in different runs caused by the random sampling procedure. Another advantage of the presented dynamic programming algorithm is its runtime and memory efficiency. To test our algorithm, we applied it not only to simulated data sets, but additionally evaluated expression profiles of squamous cell lung cancer tissue and autologous unaffected tissue.</p