78 research outputs found

    Gut microbiota and diabetes: from pathogenesis to therapeutic perspective

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    More than several hundreds of millions of people will be diabetic and obese over the next decades in front of which the actual therapeutic approaches aim at treating the consequences rather than causes of the impaired metabolism. This strategy is not efficient and new paradigms should be found. The wide analysis of the genome cannot predict or explain more than 10–20% of the disease, whereas changes in feeding and social behavior have certainly a major impact. However, the molecular mechanisms linking environmental factors and genetic susceptibility were so far not envisioned until the recent discovery of a hidden source of genomic diversity, i.e., the metagenome. More than 3 million genes from several hundreds of species constitute our intestinal microbiome. First key experiments have demonstrated that this biome can by itself transfer metabolic disease. The mechanisms are unknown but could be involved in the modulation of energy harvesting capacity by the host as well as the low-grade inflammation and the corresponding immune response on adipose tissue plasticity, hepatic steatosis, insulin resistance and even the secondary cardiovascular events. Secreted bacterial factors reach the circulating blood, and even full bacteria from intestinal microbiota can reach tissues where inflammation is triggered. The last 5 years have demonstrated that intestinal microbiota, at its molecular level, is a causal factor early in the development of the diseases. Nonetheless, much more need to be uncovered in order to identify first, new predictive biomarkers so that preventive strategies based on pre- and probiotics, and second, new therapeutic strategies against the cause rather than the consequence of hyperglycemia and body weight gain

    Deep Sequencing the Transcriptome Reveals Seasonal Adaptive Mechanisms in a Hibernating Mammal

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    Mammalian hibernation is a complex phenotype involving metabolic rate reduction, bradycardia, profound hypothermia, and a reliance on stored fat that allows the animal to survive for months without food in a state of suspended animation. To determine the genes responsible for this phenotype in the thirteen-lined ground squirrel (Ictidomys tridecemlineatus) we used the Roche 454 platform to sequence mRNA isolated at six points throughout the year from three key tissues: heart, skeletal muscle, and white adipose tissue (WAT). Deep sequencing generated approximately 3.7 million cDNA reads from 18 samples (6 time points ×3 tissues) with a mean read length of 335 bases. Of these, 3,125,337 reads were assembled into 140,703 contigs. Approximately 90% of all sequences were matched to proteins in the human UniProt database. The total number of distinct human proteins matched by ground squirrel transcripts was 13,637 for heart, 12,496 for skeletal muscle, and 14,351 for WAT. Extensive mitochondrial RNA sequences enabled a novel approach of using the transcriptome to construct the complete mitochondrial genome for I. tridecemlineatus. Seasonal and activity-specific changes in mRNA levels that met our stringent false discovery rate cutoff (1.0×10−11) were used to identify patterns of gene expression involving various aspects of the hibernation phenotype. Among these patterns are differentially expressed genes encoding heart proteins AT1A1, NAC1 and RYR2 controlling ion transport required for contraction and relaxation at low body temperatures. Abundant RNAs in skeletal muscle coding ubiquitin pathway proteins ASB2, UBC and DDB1 peak in October, suggesting an increase in muscle proteolysis. Finally, genes in WAT that encode proteins involved in lipogenesis (ACOD, FABP4) are highly expressed in August, but gradually decline in expression during the seasonal transition to lipolysis

    Implication for Functions of the Ectopic Adipocyte Copper Amine Oxidase (AOC3) from Purified Enzyme and Cell-Based Kinetic Studies

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    AOC3 is highly expressed in adipocytes and smooth muscle cells, but its function in these cells is currently unknown. The in vivo substrate(s) of AOC3 is/are also unknown, but could provide an invaluable clue to the enzyme's function. Expression of untagged, soluble human AOC3 in insect cells provides a relatively simple means of obtaining pure enzyme. Characterization of enzyme indicates a 6% titer for the active site 2,4,5-trihydroxyphenylalanine quinone (TPQ) cofactor and corrected kcat values as high as 7 s−1. Substrate kinetic profiling shows that the enzyme accepts a variety of primary amines with different chemical features, including nonphysiological branched-chain and aliphatic amines, with measured kcat/Km values between 102 and 104 M−1 s−1. Km(O2) approximates the partial pressure of oxygen found in the interstitial space. Comparison of the properties of purified murine to human enzyme indicates kcat/Km values that are within 3 to 4-fold, with the exception of methylamine and aminoacetone that are ca. 10-fold more active with human AOC3. With drug development efforts investigating AOC3 as an anti-inflammatory target, these studies suggest that caution is called for when screening the efficacy of inhibitors designed against human enzymes in non-transgenic mouse models. Differentiated murine 3T3-L1 adipocytes show a uniform distribution of AOC3 on the cell surface and whole cell Km values that are reasonably close to values measured using purified enzymes. The latter studies support a relevance of the kinetic parameters measured with isolated AOC3 variants to adipocyte function. From our studies, a number of possible substrates with relatively high kcat/Km have been discovered, including dopamine and cysteamine, which may implicate a role for adipocyte AOC3 in insulin-signaling and fatty acid metabolism, respectively. Finally, the demonstrated AOC3 turnover of primary amines that are non-native to human tissue suggests possible roles for the adipocyte enzyme in subcutaneous bacterial infiltration and obesity

    Pan-cancer analysis of whole genomes

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    Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe
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