11 research outputs found

    Microevolution of Pandemic Vibrio parahaemolyticus Assessed by the Number of Repeat Units in Short Sequence Tandem Repeat Regions

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    The emergence of the pandemic strain Vibrio parahaemolyticus O3:K6 in 1996 caused a large increase of diarrhea outbreaks related to seafood consumption in Southeast Asia, and later worldwide. Isolates of this strain constitutes a clonal complex, and their effectual differentiation is possible by comparison of their variable number tandem repeats (VNTRs). The differentiation of the isolates by the differences in VNTRs will allow inferring the population dynamics and microevolution of this strain but this requires knowing the rate and mechanism of VNTRs' variation. Our study of mutants obtained after serial cultivation of clones showed that mutation rates of the six VNTRs examined are on the order of 10−4 mutant per generation and that difference increases by stepwise addition of single mutations. The single stepwise mutation (SSM) was deduced because mutants with 1, 2, 3, or more repeat unit deletions or insertions follow a geometric distribution. Plausible phylogenetic trees are obtained when, according to SSM, the genetic distance between clusters with different number of repeats is assessed by the absolute differences in repeats. Using this approach, mutants originated from different isolates of pandemic V. parahaemolyticus after serial cultivation are clustered with their parental isolates. Additionally, isolates of pandemic V. parahaemolyticus from Southeast Asia, Tokyo, and northern and southern Chile are clustered according their geographical origin. The deepest split in these four populations is observed between the Tokyo and southern Chile populations. We conclude that proper phylogenetic relations and successful tracing of pandemic V. parahaemolyticus requires measuring the differences between isolates by the absolute number of repeats in the VNTRs considered

    Transformation of Biomass into Commodity Chemicals Using Enzymes or Cells

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    Genetic susceptibility in pharmacodynamic and pharmacokinetic pathways underlying drug-induced arrhythmia and sudden unexplained deaths

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    Drug-induced arrhythmia is an adverse drug reaction that can be potentially fatal since it is mostly related to drug-induced QT prolongation, a known risk factor for Torsade de Pointes and sudden cardiac death (SCD). Several risk factors have been described in association to these drug-induced events, such as preexistent cardiac disease and genetic variation. Our objective was to study the genetic susceptibility in pharmacodynamic and pharmacokinetic pathways underlying suspected drug-induced arrhythmias and sudden unexplained deaths in 32 patients. The genetic component in the pharmacodynamic pathway was studied by analysing 96 genes associated with higher risk of SCD through massive parallel sequencing. Pharmacokinetic-mediated genetic susceptibility was investigated by studying the genes encoding cytochrome P450 enzymes using medium-throughput genotyping. Pharmacodynamic analysis showed three probably pathogenic variants and 45 variants of uncertain significance in 28 patients, several of them previously described in relation to mild or late onset cardiomyopathies. These results suggest that genetic variants in cardiomyopathy genes, in addition to those related with channelopathies, could be relevant to drug-induced cardiotoxicity and contribute to the arrhythmogenic phenotype. Pharmacokinetic analysis showed three patients that could have an altered metabolism of the drugs they received involving CYP2C19 and/or CYP2D6, probably contributing to the arrhythmogenic phenotype. The study of genetic variants in both pharmacodynamic and pharmacokinetic pathways may be a useful strategy to understand the multifactorial mechanism of drug-induced events in both clinical practice and forensic field. However, it is necessary to comprehensively study and evaluate the contribution of the genetic susceptibility to drug-induced cardiotoxicity

    Development of a methylation marker set for forensic age estimation using analysis of public methylation data and the Agena Bioscience EpiTYPER system

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    Individual age estimation has the potential to provide key information that could enhance and extend DNA intelligence tools. Following predictive tests for externally visible characteristics developed in recent years, prediction of age could guide police investigations and improve the assessment of age-related phenotype expression patterns such as hair colour changes and early onset of male pattern baldness. DNA methylation at CpG positions has emerged as the most promising DNA tests to ascertain the individual age of the donor of a biological contact trace. Although different methodologies are available to detect DNA methylation, EpiTYPER technology (Agena Bioscience, formerly Sequenom) provides useful characteristics that can be applied as a discovery tool in localized regions of the genome. In our study, a total of twenty-two candidate genomic regions, selected from the assessment of publically available data from the Illumina HumanMethylation 450 BeadChip, had a total of 177 CpG sites with informative methylation patterns that were subsequently investigated in detail. From the methylation analyses made, a novel age prediction model based on a multivariate quantile regression analysis was built using the seven highest age-correlated loci of ELOVL2, ASPA, PDE4C, FHL2, CCDC102B, C1orf132 and chr16: 85395429. The detected methylation levels in these loci provide a median absolute age prediction error of +/- 3.07 years and a percentage of prediction error relative to the age of 6.3%. We report the predictive performance of the developed model using cross validation of a carefully age-graded training set of 725 European individuals and a test set of 52 monozygotic twin pairs. The multivariate quantile regression age predictor, using the CpG sites selected in this study, has been placed in the open-access Snipper forensic classification website. (C) 2016 Elsevier Ireland Ltd. All rights reserved

    Thyroid cancer GWAS identifies 10q26.12 and 6q14.1 as novel susceptibility loci and reveals genetic heterogeneity among populations

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    Thyroid cancer is the most heritable cancer of all those not displaying typical Mendelian inheritance. However, most of the genetic factors that would explain the high heritability remain unknown. Our aim was to identify additional common genetic variants associated with susceptibility to this disease. In order to do so, we performed a genome-wide association study in a series of 398 cases and 502 controls from Spain, followed by a replication in four well-defined Southern European case-control collections contributing a total of 1,422 cases and 1,908 controls. The association between the variation at the 9q22 locus near FOXE1 and thyroid cancer risk was consistent across all series, with several SNPs identified (rs7028661: OR = 1.64, p = 1.0 x 10(-22) , rs7037324: OR = 1.54, p = 1.2 x 10(-17) ). Moreover, the rare alleles of three SNPs (rs2997312, rs10788123 and rs1254167) at 10q26.12 showed suggestive evidence of association with higher risk of the disease (OR = 1.35, p = 1.2 x 10(-04) , OR = 1.26, p = 5.2 x 10(-04) and OR = 1.38, p = 5.9 x 10(-05) , respectively). Finally, the rare allele of rs4075570 at 6q14.1 conferred protection in the series studied (OR = 0.82, p = 2.0 x 10(-04) ). This study suggests that heterogeneity in genetic susceptibility between populations is a key feature to take into account when exploring genetic risk factors related to this disease
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