111 research outputs found

    FrameDP: sensitive peptide detection on noisy matured sequences

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    Summary: Transcriptome sequencing represents a fundamental source of information for genome-wide studies and transcriptome analysis and will become increasingly important for expression analysis as new sequencing technologies takes over array technology. The identification of the protein-coding region in transcript sequences is a prerequisite for systematic amino acid-level analysis and more specifically for domain identification. In this article, we present FrameDP, a self-training integrative pipeline for predicting CDS in transcripts which can adapt itself to different levels of sequence qualities

    Dual mobility hip arthroplasty wear measurement: Experimental accuracy assessment using radiostereometric analysis (RSA)

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    SummaryIntroductionThe use of dual mobility cups is an effective method to prevent dislocations. However, the specific design of these implants can raise the suspicion of increased wear and subsequent periprosthetic osteolysis.HypothesisUsing radiostereometric analysis (RSA), migration of the femoral head inside the cup of a dual mobility implant can be defined to apprehend polyethylene wear rate.Study objectivesThe study aimed to establish the precision of RSA measurement of femoral head migration in the cup of a dual mobility implant, and its intra- and interobserver variability.Material and methodsA total hip prosthesis phantom was implanted and placed under weight loading conditions in a simulator. Model-based RSA measurement of implant penetration involved specially machined polyethylene liners with increasing concentric wear (no wear, then 0.25, 0.5 and 0.75mm). Three examiners, blinded to the level of wear, analyzed (10 times) the radiostereometric films of the four liners. There was one experienced, one trained, and one inexperienced examiner. Statistical analysis measured the accuracy, precision, and intra- and interobserver variability by calculating Root Mean Square Error (RMSE), Concordance Correlation Coefficient (CCC), Intra Class correlation Coefficient (ICC), and Bland-Altman plots.ResultsOur protocol, that used a simple geometric model rather than the manufacturer's CAD files, showed precision of 0.072mm and accuracy of 0.034mm, comparable with machining tolerances with low variability. Correlation between wear measurement and true value was excellent with a CCC of 0.9772. Intraobserver reproducibility was very good with an ICC of 0.9856, 0.9883 and 0.9842, respectively for examiners 1, 2 and 3. Interobserver reproducibility was excellent with a CCC of 0.9818 between examiners 2 and 1, and 0.9713 between examiners 3 and 1.DiscussionQuantification of wear is indispensable for the surveillance of dual mobility implants. This in vitro study validates our measurement method. Our results, and comparison with other studies using different measurement technologies (RSA, standard radiographs, Martell method) make model-based RSA the reference method for measuring the wear of total hip prostheses in vivo.Level of evidenceLevel 3. Prospective diagnostic study

    Deciphering the genome structure and paleohistory of _Theobroma cacao_

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    We sequenced and assembled the genome of _Theobroma cacao_, an economically important tropical fruit tree crop that is the source of chocolate. The assembly corresponds to 76% of the estimated genome size and contains almost all previously described genes, with 82% of them anchored on the 10 _T. cacao_ chromosomes. Analysis of this sequence information highlighted specific expansion of some gene families during evolution, for example flavonoid-related genes. It also provides a major source of candidate genes for _T. cacao_ disease resistance and quality improvement. Based on the inferred paleohistory of the T. cacao genome, we propose an evolutionary scenario whereby the ten _T. cacao_ chromosomes were shaped from an ancestor through eleven chromosome fusions. The _T. cacao_ genome can be considered as a simple living relic of higher plant evolution

    High-quality de novo assembly of the apple genome and methylome dynamics of early fruit development

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    Using the latest sequencing and optical mapping technologies, we have produced a high-quality de novo assembly of the apple (Malus domestica Borkh.) genome. Repeat sequences, which represented over half of the assembly, provided an unprecedented opportunity to investigate the uncharacterized regions of a tree genome; we identified a new hyper-repetitive retrotransposon sequence that was over-represented in heterochromatic regions and estimated that a major burst of different transposable elements (TEs) occurred 21 million years ago. Notably, the timing of this TE burst coincided with the uplift of the Tian Shan mountains, which is thought to be the center of the location where the apple originated, suggesting that TEs and associated processes may have contributed to the diversification of the apple ancestor and possibly to its divergence from pear. Finally, genome-wide DNA methylation data suggest that epigenetic marks may contribute to agronomically relevant aspects, such as apple fruit development

    Metabolic adaptation of two in silico mutants of Mycobacterium tuberculosis during infection

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    ABSTRACT: Background: Up to date, Mycobacterium tuberculosis (Mtb) remains as the worst intracellular killer pathogen. To establish infection, inside the granuloma, Mtb reprograms its metabolism to support both growth and survival, keeping a balance between catabolism, anabolism and energy supply. Mtb knockouts with the faculty of being essential on a wide range of nutritional conditions are deemed as target candidates for tuberculosis (TB) treatment. Constraint-based genome-scale modeling is considered as a promising tool for evaluating genetic and nutritional perturbations on Mtb metabolic reprogramming. Nonetheless, few in silico assessments of the effect of nutritional conditions on Mtb’s vulnerability and metabolic adaptation have been carried out. Results: A genome-scale model (GEM) of Mtb, modified from the H37Rv iOSDD890, was used to explore the metabolic reprogramming of two Mtb knockout mutants (pfkA- and icl-mutants), lacking key enzymes of central carbon metabolism, while exposed to changing nutritional conditions (oxygen, and carbon and nitrogen sources). A combination of shadow pricing, sensitivity analysis, and flux distributions patterns allowed us to identify metabolic behaviors that are in agreement with phenotypes reported in the literature. During hypoxia, at high glucose consumption, the Mtb pfkA-mutant showed a detrimental growth effect derived from the accumulation of toxic sugar phosphate intermediates (glucose-6-phosphate and fructose-6-phosphate) along with an increment of carbon fluxes towards the reductive direction of the tricarboxylic acid cycle (TCA). Furthermore, metabolic reprogramming of the icl-mutant (icl1&icl2) showed the importance of the methylmalonyl pathway for the detoxification of propionyl-CoA, during growth at high fatty acid consumption rates and aerobic conditions. At elevated levels of fatty acid uptake and hypoxia, we found a drop in TCA cycle intermediate accumulation that might create redox imbalance. Finally, findings regarding Mtb-mutant metabolic adaptation associated with asparagine consumption and acetate, succinate and alanine production, were in agreement with literature reports. Conclusions: This study demonstrates the potential application of genome-scale modeling, flux balance analysis (FBA), phenotypic phase plane (PhPP) analysis and shadow pricing to generate valuable insights about Mtb metabolic reprogramming in the context of human granulomas

    Mycobacterium tuberculosis Exploits Asparagine to Assimilate Nitrogen and Resist Acid Stress during Infection

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    Mycobacterium tuberculosis is an intracellular pathogen. Within macrophages, M. tuberculosis thrives in a specialized membrane-bound vacuole, the phagosome, whose pH is slightly acidic, and where access to nutrients is limited. Understanding how the bacillus extracts and incorporates nutrients from its host may help develop novel strategies to combat tuberculosis. Here we show that M. tuberculosis employs the asparagine transporter AnsP2 and the secreted asparaginase AnsA to assimilate nitrogen and resist acid stress through asparagine hydrolysis and ammonia release. While the role of AnsP2 is partially spared by yet to be identified transporter(s), that of AnsA is crucial in both phagosome acidification arrest and intracellular replication, as an M. tuberculosis mutant lacking this asparaginase is ultimately attenuated in macrophages and in mice. Our study provides yet another example of the intimate link between physiology and virulence in the tubercle bacillus, and identifies a novel pathway to be targeted for therapeutic purposes. © 2014 Gouzy et al

    A regulatory network-based approach dissects late maturation processes related to the acquisition of desiccation tolerance and longevity of Medicago truncatula seeds

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    In seeds, desiccation tolerance (DT) and the ability to survive the dry state for prolonged periods of time (longevity) are two essential traits for seed quality that are consecutively acquired during maturation. Using transcriptomic and metabolomic profiling together with a conditional-dependent network of global transcription interactions, we dissected the maturation events from the end of seed filling to final maturation drying during the last 3 weeks of seed development in Medicago truncatula. The network revealed distinct coexpression modules related to the acquisition of DT, longevity, and pod abscission. The acquisition of DT and dormancy module was associated with abiotic stress response genes, including late embryogenesis abundant (LEA) genes. The longevity module was enriched in genes involved in RNA processing and translation. Concomitantly, LEA polypeptides accumulated, displaying an 18-d delayed accumulation compared with transcripts. During maturation, gulose and stachyose levels increased and correlated with longevity. A seed-specific network identified known and putative transcriptional regulators of DT, including ABSCISIC ACID-INSENSITIVE3 (MtABI3), MtABI4, MtABI5, and APETALA2/ ETHYLENE RESPONSE ELEMENT BINDING PROTEIN (AtAP2/EREBP) transcription factor as major hubs. These transcriptional activators were highly connected to LEA genes. Longevity genes were highly connected to two MtAP2/EREBP and two basic leucine zipper transcription factors. A heat shock factor was found at the transition of DT and longevity modules, connecting to both gene sets. Gain- and loss-of-function approaches of MtABI3 confirmed 80% of its predicted targets, thereby experimentally validating the network. This study captures the coordinated regulation of seed maturation and identifies distinct regulatory networks underlying the preparation for the dry and quiescent states

    Assessing Performance of Orthology Detection Strategies Applied to Eukaryotic Genomes

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    Orthology detection is critically important for accurate functional annotation, and has been widely used to facilitate studies on comparative and evolutionary genomics. Although various methods are now available, there has been no comprehensive analysis of performance, due to the lack of a genomic-scale ‘gold standard’ orthology dataset. Even in the absence of such datasets, the comparison of results from alternative methodologies contains useful information, as agreement enhances confidence and disagreement indicates possible errors. Latent Class Analysis (LCA) is a statistical technique that can exploit this information to reasonably infer sensitivities and specificities, and is applied here to evaluate the performance of various orthology detection methods on a eukaryotic dataset. Overall, we observe a trade-off between sensitivity and specificity in orthology detection, with BLAST-based methods characterized by high sensitivity, and tree-based methods by high specificity. Two algorithms exhibit the best overall balance, with both sensitivity and specificity>80%: INPARANOID identifies orthologs across two species while OrthoMCL clusters orthologs from multiple species. Among methods that permit clustering of ortholog groups spanning multiple genomes, the (automated) OrthoMCL algorithm exhibits better within-group consistency with respect to protein function and domain architecture than the (manually curated) KOG database, and the homolog clustering algorithm TribeMCL as well. By way of using LCA, we are also able to comprehensively assess similarities and statistical dependence between various strategies, and evaluate the effects of parameter settings on performance. In summary, we present a comprehensive evaluation of orthology detection on a divergent set of eukaryotic genomes, thus providing insights and guides for method selection, tuning and development for different applications. Many biological questions have been addressed by multiple tests yielding binary (yes/no) outcomes but no clear definition of truth, making LCA an attractive approach for computational biology
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