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A systematic evaluation of Mycobacterium tuberculosis Genome-Scale Metabolic Networks

机译:分枝杆菌结核病基因组代谢网络的系统评价

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The tuberculosis bacillus, Mycobacterium tuberculosis (Mtb), is a global killer causing millions of deaths every year and is therefore a major burden to human health. Treatment of tuberculosis requires a cocktail of antibiotics for a minimum of 6 months. Treatment failure is common and is a major driver in the upward trend of antibiotic resistance, recognized by the World Health Organization as one of top ten threats to global health. A key to the success of Mtb as a human pathogen is ascribed to its extraordinary metabolic flexibility. Understanding the metabolism of Mtb is therefore an important goal of TB researchers as metabolic pathways present attractive drug targets. A powerful approach to study metabolism is through the use of genome-scale metabolic networks which enable metabolism to be studied at the whole system level rather than one enzyme at a time. Here, we comprehensively compare available genome scale metabolic networks. Our results identify the best performing networks for a variety of modelling approaches. This work allowed us to refine these models for the TB community to use in future studies to probe the metabolism of this formidable human pathogen.
机译:结核病芽孢杆菌,结核分枝杆菌(MTB),是每年导致数百万死亡的全球杀手,因此是人类健康的主要负担。治疗结核病需要抗生素鸡尾酒至少6个月。治疗失败是常见的,是抗生素抗性上升趋势的主要驱动因素,由世界卫生组织认识到全球健康的十大威胁之一。 MTB作为人病原体成功的关键是其非凡的代谢灵活性。因此,理解MTB的新陈代谢是TB研究人员的重要目标,因为代谢途径存在吸引人的药物靶标。一种强大的研究代谢方法是通过使用基因组代谢网络,使得能够在整个系统水平而不是一次酶的整个系统水平来研究代谢。在这里,我们全面比较可用的基因组标量代谢网络。我们的结果确定了用于各种建模方法的最佳性能网络。这项工作使我们能够改进TB界的这些模型,以便在未来的研究中使用,以探讨这种突起的人类病原体的代谢。

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