A novel computational method to analyse metagenome for understanding of microbial community composition and functional potential

Askarbek N. Orakov, N. Sakenova, Igor Goraynin, A. Sorokin
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引用次数: 2

Abstract

There is a great potential for the use of bacterial communities for bioremediation and waste treatment. Systems metabolic engineering for microbial community redesign is a promising approach. The successful development of synthetic microbial communities is essential to add value to the main challenges for sustainable development, such as difficulties to cultivate bacteria in isolation[1], diversity of microbial communities, and many uncharacterized bacteria. Some of these challenges could be addressed by advances in computational tools and modelling. However, current tools only provide separate taxonomic [2] and functional analyses [3]. Development of a metagenomic analysis tool to investigate metagenomes deeply with the help of integrated taxonomic, functional and metabolic pathways analyses may allow to make community modelling and study complex interspecific relations inside the community. This would help finding ways to increase the functional potential of microbial communities either by optimizing external conditions and nutrients or by regulating the taxonomic content and proportions of the bacterial composition.
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一种新的计算方法来分析宏基因组,以了解微生物群落组成和功能潜力
利用细菌群落进行生物修复和废物处理具有很大的潜力。微生物群落再设计的系统代谢工程是一种很有前途的方法。合成微生物群落的成功开发对于为可持续发展的主要挑战增加价值至关重要,这些挑战包括孤立培养细菌的困难[1]、微生物群落的多样性以及许多未表征的细菌。其中一些挑战可以通过计算工具和建模的进步来解决。然而,目前的工具只提供单独的分类分析[2]和功能分析[3]。开发一种宏基因组分析工具,在综合分类、功能和代谢途径分析的帮助下深入研究宏基因组,可以建立群落模型,研究群落内部复杂的种间关系。这将有助于找到通过优化外部条件和营养物质或通过调节细菌组成的分类含量和比例来增加微生物群落功能潜力的方法。
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