Suppr超能文献

砷的微生物基因组学。

The microbial genomics of arsenic.

机构信息

Génétique Moléculaire, Génomique et Microbiologie, UMR7156 CNRS Université de Strasbourg, 67083 Strasbourg, France.

Génétique Moléculaire, Génomique et Microbiologie, UMR7156 CNRS Université de Strasbourg, 67083 Strasbourg, France

出版信息

FEMS Microbiol Rev. 2016 Mar;40(2):299-322. doi: 10.1093/femsre/fuv050. Epub 2016 Jan 19.

Abstract

Arsenic, which is a major contaminant of many aquatic ecosystems worldwide, is responsible for serious public health issues. However, life has evolved various strategies for coping with this toxic element. In particular, prokaryotic organisms have developed processes enabling them to resist and metabolize this chemical. Studies based on genome sequencing and transcriptome, proteome and metabolome profiling have greatly improved our knowledge of prokaryotes' metabolic potential and functioning in contaminated environments. The increasing number of genomes available and the development of descriptive and comparative approaches have made it possible not only to identify several genetic determinants of the arsenic metabolism, but also to elucidate their phylogenetic distribution and their modes of regulation. In addition, studies using functional genomic tools have established the pleiotropic character of prokaryotes' responses to arsenic, which can be either common to several species or species-specific. These approaches also provide promising means of deciphering the functioning of microbial communities including uncultured organisms, the genetic transfers involved and the possible occurrence of metabolic interactions as well as the evolution of arsenic resistance and metabolism.

摘要

砷是全球许多水生生态系统中的主要污染物,对公共健康造成严重影响。然而,生命已经进化出多种策略来应对这种有毒元素。特别是,原核生物已经开发出多种抵抗和代谢这种化学物质的方法。基于基因组测序、转录组、蛋白质组和代谢组分析的研究极大地提高了我们对原核生物在污染环境中的代谢潜力和功能的认识。越来越多的基因组可供使用,以及描述性和比较性方法的发展,不仅使我们能够确定砷代谢的几个遗传决定因素,还阐明了它们的系统发育分布和调控模式。此外,使用功能基因组工具的研究确立了原核生物对砷的反应的多效性,这些反应可能是几种物种共有的,也可能是特定于物种的。这些方法还为破译包括未培养生物在内的微生物群落的功能、涉及的遗传转移以及代谢相互作用的可能发生以及砷抗性和代谢的进化提供了有希望的手段。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验