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Metagenomic Functional Potential Predicts Degradation Rates of a Model Organophosphorus Xenobiotic in Pesticide Contaminated Soils

机译:偏见功能潜力预测杂种污染土壤中型有机磷异黄素的降解率

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摘要

Chemical contamination of natural and agricultural habitats is an increasing global problem and a major threat to sustainability and human health. Organophosphorus (OP) compounds are one major class of contaminant and can undergo microbial degradation, however, no studies have applied system-wide ecogenomic tools to investigate OP degradation or use metagenomics to understand the underlying mechanisms of biodegradation in situ and predict degradation potential. Thus, there is a lack of knowledge regarding the functional genes and genomic potential underpinning degradation and community responses to contamination. Here we address this knowledge gap by performing shotgun sequencing of community DNA from agricultural soils with a history of pesticide usage and profiling shifts in functional genes and microbial taxa abundance. Our results showed two distinct groups of soils defined by differing functional and taxonomic profiles. Degradation assays suggested that these groups corresponded to the organophosphorus degradation potential of soils, with the fastest degrading community being defined by increases in transport and nutrient cycling pathways and enzymes potentially involved in phosphorus metabolism. This was against a backdrop of taxonomic community shifts potentially related to contamination adaptation and reflecting the legacy of exposure. Overall our results highlight the value of using holistic system-wide metagenomic approaches as a tool to predict microbial degradation in the context of the ecology of contaminated habitats.
机译:自然和农业生境的化学污染是一个全球性问题愈益和可持续发展和人类健康的一大威胁。有机磷(OP)化合物是一个大类的污染物,并可以进行微生物降解,但是,没有研究已经应用系统范围ecogenomic工具来调查OP降解或使用宏基因组学,了解原位生物降解的基本机制和预测退化的潜力。因此,对于功能基因和基因组潜力托底退化和社区应对污染知识的缺乏。在这里,我们应对农药使用历史农用土壤进行社会DNA的鸟枪法测序和分析的功能基因和微生物类群丰富的变化这方面的知识差距。我们的结果表明由不同功能和分类配置文件中定义的土壤的两个不同组。降解测定法表明,这些基团对应于土壤的有机磷降解潜力,以最快的降解社区被潜在地参与磷代谢运输的增加和营养循环途径和酶定义。这是针对潜在的有关污染适应和反映曝光的传统分类学社区转变的背景下。总的来说,我们的研究结果强调使用全面的全系统的宏基因组的方法作为一种工具在受污染的栖息地生态环境的背景下,预测微生物降解的价值。

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