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通过监测农药降解基因表达来估算土壤中农药的生物降解性。

Estimating the biodegradation of pesticide in soils by monitoring pesticide-degrading gene expression.

机构信息

UMR CNRS 6553 'EcoBio'--IFR2116/FR90 CAREN, Université de Rennes 1, 263 Avenue du Général Leclerc, Bat 14B, 35042, Rennes Cedex, France.

出版信息

Biodegradation. 2013 Apr;24(2):203-13. doi: 10.1007/s10532-012-9574-5. Epub 2012 Jul 22.

Abstract

Assessing in situ microbial abilities of soils to degrade pesticides is of great interest giving insight in soil filtering capability, which is a key ecosystem function limiting pollution of groundwater. Quantification of pesticide-degrading gene expression by reverse transcription quantitative PCR (RT-qPCR) was tested as a suitable indicator to monitor pesticide biodegradation performances in soil. RNA extraction protocol was optimized to enhance the yield and quality of RNA recovered from soil samples to perform RT-qPCR assays. As a model, the activity of atrazine-degrading communities was monitored using RT-qPCRs to estimate the level of expression of atzD in five agricultural soils showing different atrazine mineralization abilities. Interestingly, the relative abundance of atzD mRNA copy numbers was positively correlated to the maximum rate and to the maximal amount of atrazine mineralized. Our findings indicate that the quantification of pesticide-degrading gene expression may be suitable to assess biodegradation performance in soil and monitor natural attenuation of pesticide.

摘要

评估土壤中微生物原位降解农药的能力具有重要意义,因为这可以深入了解土壤的过滤能力,而土壤的过滤能力是限制地下水污染的关键生态系统功能之一。通过反转录定量 PCR (RT-qPCR) 定量检测农药降解基因的表达被测试为监测土壤中农药生物降解性能的合适指标。优化了 RNA 提取方案,以提高从土壤样品中回收的 RNA 的产量和质量,从而进行 RT-qPCR 分析。作为一个模型,使用 RT-qPCR 监测了莠去津降解群落的活性,以估计在 5 种表现出不同莠去津矿化能力的农业土壤中 atzD 的表达水平。有趣的是,atzD mRNA 拷贝数的相对丰度与莠去津矿化的最大速率和最大量呈正相关。我们的研究结果表明,农药降解基因表达的定量可能适合评估土壤中的生物降解性能,并监测农药的自然衰减。

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