Quantification of changing Pseudomonas aeruginosa sodA, htpX and mt gene abundance in response to trace metal toxicity:: a potential in situ biomarker of environmental health
Quantification of changing Pseudomonas aeruginosa sodA, htpX and mt gene abundance in response to trace metal toxicity:: a potential in situ biomarker of environmental health
复制标题
DOI：
10.1111/j.1574-6941.2007.00296.x
复制
发表时间：
2007-05-01
影响因子：
4.2
通讯作者：
Ford, Timothy E.
中科院分区：
文献类型：
--
作者：
Bouskill, Nicolas J.;Barnhart, Elliott P.;Ford, Timothy E.
生活在沉积物中的原核生物在决定金属的命运和形态方面起着至关重要的作用，但也容易受到微量金属的生物效应的影响。本文利用优化的DNA提取纯化技术和物种特异性引物，评估铜绿假单胞菌金属解毒和一般应激基因的遗传发生率和丰度，以补充化学分析，推断蒙大拿州克拉克福克河沿岸金属污染地点的严重程度。结果表明，细菌胁迫相关候选基因在污染最严重的位点的发生率最高，而多元回归分析表明，原位金属浓度（As、Cu和Zn）、总基因发生率与金属解毒基因发生率之间存在显著相关性（P < 0.05, r(2)=0.9）。此外，绘制与金属抗性相关的基因发生率的主成分显示出明确的位点分离，并根据污染给出明确的集群。对调查位点的3个基因（sodA、htpX和mt）进行定量分析发现，污染程度较高的位点的拷贝数显著高于参考位点（方差分析，P < 0.05）。快速微生物生物标志物工具的开发是环境生物监测和金属生物利用度预测领域的重大进展。
Sediment-dwelling prokaryotes play a vital role in determining the fate and speciation of metals, yet are also susceptible to the biological effects of trace metals. In this article, optimized DNA extraction and purification techniques and species-specific primers are used to assess the genetic incidence and abundance of metal detoxification and general stress genes of Pseudomonas aeruginosa to complement chemical analysis in inferring the severity of metal-contaminated sites along the Clark Fork River, Montana. Results show the highest incidence of candidate genes related to bacterial stress at the most polluted site, while multiple regression analysis demonstrated significant correlations (P < 0.05, r(2)=0.9) between in situ metal concentrations (As, Cu and Zn), total gene incidence, and the incidence of metal detoxification genes. Furthermore, principal components plotting the incidence of genes related to metal resistance show clear separation of sites giving clear clusters on the basis of contamination. Quantification of three genes (sodA, htpX and mt) from surveyed sites found significantly higher (ANOVA, P < 0.05) copy numbers at the more contaminated sites compared with reference sites. The development of rapid microbial biomarker tools represents a significant advance in the field of environmental biomonitoring and the prediction of metal bioavailability.