Bacterial Diversity as a BioMarker of Soil Health

由于它们与土壤污染物的密切联系，我们假设 土壤细菌群落代谢活性部分的[丰富度和均匀度] 作为多环芳烃和重金属污染超级基金场地对人类健康威胁的生物标志物。 为了挑战这一假设，我们将解决三个具体目标：(1)确定 基于分子生物学的细菌多样性测量和多环芳烃和多环芳烃分析方法的结果 土壤老化过程中的重金属和模拟超级基金场地的生物修复；(2)展示了新的 以分子生物学为基础的分析方法评估细菌代谢活性部分的多样性 (3)利用生态模型预测土壤细菌群落多样性。 重金属和多环芳烃混合物的影响。该方法包括：(I)操作模拟 超级基金地点；(2)T-RFLP和(3)全细胞鱼类，以衡量细菌多样性；(4)识别 使用克隆文库的优势细菌种群；(V)评估多环芳烃和重金属的影响 关于核糖体发生；(Vi)利用微阵列识别重金属反应基因；(Vii)评估 多环芳烃降解的宏基因组学；(Viii)评价实时聚合酶链式反应以量化重金属和多环芳烃的响应 基因；(Ix)采用生态模型预测细菌多样性；(X)比较实验 使用模型预测的多样性度量；以及(Xi)评估预测的最佳营养修正 与资源比率理论相结合。这个项目是创新的，因为我们使用了基于分子生物学的 在超级基金站点，细菌多样性的测量作为一种诊断工具来预测对人类健康的威胁 (即细菌作为污染的哨兵)。我们期待这项研究的积极结果可以用来 评估生物修复战略的成功潜力，并建立一个有效的 生物修复(即，当适当的细菌多样性重新建立时，对人类的威胁 健康显著下降)。

Because of their intimate association with soil contaminants, we HYPOTHESIZE that the diversity [measured as richness and evenness) of the metabolically-active fraction of the soil bacterial community serves as a biomarker of the threat to human health from PAHs and heavy metals polluting Superfund sites. To challenge this hypothesis, we will address three SPECIFIC AIMS: (1) Identify correlations between the results of molecular biology-based measures of bacterial diversity and analytical measures of PAHs and heavy metals during soil ageing and bioremediation of mock Superfund sites; (2) Demonstrate novel molecular biology-based assays to assess the diversity of the metabolically active fraction of the bacterial community in situ; and (3) Demonstrate ecological models to predict soil bacterial community diversity under the influence of mixtures of heavy metals and PAHs. The APPROACH includes: (i) operating mock Superfund sites; (ii) T-RFLP and (iii) whole cell FISH to measure bacterial diversity; (iv) identifying predominant bacterial populations using clone libraries; (v) evaluating the impact of PAH and heavy metals on ribosome genesis; (vi) identifying heavy-metal responsive genes using microarrays; (vii) evaluating metagenomics of PAH degradation; (viii) evaluating real-time PCR to quantify heavy-metal and PAHresponsive genes; (ix) adapting ecological models to predict bacterial diversity; (x) comparing experimental measures of diversity with model predictions; and (xi) evaluating optimum nutrient amendments predicted with the resource-ratio theory. This project is INNOVATIVE because we are using molecular biology-based measures of bacterial diversity as a diagnostic tool to predict the threat to human health at Superfund sites (i.e., bacteria as sentinels for pollution). We expect that the positive findings of this study can be used to evaluate the potential for success of bioremediation strategies as well as to establish an effective endpoint of bioremediation (i.e., when appropriate bacterial diversity has been re-established and the threat to human health significantly reduced).