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， 土壤细菌群落的代谢活性部分[以丰富度和均匀度衡量] 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，我们将提出三个具体目标：（1）确定 基于分子生物学的细菌多样性措施和多环芳烃分析措施的结果， 模拟超级基金场地土壤老化和生物修复过程中的重金属;（2）展示新的 基于分子生物学的测定，以评估细菌的代谢活性部分的多样性 （3）示范生态模型，以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：（一）操作模拟 超级基金地点;（ii）T-RFLP和（iii）全细胞FISH以测量细菌多样性;（iv）鉴定 使用克隆文库的优势细菌种群;（v）评估PAH和重金属的影响 （vi）使用微阵列鉴定重金属响应基因;（vii）评估 PAH降解的宏基因组学;（viii）评估实时PCR以定量重金属和PAH响应性 基因;（ix）调整生态模型以预测细菌多样性;（x）比较实验 利用模型预测的多样性措施;以及（Xi）评估预测的最佳营养物添加剂 资源比例理论。这个项目是创新的，因为我们使用基于分子生物学的 作为诊断工具的细菌多样性的措施，以预测超级基金场所对人类健康的威胁 (i.e.,细菌作为污染的哨兵）。我们希望这项研究的积极结果可以用于 评估生物修复策略成功的潜力，并建立有效的终点， 生物修复（即，当适当的细菌多样性已经重新建立， 健康状况大幅下降）。

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).