Bacterial biosensors for detection and bioremediation of wastewater pollutants.

从阿萨巴斯卡油砂中热水提取沥青所产生的油砂过程影响水（OSPW）中存在大量污染物。市政水处理厂已经确定了几种未完全去除的药物，并在流出物中释放。生物传感器的高通量和廉价特性可以支持长期的环境测试项目。我们建议开发一种生物传感器技术，用于直接水检测，以及识别生物修复基因。目的1。构建、验证和优化重要水污染物的全生物传感器。生物传感器是经过改造的细菌菌株，可以专门检测低水平的小分子，并产生简单的定量输出。对分析物有反应的启动子被克隆为与luxCDABE报告基因的转录融合。OSPW的优先目标是环烷酸（NA）和多环芳烃（PAHs），它们含量丰富且毒性大。卡马西平（抗癫痫）和双氯芬酸（抗炎）是市政水处理后残留在废水中的药物。我们从OSPW中分离得到假单胞菌，并对4株菌株的草图基因组进行了测序。以香豆草尾砂分离物作为生物传感器底盘菌株。我们建立了一个利用细菌基因组学和合成生物学的管道，以快速创建任何环境污染物的生物传感器菌株。采用RNA-seq技术鉴定污染物暴露诱导的细菌基因/启动子。从诱导基因中合成了84个优先启动子并克隆为转录通量融合体。质粒编码的生物传感器电路将测试剂量依赖性基因表达，敏感性和特异性。通过代谢物感知转录抑制物的污染物感知机制将被探索并纳入生物传感器的改进设计中。目标2。筛选宏基因组文库，鉴定目标污染物的生物修复基因。生物修复是一种具有成本效益和可扩展的技术，可用于治疗OSPW。尾矿库微生物的多样性无法通过人工培养实现，但我们可以通过筛选宏基因组环境DNA （metagenomics environmental DNA, eDNA）寻找生物修复基因来开发这种遗传多样性。我们优化了一个在污染物存在下培养大肠杆菌宿主的共培养系统，然后在384个孔格式实验中共培养假单胞菌生物传感器，以识别降解污染物的菌株。降解将用GC-MS确认，阳性克隆的质粒将测序。具体的基因功能将通过生物信息学、突变和表型分析来证实。在这些研究中获得的遗传信息将有助于阐明降解机制，并将支持合成生物学策略来构建具有改进生物修复功能的工程微生物。

Numerous pollutants are present in the oilsands process-affected water (OSPW) generated from hot water extraction of bitumen from the Athabasca oilsands. Municipal water treatment plants have identified several pharmaceutical drugs that are not completely removed and are released in the effluent. The high throughput and inexpensive nature of biosensors can support long-term environmental testing programs. We propose to develop a biosensor technology for application in direct water testing, but also for identifying bioremediation genes. Aim 1. To construct, validate and optimize whole biosensors for important water pollutants. Biosensors are engineered bacterial strains that can specifically detect low levels of small molecules and produce a simple, quantitative output. Promoters responsive to an analyte are cloned as a transcriptional fusion to the luxCDABE reporter genes. The priority OSPW targets are naphthenic acids (NA) and polycyclic aromatic hydrocarbons (PAHs), which are abundant and toxic. Carbamazepine (anti-epileptic) and diclofenac (anti-inflammatory) are pharmaceuticals that remain in the effluent after municipal water treatment. We recovered Pseudomonas isolates from OSPW and sequenced the draft genomes of 4 strains. The P. synxantha tailings isolate was used as the biosensor chassis strain. We established a pipeline using bacterial genomics and synthetic biology to rapidly create biosensor strains for any environmental pollutant. RNA-seq was performed to identify bacterial genes/promoters induced in response to pollutant exposure. Eighty-four priority promoters from induced genes were synthesized and cloned as transcriptional lux fusions. Plasmid-encoded biosensor circuits will be tested for dose-dependent gene expression, sensitivity and specificity. The mechanism of pollutant sensing by metabolite-sensing transcriptional repressors will be explored and incorporated into an improved design of biosensors. Aim 2. To screen metagenomic libraries and identify bioremediation genes for target pollutants. Bioremediation is a cost-effective and scalable technology for potential use in treating OSPW. The diverse community of tailings ponds microbes cannot be grown, but we can exploit this genetic diversity by screening metagenomic environmental DNA (eDNA) for bioremediation genes. We optimized a co-culture system of growing the E. coli host in the presence of the pollutant, and then co-culturing our Pseudomonas biosensor in 384 well format experiments, to identify strains that degrade the contaminant. Degradation will be confirmed with GC-MS and plasmids from positive clones will be sequenced. The specific gene function will be confirmed by bioinformatic, mutation and phenotype analyses. The genetic information gained in these studies will help elucidate the mechanisms of degradation, and will support synthetic biology strategies to construct engineered microbes with improved bioremediation.