Developing a platform for rapid online DNA monitoring of microbial communities in wastewater treatment systems

这个拟议的项目是与温哥华大都会合作开发改进的技术，以检测和缓解其污水处理厂(WWTP)二级处理过程中的问题微生物，以期优化处理性能、可靠性，并最终优化环境水质。污水处理厂提供城市水循环的恢复功能，通常包括去除颗粒碳材料的一级处理和去除可溶性有机化合物以及氮和磷等营养物质的二级处理。二级废水处理完全依赖微生物来降解废水中存在的不同形式的污染，并将对接收水的影响降至最低。然而，二级废水处理中的某些微生物可能会因起泡或沉降不良(膨胀)而导致工艺不稳定和颠覆。该项目将专注于开发使用下一代便携式DNA测序技术的协议，以快速绘制废水微生物群落的概况。通过使用这些新出现的检测方法进行主动微生物监测，将有可能获得问题微生物生长的早期预警信号，并制定相应的策略来调整二级工艺操作，以满足规定的排放标准并维持加拿大环境接受水域的生态系统健康。该项目将通过让4名研究生参与应用基因组学、生物信息学和数据科学的创新解决方案来支持下一代环境工程师的培训。

This proposed project is a partnership with Metro Vancouver to develop improved technologies for the detection and mitigation of problematic microorganisms in secondary treatment processes at their wastewater treatment plants (WWTPs), with a view to optimizing treatment performance, reliability, and ultimately environmental water quality. WWTPs provide the restorative function of the urban water cycle, and typically include primary treatment to remove particulate carbon materials, and secondary treatment to remove soluble organic compounds as well as nutrients like nitrogen and phosphorus. Secondary wastewater treatment is entirely dependent on microorganisms to degrade different forms of pollution present in wastewater, and to minimize impacts on receiving waters. However, certain microorganisms in secondary wastewater treatment can cause process instability and upsets due to foaming or poor-settling (bulking). This project will focus on developing protocols using next-generation portable DNA sequencing technology to rapidly profile wastewater microbial communities. Through active microbial monitoring using these emerging detection methods, it will be possible to gain early warning signals for when problematic microorganisms are growing, and develop strategies to tune secondary process operation accordingly to meet regulated effluent standards and maintain ecosystem health in Canada's environmental receiving waters. This project will support the training of the next-generation of environmental engineers by involving 4 graduate students in innovative solutions applying genomics, bioinformatics, and data science.