Integrated microbial biotechnologies for sustainable resource recovery from wastewater

不是每个人都喜欢思考冲水后会发生什么。然而，人类目前向环境中排放的氮（N），磷（P）和碳（C）远远超过我们地球的处理能力，这可能导致对人类可持续发展至关重要的自然生态系统恶化。生活废水是这些化合物的重要贡献者，废水现在是加拿大水源污染的最大贡献者。用于转化废水中N、P和C的传统生物处理工艺具有高能量需求和温室气体排放。微生物是这些生物处理过程的驱动力，但由于它们在实验室中的分离普遍困难，因此对其多样性和代谢能力知之甚少。这一基本知识差距阻碍了新生物技术的发展，这些技术能够从废水中回收营养物质、生物能源和清洁水作为可再生资源。最近在培养独立的基因组测序技术，如宏基因组学的进展，可以帮助阐明复杂的环境系统中的新微生物的代谢能力。然而，目前的生物废水处理设计方法落后于基因组学革命，因为这种建模平台没有考虑微生物生物量的代谢能力和多样性。我的研究计划将超越传统的废水处理设计方法，将下一代基因组测序数据纳入过程模型，可以准确预测各种新兴生物反应器配置下的污染物转化。我的研究计划的长期目标是开发和应用新的微生物生物技术，从城市污水中回收能量和营养物质，同时保护环境和人类健康。该研究计划的短期目标侧重于应用基因组学工具来模拟和推进三种新兴的生物技术，包括支持总体目标：（1）节能生物除磷和回收;（2）主流废水中的低能氮去除。(3)通过厌氧消化污泥预处理提高生物能源回收。该提案包括测量这些生物过程中微生物的N、P和C转化率的计划，以及对活性微生物种群进行有针对性的宏基因组测序分析的计划。通过将过程速率测量与社区规模建模相结合，该研究计划将提供对微生物及其代谢如何相互作用的机械理解，以预测保护加拿大清洁水源的重要工程过程的结果。这将通过能源和养分回收，大大降低废水处理的运营成本和温室气体排放。

Not everyone likes to think about what happens after they flush. However, humankind is currently emitting far more nitrogen (N), phosphorus (P), and carbon (C) into the environment than our planet can process, and this could lead to the deterioration of natural ecosystems critical to human sustainability. Domestic wastewater is a significant contributor of these compounds, and wastewater is now the largest contributor of pollution to Canadian water sources. Traditional biological treatment processes used to convert N, P, and C in wastewater have high energy requirements and greenhouse gas emissions. Microorganisms are the drivers of these biological treatment processes, yet little is known about their diversity and metabolic capacities, due to their general difficulty of isolation in the lab. This fundamental knowledge gap hinders the development of new biotechnologies that enable the recovery of nutrients, bioenergy, and clean water as renewable resources from wastewater. Recent advances in cultivation-independent genome sequencing technologies, such as metagenomics, can help to elucidate the metabolic capabilities of novel microbes within complex environmental systems. Yet, current biological wastewater treatment design approaches are lagging behind the genomics revolution, as such modelling platforms do not consider the metabolic capacity and diversity of microbial biomass. My research program will progress beyond traditional wastewater treatment design approaches by incorporating next-generation genomic sequencing data into process models that can accurately predict pollutant transformation under a variety of emerging bioreactor configurations. The long-term goal of my research program is to develop and apply new microbial biotechnologies that recover energy and nutrients from municipal wastewater, while protecting environmental and human health. The short-term objectives of this research program focus on applying genomics tools to model and advance three emerging biotechnologies that inclusively support the overall goal: (1) Energy-efficient biological P removal and recovery; (2) Low-energy N removal in mainstream wastewater. (3) Enhanced bioenergy recovery through anaerobic digester sludge pretreatment. This proposal includes plans for measuring the microbial rates of N, P, and C conversion within these bioprocesses, as well as for targeted metagenomic sequencing analysis of the active microbial populations. By combining process rate measurements with community-scale modelling, this research program will provide a mechanistic understanding of how microbes and their metabolisms interact to predict outcomes of important engineered processes that preserve Canada's clean water sources. This will lead to significantly lower operational costs and greenhouse gas emissions for wastewater treatment through energy and nutrient recovery.