A predictive framework for microbial management in drinking water systems. Drinking water monitoring programs are designed for early detection of contamination events, so as to inform rapid risk mitigation strategies (i.e. a detect and mitigate approach). The scale of these monitoring programs is often several-fold higher than the likelihood of a contamination event occurring, making the "detect and mitigate" approach extremely resource intensive. For example, 99% compliance also means that 99% of the resources are spent on regulation compliant samples. We believe predicting and preventing contamination events, rather than detecting and mitigating their impacts, is the best way to ensure uninterrupted supply of safe drinking water. We are developing a predictive framework that quantifies the likelihood of microbial contamination event(s), identifies high-risk regions of the drinking water systems, and provides corrective action strategies to eliminate contamination events before they occur. Our vision is that this approach will allow utilities to forecast the microbiological quality of the water at the customers tap at least seven to days in advance.
Nitrification in the urban water infrastructure. Nitrification is a key biological process in both drinking water and wastewater systems. In drinking water distribution systems, it can adversely affect water quality, destabilize disinfectant residual, and can cause pipe corrosion. Similarly, full nitrification is an extremely energy intensive process in wastewater systems, with increasing efforts being put into partial nitrification-denitrification processes that promise significant cost savings. In both scenarios, the control of nitrification has relied on the conventional knowledge that complete nitrification from ammonia to nitrate is a two-step process involving two separate groups of organisms. The recent discovery of COMplete AMMonia OXidizing (i.e. comammox) bacteria will have significant ramifications for drinking water quality and nitrogen removal processes in wastewater treatment plants. Specifically, are nitrification episodes in drinking water distribution systems linked to comammox bacteria? Does the presence of comammox bacteria in wastewater systems challenge the effectiveness of partial nitrification-denitrification processes? We are interested in investigating the diversity, distribution, and ecology of comammox bacteria using high-throughput DNA sequencing and state-of-the-art bioinformatics approaches to assemble and extract their genomes. Detailed genomic data will help determine situations under which comammox bacteria are likely to be process relevant and inform laboratory/pilot scale experiments to develop strategies to limit their activity and abundance.
Remote & real-time DNA sequencing for microbiological water quality monitoring. Microbiological water quality monitoring relies on collecting samples in the field, their transport to the laboratory, and plate-based analysis that can take 2-3 days to provide data while only providing information on the small proportion of bacteria that are amenable to culturing. Though recent developments in DNA sequencing technology have made culture independent approaches feasible, these approaches still cannot provide rapid data. We are utilizing a portable, USB stick-size device that is powered by connecting to a laptop and can sequence DNA from a sample on a continuous basis while providing sequence data in real-time. We are also developing protocols for sample processing that can be performed in the field, with the goal of automating these protocols such that samples are collected, processed, and sequenced on-site without the requirement of human intervention. Our vision is that in the near future water utilities will deploy dozens to hundreds of these devices for remote DNA sequencing in the distribution system, with processed data streamed in real-time to operators at drinking water treatment plants in a user-friendly and interactive format.
Metagenome-guided optimization of biological drinking water treatment systems. Biological drinking water treatment utilizes microbially catalyzed reactions to remove pollutants and is a sustainable and cost-effective alternative to conventional physical and chemical processes. Biological filtration processes have successfully demonstrated the removal of a range of organic and inorganic pollutants through the optimization of reactor design and operational parameters. Yet, the number of process control variables pale in comparison to the diversity of emerging contaminants that water treatment plants will be required to treat over the years. Comprehensive understanding of the metabolic potential of microbial communities in biological filters has the potential to help water utilities maximally exploit the biology at their disposal. One of our key expertise lies in revealing the metabolic potential of microbial communities at the genome level. Through the use of cutting-edge metagenomic sequencing and bioinformatics techniques we can not only quantify the microbial composition of a sample, but also catalogue the genetic inventory of individual microorganisms. Using this information, we can identify metabolic pathways for biological transformation of pollutants in individual organisms and at the entire community level. A priori knowledge of biofilter genetic inventory can help identify operational parameters and chemical conditions that can maximize biofilter performance while diversifying the range of pollutants removed. Our vision is that biofilter genetic inventories will enable drinking water treatment plants to enhance or suppress target microbial activity in response to changes in concentrations and diversity of pollutants in drinking water sources over biologically relevant time-scales.