Wastewater

Quorum Sensing Induction and Quenching in Biological Nutrient Removal Systems

Biological nutrient removal (BNR) systems at water reclamation facilities employ key microorganisms and consortia that oxidize bioavailable nutrients (e.g., ammonia) to their inert forms (e.g., nitrogen gas). Each step of nitrogen transformation is performed by distinct microbial consortia working in concert with others, where the products of one group feed in as the reactants of another group. The collaborative and syntrophic nature of microbial nitrogen transformation encourages study of the intercellular interactions within these communities. Quorum sensing is a microbial intercellular communication and collaboration system wherein cells send signaling molecules (autoinducers) to each other to coordinate collective behavior and activity. Quorum sensing induction—via exogenous autoinducer supplementation—is being explored as a strategy for boosting BNR efficiency. Conversely and simultaneously, microbial quorum quenching systems inhibit quorum sensing signaling to suppress excessive activity. Together, quorum sensing and quorum quenching regulate community cellular activity and efficiency.

Biofilm reactors in water reclamation systems offer operational advantages including resilience to load changes and lower space requirements, but it can be time and energy intensive to establish stable BNR communities. These biofilms are teeming with diverse, syntrophic microbial communities that live and thrive closely with their neighbors; quorum sensing and quenching are vital drivers of those collaborations.

We seek to:

understand the effects of quorum sensing induction and quenching on ammonia-oxidizing and nitrite-oxidizing bacteria in terms of their community composition dynamics and nitrogen transformation activity and efficiency;
determine the key quorum sensing and quenching molecules that contribute to enhanced nitrogen transformation and accelerated biofilm development

This research will systematically formulate optimal autoinducer cocktails that could supplement existing systems, effectively tuning microbial communities using quorum sensing induction and quenching for more efficient nitrogen transformation.

quorum sensing in nitrogen cycle — Figure created in BioRender.com

Researchers

Hira Waheed, PhD
Lan Nguyen

Funding

National Science Foundation (CAREER)

Collaborators

Lee Ferguson
Abbey Joyce

Evaluating the impact of extreme weather events on biological wastewater treatment processes using modeling

Climate change is increasing the frequency of intense wet weather, placing considerable stress on wastewater treatment plants. The surge in high-flow events threatens to push operational plant capacities to their limits, particularly for older infrastructure. This will potentially also lead to biomass loss from biological treatment processes and even plant malfunctions. Current models often struggle to predict these transient high flows due to their sporadic occurrence and limited data. To address this, we are developing predictive models specifically designed to capture high flows. These models leverage monitoring data from routine plant operations and apply extreme value analysis to focus on the high-flow variations. This approach helps the model focus on these critical flows which are hoped to provide a more precise prediction of high-impact flows. By tailoring models to capture such irregularities, we aim to improve the ability of models to forecast and respond to extreme flows, thereby reducing the risk of overflows and operational strain.

We are also developing resilience-oriented process models and life cycle assessment (LCA) models of wet weather management strategies. Resilience-oriented process models are calibrated with data from facilities with strict nitrogen discharge requirements. By simulating how these technologies can manage wet weather surges while optimizing existing infrastructure, these models provide valuable insights into treatment resilience under varying conditions. LCA models of wet weather management strategies will evaluate trade-offs between system resiliency and other outputs such as increased energy demands, higher chemical use, potential GHG emissions, and the risk of discharging partially treated water. This analysis is vital for developing wet weather management practices that align with long-term environmental objectives.

Researcher

Isaac Musaazi

Collaborators

Internal carbon storage

Conventional nitrogen removal processes typically require external carbon sources to drive denitrification, increasing both operational costs and carbon emissions. Recent evidence suggests that certain heterotrophic denitrifying bacteria can store organic carbon intracellularly under anaerobic conditions and later use it for nitrate reduction in the absence of external carbon.

This project investigates the microbial ecology and genetic mechanisms behind anaerobic intracellular carbon storage, endogenous denitrification, and their role in sustainable nitrogen removal. We use stable isotope probing (SIP), DNA/RNA sequencing, metagenomic and metatranscriptomic analysis to identify active microbial populations and key functional genes involved in carbon uptake and utilization. Experimental enrichment and controlled incubations are conducted using activated sludge collected from full-scale wastewater treatment plants to simulate relevant environmental conditions and assess the dynamics of carbon storage and denitrification.

Building on these experimental insights, we are developing a gene- and genome-resolved mathematical modeling framework that incorporates microbial gene expression and population-level behavior. The modeling aims to enhance prediction and optimization of nitrogen removal performance by capturing microbial functional diversity beyond traditional biomass-based models.