Periodic Reporting for period 1 - MTSonNAS (Application of a New Kinetic Microbial Theory-Microbial Transition State- on Enriched Nitrifying Activated Sludge Model)
Reporting period: 2023-01-01 to 2024-12-31
Traditional engineering models known as Activated Sludge Model (ASM) are commonly used for operation, design, and optimization of wastewater treatment plants. ASM is implemented in simulation platforms and predicts microbial growth with simulation and calibration of many model parameters which are bound to a range of experimental conditions. The model calibration values have been backed up by decades of expertise through experiments, observations, and applications.
Recently, a statistical physics-based theory, Microbial Transition State (MTS), was proposed to predict microbial growth which relies on fully elemental stoichiometry of biochemical reactions. ASM and MTS models has been tested for different scenarios and comparisons of key features. Basically, ASM predictions are based on empirical formula of Monod and requires calibrating a high number of parameters while MTS requires a smaller number of parameters. However, MTS has not been fully verified with proper experimental data on mixed microbial cultures such as those sustained in wastewater treatment systems. Additionally, conditions such as inhibition of growth by any pollutant compound originated from industrial processes has not been considered for validation of MTS theory yet.
Nitrification is one of the essential processes which takes place in aerobic treatment of wastewater. In this process, ammonia from domestic or industrial activities is converted to nitrite and nitrate by nitrifying bacteria. Nitrification process covers oxidation of ammonia to nitrite by Ammonia Oxidizing Bacteria (AOB). Nitrite is further utilized by Nitrite Oxidizing Bacteria (NOB) and converted to nitrate.
Heavy metal and pharmaceutical pollution have been emerging issues in recent years originating from industrial/domestic/hospital wastewater discharges, landfill leachates and agricultural applications. They threaten marine ecosystems and human health through food chain, bioaccumulation, and biomagnification.
This project is an intersection of environmental engineering, molecular biology and modeling where the main objective was to expand the use of energy-based MTS theory on design and control of wastewater treatment systems. For this purpose, nitrification process was focused. MTS was used for estimating microbial growth kinetics in before and after addition of pollutants from industrial wastewater. Metagenomic and metatranscriptomic tools were utilized for proper estimation of nitrification bacteria abundance and functional activity of microbial community.
Recently, a statistical physics-based theory, Microbial Transition State (MTS), was proposed to predict microbial growth which relies on fully elemental stoichiometry of biochemical reactions. ASM and MTS models has been tested for different scenarios and comparisons of key features. Basically, ASM predictions are based on empirical formula of Monod and requires calibrating a high number of parameters while MTS requires a smaller number of parameters. However, MTS has not been fully verified with proper experimental data on mixed microbial cultures such as those sustained in wastewater treatment systems. Additionally, conditions such as inhibition of growth by any pollutant compound originated from industrial processes has not been considered for validation of MTS theory yet.
Nitrification is one of the essential processes which takes place in aerobic treatment of wastewater. In this process, ammonia from domestic or industrial activities is converted to nitrite and nitrate by nitrifying bacteria. Nitrification process covers oxidation of ammonia to nitrite by Ammonia Oxidizing Bacteria (AOB). Nitrite is further utilized by Nitrite Oxidizing Bacteria (NOB) and converted to nitrate.
Heavy metal and pharmaceutical pollution have been emerging issues in recent years originating from industrial/domestic/hospital wastewater discharges, landfill leachates and agricultural applications. They threaten marine ecosystems and human health through food chain, bioaccumulation, and biomagnification.
This project is an intersection of environmental engineering, molecular biology and modeling where the main objective was to expand the use of energy-based MTS theory on design and control of wastewater treatment systems. For this purpose, nitrification process was focused. MTS was used for estimating microbial growth kinetics in before and after addition of pollutants from industrial wastewater. Metagenomic and metatranscriptomic tools were utilized for proper estimation of nitrification bacteria abundance and functional activity of microbial community.
The scientific achievements of MTSonNAS project covers several scientific axes by integrating mathematical models and microbial biology information. The results serve as the first estimate of the growth kinetics of nitrifiers sustained in wastewater treatment systems using MTS model (environmental engineering). Estimation of growth kinetics using this model has been limited to only model simulations in theoretical studies. MTS theory was for the first time validated by supplying the relevant data which was provided by establishment of realistic test conditions (modeling).
The project involved the input of most appropriate scientific tools for collecting data related to microbial processes in activated sludge systems. Respirometry was chosen as a unique tool to give reliable data for determining process kinetics in the absence and presence of inhibitory compounds. Next generation sequencing tools were used for identification and quantification of existing microorganisms. Metagenomic analysis provided abundance information for particularly nitrifying bacteria, AOB and NOB. Metatranscriptomic analyses yield in functional characterization of whole microbial community covering nitrifiers and heterotrophic bacteria (molecular biology).
The project involved the input of most appropriate scientific tools for collecting data related to microbial processes in activated sludge systems. Respirometry was chosen as a unique tool to give reliable data for determining process kinetics in the absence and presence of inhibitory compounds. Next generation sequencing tools were used for identification and quantification of existing microorganisms. Metagenomic analysis provided abundance information for particularly nitrifying bacteria, AOB and NOB. Metatranscriptomic analyses yield in functional characterization of whole microbial community covering nitrifiers and heterotrophic bacteria (molecular biology).
The modeling results were the first numerical values for nitrifier growth kinetics where abundance of microbial community members, essential microbial processes and gene activity deviations were considered together and information integrated to model calibrations. Comparison of MTS and traditional ASM calibration results pointed out similar range of microbial growth rates. However, MTS required a smaller number of parameters in the calibration process. Model interpretations indicated predictive ability of MTS for future applications not only in environmental engineering but also in diverse bioprocess from environment and industries.
Exposure of nitrifying activated sludge to selected pollutants (nickel, chromium, and diclofenac) highlighted different inhibitory/toxic effects on the growth of nitrifying bacteria and decay associated processes. Interpretation of microbial community analyses together with modeling showed that pollutants affected not only nitrifiers but also heterotrophic bacteria. Related biological processes such as biomass decay and hydrolysis of biomass components were implemented to MTS and ASM model structure in order to represent all microbial activity and estimate nitrifier growth kinetics accurately. The results indicated the importance of further research on the composition of extracellular polymeric substances or microbial products generated by microorganisms for proper implementation of related processes.
These results provided experimental grounds, numerical data and insights to environmental engineers, biologists, bioprocess engineers, model developers from research institutions and industry to better understand ongoing bioprocesses in wastewater treatment or industry. Furthermore, they contribute to predicting and controlling pollution generated from related industrial activities and efforts on the mitigation of pollutants in the engineered systems and nature.
Exposure of nitrifying activated sludge to selected pollutants (nickel, chromium, and diclofenac) highlighted different inhibitory/toxic effects on the growth of nitrifying bacteria and decay associated processes. Interpretation of microbial community analyses together with modeling showed that pollutants affected not only nitrifiers but also heterotrophic bacteria. Related biological processes such as biomass decay and hydrolysis of biomass components were implemented to MTS and ASM model structure in order to represent all microbial activity and estimate nitrifier growth kinetics accurately. The results indicated the importance of further research on the composition of extracellular polymeric substances or microbial products generated by microorganisms for proper implementation of related processes.
These results provided experimental grounds, numerical data and insights to environmental engineers, biologists, bioprocess engineers, model developers from research institutions and industry to better understand ongoing bioprocesses in wastewater treatment or industry. Furthermore, they contribute to predicting and controlling pollution generated from related industrial activities and efforts on the mitigation of pollutants in the engineered systems and nature.