Respirometric response and microbial succession of nitrifying sludge to m-cresol pulses in a sequencing batch reactor

Co-based metal-organic frameworks for enhanced nickel adsorption and its impact on nitrifying microbial activity

The release of nickel "Ni(II)" into aquatic environments is of great concern because of environmental and health issues. Metal-organic frameworks (MOFs) are one of the most promising technologies for removing heavy metals from water. In this work, an octahedral Co-based MOF (Co-MOF) was synthesized with a high Ni(II) removal capacity (qmax of 1534.09 ± 45.49 mg g-1) in aqueous media. For the first time, the effect of Co-MOF alone and in co-exposure with Ni(II) on nitrifying microbial consortium was assessed using dynamic microrespirometry. A single concentration of Co-MOF had no significant effects on nitrifying microbial consortium, while the concentration of Ni(II) exerted non-competitive inhibition on the nitrifying microbial consortium with an IC50 of 1.67 ± 0.03 mg L-1. In addition, the theoretical speciation analysis showed a decrease of 40% of IC50 when the free Ni(II) concentration was considered. Co-exposure of Co-MOF and Ni(II) during the nitrifying process allowed us to conclude that Co-MOF is an effective adsorbent for Ni(II) and can be used to mitigate the inhibitory effects of nickel on nitrifying microbial consortia, which is crucial for maintaining the good operation of wastewater treatment and balance of nitrogen cycle.

Predicting the Simultaneous Oxidation of Ammonia, Nitrite, and m-cresol and Microbial Growth in a Sequencing Batch Reactor with a Kinetic Model Using Inhibition and Inactivation Effects

The kinetic model derived in this study was able to adequately predict the simultaneous oxidation of ammonia, nitrite, and m-cresol and microbial growth using nitrifying sludge in a sequencing batch reactor. Time-varying inhibition and inactivation effects were successfully incorporated in the process kinetics to account for the past cell exposure history to m-cresol increasing concentrations (up to 150 mg C L^-1). The initial concentration of the microbial species (ammonia and nitrite oxidizers, heterotrophs) was evaluated using pyrosequencing of DNA samples of the consortium. These measurements allowed to establish a model that explicitly handles specific reaction rates and to enhance the practical identifiability of the model parameters. A single simulation run was used to adequately predict the kinetic behavior of the main variables throughout the 242 cycles using a single set of initial conditions in the first cycle. This kind of dynamic model may be used as a helpful predictive tool to improve nitrification by avoiding the occurrence of severely repetitive inhibitive conditions due to the presence of inhibitive/toxic aromatic compounds.

Flux balance analysis of the ammonia-oxidizing bacterium Nitrosomonas europaea ATCC19718 unravels specific metabolic activities while degrading toxic compounds

The ammonia-oxidizing bacterium Nitrosomonas europaea has been widely recognized as an important player in the nitrogen cycle as well as one of the most abundant members in microbial communities for the treatment of industrial or sewage wastewater. Its natural metabolic versatility and extraordinary ability to degrade environmental pollutants (e.g., aromatic hydrocarbons such as benzene and toluene) enable it to thrive under various harsh environmental conditions. Constraint-based metabolic models constructed from genome sequences enable quantitative insight into the central and specialized metabolism within a target organism. These genome-scale models have been utilized to understand, optimize, and design new strategies for improved bioprocesses. Reduced modeling approaches have been used to elucidate Nitrosomonas europaea metabolism at a pathway level. However, genome-scale knowledge about the simultaneous oxidation of ammonia and pollutant metabolism of N. europaea remains limited. Here, we describe the reconstruction, manual curation, and validation of the genome-scale metabolic model for N. europaea, iGC535. This reconstruction is the most accurate metabolic model for a nitrifying organism to date, reaching an average prediction accuracy of over 90% under several growth conditions. The manually curated model can predict phenotypes under chemolithotrophic and chemolithoorganotrophic conditions while oxidating methane and wastewater pollutants. Calculated flux distributions under different trophic conditions show that several key pathways are affected by the type of carbon source available, including central carbon metabolism and energy production.

Nitrosomonas europaea catalyzes the first step of the nitrification process (ammonia to nitrite). It has been recognized as one of the most important members of microbial communities of wastewater treatment processes. Genome-scale models are powerful tools in process optimization since they can predict the organism’s behavior under different growth conditions. The final genome-scale model of N. europaea ATCC19718, iGC535, can predict growth and oxygen uptake rates with 90.52% accuracy under chemolithotrophic and chemolitoorganotrophic conditions. Moreover, iGC535 can predict the simultaneous oxidation of ammonia and wastewater pollutants, such as benzene, toluene, phenol and, chlorobenzene. iGC535 represents the most comprehensive knowledge-base for a nitrifying organism available to date. The genome-scale model reconstructed in this work brings us closer to understanding N. europaea’s role in a community with other nitrifying bacteria.

Aerobic biodegradation of p-nitrophenol in a nitrifying sludge bioreactor: System performance, sludge property and microbial community shift

The system performance, sludge property and microbial community shift were evaluated in a nitrifying sludge (NS) bioreactor for simultaneous treating p-Nitrophenol (PNP) and high ammonia wastewater. After long-term acclimation for 80 days, the removal efficiencies of PNP and NH₄⁺-N reached to 99.9% and 99.5%, respectively. Meanwhile, the effluent PNP gradually decreased from 7.9 to 0.1 mg/L by acclimation of sludge. The particle size of NS increased from 115.2 μm to 226.3 μm accompanied by the decreased zeta potential as a self-protection strategy. The presence of PNP exposure altered the effluent soluble microbial products (SMP) fluorescent components and molecular composition. The increase in the relative abundance of Thauera, Nitrospiraceae and Nitrosomonas indicated the nitrification and denitrification capacities of NS increased, which maybe the PNP cometabolic biodegradation effect. Moreover, Ignavibacteria and Aeromonas were responsible as the dominant bacteria for degrading PNP in the nitrifying system.