Linking ecological strategies to niche breadth: interpretable machine learning unravels community patterns of nirS-type aerobic denitrifiers along oxygen gradients in drinking water reservoirs.

Sustainable hydrogen and vivianite recovery from waste activated sludge in electro-fermentation: Perspectives of product regulation and microbial interaction.

Reservoir hydrological fluctuations induce rhizosphere N-cycling divergent patterns: integrating root multi-adaptive strategies perspectives.

Improved microbial compatibility and granular stability in the partial nitrification/Anammox process for food waste digestate treatment.

Improvements in denitrifying bacteria since 1970 have optimized the activity of autotrophic denitrification and heterotrophic nitrification. Synchronous autotrophic biofilms, denitrification, and nitrification have enhanced nitrogen removal from industrial wastewater, but so far, this process relies on variables such as dissolved oxygen, pH, and carbon sources. The aerobic denitrification capability of the coking wastewater-derived Stutzerimonas stutzeri KA1 is quantified in the present investigation to enhance nitrogen removal potential under various environmental conditions. The strain was studied for its ability to isolate nitrate using sodium acetate as the carbon source, and the effectiveness of the microorganism was tested at different dissolved oxygen, pH, and C/N levels. Findings indicate that strain KA1 achieved nearly 100% nitrate elimination within 40h at pH 6-10 and an optimal C/N ratio of 8, demonstrating resilience under both aerobic and anaerobic conditions. Strain KA1 showed robust denitrification across a wide range of dissolved oxygen levels (0-100%), including stable nitrate reduction under aerobic bulk conditions. Bioaugmentation experiments conducted in a Sequential Batch Reactor (SBR) confirmed that strain KA1 significantly enhanced nitrogen removal, particularly under saline wastewater conditions, exceeding the control systems. In conjunction with nitrogen elimination, the strain also demonstrates robust Chemical Oxygen Demand (COD) reduction, efficiently degrading organic pollutants in coking wastewater. Compared to other studies, Stutzerimonas stutzeri KA1 demonstrated higher denitrification efficiency and greater resistance to environmental stress, making it a scalable, cost-effective solution for denitrifying industrial wastewater. The results offer valuable insights into optimizing wastewater treatment parameters and can advance microbial biotechnology to foster sustainable environmental practices.

Exploring the high-concentration powdered carrier bio-fluidized bed process nitrogen removal performance: Effect of dissolved oxygen.

Dual-function of nitrogen removal and autoinducer-2 quorum quenching improves MBR performance in treating TMAH-containing wastewater.

Aerobic denitrification coupled with iron-carbon micro-electrolysis to enhance synchronous removal of nitrogen and phosphorus in wetlands.

Microbial succession and operational strategies unlocking high-rate performance in IC-Anammox-HAP granular system.

Synergistic antibacterial effects and mechanisms of different phenolic acids against Shewanella putrefaciens from fish, with emphasis on the combination of gallic acid and caffeic acid.

Magnetic properties driving nitrogen removal improvement in magnetite-enhanced activated sludge: Mechanistic insights and process validation.

Microplastics exacerbate antibiotic resistance by regulating microbial and functional gene dynamics in sludge and food waste composting.

Microbial self-regulation and electron transport reconstruction under Cr(VI)-4-CP stress: From synergistic inhibition to antagonistic interaction.

Plant and microbial interactions under different planting patterns regulate nitrogen removal in constructed wetlands.

Linking carbon, nitrogen and sulfur cycles: Electron transfer model for nitrate and sulfate dependent anaerobic oxidation of methane.

Differential modulation of rhizosphere dissimilatory nitrate reduction to ammonium (DNRA) by wheat cultivars under nitrogen deficiency

Static magnetic field enhances respiratory dissimilatory nitrate reduction to ammonium over denitrification in sulfide-based autotrophic systems.

Effects of micro(nano)plastics on nutrient removal and greenhouse gas production under heavy metals cooccurence in AMF-enhanced constructed wetlands.

Dermatophilaceae polyphosphate-accumulating organisms (PAOs), formerly classified as Tetrasphaera PAOs, play pivotal roles in enhanced biological phosphorus removal (EBPR). However, their phylogenetic diversity, ecological preferences, and metabolic traits remain poorly characterized, and a robust marker gene for their classification is lacking. Here, we performed an extensive phylogenomic and metabolic analysis of Dermatophilaceae PAOs utilizing 46 newly recovered metagenome-assembled genomes from a laboratory-scale EBPR reactor treating high-strength wastewater and full-scale wastewater treatment plants. These analyses revealed a previously uncharacterized PAO genus, named here as Candidatus Dermatophostum, which shows specific preference for high-phosphorus environments. Its representative species, Ca. Dermatophostum ammonifactor, was enriched in the EBPR reactor and its PAO phenotype was confirmed by polyphosphate staining and fluorescence in situ hybridization. Integrative meta-omics combining genomic, transcriptomic, and protein structure analyses revealed its specialized metabolic capabilities for phosphate metabolism, glycogen synthesis, and dissimilatory nitrate reduction to ammonium. Moreover, Ca. Dermatophostum was found to be widely distributed across wastewater treatment plants worldwide, underscoring both its diverse metabolic capabilities and potential engineering implications for mitigating nitrous oxide (N2O) emissions for EBPR system. Finally, we propose a ppk1-based classification framework that resolves Dermatophilaceae PAOs into six distinct clades, consistent with whole-genome phylogeny, and demonstrates that ppk1 can serve as a reliable marker gene for tracking these populations. Together, these findings expand the ecological and functional understanding of Dermatophilaceae PAOs and highlight their promise for advancing sustainable wastewater treatment and resource recovery.

Efficient treatment of aquaculture effluent is a crucial measure for ensuring the green and sustainable development of fisheries and alleviating pressure on aquatic ecosystems. However, traditional treatment technologies face bottlenecks of low efficiency and poor adaptability, making it difficult to meet the pollution control demands of large-scale aquaculture development. This is a systematic review focusing on artificial intelligence (AI) applications in aquaculture effluent treatment, aiming to clarify the technical framework, core application scenarios, industry trends, challenges, and future directions of AI-driven aquaculture effluent treatment. It first outlines core machine learning technologies, compares model adaptability, and analyzes AI synergies with IoT and digital twins. It then details AI implementation pathways across four core scenarios: precision feeding for pollution reduction, water quality monitoring and prediction, development of denitrifying and phosphorus-removing engineering bacteria, and system module control. Finally, it validates technical effectiveness through case studies, identifies industry trends toward integrated models and predictive monitoring, highlights existing challenges, such as data quality bottlenecks, system coupling complexity, and insufficient implementation economics, and proposes future research directions. This study provides theoretical foundations and practical references for the intelligent upgrading of aquaculture effluent treatment and the high-quality development of the fisheries industry.