Abstract
Nitrite is a key intermediate in nitrogen metabolism that determines microbial transformations of N and P, greenhouse gas (N2O) emissions, and system nutrient removal efficiency. However, nitrite also exerts toxic effects on microorganisms. A lack of understanding of high nitrite-resistance mechanisms at community- and genome-scale resolutions hinders the optimization for robustness of wastewater treatment systems. Here, we established nitrite-dependent denitrifying and phosphorus removal (DPR) systems under a gradient concentration of nitrite (0, 5, 10, 15, 20, and 25 mg N/L), relying on 16S rRNA gene amplicon and metagenomics to explore high nitrite-resistance mechanism. The results demonstrated that specific taxa were adopted to change the metabolic relationship of the community through phenotypic evolution to resist toxic nitrite contributing to the enhancement of denitrification and inhibition of nitrification and phosphorus removal. The key specific species, Thauera enhanced denitrification, whereas Candidatus Nitrotoga decreased in abundance to maintain partial nitrification. The extinction of Candidatus Nitrotoga induced a simpler restructuring-community, forcing high nitrite-stimulating microbiome to establish a more focused denitrification rather than nitrification or P metabolism in response to nitrite toxicity. Our work provides insights for understanding microbiome adaptation to toxic nitrite and giving theoretical support for operation strategy of nitrite-based wastewater treatment technology.
| Original language | English |
|---|---|
| Article number | 121549 |
| Journal | Environmental Pollution |
| Volume | 327 |
| DOIs | |
| State | Published - 15 Jun 2023 |
| Externally published | Yes |
Keywords
- Metagenomics
- Microbial interactions
- Nitrogen cycle
- Phosphorus metabolism
- Random forest
- Wastewater treatment
Fingerprint
Dive into the research topics of 'Nitrite-resistance mechanisms on wastewater treatment in denitrifying phosphorus removal process revealed by machine learning, co-occurrence, and metagenomics analysis'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver