Marine microorganisms have an inherent advantage in the treatment of saline wastewater due to their halophilic properties. Ammonium assimilation is the most important and common nitrogen conversion pathway in the ocean, which means that it may be a suitable nitrogen removal strategy under high salinity conditions. However, the targeted construction of engineering microbiomes with ammonium assimilation function for nitrogen recovery has not been realized. Here, we constructed four halophilic ammonium assimilation microbiomes from marine microbial community under varying chemical oxygen demand (COD) to nitrogen (COD/N) ratios. The regulation of COD/N ratio on microbial self-assembly was explored at the phenotypic, genetic, and microbial levels. The results of nitrogen balance tests, functional genes abundance and microbial community structure confirmed that the microbiomes regulated by different COD/N ratios all performed obligate ammonium assimilation functions. >93% of ammonium, 90% of TN, 98% of COD, and 82% of phosphorus were simultaneously removed by microbial assimilation under the COD/N ratio of 20. COD/N ratios significantly affected the self-assembly of microbiomes by selectively enriching heterotrophic microorganisms with different preference for organic carbon load. Additionally, the increase of COD/N ratio intensified the competition among species within the microbiome (the proportion of negative connections of microbial network increased from 5.0% to 24.4%), which may enhance the stability of community structure. Taken together, these findings can provide theoretical guidance for the construction and optimization of engineering microbiomes for synergistic nitrogen removal and recovery.

This study aims at applying and verifying the MFI-UF method to predict particulate fouling in RO plants. Two full-scale RO plants treating surface water, with average capacity of 800–2000 m³/h, were studied. Firstly, the MFI-UF of RO feed and concentrate was measured using 5–100 kDa membranes at same flux applied in the RO plants (20–26 L/m².h). Subsequently, the particle disposition factor (Ω) was calculated to simulate particle deposition in RO cross-flow filtration. Finally, particulate fouling rates were predicted based on MFI-UF and Ω, and compared with the actual fouling rates in the plants. For plant A, the results showed that the fouling rates predicted using MFI-UF measured with 100 kDa membrane have the best agreement with the actual fouling (with 3–11 % deviation). For plant B, the fouling rates predicted based on both 10 and 100 kDa membranes agree well with the actual fouling (with 2 % and 15 % deviation, respectively). However, the fouling predicted based on 5 kDa membrane is considerably overestimated for both plants, which is attributed to the effect of the low surface porosity of 5 kDa membrane. More widespread applications of MFI-UF in full-scale RO plants are required to demonstrate the most suitable MFI-UF membranes for fouling prediction.

The contradiction between theoretical metabolism of ammonium assimilation and experiential understanding of conventional biosystems makes the rational optimization of the ammonium-assimilating microbiome through carbon to nitrogen (C/N) ratios perplexing. The effect of different C/N ratios on ammonium-assimilating biosystems was investigated in saline wastewater treatment. C/N ratios significantly hindered the nutrient removal efficiency, but ammonium-assimilating biosystems maintained functional stability in nitrogen conversions and microbial communities. With sufficient biomass, higher than 86% ammonium and 73% phosphorus were removed when C/N ratios were higher than 25. Ammonium assimilation dominated the nitrogen metabolism in all biosystems even under relatively low C/N ratios, evidenced by the extremely low abundances of nitrification functional genes. Different C/N ratios did not significantly change the bacterial community structure of ammonium-assimilating biosystems. It is anticipated that the ammonium-assimilating biosystem with advantages of clear metabolic pathway and easy optimization can be applied to nutrient removal and recovery in saline environments.