With the continuous development of intensive mariculture, the application of the integrated bioremediation system of aquaculture wastewater (IBSAW) is increasingly promoted. However, the process and nutrients removal performance of the IBSAW need to be further optimized due to its immature technologies. In this study, exogenous compound bacteria (ECB) were added to IBSAW to investigate its pollutants removal efficiency and the relevant mechanisms. High-throughput sequencing and Geochip gene array were used to analyze the correlation between nutrients and bacteria, and the abundance of N and P cycling genes were quantified. Multivariable statistics, dimensionality reduction analysis, and network analysis were applied to explore the mechanisms of IBSAW operation. The results showed that the nutrients decreased significantly after adding ECB, with the brush treatment group significantly outperforming the ceramsite in removing NO and PO. Ceramsite has an advantage in removing NO-N. The addition of ECB and different substrates significantly affected the composition of bacterial communities. The contents of nosZ and nirKS related to denitrification in the treatment groups were significantly higher than those in the control group, and the contents in the brush treatment group were significantly higher than that of ceramsite. The biomarkers Psychroserpens and Ruegeria on the biofilm of the brush treatment group were positively correlated with nirKS, while Mycobacterium, Erythrobacter and Paracoccus, Pseudohaliea in the ceramsite group were positively correlated with nirS and nirK, respectively. Therefore, it is speculated that the ECB significantly promoted the increase of denitrification bacteria by affecting the composition of bacterial communities, and the ECB combined with functional genera improved the efficiency of nutrients removal in the system. This study provided a reference for understanding the process and mechanism of nutrients removal, optimizing the wastewater purification technology of the IBSAW and improving the performance of the system.

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http://dx.doi.org/10.1016/j.envres.2024.118864DOI Listing

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