Responses of microbial interactions to elevated salinity in activated sludge microbial community

Highlights

● Salinity led to the elevation of NAR over 99.72%.

● Elevated salinity resulted in a small, complex, and more competitive network.

● Various AOB or denitrifiers responded differently to elevated salinity.

● Putative keystone taxa were dynamic and less abundant among various networks.

Abstract

Biological treatment processes are critical for sewage purification, wherein microbial interactions are tightly associated with treatment performance. Previous studies have focused on assessing how environmental factors (such as salinity) affect the diversity and composition of the microbial community but ignore the connections among microorganisms. Here, we described the microbial interactions in response to elevated salinity in an activated sludge system by performing an association network analysis. It was found that higher salinity resulted in low microbial diversity, and small, complex, more competitive overall networks, leading to poor performance of the treatment process. Subnetworks of major phyla (Proteobacteria, Bacteroidetes, and Chloroflexi) and functional bacteria (such as AOB, NOB and denitrifiers) differed substantially under elevated salinity process. Compared with subnetworks of Nitrosomonadaceae, Nitrosomonas (AOB) made a greater contribution to nitrification under higher salinity (especially 3%) in the activated sludge system. Denitrifiers established more proportion of cooperative relationships with other bacteria to resist 3% salinity stress. Furthermore, identified keystone species playing crucial roles in maintaining process stability were dynamics and less abundant under salinity disturbance. Knowledge gleaned from this study deepened our understanding of microbial interaction in response to elevated salinity in activated sludge systems.

Graphical abstract

Keywords

Elevated salinity / Activated sludge system / Pollution removal / Microbial interactions / Competitive relationship

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Acknowledgements

This study was supported by the Open Research Fund Program of State Environmental Protection Key Laboratory of Food Chain Pollution Control (China) (FC2022YB08) and the Fundamental Research Funds for the Central Universities (China) (JD2227).

Electronic Supplementary Material

Supplementary material is available in the online version of this article at https://doi.org/10.1007/s11783-023-1660-x and is accessible for authorized users.

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