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

Highlight

● 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.

Keywords

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

参考文献

[1] Baumann B, Snozzi M, Van Der Meer J R, Zehnder A J B. (1997). Development of stable denitrifying cultures during repeated aerobic-anaerobic transient periods. Water Research, 31(8): 1947–1954

[2] Blonder B, Wey T W, Dornhaus A, James R, Sih A. (2012). Temporal dynamics and network analysis. Methods in Ecology and Evolution, 3(6): 958–972

[3] Deng Y, Jiang Y H, Yang Y, He Z, Luo F, Zhou J. (2012). Molecular ecological network analyses. BMC Bioinformatics, 13: 113

[4] Deng Y, Zhang P, Qin Y, Tu Q, Yang Y, He Z, Schadt C W, Zhou J. (2016). Network succession reveals the importance of competition in response to emulsified vegetable oil amendment for uranium bioremediation. Environmental Microbiology, 18(1): 205–218

[5] Duan J, Fang H, Su B, Chen J, Lin J. (2015). Characterization of a halophilic heterotrophic nitrification-aerobic denitrification bacterium and its application on treatment of saline wastewater. Bioresource Technology, 179: 421–428

[6] Eiler A, Heinrich F, Bertilsson S. (2012). Coherent dynamics and association networks among lake bacterioplankton taxa. ISME Journal, 6(2): 330–342

[7] García-Ruiz . (2018). Effects of salinity on the nitrogen removal efficiency and bacterial community structure in fixed-bed biofilm CANON bioreactors. Chemical Engineering Journal, 347: 156–164

[8] Girvan M, Newman M E J. (2002). Community structure in social and biological networks. Proceedings of the National Academy of Sciences of the United States of America, 99(12): 7821–7826

[9] Grießmeier V, Bremges A, McHardy A C, Gescher J. (2017). Investigation of different nitrogen reduction routes and their key microbial players in wood chip-driven denitrification beds. Scientific Reports, 7: 17028

[10] Han F, Zhang M, Liu Z, Shang H, Li Q, Zhou W. (2021). Dynamic characteristics of microbial community and soluble microbial products in partial nitrification biofilm system developed from marine sediments treating high salinity wastewater. Journal of Environmental Management, 290: 112586

[11] Hu Y R, Jiang L, Sun X Y, Wu J Q, Ma L, Zhou Y B, Lin K F, Luo Y, Cui C Z. (2021). Risk assessment of antibiotic resistance genes in the drinking water system. Science of the Total Environment, 800: 149650

[12] Huang X, Xing Y X, Wang H J, Dai Z Y, Chen T T. (2022). Nitrogen advanced treatment of urban sewage by denitrification deep-bed filter: removal performance and metabolic pathway. Frontiers in Microbiology, 12: 811697

[13] Kämpfer P, Jerzak L, Wilharm G, Golke J, Busse H J, Glaeser S P. (2015). Gemmobacter intermedius sp. nov., isolated from a white stork (Ciconia ciconia). International Journal of Systematic and Evolutionary Microbiology, 65(Pt_3): 778–783

[14] Kishor R, Purchase D, Saratale G D, Saratale R G, Ferreira L F R, Bilal M, Chandra R, Bharagava R N. (2021). Ecotoxicological and health concerns of persistent coloring pollutants of textile industry wastewater and treatment approaches for environmental safety. Journal of Environmental Chemical Engineering, 9(2): 105012

[15] Lefebvre O, Moletta R. (2006). Treatment of organic pollution in industrial saline wastewater: a literature review. Water Research, 40(20): 3671–3682

[16] Li J B, Ma J X, Sun L, Liu X, Liao H Y, He D. (2022). Mechanistic insight into the biofilm formation and process performance of a passive aeration ditch (PAD) for decentralized wastewater treatment. Frontiers of Environmental Science & Engineering, 16(7): 86

[17] Liu X, Dai J, Ng T L, Chen G. (2019). Evaluation of potential environmental benefits from seawater toilet flushing. Water Research, 162: 505–515

[18] Luo F, Zhong J, Yang Y, Scheuermann R H, Zhou J. (2006). Application of random matrix theory to biological networks. Physics Letters. [Part A], 357(6): 420–423

[19] Luo L, Zhou W, Yuan Y, Zhong H, Zhong C. (2021). Effects of salinity shock on simultaneous nitrification and denitrification by a membrane bioreactor: performance, sludge activity, and functional microflora. Science of the Total Environment, 801: 149748

[20] Luo W, Hai F I, Kang J, Price W E, Guo W, Ngo H H, Yamamoto K, Nghiem L D. (2015). Effects of salinity build-up on biomass characteristics and trace organic chemical removal: implications on the development of high retention membrane bioreactors. Bioresource Technology, 177: 274–281

[21] Maqbool T, Cho J, Hur J. (2018). Changes in spectroscopic signatures in soluble microbial products of activated sludge under different osmotic stress conditions. Bioresource Technology, 255: 29–38

[22] Miao L, Wang S, Li B, Cao T, Zhang F, Wang Z, Peng Y. (2016). Effect of carbon source type on intracellular stored polymers during endogenous denitritation (ED) treating landfill leachate. Water Research, 100: 405–412

[23] Mota C, Head M A, Ridenoure J A, Cheng J J, de Los Reyes F L 3rd. (2005). Effects of aeration cycles on nitrifying bacterial populations and nitrogen removal in intermittently aerated reactors. Applied and Environmental Microbiology, 71(12): 8565–8572

[24] Olesen J M, Bascompte J, Dupont Y L, Jordano P. (2007). The modularity of pollination networks. Proceedings of the National Academy of Sciences of the United States of America, 104(50): 19891–19896

[25] Peng L, Ni B J, Ye L, Yuan Z. (2015). N₂O production by ammonia oxidizing bacteria in an enriched nitrifying sludge linearly depends on inorganic carbon concentration. Water Research, 74: 58–66

[26] Shi S, Nuccio E E, Shi Z J, He Z, Zhou J, Firestone M K. (2016). The interconnected rhizosphere: high network complexity dominates rhizosphere assemblages. Ecology Letters, 19(8): 926–936

[27] Smolders G J F, van der Meij J, van Loosdrecht M C, Heijnen J J. (1994). Stoichiometric model of the aerobic metabolism of the biological phosphorus removal process. Biotechnology and Bioengineering, 44(7): 837–848

[28] Sun X, Xu R, Dong Y, Li F, Tao W, Kong T, Zhang M, Qiu L, Wang X, Sun W. (2020). Investigation of the ecological roles of putative keystone taxa during tailing revegetation. Environmental Science & Technology, 54(18): 11258–11270

[29] Tang Z, Lin Z, Wang Y, Zhao P, Kuang F, Zhou J. (2020). Coupling of thermophilic biofilm-based systems and ozonation for enhanced organics removal from high-temperature pulping wastewater: performance, microbial communities, and pollutant transformations. Science of the Total Environment, 714: 136802

[30] Teske A, Alm E, Regan J M, Toze S, Rittmann B E, Stahl D A. (1994). Evolutionary relationships among ammonia- and nitrite-oxidizing bacteria. Journal of Bacteriology, 176(21): 6623–6630

[31] Wang J, Gong B, Huang W, Wang Y, Zhou J. (2017a). Bacterial community structure in simultaneous nitrification, denitrification and organic matter removal process treating saline mustard tuber wastewater as revealed by 16S rRNA sequencing. Bioresource Technology, 228: 31–38

[32] Wang J, Liu Q, Wu B, Hu H, Dong D, Yin J, Ren H. (2020a). Effect of salinity on mature wastewater treatment biofilm microbial community assembly and metabolite characteristics. Science of the Total Environment, 711: 134437

[33] Wang J, Zhou J, Wang Y, Wen Y, He L, He Q. (2020b). Efficient nitrogen removal in a modified sequencing batch biofilm reactor treating hypersaline mustard tuber wastewater: The potential multiple pathways and key microorganisms. Water Research, 177: 115734

[34] Wang X, Li J, Liu R, Hai R, Zou D, Zhu X, Luo N. (2017b). Responses of bacterial communities to CuO nanoparticles in activated sludge system. Environmental Science & Technology, 51(10): 5368–5376

[35] WangX, Ya T, ZhangM, LiuL, HouP, LuS (2019). Cadmium (II) alters the microbial community structure and molecular ecological network in activated sludge system. Environmental Pollution, 255(Pt 2): 113225

[36] Wang Y, Shen L, Wu J, Zhong F, Cheng S. (2020c). Step-feeding ratios affect nitrogen removal and related microbial communities in multi-stage vertical flow constructed wetlands. Science of the Total Environment, 721: 137689

[37] Wu L, Yang Y, Chen S, Zhao M, Zhu Z, Yang S, Qu Y, Ma Q, He Z, Zhou J, He Q. (2016). Long-term successional dynamics of microbial association networks in anaerobic digestion processes. Water Research, 104: 1–10

[38] Xia Y, Kong Y, Thomsen T R, Halkjaer Nielsen P. (2008). Identification and ecophysiological characterization of epiphytic protein-hydrolyzing saprospiraceae (Candidatus Epiflobacter spp.) in activated sludge. Applied and Environmental Microbiology, 74(7): 2229–2238

[39] Xiao N, Zhou A, Kempher M L, Zhou B Y, Shi Z J, Yuan M, Guo X, Wu L, Ning D, Van Nostrand J, Firestone M K, Zhou J. (2022). Disentangling direct from indirect relationships in association networks. Proceedings of the National Academy of Sciences of the United States of America, 119(2): e2109995119

[40] Xu J, Pang H L, He J G, Nan J. (2020). The effect of supporting matrix on sludge granulation under low hydraulic shear force: performance, microbial community dynamics and microorganisms migration. Science of the Total Environment, 712: 136562

[41] Ya T, Du S, Li Z, Liu S, Zhu M, Liu X, Jing Z, Hai R, Wang X. (2021). Successional dynamics of molecular ecological network of anammox microbial communities under elevated salinity. Water Research, 188: 116540

[42] Ye L, Peng C, Tang B, Wang S, Zhao K, Peng Y (2009). Determination effect of influent salinity and inhibition time on partial nitrification in a sequencing batch reactor treating saline sewage.Desalination, 246(1–3): 556–566

[43] Yuan M M, Guo X, Wu L W, Zhang Y, Xiao N J, Ning D L, Shi Z, Zhou X S, Wu L Y, Yang Y F. . (2021). Climate warming enhances microbial network complexity and stability. Nature Climate Change, 11(4): 343–348

[44] Zhang L L, Ding L L, He X M, Ma H J, Fu H M, Wang J F, Ren H Q. (2019). Effect of continuous and intermittent electric current on lignin wastewater treatment and microbial community structure in electro-microbial system. Scientific Reports, 9: 805

[45] Zhao Y, Park H D, Park J H, Zhang F, Chen C, Li X, Zhao D, Zhao F. (2016). Effect of different salinity adaptation on the performance and microbial community in a sequencing batch reactor. Bioresource Technology, 216: 808–816

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.

版权

2023 Higher Education Press