Impacts of electrochemical disinfection on the viability and structure of the microbiome in secondary effluent water

doi:10.1007/s11783-024-1818-1

Front. Environ. Sci. Eng.

2024, Vol. 18

Issue (5) : 58 https://doi.org/10.1007/s11783-024-1818-1

Impacts of electrochemical disinfection on the viability and structure of the microbiome in secondary effluent water

Marvin Yeung¹, Lan Tian¹, Yuhong Liu^1,², Hairong Wang^1,², Jinying Xi¹(

)

¹. Environmental Simulation and Pollution Control State Key Joint Laboratory, School of Environment, Tsinghua University, Beijing 100084, China
². Graduate School at Shenzhen, Tsinghua University, Shenzhen 518055, China

Download: PDF(3828 KB) HTML
Export: BibTeX | EndNote | Reference Manager | ProCite | RefWorks

Abstract

● ECD decreased cell count by five orders of magnitude after 150 s of disinfection.

● Biodiversity was suppressed, but a higher level of evenness & stability is retained.

● Pathogenic and stress-tolerant taxa increased while biofilm-forming taxa decreased.

● Co-occurrence networks show ECD effectively destabilized the microbiome.

● Membrane synthesis and organic compound degrading functions are enriched after ECD.

Electrochemical disinfection (ECD) is a promising disinfection technique for wastewater reclamation; however, the impacts of ECD on the microbiome in secondary effluent wastewater remain unknown. In this study, Propidium monoazide-qPCR (PMA-qPCR) and the plate count method were used to evaluate the inactivation performance, and the PMA-16S rRNA gene sequences of living cells were targeted to study the microbiome. A discrepancy was found between PMA-qPCR and the plate count method in the evaluation of cell count, with increases of 1.5 to 2.2 orders of magnitude in the disinfection rate after 150 s of disinfection. However, the cell count recovered and occasionally exceeded original levels within 3 d after disinfection. Biodiversity was suppressed after ECD, but the microbiome after 150 s disinfection retained a higher level of evenness and stability in the community with a median Shannon index (> 3.7). Pathogenic bacteria remained high in relative abundance even after 150 s of 25 V disinfection, but the biofilm-forming population was effectively suppressed by ECD. The co-occurrence network revealed a centralized and fragile network as disinfection persisted, demonstrating the destabilizing effects of ECD on the microbiome. Functional pathways for cell membrane synthesis and organic compound degradation were enriched after ECD. The reaction of the microbiome after ECD was similar to other disinfection techniques in terms of community structure.

Keywords Electrochemical disinfection Secondary effluent Microbiome

Corresponding Author(s): Jinying Xi

Issue Date: 26 January 2024

Cite this article:

Marvin Yeung,Lan Tian,Yuhong Liu, et al. Impacts of electrochemical disinfection on the viability and structure of the microbiome in secondary effluent water[J]. Front. Environ. Sci. Eng., 2024, 18(5): 58.

URL:

https://academic.hep.com.cn/fese/EN/10.1007/s11783-024-1818-1
https://academic.hep.com.cn/fese/EN/Y2024/V18/I5/58

Tab.1 Water quality index of the original water sample before disinfection

Fig.1 The inactivation rate and residual chlorine concentration with different disinfection times.

Fig.2 Bacterial concentration before and after disinfection.

Fig.3 The change of community structure with different disinfection times at (a) phyla level, (b) class level, and (c) order level.

Fig.4 Alpha diversity indexes of samples under increasing disinfection time. (a) Observed OTU count, (b) Shannon index, (c) Simpson index.

Fig.5 Topological networks of bacterial communities in increasing disinfection time, grouped (a) 0–50 s network, (b) 100–150 s network. The color of nodes represent phylum, the size represents betweenness, edge color represents positive and negative correlations.

Fig.6 Predicted functional and morphological traits of the microbiome.

Fig.7 MetaCyc pathways highly differentiated before and after ECD.

1	M Bastian , S Heymann , M Jacomy . (2009). Gephi: an open source software for exploring and manipulating networks. International AAAI Conference on Weblogs and Social Media, 3(1): 361–362 https://doi.org/10.1609/icwsm.v3i1.13937
2	B J Callahan , P J Mcmurdie , M J Rosen , A W Han , A J A Johnson , S P Holmes . (2016). Dada2: high-resolution sample inference from illumina amplicon data. Nature Methods, 13(7): 581–583 https://doi.org/10.1038/nmeth.3869
3	P F Chen , R J Zhang , S B Huang , J H Shao , B Cui , Z L Du , L Xue , N Zhou , B Hou , C Lin . (2020). UV dose effects on the revival characteristics of microorganisms in darkness after UV disinfection: evidence from a pilot study. Science of the Total Environment, 713: 136582 https://doi.org/10.1016/j.scitotenv.2020.136582
4	T H Chiao , T M Clancy , A Pinto , C Xi , L Raskin . (2014). Differential resistance of drinking water bacterial populations to monochloramine disinfection. Environmental Science & Technology, 48(7): 4038–4047 https://doi.org/10.1021/es4055725
5	B T T Chu , M L Petrovich , A Chaudhary , D Wright , B Murphy , G Wells , R Poretsky . (2018). Metagenomics reveals the impact of wastewater treatment plants on the di spersal of microorganisms and genes in aquatic sediments. Applied and Environmental Microbiology, 84(5): e02168 https://doi.org/10.1128/AEM.02168-17
6	Y Deng , Y Jiang , Y Yang , Z He , F Luo , J Zhou . (2012). Molecular ecological network analyses. BMC Bioinformatics, 13: 113 https://doi.org/10.1186/1471-2105-13-113
7	T Z DeSantis , P Hugenholtz , N Larsen , M Rojas , E L Brodie , K Keller , T Huber , D Dalevi , P Hu , G L Andersen . (2006). Greengenes, a Chimera-checked 16S rRNA gene database and workbench compatible with ARB. Applied and Environmental Microbiology, 72(7): 5069–5072 https://doi.org/10.1128/AEM.03006-05
8	G M Douglas , V J Maffei , J R Zaneveld , S N Yurgel , J R Brown , C M Taylor , C Huttenhower , M G I Langille . (2020). PICRUSt2 for prediction of metagenome functions. Nature Biotechnology, 38(6): 685–688 https://doi.org/10.1038/s41587-020-0548-6
9	A D Fernandes , J M Macklaim , T G Linn , G Reid , G B Gloor . (2013). ANOVA-like differential gene expression analysis of single-organism and Meta-RNA-Seq. PLoS One, 8(7): e67019 https://doi.org/10.1371/journal.pone.0067019
10	M J FiguerasR (2014) Beaz-Hidalgo. Encyclopedia of Food Microbiology. 2nd ed. Cambridge: Academic Press
11	M Glick , A E Klon , P Acklin , J W Davies . (2004). Enrichment of extremely noisy high-throughput screening data using a naive Bayes classifier. SLAS Discovery, 9(1): 32–36 https://doi.org/10.1177/1087057103260590
12	V Gomez-Alvarez , H Liu , J G Pressman , D G Wahman . (2021). Metagenomic profile of microbial communities in a drinking water storage tank sediment after sequential exposure to monochloramine, free chlorine, and monochloramine. ACS ES&T Water, 1(5): 1283–1294 https://doi.org/10.1021/acsestwater.1c00016
13	B Guo, L Zhang, H Sun, M Gao, N Yu, Q Zhang, A Mou, Y Liu (2022). Microbial co-occurrence network topological properties link with reactor parameters and reveal importance of low-abundance genera. npj Biofilms & Microbiomes, 8: 3
14	S Hand , R D Cusick . (2021). Electrochemical disinfection in water and wastewater treatment: identifying impacts of water quality and operating conditions on performance. Environmental Science & Technology, 55(6): 3470–3482 https://doi.org/10.1021/acs.est.0c06254
15	V Hauryliuk , G C Atkinson , K S Murakami , T Tenson , K Gerdes . (2015). Recent functional insights into the role of (p)ppGpp in bacterial physiology. Nature Reviews. Microbiology, 13(5): 298–309 https://doi.org/10.1038/nrmicro3448
16	X Huang , Y Qu , C A Cid , C Finke , M R Hoffmann , K Lim , S C Jiang . (2016). Electrochemical disinfection of toilet wastewater using wastewater electrolysis cell. Water Research, 92: 164–172 https://doi.org/10.1016/j.watres.2016.01.040
17	J Jeong , J Y Kim , J Yoon . (2006). The role of reactive oxygen species in the electrochemical inactivation of microorganisms. Environmental Science & Technology, 40(19): 6117–6122 https://doi.org/10.1021/es0604313
18	I Kauser , M Ciesielski , R S Poretsky . (2019). Ultraviolet disinfection impacts the microbial community composition and function of treated wastewater effluent and the receiving urban river. PeerJ, 7: e7455 https://doi.org/10.7717/peerj.7455
19	J A Klappenbach , P R Saxman , J R Cole , T M Schmidt . (2001). rrndb: the ribosomal RNA operon copy number database. Nucleic Acids Research, 29(1): 181–184 https://doi.org/10.1093/nar/29.1.181
20	Y Liao , M Tang , M Li , P Shi , A Li , Y Zhang , Y Pan . (2023). Control strategies for disinfection byproducts by ion exchange resin, nanofiltration and their sequential combination. Frontiers of Environmental Science & Engineering, 17(10): 125 https://doi.org/10.1007/s11783-023-1725-x
21	B Ma , Y Wang , S Ye , S Liu , E Stirling , J A Gilbert , K Faust , R Knight , J K Jansson , C Cardona . et al.. (2020). Earth microbial co-occurrence network reveals interconnection pattern across microbiomes. Microbiome, 8(1): 82 https://doi.org/10.1186/s40168-020-00857-2
22	M Martin . (2011). Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet.Journal, 17(1): 10–12 https://doi.org/10.14806/ej.17.1.200
23	C A Martínez-Huitle , E Brillas . (2021). A critical review over the electrochemical disinfection of bacteria in synthetic and real wastewaters using a boron-doped diamond anode. Current Opinion in Solid State and Materials Science, 25(4): 100926 https://doi.org/10.1016/j.cossms.2021.100926
24	P J McMurdie , S Holmes . (2013). phyloseq: an R Package for reproducible interactive analysis and graphics of microbiome census data. PLoS One, 8(4): e61217 https://doi.org/10.1371/journal.pone.0061217
25	L Mezule , M Reimanis , V Krumplevska , J Ozolins , T Juhna . (2014). Comparing electrochemical disinfection with chlorination for inactivation of bacterial spores in drinking water. Water Science and Technology: Water Supply, 14(1): 158–164 https://doi.org/10.2166/ws.2013.182
26	B Mundy , B Kuhnel , G Hunter , R Jarnis , D Funk , S Walker , N Burns , J Drago , W Nezgod , J Huang . et al.. (2018). A review of ozone systems costs for municipal applications. Ozone: Science & Engineering, 40(4): 266–274 https://doi.org/10.1080/01919512.2018.1467187
27	A Nocker , P Sossa-Fernandez , M D Burr , A K Camper . (2007). Use of propidium monoazide for live/dead distinction in microbial ecology. Applied Environmenal Microbiology, 73(16): 5111–7 https://doi.org/10.1128/AEM.02987-06
28	Y C Pang , J Y Xi , Y Xu , Z Y Huo , H Y Hu . (2016). Shifts of live bacterial community in secondary effluent by chlorine disinfection revealed by Miseq high-throughput sequencing combined with propidium monoazide treatment. Applied Microbiology and Biotechnology, 100(14): 6435–6446 https://doi.org/10.1007/s00253-016-7452-5
29	J Pasqualino , M Meneses , F Castells . (2011). The carbon footprint and energy consumption of beverage packaging selection and disposal. Journal of Food Engineering, 103(4): 357–365 https://doi.org/10.1016/j.jfoodeng.2010.11.005
30	M H Phe , M Dossot , H Guilloteau , J C Block . (2005). Nucleic acid fluorochromes and flow cytometry prove useful in assessing the effect of chlorination on drinking water bacteria. Water Research, 39(15): 3618–3628 https://doi.org/10.1016/j.watres.2005.06.002
31	S Potgieter , Z Dai , M Havenga , S Vosloo , M Sigudu , A Pinto , S Venter . (2021). Reproducible microbial community dynamics of two drinking water systems treating similar source waters. ACS ES&T Water, 1(7): 1617–1627 https://doi.org/10.1021/acsestwater.1c00093
32	C Quast , E Pruesse , P Yilmaz , J Gerken , T Schweer , P Yarza , J Peplies , F O Glöckner . (2012). The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Research, 41(D1): D590–D596 https://doi.org/10.1093/nar/gks1219
33	M K Ramseier , U Von Gunten , P Freihofer , F Hammes . (2011). Kinetics of membrane damage to high (HNA) and low (LNA) nucleic acid bacterial clusters in drinking water by ozone, chlorine, chlorine dioxide, monochloramine, ferrate(VI), and permanganate. Water Research, 45(3): 1490–1500 https://doi.org/10.1016/j.watres.2010.11.016
34	T Rognes , T Flouri , B Nichols , C Quince , F Mahé . (2016). VSEARCH: a versatile open source tool for metagenomics. PeerJ, 4: e2584 https://doi.org/10.7717/peerj.2584
35	L A Salas , M Bustamante , J R Gonzalez , E Gracia-Lavedan , V Moreno , M Kogevinas , C M Villanueva . (2015). DNA methylation levels and long-term trihalomethane exposure in drinking water: an epigenome-wide association study. Epigenetics, 10(7): 650–661 https://doi.org/10.1080/15592294.2015.1057672
36	K M Scow, E Schwartz, M J Johnson, J L Macalady (2001). Measurement of Microbial Biodiversity. Amsterdam: Elsevier
37	Z Q Shao , W Seffens , W Mulbry , R M Behki . (1995). Cloning and expression of the S-triazine hydrolase gene (trzA) from Rhodococcus corallinus and development of Rhodococcus recombinant strains capable of dealkylating and dechlorinating the herbicide atrazine. Journal of Bacteriology, 177(20): 5748–5755 https://doi.org/10.1128/jb.177.20.5748-5755.1995
38	S K Shukla, K Atif, T S Rao (2021). Microbial and Natural Macromolecules. London: Academic Press
39	S Sun , R B Jones , A A Fodor . (2020). Inference-based accuracy of metagenome prediction tools varies across sample types and functional categories. Microbiome, 8(1): 46 https://doi.org/10.1186/s40168-020-00815-y
40	G Tchobanoglous, F L Burton, D H Stensel (2003). Wastewater Engineering: Treatment, and Reuse, 4th ed. New York: Metcalf & Eddy, Inc., McGraw-Hill Book Company
41	T Ward, J Larson, J Meulemans, B Hillmann, J Lynch, D Sidiropoulos, J R Spear, G Caporaso, R Blekhman, R Knight, et al. (2017). BugBase predicts organism-level microbiome phenotypes. biorxiv, doi: https://doi.org/10.1101/133462 10.1101/133462
42	D M Warsinger , S Chakraborty , E W Tow , M H Plumlee , C Bellona , S Loutatidou , L Karimi , A M Mikelonis , A Achilli , A Ghassemi . et al.. (2018). A review of polymeric membranes and processes for potable water reuse. Progress in Polymer Science, 81: 209–237 https://doi.org/10.1016/j.progpolymsci.2018.01.004
43	M A Webber , L J V Piddock . (2003). The importance of efflux pumps in bacterial antibiotic resistance. Journal of Antimicrobial Chemotherapy, 51(1): 9–11 https://doi.org/10.1093/jac/dkg050
44	(2003) WHO. Emerging Issues in Water and Infectious Disease. Washington, DC: World Health Organization
45	D Xiao , Z Lyu , S Chen , Y Huo , W Fan , M Huo . (2022). Tracking Cryptosporidium in urban wastewater treatment plants in a cold region: occurrence, species and infectivity. Frontiers of Environmental Science & Engineering, 16(9): 112 https://doi.org/10.1007/s11783-022-1533-8
46	M Yeung , P Saingam , Y Xu , J Xi . (2021). Low-dosage ozonation in gas-phase biofilter promotes community diversity and robustness. Microbiome, 9(1): 14 https://doi.org/10.1186/s40168-020-00944-4
47	H Zhao , C H Huang , C Zhong , P Du , P Sun . (2022a). Enhanced formation of trihalomethane disinfection byproducts from halobenzoquinones under combined UV/chlorine conditions. Frontiers of Environmental Science & Engineering, 16(6): 76 https://doi.org/10.1007/s11783-021-1510-7
48	J Zhao , B Li , P Lv , J Hou , Y Qiu , X Huang . (2022b). Distribution of antibiotic resistance genes and their association with bacteria and viruses in decentralized sewage treatment facilities. Frontiers of Environmental Science & Engineering, 16(3): 35 https://doi.org/10.1007/s11783-021-1469-4

[1]	Carlos O. Lomeli-Ortega, Mingming Sun, José Luis Balcázar. Unraveling the interaction between soil microbiomes and their potential for restoring polluted soils[J]. Front. Environ. Sci. Eng., 2024, 18(8): 104-.
[2]	Shan-Shan Yang, Wei-Min Wu, Federica Bertocchini, Mark Eric Benbow, Suja P. Devipriya, Hyung Joon Cha, Bo-Yu Peng, Meng-Qi Ding, Lei He, Mei-Xi Li, Chen-Hao Cui, Shao-Nan Shi, Han-Jun Sun, Ji-Wei Pang, Defu He, Yalei Zhang, Jun Yang, Deyi Hou, De-Feng Xing, Nan-Qi Ren, Jie Ding, Craig S. Criddle. Radical innovation breakthroughs of biodegradation of plastics by insects: history, present and future perspectives[J]. Front. Environ. Sci. Eng., 2024, 18(6): 78-.
[3]	Xin Tang, Yin Ye, Chunlin Wang, Bingqian Wang, Zemin Qin, Cui Li, Yanlong Chen, Yuheng Wang, Zhiling Li, Miao Lv, Aijie Wang, Fan Chen. Microbial-driven ectopic uranium extraction with net electrical energy production[J]. Front. Environ. Sci. Eng., 2024, 18(1): 4-.
[4]	María del Carmen Calderón-Ezquerro, Elizabeth Selene Gómez-Acata, Carolina Brunner-Mendoza. Airborne bacteria associated with particulate matter from a highly urbanised metropolis: A potential risk to the population’s health[J]. Front. Environ. Sci. Eng., 2022, 16(9): 120-.
[5]	Bingdi Liu, Lin Zhang, Jason H. Knouft, Fangqiong Ling. Meter-scale variation within a single transect demands attention to taxon accumulation curves in riverine microbiome studies[J]. Front. Environ. Sci. Eng., 2022, 16(5): 64-.
[6]	Liu Cao, Lu Yang, Clifford S. Swanson, Shuai Li, Qiang He. Comparative analysis of impact of human occupancy on indoor microbiomes[J]. Front. Environ. Sci. Eng., 2021, 15(5): 89-.
[7]	Shuai Li, Zhiyao Yang, Da Hu, Liu Cao, Qiang He. Understanding building-occupant-microbiome interactions toward healthy built environments: A review[J]. Front. Environ. Sci. Eng., 2021, 15(4): 65-.
[8]	Xinshu Liu, Xiaoman Su, Sijie Tian, Yue Li, Rongfang Yuan. Mechanisms for simultaneous ozonation of sulfamethoxazole and natural organic matters in secondary effluent from sewage treatment plant[J]. Front. Environ. Sci. Eng., 2021, 15(4): 75-.
[9]	Bin Liang, Deyong Kong, Mengyuan Qi, Hui Yun, Zhiling Li, Ke Shi, E Chen, Alisa S. Vangnai, Aijie Wang. Anaerobic biodegradation of trimethoprim with sulfate as an electron acceptor[J]. Front. Environ. Sci. Eng., 2019, 13(6): 84-.

Viewed

Full text

Abstract

Cited

Shared

Discussed