Mitigating microbiological risks of potential pathogens carrying antibiotic resistance genes and virulence factors in receiving rivers: Benefits of wastewater treatment plant upgrade

doi:10.1007/s11783-023-1682-4

Front. Environ. Sci. Eng.

2023, Vol. 17

Issue (7) : 82 https://doi.org/10.1007/s11783-023-1682-4

RESEARCH ARTICLE

Mitigating microbiological risks of potential pathogens carrying antibiotic resistance genes and virulence factors in receiving rivers: Benefits of wastewater treatment plant upgrade

Guannan Mao^1,², Donglin Wang^1,³, Yaohui Bai¹(

), Jiuhui Qu¹

¹. Key Laboratory of Drinking Water Science and Technology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
². State Key Laboratory of Tibetan Plateau Earth System, Environment and Resources (TPESER), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China
³. University of Chinese Academy of Sciences, Beijing 100049, China

Download: PDF(2585 KB) HTML
Export: BibTeX | EndNote | Reference Manager | ProCite | RefWorks

Abstract

● Abundance of MAGs carrying ARG-VF pairs unchanged in rivers after WWTP upgrade.

● Upgrade of WWTPs significantly reduced diversity of pathogenic genera in rivers.

● Upgrade of WWTPs reduced most VF (ARG) types carried by potential pathogens in rivers.

● Upgrade of WWTPs narrowed the pathogenic host ranges of ARGs and VFs in rivers.

Wastewater treatment plants (WWTPs) with additional tertiary ultrafiltration membranes and ozonation treatment can improve water quality in receiving rivers. However, the impacts of WWTP upgrade (WWTP-UP) on pathogens carrying antibiotic resistance genes (ARGs) and virulence factors (VFs) in rivers remain poorly understood. In this study, ARGs, VFs, and their pathogenic hosts were investigated in three rivers impacted by large-scale WWTP-UP. A five-year sampling campaign covered the periods before and after WWTP-UP. Results showed that the abundance of total metagenome-assembled genomes (MAGs) containing both ARGs and VFs in receiving rivers did not decrease substantially after WWTP-UP, but the abundance of MAGs belonging to pathogenic genera that contain both ARGs and VFs (abbreviated as PAVs) declined markedly. Genome-resolved metagenomics further revealed that WWTP-UP not only reduced most types of VFs and ARGs in PAVs, but also effectively eliminated efflux pump and nutritional VFs carried by PAVs in receiving rivers. WWTP-UP narrowed the pathogenic host ranges of ARGs and VFs and mitigated the co-occurrence of ARGs and VFs in receiving rivers. These findings underline the importance of WWTP-UP for the alleviation of pathogens containing both ARGs and VFs in receiving rivers.

Keywords Wastewater treatment plant upgrade Antibiotic resistance genes (ARGs) Virulence factors (VFs) Gene co-occurrence Genome-centric analysis

Corresponding Author(s): Yaohui Bai

Issue Date: 03 February 2023

Cite this article:

Guannan Mao,Donglin Wang,Yaohui Bai, et al. Mitigating microbiological risks of potential pathogens carrying antibiotic resistance genes and virulence factors in receiving rivers: Benefits of wastewater treatment plant upgrade[J]. Front. Environ. Sci. Eng., 2023, 17(7): 82.

URL:

https://academic.hep.com.cn/fese/EN/10.1007/s11783-023-1682-4
https://academic.hep.com.cn/fese/EN/Y2023/V17/I7/82

Fig.1 Relative abundances of MAGs containing both ARGs and VFs, VFs, and ARGs in two receiving rivers before and after WWTP-UP. * and ** indicate p < 0.05 and p < 0.01, respectively.

Fig.2 Profiles of PAVs in receiving rivers before and after WWTP-UP. (a) Relative abundance of PAVs. (b) Relative abundance of different pathogenic hosts of ARGs and VFs. * and ** indicate p < 0.05 and p < 0.01, respectively. (c) PCoA of PAVs based on Bray-Curtis metrics. PERMANOVA: permutational multivariate analysis of variance.

Fig.3 Percentages of VFs (a) and ARGs (b) carried by PAVs in all receiving rivers before and after WWTP-UP. * and ** indicate p < 0.05 and p < 0.01, respectively. N.D. means not detected.

Fig.4 (a) The number of ARGs and VFs carried by pathogenic genera before and after the WWTP-UP. (b) The mapping relationship of ARGs and VFs carried by pathogenic genera before and after the WWTP-UP.

1	J Alneberg , B S Bjarnason , I de Bruijn , M Schirmer , J Quick , U Z Ijaz , L Lahti , N J Loman , A F Andersson , C Quince . (2014). Binning metagenomic contigs by coverage and composition. Nature Methods, 11(11): 1144–1146 https://doi.org/10.1038/nmeth.3103
2	J L Balcázar , J Subirats , C M Borrego . (2015). The role of biofilms as environmental reservoirs of antibiotic resistance. Frontiers in Microbiology, 6: 1216 https://doi.org/10.3389/fmicb.2015.01216
3	B K Biswal , A Mazza , L Masson , R Gehr , D Frigon . (2014). Impact of wastewater treatment processes on antimicrobial resistance genes and their co-occurrence with virulence genes in Escherichia coli. Water Research, 50: 245–253 https://doi.org/10.1016/j.watres.2013.11.047
4	X Cheng , J Xu , G Smith , N Nirmalakhandan , Y Zhang . (2021). Metagenomic profiling of antibiotic resistance and virulence removal: Activated sludge vs. Algal wastewater treatment system. Journal of Environmental Management, 295: 113129 https://doi.org/10.1016/j.jenvman.2021.113129
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 dispersal of microorganisms and genes in aquatic sediments. Applied and Environmental Microbiology, 84(5): e02168–17 https://doi.org/10.1128/AEM.02168-17
6	D Das , A Bordoloi , M P Achary , D J Caldwell , R P S Suri . (2022). Degradation and inactivation of chromosomal and plasmid encoded resistance genes/ARBs and the impact of different matrices on UV and UV/H2O2 based advanced oxidation process. Science of the Total Environment, 833: 155205 https://doi.org/10.1016/j.scitotenv.2022.155205
7	D J Eaves , V Ricci , L J V Piddock . (2004). Expression of acrB, acrF, acrD, marA, and soxS in salmonella enterica serovar typhimurium: Role in multiple antibiotic resistance. Antimicrobial Agents and Chemotherapy, 48(4): 1145–1150 https://doi.org/10.1128/AAC.48.4.1145-1150.2004
8	R I L Eggen , J Hollender , A Joss , M Schärer , C Stamm . (2014). Reducing the discharge of micropollutants in the aquatic environment: the benefits of upgrading wastewater treatment plants. Environmental Science & Technology, 48(14): 7683–7689 https://doi.org/10.1021/es500907n
9	T W Gao , K Xiao , J Zhang , W C Xue , C H Wei , X P Zhang , S Liang , X M Wang , X Huang . (2022). Techno-economic characteristics of wastewater treatment plants retrofitted from the conventional activated sludge process to the membrane bioreactor process. Frontiers of Environmental Science & Engineering, 16(4): 49 https://doi.org/10.1007/s11783-021-1483-6
10	D Gu , N Dong , Z Zheng , D Lin , M Huang , L Wang , E W C Chan , L Shu , J Yu , R Zhang , S Chen . (2018). A fatal outbreak of ST11 carbapenem-resistant hypervirulent Klebsiella pneumoniae in a Chinese hospital: a molecular epidemiological study. Lancet. Infectious Diseases, 18(1): 37–46 https://doi.org/10.1016/S1473-3099(17)30489-9
11	M Harnisz , E Kiedrzyńska , M Kiedrzyński , E Korzeniewska , M Czatzkowska , I Koniuszewska , A Jóźwik , S Szklarek , S Niestępski , Mm Zalewski . (2020). The impact of WWTP size and sampling season on the prevalence of antibiotic resistance genes in wastewater and the river system. Science of the Total Environment, 741: 140466 https://doi.org/10.1016/j.scitotenv.2020.140466
12	S J Ho Sui , A Fedynak , W W L Hsiao , M G I Langille , F S L Brinkman . (2009). The association of virulence factors with genomic islands. PLoS One, 4(12): e8094 https://doi.org/10.1371/journal.pone.0008094
13	Y Hu , X Yang , J Qin , N Lu , G Cheng , N Wu , Y Pan , J Li , L Zhu , X Wang , Z Meng , F Zhao , D Liu , J Ma , N Qin , C Xiang , Y Xiao , L Li , H Yang , J Wang , R Yang , G F Gao , J Wang , B Zhu . (2013). Metagenome-wide analysis of antibiotic resistance genes in a large cohort of human gut microbiota. Nature Communications, 4(1): 2151 https://doi.org/10.1038/ncomms3151
14	Y R Hu , T Y Zhang , L Jiang , Y Luo , S J Yao , D Zhang , K Lin , C Cui . (2019). Occurrence and reduction of antibiotic resistance genes in conventional and advanced drinking water treatment processes. Science of the Total Environment, 669: 777–784 https://doi.org/10.1016/j.scitotenv.2019.03.143
15	D Hyatt , G L Chen , P F LoCascio , M L Land , F W Larimer , L J Hauser . (2010). Prodigal: prokaryotic gene recognition and translation initiation site identification. BMC Bioinformatics, 11(1): 119 https://doi.org/10.1186/1471-2105-11-119
16	I C Iakovides , I Michael-Kordatou , N F F Moreira , A R Ribeiro , T Fernandes , M F R Pereira , O C Nunes , C M Manaia , A M T Silva , D Fatta-Kassinos . (2019). Continuous ozonation of urban wastewater: Removal of antibiotics, antibiotic-resistant Escherichia coli and antibiotic resistance genes and phytotoxicity. Water Research, 159: 333–347 https://doi.org/10.1016/j.watres.2019.05.025
17	T Jäger , N Hembach , C Elpers , A Wieland , J Alexander , C Hiller , G Krauter , T Schwartz . (2018). Reduction of antibiotic resistant bacteria during conventional and advanced wastewater treatment, and the disseminated loads released to the environment. Frontiers in Microbiology, 9: 2599 https://doi.org/10.3389/fmicb.2018.02599
18	C Jain , L Rodríguez-R , M Phillippy , A T K Konstantinidis , S Aluru . (2018). High throughput ANI analysis of 90K prokaryotic genomes reveals clear species boundaries. Nature Communications, 9(1): 5114 https://doi.org/10.1038/s41467-018-07641-9
19	Y N Jiao , H Chen , R X Gao , Y G Zhu , C Rensing . (2017). Organic compounds stimulate horizontal transfer of antibiotic resistance genes in mixed wastewater treatment systems. Chemosphere, 184: 53–61 https://doi.org/10.1016/j.chemosphere.2017.05.149
20	C Josenhans , S Suerbaum . (2002). The role of motility as a virulence factor in bacteria. International Journal of Medical Microbiology, 291(8): 605–614 https://doi.org/10.1078/1438-4221-00173
21	F Ju , B Li , L P Ma , Y B Wang , D P Huang , T Zhang . (2016). Antibiotic resistance genes and human bacterial pathogens: co-occurrence, removal, and enrichment in municipal sewage sludge digesters. Water Research, 91: 1–10 https://doi.org/10.1016/j.watres.2015.11.071
22	D W D Kang , F Li , E Kirton , A Thomas , R Egan , H An , Z Wang . (2019). MetaBAT 2: an adaptive binning algorithm for robust and efficient genome reconstruction from metagenome assemblies. PeerJ, 7: e7359 https://doi.org/10.7717/peerj.7359
23	J W Keum , H Bermudez . (2009). Enhanced resistance of DNA nanostructures to enzymatic digestion. Chemical Communications (Cambridge), 7(45): 7036–7038 https://doi.org/10.1039/b917661f
24	T H Le , C Ng , N Tran , H Chen , K Y Gin . (2018). Removal of antibiotic residues, antibiotic resistant bacteria and antibiotic resistance genes in municipal wastewater by membrane bioreactor systems. Water Research, 145: 498–508 https://doi.org/10.1016/j.watres.2018.08.060
25	H Leclerc , A Moreau . (2002). Microbiological safety of natural mineral water. FEMS Microbiology Reviews, 26(2): 207–222 https://doi.org/10.1111/j.1574-6976.2002.tb00611.x
26	L N Lemos , R V Pereira , R B Quaggio , L F Martins , L M S Moura , A R da Silva , L P Antunes , A M da Silva , J C Setubal . (2017). Genome-centric analysis of a thermophilic and cellulolytic bacterial consortium derived from composting. Frontiers in Microbiology, 8: 644 https://doi.org/10.3389/fmicb.2017.00644
27	D Li , C M Liu , R Luo , K Sadakane , T W Lam . (2015). MEGAHIT: an ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph. Bioinformatics (Oxford, England), 31(10): 1674–1676 https://doi.org/10.1093/bioinformatics/btv033
28	J Liang , G Mao , X Yin , L Ma , L Liu , Y Bai , T Zhang , J Qu . (2020). Identification and quantification of bacterial genomes carrying antibiotic resistance genes and virulence factor genes for aquatic microbiological risk assessment. Water Research, 168: 115160 https://doi.org/10.1016/j.watres.2019.115160
29	Z J Lin , Z C Zhou , L Zhu , L X Meng , X Y Shuai , Y J Sun , H Chen . (2021). Behavior of antibiotic resistance genes in a wastewater treatment plant with different upgrading processes. Science of the Total Environment, 771: 144814 https://doi.org/10.1016/j.scitotenv.2020.144814
30	B Liu , D D Zheng , Q Jin , L H Chen , J Yang . (2019). VFDB 2019: a comparative pathogenomic platform with an interactive web interface. Nucleic Acids Research, 47(D1): D687–692 https://doi.org/10.1093/nar/gky1080
31	F Lüddeke , S Heß , C Gallert , J Winter , H Güde , H Löffler . (2015). Removal of total and antibiotic resistant bacteria in advanced wastewater treatment by ozonation in combination with different filtering techniques. Water Research, 69: 243–251 https://doi.org/10.1016/j.watres.2014.11.018
32	H J Majeed , M V Riquelme , B C Davis , S Gupta , L Angeles , D S Aga , E Garner , A Pruden , P J Vikesland . (2021). Evaluation of metagenomic-enabled antibiotic resistance surveillance at a conventional wastewater treatment plant. Frontiers in Microbiology, 12: 657954 https://doi.org/10.3389/fmicb.2021.657954
33	D Q Mao , Y Luo , J Mathieu , Q Wang , L Feng , Q H Mu , C Y Feng , P J J Alvarez . (2014). Persistence of extracellular DNA in river sediment facilitates antibiotic resistance gene propagation. Environmental Science & Technology, 48(1): 71–78 https://doi.org/10.1021/es404280v
34	A Q Nguyen , H P Vu , L N Nguyen , Q L Wang , S P Djordjevic , E Donner , H B Yin , L D Nghiem . (2021). Monitoring antibiotic resistance genes in wastewater treatment: Current strategies and future challenges. Science of the Total Environment, 783: 146964 https://doi.org/10.1016/j.scitotenv.2021.146964
35	Y Pan , J Zeng , L Li , J Yang , Z Tang , W Xiong , Y Li , S Chen , Z Zeng . (2020). Coexistence of antibiotic resistance genes and virulence factors deciphered by large-scale complete genome analysis. mSystems, 5(3): e00821–19 https://doi.org/10.1128/mSystems.00821-19
36	D H Parks , M Chuvochina , D W Waite , C Rinke , A Skarshewski , P A Chaumeil , P Hugenholtz . (2018). A standardized bacterial taxonomy based on genome phylogeny substantially revises the tree of life. Nature Biotechnology, 36(10): 996–1004 https://doi.org/10.1038/nbt.4229
37	R Penttinen , H Kinnula , A Lipponen , J K Bamford , L R Sundberg . (2016). High nutrient concentration can induce virulence factor expression and cause higher virulence in an environmentally transmitted pathogen. Microbial Ecology, 72(4): 955–964 https://doi.org/10.1007/s00248-016-0781-1
38	M Piotrowska , M Popowska . (2014). The prevalence of antibiotic resistance genes among aeromonas species in aquatic environments. Annals of Microbiology, 64(3): 921–934 https://doi.org/10.1007/s13213-014-0911-2
39	M V Riquelme Breazeal , J T Novak , P J Vikesland , A Pruden . (2013). Effect of wastewater colloids on membrane removal of antibiotic resistance genes. Water Research, 47(1): 130–140 https://doi.org/10.1016/j.watres.2012.09.044
40	C Stamm , K Rasanen , F J Burdon , F Altermatt , J Jokela , A Joss , M Ackermann , R I L Eggen . (2016). Unravelling the impacts of micropollutants in aquatic ecosystems: interdisciplinary studies at the interface of large-scale ecology. Advances in Ecological Research, 55: 183–223 https://doi.org/10.1016/bs.aecr.2016.07.002
41	C Stange , J P S Sidhu , S Toze , A Tiehm . (2019). Comparative removal of antibiotic resistance genes during chlorination, ozonation, and UV treatment. International Journal of Hygiene and Environmental Health, 222(3): 541–548 https://doi.org/10.1016/j.ijheh.2019.02.002
42	D Su , W Ben , B W Strobel , Z Qiang . (2021). Impacts of wastewater treatment plant upgrades on the distribution and risks of pharmaceuticals in receiving rivers. Journal of Hazardous Materials, 406: 124331 https://doi.org/10.1016/j.jhazmat.2020.124331
43	J Y Tang , Y Q Bu , X X Zhang , K L Huang , X W He , L Ye , Z J Shan , H Q Ren . (2016). Metagenomic analysis of bacterial community composition and antibiotic resistance genes in a wastewater treatment plant and its receiving surface water. Ecotoxicology and Environmental Safety, 132: 260–269 https://doi.org/10.1016/j.ecoenv.2016.06.016
44	R D S Tavares , M Tacao , A S Figueiredo , A S Duarte , F Esposito , N Lincopan , C M Manaia , I Henriques . (2020). Genotypic and phenotypic traits of blaCTX-M-carrying Escherichia coli strains from an UV-C-treated wastewater effluent. Water Research, 184: 116079 https://doi.org/10.1016/j.watres.2020.116079
45	A R Varela , C M Manaia . (2013). Human health implications of clinically relevant bacteria in wastewater habitats. Environmental Science and Pollution Research International, 20(6): 3550–3569 https://doi.org/10.1007/s11356-013-1594-0
46	H Wang , J Xu , W Tang , H Li , S Xia , J Zhao , W X Zhang , Y Yang . (2019). Removal efficacy of opportunistic pathogens and bacterial community dynamics in two drinking water treatment trains. Small, 15: 1804436
47	Q Wang , J Liang , C Zhao , Y Bai , R Liu , H Liu , J Qu . (2020). Wastewater treatment plant upgrade induces the receiving river retaining bioavailable nitrogen sources. Environmental Pollution, 263: 114478 https://doi.org/10.1016/j.envpol.2020.114478
48	Y W Wu , B A Simmons , S W Singer . (2016). MaxBin 2.0: an automated binning algorithm to recover genomes from multiple metagenomic datasets. Bioinformatics (Oxford, England), 32(4): 605–607 https://doi.org/10.1093/bioinformatics/btv638
49	L Yang , Q X Wen , Z Q Chen , R Duan , P Yang . (2019). Impacts of advanced treatment processes on elimination of antibiotic resistance genes in a municipal wastewater treatment plant. Frontiers of Environmental Science & Engineering, 13(3): 32 https://doi.org/10.1007/s11783-019-1116-5
50	X Yin , X T Jiang , B Chai , L Li , Y Yang , J R Cole , J M Tiedje , T Zhang . (2018). ARGs-OAP v2.0 with an expanded SARG database and Hidden Markov Models for enhancement characterization and quantification of antibiotic resistance genes in environmental metagenomes. Bioinformatics (Oxford, England), 34(13): 2263–2270 https://doi.org/10.1093/bioinformatics/bty053
51	Q B Yuan , Y M Huang , W B Wu , P Zuo , N Hu , Y Z Zhou , P J J Alvarez . (2019). Redistribution of intracellular and extracellular free & adsorbed antibiotic resistance genes through a wastewater treatment plant by an enhanced extracellular DNA extraction method with magnetic beads. Environment International, 131: 104986 https://doi.org/10.1016/j.envint.2019.104986
52	B Zhang , Y Xia , X H Wen , X H Wang , Y F Yang , J Z Zhou , Y Zhang . (2016). The composition and spatial patterns of bacterial virulence factors and antibiotic resistance genes in 19 wastewater treatment plants. PLoS One, 11(12): e0167422 https://doi.org/10.1371/journal.pone.0167422
53	J Zhang , D Yu , L Dian , Y Hai , Y Xin , Y Wei . (2022). Metagenomics insights into the profiles of antibiotic resistome in combined sewage overflows from reads to metagenome assembly genomes. Journal of Hazardous Materials, 429: 128277 https://doi.org/10.1016/j.jhazmat.2022.128277
54	J Zhao , B Li , P Lv , J Hou , Y Qiu , X Huang . (2022). 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]

FSE-22128-OF-MGN_suppl_1

Download

[1]	Lian Yang, Qinxue Wen, Zhiqiang Chen, Ran Duan, Pan Yang. Impacts of advanced treatment processes on elimination of antibiotic resistance genes in a municipal wastewater treatment plant[J]. Front. Environ. Sci. Eng., 2019, 13(3): 32-.
[2]	Menglu Zhang, Sheng Chen, Xin Yu, Peter Vikesland, Amy Pruden. Degradation of extracellular genomic, plasmid DNA and specific antibiotic resistance genes by chlorination[J]. Front. Environ. Sci. Eng., 2019, 13(3): 38-.

Viewed

Full text

Abstract

Cited

Shared

Discussed