The DOI matches its Crossref record; 46 of the 46 references it cites were found in a registry or an index.
Removal of antibiotic residues, antibiotic resistant bacteria and antibiotic resistance genes in municipal wastewater by membrane bioreactor systems
Abstract
Antibiotic residues, antibiotic resistant bacteria (ARB) and antibiotic resistance genes (ARGs) are considered new classes of water contaminants due to their potential adverse effects on aquatic ecosystems and human health. This paper provides comprehensive data on the occurrences of 19 antibiotics, bacteria resistant to 10 antibiotics, and 15 ARGs in raw influent and different treatment stages of conventional activated sludge (CAS) and membrane bioreactor (MBR) systems. Seventeen out of the 19 target antibiotics were detected in raw influent with concentrations of up to ten micrograms per liter. Concentrations of antibiotics measured in the secondary effluent were much lower compared to those in the raw influent. Among the antibiotics, amoxicillin, azithromycin, ciprofloxacin, chloramphenicol, meropenem, minocycline, oxytetracycline, sulfamethazine and vancomycin had highest removal by CAS or MBR systems with median removal efficiency (RE) > 70%, while trimethoprim and lincomycin were recalcitrant in the CAS system with median RE <50%. Similarly, the target ARB and ARGs were omnipresent in the raw influent samples with average concentrations as high as 2.6 × 106 CFU/mL and 2.0 × 107 gene copies/mL, respectively. The concentrations of ARB in secondary effluent of the CAS system declined relative to the raw influent (i.e. lower than raw influent by 2-3 orders of magnitude) and no ARB were detected in the MF permeate of the MBR system. For ARGs, their concentrations in secondary effluent/MF permeate ranged from below method quantification limit (<MQL) to 104 gene copies/mL. It is noteworthy that several ARGs, i.e. blaKPC, blaNDM, blaSHV, ermB, intI1, sul1 and tetO, were still found in the MF permeate of the MBR system at average concentrations up to 103 copies/mL. In conclusion, MBR outperformed CAS in the elimination of ARB, ARGs and most target antibiotics.
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Cites
Antibiotic resistance threats in the United States, 2019
(U.S.), C. F. D. C. A. P. (2019) · doi:10.15620/cdc:82532 · Cited by 5,782
Antibiotics in the aquatic environment – A review – Part I
Kümmerer, K. (2009) · Chemosphere · doi:10.1016/j.chemosphere.2008.11.086 · Cited by 4,475
Antibiotic resistance-the need for global solutions
Laxminarayan, R., Duse, A., Wattal, C., Zaidi, A. K. M., Wertheim, H. F. L., Sumpradit, N., Vlieghe, E., Hara, G. L., Gould, I. M., Goossens, H., et al. (2013) · The Lancet Infectious Diseases · doi:10.1016/s1473-3099(13)70318-9 · Cited by 4,439
Rizzo, L., Manaia, C., Merlin, C., Schwartz, T., Dagot, C., Ploy, M. C., Michael, I., & Fatta-Kassinos, D. (2013) · Science of The Total Environment · doi:10.1016/j.scitotenv.2013.01.032 · Cited by 2,493
Tackling antibiotic resistance: the environmental framework
Berendonk, T. U., Manaia, C. M., Merlin, C., Fatta-Kassinos, D., Cytryn, E., Walsh, F., Bürgmann, H., Sørum, H., Norström, M., Pons, M.-N., et al. (2015) · Nature Reviews Microbiology · doi:10.1038/nrmicro3439 · Cited by 2,338
Tran, N. H., Reinhard, M., & Gin, K. Y.-H. (2018) · Water Research · doi:10.1016/j.watres.2017.12.029 · Cited by 1,686
Self-citationMetallo-β-Lactamases: the Quiet before the Storm?
Walsh, T. R., Toleman, M. A., Poirel, L., & Nordmann, P. (2005) · Clinical Microbiology Reviews · doi:10.1128/cmr.18.2.306-325.2005 · Cited by 1,431
Radjenović, J., Petrović, M., & Barceló, D. (2009) · Water Research · doi:10.1016/j.watres.2008.11.043 · Cited by 1,224
Antibiotic resistance genes in water environment
Zhang, X.-X., Zhang, T., & Fang, H. H. P. (2009) · Applied Microbiology and Biotechnology · doi:10.1007/s00253-008-1829-z · Cited by 998
Munir, M., Wong, K., & Xagoraraki, I. (2011) · Water Research · doi:10.1016/j.watres.2010.08.033 · Cited by 881
Cited by
Nguyen, A. Q., Vu, H. P., Nguyen, L. N., Wang, Q., Djordjevic, S. P., Donner, E., Yin, H., & Nghiem, L. D. (2021) · Science of The Total Environment · doi:10.1016/j.scitotenv.2021.146964 · Cited by 339
Majumder, A., Gupta, A. K., Ghosal, P. S., & Varma, M. (2021) · Journal of Environmental Chemical Engineering · doi:10.1016/j.jece.2020.104812 · Cited by 331
Zhao, Y., Liu, D., Huang, W., Yang, Y., Ji, M., Nghiem, L. D., Trinh, Q. T., & Tran, N. H. (2019) · Bioresource Technology · doi:10.1016/j.biortech.2019.121619 · Cited by 258
Self-citationBiochar based catalysts for the abatement of emerging pollutants: a review
Do Minh, T., Song, J., Deb, A., Cha, L., Srivastava, V., & Sillanpää, M. (2020) · Chemical Engineering Journal · doi:10.1016/j.cej.2020.124856 · Cited by 231
Burch, T. R., Newton, R. J., Kimbell, L. K., LaMartina, E. L., O'Malley, K., Thomson, S. M., Marshall, C. W., & McNamara, P. J. (2022) · Environmental Science: Water Research & Technology · doi:10.1039/d2ew00087c · Cited by 26
Metadata
- Authors
- Le, T.-H., Ng, C., Tran, N. H., Chen, H., & Gin, K. Y.-H.
- Venue
- Water Research
- Publisher
- Elsevier BV
- Published
- 2018-11
- Volume
- 145
- Pages
- 498-508
- ISSN
- 0043-1354 (ISSN-L)
- OpenAlex
- W2889084707
- Cited by
- 355
- References
- 46
- FWCI
- 11.23
- Type
- journal article
- Language
- en
- Open access
- closed
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- Le, T.-H., Ng, C., Tran, N. H., Chen, H., & Gin, K. Y.-H. (2018). Removal of antibiotic residues, antibiotic resistant bacteria and antibiotic resistance genes in municipal wastewater by membrane bioreactor systems. Water Research. https://doi.org/10.1016/j.watres.2018.08.060
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