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Article: Tracking antibiotic resistome during wastewater treatment using high throughput quantitative PCR

TitleTracking antibiotic resistome during wastewater treatment using high throughput quantitative PCR
Authors
Issue Date2018
Citation
Environment International, 2018, v. 117, p. 146-153 How to Cite?
AbstractWastewater treatment plants (WWTPs) contain diverse antibiotic resistance genes (ARGs), and thus are considered as a major pathway for the dissemination of these genes into the environments. However, comprehensive evaluations of ARGs dynamic during wastewater treatment process lack extensive investigations on a broad spectrum of ARGs. Here, we investigated the dynamics of ARGs and bacterial community structures in 114 samples from eleven Chinese WWTPs using high-throughput quantitative PCR and 16S rRNA-based Illumina sequencing analysis. Significant shift of ARGs profiles was observed and wastewater treatment process could significantly reduce the abundance and diversity of ARGs, with the removal of ARGs concentration by 1–2 orders of magnitude. Whereas, a considerable number of ARGs were detected and enriched in effluents compared with influents. In particular, seven ARGs mainly conferring resistance to beta-lactams and aminoglycosides and three mobile genetic elements persisted in all WWTPs samples after wastewater treatment. ARGs profiles varied with wastewater treatment processes, seasons and regions. This study tracked the footprint of ARGs during wastewater treatment process, which would support the assessment on the spread of ARGs from WWTPs and provide data for identifying management options to improve ARG mitigation in WWTPs.
Persistent Identifierhttp://hdl.handle.net/10722/294028
ISSN
2019 Impact Factor: 7.577
2015 SCImago Journal Rankings: 2.684

 

DC FieldValueLanguage
dc.contributor.authorAn, X-
dc.contributor.authorSu, J-
dc.contributor.authorLi, B-
dc.contributor.authorOuyang, W-
dc.contributor.authorZhao, Y-
dc.contributor.authorChen, Q-
dc.contributor.authorCui, L-
dc.contributor.authorChen, H-
dc.contributor.authorGillings, MR-
dc.contributor.authorZhang, T-
dc.contributor.authorZhu, Y-
dc.date.accessioned2020-11-23T08:25:19Z-
dc.date.available2020-11-23T08:25:19Z-
dc.date.issued2018-
dc.identifier.citationEnvironment International, 2018, v. 117, p. 146-153-
dc.identifier.issn0160-4120-
dc.identifier.urihttp://hdl.handle.net/10722/294028-
dc.description.abstractWastewater treatment plants (WWTPs) contain diverse antibiotic resistance genes (ARGs), and thus are considered as a major pathway for the dissemination of these genes into the environments. However, comprehensive evaluations of ARGs dynamic during wastewater treatment process lack extensive investigations on a broad spectrum of ARGs. Here, we investigated the dynamics of ARGs and bacterial community structures in 114 samples from eleven Chinese WWTPs using high-throughput quantitative PCR and 16S rRNA-based Illumina sequencing analysis. Significant shift of ARGs profiles was observed and wastewater treatment process could significantly reduce the abundance and diversity of ARGs, with the removal of ARGs concentration by 1–2 orders of magnitude. Whereas, a considerable number of ARGs were detected and enriched in effluents compared with influents. In particular, seven ARGs mainly conferring resistance to beta-lactams and aminoglycosides and three mobile genetic elements persisted in all WWTPs samples after wastewater treatment. ARGs profiles varied with wastewater treatment processes, seasons and regions. This study tracked the footprint of ARGs during wastewater treatment process, which would support the assessment on the spread of ARGs from WWTPs and provide data for identifying management options to improve ARG mitigation in WWTPs.-
dc.languageeng-
dc.relation.ispartofEnvironment International-
dc.titleTracking antibiotic resistome during wastewater treatment using high throughput quantitative PCR-
dc.typeArticle-
dc.identifier.emailZhang, T: zhangt@hkucc.hku.hk-
dc.identifier.authorityZhang, T=rp00211-
dc.identifier.doi10.1016/j.envint.2018.05.011-
dc.identifier.hkuros319354-
dc.identifier.volume117-
dc.identifier.spage146-
dc.identifier.epage153-

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