Genome-Resolved Metagenomics and Antibiotic Resistance Genes Analysis in Reclaimed Water Distribution Systems

Changzhi Wang, Pei-Ying Hong

Research output: Contribution to journalArticlepeer-review

6 Scopus citations


Water reuse is increasingly pursued to alleviate global water scarcity. However, the wastewater treatment process does not achieve full removal of biological contaminants from wastewater, hence microorganisms and their genetic elements can be disseminated into the reclaimed water distribution systems (RWDS). In this study, reclaimed water samples are investigated via metagenomics to assess their bacterial diversity, metagenome-assembled genomes (MAGs) and antibiotic resistance genes (ARGs) at both point of entry (POE) and point of use (POU) in 3 RWDS. The number of shared bacterial orders identified by metagenome was higher at the POE than POU among the three sites, indicating that specific conditions in RWDS can cause further differentiation in the microbial communities at the end of the distribution system. Two bacterial orders, namely Rhizobiales and Sphingomonadales, had high replication rates in two of the examined RWDS (i.e., site A and B), and were present in higher relative abundance in POU than at POE. In addition, MAG and ARG relative abundance exhibited a strong correlation (R2 = 0.58) in POU, indicating that bacteria present in POU may have a high incidence of ARG. Specifically, resistance genes associated with efflux pump mechanisms (e.g., adeF and qacH) increased in its relative abundance from POU to POE at two of the RWDS (i.e., site A and B). When correlated with the water quality data that suggests a significantly lower dissolved organic carbon (DOC) concentration at site D than the other two RWDS, the metagenomic data suggest that low DOC is needed to maintain the biological stability of reclaimed water along the distribution network.
Original languageEnglish (US)
Pages (from-to)3477
Issue number12
StatePublished - Dec 10 2020

Bibliographical note

KAUST Repository Item: Exported on 2020-12-14
Acknowledged KAUST grant number(s): BAS/1/1033-01-01
Acknowledgements: This research was funded by KAUST baseline funding BAS/1/1033-01-01 awarded to P.-Y. Hong.


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