Toward shotgun metagenomic approaches for microbial source tracking sewage spills based on laboratory mesocosms.

Metagenomics Microbial ecology Sewage collection systems Source tracking Wastewater Water quality

Journal

Water research
ISSN: 1879-2448
Titre abrégé: Water Res
Pays: England
ID NLM: 0105072

Informations de publication

Date de publication:
15 Feb 2022
Historique:
received: 04 10 2021
revised: 17 12 2021
accepted: 18 12 2021
pubmed: 4 1 2022
medline: 27 1 2022
entrez: 3 1 2022
Statut: ppublish

Résumé

Little is known about the genomic diversity of the microbial communities associated with raw municipal wastewater (sewage), including whether microbial populations specific to sewage exist and how such populations could be used to improve source attribution and apportioning in contaminated waters. Herein, we used the influent of three wastewater treatment plants in Atlanta, Georgia (USA) to perturb laboratory freshwater mesocosms, simulating sewage contamination events, and followed these mesocosms with shotgun metagenomics over a 7-day observational period. We describe 15 abundant non-redundant bacterial metagenome-assembled genomes (MAGs) ubiquitous within all sewage inocula yet absent from the unperturbed freshwater control at our analytical limit of detection. Tracking the dynamics of the populations represented by these MAGs revealed varied decay kinetics, depending on (inferred) phenotypes, e.g., anaerobes decayed faster than aerobes under the well-aerated incubation conditions. Notably, a portion of these populations showed decay patterns similar to those of common markers, Enterococcus and HF183. Despite the apparent decay of these populations, the abundance of β-lactamase encoding genes remained high throughout incubation relative to the control. Lastly, we constructed genomic libraries representing several different fecal sources and outline a bioinformatic approach which leverages these libraries for identifying and apportioning contamination signal among multiple probable sources using shotgun metagenomic data.

Identifiants

pubmed: 34979467
pii: S0043-1354(21)01187-8
doi: 10.1016/j.watres.2021.117993
pii:
doi:

Substances chimiques

Sewage 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

117993

Informations de copyright

Copyright © 2021. Published by Elsevier Ltd.

Auteurs

Blake G Lindner (BG)

School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA.

Brittany Suttner (B)

School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA.

Kevin J Zhu (KJ)

School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA.

Roth E Conrad (RE)

Ocean Science and Engineering, Georgia Institute of Technology, 311 Ferst Drive, ES&T Building, Room 3321, Atlanta, GA 30332, USA.

Luis M Rodriguez-R (LM)

School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA; Department of Microbiology and Digital Science Center (DiSC), University of Innsbruck, Innsbruck, Tyrol 6020, Austria.

Janet K Hatt (JK)

School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA.

Joe Brown (J)

School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA.

Konstantinos T Konstantinidis (KT)

School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA. Electronic address: kostas@ce.gatech.edu.

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Classifications MeSH