Exploiting microplastics and the plastisphere for the surveillance of human pathogenic bacteria discharged into surface waters in wastewater effluent

IF 11.4 1区 环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL
Luke Woodford, Lauren F. Messer, Michael J. Ormsby, Hannah L. White, Rosie Fellows, Richard S. Quilliam
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引用次数: 0

Abstract

Discharge from wastewater treatment plants (WWTPs) is a well-characterised source of human pathogens and antimicrobial resistance genes entering the environment. However, determining whether pathogens released from effluent into surface waters are viable, and consequently pose a risk to human health, is hindered by the use of transient grab-sampling monitoring approaches. Here we present a novel surveillance system using low-cost microparticles (polyethylene, cork and rubber) deployed upstream and downstream of a WWTP effluent pipe, that exploits the ability of bacterial pathogens to form biofilms. Using quantitative culture-based and molecular methods, viable E. coli, Klebsiella sp., Citrobacter sp., and Enterococcus spp. were identified after only 24-hour of deployment. Moreover, these pathogens were continually present at each timepoint (2, 4, 6, 8, 10, 14 and 23 days) as biofilm communities matured, with all pathogens detected at higher concentrations downstream of the WWTP effluent pipe. Long-read whole genome sequencing revealed a suite of plasmids, virulence genes and antimicrobial resistance genes in bacterial pathogens isolated from biofilms formed downstream of the effluent pipe. Furthermore, recognising that pathogens are typically present at proportionally low concentrations within mixed biofilm communities, total biofilm pathogenicity was confirmed using a Galleria mellonella infection model. Full-length 16S rRNA gene sequencing revealed that human pathogens present in microplastic biofilms (the ‘plastisphere’) dominated the microbial community of infected G. mellonella larvae within 24 hr, suggesting these bacteria remained highly virulent. Overall, this study demonstrated the efficacy of an easy-to-deploy system for the surveillance and rapid detection of pathogenic bacteria being discharged from point-source pollution. We envisage that if used as part of an integrated environmental management approach, this approach could help to reduce the public and environmental health risks of human pathogens and antimicrobial resistance genes, by monitoring viable human pathogens entering surface waters.
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来源期刊
Water Research
Water Research 环境科学-工程:环境
CiteScore
20.80
自引率
9.40%
发文量
1307
审稿时长
38 days
期刊介绍: Water Research, along with its open access companion journal Water Research X, serves as a platform for publishing original research papers covering various aspects of the science and technology related to the anthropogenic water cycle, water quality, and its management worldwide. The audience targeted by the journal comprises biologists, chemical engineers, chemists, civil engineers, environmental engineers, limnologists, and microbiologists. The scope of the journal include: •Treatment processes for water and wastewaters (municipal, agricultural, industrial, and on-site treatment), including resource recovery and residuals management; •Urban hydrology including sewer systems, stormwater management, and green infrastructure; •Drinking water treatment and distribution; •Potable and non-potable water reuse; •Sanitation, public health, and risk assessment; •Anaerobic digestion, solid and hazardous waste management, including source characterization and the effects and control of leachates and gaseous emissions; •Contaminants (chemical, microbial, anthropogenic particles such as nanoparticles or microplastics) and related water quality sensing, monitoring, fate, and assessment; •Anthropogenic impacts on inland, tidal, coastal and urban waters, focusing on surface and ground waters, and point and non-point sources of pollution; •Environmental restoration, linked to surface water, groundwater and groundwater remediation; •Analysis of the interfaces between sediments and water, and between water and atmosphere, focusing specifically on anthropogenic impacts; •Mathematical modelling, systems analysis, machine learning, and beneficial use of big data related to the anthropogenic water cycle; •Socio-economic, policy, and regulations studies.
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