ArticleMicrobiology spectrum2026
Environmental reservoirs account for high levels of carbapenem resistance genes in wastewater.
Article in Microbiology spectrum, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
1 citing paper in PubMed.
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Authors and funding
7 authors.
Funding
Abstract
Wastewater surveillance has moved to the forefront as a practical and informative public health tool for assessing viral and bacterial pathogens in the human population; however, the usefulness for tracking antimicrobial-resistance genes (ARGs) of clinical concern is not straightforward given the large reservoir of free-living bacteria within sewer systems. In this study, we examined six high-priority carbapenem resistance gene targets and common host organisms in wastewater collected from two treatment plants. Polymerase chain reaction (PCR)-based assays demonstrated an extremely high abundance of IMPORTANCE: Wastewater surveillance for carbapenem-resistant bacteria has been proposed as a potentially valuable tool for assessing the human burden, but their distribution in environmental reservoirs is not well understood. Untreated sewage contains a high density of resident organisms mixed with human inputs, which are transported through the complex environment of sewer conveyance systems. In addition to resident microbial community members, organisms seeded into the system from the human microbiome have the potential to grow. This work shows that environmental bacteria may be a significant source of carbapenem resistance genes collected from sewer systems, making wastewater surveillance data difficult to interpret or use for public health actions. More knowledge is needed to unravel the ecology of these systems and identify targets for surveillance that are meaningful to clinicians. This work sheds light on the complex dynamics and confounding factors for antimicrobial-resistance gene wastewater surveillance, which will improve the interpretation of wastewater surveillance data.
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