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Wednesday, October 22, 2025 at 12:00 PM Eastern Daylight Time.

Surveillance of wastewater from healthcare facilities has the potential to identify the emergence of multidrug-resistance (MDR) genes of public health importance. Specifically, wastewater surveillance (WWS) can provide sentinel surveillance of novel MDR genes or organisms in healthcare facilities, helping to direct targeted prevention efforts and monitor longitudinal effects. Several knowledge gaps need to be addressed before WWS can be used routinely for MDR surveillance, including determining optimal approaches to sampling, processing, and testing wastewater.MethodsTo this end, we evaluated multiple methods for wastewater collection (passive, composite, and grab), concentration (nanoparticles, filtration, and centrifugation), and PCR quantification (real-time quantitative PCR vs. digital PCR) for Candida auris and 5 carbapenemase genes (blaKPC, blaNDM, blaVIM, blaIMP, and blaOXA-48-like) twice weekly for 6 months at a long-term acute care hospital in Chicago, IL. We also tested the effects of different transport and sample storage conditions on PCR quantification.ResultsAll genes were detected in facility wastewater, with blaKPC being the most consistently abundant. Experiments were done in triplicate with gene copy, variance, and number of detections between triplicates used to determine method efficacy. We found that passive samples processed immediately by centrifugation followed by bead-beating and dPCR provided the most reliable results for detecting MDR genes and C. auris. We also present the tradeoffs of different approaches and use culture and metagenomics to elucidate clinical relevance.ConclusionsThis study establishes a practical approach for WWS as a potential tool for public health monitoring of MDR burden in healthcare facilities.

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Efficient use of environmental nucleic acids (eNAs) in freshwater biodiversity monitoring requires understanding their degradation and detectability in interconnected ecosystems. We employed a novel ....

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Analysis, visualisation and simulation of digital polymerase chain reaction (dPCR) (Burdukiewicz et al. (2016) &lt;<a href="https://doi.org/10.1016%2Fj.bdq.2016.06.004" target="_top">doi:10.1016/j.bdq.2016.06.004</a>&gt;). Supports data formats of commercial systems (Bio-Rad QX100 and QX200; Fluidigm BioMark) and other systems.