Publications by authors named "Ayella Maile-Moskowitz"

Article Synopsis
  • The study explored the behavior of antibiotic resistance genes (ARGs) in wastewater treatment plants (WWTPs) and found significant variation in ARG responses, as they may either decrease or increase depending on the specific plant.
  • Researchers used metagenomic sequencing on samples from 12 international WWTPs, identifying 1079 different ARGs, with overall decreases in ARG abundance observed at most sites, except for one where 40% of ARGs increased.
  • The findings suggest that while WWTPs generally reduce antibiotic resistance loads, the increase in mobile genetic elements during treatment does not necessarily correlate with more transmissible ARGs, indicating a need for better wastewater surveillance strategies.
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Activated sludge is the centerpiece of biological wastewater treatment, as it facilitates removal of sewage-associated pollutants, fecal bacteria, and pathogens from wastewater through semi-controlled microbial ecology. It has been hypothesized that horizontal gene transfer facilitates the spread of antibiotic resistance genes within the wastewater treatment plant, in part because of the presence of residual antibiotics in sewage. However, there has been surprisingly little evidence to suggest that sewage-associated antibiotics select for resistance at wastewater treatment plants via horizontal gene transfer or otherwise.

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Wastewater-based surveillance (WBS) has gained attention as a strategy to monitor and provide an early warning for disease outbreaks. Here, we applied an isothermal gene amplification technique, reverse-transcription loop-mediated isothermal amplification (RT-LAMP), coupled with nanopore sequencing (LAMPore) as a means to detect SARS-CoV-2. Specifically, we combined barcoding using both an RT-LAMP primer and the nanopore rapid barcoding kit to achieve highly multiplexed detection of SARS-CoV-2 in wastewater.

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Wastewater-based surveillance (WBS) for disease monitoring is highly promising but requires consistent methodologies that incorporate predetermined objectives, targets, and metrics. Herein, we describe a comprehensive metagenomics-based approach for global surveillance of antibiotic resistance in sewage that enables assessment of 1) which antibiotic resistance genes (ARGs) are shared across regions/communities; 2) which ARGs are discriminatory; and 3) factors associated with overall trends in ARGs, such as antibiotic concentrations. Across an internationally sourced transect of sewage samples collected using a centralized, standardized protocol, ARG relative abundances (16S rRNA gene-normalized) were highest in Hong Kong and India and lowest in Sweden and Switzerland, reflecting national policy, measured antibiotic concentrations, and metal resistance genes.

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To evaluate the use of wastewater-based surveillance and epidemiology to monitor and predict SARS-CoV-2 virus trends, over the 2020-2021 academic year we collected wastewater samples twice weekly from 17 manholes across Virginia Tech's main campus. We used data from external door swipe card readers and student isolation/quarantine status to estimate building-specific occupancy and COVID-19 case counts at a daily resolution. After analyzing 673 wastewater samples using reverse transcription quantitative polymerase chain reaction (RT-qPCR), we reanalyzed 329 samples from isolation and nonisolation dormitories and the campus sewage outflow using reverse transcription digital droplet polymerase chain reaction (RT-ddPCR).

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The impacts of the ongoing coronavirus pandemic highlight the importance of environmental monitoring to inform public health safety. Wastewater based epidemiology (WBE) has drawn interest as a tool for analysis of biomarkers in wastewater networks. Wide scale implementation of WBE requires a variety of field deployable analytical tools for real-time monitoring.

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River networks are one of the main routes by which the public could be exposed to environmental sources of antibiotic resistance, that may be introduced e.g. via treated wastewater.

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The emergence of next generation sequencing (NGS) is revolutionizing the potential to address complex microbiological challenges in the water industry. NGS technologies can provide holistic insight into microbial communities and their functional capacities in water and wastewater systems, thus eliminating the need to develop a new assay for each target organism or gene. However, several barriers have hampered wide-scale adoption of NGS by the water industry, including cost, need for specialized expertise and equipment, challenges with data analysis and interpretation, lack of standardized methods, and the rapid pace of development of new technologies.

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The World Health Organization Global Action Plan recommends integrated surveillance programs as crucial strategies for monitoring antibiotic resistance. Although several national surveillance programs are in place for clinical and veterinary settings, no such schemes exist for monitoring antibiotic-resistant bacteria in the environment. In this transnational study, we developed, validated, and tested a low-cost surveillance and easy to implement approach to evaluate antibiotic resistance in wastewater treatment plants (WWTPs) by targeting cefotaxime-resistant (CTX-R) coliforms as indicators.

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Antimicrobial resistance (AMR) is one of the greatest threats faced by humankind. The development of resistance in clinical and hospital settings has been well documented ever since the initial discovery of penicillin and the subsequent introduction of sulfonamides as clinical antibiotics. In contrast, the environmental (i.

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Three tubular anaerobic digestion (AD) systems were installed in Haiti to treat black water (toilet-based wastewater), including a three cell 36m clinic digester (CD), a two cell 2m hotel digester (HD), and a three-cell 3m farm digester (FD) for worker use. During digestion, total coliforms were reduced by 99.1%, E.

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