Exposure to benzalkonium chloride disinfectants promotes antibiotic resistance in sewage sludge microbiomes.

Disinfectants are routinely used in human environments to control and prevent the transmission of microbial disease, and this is particularly true during the current COVID-19 crisis. However, it remains unclear whether the increased disinfectant loadings to wastewater treatment plants facilitate the dissemination of antibiotic resistance genes (ARGs) in sewage sludge microbiomes. Here, we investigated the impacts of benzalkonium chlorides (BACs), widely used disinfectants, on ARGs profiles and microbial community structures in sewage sludge by using high-throughput quantitative PCR and Illumina sequencing. A total of 147 unique ARGs and 39 mobile genetic elements (MGEs) were detected in all sewage sludge samples. Our results show that exposure to BACs disinfectants at environmentally relevant concentrations significantly promotes both the diversity and absolute abundance of ARGs in sludge microbiomes, indicating the co-selection of ARGs by BACs disinfectants. The enrichment of ARGs abundance varied from 2.15-fold to 3.63-fold compared to controls. In addition, BACs exposure significantly alters bacterial and protistan communities, resulting in dysbiosis of the sludge microbiota. The Mantel test and Procrustes analysis confirm that bacterial communities are significantly correlated with ARGs profiles under BACs treatments. The structural equation model explains 83.8 % of the total ARGs variation and further illustrates that the absolute abundance of MGEs exerts greater impacts on the variation of absolute abundance of ARGs than microbial communities under BACs exposure, suggesting BACs may promote antibiotic resistance by enhancing the horizontal gene transfer of ARGs across sludge microbiomes. Collectively, our results provide new insights into the proliferation of antibiotic resistance through disinfectant usage during the pandemic and highlight the necessity to minimize the environmental release of disinfectants into the non-target environment for combating antibiotic resistance.

Persistence of surrogates for high consequence viral and bacterial pathogens in a pilot-scale activated sludge treatment system.

The persistence of high consequence public health pathogens in a wastewater treatment system can significantly impact worker safety, as well as the public and downstream water bodies, particularly if the system is forced to shut down the treatment processes. This study utilizes organism viability to compare the persistence of three pathogen surrogates in wastewater using a pilot-scale activated sludge treatment (AST) system, operated to mimic treatment processes of large-scale plants. Bacillus globigii spores, surrogate for Bacillus anthracis, persisted in the AST system for at least a 50-day observation period leading to a possible steady condition far beyond the solid retention time for sludge particles. MS2 bacteriophage, surrogate for Poliovirus and other non-enveloped enteric viruses, was observed for up to 35 days after introduction, which largely and expectedly correlated to the measured solid retention time. Phi-6 bacteriophage, a surrogate for Ebola virus and other enveloped viruses, was detected for no more than 4 days after introduction, even though the AST system was operated to provide three times slower solids removal than for the other surrogates. This suggests Phi-6 is subject to inactivation under AST conditions rather than physical removal. These results may suggest similar persistence for the surrogated pathogens, leading to appropriate consequence management actions.

Urban monitoring of antimicrobial resistance during a COVID-19 surge through wastewater surveillance.

During the early phase of the COVID-19 pandemic, infected patients presented with symptoms similar to bacterial pneumonias and were treated with antibiotics before confirmation of a bacterial or fungal co-infection. We reasoned that wastewater surveillance could reveal potential relationships between reduced antimicrobial stewardship, specifically misprescribing antibiotics to treat viral infections, and the occurrence of antimicrobial resistance (AMR) in an urban community. Here, we analyzed microbial communities and AMR profiles in sewage samples from a wastewater treatment plant (WWTP) and a community shelter in Las Vegas, Nevada during a COVID-19 surge in December 2020. Using a respiratory pathogen and AMR enrichment next-generation sequencing panel, we identified four major phyla in the wastewater, including Actinobacteria, Firmicutes, Bacteroidetes and Proteobacteria. Consistent with antibiotics that were reportedly used to treat COVID-19 infections (e.g., fluoroquinolones and beta-lactams), we also measured a significant spike in corresponding AMR genes in the wastewater samples. AMR genes associated with colistin resistance (mcr genes) were also identified exclusively at the WWTP, suggesting that multidrug resistant bacterial infections were being treated during this time. We next compared the Las Vegas sewage data to local 2018-2019 antibiograms, which are antimicrobial susceptibility profile reports about common clinical pathogens. Similar to the discovery of higher levels of beta-lactamase resistance genes in sewage during 2020, beta-lactam antibiotics accounted for 51 ± 3 % of reported antibiotics used in antimicrobial susceptibility tests of 2018-2019 clinical isolates. Our data highlight how wastewater-based epidemiology (WBE) can be leveraged to complement more traditional surveillance efforts by providing community-level data to help identify current and emerging AMR threats.

Multidrug-resistant enteroaggregative Escherichia coli (EAEC) enters dormant state during heat treatment: A potential hazard in municipal sludge.

Reuse of sewage sludge is a general trend and land application is an essential way to reuse sludge. The outbreak of coronavirus disease has raised concerns about human pathogens and their serious threat to public health. The risk of pathogenic bacterial contamination from land application of municipal sludge has not been well assessed. The purpose of this study was to investigate the presence of pathogenic bacteria in municipal sewage sludge and to examine the survival potential of certain multidrug-resistant enteroaggregative Escherichia coli (EAEC) strain isolated from sewage sludge during heat treatment. The sewage sludge produced in the two wastewater treatment plants contained pathogenic bacteria such as pathogenic E. coli, Shigella flexneri, and Citrobacter freundii. The environmental strain of EAEC isolated from the sludge was resistant to eight types of antibiotics. It could also enter the dormant state after 4.5 h of treatment at 55 °C and regrow at 37 °C, while maintaining its antibiotic resistance. Our results indicate that the dormancy of EAEC might be why it is heat-resistant and could not be killed completely during the sludge heat treatment process. Owing to the regrowth of the dormant pathogenic bacteria, it is risky to apply the sludge to land even if the sludge is heat-treated, and there is also a risk of spreading antibiotic resistance.

Microbiological and Toxicological Hazards in Sewage Treatment Plant Bioaerosol and Dust.

Despite the awareness that work in the sewage treatment plant is associated with biological hazards, they have not been fully recognised so far. The research aims to comprehensively evaluate microbiological and toxicological hazards in the air and settled dust in workstations in a sewage treatment plant. The number of microorganisms in the air and settled dust was determined using the culture method and the diversity was evaluated using high-throughput sequencing. Endotoxin concentration was assessed with GC-MS (gas chromatography-mass spectrometry) while secondary metabolites with LC-MS/MS (liquid chromatography coupled to tandem mass spectrometry). Moreover, cytotoxicity of settled dust against a human lung epithelial lung cell line was determined with the MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) assay and UHPLC-Q-ToF-UHRMS (ultra-high-performance liquid chromatography-quadrupole time-of-flight ultrahigh-resolution mass spectrometry) analysis was performed to determine the source of cytotoxicity. The total dust concentration in the sewage treatment plant was low and ranged from 0.030 mg m-3 to 0.044 mg m-3. The highest microbiological contamination was observed in sludge thickening building and screenings storage. Three secondary metabolites were detected in the air and sixteen in the settled dust. They were dominated by compounds typical of lichen and plants and Aspergillus, Penicillium and Fusarium genera mould. The settled dust from the sludge thickening building revealed high cytotoxicity to human lung epithelial cells A-549 (IC50 = 6.98 after 72 h). This effect can be attributed to a biocidal compound-didecyldimethylammonium chloride (DDAC-C10) and seven toxic compounds: 4-hydroxynonenal, carbofuran, cerulenin, diethylphosphate, fenpropimorph, naphthalene and onchidal. The presence of DDAC-C10 and other biocidal substances in the sewage treatment plant environment may bring negative results for biological sewage treatment and the natural environment in the future and contribute to microorganisms' increasing antibiotics resistance. Therefore, the concentration of antibiotics, pesticides and disinfectants in sewage treatment plant workstations should be monitored.

Aligning SARS-CoV-2 indicators via an epidemic model: application to hospital admissions and RNA detection in sewage sludge.

Ascertaining the state of coronavirus outbreaks is crucial for public health decision-making. Absent repeated representative viral test samples in the population, public health officials and researchers alike have relied on lagging indicators of infection to make inferences about the direction of the outbreak and attendant policy decisions. Recently researchers have shown that SARS-CoV-2 RNA can be detected in municipal sewage sludge with measured RNA concentrations rising and falling suggestively in the shape of an epidemic curve while providing an earlier signal of infection than hospital admissions data. The present paper presents a SARS-CoV-2 epidemic model to serve as a basis for estimating the incidence of infection, and shows mathematically how modeled transmission dynamics translate into infection indicators by incorporating probability distributions for indicator-specific time lags from infection. Hospital admissions and SARS-CoV-2 RNA in municipal sewage sludge are simultaneously modeled via maximum likelihood scaling to the underlying transmission model. The results demonstrate that both data series plausibly follow from the transmission model specified and provide a 95% confidence interval estimate of the reproductive number R0 ≈ 2.4 ± 0.2. Sensitivity analysis accounting for alternative lag distributions from infection until hospitalization and sludge RNA concentration respectively suggests that the detection of viral RNA in sewage sludge leads hospital admissions by 3 to 5 days on average. The analysis suggests that stay-at-home restrictions plausibly removed 89% of the population from the risk of infection with the remaining 11% exposed to an unmitigated outbreak that infected 9.3% of the total population.