Metagenomic evaluation of the performance of passive Moore swabs for sewage monitoring relative to composite sampling over time resolved deployments.

Moore swabs have re-emerged as a versatile tool in the field of wastewater-based epidemiology during the COVID-19 pandemic and offer unique advantages for monitoring pathogens in sewer systems, especially at the neighborhood-level. However, whether Moore swabs provide comparable results to more commonly used composite samples remains to be rigorously tested including the optimal duration of Moore swab deployment. This study provides new insights into these issues by comparing the results from Moore swab samples to those of paired composite samples collected from the same sewer lines continuously over six to seventy-two hours post-deployment, during low COVID-19 prevalence periods. Our results show that Moore swabs accumulated approximately 10-fold higher PMMoV concentrations (on a basis of mL of Moore swab squeezed filtrate to mL of composite sewage) and showed comparable trends in terms of bacterial species abundance when compared to composite samples. Moore swabs also generally captured higher SARS-CoV-2 N1/N2 RNA concentrations than composite samples. Moore swabs showed comparable trends in terms of abundance dynamics of the sewage microbiome to composite samples and variable signs of saturation over time that were site and/or microbial population-specific. Based on our dual ddRT-PCR and shotgun metagenomic approach, we find that Moore swabs at our sites were optimally deployed for 6 h at a time at two sites.

Parallel deployment of passive and composite samplers for surveillance and variant profiling of SARS-CoV-2 in sewage.

Wastewater-based epidemiology during the COVID-19 pandemic has proven useful for public health decision-making but is often hampered by sampling methodology constraints, particularly at the building- or neighborhood-level. Time-weighted composite samples are commonly used; however, autosamplers are expensive and can be affected by intermittent flows in sub-sewershed contexts. In this study, we compared time-weighted composite, grab, and passive sampling via Moore swabs, at four locations across a college campus to understand the utility of passive sampling. After optimizing the methods for sample handling and processing for viral RNA extraction, we quantified SARS-CoV-2 N1 and N2, as well as a fecal strength indicator, PMMoV, by ddRT-PCR and applied tiled amplicon sequencing of the SARS-CoV-2 genome. Passive samples compared favorably with composite samples in our study area: for samples collected concurrently, 42 % of the samples agreed between Moore swab and composite samples and 58 % of the samples were positive for SARS-CoV-2 using Moore swabs while composite samples were below the limit of detection. Variant profiles from Moore swabs showed a shift from variant BA.1 to BA.2, consistent with in-person saliva samples. These data have implications for the broader implementation of sewage surveillance without advanced sampling technologies and for the utilization of passive sampling approaches for other emerging pathogens.

Elevated Fecal Mitochondrial DNA from Symptomatic Norovirus Infections Suggests Potential Health Relevance of Human Mitochondrial DNA in Fecal Source Tracking.

An end goal of fecal source tracking (FST) is to provide information on risk of transmission of waterborne illnesses associated with fecal contamination. Ideally, concentrations of FST markers in ambient waters would reflect exposure risk. Human mtDNA is an FST marker that is exclusively human in origin and may be elevated in feces of individuals experiencing gastrointestinal inflammation. In this study, we examined whether human mtDNA is elevated in fecal samples from individuals with symptomatic norovirus infections using samples from the United States (US), Mozambique, and Bangladesh. We quantified hCYTB484 (human mtDNA) and HF183/BacR287 (human-associated Bacteroides) FST markers using droplet digital polymerase chain reaction. We observed the greatest difference in concentrations of hCYTB484 when comparing samples from individuals with symptomatic norovirus infections versus individuals without norovirus infections or diarrhea symptoms: log10 increase of 1.42 in US samples (3,820% increase, p-value = 0.062), 0.49 in Mozambique (308% increase, p-value = 0.061), and 0.86 in Bangladesh (648% increase, p-value = 0.035). We did not observe any trends in concentrations of HF183/BacR287 in the same samples. These results suggest concentrations of fecal mtDNA may increase during symptomatic norovirus infection and that mtDNA in environmental samples may represent an unambiguously human source-tracking marker that correlates with enteric pathogen exposure risk.

Effect of peracetic acid solution on a nitrifying culture: Kinetics, inhibition, cellular and transcriptional responses.

Peracetic acid (PAA) has been widely used as a disinfectant in many industries. However, information related to the potential inhibitory effect of PAA solutions (PAA and H2O2) on biological wastewater treatment processes is very limited. The work reported here assessed the effect of PAA and H2O2 solutions on nitrification kinetics and inhibition, cellular level responses and gene expression of a suspended-growth nitrifying culture. The initial ammonia removal and nitrate production rates significantly decreased at 1/0.14 to 3/0.42 mg/L PAA/H2O2. H2O2 up to 3 mg/L did not impact nitrification, cell viability or related respiratory activities; thus, the impact of the PAA solution is attributed to PAA alone or in some combination with H2O2. Nitrification inhibition by PAA was predominantly related to enzyme inhibition, rather than to loss of cell viability and/or cell lysis. PAA and H2O2 negatively affected Nitrosomonas but resulted in Nitrosospira enrichment. Most nitrogen metabolism-related genes (e.g., hydroxylamine oxidoreductase and nitrite oxidoreductase genes) as well as oxidase genes (e.g., cytochrome c oxidase, catalase-peroxidase, and peroxidase genes) were upregulated in PAA- and H2O2-amended cultures. Major ATPase genes were downregulated while ATP synthase genes upregulated under the effect of PAA and/or H2O2. Upregulation of ATP-dependent protease genes indicates protein damage predominantly caused by PAA rather than H2O2. The transcriptional level of genes related to cell division and DNA repair did not show a particular pattern; thus, cell division functionality and DNA integrity were not significantly affected by PAA or H2O2. The results of this study have significant implications in the design and operation of effective biological nitrogen removal systems for the treatment of PAA-bearing wastewater.

Toward shotgun metagenomic approaches for microbial source tracking sewage spills based on laboratory mesocosms.

Little is known about the genomic diversity of the microbial communities associated with raw municipal wastewater (sewage), including whether microbial populations specific to sewage exist and how such populations could be used to improve source attribution and apportioning in contaminated waters. Herein, we used the influent of three wastewater treatment plants in Atlanta, Georgia (USA) to perturb laboratory freshwater mesocosms, simulating sewage contamination events, and followed these mesocosms with shotgun metagenomics over a 7-day observational period. We describe 15 abundant non-redundant bacterial metagenome-assembled genomes (MAGs) ubiquitous within all sewage inocula yet absent from the unperturbed freshwater control at our analytical limit of detection. Tracking the dynamics of the populations represented by these MAGs revealed varied decay kinetics, depending on (inferred) phenotypes, e.g., anaerobes decayed faster than aerobes under the well-aerated incubation conditions. Notably, a portion of these populations showed decay patterns similar to those of common markers, Enterococcus and HF183. Despite the apparent decay of these populations, the abundance of ß-lactamase encoding genes remained high throughout incubation relative to the control. Lastly, we constructed genomic libraries representing several different fecal sources and outline a bioinformatic approach which leverages these libraries for identifying and apportioning contamination signal among multiple probable sources using shotgun metagenomic data.