Heather Nicole Bischel

Wastewater sequencing using probe-capture enrichment of public health-relevant viruses is a powerful, non-intrusive approach to monitor infectious diseases, but performance depends on sample type and processing approach. We compared two processing pipelines from wastewater influent samples collected at three timepoints across three wastewater treatment facilities. Each sample was split for parallel processing, with viruses concentrated (1) directly from whole influent using nano-sized affinity particles and (2) by settling and dewatering the solids fraction. Combined DNA/RNA extracts were prepared into libraries using a pre-commercial Illumina protocol, then probe-capture enrichment was performed with Illumina’s Viral Surveillance Panel (VSP) v1 (66 targets) and v2 (242 targets). Sequencing depth was increased for VSP v2 to accommodate the expanded target set. On average, 160 ± 146 viral species were detected per sample, with wastewater fraction (sample type) explaining 19% of the variance in viral abundances. Solids contained a higher abundance of DNA viruses compared to RNA viruses, while influent exhibited the inverse. Metagenomic analysis of the VSP v2 sequencing data detected more viral species in influent (median 358) than in solids (median 184), but probe-capture enrichment produced more comparable target-virus readouts across fractions, supporting the use of either fraction for wastewater-based epidemiology.

The structural diversity of poly- and perfluoroalkyl substances (PFASs) poses challenges for class-based chemical hazard assessments. Computational simulations of PFAS-protein binding provide a means to improve screening-level evaluations by considering molecular interactions with toxicologically relevant proteins. Many PFASs are known to interact with carrier and channel proteins that influence bioaccumulation and toxicity, yet experimental data remain limited. To address this gap, we developed multicondition quantitative structure–activity relationship (QSAR) models that incorporate PFAS-protein associations. We simulated interactions of 4,397 PFASs with six health-relevant proteins, generating molecular docking binding scores for 12 ligand-binding sites. We then constructed seven bioactivity prediction models, integrating 44 additional chemical descriptors for each target. Training used binary bioactivity classifications for 560 PFASs derived from public toxicology and bioactivity databases. Using the best performing model (random forest), we classified the bioactivity potential of 2,649 PFASs within the applicability domain. Strong binding of PFASs to human serum albumin (fatty acid binding sites 3 and 4) and peroxisome proliferator-activated receptor γ, along with molecular complexity and the number of saturated hetero rings, were associated with PFAS bioactivity. A structure–activity landscape index analysis further suggested that nonfluorinated moietiesincluding bromine substitution, benzimidazole, and dinitroaniline groupscontribute to PFAS bioactivity.

Water demand necessitates innovative water management strategies, including wastewater reuse. However, the presence of viruses in reused water is a significant public health concern. This study investigated the potential of using somatic and F-specific coliphages as surrogates for routine monitoring during wastewater reclamation for reuse. Samples were collected from the primary influent, secondary effluent, and final effluent from six wastewater treatment plants across the United States. Analysis revealed geographic and seasonal variability in coliphage concentrations in the raw influents, with somatic coliphage ranging between 2.6 × 103 and 9.7 × 103 plaque forming unit (PFU)/mL and F-specific coliphage from 0.6 to 7.7 × 103 PFU/mL. From influent to effluent, 3.46 to 5.14 log virus removal (LVR) was observed for somatic coliphage, while F-specific coliphage removal ranged from 2.85 to 5.40 LVR. Most facilities showed a 4 or greater LVR of somatic coliphage from the influent to the final effluent. These findings support the inclusion of somatic coliphage for LVR monitoring since it was detected consistently in downstream processes. More research is needed to assess the ability of different unit operations in different climates to remove viruses during wastewater treatment.

Wastewater surveillance has emerged as a critical public health tool, enabling early detection of infectious disease outbreaks and providing timely, population-level insights into community health trends. However, variability in sample collection and processing, for example between wastewater influent and settled solids, can introduce methodological noise that differentially impacts true epidemiological signals and limits cross-site comparability. To address this challenge, we aimed to discern underlying disease trends from methodological variability in SARS-CoV-2 wastewater data using discrete wavelet transform (DWT), with a focus on comparing influent and solids samples from the same geographic locations. We applied DWT to longitudinal SARS-CoV-2 RNA concentrations in wastewater from five California cities, each with paired influent and solids samples. DWT decomposes each signal into two components: (1) approximation coefficients that capture smoothed long-term trends, and (2) detail coefficients that isolate high-frequency fluctuations and transient variations in the signal. We reconstructed signals by progressively removing the high-frequency components and assessed similarity between sample types using hierarchical clustering. Clustering of raw signals did not yield city-specific groupings, indicating that methodological noise obscured the underlying epidemiological signal. Intermediate reconstructions that retained some high-frequency components continued to show mixed groupings. In contrast, reconstructions based solely on low-frequency approximation coefficients revealed clear, city-specific clustering, with influent and solids samples from the same city aligning closely. These findings support our hypothesis that high-frequency components are primarily driven by sample processing and laboratory noise, while low-frequency components reflect shared epidemiological trends.

Flow virometry (FVM) offers a promising approach for monitoring viruses and virus-like particles (VLPs) in environmental samples. This study compares levels of non-specific VLPs across a wastewater treatment plant (WWTP) with levels of somatic coliphage, (F+) specific coliphage, Pepper Mild Mottle Virus (PMMoV), CrAssphage (CrAss), and Tomato Brown Rugose Fruit Virus (ToBRFV). All targets were quantified in influent, secondary-treated effluent, and tertiary-treated effluent at the University of California, Davis Wastewater Treatment Plant (UCDWWTP) over 11 weeks. We established an FVM-gating boundary for VLPs using bacteriophages T4 and ϕ6 as well as four phages isolated from wastewater. We then utilize T4 alongside three submicron beads as quality controls in the FVM assay. Coliphage was measured by standard plaque assays, and genome copies of PMMoV, CrAss, and ToBRFV were measured by digital droplet (dd)PCR. FVM results for wastewater revealed distinct microbial profiles at each treatment stage. However, correlations between VLPs and targeted viruses were poor. Trends for virus inactivation and removal, observed for targeted viruses during wastewater treatment, were consistent with expectations. Conversely, VLP counts were elevated in the WWTP effluent relative to the influent. Additional sampling revealed a decrease in VLP counts during the filtration treatment step following secondary treatment but a substantial increase in VLPs following ultraviolet disinfection. Defining application boundaries remain crucial to ensuring meaningful data interpretation as flow cytometry and virometry take on greater significance in water quality monitoring.

The SARS-CoV-2 Omicron (BA.1/BA.1.1) variant was declared a variant of concern (VOC) on November 26, 2021 and rapidly became the dominant lineage globally. Monitoring for VOCs is a public health priority, but standard case-based surveillance requires a robust, local whole genome sequencing (WGS) network and results may take weeks. Wastewater monitoring of VOCs is appealing as a potentially sensitive and timely approach to VOC monitoring that could provide complementary information to case-based WGS and a more complete picture of VOC circulation. However, wastewater VOC monitoring through PCR assays and WGS each have unique advantages and disadvantages that are not well characterized. The California Department of Public Health collaborated with academic partners to conduct wastewater VOC monitoring during the emergence of Omicron BA.1./BA.1.1 in late 2021. Wastewater monitoring was conducted via RT-PCR assays targeting specific mutations and via wastewater sequencing. Wastewater data was analyzed within the context of case-based WGS data to track the emergence of Omicron in California. In most locations across California, wastewater PCR provided early identification of the emergence and subsequent dominance of Omicron BA.1./BA.1.1. These results were then corroborated and confirmed as case-based WGS results became available. These data helped guide real-time public health response during the Omicron surge. Wastewater monitoring of VOC's provides a timely, accurate, and sensitive methodology for VOC monitoring. Successful implementation of wastewater VOC monitoring requires wastewater surveillance infrastructure as well as ongoing investment and research to support the development and deployment of assays and sequencing methodologies for emerging variants.

Sub-city, or sub-sewershed, wastewater monitoring for infectious diseases offers a data-driven strategy to inform local public health response and complements city-wide data from centralized wastewater treatment plants.

In 2022, the US Centers for Disease Control and Prevention commissioned the National Academies of Sciences, Engineering, and Medicine to assess the role of community-level wastewater-based disease surveillance (WDS) beyond COVID-19. WDS is recognized as a promising mechanism for promptly identifying infectious diseases, including COVID-19 and other novel pathogens. An important conclusion drawn from this initiative is that it is crucial to maintain equity and expand access to maximize the advantages of WDS for marginalized communities. To address this need, we propose an optimization framework that focuses on the strategic allocation of wastewater monitoring resources at the wastewater treatment plant level. The framework’s purpose is to obtain a balanced spatial distribution, inclusive population coverage, and efficient representation of vulnerable communities in allocating resources for WDS. This study offers an opportunity to improve wastewater surveillance by tailoring location selection strategies to address specific priorities, improving decision-making in public health responses.