Ohio Coronavirus Wastewater Monitoring Network: Implementation of Statewide Monitoring for Protecting Public Health

CONTEXT

Prior to the COVID-19 pandemic, wastewater influent monitoring for tracking disease burden in sewered communities was not performed in Ohio, and this field was only on the periphery of the state academic research community.

PROGRAM

Because of the urgency of the pandemic and extensive state-level support for this new technology to detect levels of community infection to aid in public health response, the Ohio Water Resources Center established relationships and support of various stakeholders. This enabled Ohio to develop a statewide wastewater SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) monitoring network in 2 months starting in July 2020.

IMPLEMENTATION

The current Ohio Coronavirus Wastewater Monitoring Network (OCWMN) monitors more than 70 unique locations twice per week, and publicly available data are updated weekly on the public dashboard.

EVALUATION

This article describes the process and decisions that were made during network initiation, the network progression, and data applications, which can inform ongoing and future pandemic response and wastewater monitoring.

DISCUSSION

Overall, the OCWMN established wastewater monitoring infrastructure and provided a useful tool for public health professionals responding to the pandemic.

Analysis of metatranscriptomic methods to enable wastewater-based biosurveillance of all infectious diseases

Introduction

Wastewater-based surveillance emerged during the COVID-19 pandemic as an efficient way to quickly screen large populations, monitor infectious disease transmission over time, and identify whether more virulent strains are becoming more prevalent in the region without burdening the health care system with individualized testing. Ohio was one of the first states to implement wastewater monitoring through its Ohio Coronavirus Wastewater Monitoring Network (OCWMN), originally tracking the prevalence of COVID-19 by quantitative qPCR from over 67 sites across the state. The OCWMN evolved along with the pandemic to include sequencing the SARS-CoV-2 genome to assess variants of concern circulating within the population. As the pandemic wanes, networks such as OCWMN can be expanded to monitor other infectious diseases and outbreaks of interest to the health department to reduce the burden of communicable diseases. However, most surveillance still utilizes qPCR based diagnostic tests for individual pathogens, which is hard to scale for surveillance of multiple pathogens.

Methods

Here we have tested several genomic methods, both targeted and untargeted, for wastewater-based biosurveillance to find the most efficient procedure to detect and track trends in reportable infectious diseases and outbreaks of known pathogens as well as potentially novel pathogens or variants on the rise in our communities. RNA extracts from the OCWMN were provided weekly from 10 sites for 6 weeks. Total RNA was sequenced from the samples on the Illumina NextSeq and on the MinION to identify pathogens present. The MinION long read platform was also used to sequence SARS-CoV-2 with the goal of reducing the complexity of variant calling in mixed populations as occurs with short Illumina reads. Finally, a targeted hybridization approach was tested for compatibility with wastewater RNA samples.

Results and discussion

The data analyzed here provides a baseline assessment that demonstrates that wastewater is a rich resource for infectious disease epidemiology and identifies technology gaps and potential solutions to enable this resource to be used by public health laboratories to monitor the infectious disease landscape of the regions they serve.

Feasibility of neighborhood and building scale wastewater-based genomic epidemiology for pathogen surveillance

The benefits of wastewater-based epidemiology (WBE) for tracking the viral load of SARS-CoV-2, the causative agent of COVID-19, have become apparent since the start of the pandemic. However, most sampling occurs at the wastewater treatment plant influent and therefore monitors the entire catchment, encompassing multiple municipalities, and is conducted using quantitative polymerase chain reaction (qPCR), which only quantifies one target. Sequencing methods provide additional strain information and also can identify other pathogens, broadening the applicability of WBE to beyond the COVID-19 pandemic. Here we demonstrate feasibility of sampling at the neighborhood or building complex level using qPCR, targeted sequencing, and untargeted metatranscriptomics (total RNA sequencing) to provide a refined understanding of the local dynamics of SARS-CoV-2 strains and identify other pathogens circulating in the community. We demonstrate feasibility of tracking SARS-CoV-2 at the neighborhood, hospital, and nursing home level with the ability to detect one COVID-19 positive out of 60 nursing home residents. The viral load obtained was correlative with the number of COVID-19 patients being treated in the hospital. Targeted wastewater-based sequencing over time demonstrated that nonsynonymous mutations fluctuate in the viral population. Clades and shifts in mutation profiles within the community were monitored and could be used to determine if vaccine or diagnostics need to be adapted to ensure continued efficacy. Furthermore, untargeted RNA sequencing identified several other pathogens in the samples. Therefore, untargeted RNA sequencing could be used to identify new outbreaks or emerging pathogens beyond the COVID-19 pandemic.

Feasibility of neighborhood and building scale wastewater-based genomic epidemiology for pathogen surveillance

The benefits of wastewater-based epidemiology (WBE) for tracking the viral load of SARS-CoV-2, the causative agent of COVID-19, have become apparent since the start of the pandemic. However, most sampling occurs at the wastewater treatment plant influent and therefore monitors the entire catchment, encompassing multiple municipalities, and is conducted using quantitative polymerase chain reaction (qPCR), which only quantifies one target. Sequencing methods provide additional strain information and also can identify other pathogens, broadening the applicability of WBE to beyond the COVID-19 pandemic. Here we demonstrate feasibility of sampling at the neighborhood or building complex level using qPCR, targeted sequencing, and untargeted metatranscriptomics (total RNA sequencing) to provide a refined understanding of the local dynamics of SARS-CoV-2 strains and identify other pathogens circulating in the community. We demonstrate feasibility of tracking SARS-CoV-2 at the neighborhood, hospital, and nursing home level with the ability to detect one COVID-19 positive out of 60 nursing home residents. The viral load obtained was correlative with the number of COVID-19 patients being treated in the hospital. Targeted wastewater-based sequencing over time demonstrated that nonsynonymous mutations fluctuate in the viral population. Clades and shifts in mutation profiles within the community were monitored and could be used to determine if vaccine or diagnostics need to be adapted to ensure continued efficacy. Furthermore, untargeted RNA sequencing identified several other pathogens in the samples. Therefore, untargeted RNA sequencing could be used to identify new outbreaks or emerging pathogens beyond the COVID-19 pandemic.

Application of a multiple lines of evidence approach to document natural attenuation of hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX) in groundwater

This study utilized innovative analyses to develop multiple lines of evidence for natural attenuation of hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX) in groundwater at the U.S. Department of Energy's Pantex Plant. RDX, as well as the degradation product 4-nitro-2,4-diazabutanal (NDAB; produced by aerobic biodegradation or alkaline hydrolysis) were detected in a large portion of the plume, with lower concentrations of the nitroso-containing metabolites produced during anaerobic biodegradation. 16S metagenomic sequencing detected the presence of bacteria known to aerobically degrade RDX (e.g., Gordonia, Rhodococcus) and NDAB (Methylobacterium), as well as the known anoxic RDX degrader Pseudomonas fluorescens I-C. Proteomic analysis detected both the aerobic RDX degradative enzyme XplA, and the anoxic RDX degradative enzyme XenB. Groundwater enrichment cultures supplied with low concentrations of labile carbon confirmed the potential of the extant groundwater community to aerobically degrade RDX and produce NDAB. Compound-specific isotope analysis (CSIA) of RDX collected at the site showed fractionation of nitrogen isotopes with δ¹⁵N values ranging from approximately -5‰ to +9‰, providing additional evidence of RDX degradation. Taken together, these results provide evidence of in situ RDX degradation in the Pantex Plant groundwater. Furthermore, they demonstrate the benefit of multiple lines of evidence in supporting natural attenuation assessments, especially with the application of innovative isotopic and -omic technologies.

Sequence-based autosomal STR characterization in four US populations using PowerSeq™ Auto/Y system

The forensic science community is poised to utilize modern advances in massively parallel sequencing (MPS) technologies to better characterize biological samples with higher resolution. A critical component towards the advancement of forensic DNA analysis with these technologies is a comprehensive understanding of the diversity and population distribution of sequence-based short tandem repeat (STR) alleles. Here we analyzed 786 samples of individuals from different population groups, including four of the mostly commonly encountered in forensic casework in the USA. DNA samples were amplified with the PowerSeq™ Auto/Y System Prototype Kit (Promega Corp.), and sequencing was performed on an Illumina® MiSeq instrument. Sequence data were analyzed using a bioinformatics processing tool, Altius. For additional data analysis and profile comparison, capillary electrophoresis (CE) size-based STR genotypes were generated for a subset of individuals, and where possible, also with a second commercially available MPS STR assay. Autosomal STR loci were analyzed and frequencies were calculated based on sequence composition. Also, population genetics studies were performed, with Hardy-Weinberg equilibrium, polymorphic information content (PIC), and observed and expected heterozygosity all assessed. Overall, sequence-based allelic variants of the repeat region were observed in 20 out of 22 different STR loci commonly used in forensic DNA genotyping, with the highest number of sequence variation observed at locus D12S391. The highest increase in allelic diversity and in PIC through sequence-based genotyping was observed at loci D3S1358 and D8S1179. Such detailed sequence analysis, as the one performed in the present study, is important to help understand the diversity of sequence-based STR alleles across different populations and to demonstrate how such allelic variation can improve statistics used for forensic casework.

Use of omic tools to assess methyl tert-butyl ether (MTBE) degradation in groundwater

This study employed innovative technologies to evaluate multiple lines of evidence for natural attenuation (NA) of methyl tertiary-butyl ether (MTBE) in groundwater at the 22 Area of Marine Corps Base (MCB) Camp Pendleton after decommissioning of a biobarrier system. For comparison, data from the 13 Area Gas Station where active treatment of MTBE is occurring was used to evaluate the effectiveness of omic techniques in assessing biodegradation. Overall, the 22 Area Gas Station appeared to be anoxic. MTBE was detected in large portion of the plume. In comparison, concentrations of MTBE at the 13 Area Gas Station were much higher (42,000 μg/L to 2800 μg/L); however, none of the oxygenates were detected. Metagenomic analysis of the indigenous groundwater microbial community revealed the presence of bacterial strains known to aerobically and anaerobically degrade MTBE at both sites. While proteomic analysis at the 22 Area Gas Station showed the presence of proteins of MTBE degrading microorganisms, the MTBE degradative proteins were only found at the 13 Area Gas Station. Taken together, these results provide evidence for previous NA of MTBE in the groundwater at 22 Area Gas Station and demonstrate the effectiveness of innovative-omic technologies to assist monitored NA assessments.

Biodegradation of dispersed Macondo crude oil by indigenous Gulf of Mexico microbial communities

Because of the extreme conditions of the Deepwater Horizon (DWH) release (turbulent flow at 1500m depth and 5°C water temperature) and the sub-surface application of dispersant, small but neutrally buoyant oil droplets <70μm were formed, remained in the water column and were subjected to in-situ biodegradation processes. In order to investigate the biodegradation of Macondo oil components during the release, we designed and performed an experiment to evaluate the interactions of the indigenous microbial communities present in the deep waters of the Gulf of Mexico (GOM) with oil droplets of two representative sizes (10μm and 30μm median volume diameter) created with Macondo source oil in the presence of Corexit 9500 using natural seawater collected at the depth of 1100-1300m in the vicinity of the DWH wellhead. The evolution of the oil was followed in the dark and at 5°C for 64days by collecting sacrificial water samples at fixed intervals and analyzing them for a wide range of chemical and biological parameters including volatile components, saturated and aromatic hydrocarbons, dispersant markers, dissolved oxygen, nutrients, microbial cell counts and microbial population dynamics. A one phase exponential decay from a plateau model was used to calculate degradation rates and lag times for more than 150 individual oil components. Calculations were normalized to a conserved petroleum biomarker (30αβ-hopane). Half-lives ranged from about 3days for easily degradable compounds to about 60days for higher molecular weight aromatics. Rapid degradation was observed for BTEX, 2-3 ring PAHs, and n-alkanes below n-C23. The results in this experimental study showed good agreement with the n-alkane (n-C13 to n-C26) half-lives (0.6-9.5days) previously reported for the Deepwater Horizon plume samples and other laboratory studies with chemically dispersed Macondo oil conducted at low temperatures (<8°C). The responses of the microbial populations also were consistent with what was reported during the actual oil release, e.g. Colwellia, Cycloclasticus and Oceanospirillales (including the specific DWH Oceanospirillales) were present and increased in numbers indicating that they were degrading components of the oil. The consistency of the field and laboratory data indicate that these results could be used, in combination with other field and model data to characterize the dissipation of Macondo oil in the deepwater environment as part of the risk assessment estimations.

Oil Biodegradation and Oil-Degrading Microbial Populations in Marsh Sediments Impacted by Oil from the Deepwater Horizon Well Blowout

To study hydrocarbon biodegradation in marsh sediments impacted by Macondo oil from the Deepwater Horizon well blowout, we collected sediment cores 18-36 months after the accident at the marshes in Bay Jimmy (Upper Barataria Bay), Louisiana, United States. The highest concentrations of oil were found in the top 2 cm of sediment nearest the waterline at the shorelines known to have been heavily oiled. Although petroleum hydrocarbons were detectable, Macondo oil could not be identified below 8 cm in 19 of the 20 surveyed sites. At the one site where oil was detected below 8 cm, concentrations were low. Residual Macondo oil was already highly weathered at the start of the study, and the concentrations of individual saturated hydrocarbons and polycyclic aromatic hydrocarbons continued to decrease over the course of the study due to biodegradation. Desulfococcus oleovorans, Marinobacter hydrocarbonoclasticus, Mycobacterium vanbaalenii, and related mycobacteria were the most abundant oil-degrading microorganisms detected in the top 2 cm at the oiled sites. Relative populations of these taxa declined as oil concentrations declined. The diversity of the microbial community was low at heavily oiled sites compared to that of the unoiled reference sites. As oil concentrations decreased over time, microbial diversity increased and approached the diversity levels of the reference sites. These trends show that the oil continues to be biodegraded, and microbial diversity continues to increase, indicating ongoing overall ecological recovery.

Short-read, high-throughput sequencing technology for STR genotyping

DNA-based methods for human identification principally rely upon genotyping of short tandem repeat (STR) loci. Electrophoretic-based techniques for variable-length classification of STRs are universally utilized, but are limited in that they have relatively low throughput and do not yield nucleotide sequence information. High-throughput sequencing technology may provide a more powerful instrument for human identification, but is not currently validated for forensic casework. Here, we present a systematic method to perform high-throughput genotyping analysis of the Combined DNA Index System (CODIS) STR loci using short-read (150 bp) massively parallel sequencing technology. Open source reference alignment tools were optimized to evaluate PCR-amplified STR loci using a custom designed STR genome reference. Evaluation of this approach demonstrated that the 13 CODIS STR loci and amelogenin (AMEL) locus could be accurately called from individual and mixture samples. Sensitivity analysis showed that as few as 18,500 reads, aligned to an in silico referenced genome, were required to genotype an individual (>99% confidence) for the CODIS loci. The power of this technology was further demonstrated by identification of variant alleles containing single nucleotide polymorphisms (SNPs) and the development of quantitative measurements (reads) for resolving mixed samples.