Inter-institutional laboratory standardization for SARS-CoV-2 surveillance through wastewater-based epidemiology applied to Mexico City.

Objectives: Wastewater-based surveillance applied to SARS-CoV-2 viral load quantification for COVID-19 has become one of the most relevant complementary tools in epidemiologic prevention programs worldwide. However, this valuable decision-making tool still requires fine-tuning to produce comparable results between laboratories, especially when applied to the surveillance of megacities. Methods: Six laboratories across Mexico and one from the United States executed an interlaboratory study to set up a singular standardized protocol considering method cost, installed infrastructure, materials available, and supply availability for SARS-CoV-2 quantification from five Mexico City sampling sites across this megacity. Results: Comparable data from processing outcomes in the Mexican laboratories and in the external international laboratory serve as a validating data source. The Bland-Altman comparison showed consistency, with cycle threshold values within ±1.96 SD of SARS-CoV-2 genetic copies for the standard curve quantification, with a mismatch of two laboratories. In addition, MS2 bacteriophage recovery rates varied between 35% and 67% among all participating laboratories. Finally, the efficiency of viral genetic material recovered from all participating laboratories varied between 65% and 93% for the participating laboratories. Conclusion: This work lays the foundation for extensive and continuous wastewater-based surveillance application across independent Mexican laboratories in a time- and resource-effective manner.

Nine Rhizobium phage genomes recovered from wastewater in Tempe, AZ, October 2019-March 2020.

We describe nine Rhizobium microvirus genomes identified in wastewater in Tempe, AZ, USA, between October 2019 and March 2020. The major capsid protein (MCP) encoded in these genomes phylogenetically cluster together and are distinct from the MCPs of Rhizobium microviruses identified in Mexico and Argentina.

Exploring Canine Picornavirus Diversity in the USA Using Wastewater Surveillance: From High-Throughput Genomic Sequencing to Immuno-Informatics and Capsid Structure Modeling.

The SARS-CoV-2 pandemic resulted in a scale-up of viral genomic surveillance globally. However, the wet lab constraints (economic, infrastructural, and personnel) of translating novel virus variant sequence information to meaningful immunological and structural insights that are valuable for the development of broadly acting countermeasures (especially for emerging and re-emerging viruses) remain a challenge in many resource-limited settings. Here, we describe a workflow that couples wastewater surveillance, high-throughput sequencing, phylogenetics, immuno-informatics, and virus capsid structure modeling for the genotype-to-serotype characterization of uncultivated picornavirus sequences identified in wastewater. Specifically, we analyzed canine picornaviruses (CanPVs), which are uncultivated and yet-to-be-assigned members of the family Picornaviridae that cause systemic infections in canines. We analyzed 118 archived (stored at -20 °C) wastewater (WW) samples representing a population of ~700,000 persons in southwest USA between October 2019 to March 2020 and October 2020 to March 2021. Samples were pooled into 12 two-liter volumes by month, partitioned (into filter-trapped solids [FTSs] and filtrates) using 450 nm membrane filters, and subsequently concentrated to 2 mL (1000×) using 10,000 Da MW cutoff centrifugal filters. The 24 concentrates were subjected to RNA extraction, CanPV complete capsid single-contig RT-PCR, Illumina sequencing, phylogenetics, immuno-informatics, and structure prediction. We detected CanPVs in 58.3% (14/24) of the samples generated 13,824,046 trimmed Illumina reads and 27 CanPV contigs. Phylogenetic and pairwise identity analyses showed eight CanPV genotypes (intragenotype divergence <14%) belonging to four clusters, with intracluster divergence of <20%. Similarity analysis, immuno-informatics, and virus protomer and capsid structure prediction suggested that the four clusters were likely distinct serological types, with predicted cluster-distinguishing B-cell epitopes clustered in the northern and southern rims of the canyon surrounding the 5-fold axis of symmetry. Our approach allows forgenotype-to-serotype characterization of uncultivated picornavirus sequences by coupling phylogenetics, immuno-informatics, and virus capsid structure prediction. This consequently bypasses a major wet lab-associated bottleneck, thereby allowing resource-limited settings to leapfrog from wastewater-sourced genomic data to valuable immunological insights necessary for the development of prophylaxis and other mitigation measures.

Wastewater and clinical surveillance of respiratory viral pathogens on a university campus.

Areas of dense population congregation are prone to experience respiratory virus outbreaks. We monitored wastewater and clinic patients for the presence of respiratory viruses on a large, public university campus. Campus sewer systems were monitored in 16 locations for the presence of viruses using next generation sequencing over 22 weeks in 2023. During this period, we detected a surge in human adenovirus (HAdV) levels in wastewater. Hence, we initiated clinical surveillance at an on-campus clinic from patients presenting with acute respiratory infection. From whole genome sequencing of 123 throat and/or nasal swabs collected, we identified an outbreak of HAdV, specifically of HAdV-E4 and HAdV-B7 genotypes overlapping in time. The temporal dynamics and proportions of HAdV genotypes found in wastewater were corroborated in clinical infections. We tracked specific single nucleotide polymorphisms (SNPs) found in clinical virus sequences and showed that they arose in wastewater signals concordant with the time of clinical presentation, linking community transmission of HAdV to the outbreak. This study demonstrates how wastewater-based epidemiology can be integrated with surveillance at ambulatory healthcare settings to monitor areas prone to respiratory virus outbreaks and provide public health guidance.

Carcinogenic formaldehyde in U.S. residential buildings: Mass inventories, human health impacts, and associated healthcare costs.

Formaldehyde, a human carcinogen, is formulated into building materials in the U.S. and worldwide. We used literature information and mass balances to obtain order-of-magnitude estimates of formaldehyde inventories in U.S. residential buildings as well as associated exposures, excess morbidity, and healthcare costs along with other economic ramifications. Use of formaldehyde in building materials dates to the 1940s and continues today unabated, despite its international classification in 2004 as a human carcinogen. Global production of formaldehyde was about 32 million metric tons (MMT) in 2006. In the U.S., 5.7 ± 0.05 to 7.4 ± 0.125 MMT of formaldehyde were produced annually from 2006 to 2022, with 65 ± 5 % of this mass (3.7 ± 0.03 to 4.8 ± 0.08 MMT) entering building materials. For a typical U.S. residential building constructed in 2022, we determined an average total mass of formaldehyde containing chemicals of 48.2 ± 10.1 kg, equivalent to 207 ± 40 g of neat formaldehyde per housing unit. When extrapolated to the entire U.S. housing stock, this equates to 29,800 ± 5760 metric tons of neat formaldehyde. If the health threshold in indoor air of 0.1 mg/m3 is never surpassed in a residential building, safe venting of embedded formaldehyde would take years. Using reported indoor air exceedances, up to 645 ± 33 excess cancer cases may occur U.S. nationwide annually generating up to US$65 M in cancer treatment costs alone, not counting ~16,000 ± 1000 disability adjusted life-years. Other documents showed health effects of formaldehyde exist, but could not be quantified reliably, including sick building syndrome outcomes such as headache, asthma, and various respiratory illnesses. Opportunities to improve indoor air exposure assessments are discussed with special emphasis on monitoring of building wastewater. Safer alternatives to formaldehyde in building products exist and are recommended for future use.

Seasonality of respiratory, enteric, and urinary viruses revealed by wastewater genomic surveillance.

Wastewater surveillance can reveal population-level infectious disease burden and emergent public health threats can be reliably assessed through wastewater surveillance. While molecular methods for wastewater monitoring of microorganisms have traditionally relied on PCR-based approaches, next-generation sequencing (NGS) can provide deeper insights via genomic analyses of multiple diverse pathogens. We conducted a year-long sequencing surveillance of 1,408 composite wastewater samples collected from 12 neighborhood-level access points in the greater Tempe area, Arizona, USA, and show that variation in wastewater viruses is driven by seasonal time and location. The temporal dynamics of viruses in wastewater were influenced cyclically, with the most dissimilarity between samples 23 weeks apart (i.e., winter vs summer, spring vs fall). We identified diverse urinary and enteric viruses including polyomaviruses, astroviruses, and noroviruses, and showed that their genotypes/subtypes shifted across seasons. We show that while wastewater data of certain respiratory viruses like severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) strongly correlate with clinical case rates, laboratory-reported case incidences were discordant with surges of high viral load in wastewater for other viruses like human coronavirus 229E. These results demonstrate the utility of wastewater sequencing for informing decision-making in public health.IMPORTANCEWastewater surveillance can provide insights into the spread of pathogens in communities. Advances in next-generation sequencing (NGS) methodologies allow for more precise detection of viruses in wastewater. Long-term wastewater surveillance of viruses is an important tool for public health preparedness. This system can act as a public health observatory that gives real-time early warning for infectious disease outbreaks and improved response times.

Encrypted data-sharing for preserving privacy in wastewater-based epidemiology.

The rapidly expanding use of wastewater for public health surveillance requires new strategies to protect privacy rights, while data are collected at increasingly discrete geospatial scales, i.e., city, neighborhood, campus, and building-level. Data collected at high geospatial resolution can inform on labile, short-lived biomarkers, thereby making wastewater-derived data both more actionable and more likely to cause privacy concerns and stigmatization of subpopulations. Additionally, data sharing restrictions among neighboring cities and communities can complicate efforts to balance public health protections with citizens' privacy. Here, we have created an encrypted framework that facilitates the sharing of sensitive population health data among entities that lack trust for one another (e.g., between adjacent municipalities with different governance of health monitoring and data sharing). We demonstrate the utility of this approach with two real-world cases. Our results show the feasibility of sharing encrypted data between two municipalities and a laboratory, while performing secure private computations for wastewater-based epidemiology (WBE) with high precision, fast speeds, and low data costs. This framework is amenable to other computations used by WBE researchers including population normalized mass loads, fecal indicator normalizations, and quality control measures. The Centers for Disease Control and Prevention's National Wastewater Surveillance System shows ∼8 % of the records attributed to collection before the wastewater treatment plant, illustrating an opportunity to further expand currently limited community-level sampling and public health surveillance through security and responsible data-sharing as outlined here.

Prevalence rates of neurodegenerative diseases versus human exposures to heavy metals across the United States.

Novel means are needed to identify individuals and subpopulations susceptible to and afflicted by neurodegenerative diseases (NDDs). This study aimed to utilize geographic distribution of heavy metal sources and sinks to investigate a potential human health risk of developing NDDs. Known or hypothesized environmental factors driving disease prevalence of Alzheimer's Disease (AD), Parkinson's Disease (PD), and amyotrophic lateral sclerosis (ALS) are heavy metals, including arsenic (As), cadmium (Cd), manganese (Mn) and mercury (Hg). Lead (Pb) has been associated with AD and ALS. Analyzable mediums of human exposure to heavy metals (i.e., toxic metals and metalloids), or proxies thereof, include infant blood, topsoil, sewage sludge, and well water. U.S. concentrations of heavy metals in topsoil, sewage sludge, well water, and infant blood were mapped and compared to prevalence rates of major NDDs. Data from federal and state agencies (i.e., CDC, EPA, and the US Geological Survey) on heavy metal concentrations, age distribution, and NDD prevalence rates were geographically represented and statistically analyzed to quantify possible correlations. Aside from an expected significant association between NDD prevalence and age (p < 0.0001), we found significant associations between the prevalence of the sum of three major NDDs with: Pb in topsoil (p = 0.0433); Cd (p < 0.0001) and Pb (p < 0.0001) in sewage sludge; Pb in infant blood (p < 0.0001). Concentrations in sewage sludge of Cd and Pb were significantly correlated with NDD prevalence rates with an odds ratio of 2.91 (2.04, 4.225 95%CI) and 4.084 (3.14, 5.312 95%CI), respectively. The presence of toxic metals in the U.S. environment in multiple matrices, including sewage sludge, was found to be significantly associated with NDD prevalence. This is the first use of sewage sludge as an environmental proxy matrix to infer risk of developing NDDs.

Literature review and meta-analysis of environmental toxins associated with increased risk of Parkinson's disease.

Parkinson's disease (PD) is a neurodegenerative disorder and leading cause of death worldwide, whose pathogenesis has been linked to toxic environmental exposures. We used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines (i) to compile, and group by exposure setting (non-specified general; residential; occupational), environmental factors reported to modulate the risk of developing PD and (ii) to map and geospatially analyze global regions of both research activity and paucity. Among the broader environmental settings, occupational exposures had the highest average odds ratio value at 3.82, followed by general (non-specified or mixed) exposures at 3.07, and residential exposures at 2.36. Occupational exposure to industrial toxins was the highest ranked subset of exposures with an odds ratio of 10.74. Among the studies meeting the inclusion criteria, 75 % were conducted in Europe or the Western United States. The number of individuals partaking per study ranged from a high of 55,585 (Taiwan) to a low of 233 (Faroe Islands), with a mean of n = 14,462. The top three environmental factors associated with high odds ratios for increased risk of developing PD were (i) exposure to dyes (25.33), (ii) methylene chloride (16.5) and specifically in adult men (iii) consumption of fatty whale meat (10.57), which is known to harbor a broad spectrum of so called persistent, bioaccumulative, toxic (PBT) pollutants. Geospatially, the highest odds ratio values were identified in European countries, whereas notable data gaps were revealed for South America, Australia, Africa, and the majority of Asia with the exception of Taiwan. Whereas occupational exposures to industrial chemicals, such as harmful dyes and methylene chloride, ranked highest in risk values, available data suggest notable opportunities for reducing PD cases globally by limiting harmful environmental exposures to a spectrum of toxic chemicals, particularly via the food intake route. Thus, current efforts in improving environmental quality globally by limiting toxic emission may deliver the added benefit of helping to reign in PD. Agents of concern in this respect include pesticides (e.g., paraquat, demeton, monocrotophos), particulate matter associated with air pollution, and a spectrum of organic and inorganic neurotoxins including heavy metals.

Human adenovirus outbreak at a university campus monitored by wastewater and clinical surveillance.

Areas of dense population congregation are prone to experience respiratory virus outbreaks. We monitored wastewater and clinic patients for the presence of respiratory viruses on a large, public university campus. Campus sewer systems were monitored in 16 locations for the presence of viruses using next generation sequencing over 22 weeks in 2023. During this period, we detected a surge in human adenovirus (HAdV) levels in wastewater. Hence, we initiated clinical surveillance at an on-campus clinic from patients presenting with acute respiratory infection. From whole genome sequencing of 123 throat and/or nasal swabs collected, we identified an outbreak of HAdV, specifically of HAdV-E4 and HAdV-B7 genotypes overlapping in time. The temporal dynamics and proportions of HAdV genotypes found in wastewater were corroborated in clinical infections. We tracked specific single nucleotide polymorphisms (SNPs) found in clinical virus sequences and showed that they arose in wastewater signals concordant with the time of clinical presentation, linking community transmission of HAdV to the outbreak. This study demonstrates how wastewater-based epidemiology can be integrated with surveillance at ambulatory healthcare settings to monitor areas prone to respiratory virus outbreaks and provide public health guidance.

Workflow to facilitate the detection of new psychoactive substances and drugs of abuse in influent urban wastewater.

The complexity around the dynamic markets for new psychoactive substances (NPS) forces researchers to develop and apply innovative analytical strategies to detect and identify them in influent urban wastewater. In this work a comprehensive suspect screening workflow following liquid chromatography - high resolution mass spectrometry analysis was established utilising the open-source InSpectra data processing platform and the HighResNPS library. In total, 278 urban influent wastewater samples from 47 sites in 16 countries were collected to investigate the presence of NPS and other drugs of abuse. A total of 50 compounds were detected in samples from at least one site. Most compounds found were prescription drugs such as gabapentin (detection frequency 79%), codeine (40%) and pregabalin (15%). However, cocaine was the most found illicit drug (83%), in all countries where samples were collected apart from the Republic of Korea and China. Eight NPS were also identified with this protocol: 3-methylmethcathinone 11%), eutylone (6%), etizolam (2%), 3-chloromethcathinone (4%), mitragynine (6%), phenibut (2%), 25I-NBOH (2%) and trimethoxyamphetamine (2%). The latter three have not previously been reported in municipal wastewater samples. The workflow employed allowed the prioritisation of features to be further investigated, reducing processing time and gaining in confidence in their identification.

Wastewater-based monitoring of the nitazene analogues: First detection of protonitazene in wastewater.

Synthetic opioids, particularly the nitazene analogues class, have become a public health concern due to their high potency. Wastewater-based epidemiology can detect community use of these compounds. The objective of this work was to detect nitazene analogues in wastewater from samples collected from eight sites in the United States. Influent wastewater samples were collected from eight sites in seven states (Arizona, Oregon, New Mexico, Illinois, New Jersey, Washington and Georgia) in the United States. Samples were collected from each site on three days between 27 December 2022 and 4 January 2023, acidified on collection, stored frozen and shipped to Arizona State University (Tempe, AZ) for sample processing. Samples were then shipped to The University of Queensland (Brisbane, Australia) for sample analysis. Protonitazene was found in samples collected from two sites in Washington and Illinois. The concentration was estimated up to 0.5 ng/L, with estimated excreted mass loads up to 0.3 mg/day/1000 people. This work has shown that it is possible to detect nitazene analogues in wastewater using a combination of sample pre-concentration and sensitive instrumentation, thereby further expanding the utility of wastewater-based epidemiology.

Direct detection of canine picornavirus complete coding sequence in wastewater using long-range reverse-transcriptase polymerase chain reaction and long-read sequencing.

We describe four complete coding sequence (cCDS) of canine picornavirus from wastewater in Arizona, USA detected by coupling cCDS single-contig (∼7.5 kb) reverse-transcriptase polymerase chain reaction (RT-PCR) and low-cost long-read high-throughput sequencing. For viruses of medical/veterinary importance, this workflow expands possibilities of wastewater based genomic epidemiology for exploring virus evolutionary dynamics especially in low-resource settings.

Wastewater surveillance for bacterial targets: current challenges and future goals.

Wastewater-based epidemiology (WBE) expanded rapidly in response to the COVID-19 pandemic. As the public health emergency has ended, researchers and practitioners are looking to shift the focus of existing wastewater surveillance programs to other targets, including bacteria. Bacterial targets may pose some unique challenges for WBE applications. To explore the current state of the field, the National Science Foundation-funded Research Coordination Network (RCN) on Wastewater Based Epidemiology for SARS-CoV-2 and Emerging Public Health Threats held a workshop in April 2023 to discuss the challenges and needs for wastewater bacterial surveillance. The targets and methods used in existing programs were diverse, with twelve different targets and nine different methods listed. Discussions during the workshop highlighted the challenges in adapting existing programs and identified research gaps in four key areas: choosing new targets, relating bacterial wastewater data to human disease incidence and prevalence, developing methods, and normalizing results. To help with these challenges and research gaps, the authors identified steps the larger community can take to improve bacteria wastewater surveillance. This includes developing data reporting standards and method optimization and validation for bacterial programs. Additionally, more work is needed to understand shedding patterns for potential bacterial targets to better relate wastewater data to human infections. Wastewater surveillance for bacteria can help provide insight into the underlying prevalence in communities, but much work is needed to establish these methods.IMPORTANCEWastewater surveillance was a useful tool to elucidate the burden and spread of SARS-CoV-2 during the pandemic. Public health officials and researchers are interested in expanding these surveillance programs to include bacterial targets, but many questions remain. The NSF-funded Research Coordination Network for Wastewater Surveillance of SARS-CoV-2 and Emerging Public Health Threats held a workshop to identify barriers and research gaps to implementing bacterial wastewater surveillance programs.

Enhanced detection of mpox virus in wastewater using a pre-amplification approach: A pilot study informing population-level monitoring of low-titer pathogens.

A recent outbreak of the mpox virus (MPXV) occurred in non-endemic regions of the world beginning in May 2022. Pathogen surveillance systems faced pressure to quickly establish response protocols, offering an opportunity to employ wastewater-based epidemiology (WBE) for population-level monitoring. The pilot study reported herein aimed to: (i) develop a reliable protocol for MPXV DNA detection in wastewater which would reduce false negative reporting, (ii) test this protocol on wastewater from various regions across the United States, and (iii) conduct a state of the science review of the current literature reporting on experimental methods for MPXV detection using WBE. Twenty-four-hour composite samples of untreated municipal wastewater were collected from the states of New Jersey, Georgia, Illinois, Texas, Arizona, and Washington beginning July 3rd, 2022 through October 16th, 2022 (n = 60). Samples underwent vacuum filtration, DNA extraction from captured solids, MPXV DNA pre-amplification, and qPCR analysis. Of the 60 samples analyzed, a total of eight (13%) tested positive for MPXV in the states of Washington, Texas, New Jersey, and Illinois. The presence of clade IIb MPXV DNA in these samples was confirmed via Sanger sequencing and integration of pre-amplification prior to qPCR decreased the rate of false negative detections by 87% as compared to qPCR analysis alone. Wastewater-derived detections of MPXV were compared to clinical datasets, with 50% of detections occurring as clinical cases were increasing/peaking and 50% occurring as clinical cases waned. Results from the literature review (n = 9 studies) revealed successful strategies for the detection of MPXV DNA in wastewater, however also emphasized a need for further method optimization and standardization. Overall, this work highlights the use of pre-amplification prior to qPCR detection as a means to capture the presence of MPXV DNA in community wastewater and offers guidance for monitoring low-titer pathogens via WBE.

Three years of wastewater surveillance for new psychoactive substances from 16 countries.

The proliferation of new psychoactive substances (NPS) over recent years has made their surveillance complex. The analysis of raw municipal influent wastewater can allow a broader insight into community consumption patterns of NPS. This study examines data from an international wastewater surveillance program that collected and analysed influent wastewater samples from up to 47 sites in 16 countries between 2019 and 2022. Influent wastewater samples were collected over the New Year period and analysed using validated liquid chromatography - mass spectrometry methods. Over the three years, a total of 18 NPS were found in at least one site. Synthetic cathinones were the most found class followed by phenethylamines and designer benzodiazepines. Furthermore, two ketamine analogues, one plant based NPS (mitragynine) and methiopropamine were also quantified across the three years. This work demonstrates that NPS are used across different continents and countries with the use of some more evident in particular regions. For example, mitragynine has highest mass loads in sites in the United States, while eutylone and 3-methylmethcathinone increased considerably in New Zealand and in several European countries, respectively. Moreover, 2F-deschloroketamine, an analogue of ketamine, has emerged more recently and could be quantified in several sites, including one in China, where it is considered as one of the drugs of most concern. Finally, some NPS were detected in specific regions during the initial sampling campaigns and spread to additional sites by the third campaign. Hence, wastewater surveillance can provide an insight into temporal and spatial trends of NPS use.

Quaternary Ammonium Compounds: A Chemical Class of Emerging Concern.

Quaternary ammonium compounds (QACs), a large class of chemicals that includes high production volume substances, have been used for decades as antimicrobials, preservatives, and antistatic agents and for other functions in cleaning, disinfecting, personal care products, and durable consumer goods. QAC use has accelerated in response to the COVID-19 pandemic and the banning of 19 antimicrobials from several personal care products by the US Food and Drug Administration in 2016. Studies conducted before and after the onset of the pandemic indicate increased human exposure to QACs. Environmental releases of these chemicals have also increased. Emerging information on adverse environmental and human health impacts of QACs is motivating a reconsideration of the risks and benefits across the life cycle of their production, use, and disposal. This work presents a critical review of the literature and scientific perspective developed by a multidisciplinary, multi-institutional team of authors from academia, governmental, and nonprofit organizations. The review evaluates currently available information on the ecological and human health profile of QACs and identifies multiple areas of potential concern. Adverse ecological effects include acute and chronic toxicity to susceptible aquatic organisms, with concentrations of some QACs approaching levels of concern. Suspected or known adverse health outcomes include dermal and respiratory effects, developmental and reproductive toxicity, disruption of metabolic function such as lipid homeostasis, and impairment of mitochondrial function. QACs' role in antimicrobial resistance has also been demonstrated. In the US regulatory system, how a QAC is managed depends on how it is used, for example in pesticides or personal care products. This can result in the same QACs receiving different degrees of scrutiny depending on the use and the agency regulating it. Further, the US Environmental Protection Agency's current method of grouping QACs based on structure, first proposed in 1988, is insufficient to address the wide range of QAC chemistries, potential toxicities, and exposure scenarios. Consequently, exposures to common mixtures of QACs and from multiple sources remain largely unassessed. Some restrictions on the use of QACs have been implemented in the US and elsewhere, primarily focused on personal care products. Assessing the risks posed by QACs is hampered by their vast structural diversity and a lack of quantitative data on exposure and toxicity for the majority of these compounds. This review identifies important data gaps and provides research and policy recommendations for preserving the utility of QAC chemistries while also seeking to limit adverse environmental and human health effects.

Impact of LC-MS/MS quantification methods on analytical results by example of nationwide U.S. environmental samples.

Although different quantification methods are extensively used in environmental chemistry, the impact of the choice of method on the quality and range of analytical results is understudied. This two-part study consists of (a) in-lab evaluation and (b) a traditional meta-analysis (n = 66) of commonly used quantification methods): (i) external calibration; (ii) isotope dilution method with authentic target analogs; (iii) isotope dilution with non-target standards; and (iv) standard addition prior to LC-MS/MS in liquid chromatography tandem mass spectrometry (LC-MS/MS) by example of antibiotics in sewage sludge from across the U.S. Using method (i) as the benchmark quantification method for the antibiotic erythromycin in biosolids, other quantification methods resulted in an overestimation (110-450 %) or an underestimation (10-60 %). Using the method (iv) as the benchmark for other compounds resulted in an overestimation (101-14,700 %) or an underestimation (6-98 %). Matrix effects were also observed and were dependent on the matrix and analyte type. For example, in the case of erythromycin, all sample matrices showed signal suppression. This study showed that in the absence of isotopically labeled analogs, the most accurate alternate quantification method may need to be experimentally determined depending on the analyte. Analysis of published literature on pharmaceuticals in sewage sludge indicated that isotope dilution with authentic target analog is most commonly used, followed by non-target isotope standards, standard addition, and finally external calibration.

Rhizobium Phage-Like Microvirus Genome Sequence Identified in Wastewater in Arizona, USA, in November 2020 Encodes an Endolysin and a Putative Multiheme Cytochrome c-like Protein.

We describe the genome (4,696 nucleotides [GC content, 56%; coverage, 3,641×) of MAZ-Nov-2020, a microvirus identified from municipal wastewater in Maricopa County, Arizona, USA, in November 2020. The MAZ-Nov-2020 genome encodes major capsid protein, endolysin, replication initiator protein, and two hypothetical proteins, one of which was predicted to likely be a membrane-associated multiheme cytochrome c.