Wastewater-based surveillance as a tool for public health action: SARS-CoV-2 and beyond.

Wastewater-based surveillance (WBS) has undergone dramatic advancement in the context of the coronavirus disease 2019 (COVID-19) pandemic. The power and potential of this platform technology were rapidly realized when it became evident that not only did WBS-measured SARS-CoV-2 RNA correlate strongly with COVID-19 clinical disease within monitored populations but also, in fact, it functioned as a leading indicator. Teams from across the globe rapidly innovated novel approaches by which wastewater could be collected from diverse sewersheds ranging from wastewater treatment plants (enabling community-level surveillance) to more granular locations including individual neighborhoods and high-risk buildings such as long-term care facilities (LTCF). Efficient processes enabled SARS-CoV-2 RNA extraction and concentration from the highly dilute wastewater matrix. Molecular and genomic tools to identify, quantify, and characterize SARS-CoV-2 and its various variants were adapted from clinical programs and applied to these mixed environmental systems. Novel data-sharing tools allowed this information to be mobilized and made immediately available to public health and government decision-makers and even the public, enabling evidence-informed decision-making based on local disease dynamics. WBS has since been recognized as a tool of transformative potential, providing near-real-time cost-effective, objective, comprehensive, and inclusive data on the changing prevalence of measured analytes across space and time in populations. However, as a consequence of rapid innovation from hundreds of teams simultaneously, tremendous heterogeneity currently exists in the SARS-CoV-2 WBS literature. This manuscript provides a state-of-the-art review of WBS as established with SARS-CoV-2 and details the current work underway expanding its scope to other infectious disease targets.

A Bayesian framework for modeling COVID-19 case numbers through longitudinal monitoring of SARS-CoV-2 RNA in wastewater.

Wastewater-based surveillance has become an important tool for research groups and public health agencies investigating and monitoring the COVID-19 pandemic and other public health emergencies including other pathogens and drug abuse. While there is an emerging body of evidence exploring the possibility of predicting COVID-19 infections from wastewater signals, there remain significant challenges for statistical modeling. Longitudinal observations of viral copies in municipal wastewater can be influenced by noisy datasets and missing values with irregular and sparse samplings. We propose an integrative Bayesian framework to predict daily positive cases from weekly wastewater observations with missing values via functional data analysis techniques. In a unified procedure, the proposed analysis models severe acute respiratory syndrome coronavirus-2 RNA wastewater signals as a realization of a smooth process with error and combines the smooth process with COVID-19 cases to evaluate the prediction of positive cases. We demonstrate that the proposed framework can achieve these objectives with high predictive accuracies through simulated and observed real data.

Surveillance for SARS-CoV-2 and its variants in wastewater of tertiary care hospitals correlates with increasing case burden and outbreaks.

Wastewater-based SARS-CoV-2 surveillance enables unbiased and comprehensive monitoring of defined sewersheds. We performed real-time monitoring of hospital wastewater that differentiated Delta and Omicron variants within total SARS-CoV-2-RNA, enabling correlation to COVID-19 cases from three tertiary-care facilities with >2100 inpatient beds in Calgary, Canada. RNA was extracted from hospital wastewater between August/2021 and January/2022, and SARS-CoV-2 quantified using RT-qPCR. Assays targeting R203M and R203K/G204R established the proportional abundance of Delta and Omicron, respectively. Total and variant-specific SARS-CoV-2 in wastewater was compared to data for variant specific COVID-19 hospitalizations, hospital-acquired infections, and outbreaks. Ninety-six percent (188/196) of wastewater samples were SARS-CoV-2 positive. Total SARS-CoV-2 RNA levels in wastewater increased in tandem with total prevalent cases (Delta plus Omicron). Variant-specific assessments showed this increase to be mainly driven by Omicron. Hospital-acquired cases of COVID-19 were associated with large spikes in wastewater SARS-CoV-2 and levels were significantly increased during outbreaks relative to nonoutbreak periods for total SARS-CoV2, Delta and Omicron. SARS-CoV-2 in hospital wastewater was significantly higher during the Omicron-wave irrespective of outbreaks. Wastewater-based monitoring of SARS-CoV-2 and its variants represents a novel tool for passive COVID-19 infection surveillance, case identification, containment, and potentially to mitigate viral spread in hospitals.

Tracking Emergence and Spread of SARS-CoV-2 Omicron Variant in Large and Small Communities by Wastewater Monitoring in Alberta, Canada.

Wastewater monitoring of SARS-CoV-2 enables early detection and monitoring of the COVID-19 disease burden in communities and can track specific variants of concern. We determined proportions of the Omicron and Delta variants across 30 municipalities covering >75% of the province of Alberta (population 4.5 million), Canada, during November 2021-January 2022. Larger cities Calgary and Edmonton exhibited more rapid emergence of Omicron than did smaller and more remote municipalities. Notable exceptions were Banff, a small international resort town, and Fort McMurray, a medium-sized northern community that has many workers who fly in and out regularly. The integrated wastewater signal revealed that the Omicron variant represented close to 100% of SARS-CoV-2 burden by late December, before the peak in newly diagnosed clinical cases throughout Alberta in mid-January. These findings demonstrate that wastewater monitoring offers early and reliable population-level results for establishing the extent and spread of SARS-CoV-2 variants.

Divergent Electrochemical Carboamidation of Cyclic Amines.

We developed an electrochemical carboamidation sequence that affords either cyclic ß-amidoamine products via direct functionalization or linear hydroxybisamide products via a ring opening pathway. The reaction pathway was dependent on the nature of the N-acyl activating group, with carbamate groups favoring direct isocyanide addition to the N-acyliminium ion intermediate and the benzoyl activating group favoring the ring opening-functionalization pathway. Both protocols are one-pot reaction sequences, have general applicability, and lead to peptide-like products of greatly increased molecular complexity.

Development of pyrimidone D1 dopamine receptor positive allosteric modulators.

MLS1082 is a structurally novel pyrimidone-based D1-like dopamine receptor positive allosteric modulator. Potentiation of D1 dopamine receptor (D1R) signaling is a therapeutic strategy for treating neurocognitive disorders. Here, we investigate the relationship between D1R potentiation and two prominent structural features of MLS1082, namely the pendant N-aryl and C-alkyl groups on the pyrimidone ring. To this end, we synthesized 24 new analogues and characterized their ability to potentiate dopamine signaling at the D1R and the closely related D5R. We identified structure-activity relationship trends for both aryl and alkyl modifications and our efforts afforded several analogues with improvements in activity. The most effective analogues demonstrated an approximately 8-fold amplification of dopamine-mediated D1R signaling. These findings advance the understanding of structural moieties underlying the activity of pyrimidone-based D1R positive allosteric modulators.

Discovery of sultam-containing small-molecule disruptors of the huntingtin-calmodulin protein-protein interaction.

The aberrant protein-protein interaction between calmodulin and mutant huntingtin protein in Huntington's disease patients has been found to contribute to Huntington's disease progression. A high-throughput screen for small molecules capable of disrupting this interaction revealed a sultam series as potent small-molecule disruptors. Diversification of the sultam scaffold afforded a set of 24 analogs or further evaluation. Several structure-activity trends within the analog set were found, most notably a negligible effect of absolute stereochemistry and a strong beneficial correlation with electron-withdrawing aromatic substituents. The most promising analogs were profiled for off-target effects at relevant kinases and, ultimately, one candidate molecule was evaluated for neuroprotection in a neuronal cell model of Huntington's disease.

Identification of Positive Allosteric Modulators of the D1 Dopamine Receptor That Act at Diverse Binding Sites.

The D1 dopamine receptor is linked to a variety of neuropsychiatric disorders and represents an attractive drug target for the enhancement of cognition in schizophrenia, Alzheimer disease, and other disorders. Positive allosteric modulators (PAMs), with their potential for greater selectivity and larger therapeutic windows, may represent a viable drug development strategy, as orthosteric D1 receptor agonists possess known clinical liabilities. We discovered two structurally distinct D1 receptor PAMs, MLS6585 and MLS1082, via a high-throughput screen of the NIH Molecular Libraries program small-molecule library. Both compounds potentiate dopamine-stimulated G protein- and ß-arrestin-mediated signaling and increase the affinity of dopamine for the D1 receptor with low micromolar potencies. Neither compound displayed any intrinsic agonist activity. Both compounds were also found to potentiate the efficacy of partial agonists. We tested maximally effective concentrations of each PAM in combination to determine if the compounds might act at separate or similar sites. In combination, MLS1082 + MLS6585 produced an additive potentiation of dopamine potency beyond that caused by either PAM alone for both ß-arrestin recruitment and cAMP accumulation, suggesting diverse sites of action. In addition, MLS6585, but not MLS1082, had additive activity with the previously described D1 receptor PAM "Compound B," suggesting that MLS1082 and Compound B may share a common binding site. A point mutation (R130Q) in the D1 receptor was found to abrogate MLS1082 activity without affecting that of MLS6585, suggesting this residue may be involved in the binding/activity of MLS1082 but not that of MLS6585. Together, MLS1082 and MLS6585 may serve as important tool compounds for the characterization of diverse allosteric sites on the D1 receptor as well as the development of optimized lead compounds for therapeutic use.

Synthesis of Kappa Opioid Antagonists Based On Pyrrolo[1,2-α]quinoxalinones Using an N-Arylation/Condensation/Oxidation Reaction Sequence.

The quinoxaline and quinoxalinone family of nitrogen heterocycles is present in molecules of therapeutic relevance for diverse applications ranging from infectious diseases to neuroscience targets. Here, we describe a general synthetic sequence to afford pyrrolo[1,2-α]quinoxalinones from commercially available starting materials and their use in preparing potential kappa opioid receptor antagonists. The biological data obtained from the latter set of compounds is briefly presented and discussed.

Decahydrobenzoquinolin-5-one sigma receptor ligands: Divergent development of both sigma 1 and sigma 2 receptor selective examples.

Analogues of the decahydrobenzoquinolin-5-one class of sigma (σ) receptor ligands were used to probe the structure-activity relationship trends for this recently discovered series of σ ligands. In all, 29 representatives were tested for σ and opioid receptor affinity, leading to the identification of compounds possessing improved σ1 selectivity and, for the first time in this series, examples possessing preferential σ2 affinity. Several structural features associated with these selectivity trends have been identified. Two analogues of improved selectivity were evaluated in a binding panel of 43 CNS-relevant targets to confirm their sigma receptor preference.

Potency enhancement of the κ-opioid receptor antagonist probe ML140 through sulfonamide constraint utilizing a tetrahydroisoquinoline motif.

Optimization of the sulfonamide-based kappa opioid receptor (KOR) antagonist probe molecule ML140 through constraint of the sulfonamide nitrogen within a tetrahydroisoquinoline moiety afforded a marked increase in potency. This strategy, when combined with additional structure-activity relationship exploration, has led to a compound only six-fold less potent than norBNI, a widely utilized KOR antagonist tool compound, but significantly more synthetically accessible. The new optimized probe is suitably potent for use as an in vivo tool to investigate the therapeutic potential of KOR antagonists.

Practical Electrochemical Anodic Oxidation of Polycyclic Lactams for Late Stage Functionalization.

Electrochemistry provides a powerful tool for the late-stage functionalization of complex lactams. A two-stage protocol for converting lactams, many of which can be prepared through the intramolecular Schmidt reaction of keto azides, is presented. In the first step, anodic oxidation in MeOH using a repurposed power source provides a convenient route to lactams bearing a methoxy group adjacent to nitrogen. Treatment of these intermediates with a Lewis acid in dichloromethane permits the regeneration of a reactive acyliminium ion that is then reacted with a range of nucleophilic species.

Primuline derivatives that mimic RNA to stimulate hepatitis C virus NS3 helicase-catalyzed ATP hydrolysis.

ATP hydrolysis fuels the ability of helicases and related proteins to translocate on nucleic acids and separate base pairs. As a consequence, nucleic acid binding stimulates the rate at which a helicase catalyzes ATP hydrolysis. In this study, we searched a library of small molecule helicase inhibitors for compounds that stimulate ATP hydrolysis catalyzed by the hepatitis C virus (HCV) NS3 helicase, which is an important antiviral drug target. Two compounds were found that stimulate HCV helicase-catalyzed ATP hydrolysis, both of which are amide derivatives synthesized from the main component of the yellow dye primuline. Both compounds possess a terminal pyridine moiety, which was critical for stimulation. Analogs lacking a terminal pyridine inhibited HCV helicase catalyzed ATP hydrolysis. Unlike other HCV helicase inhibitors, the stimulatory compounds differentiate between helicases isolated from various HCV genotypes and related viruses. The compounds only stimulated ATP hydrolysis catalyzed by NS3 purified from HCV genotype 1b. They inhibited helicases from other HCV genotypes (e.g. 1a and 2a) or related flaviviruses (e.g. Dengue virus). The stimulatory compounds interacted with HCV helicase in the absence of ATP with dissociation constants of about 2 µM. Molecular modeling and site-directed mutagenesis studies suggest that the stimulatory compounds bind in the HCV helicase RNA-binding cleft near key residues Arg-393, Glu-493, and Ser-231.

Chemotype-selective modes of action of κ-opioid receptor agonists.

The crystal structures of opioid receptors provide a novel platform for inquiry into opioid receptor function. The molecular determinants for activation of the κ-opioid receptor (KOR) were studied using a combination of agonist docking, functional assays, and site-directed mutagenesis. Eighteen positions in the putative agonist binding site of KOR were selected and evaluated for their effects on receptor binding and activation by ligands representing four distinct chemotypes: the peptide dynorphin A(1-17), the arylacetamide U-69593, and the non-charged ligands salvinorin A and the octahydroisoquinolinone carboxamide 1xx. Minimally biased docking of the tested ligands into the antagonist-bound KOR structure generated distinct binding modes, which were then evaluated biochemically and pharmacologically. Our analysis identified two types of mutations: those that affect receptor function primarily via ligand binding and those that primarily affect function. The shared and differential mechanisms of agonist binding and activation in KOR are further discussed. Usually, mutations affecting function more than binding were located at the periphery of the binding site and did not interact strongly with the various ligands. Analysis of the crystal structure along with the present results provide fundamental insights into the activation mechanism of the KOR and suggest that "functional" residues, along with water molecules detected in the crystal structure, may be directly involved in transduction of the agonist binding event into structural changes at the conserved rotamer switches, thus leading to receptor activation.

Development of functionally selective, small molecule agonists at kappa opioid receptors.

The kappa opioid receptor (KOR) is widely expressed in the CNS and can serve as a means to modulate pain perception, stress responses, and affective reward states. Therefore, the KOR has become a prominent drug discovery target toward treating pain, depression, and drug addiction. Agonists at KOR can promote G protein coupling and ßarrestin2 recruitment as well as multiple downstream signaling pathways, including ERK1/2 MAPK activation. It has been suggested that the physiological effects of KOR activation result from different signaling cascades, with analgesia being G protein-mediated and dysphoria being mediated through ßarrestin2 recruitment. Dysphoria associated with KOR activation limits the therapeutic potential in the use of KOR agonists as analgesics; therefore, it may be beneficial to develop KOR agonists that are biased toward G protein coupling and away from ßarrestin2 recruitment. Here, we describe two classes of biased KOR agonists that potently activate G protein coupling but weakly recruit ßarrestin2. These potent and functionally selective small molecule compounds may prove to be useful tools for refining the therapeutic potential of KOR-directed signaling in vivo.

Identification and analysis of hepatitis C virus NS3 helicase inhibitors using nucleic acid binding assays.

Typical assays used to discover and analyze small molecules that inhibit the hepatitis C virus (HCV) NS3 helicase yield few hits and are often confounded by compound interference. Oligonucleotide binding assays are examined here as an alternative. After comparing fluorescence polarization (FP), homogeneous time-resolved fluorescence (HTRF®; Cisbio) and AlphaScreen® (Perkin Elmer) assays, an FP-based assay was chosen to screen Sigma's Library of Pharmacologically Active Compounds (LOPAC) for compounds that inhibit NS3-DNA complex formation. Four LOPAC compounds inhibited the FP-based assay: aurintricarboxylic acid (ATA) (IC50=1.4 µM), suramin sodium salt (IC50=3.6 µM), NF 023 hydrate (IC50=6.2 µM) and tyrphostin AG 538 (IC50=3.6 µM). All but AG 538 inhibited helicase-catalyzed strand separation, and all but NF 023 inhibited replication of subgenomic HCV replicons. A counterscreen using Escherichia coli single-stranded DNA binding protein (SSB) revealed that none of the new HCV helicase inhibitors were specific for NS3h. However, when the SSB-based assay was used to analyze derivatives of another non-specific helicase inhibitor, the main component of the dye primuline, it revealed that some primuline derivatives (e.g. PubChem CID50930730) are up to 30-fold more specific for HCV NS3h than similarly potent HCV helicase inhibitors.

Synthesis and receptor profiling of Stemona alkaloid analogues reveal a potent class of sigma ligands.

Reported biological activities of Stemona natural products, such as antitussive activity, inspired the development of synthetic methods to access several alkaloids within this family and in so doing develop a general route to the core skeleta shared by the class of natural products. The chemistry was subsequently adapted to afford a series of analogue sets bearing simplified, diverse Stemona-inspired skeleta. Over 100 of these analogues were subjected to general G protein-coupled receptor profiling along with the known antitussive compound, neostenine; this led to the identification of hit compounds targeting several receptor types. The particularly rich hit subset for sigma receptors was expanded with two focused library sets, which resulted in the discovery of a fully synthetic, potent chemotype of sigma ligands. This collaborative effort combined the development of synthetic methods with extensive, flexible screening resources and exemplifies the role of natural products in bioactivity mining.

Wastewater-based surveillance can be used to model COVID-19-associated workforce absenteeism.

Wastewater-based surveillance (WBS) of infectious diseases is a powerful tool for understanding community COVID-19 disease burden and informing public health policy. The potential of WBS for understanding COVID-19's impact in non-healthcare settings has not been explored to the same degree. Here we examined how SARS-CoV-2 measured from municipal wastewater treatment plants (WWTPs) correlates with workforce absenteeism. SARS-CoV-2 RNA N1 and N2 were quantified three times per week by RT-qPCR in samples collected at three WWTPs servicing Calgary and surrounding areas, Canada (1.4 million residents) between June 2020 and March 2022. Wastewater trends were compared to workforce absenteeism using data from the largest employer in the city (>15,000 staff). Absences were classified as being COVID-19-related, COVID-19-confirmed, and unrelated to COVID-19. Poisson regression was performed to generate a prediction model for COVID-19 absenteeism based on wastewater data. SARS-CoV-2 RNA was detected in 95.5 % (85/89) of weeks assessed. During this period 6592 COVID-19-related absences (1896 confirmed) and 4524 unrelated absences COVID-19 cases were recorded. A generalized linear regression using a Poisson distribution was performed to predict COVID-19-confirmed absences out of the total number of absent employees using wastewater data as a leading indicator (P < 0.0001). The Poisson regression with wastewater as a one-week leading signal has an Akaike information criterion (AIC) of 858, compared to a null model (excluding wastewater predictor) with an AIC of 1895. The likelihood-ratio test comparing the model with wastewater signal with the null model shows statistical significance (P < 0.0001). We also assessed the variation of predictions when the regression model was applied to new data, with the predicted values and corresponding confidence intervals closely tracking actual absenteeism data. Wastewater-based surveillance has the potential to be used by employers to anticipate workforce requirements and optimize human resource allocation in response to trackable respiratory illnesses like COVID-19.

Wastewater surveillance monitoring of SARS-CoV-2 variants of concern and dynamics of transmission and community burden of COVID-19.

Wastewater-based surveillance is a valuable approach for monitoring COVID-19 at community level. Monitoring SARS-CoV-2 variants of concern (VOC) in wastewater has become increasingly relevant when clinical testing capacity and case-based surveillance are limited. In this study, we ascertained the turnover of six VOC in Alberta wastewater from May 2020 to May 2022. Wastewater samples from nine wastewater treatment plants across Alberta were analysed using VOC-specific RT-qPCR assays. The performance of the RT-qPCR assays in identifying VOC in wastewater was evaluated against next generation sequencing. The relative abundance of each VOC in wastewater was compared to positivity rate in COVID-19 testing. VOC-specific RT-qPCR assays performed comparatively well against next generation sequencing; concordance rates ranged from 89% to 98% for detection of Alpha, Beta, Gamma, Omicron BA.1 and Omicron BA.2, with a slightly lower rate of 85% for Delta (p < 0.01). Elevated relative abundance of Alpha, Delta, Omicron BA.1 and BA.2 were each associated with increased COVID-19 positivity rate. Alpha, Delta and Omicron BA.2 reached 90% relative abundance in wastewater within 80, 111 and 62 days after their initial detection, respectively. Omicron BA.1 increased more rapidly, reaching a 90% relative abundance in wastewater after 35 days. Our results from VOC surveillance in wastewater correspond with clinical observations that Omicron is the VOC with highest disease burden over the shortest period in Alberta to date. The findings suggest that changes in relative abundance of a VOC in wastewater can be used as a supplementary indicator to track and perhaps predict COVID-19 burden in a population.

Campus node-based wastewater surveillance enables COVID-19 case localization and confirms lower SARS-CoV-2 burden relative to the surrounding community.

Wastewater-based surveillance (WBS) has been established as a powerful tool that can guide health policy at multiple levels of government. However, this approach has not been well assessed at more granular scales, including large work sites such as University campuses. Between August 2021 and April 2022, we explored the occurrence of SARS-CoV-2 RNA in wastewater using qPCR assays from multiple complimentary sewer catchments and residential buildings spanning the University of Calgary's campus and how this compared to levels from the municipal wastewater treatment plant servicing the campus. Real-time contact tracing data was used to evaluate an association between wastewater SARS-CoV-2 burden and clinically confirmed cases and to assess the potential of WBS as a tool for disease monitoring across worksites. Concentrations of wastewater SARS-CoV-2 N1 and N2 RNA varied significantly across six sampling sites - regardless of several normalization strategies - with certain catchments consistently demonstrating values 1-2 orders higher than the others. Relative to clinical cases identified in specific sewersheds, WBS provided one-week leading indicator. Additionally, our comprehensive monitoring strategy enabled an estimation of the total burden of SARS-CoV-2 for the campus per capita, which was significantly lower than the surrounding community (p≤0.001). Allele-specific qPCR assays confirmed that variants across campus were representative of the community at large, and at no time did emerging variants first debut on campus. This study demonstrates how WBS can be efficiently applied to locate hotspots of disease activity at a very granular scale, and predict disease burden across large, complex worksites.