Wastewater-Based Estimation of the Effective Reproductive Number of SARS-CoV-2

BACKGROUND

The effective reproductive number, R e , is a critical indicator to monitor disease dynamics, inform regional and national policies, and estimate the effectiveness of interventions. It describes the average number of new infections caused by a single infectious person through time. To date, R e estimates are based on clinical data such as observed cases, hospitalizations, and/or deaths. These estimates are temporarily biased when clinical testing or reporting strategies change.

OBJECTIVES

We show that the dynamics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA in wastewater can be used to estimate R e in near real time, independent of clinical data and without the associated biases.

METHODS

We collected longitudinal measurements of SARS-CoV-2 RNA in wastewater in Zurich, Switzerland, and San Jose, California, USA. We combined this data with information on the temporal dynamics of shedding (the shedding load distribution) to estimate a time series proportional to the daily COVID-19 infection incidence. We estimated a wastewater-based R e from this incidence.

RESULTS

The method to estimate R e from wastewater worked robustly on data from two different countries and two wastewater matrices. The resulting estimates were as similar to the R e estimates from case report data as R e estimates based on observed cases, hospitalizations, and deaths are among each other. We further provide details on the effect of sampling frequency and the shedding load distribution on the ability to infer R e .

DISCUSSION

To our knowledge, this is the first time R e has been estimated from wastewater. This method provides a low-cost, rapid, and independent way to inform SARS-CoV-2 monitoring during the ongoing pandemic and is applicable to future wastewater-based epidemiology targeting other pathogens. https://doi.org/10.1289/EHP10050.

Wastewater-Based Estimation of the Effective Reproductive Number of SARS-CoV-2

BACKGROUND

The effective reproductive number, Re, is a critical indicator to monitor disease dynamics, inform regional and national policies, and estimate the effectiveness of interventions. It describes the average number of new infections caused by a single infectious person through time. To date, Re estimates are based on clinical data such as observed cases, hospitalizations, and/or deaths. These estimates are temporarily biased when clinical testing or reporting strategies change.

OBJECTIVES

We show that the dynamics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA in wastewater can be used to estimate Re in near real time, independent of clinical data and without the associated biases.

METHODS

We collected longitudinal measurements of SARS-CoV-2 RNA in wastewater in Zurich, Switzerland, and San Jose, California, USA. We combined this data with information on the temporal dynamics of shedding (the shedding load distribution) to estimate a time series proportional to the daily COVID-19 infection incidence. We estimated a wastewater-based Re from this incidence.

RESULTS

The method to estimate Re from wastewater worked robustly on data from two different countries and two wastewater matrices. The resulting estimates were as similar to the Re estimates from case report data as Re estimates based on observed cases, hospitalizations, and deaths are among each other. We further provide details on the effect of sampling frequency and the shedding load distribution on the ability to infer Re.

DISCUSSION

To our knowledge, this is the first time Re has been estimated from wastewater. This method provides a low-cost, rapid, and independent way to inform SARS-CoV-2 monitoring during the ongoing pandemic and is applicable to future wastewater-based epidemiology targeting other pathogens. https://doi.org/10.1289/EHP10050.

Chromatin profiling in human neurons reveals aberrant roles for histone acetylation and BET family proteins in schizophrenia

Schizophrenia (SZ) is a psychiatric disorder with complex genetic risk dictated by interactions between hundreds of risk variants. Epigenetic factors, such as histone posttranslational modifications (PTMs), have been shown to play critical roles in many neurodevelopmental processes, and when perturbed may also contribute to the precipitation of disease. Here, we apply an unbiased proteomics approach to evaluate combinatorial histone PTMs in human induced pluripotent stem cell (hiPSC)-derived forebrain neurons from individuals with SZ. We observe hyperacetylation of H2A.Z and H4 in neurons derived from SZ cases, results that were confirmed in postmortem human brain. We demonstrate that the bromodomain and extraterminal (BET) protein, BRD4, is a bona fide 'reader' of H2A.Z acetylation, and further provide evidence that BET family protein inhibition ameliorates transcriptional abnormalities in patient-derived neurons. Thus, treatments aimed at alleviating BET protein interactions with hyperacetylated histones may aid in the prevention or treatment of SZ.

SARS-CoV-2 RNA is enriched by orders of magnitude in primary settled solids relative to liquid wastewater at publicly owned treatment works

Wastewater-based epidemiology has gained attention throughout the world for detection of SARS-CoV-2 RNA in wastewater to supplement clinical testing. Raw wastewater consists of small particles, or solids, suspended in liquid. Methods have been developed to measure SARS-CoV-2 RNA in the liquid and the solid fraction of wastewater, with some studies reporting higher concentrations in the solid fraction. To investigate this relationship further, six laboratories collaborated to conduct a study across five publicly owned treatment works (POTWs) where both primary settled solids obtained from primary clarifiers and raw wastewater influent samples were collected and quantified for SARS-CoV-2 RNA. Settled solids and influent samples were processed by participating laboratories using their respective methods and retrospectively paired based on date of collection. SARS-CoV-2 RNA concentrations, on a mass equivalent basis, were higher in settled solids than in influent by approximately three orders of magnitude. Concentrations in matched settled solids and influent were positively and significantly correlated at all five POTWs. RNA concentrations in both settled solids and influent were correlated to COVID-19 incidence rates in the sewersheds and thus representative of disease occurrence; the settled solids methods appeared to produce a comparable relationship between SARS-CoV-2 RNA concentration measurements and incidence rates across all POTWs. Settled solids and influent methods showed comparable sensitivity, N gene detection frequency, and calculated empirical incidence rate lower limits. Analysis of settled solids for SARS-CoV-2 RNA has the advantage of using less sample volume to achieve similar sensitivity to influent methods.

SARS-CoV-2 RNA is enriched by orders of magnitude in primary settled solids relative to liquid wastewater at publicly owned treatment works

Wastewater-based epidemiology has gained attention throughout the world for detection of SARS-CoV-2 RNA in wastewater to supplement clinical testing. Raw wastewater consists of small particles, or solids, suspended in liquid. Methods have been developed to measure SARS-CoV-2 RNA in the liquid and the solid fraction of wastewater, with some studies reporting higher concentrations in the solid fraction. To investigate this relationship further, six laboratories collaborated to conduct a study across five publicly owned treatment works (POTWs) where both primary settled solids obtained from primary clarifiers and raw wastewater influent samples were collected and quantified for SARS-CoV-2 RNA. Settled solids and influent samples were processed by participating laboratories using their respective methods and retrospectively paired based on date of collection. SARS-CoV-2 RNA concentrations, on a mass equivalent basis, were higher in settled solids than in influent by approximately three orders of magnitude. Concentrations in matched settled solids and influent were positively and significantly correlated at all five POTWs. RNA concentrations in both settled solids and influent were correlated to COVID-19 incidence rates in the sewersheds and thus representative of disease occurrence; the settled solids methods appeared to produce a comparable relationship between SARS-CoV-2 RNA concentration measurements and incidence rates across all POTWs. Settled solids and influent methods showed comparable sensitivity, N gene detection frequency, and calculated empirical incidence rate lower limits. Analysis of settled solids for SARS-CoV-2 RNA has the advantage of using less sample volume to achieve similar sensitivity to influent methods.

High-Frequency, High-Throughput Quantification of SARS-CoV-2 RNA in Wastewater Settled Solids at Eight Publicly Owned Treatment Works in Northern California Shows Strong Association with COVID-19 Incidence

A number of recent retrospective studies have demonstrated that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA concentrations in wastewater are associated with coronavirus disease 2019 (COVID-19) cases in the corresponding sewersheds. Implementing high-resolution, prospective efforts across multiple plants depends on sensitive measurements that are representative of COVID-19 cases, scalable for high-throughput analysis, and comparable across laboratories. We conducted a prospective study across eight publicly owned treatment works (POTWs). A focus on SARS-CoV-2 RNA in solids enabled us to scale up our measurements with a commercial lab partner. Samples were collected daily, and results were posted to a website within 24 h. SARS-CoV-2 RNA in daily samples correlated with the incidence of COVID-19 cases in the sewersheds; a 1 log10 increase in SARS-CoV-2 RNA in settled solids corresponds to a 0.58 log10 (4×) increase in sewershed incidence rate. SARS-CoV-2 RNA signals measured with the commercial laboratory partner were comparable across plants and comparable to measurements conducted in a university laboratory when normalized by pepper mild mottle virus (PMMoV) RNA. Results suggest that SARS-CoV-2 RNA should be detectable in settled solids for COVID-19 incidence rates of >1/100,000 (range, 0.8 to 2.3 cases per 100,000). These sensitive, representative, scalable, and comparable methods will be valuable for future efforts to scale up wastewater-based epidemiology. IMPORTANCE Access to reliable, rapid monitoring data is critical to guide response to an infectious disease outbreak. For pathogens that are shed in feces or urine, monitoring wastewater can provide a cost-effective snapshot of transmission in an entire community via a single sample. In order for a method to be useful for ongoing COVID-19 monitoring, it should be sensitive for detection of low concentrations of SARS-CoV-2, representative of incidence rates in the community, scalable to generate data quickly, and comparable across laboratories. This paper presents a method utilizing wastewater solids to meet these goals, producing measurements of SARS-CoV-2 RNA strongly associated with COVID-19 cases in the sewershed of a publicly owned treatment work. Results, provided within 24 h, can be used to detect incidence rates as low as approximately 1/100,000 cases and can be normalized for comparison across locations generating data using different methods.

High-Frequency, High-Throughput Quantification of SARS-CoV-2 RNA in Wastewater Settled Solids at Eight Publicly Owned Treatment Works in Northern California Shows Strong Association with COVID-19 Incidence

A number of recent retrospective studies have demonstrated that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA concentrations in wastewater are associated with coronavirus disease 2019 (COVID-19) cases in the corresponding sewersheds. Implementing high-resolution, prospective efforts across multiple plants depends on sensitive measurements that are representative of COVID-19 cases, scalable for high-throughput analysis, and comparable across laboratories. We conducted a prospective study across eight publicly owned treatment works (POTWs). A focus on SARS-CoV-2 RNA in solids enabled us to scale up our measurements with a commercial lab partner. Samples were collected daily, and results were posted to a website within 24 h. SARS-CoV-2 RNA in daily samples correlated with the incidence of COVID-19 cases in the sewersheds; a 1 log₁₀ increase in SARS-CoV-2 RNA in settled solids corresponds to a 0.58 log₁₀ (4×) increase in sewershed incidence rate. SARS-CoV-2 RNA signals measured with the commercial laboratory partner were comparable across plants and comparable to measurements conducted in a university laboratory when normalized by pepper mild mottle virus (PMMoV) RNA. Results suggest that SARS-CoV-2 RNA should be detectable in settled solids for COVID-19 incidence rates of >1/100,000 (range, 0.8 to 2.3 cases per 100,000). These sensitive, representative, scalable, and comparable methods will be valuable for future efforts to scale up wastewater-based epidemiology. IMPORTANCE Access to reliable, rapid monitoring data is critical to guide response to an infectious disease outbreak. For pathogens that are shed in feces or urine, monitoring wastewater can provide a cost-effective snapshot of transmission in an entire community via a single sample. In order for a method to be useful for ongoing COVID-19 monitoring, it should be sensitive for detection of low concentrations of SARS-CoV-2, representative of incidence rates in the community, scalable to generate data quickly, and comparable across laboratories. This paper presents a method utilizing wastewater solids to meet these goals, producing measurements of SARS-CoV-2 RNA strongly associated with COVID-19 cases in the sewershed of a publicly owned treatment work. Results, provided within 24 h, can be used to detect incidence rates as low as approximately 1/100,000 cases and can be normalized for comparison across locations generating data using different methods.

Effect of storage conditions on SARS-CoV-2 RNA quantification in wastewater solids

SARS-CoV-2 RNA in wastewater settled solids is associated with COVID-19 incidence in sewersheds and therefore, there is a strong interest in using these measurements to augment traditional disease surveillance methods. A wastewater surveillance program should provide rapid turn around for sample measurements (ideally within 24 hours), but storage of samples is necessary for a variety of reasons including biobanking. Here we investigate how storage of wastewater solids at 4 °C, -20 °C, and -80 °C affects measured concentrations of SARS-CoV-2 RNA. We find that short term (7 or 8 d) storage of raw solids at 4 °C has little effect on measured concentrations of SARS-CoV-2 RNA, whereas longer term storage at 4 °C (35-122 d) or freezing reduces measurements by 60%, on average. We show that normalizing SARS-CoV-2 RNA concentrations by concentrations of pepper mild mottle virus (PMMoV) RNA, an endogenous wastewater virus, can correct for changes during storage as storage can have a similar effect on PMMoV RNA as on SARS-CoV-2 RNA. The reductions in SARS-CoV-2 RNA in solids during freeze thaws is less than those reported for the same target in liquid influent by several authors.

Abstract B66: High-throughput synthesis and screening for tumor-targeting liposomal nanoparticles

The identification of therapeutic nanoparticles formulation with preferential distribution to the tumor microenvironment remains an unsolved challenge. We have developed a high-throughput synthesis and screening platform to discover novel tumor-targeting liposomal nanoparticles. Over 1,000 unique liposomal formulations were synthesized using a combinatorial approach. The characterization of physicochemical properties (e.g., size, charge and stability) allowed the prioritization of ~500 formulations further profiled with in vitro cell-based assays (e.g., cell binding, cytotoxicity and cell barrier crossing). A subset of formulations with diverse properties was selected to create a library of 47 DNA-barcoded nanoparticles. The pharmacokinetics and biodistribution of the formulations library were measured in tumor xenografts mouse models in a highly multiplexed fashion by sequencing the DNA barcodes. The established synthesis and screening platform provides an effective approach to identify novel liposomal formulations with improved tumor and tissue distribution profile.

Note: This abstract was not presented at the conference.

Citation Format: Mark Audeh, Manali Dwarakanath, Michael Hopkins, Alisha Knudson, Sally Kwok, Stephen Morton, Nikki Peck, Tim Ruckh, Sarah Sanowar, Zach Scott, Peter Thana, Gary Tong, Aaron Topol, Alberto C Vitari, Eugeni Vaisberg, Jane Wang, Stanley Wong. High-throughput synthesis and screening for tumor-targeting liposomal nanoparticles [abstract]. In: Proceedings of the AACR Special Conference on Tumor Immunology and Immunotherapy; 2018 Nov 27-30; Miami Beach, FL. Philadelphia (PA): AACR; Cancer Immunol Res 2020;8(4 Suppl):Abstract nr B66.

Synergistic effects of common schizophrenia risk variants

The mechanisms by which common risk variants of small effect interact to contribute to complex genetic disorders are unclear. Here, we apply a genetic approach, using isogenic human induced pluripotent stem cells, to evaluate the effects of schizophrenia (SZ)-associated common variants predicted to function as SZ expression quantitative trait loci (eQTLs). By integrating CRISPR-mediated gene editing, activation and repression technologies to study one putative SZ eQTL (FURIN rs4702) and four top-ranked SZ eQTL genes (FURIN, SNAP91, TSNARE1 and CLCN3), our platform resolves pre- and postsynaptic neuronal deficits, recapitulates genotype-dependent gene expression differences and identifies convergence downstream of SZ eQTL gene perturbations. Our observations highlight the cell-type-specific effects of common variants and demonstrate a synergistic effect between SZ eQTL genes that converges on synaptic function. We propose that the links between rare and common variants implicated in psychiatric disease risk constitute a potentially generalizable phenomenon occurring more widely in complex genetic disorders.

Inhibition of STEP61 ameliorates deficits in mouse and hiPSC-based schizophrenia models

The brain-specific tyrosine phosphatase, STEP (STriatal-Enriched protein tyrosine Phosphatase) is an important regulator of synaptic function. STEP normally opposes synaptic strengthening by increasing N-methyl D-aspartate glutamate receptor (NMDAR) internalization through dephosphorylation of GluN2B and inactivation of the kinases extracellular signal-regulated kinase 1/2 and Fyn. Here we show that STEP₆₁ is elevated in the cortex in the Nrg1^+/- knockout mouse model of schizophrenia (SZ). Genetic reduction or pharmacological inhibition of STEP prevents the loss of NMDARs from synaptic membranes and reverses behavioral deficits in Nrg1^+/- mice. STEP₆₁ protein is also increased in cortical lysates from the central nervous system-specific ErbB2/4 mouse model of SZ, as well as in human induced pluripotent stem cell (hiPSC)-derived forebrain neurons and Ngn2-induced excitatory neurons, from two independent SZ patient cohorts. In these selected SZ models, increased STEP₆₁ protein levels likely reflect reduced ubiquitination and degradation. These convergent findings from mouse and hiPSC SZ models provide evidence for STEP₆₁ dysfunction in SZ.

Dysregulation of miRNA-9 in a Subset of Schizophrenia Patient-Derived Neural Progenitor Cells

Converging evidence indicates that microRNAs (miRNAs) may contribute to disease risk for schizophrenia (SZ). We show that microRNA-9 (miR-9) is abundantly expressed in control neural progenitor cells (NPCs) but also significantly downregulated in a subset of SZ NPCs. We observed a strong correlation between miR-9 expression and miR-9 regulatory activity in NPCs as well as between miR-9 levels/activity, neural migration, and diagnosis. Overexpression of miR-9 was sufficient to ameliorate a previously reported neural migration deficit in SZ NPCs, whereas knockdown partially phenocopied aberrant migration in control NPCs. Unexpectedly, proteomic- and RNA sequencing (RNA-seq)-based analysis revealed that these effects were mediated primarily by small changes in expression of indirect miR-9 targets rather than large changes in direct miR-9 targets; these indirect targets are enriched for migration-associated genes. Together, these data indicate that aberrant levels and activity of miR-9 may be one of the many factors that contribute to SZ risk, at least in a subset of patients.

From "directed differentiation" to "neuronal induction": modeling neuropsychiatric disease

Aberrant behavior and function of neurons are believed to be the primary causes of most neurological diseases and psychiatric disorders. Human postmortem samples have limited availability and, while they provide clues to the state of the brain after a prolonged illness, they offer limited insight into the factors contributing to disease onset. Conversely, animal models cannot recapitulate the polygenic origins of neuropsychiatric disease. Novel methods, such as somatic cell reprogramming, deliver nearly limitless numbers of pathogenic human neurons for the study of the mechanism of neuropsychiatric disease initiation and progression. First, this article reviews the advent of human induced pluripotent stem cell (hiPSC) technology and introduces two major methods, “directed differentiation” and “neuronal induction,” by which it is now possible to generate neurons for modeling neuropsychiatric disease. Second, it discusses the recent applications, and the limitations, of these technologies to in vitro studies of psychiatric disorders.

A guide to generating and using hiPSC derived NPCs for the study of neurological diseases

Post-mortem studies of neurological diseases are not ideal for identifying the underlying causes of disease initiation, as many diseases include a long period of disease progression prior to the onset of symptoms. Because fibroblasts from patients and healthy controls can be efficiently reprogrammed into human induced pluripotent stem cells (hiPSCs), and subsequently differentiated into neural progenitor cells (NPCs) and neurons for the study of these diseases, it is now possible to recapitulate the developmental events that occurred prior to symptom onset in patients. We present a method by which to efficiently differentiate hiPSCs into NPCs, which in addition to being capable of further differentiation into functional neurons, can also be robustly passaged, freeze-thawed or transitioned to grow as neurospheres, enabling rapid genetic screening to identify the molecular factors that impact cellular phenotypes including replication, migration, oxidative stress and/or apoptosis. Patient derived hiPSC NPCs are a unique platform, ideally suited for the empirical testing of the cellular or molecular consequences of manipulating gene expression.

Neural stem and progenitor cells in health and disease

Neural stem/progenitor cells (NSPCs) have the potential to differentiate into neurons, astrocytes, and/or oligodendrocytes. Because these cells can be expanded in culture, they represent a vast source of neural cells. With the recent discovery that patient fibroblasts can be reprogrammed directly into induced NSPCs, the regulation of NSPC fate and function, in the context of cell-based disease models and patient-specific cell-replacement therapies, warrants review.