Nationwide Trends in COVID-19 Cases and SARS-CoV-2 RNA Wastewater Concentrations in the United States

Wastewater-based epidemiology has emerged as a promising technology for population-level surveillance of COVID-19. In this study, we present results of a large nationwide SARS-CoV-2 wastewater monitoring system in the United States. We profile 55 locations with at least six months of sampling from April 2020 to May 2021. These locations represent more than 12 million individuals across 19 states. Samples were collected approximately weekly by wastewater treatment utilities as part of a regular wastewater surveillance service and analyzed for SARS-CoV-2 RNA concentrations. SARS-CoV-2 RNA concentrations were normalized to pepper mild mottle virus, an indicator of fecal matter in wastewater. We show that wastewater data reflect temporal and geographic trends in clinical COVID-19 cases and investigate the impact of normalization on correlations with case data within and across locations. We also provide key lessons learned from our broad-scale implementation of wastewater-based epidemiology, which can be used to inform wastewater-based epidemiology approaches for future emerging diseases. This work demonstrates that wastewater surveillance is a feasible approach for nationwide population-level monitoring of COVID-19 disease. With an evolving epidemic and effective vaccines against SARS-CoV-2, wastewater-based epidemiology can serve as a passive surveillance approach for detecting changing dynamics or resurgences of the virus.

Nationwide Trends in COVID-19 Cases and SARS-CoV-2 RNA Wastewater Concentrations in the United States

Wastewater-based epidemiology has emerged as a promising technology for population-level surveillance of COVID-19. In this study, we present results of a large nationwide SARS-CoV-2 wastewater monitoring system in the United States. We profile 55 locations with at least six months of sampling from April 2020 to May 2021. These locations represent more than 12 million individuals across 19 states. Samples were collected approximately weekly by wastewater treatment utilities as part of a regular wastewater surveillance service and analyzed for SARS-CoV-2 RNA concentrations. SARS-CoV-2 RNA concentrations were normalized to pepper mild mottle virus, an indicator of fecal matter in wastewater. We show that wastewater data reflect temporal and geographic trends in clinical COVID-19 cases and investigate the impact of normalization on correlations with case data within and across locations. We also provide key lessons learned from our broad-scale implementation of wastewater-based epidemiology, which can be used to inform wastewater-based epidemiology approaches for future emerging diseases. This work demonstrates that wastewater surveillance is a feasible approach for nationwide population-level monitoring of COVID-19 disease. With an evolving epidemic and effective vaccines against SARS-CoV-2, wastewater-based epidemiology can serve as a passive surveillance approach for detecting changing dynamics or resurgences of the virus.

Lineage abundance estimation for SARS-CoV-2 in wastewater using transcriptome quantification techniques

Effectively monitoring the spread of SARS-CoV-2 mutants is essential to efforts to counter the ongoing pandemic. Predicting lineage abundance from wastewater, however, is technically challenging. We show that by sequencing SARS-CoV-2 RNA in wastewater and applying algorithms initially used for transcriptome quantification, we can estimate lineage abundance in wastewater samples. We find high variability in signal among individual samples, but the overall trends match those observed from sequencing clinical samples. Thus, while clinical sequencing remains a more sensitive technique for population surveillance, wastewater sequencing can be used to monitor trends in mutant prevalence in situations where clinical sequencing is unavailable.

Metrics to relate COVID-19 wastewater data to clinical testing dynamics

Wastewater surveillance has emerged as a useful tool in the public health response to the COVID-19 pandemic. While wastewater surveillance has been applied at various scales to monitor population-level COVID-19 dynamics, there is a need for quantitative metrics to interpret wastewater data in the context of public health trends. 24-hour composite wastewater samples were collected from March 2020 through May 2021 from a Massachusetts wastewater treatment plant and SARS-CoV-2 RNA concentrations were measured using RT-qPCR. The relationship between wastewater copy numbers of SARS-CoV-2 gene fragments and COVID-19 clinical cases and deaths varies over time. We demonstrate the utility of three new metrics to monitor changes in COVID-19 epidemiology: (1) the ratio between wastewater copy numbers of SARS-CoV-2 gene fragments and clinical cases (WC ratio), (2) the time lag between wastewater and clinical reporting, and (3) a transfer function between the wastewater and clinical case curves. The WC ratio increases after key events, providing insight into the balance between disease spread and public health response. Time lag and transfer function analysis showed that wastewater data preceded clinically reported cases in the first wave of the pandemic but did not serve as a leading indicator in the second wave, likely due to increased testing capacity, which allows for more timely case detection and reporting. These three metrics could help further integrate wastewater surveillance into the public health response to the COVID-19 pandemic and future pandemics.

SARS-CoV-2 RNA concentrations in wastewater foreshadow dynamics and clinical presentation of new COVID-19 cases

Current estimates of COVID-19 prevalence are largely based on symptomatic, clinically diagnosed cases. The existence of a large number of undiagnosed infections hampers population-wide investigation of viral circulation. Here, we quantify the SARS-CoV-2 concentration and track its dynamics in wastewater at a major urban wastewater treatment facility in Massachusetts, between early January and May 2020. SARS-CoV-2 was first detected in wastewater on March 3. SARS-CoV-2 RNA concentrations in wastewater correlated with clinically diagnosed new COVID-19 cases, with the trends appearing 4-10 days earlier in wastewater than in clinical data. We inferred viral shedding dynamics by modeling wastewater viral load as a convolution of back-dated new clinical cases with the average population-level viral shedding function. The inferred viral shedding function showed an early peak, likely before symptom onset and clinical diagnosis, consistent with emerging clinical and experimental evidence. This finding suggests that SARS-CoV-2 concentrations in wastewater may be primarily driven by viral shedding early in infection. This work shows that longitudinal wastewater analysis can be used to identify trends in disease transmission in advance of clinical case reporting, and infer early viral shedding dynamics for newly infected individuals, which are difficult to capture in clinical investigations.

Wastewater surveillance of SARS-CoV-2 across 40 U.S. states from February to June 2020

Wastewater-based disease surveillance is a promising approach for monitoring community outbreaks. Here we describe a nationwide campaign to monitor SARS-CoV-2 in the wastewater of 159 counties in 40 U.S. states, covering 13% of the U.S. population from February 18 to June 2, 2020. Out of 1,751 total samples analyzed, 846 samples were positive for SARS-CoV-2 RNA, with overall viral concentrations declining from April to May. Wastewater viral titers were consistent with, and appeared to precede, clinical COVID-19 surveillance indicators, including daily new cases. Wastewater surveillance had a high detection rate (>80%) of SARS-CoV-2 when the daily incidence exceeded 13 per 100,000 people. Detection rates were positively associated with wastewater treatment plant catchment size. To our knowledge, this work represents the largest-scale wastewater-based SARS-CoV-2 monitoring campaign to date, encompassing a wide diversity of wastewater treatment facilities and geographic locations. Our findings demonstrate that a national wastewater-based approach to disease surveillance may be feasible and effective.

Metrics to relate COVID-19 wastewater data to clinical testing dynamics

Wastewater surveillance has emerged as a useful tool in the public health response to the COVID-19 pandemic. While wastewater surveillance has been applied at various scales to monitor population-level COVID-19 dynamics, there is a need for quantitative metrics to interpret wastewater data in the context of public health trends. We collected 24-hour composite wastewater samples from March 2020 through May 2021 from a Massachusetts wastewater treatment plant and measured SARS-CoV-2 RNA concentrations using RT-qPCR. We show that the relationship between wastewater viral titers and COVID-19 clinical cases and deaths varies over time. We demonstrate the utility of three new metrics to monitor changes in COVID-19 epidemiology: (1) the ratio between wastewater viral titers and clinical cases (WC ratio), (2) the time lag between wastewater and clinical reporting, and (3) a transfer function between the wastewater and clinical case curves. We find that the WC ratio increases after key events, providing insight into the balance between disease spread and public health response. We also find that wastewater data preceded clinically reported cases in the first wave of the pandemic but did not serve as a leading indicator in the second wave, likely due to increased testing capacity. These three metrics could complement a framework for integrating wastewater surveillance into the public health response to the COVID-19 pandemic and future pandemics.

Wastewater Surveillance of SARS-CoV-2 across 40 U.S. states

Wastewater-based disease surveillance is a promising approach for monitoring community outbreaks. Here we describe a nationwide campaign to monitor SARS-CoV-2 in the wastewater of 159 counties in 40 U.S. states, covering 13% of the U.S. population from February 18 to June 2, 2020. Out of 1,751 total samples analyzed, 846 samples were positive for SARS-CoV-2 RNA, with overall viral concentrations declining from April to May. Wastewater viral titers were consistent with, and appeared to precede, clinical COVID-19 surveillance indicators, including daily new cases. Wastewater surveillance had a high detection rate (>80%) of SARS-CoV-2 when the daily incidence exceeded 13 per 100,000 people. Detection rates were positively associated with wastewater treatment plant catchment size. To our knowledge, this work represents the largest-scale wastewater-based SARS-CoV-2 monitoring campaign to date, encompassing a wide diversity of wastewater treatment facilities and geographic locations. Our findings demonstrate that a national wastewater-based approach to disease surveillance may be feasible and effective.

SARS-CoV-2 titers in wastewater foreshadow dynamics and clinical presentation of new COVID-19 cases

Current estimates of COVID-19 prevalence are largely based on symptomatic, clinically diagnosed cases. The existence of a large number of undiagnosed infections hampers population-wide investigation of viral circulation. Here, we use longitudinal wastewater analysis to track SARS-CoV-2 dynamics in wastewater at a major urban wastewater treatment facility in Massachusetts, between early January and May 2020. SARS-CoV-2 was first detected in wastewater on March 3. Viral titers in wastewater increased exponentially from mid-March to mid-April, after which they began to decline. Viral titers in wastewater correlated with clinically diagnosed new COVID-19 cases, with the trends appearing 4-10 days earlier in wastewater than in clinical data. We inferred viral shedding dynamics by modeling wastewater viral titers as a convolution of back-dated new clinical cases with the viral shedding function of an individual. The inferred viral shedding function showed an early peak, likely before symptom onset and clinical diagnosis, consistent with emerging clinical and experimental evidence. Finally, we found that wastewater viral titers at the neighborhood level correlate better with demographic variables than with population size. This work suggests that longitudinal wastewater analysis can be used to identify trends in disease transmission in advance of clinical case reporting, and may shed light on infection characteristics that are difficult to capture in clinical investigations, such as early viral shedding dynamics.

The Epithelial adhesin 1 tandem repeat region mediates protein display through multiple mechanisms

The pathogenic yeast Candida glabrata is reliant on a suite of cell surface adhesins that play a variety of roles necessary for transmission, establishment and proliferation during infection. One particular adhesin, Epithelial Adhesin 1 [Epa1p], is responsible for binding to host tissue, a process which is essential for fungal propagation. Epa1p structure consists of three domains: an N-terminal intercellular binding domain responsible for epithelial cell binding, a C-terminal GPI anchor for cell wall linkage and a serine/threonine-rich linker domain connecting these terminal domains. The linker domain contains a 40-amino acid tandem repeat region, which we have found to be variable in repeat copy number between isolates from clinical sources. We hypothesized that natural variation in Epa1p repeat copy may modulate protein function. To test this, we recombinantly expressed Epa1p with various repeat copy numbers in S. cerevisiae to determine how differences in repeat copy number affect Epa1p expression, surface display and binding to human epithelial cells. Our data suggest that repeat copy number variation has pleiotropic effects, influencing gene expression, protein surface display and shedding from the cell surface of the Epa1p adhesin. This study serves to demonstrate repeat copy number variation can modulate protein function through a number of mechanisms in order to contribute to pathogenicity of C. glabrata.

Bivalent complexes of PRC1 with orthologs of BRD4 and MOZ/MORF target developmental genes in Drosophila

Kang et al. confirm PRC1–Br140 and PRC1–Fs(1)h interactions and identify their genomic binding sites. PRC1–Br140 bind developmental genes in fly embryos, with analogous co-occupancy of PRC1 and BRD1 at bivalent loci in human ES cells.

Regulatory decisions in Drosophila require Polycomb group (PcG) proteins to maintain the silent state and Trithorax group (TrxG) proteins to oppose silencing. Since PcG and TrxG are ubiquitous and lack apparent sequence specificity, a long-standing model is that targeting occurs via protein interactions; for instance, between repressors and PcG proteins. Instead, we found that Pc-repressive complex 1 (PRC1) purifies with coactivators Fs(1)h [female sterile (1) homeotic] and Enok/Br140 during embryogenesis. Fs(1)h is a TrxG member and the ortholog of BRD4, a bromodomain protein that binds to acetylated histones and is a key transcriptional coactivator in mammals. Enok and Br140, another bromodomain protein, are orthologous to subunits of a mammalian MOZ/MORF acetyltransferase complex. Here we confirm PRC1–Br140 and PRC1–Fs(1)h interactions and identify their genomic binding sites. PRC1–Br140 bind developmental genes in fly embryos, with analogous co-occupancy of PRC1 and a Br140 ortholog, BRD1, at bivalent loci in human embryonic stem (ES) cells. We propose that identification of PRC1–Br140 “bivalent complexes” in fly embryos supports and extends the bivalency model posited in mammalian cells, in which the coexistence of H3K4me3 and H3K27me3 at developmental promoters represents a poised transcriptional state. We further speculate that local competition between acetylation and deacetylation may play a critical role in the resolution of bivalent protein complexes during development.

upSET, the Drosophila homologue of SET3, Is Required for Viability and the Proper Balance of Active and Repressive Chromatin Marks

Chromatin plays a critical role in faithful implementation of gene expression programs. Different post-translational modifications (PTMs) of histone proteins reflect the underlying state of gene activity, and many chromatin proteins write, erase, bind, or are repelled by, these histone marks. One such protein is UpSET, the Drosophila homolog of yeast Set3 and mammalian KMT2E (MLL5). Here, we show that UpSET is necessary for the proper balance between active and repressed states. Using CRISPR/Cas-9 editing, we generated S2 cells that are mutant for upSET We found that loss of UpSET is tolerated in S2 cells, but that heterochromatin is misregulated, as evidenced by a strong decrease in H3K9me2 levels assessed by bulk histone PTM quantification. To test whether this finding was consistent in the whole organism, we deleted the upSET coding sequence using CRISPR/Cas-9, which we found to be lethal in both sexes in flies. We were able to rescue this lethality using a tagged upSET transgene, and found that UpSET protein localizes to transcriptional start sites (TSS) of active genes throughout the genome. Misregulated heterochromatin is apparent by suppressed position effect variegation of the wm4 allele in heterozygous upSET-deleted flies. Using nascent-RNA sequencing in the upSET-mutant S2 lines, we show that this result applies to heterochromatin genes generally. Our findings support a critical role for UpSET in maintaining heterochromatin, perhaps by delimiting the active chromatin environment.

Sex comb on midleg (Scm) is a functional link between PcG-repressive complexes in Drosophila

In this study, Kang et al. investigate how PcG complexes form repressive chromatin domains. The findings show that Scm, a transcriptional repressor, is an important regulator of PRC1, PRC2, and transcriptional silencing and suggest that Scm coordinates PcG complexes and polymerizes, resulting in PcG silencing.

The Polycomb group (PcG) proteins are key regulators of development in Drosophila and are strongly implicated in human health and disease. How PcG complexes form repressive chromatin domains remains unclear. Using cross-linked affinity purifications of BioTAP-Polycomb (Pc) or BioTAP-Enhancer of zeste [E(z)], we captured all PcG-repressive complex 1 (PRC1) or PRC2 core components and Sex comb on midleg (Scm) as the only protein strongly enriched with both complexes. Although previously not linked to PRC2, we confirmed direct binding of Scm and PRC2 using recombinant protein expression and colocalization of Scm with PRC1, PRC2, and H3K27me3 in embryos and cultured cells using ChIP-seq (chromatin immunoprecipitation [ChIP] combined with deep sequencing). Furthermore, we found that RNAi knockdown of Scm and overexpression of the dominant-negative Scm-SAM (sterile α motif) domain both affected the binding pattern of E(z) on polytene chromosomes. Aberrant localization of the Scm-SAM domain in long contiguous regions on polytene chromosomes revealed its independent ability to spread on chromatin, consistent with its previously described ability to oligomerize in vitro. Pull-downs of BioTAP-Scm captured PRC1 and PRC2 and additional repressive complexes, including PhoRC, LINT, and CtBP. We propose that Scm is a key mediator connecting PRC1, PRC2, and transcriptional silencing. Combined with previous structural and genetic analyses, our results strongly suggest that Scm coordinates PcG complexes and polymerizes to produce broad domains of PcG silencing.

BioTAP-XL: Cross-linking/Tandem Affinity Purification to Study DNA Targets, RNA, and Protein Components of Chromatin-Associated Complexes

In order to understand how chromatin complexes function in the nucleus, it is important to obtain a comprehensive picture of their protein, DNA, and RNA components, as well as their mutual interactions. This unit presents a chromatin cross-linking approach (BioTAP-XL) that utilizes a special BioTAP-tagged transgenic protein bait along with mass spectrometry to identify protein complex components, and high-throughput sequencing to identify RNA components and DNA binding sites. Full protocols are provided for Drosophila cells and for human cells in culture, along with an additional protocol for Drosophila embryos as the source material. A key element of the approach in all cases is the generation of control data from input chromatin samples.

Are we there yet? Initial targeting of the Male-Specific Lethal and Polycomb group chromatin complexes in Drosophila

Chromatin-binding proteins must navigate the complex nuclear milieu to find their sites of action, and a constellation of protein factors and other properties are likely to influence targeting specificity. Despite considerable progress, the precise rules by which binding specificity is achieved have remained elusive. Here, we consider early targeting events for two groups of chromatin-binding complexes in Drosophila: the Male-Specific Lethal (MSL) and the Polycomb group (PcG) complexes. These two serve as models for understanding targeting, because they have been extensively studied and play vital roles in Drosophila, and their targets have been documented at high resolution. Furthermore, the proteins and biochemical properties of both complexes are largely conserved in multicellular organisms, including humans. While the MSL complex increases gene expression and PcG members repress genes, the two groups share many similarities such as the ability to modify their chromatin environment to create active or repressive domains, respectively. With legacies of in-depth genetic, biochemical and now genomic approaches, the MSL and PcG complexes will continue to provide tractable systems for understanding the recruitment of multiprotein chromatin complexes to their target loci.