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.

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.

No abstract

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 crosslinked 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 BioTAPScm 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.