Temporal Detection and Phylogenetic Assessment of SARS-CoV-2 in Municipal Wastewater

Abstract

SARS-CoV-2 has recently been detected in feces, which indicates that wastewater may be used to monitor viral prevalence in the community. Here, we use RT-qPCR to monitor wastewater for SARS-CoV-2 RNA over a 74-day time course. We show that changes in SARS-CoV-2 RNA concentrations follow symptom onset gathered by retrospective interview of patients but precedes clinical test results. In addition, we determine a nearly complete (98.5%) SARS-CoV-2 genome sequence from wastewater and use phylogenetic analysis to infer viral ancestry. Collectively, this work demonstrates how wastewater can be used as a proxy to monitor viral prevalence in the community and how genome sequencing can be used for genotyping viral strains circulating in a community.

Keywords: COVID-19; SARS-CoV-2; genome sequencing; wastewater-based epidemiology.

Graphical abstract

Figure 1

Detection and Quantification of SARS-CoV-2 in Wastewater and in the Community (A) Temporal dynamics of SARS-CoV-2 RNA in the municipal wastewater is superimposed on the epidemiological data. Symptom onset data (teal bars) were collected by retrospective interviews of COVID-19 patients who previously tested positive for SARS-CoV-2 (coral bars). The red circles and blue triangles show SARS-CoV-2 RNA concentration in municipal wastewater (means ± SDs) measured with qRT-PCR using the N1 and N2 primer pairs, respectively (see Method Details). The lines show curves fitted to qRT-PCR and epidemiological data using local polynomial regression (LOESS, locally estimated scatterplot smoothing). (B and C) Linear regions of the epidemiological and wastewater curves. Curves were displaced relative to each other and Pearson correlation coefficients (r) were calculated. The 95% confidence intervals for the highest Pearson’s r values and respective offsets are shown. Data for initial surge (March–April) and resurgence (May) were analyzed separately. Surge boundaries were defined as the earliest reported symptom onset (left boundary) and date with last reported positive test (right boundary). The interval between surges with zero reported cases/symptoms (mid-April–mid-May) was dropped from the analysis. (D) Timeline of the indicators used in the study. Symptom onset is the earliest available estimate of the viral spread. However, these data are collected retrospectively, which preclude its use for real-time tracking of the outbreak. Wastewater correlates with symptom onset and could be used to track progressing outbreak.

Figure 2

Phylogenetic Analysis of SARS-CoV-2 Sequence Isolated from Wastewater (A) Maximum-likelihood phylogeny of the SARS-CoV-2-related lineage (n = 14,971 sequences). The phylogenetic history of SARS-CoV-2 strain sequenced from Bozeman’s wastewater (WW) is shown in crimson. The outer ring is colored according to regions of the world where the samples were isolated. The tree is rooted relative to the RaTG13 genome (a bat coronavirus with 96% sequence similarity to SARS-CoV-2; GenBank: MN996532.1). Mutations that occurred over space and time are shown in red. (B) Sequences isolated from Bozeman WW clade with sequences of US and Australian origin (left). The sequences are named according to the geographic origin and the viral isolation date. A comparison of mutations in sequences is shown in the inset (right). The Wuhan reference sequence for each of the positions where mutations occur is shown across the top. The mutated positions and bases present in Bozeman WW sequence are shown in red, the bases matching Wuhan reference sequence are shown in white, and the mutations not present in the Bozeman WW sequence are shown in blue.