Effect of SARS-CoV-2 digital droplet RT-PCR assay sensitivity on COVID-19 wastewater based epidemiology

We developed and implemented a framework for examining how molecular assay sensitivity for a viral RNA genome target affects its utility for wastewater-based epidemiology. We applied this framework to digital droplet RT-PCR measurements of SARS-CoV-2 and Pepper Mild Mottle Virus genes in wastewater. Measurements were made using 10 replicate wells which allowed for high assay sensitivity, and therefore enabled detection of SARS-CoV-2 RNA even when COVID-19 incidence rates were relatively low (~10−5). We then used a computational downsampling approach to determine how using fewer replicate wells to measure the wastewater concentration reduced assay sensitivity and how the resultant reduction affected the ability to detect SARS-CoV-2 RNA at various COVID-19 incidence rates. When percent of positive droplets was between 0.024% and 0.5% (as was the case for SARS-CoV-2 genes during the Delta surge), measurements obtained with 3 or more wells were similar to those obtained using 10. When percent of positive droplets was less than 0.024% (as was the case prior to the Delta surge), then 6 or more wells were needed to obtain similar results as those obtained using 10 wells. When COVID-19 incidence rate is low (~ 10−5), as it was before the Delta surge and SARS-CoV-2 gene concentrations are <104 cp/g, using 6 wells will yield a detectable concentration 90% of the time. Overall, results support an adaptive approach where assay sensitivity is increased by running 6 or more wells during periods of low SARS-CoV-2 gene concentrations, and 3 or more wells during periods of high SARS-CoV-2 gene concentrations

Example output of simulation results to calculate the final concentration in wastewater solids.

(Top) SARS-CoV-2 N gene in June 1, 2021 sample during low COVID-19 incidence, (middle) SARS-CoV-2 N gene in August 31, 2021 sample during high COVID-19 incidence, and (bottom) for PMMoV in June 6, 2021 sample. For X = 1–9, the circle in the box represents the median, and the top and bottom of the box represent 75th and 25th percentile, respectively. Any X that resulted in ND in all simulations are marked with an unfilled circle. For X = 10, the circle in the red box represents the software reported concentration from merging all ten wells, and the top and bottom of the box represent upper and lower confidence intervals, respectively, from 68% total error as given by the instrument software, which includes errors associated with the Poisson distribution and variability among replicate wells. Percentage of positive droplets in 10 wells is shown in boxes within each plot.</p

Supplemental Tables and Figs.

(DOCX)</p

Brief description of experimental methods.

(DOCX)</p

Detection frequency for all samples across four POTWs against true concentration.

True concentration is defined as concentration obtained by merging all ten wells. Each data point shows the fraction of 1000 simulations that did not result in ND in each well on the y-axis and its true concentration on the x-axis. ND for X = 10 was substituted with half of the theoretical lower measurement limit. 95% confidence intervals of the logistic regression are shown as the gray ribbon.</p

Time series of SARS-CoV-2 N gene concentration in wastewater solids.

(Top to bottom) X = 1, 3, 6, for wastewater SARS-CoV-2 gene concentration (cp/g dry weight) and 7 day centered smoothed average laboratory-confirmed SARS-CoV-2 incidence rate for each of the four POTWs from June 1, 2021 to August 31, 2021. Note that the SARS-CoV-2 N gene concentrations are displayed in log10-scale format for ease of visualization. Each wastewater data point represents median SARS-CoV-2 RNA concentration for a single sample obtained from 1000 simulations; for X = 10, each data point is the concentration obtained by merging 10 wells. Samples that resulted in ND were substituted with zero. A figure showing all possible numbers of merged wells is included in the SI (Fig D in S3 Text).</p

Details on COVID-19 epidemiology data.

(DOCX)</p

C_0.5 and corresponding clinical and wastewater characterization.

C0.5 and corresponding clinical and wastewater characterization.</p

Time series of SARS-CoV-2 concentration in wastewater solids during low COVID-19 incidence month of June.

Note that the SARS-CoV-2 RNA concentrations are displayed in log10-scale format for ease of visualization. Each wastewater data point represents SARS-CoV-2 concentration measured for a single sample. Samples above the lower measurement limit are shown as filled circles. Samples that resulted in ND, shown as empty circles, were substituted with half the lower measurement limit.</p

A Kinetic Isotope Effect and Isotope Exchange Study of the Nonenzymatic and the Equine Serum Butyrylcholinesterase-Catalyzed Thioester Hydrolysis

Formylthiocholine (FTC) was synthesized and found to be a substrate for nonenzymatic and butyrylcholinesterase (BChE)-catalyzed hydrolysis. Solvent (D₂O) and secondary formyl-H kinetic isotope effects (KIEs) were measured by an NMR spectroscopic method. The solvent (D₂O) KIEs are ^D₂O<i>k</i> = 0.20 in 200 mM HCl, ^D₂O<i>k</i> = 0.81 in 50 mM HCl, and ^D₂O<i>k</i> = 4.2 in pure water. The formyl-H KIEs are ^D<i>k</i> = 0.80 in 200 mM HCl, ^D<i>k</i> = 0.77 in 50 mM HCl, ^D<i>k</i> = 0.75 in pure water, ^D<i>k</i> = 0.88 in 50 mM NaOH, and ^D(<i>V</i>/<i>K</i>) = 0.89 in the BChE-catalyzed hydrolysis in MES buffer at pH 6.8. Positional isotope exchange experiments showed no detectable exchange of ¹⁸O into the carbonyl oxygen of FTC or the product, formate, under any of the above conditions. Solvent nucleophile-O KIEs were determined to be ¹⁸<i>k</i> = 0.9917 under neutral conditions, ¹⁸<i>k</i> = 1.0290 (water nucleophile) or ¹⁸<i>k</i> = 0.989 (hydroxide nucleophile) under alkaline conditions, and ¹⁸(<i>V</i>/<i>K</i>) = 0.9925 for BChE catalysis. The acidic, neutral, and BChE-catalyzed reactions are explained in terms of a stepwise mechanism with tetrahedral intermediates. Evidence for a change to a direct displacement mechanism under alkaline conditions is presented