key: cord-0994183-h652vxx3 authors: Simpson, A.; Topol, A.; White, B.; Wolfe, M.; Wigginton, K.; Boehm, A. B. title: Effect of storage conditions on SARS-CoV-2 RNA quantification in wastewater solids date: 2021-05-08 journal: nan DOI: 10.1101/2021.05.04.21256611 sha: 42e9fd2f50316338483c343ade567b9eee0492a9 doc_id: 994183 cord_uid: h652vxx3 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 4C, -20C, and -80C affects measured concentrations of SARS-CoV-2 RNA. We find that short term (7-8 d) storage of raw solids at 4C has little effect on measured concentrations of SARS-CoV-2 RNA, whereas longer term storage at 4C (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. SARS-CoV-2 RNA in settled solids from wastewater treatment plants correlates to incidence in the sewershed population [1] [2] [3] . As a result, local and federal governmental 36 agencies are establishing wastewater-based epidemiology methods to help inform pandemic 37 response [4] . Wastewater consists of liquid and solid components. While many wastewater 38 surveillance efforts have focused on measuring SARS-CoV-2 in the liquid component of 39 wastewater [5, 6] , the solids have 10 3 to 10 4 higher concentrations of SARS-CoV-2 RNA on a 40 per mass basis [2, 7] . Settled solids are readily collected from the primary clarifier where they 41 settle as part of the wastewater treatment process, or they can be settled from wastewater 42 influent using standard method SM2540 F [8] if a wastewater treatment plant does not have a 43 primary clarifier unit process. 44 45 In order for wastewater data on SARS-CoV-2 to be useful for real time disease response, 46 samples should be analyzed quickly and results reported as soon as possible to public health 47 officials. In such a scenario, samples are not stored, but are processed as soon as they are 48 collected. Even if this is done as recommended, sample storage is essential. It may take 24 49 hours or longer for results from a sample to be obtained. In cases where an instrument 50 malfunctions or results do not pass quality control metrics, samples might need to be rerun. 51 Samples therefore need to be stored for at least as long as it takes to obtain results. 52 Additionally, labs may want to create a biobank of samples; these samples can be used in the 53 future to probe the presence of variants of concerns or other pathogens as needed. 54 55 A few studies have investigated how storage conditions affect quantification of SARS-CoV-2 56 RNA in liquid influent [6, [9] [10] [11] [12] and determined that storage and freeze thaws of the liquid 57 influent can reduce measured concentrations of the viral RNA an order of magnitude or more. 58 No published studies to date have investigated the effect of storage conditions on quantification 59 of SARS-CoV-2 RNA in settled solids. Therefore, the goal of this study is to assess the impact 60 of different realistic storage conditions on the quantification of SARS-CoV-2 RNA and an 61 endogenous viral control (pepper mild mottle virus, PMMoV) in settled solids. The results of this 62 study will inform optimal storage conditions for settled solids for use for wastewater-based 63 epidemiology. 64 65 Sample collection. Eleven (11) 50-ml samples of settled solids were collected from the primary 68 clarifiers at four unique wastewater treatment plants (Table 1) using sterile technique and clean 69 containers. Samples were immediately stored on ice and transported to the lab where they were 70 processed within 6 hours of sample pick up from the plants with high throughput methods [13-71 15] . Thereafter, the samples were subjected to different storage treatments in the laboratory 72 ( CoV-2 N, S, and ORF1a RNA gene targets in a triplex assay, and BCoV and PMMoV in a 102 duplex assay (see Table 3 for primer and probe sequences, purchased from IDT). Undiluted 103 extract was used for the SARS-CoV-2 assay template and a 1:100 dilution of the extract was 104 used for the BCoV / PMMoV assay template. Digital RT-PCR was performed on 20 µl samples 105 from a 22 µl reaction volume, prepared using 5.5 µl template, mixed with 5.5 µl of One-Step RT-106 ddPCR Advanced Kit for Probes (Bio-Rad 1863021), 2.2 µl Reverse Transcriptase, 1.1 µl DTT 107 and primers and probes at a final concentration of 900nM and 250nM respectively. Droplets 108 were generated using the AutoDG Automated Droplet Generator (Bio-Rad). PCR was 109 performed using Mastercycler Pro with the following protocol: reverse transcription at 50℃ for 110 60 minutes, enzyme activation at 95℃ for 5 minutes, 40 cycles of denaturation at 95℃ for 30 111 seconds and annealing and extension at either 59℃ (for SARS-CoV-2 assay) or 56℃ (for 112 PMMoV/BCoV duplex assay) for 30 seconds, enzyme deactivation at 98℃ for 10 minutes then 113 an indefinite hold at 4℃. The ramp rate for temperature changes were set to 2℃/second and the 114 final hold at 4℃ was performed for a minimum of 30 minutes to allow the droplets to stabilize. 115 Droplets were analyzed using the QX200 Droplet Reader (Bio-Rad). All liquid transfers were 116 performed using the Agilent Bravo (Agilent Technologies). 117 118 Each sample was run in 10 replicate wells, extraction negative controls were run in 7 wells, and 119 extraction positive controls in 1 well. In addition, PCR positive controls for SARS-CoV-2 RNA, 120 BCoV, and PMMoV were run in 1 well, and NTC were run in 7 wells. Positive controls consisted 121 of BCoV and PMMoV gene block controls (purchased from IDT) and gRNA of SARS-CoV-2 122 (ATCC® VR-1986D™). Results from replicate wells were merged for analysis. Thresholding 123 was done using QuantaSoft™ Analysis Pro Software (Bio-Rad, version 1.0.596). Additional 124 details are provided in supporting material per the dMIQE guidelines [16] . 125 126 127 . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted May 8, 2021. ; https://doi.org/10.1101/2021.05.04.21256611 doi: medRxiv preprint Data analysis. Concentrations of RNA targets were converted to concentrations per dry weight 128 of solids in units of copies/g dry weight. The total error is reported as 68% confidence intervals 129 and includes the errors associated with the poisson distribution and the variability among the 10 130 replicates. The recovery of BCoV was determined by normalizing the concentration of BCoV by 131 the expected concentration given the value measured in the spiked DNA/RNA shield. If the 132 BCoV recovery was less than 10%, then the sample was rerun. 133 134 PMMoV, N, S, ORF1a, as well as N/PMMoV, S/PMMoV, and ORF1a/PMMoV were compared 135 for each sample control and treatment, 1 by 1, by examining the measurement and the 68% 136 error associated with the measurement. The error associated with the quotients was estimated 137 by propagating errors on the numerator and denominator. If the measurement of the treatment 138 condition fell within the error range of the control condition, then the measurement was deemed 139 "not different". This approach is equivalent to a t-test where the null hypothesis (Ho) is the value 140 of the treatment is the same as the control and the alternate hypothesis (Ha) is that the values 141 are different. In this study, we are particularly concerned about type 2 errors (failing to reject Ho 142 when it is false) as we are concerned with whether storage renders different measurements. As 143 such, in order to increase the power of the analysis, we chose to make comparisons using the 144 68% confidence intervals. With the 10 replicates, this gives ~90% power of avoiding a type 2 145 error assuming an effect size equal to the standard deviation. 146 147 For measurements deemed "different", the percent difference (% diff) was calculated as % diff 148 = 100 x (control-treatment)/control where control and treatment are the associated 149 measurements. A positive % diff indicates that the treatment result is smaller than the control, 150 whereas a negative percent indicates the treatment had higher concentrations than the control. 151 Errors for % diff were propagated from the measurements as standard deviations. by PMMoV gene concentrations, the ratios were not different between treatment and control in 174 any of the 4 samples ( Figure 1 ). For the sample that had lower SARS-CoV-2 RNA gene 175 concentrations in the treatment compared to the control, the concentrations of the N, S, and 176 ORF1 genes differed by 60%, 80%, and 73% respectively (Table 3) . For those 2 samples, ratios were lower and different in the treatments compared to the controls 183 ( Figure 1 ). The difference between the treatment and controls are shown in Table 3 . Generally, 184 the differences in the measurements, when they were different, were ~50%. 185 186 Storage at -20°C. Four samples were processed within 6 hours of collection to obtain control 187 measurements. The same samples were also frozen at -20°C for 2 or 3 days, and then 188 defrosted and processed to obtain treatment measurement. in these influent studies, except for Fernandez-Cassi et al. [19] ; overall we saw minimal 240 reduction (less than an order of magnitude) even for samples stored over 100 days. However, 241 the effect of freeze thaw on our measurements with solids is small compared to those reported 242 by Markt et al. [18] and Fernandez-Cassi et al. [19] for infuent. We could identify only one 243 published study on SARS-CoV-2 RNA decay in solids: Hokajärvi et al. [10] report minimal decay 244 of SARS-CoV-2 RNA in a "pellet" consisting of settled solids from influent during storage at 4°C, 245 -20°C, and -75°C. 246 247 Researchers have used PMMoV as an internal process control in their efforts to monitor SARS-248 CoV-2 in wastewater [1, 20, 21] . Assuming endogenous PMMoV RNA is recovered in the sample 249 processing and RNA extraction and purification process in the same manner as SARS-CoV-2 250 RNA, then normalizing SARS-CoV-2 RNA by PMMoV RNA provides a ratio that does not 251 depend on recovery. Wolfe et al. [1] showed the ratio of SARS-CoV-2 RNA/PMMoV RNA in 252 settled solids is associated with COVID-19 incidence rates empirically, and the relationship 253 between the ratio and COVID-19 incidence rates also falls from a mass balance model that 254 relates wastewater solid concentrations to the number of people shedding SARS-CoV-2 RNA in 255 their stool. 256 257 . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted May 8, 2021 RNA measurements in wastewater solids, and whether normalizing measurements by 286 concentrations of an internal control corrects for the effects of storage. 287 288 We found storage at 4°C for short durations of 7-8 days had limited to no effect on measured 289 concentrations, but other storage conditions and durations affected concentrations by reducing 290 them by ~60%, on average, and in one case increasing them by up to 170%. However, we 291 found that the normalizing concentrations by the internal control PMMoV corrected for the 292 observed differences in many cases. 293 294 As such, we recommend short duration storage at 4°C, and normalizing concentrations of 295 SARS-CoV-2 RNA by concentrations of PMMoV in the sample. Even under the longer storage 296 conditions including those that required a freeze/thaw, changes in concentrations observed with 297 the solids were less than one order of magnitude and similar among samples subjected to the 298 same treatment. 299 300 Acknowledgements 301 . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted May 8, 2021 . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted May 8, 2021 . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted May 8, 2021 . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted May 8, 2021. 328 Table 3 . Results for comparisons between experimental treatments and controls.The percent difference 329 (% diff) in SARS-CoV-2 RNA measured in treatments versus their control is shown then the difference 330 was significantly different. "N" indicates that measurements or ratios were not different. The value after 331 the ± is the standard deviation propagated from the measurements used to make the calculation. A 332 positive percent difference indicates the treatment was lower than the control, a negative percent 333 difference indicates the treatment was higher in the control. See methods for more details on the 334 calculations. . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. Table 1 ). . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. Table 1 ). . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted May 8, 2021. ; https://doi.org/10.1101/2021.05.04.21256611 doi: medRxiv preprint Scaling of SARS-CoV-2 RNA in settled solids from multiple wastewater treatment plants to compare relative incidence of laboratory-confirmed COVID-19 in their sewersheds SARS-CoV-2 RNA in Wastewater Settled Solids Is Associated with COVID-19 Cases in a Large Urban Sewershed SARS-CoV-2 RNA concentrations in primary municipal sewage sludge as a leading indicator of COVID-19 outbreak dynamics Presence of SARS-Coronavirus-2 RNA in Sewage and Correlation with Reported COVID-19 Prevalence in the Early Stage of the Epidemic in The Netherlands Correlation of SARS-CoV-2 RNA in wastewater with COVID-19 disease burden in sewersheds Fine-Scale Temporal Dynamics of SARS-CoV-2 RNA Abundance in Wastewater during A COVID-19 Lockdown Methods for the Examination of Water and Wastewater Salt, Silica, and SARS-CoV-2 (4S): An Economical Kit-Free Method for Direct Capture of SARS-CoV-2 RNA from Wastewater The detection and stability of the SARS-CoV-2 RNA biomarkers in wastewater influent in Helsinki, Finland. Science of The Total Environment Persistence of SARS-CoV-2 in Water and Wastewater Decay of SARS-CoV-2 and surrogate murine hepatitis virus RNA in untreated wastewater to inform application in wastewater-based epidemiology High Throughput pre-analytical processing of wastewater settled solids for SARS-CoV-2 RNA analyses. protocols.io High Throughput SARS-COV-2, PMMOV, and BCoV quantification in settled solids using digital RT-PCR. protocols.io High Throughput RNA Extraction and PCR Inhibitor Removal of Settled Solids for Wastewater Surveillance of SARS-CoV-2 RNA. protocols.io The Digital MIQE Guidelines Update: Minimum Information for Publication of Quantitative Digital PCR Experiments for 2020 Effect of storage on concentrations of SARS-CoV-2 RNA in settled solids of wastewater treatment plants Detection and stability of SARS-CoV-2 fragments in wastewater: Impact of storage temperature Wastewater monitoring outperforms case numbers as a tool to track COVID-19 incidence dynamics when test positivity rates are high SARS-CoV-2 Titers in Wastewater Are Higher than Expected from Clinically Confirmed Cases Evaluation of sampling frequency and normalization of SARS-CoV-2 wastewater concentrations for capturing COVID-19 burdens in the community Estimation and worldwide monitoring of the effective reproductive number of SARS-CoV-2