Design and Validation of Sample Splitting Protocol for Comparison of SARS-CoV-2 Quantification in Wastewater

Chik, Alex H. S.; Ho, Jane J. Y.; Srikanthan, Nivetha; Dhiyebi, Hadi; Servos, Mark

doi:10.1061/(ASCE)EE.1943-7870.0001994

Open access

Technical Notes

Jun 2, 2022

Design and Validation of Sample Splitting Protocol for Comparison of SARS-CoV-2 Quantification in Wastewater

Authors: Alex H. S. Chik https://orcid.org/0000-0002-3134-9622 [email protected], Jane J. Y. Ho https://orcid.org/0000-0002-6303-2435, Nivetha Srikanthan https://orcid.org/0000-0001-7412-1313, Hadi Dhiyebi https://orcid.org/0000-0002-8101-8960, and Mark ServosAuthor Affiliations

Publication: Journal of Environmental Engineering

Volume 148, Issue 8

https://doi.org/10.1061/(ASCE)EE.1943-7870.0001994

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Abstract

Evaluations of analytical performance through interlaboratory comparisons and proficiency tests are underway globally for biomolecular-based methods [e.g., reverse-transcription quantitative polymerase chain reaction (RT-qPCR)] used in the surveillance of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in wastewater. These evaluations often rely on sharing a common reference wastewater sample that is split among participating laboratories. A known quantity of recovery surrogates can be introduced to the wastewater matrix by the coordinating laboratory as an exogenous control in a spike-and-recovery approach; however, split-sample comparisons are increasingly performed to evaluate in situ quantities of SARS-CoV-2 genetic signal native to the sample due to the lack of a universally accepted recovery surrogate of SARS-CoV-2. A reproducible procedure that minimizes the variability of SARS-CoV-2 genetic signal among split wastewater aliquots is therefore necessary to facilitate the method comparisons, especially when a large number of aliquots are required. Emerging literature has suggested that SARS-CoV-2 genetic signal in wastewater is linked to the solids fraction. Accordingly, a protocol that allows for equal distribution of solids content evenly among wastewater aliquots was also likely to facilitate even distribution of the SARS-CoV-2 genetic signal. Based on this premise, we reviewed existing sample splitting apparatus and approaches used for solids-based parameters in environmental samples. A portable batch reactor was designed, comprised of readily accessible materials and equipment. This design was validated through splitting of real wastewater samples collected from a municipal wastewater treatment facility serving a population with reported cases of COVID-19. This work applies well-established solid-liquid mixing theory and concepts that are likely unfamiliar to molecular microbiologists and laboratory analysts, providing (1) a prototype adaptable for a range of sample quantities, aliquot sizes, microbial targets, and water matrices; and (2) a pragmatic demonstration of critical considerations for design and validation of a reproducible and effective sample splitting protocol.

Introduction

Wastewater surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) using reverse-transcription quantitative polymerase chain reaction (RT-qPCR)–based methods has emerged as a potentially useful tool to complement conventional epidemiological metrics for tracking disease prevalence in a community. Interlaboratory method comparisons, such as those recently reported by Chik et al. (2021), Pecson et al. (2021), and Griffiths et al. (2021), are conducted to evaluate method performance through the distribution and analysis of a common reference wastewater sample with target analytes evenly distributed among aliquots. While the use of an exogenous control administered by the coordinating laboratory to the aliquots might better control the quantity of target analytes seeded among aliquots (e.g., Chik et al. 2021; Griffiths et al. 2021), the lack of a universally accepted recovery surrogate of SARS-CoV-2 and the uncertainty with respect to the ability of the surrogate(s) to adequately represent the recovery of in situ SARS-CoV-2 in real wastewaters (e.g., Kantor et al. 2021) have led to the need for such evaluations to be made directly based on SARS-CoV-2 and other indicators present within the original wastewater sample collected.

Few studies have reported a detailed approach for sample splitting to compare RT-qPCR-based methods for SARS-CoV-2 genetic material. Agitation and manual pouring of the sample in portions is often sufficient when few aliquots are required (e.g., Chik et al. 2021), but becomes less effective and impractical when larger sample quantities and aliquots are required (Praner and Sprewell 1992). Pecson et al. (2021) collected a single 40 US gallon (approximately 150 L) grab wastewater sample and distributed the bulk sample into 1 US gallon containers (3.785 L, one for each lab) while continuously mixing the bulk sample to promote homogeneity. The homogeneity of the samples was confirmed by testing aliquots obtained through evaluating total suspended solids, temperature, and pH as indicators of sample homogeneity. Although a detailed approach was not available for the stated purpose, emerging studies have suggested the SARS-CoV-2 genetic signal in wastewater is likely linked to the solids/colloidal fraction (Balboa et al. 2021; D’Aoust et al. 2021; Li et al. 2021; Palmer et al. 2021). This suggests that an approach that achieves equal splitting of the solids content in the wastewater might be effective, and therefore has been assumed as a key consideration of the sample splitting design. A focused review of approaches used for splitting samples of stormwater and surface water sources with similar solids content (i.e., total suspended solids) revealed that two major configurations have been deployed. The cone configuration (e.g., Dekaport, Geotech Environmental Equipment, Denver) is usually comprised of a vessel that gravity drains a sample into a splitting chamber with evenly spaced outlets (Capel and Larson 1996; Pickering 1978, 1980). This configuration is most appropriate for fewer aliquots of lesser volumes. The churn configuration involves continuous agitation of a sample within a vessel while draining or siphoning portions as aliquots (Wilde et al. 2006). When a larger number and greater volume of aliquots are desired (such as for interlaboratory method comparisons), the churn configuration is more appropriate because it is not limited by a finite number of outlets in the cone configuration.

Given that existing churn configuration splitters are typically

< 15 L

and have only been validated for their ability to split the solids content of a water matrix, the main goal of this work was to design, build, and validate a wastewater sample splitting approach and apparatus that does not impart additional variability of SARS-CoV-2 genetic signal among aliquots beyond that typically observed between aliquots of the same sample analyzed using a single analytical method. To increase the transferability and feasibility of this approach, materials and equipment that are commonly available to laboratories or easily procured off-the-shelf were used where possible, with special consideration given to portability and ease of use.

Design and Methods

Sample splitting for wastewater microbial quality analyses has unique considerations and design constraints (Table S1). The splitting process should minimize overall worker exposure (e.g., avoid aerosolization of the wastewater and its constituents). The splitting apparatus should also allow thorough cleaning to minimize potential for cross contamination if deployed at multiple sites and/or used on multiple occasions. Specific design considerations related to interlaboratory split-sample analysis may include flexibility to accommodate more aliquots of greater volumes. For interlaboratory method comparisons of approaches to quantify SARS-CoV-2 genetic signal, the SARS-CoV-2 genetic signal should be consistent among aliquots tested using the same method. Relative standard deviations (RSDs) ranging from 25% to 35% have been deemed acceptable to demonstrate reproducibility of RT-qPCR methods (Forootan et al. 2017; Haugland et al. 2016; Klymus et al. 2020; Kralik and Ricchi 2017). Feng et al. (2021) reported median RSDs of duplicate analyses for SARS-CoV-2 N1 gene target in real wastewater of 14% between assay replicates, and 24% between duplicate filters, with RSDs observed generally below 40%. Accordingly, aliquots split successfully should exhibit a comparable level of variability.

The churn configuration was determined as the preferred basis for the design given its suitability for handling a range of aliquot sizes and volumes consistent with those required for interlaboratory method comparisons. Off-the-shelf churn sample splitters are readily available for lesser sample volumes [e.g., 14-L churn splitters (Barr 2018)]. Accordingly, a redesign and scaling up of the churn configuration using off-the-shelf components was necessary. A 7 US Gallon (

\sim 26.5 L

) plastic pail (S-16969W, Uline, Milton, Ontario, Canada) was selected as the mixing reservoir due to its sufficiently large capacity (usable volume approximately 30.5 L) and regular cylindrical geometry (

diameter = 0.285 m

). This geometry simplifies design calculations (Tables S2 and S3) while promoting predictable mixing patterns. To maximize consistency of the mixing, a single impeller mounted on a stainless steel shaft (GH-04552-05, Cole-Parmer North America, Vernon Hills, Illinois) attached to a laboratory stand mixer (RK-50800-00, Mfr # BDC1850, Caframco, Georgian Bluffs, Ontario, Canada) was selected as a means of imparting mixing energy to keep solids evenly suspended in the mixing reservoir. To promote axial flow (and thereby minimize settling of solids in the sample) and more thorough mixing, the 3-in. (

\sim 7.5 cm

) propeller-type stainless steel impeller (RK-04552-60, Cole-Parmer) was mounted at an angle and positioned off-center within the reservoir. The impeller was suspended off the bottom of the pail at a height approximately equal to a third of the reservoir diameter (10 cm). Aliquots were drawn from the volume above the level of the submerged impeller; the impeller was never exposed above the level of the wastewater sample to avoid entrainment of air into the sample (and possible aerosolization of wastewater and its constituents).

The minimum agitation speed to achieve complete suspension of solids in the reservoir estimated using Zwietering’s equation (Zwietering 1958) was adjusted using ratios reported by Oldshue (1983) to determine the agitation speed required for achieving uniform suspension of solids in the reservoir (Paul et al. 2003). The rotational speed of 1,000 rpm was determined to be adequate for suspending solids expected to pass through coarse grit screens in Ontario (0.025 m) (Ministry of Environment, Conservation and Parks 2008). This rotational speed allows for a velocity gradient (G-value) of

379 s^{- 1}

to be achieved, which is greater than the minimum G-value recommended of

300 s^{- 1}

used in rapid mixing of solutes in water treatment engineering (Metcalf & Eddy, Inc. et al. 2013). The approach for determining operational conditions that promotes total uniform suspension of solids is summarized in the Supplemental Materials. Relevant design calculations have also been included to maximize transferability and adaptability of this design to other applications.

The procedure for setting up and operating the sample splitting apparatus (as shown in Fig. 1) is also detailed in the Supplemental Materials. Briefly, the reservoir is filled with the wastewater sample. After initiating the impeller to reach the desired mixing speed and approximately 30 s of continuous mixing (approximately three times the theoretical hydraulic residence time when the reservoir is full), a dedicated plastic pail pump (H-2634, Uline) installed on a pail lid (S-9943BL, Uline) precut to accommodate the mixing shaft and impeller is primed with the sample. [A stainless steel pail pump (H-4897, Uline) can be reused in place of the single-use plastic pail pump with appropriate decontamination procedures.] The sample is subsequently aliquoted by dispensing the wastewater into individual precleaned 500-mL Pro-Clean high-density polyethylene (HDPE) wide-mouth packer bottles (Systems Plus, Baden, Ontario, Canada). Field parameters (pH, temperature, electrical conductivity, dissolved oxygen) were monitored throughout the dispensing of aliquots using a field-calibrated multiparameter meter (Thermo Scientific Orion Star A3295 portable multiparameter meter, Thermo Scientific, Waltham, Massachusetts) operated in accordance with the manufacturer’s instructions. Turbidity was also monitored using a portable photometric turbidimeter (Hach, Loveland, Colorado). If more aliquots or greater volumes are required beyond that available in the reservoir (i.e., without exposing the impeller to air above the surface of the wastewater), aliquoting could be performed by compositing each bottle with equal portions of wastewater sample from multiple rounds after refilling the reservoir with additional wastewater.

Fig. 1. Stirred, not shaken: design and validation of a sample splitting protocol that facilitates comparisons of SARS-CoV-2 quantification in wastewater: (a) wastewater grab sample is collected, post-grit filter; (b) applying solid-liquid mixing theory and concepts, the wastewater sample is continuously stirred and aliquoted; and (c) evenly distributed solids and viral genetic signals among aliquots facilitate method comparisons of SARS-CoV-2 quantification in wastewater.

Protocol Validation

The effectiveness of the sample splitting apparatus/protocol for evenly splitting SARS-CoV-2 genetic signal was validated by collecting an 80-L raw wastewater grab sample, post-grit filter, from a wastewater treatment facility in a sewershed known to be subject to active COVID-19 cases on January 20, 2021. At the time of sample collection, 821 active cases of COVID-19 were reported in the municipality from which the sample was collected. To mimic the process for splitting a large number of 500-mL aliquots, each sample bottle was filled by approximately a third over three discrete rounds to composite wastewater dispensed at the beginning, middle, and end of each individual round. Aliquots were put on ice and transported to the laboratory immediately for RT-qPCR (details provided in Supplemental Materials) testing for the genetic material of SARS-CoV-2 and pepper mild mottle virus (PMMoV), a fecal viral indicator of wastewater strength. Heat-inactivated human coronavirus strain 229E (HCoV-229E) was also spiked in as a whole process recovery control in some replicates and quantified using RT-qPCR. The ability for the sample splitting apparatus/procedure to evenly split solids content was also evaluated. Turbidity and total suspended solids (TSS) were evaluated in aliquots coinciding with those collected for RT-qPCR testing as field and laboratory surrogate measures of solids content from the split samples, respectively.

Validation Testing

Considering the anticipated role of solids in the fate of SARS-CoV-2 in wastewater, the ability for the sample splitting apparatus to evenly split surrogate parameters linked to solids was believed to be critical. Turbidity [

210 \pm 9.9

NTU (mean ± standard deviation)] and TSS (

283 \pm 22.3 mg / L

) yielded results that suggested a good degree of consistency among the aliquots collected on January 20, 2021. Each aliquot was comprised of a composite of the beginning (Sample X, Aliquot 1), middle (Sample X, Aliquot 2), and end (Sample X, Aliquot 3) of each round of sample splitting after refilling the sample reservoir. A side-by-side visual check of the aliquots that have settled (30 min postsplitting) (Fig. S1) confirmed that the aliquots were qualitatively consistent. However, because turbidity (as well as the visual check) are optical assessments that can be influenced by both particles and colored material that has no intrinsic physical, chemical, or biological significance (Campbell Scientific 2014), the measurement of total suspended solids provides a more directly relevant indicator of solids content (APHA et al. 2017).

The identical procedure performed at other wastewater treatment facilities on separate occasions (Samples A, B, and C) suggested a similar degree of concordance of TSS concentrations among aliquots from the same wastewater sample using the sample splitting approach described herein (Table 1). The RSDs of TSS in the various wastewater matrices examined are largely consistent with the expected precision of the analytical method itself. The published precision range for Standard Method 2540D states that RSDs of between 10% and 33% could be expected (APHA et al. 2017). TSS concentrations reported in wastewater samples split from two US wastewater treatment facilities (also for the purpose of SARS-CoV-2 interlaboratory methods comparisons) also exhibited a degree of variation within this range (8% and 14%, respectively), albeit at TSS concentrations almost double that of the present study (

420 \pm 60

and

520 \pm 40 mg / L

) (Pecson et al. 2021).

Table 1. Total suspended solids concentrations of aliquots from four grab wastewater samples

Category	Sample
Category	X	A	B	C
Concentration, mean ± SD ( $mg / L$ )	$283.0 \pm 22.3$	$220.0 \pm 43.6$	$243.3 \pm 20.8$	$206.7 \pm 23.1$
Relative standard deviation (%)	7.9	19.8	8.6	11.2

For aliquots split from the grab sample collected on January 20, 2021, four viral targets were quantified using RT-qPCR (Table 2). While final concentration estimates of viral targets are commonly reported and provide a more tangible result, observed quantification cycles (Cqs) for each duplicate and aliquot offer a commonly accepted measure of precision for RT-qPCR results that is independent of biases attributable to the measurement of the standard material used for quantitation (Ahmed et al. 2021; Bivins et al. 2021). The standard deviation of observed Cqs for SARS-CoV-2 (N1 and N2 gene fragments) and PMMoV evaluated was consistently less than approximately 0.5 Cq. This suggests that the sample splitting procedure did not appear to introduce more variability beyond that inherent to RT-qPCR results (Kralik and Ricchi 2017) for the evaluation of the viral targets present in the wastewater sample.

Table 2. Summary of results obtained using RT-qPCR for viral targets estimated in wastewater Sample X

Aliquot from Sample X	Viral target
	SARS-CoV-2				PMMoV		HCoV-229E (spiked-in)
	N1 gene target		N2 gene target		PMMoV		HCoV-229E (spiked-in)
	Cq	Concentration estimate	Cq	Concentration estimate	Cq	Concentration estimate	Cq	Concentration estimate
Aliquot 1
Replicate 1^a	33.3	17.3	34.3	19.2	24.8	$1.4 \times 10^{5}$	35.9	93.3
Replicate 2	33.2	18.5	33.9	25.0	25.3	$1.0 \times 10^{5}$	ND
Average	33.3	17.9	34.1	22.1	25.1	$1.2 \times 10^{5}$	N/A
Aliquot 2
Replicate 1^a	32.9	23.7	33.6	31.5	24.4	$1.8 \times 10^{5}$	36.3	72.1
Replicate 2	33.1	20.2	33.5	32.6	25.2	$1.2 \times 10^{5}$	ND
Average	33.0	22.0	33.5	32.1	24.8	$1.5 \times 10^{5}$	N/A
Aliquot 3
Replicate 1^a	33.7	13.6	33.9	25.8	24.5	$1.7 \times 10^{5}$	35.5	123.8
Replicate 2	33.4	16.2	33.6	29.6	24.9	$1.4 \times 10^{5}$	ND
Average	33.6	14.9	33.7	27.7	24.7	$1.6 \times 10^{5}$	N/A
Mean (across all aliquots)	$33.3 \pm 0.3$	$18.2 \pm 3.6$	$33.8 \pm 0.3$	$27.3 \pm 5.0$	$24.9 \pm 0.2$	$1.4 \times 10^{5} \pm 1.8 \times 10^{4}$	$35.9 \pm 0.4$ ^a	$96.4 \pm 26.0$ ^a
Relative standard deviation (%)	—	19.5	—	18.3	—	12.7	—	27.0

Note: Aliquots 1, 2, and 3 were composited over three rounds of refilling the sample splitting reservoir, collected at the beginning, middle, and end of each individual round. The reported Cq values are the arithmetic means of triplicate PCR reactions; concentration estimates are in units of gene copies per milliliter of wastewater. ND = non-detect.

a

Across replicates spiked with whole process control HCoV-229E.

Estimated SARS-CoV-2 N2 concentrations were consistently greater in magnitude than those observed for N1 for all duplicates tested. However, neither the variability nor the observed difference in magnitude of the mean aliquot concentration estimates using either gene target were significantly different (

p = 0.34

,

F

-test for sample variances;

p = 0.06

, two-sample

t

-test assuming equal variances). Ultimately, this was reflected by the similar RSDs of N1 (19.5%) and N2 (18.3%) observed in this study, which fall well within the range of variability reported between sample duplicates in real wastewater previously reported (e.g., Feng et al. 2021). PMMoV exhibited less variability (

RSD = 12.7 %

) compared to the SARS-CoV-2 gene targets among aliquots. The RNA signal of HCoV-229E was consistently absent in duplicates for which this whole process recovery control was not administered, but exhibited slightly more variability (

RSD = 27.0 %

) than the viral targets present within the wastewater sample. However, this level of variability remains well within the 25%–35% RSD range deemed acceptable to demonstrate reproducibility of RT-qPCR methods (Forootan et al. 2017; Haugland et al. 2016; Klymus et al. 2020; Kralik and Ricchi 2017). In a separate wastewater sample splitting event performed using the same procedure described herein (Table S5), intra- and interaliquot variability of in situ viral targets’ genetic signals in the wastewater were again characterized and demonstrated to be comparable and within the acceptable range of variability. Collectively, these results demonstrate that the wastewater sample splitting approach described is effective for the overall goal of minimizing additional variability to SARS-CoV-2 (as well as PMMoV) genetic signal among aliquots and is suitable for applications such as interlaboratory method comparisons.

Conclusions

Based on emerging evidence by other works that the in situ SARS-CoV-2 genetic signal has been linked to the solid fractions of wastewater, the design of an apparatus (and accordant protocol) that distributes SARS-CoV-2 RNA and solids content evenly in split-sample aliquots was undertaken. The design was validated by splitting aliquots of a real wastewater sample with SARS-CoV-2 RNA for analysis using a single method. The variability of four viral RNA concentration estimates (in situ SARS-CoV-2 N1, SARS-CoV-2 N2, PMMoV, spiked-in HCoV-229E) associated with the aliquots split using this approach was well within the ranges typically expected from analysis of replicates using the same RT-qPCR-based method (RSD in situ targets

< 20 %

; RSD spiked-in

target = 27 %

in this study). Solids-related parameters were also evaluated for the aliquots. The variability of TSS from aliquots split using this approach was consistent with those expected of evenly split aliquots (

RSD < 20 %

in this study). While TSS provides a more direct indicator of solids content of the wastewater, this physically based parameter must be determined in a laboratory. Accordingly, turbidity measurements throughout the sample splitting process (

RSD = 5 %

in this study) and a visual inspection of the aliquots approximately 30 min postsplitting (to verify whether settled wastewater characteristics are qualitatively consistent) may provide additional field verification that an even distribution of solid concentrations—and thereby analytes of interest that are solids associated—was achieved.

The design and operating procedure of the sample splitting device herein described offers a reliable, cost-effective means of sample splitting that is portable and readily adaptable, while overcoming limitations of conventional sample splitting apparatus that cannot accommodate higher total volumes. The total cost of the sample splitting device is approximately USD 2,500, of which the mixer assembly (stand, brushless mixer)—which is commonly found in many analytical laboratories—accounts for approximately 90% of the total cost. The design and validation approach demonstrated in this work could serve as a template for subsequent modification and application to a broader range of microbial analytes in environmental matrices.

Supplemental Materials

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Data Availability Statement

All data, models, and code generated or used during the study appear in the published article.

Acknowledgments

We acknowledge the support of the Canada Research Chairs program, Global Water Futures and Ontario Ministry of the Environment, Conservation and Parks Wastewater Surveillance Initiative. We thank Shirley Anne Smyth, Rhonda Reeves, and Harold Malle (Environment and Climate Change Canada) for insightful discussions about sample splitting for environmental samples. Mark Sobon kindly provided assistance in the procurement of equipment and materials for building the sample splitting apparatus. Dr. Scott Joseph Boegel of Dr. Marc Aucoin’s laboratory in the Department of Chemical Engineering (University of Waterloo) kindly propagated the HCoV-229E used as the whole process recovery control in this study. Dominika Celmer-Repin and Trevor Brown (Regional Municipality of Waterloo) kindly provided access to wastewater treatment facilities; Hank Andres, Chris Adams, and Kyle Walton (Ontario Clean Water Agency) are thanked for coordinating site access.

References

Ahmed, W., et al. 2021. “Minimizing errors in RT-PCR detection and quantification of SARS-CoV-2 RNA for wastewater surveillance.” Sci. Total Environ. 805 (Jan): 149877. https://doi.org/10.1016/j.scitotenv.2021.149877.

Abstract

Introduction

Design and Methods

Protocol Validation

Validation Testing

Conclusions

Supplemental Materials

Data Availability Statement

Acknowledgments

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