key: cord-0333654-ipxotmj9
authors: Oh, C.; Sashittal, P.; Zhou, A.; Wang, L.; El-Kebir, M.; Nguyen, T. H.
title: Regional and temporal variations affect the accuracy of variant-specific SARS-CoV-2 PCR assays
date: 2021-11-09
journal: nan
DOI: 10.1101/2021.11.08.21266083
sha: 3cf74d9b13a86ade214de8766c4d8a56d1c0935f
doc_id: 333654
cord_uid: ipxotmj9

Monitoring the prevalence of SARS-CoV-2 variants is necessary to make informed public health decisions during the COVID-19 pandemic. PCR assays have received global attention, facilitating rapid understanding of variant dynamics because they are more accessible and scalable than genome sequencing. However, as PCR assays target only a few mutations, their accuracy could be compromised when these mutations are not exclusive to target variants. Here we show how to design variant-specific PCR assays with high sensitivity and specificity across different geographical regions by incorporating sequences deposited in the GISAID database. Furthermore, we demonstrate that several previously developed PCR assays have decreased accuracy outside their study areas. We introduce PRIMES, an algorithm that enables the design of reliable PCR assays, as demonstrated in our experiments that enabled tracking of dominant SARS-CoV-2 variants in local sewage samples. Our findings will contribute to improving PCR assays for SARS-CoV-2 variant surveillance.

Introduction 4 by a group of different mutations located throughout the entire genome. Therefore, distinct variants 60 may have the same mutations, reducing specificity when used in PCR assays 14 . 61 In this study, we introduce a computational tool, PRIMES (PRIMer Efficacy Sleuth), that 62 can be used to analyze sequences available in open source databases such as GISAID 15,16 , to predict 63 the sensitivity and specificity of a PCR assay to detect specific pathogen lineages of interest. 64 Moreover, for a given set of mutations characterizing the target variant, PRIMES can also identify 65 a subset of variant-specific mutations for designing PCR assays with high specificity and 66 sensitivity. Using PRIMES, we show multiple examples of previous PCR assays 13,17,18 that were 67 successfully applied to certain study areas might not work for other regions (Fig. 1) . We also 68 demonstrate that the PCR assays designed using PRIMES successfully identify the dominant 69 lineages in sewage samples from Champaign County, IL, USA. We conclude that PCR assays 70 ought to be designed or modified considering regional and temporal variations and that in silico 71 analyses using open source databases can address the weaknesses of PCR assays. These findings 72 will allow PCR assays to be applied more reliably for SARS-CoV-2 surveillance. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

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Analysis and design of PCR assays using PRIMES 78 As new variants of SARS-CoV-2 emerge and fade away throughout the world, a number lineages are limited to where they emerged, outbreaks of some lineages occasionally spread across 84 the borders and become global concerns (such as variants of concern (VOCs) and variants of 85 interest (VOIs)). Thus, regional and temporal differences in variant dynamics have to be 86 considered for PCR assays. 87 The most widely used computational tool for assigning lineages to SARS-CoV-2 genomes 88 is the Phylogenetic Assignment of Named Global Outbreak Lineages (Pangolin, 89 https://pangolin.cog-uk.io/). Pangolin is a lineage designation pipeline that takes a FASTA file as 90 input, containing one or more query sequences. Each query sequence is first aligned to the SARS- 91 CoV-2 reference genome (Wuhan-Hu-1, NC_045512.2) using minimap2 v2.17 20 . After trimming 92 the non-coding regions in the 5' and 3' ends of the aligned sequences, they are assigned to the 93 most likely lineage out of all currently designated lineages using an underlying machine learning 94 model referred to as PangoLEARN. The current version of PangoLEARN is a decision tree that is 95 trained on data from GISAID that was manually curated with lineages. 96 By considering the lineage designation of Pangolin as ground truth, we perform an in silico 97 analysis of the efficacy of PCR assays using PRIMES (available at https://github.com/elkebir-98 group/primer-analysis). Specifically, we search for the probing sequence (containing a mutation 99 All rights reserved. No reuse allowed without permission.

(which was not certified by peer review) 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 November 9, 2021. ; https://doi.org/10.1101/2021.11.08.21266083 doi: medRxiv preprint 6 targeted by the PCR assay) in each GISAID sequence and then estimate the overall specificity and 100 sensitivity of the PCR assay. While this information is crucial in its own right, it can also be used 101 to design lineage-specific PCR assays. Specifically, for a lineage of interest and a set of 102 characteristic mutations, we use PRIMES to identify the set of mutations that should be targeted 103 by PCR assays to get high specificity and sensitivity. We employ this approach to design PCR 104 assays to detect the presence SARS-CoV-2 of both Alpha (e.g., B.1.1.7) and Delta (e.g., B.1.617.2) 105 variants in sewage samples. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) 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 November 9, 2021. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

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We conducted a similar analysis for another PCR assay targeting mutation S:Δ144/145 to 163 detect the Alpha variant 13 . This assay was applied to samples from wastewater treatment plants 164 and selected residential buildings across the USA to track the occurrence of the Alpha variant over 165 time in 19 communities. SI Fig. 1a shows that this assay works well for GISAID sequences from (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (Fig. 3a) . However, the B.1.1.519 lineage was dominant in Mexico (n=28,956) and 191 explained 30% of the total GISAID sequences from January 2021 to October 2021 (Fig. 3b) . 192 Therefore, our analysis shows that the PCR assay targeting S:T478K would estimate that the Delta (which was not certified by peer review) 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 November 9, 2021. The examples of regional and temporal characteristics affecting the accuracy of PCR (which was not certified by peer review) 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 November 9, 2021. ; https://doi.org/10.1101/2021.11.08.21266083 doi: medRxiv preprint 13 respectively. The number of B.1.258 lineage was less than 0.5% of total sequences worldwide, but 214 it accounted for 54% of cases in Cyprus. 215 We summarized SARS-CoV-2 lineages that have the same mutation that our target variant 216 possesses in SI Table 1 . When we use PCR assays targeting certain mutations, this table will help 217 identify the lineages that would interfere with our PCR assay. In SI Table 2 , we also tabulated 218 countries where each of the SARS-CoV-2 lineages summarized in SI Table 1 accounted for higher 219 than 1% of total sequences. This table will explain whether the lineages that would interfere with 220 your PCR assays are dominant in the study areas. By interpreting SI Table 1 and SI Table 2 221 together, we can find various examples where certain PCR assays would not work reliably. In Design of variant-specific PCR assays considering regional and temporal characteristics 228 We describe the proposed workflow to design variant-specific PCR assays considering regional 229 and temporal variant dynamics using PRIMES (Fig. 4a) . Our goal is to design variant-specific 230 PCR assays to track variants with significant prevalence in the USA, with a particular focus on the 231 state of Illinois. (which was not certified by peer review) 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 November 9, 2021. ; https://doi.org/10.1101/2021.11.08.21266083 doi: medRxiv preprint 14 using Pangolin (Fig. 4b, e) . Focusing on the variant dynamics in the state of Illinois (Fig. 4b) and 0.4% of total sequences, respectively. Similar trends were observed in sequences collected 243 throughout the USA (Fig. 4e) . Based on the variant dynamics of our regions of interest, we decided 244 to design PCR assays to enable monitoring of the two major variants, the Alpha and the Delta 245 variants.

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The copyright holder for this preprint this version posted November 9, 2021. ; https://doi.org/10.1101/2021.11.08.21266083 doi: medRxiv preprint Second, we designed PCR assays to find unique mutations that are exclusive to our lineage 257 of interest. We utilized https://covariants.org to list up nonsynonymous mutations that define target 258 variants (SI Table 1 ). We focused on mutations located in the spike gene, which has a higher (which was not certified by peer review) 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 November 9, 2021. The fourth step is to design the allele-specific primers for the selected mutations. Since 286 both our selected target mutations are single nucleotide polymorphisms (SNPs), we designed 287 All rights reserved. No reuse allowed without permission.

(which was not certified by peer review) 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 November 9, 2021. ; https://doi.org/10.1101/2021.11.08.21266083 doi: medRxiv preprint allele-specific qPCR assays in which either a forward or a reverse primer target the SNP at the 3' 288 end with a mismatch near the SNP location to improve the specificity of the assays 13 . All RT-289 qPCR assays were designed using PrimerQuest (Integrated DNA Technologies; IDT, USA) to 290 have an annealing temperature from 58 to 63 ℃ for primers and GC contents from 30 to 60%.

Finally, we estimate the efficacy of the candidate RT-qPCR assays using PRIMES.

Specifically, we determine the sensitivity and specificity of our assays on the GISAID samples 293 collected from the regions of interest by searching for sequences of a forward primer and a reverse 294 primer in each query sequence. Note that the sequences of reverse primers were converted to 295 reverse sequences to have all sequences, including primers and viruses, on the same strand. If the 296 viral sequence includes the forward and reverse sequences, we assumed that the PCR assay would 297 detect the viral sequence (an illustrative example is shown in SI Fig. 3) . We note that operational for the previously developed PCR assays in their regions of interest (see Fig. 1, 2 and 3) . In the 310 All rights reserved. No reuse allowed without permission.

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The copyright holder for this preprint this version posted November 9, 2021. ; https://doi.org/10.1101/2021.11.08.21266083 doi: medRxiv preprint subsequent section, we demonstrate this performance of our PCR assays translated to synthetic 311 controls and actual sewage samples collected in our community.

Verification of PRIMES-designed PCR assays by synthetic RNA controls 314 We applied the RT-qPCR assays designed with PRIMES to synthetic RNA controls for 315 WT, Alpha, and Delta variants to experimentally confirm the sensitivity (i.e., the limit of 316 quantification; LOQ and limit of detection; LOD) and specificity (i.e., cross-reactivity). Regarding 317 sensitivity, we found that the LOQs for total SARS-CoV-2, Alpha variant, and Delta variant were 318 all 10 gene copies (gc)/µL or 50, 30, and 30 gc/reaction, respectively (SI Fig. 5a) . Also, the LODs 319 of RT-qPCR assays for total SARS-CoV-2, Alpha variant, and Delta variant were 1.0, 1.3, and 1.3 320 gc/µL or 5.0, 3.9, and 3.8 gc/reaction, respectively (SI Fig. 5b) . Because LODs for our assays 321 were close to the theoretical LODs of RT-qPCR (3.0 gc/reaction) 23 , we concluded that our RT-322 qPCR assays are sensitive to detect RNA of target variants.

As for the cross-reactivity, we found that when the concentrations of the RNA synthetic 324 control were high (i.e., 10 4 and 10 5 gc/µL), we detected Cq values from WT RNA controls. This 325 finding suggests that the presence of WT caused false positives for the Alpha variant detection 326 (SI Fig. 6a) . However, the Cq value differences between the Alpha variant and WT were greater 327 than 11 that is about 10 3 -fold difference in RNA concentrations. This difference in Cq values is 328 equivalent to less than 0.1% error when quantifying the Alpha variant, and thus we considered this 329 error is acceptable for our study. When the RNA synthetic control concentrations were low (i.e., 330 less than 10 3 gc/µL), the Cq values from WT were lower than LOD, which will be disregarded in 331 this study, so the false positives were not detected. We found similar results from the specificity 332 experiments for the Delta variant assay (SI Fig. 6b) . When the concentrations of the RNA synthetic 333 All rights reserved. No reuse allowed without permission.

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The copyright holder for this preprint this version posted November 9, 2021. ; https://doi.org/10.1101/2021.11.08.21266083 doi: medRxiv preprint controls were high (i.e., 10 4 and 10 5 gc/µL), the Cq value differences from Delta variant and WT 334 were greater than 13. At the lower concentration (i.e., less than 10 3 gc/µL), the Cq values from 335 WT (i.e., false positives) were less than LOD. Because the measured cross-reactivities by WT were 336 negligible, we concluded our RT-qPCR assays are specific to measure target variants. 337 We further confirmed the applicability of PRIMES-designed PCR assay to determine 338 predominant variants in mixtures of synthetic RNA controls. The results from the mixtures of 339 synthetic RNA controls are presented in Fig. 5a and 5b . The y-axis shows the prevalences, which 3. In addition, we found that the PCR assays assigned the dominant variant correctly when the 353 total virus concentrations were 10 1 gc/µL for all mixing ratios (Fig. 5b) . However, the statistical 354 analysis showed that the comparisons of prevalences determined by the RT-qPCR were significant 355 only when the mixing ratios were 0.9:0.1 or vice versa for mixtures of WT and Alpha variant or 356 All rights reserved. No reuse allowed without permission.

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The copyright holder for this preprint this version posted November 9, 2021. ; https://doi.org/10.1101/2021.11.08.21266083 doi: medRxiv preprint 20 Alpha variant and Delta variant. Note that when total virus concentrations were 10 1 gc/µL, 357 concentrations of each synthetic RNA control were ranging from 1×10 0 to 9×10 0 gc/µL depending 358 on the mixing ratios, which were less than their LOQs (10 1 gc/µL). Based on these findings, we 359 concluded that our RT-qPCR assays could find the dominant variant when total SARS-CoV-2 360 concentrations are higher than LOQs (10 1 gc/µL) and the prevalence of target variants is higher 361 than 0.9 (Fig. 5b) . When the total SARS-CoV-2 concentrations become higher, Alpha and Delta 362 variant concentrations are higher than LOQs of the RT-qPCR assays (10 1 gc/µL), our RT-qPCR 363 assays can assign the dominant variant when its prevalence is higher than 0.7 (Fig. 5a) . (which was not certified by peer review) 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 November 9, 2021. 378 We applied our PCR assays to six different local sewage samples. We first obtained RNA 379 extracts from those sewage samples. The total SARS-CoV-2 concentrations (i.e., N gene) of these 380 RNA extracts ranged from 1.4 × 10 1 to 1.8 × 10 2 gc/µL (SI Table 3 ). After accounting for 381 All rights reserved. No reuse allowed without permission.

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The copyright holder for this preprint this version posted November 9, 2021. respectively. On the other hand, none of the Alpha and Delta variants presented higher than 0.5 390 prevalence for Sample #2, #3, and #4, so we assigned Others to these three samples.

To further confirm whether the RT-qPCR results were correct, we conducted NGS analysis (Table 1) . Therefore, the agreement between the NGS analysis and 404 All rights reserved. No reuse allowed without permission.

(which was not certified by peer review) 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 November 9, 2021. ; https://doi.org/10.1101/2021.11.08.21266083 doi: medRxiv preprint RT-qPCR assays supports that our RT-qPCR can assign the most likely variant for the local sewage 405 samples. (which was not certified by peer review) 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 November 9, 2021. ; https://doi.org/10.1101/2021.11.08.21266083 doi: medRxiv preprint outbreak.info) to design PCR primers to determine the dominant SARS-CoV-2 variants (i.e., (which was not certified by peer review) 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 November 9, 2021. ; https://doi.org/10.1101/2021.11.08.21266083 doi: medRxiv preprint Perfect loci to target viral mutation are not realistic because viruses evolve randomly, so 444 one that looks perfect could be affected by emerging variants. For example, the S:Δ69/70 mutation 445 used to be a unique mutation for the Alpha variant, but the Eta variant, which appeared later, also 446 has the same mutation. Thus, if the S:Δ69/70 is considered an exclusive mutation to the Alpha Table 4 . Also, detailed information from sample collection to 466 All rights reserved. No reuse allowed without permission.

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The copyright holder for this preprint this version posted November 9, 2021. ; https://doi.org/10.1101/2021.11.08.21266083 doi: medRxiv preprint data analysis is described in SI Table 5 . Briefly, we used ISCO automatic samplers (6712 ISCO, 467 Teledyne ISCO, USA) to collect three-day composite sewages (about 2 L) from the sewer were ready. The same sample preparation processes were applied to drainages discharged from a 481 food processing industry whenever we processed sewage samples. There are no sources of human 482 feces that merged to these drainages, which were therefore used for negative controls. Indeed, we 483 did not detect any SARS-CoV-2 from these negative controls. Therefore, we are confident there (which was not certified by peer review) 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 November 9, 2021. ; https://doi.org/10.1101/2021.11.08.21266083 doi: medRxiv preprint = !ℎ$ 0#AB$" ': C9'@ )0 456 $7*".8* !ℎ$ 0#AB$" ': C9'@ )0 )0)*)./ ($3.1$ (Eq. 5) where E is a qPCR efficiency, SD is a standard deviation of Cq values.

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The copyright holder for this preprint this version posted November 9, 2021. ; https://doi.org/10.1101/2021.11.08.21266083 doi: medRxiv preprint 28 510 PCR assays for SARS-CoV-2 variant detection in synthetic RNA control 511 We applied the RT-qPCR assays to 10-fold serial dilutions of synthetic RNA controls to determine 512 LOQs and LODs. LOQ was defined as the lowest concentration with coefficient of variation (CV) 513 less than 35% 36 and LOD was defined as the concentration at which RNA samples test positive 514 (i.e., Cq<40) with 95% probability. For example, we applied the RT-qPCR assay for Alpha variant (Fig. 4b) . Total SARS-CoV-2 concentrations (i.e., N gene concentrations) of 527 the mixtures were 10 4 and 10 1 gc/µL, which are the reasonable concentration range of SARS-CoV-528 2 of local sewage samples 24 . Also, we mixed the two different RNA controls with four different 529 ratios (i.e., 9:1, 7:3, 3:7, and 1:9) to mimic different scenarios of variant dynamics.

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The copyright holder for this preprint this version posted November 9, 2021. ; https://doi.org/10.1101/2021.11.08.21266083 doi: medRxiv preprint PCR assays for SARS-CoV-2 variant detection in sewage samples 532 We conducted six different RT-qPCR assays to analyze sewage samples. Three of them targeted 533 different loci of SARS-CoV-2 genome for virus quantification and the dominant variant detection.

The other three assays were applied to measure bovine coronavirus (BCoV), pepper mild mottle 535 virus (PMMoV), and Tulane virus (TV), which were used for calculation of virus recovery 536 efficiency, normalization of SARS-CoV-2 to human feces, and inhibition tests, respectively. 2-537 fold diluted the RNA samples in molecular biology grade water (Milliporesigma, USA) before the 538 quantification. We used Taqman-based RT-qPCR for the N1 gene detection as suggested by CDC 539 and SYBR-based RT-qPCR for the other six assays (SI Table 6 ). The SYBR-based RT-qPCR 

The PCR cocktail for the one-step RT-qPCR was placed in 96-well plates (4306737, Applied 545 Biosystems, USA) and analyzed by a qPCR system (QuantStudio 3, Thermo Fisher Scientific, 546 USA). The thermocycle began with 10 minutes at 50℃ and 1 minute at 90℃ followed by 40 cycles 547 of 30 seconds at 60℃ and 1 minute at 90℃. The Taqman-based RT-qPCR was initiated by mixing qPCR system as used for the SYBR-based RT-qPCR, except for a different thermal cycle (5 552 minutes at 50℃, 20 seconds at 95℃ followed by 45 cycles of 3 seconds at 95℃ and 30 seconds 553 at 55℃). We used synthetic RNA controls to get standard curves for WT, Alpha variant, and Delta 554 All rights reserved. No reuse allowed without permission.

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The copyright holder for this preprint this version posted November 9, 2021. ; https://doi.org/10.1101/2021.11.08.21266083 doi: medRxiv preprint variant (TWIST Bioscience, USA, Part numbers are 102024, 103907, and 104533, respectively).

The PCR standard curves were obtained for every RT-qPCR analysis with 10-fold serial dilutions 556 of synthetic RNA controls and PCR efficiencies for RT-qPCR were higher than 85% (R 2 >0.99).

The SYBR signal was normalized to the ROX reference dye. The cycle of quantification (Cq) 558 values was determined automatically by QuantStudio TM Design & Analysis Software (v1.5.1).

Based on the melting curves, the primers were specifically bound to the target genome. The (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

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