Antigen test swabs are comparable to nasopharyngeal swabs for sequencing of SARS-CoV-2

Viral genomic surveillance has been integral in the global response to the SARS-CoV-2 pandemic. Surveillance efforts rely on the availability of representative clinical specimens from ongoing testing activities. However, testing practices have recently shifted due to the widespread availability and use of rapid antigen tests, which could lead to gaps in future monitoring efforts. As such, genomic surveillance strategies must adapt to include laboratory workflows that are robust to sample type. To that end, we compare the results of RT-qPCR and viral genome sequencing using samples from positive BinaxNOW COVID-19 Antigen Card swabs (N = 555) to those obtained from nasopharyngeal (NP) swabs used for nucleic acid amplification testing (N = 135). We show that swabs obtained from antigen cards are comparable in performance to samples from NP swabs, providing a viable alternative and allowing for the potential expansion of viral genomic surveillance to outpatient clinic as well as other settings where rapid antigen tests are often used.

www.nature.com/scientificreports/ As robust viral genomic surveillance hinges on acquiring positive cases through testing, changes to testing practice will impact surveillance efforts if laboratory workflows are not robust to sample type. The ability to use previously collected swabs from positive LFTs for genomic analysis would be of particular benefit. As testing practices in US and abroad continue to shift, a greater proportion of testing will be conducted via LFTs. The ability to sequence from LFTs will allow researchers to obtain representative viral samples spanning the geographic and epidemiological scope of the pandemic, as viral genomic surveillance efforts continue throughout the subsequent phases of the response. Further, more LFT testing is likely to occur outside of the healthcare setting. This change could significantly reduce available samples for viral genomic surveillance and skew the available samples to only those tests performed in a clinical setting, which would result in a bias toward more severe cases. Capturing samples from LFTs would expand the representation of genomic surveillance. To this end, we compared the ability to use swabs collected from LFTs for viral genome sequencing to nasopharyngeal (NP) swabs used for NAATs. Primarily, we sought to determine whether the extraction reagent or other component of sample processing used for BinaxNOW COVID-19 Ag Card testing disrupted the ability to perform SARS-CoV-2 genome sequencing.

Results
Of the 690 samples, 611 had detectible virus in the sample based on RT-qPCR Ct values after RNA extraction. There was a significant difference between NAAT samples and LFT that failed to amplify with a greater proportion of LFT samples successfully extracted (80.7% N = 109 NAAT samples vs 90.5% N = 502 LFT, p < 0.00001) (Fig. 1A). Among the samples that had detectable virus, we compared the RT-qPCR Ct values and found no significant difference between NAAT and LFT samples (median of 21.7 for NAAT and 21.9 for LFT, p = 0.27) (Fig. 1B).
Using a cut-off Ct value of ≤ 30, 519 samples (78 NAAT and 390 LFT) were moved forward to viral genome sequencing. Subsequently, we found that there was no significant difference between NAAT vs LFT samples in the proportion that failed sequencing (8.1% NAAT vs 10.3% LFT, p = 0.48) and only a moderate significant difference in median sequencing coverage (median of 183 for NAAT vs 199 LFT, p = 0.0018) ( Supplementary Fig. 1A). The lineage assignments for sequenced samples are shown in Fig. 2. Most samples (96.2%) were assigned to the SARS-CoV-2 Omicron variant (BA.1 and BA.1.1).
Comparing the time from sample collection to RNA extraction identified that the time to extraction was significantly shorter for LFT samples due to the logistics of our sample acquisition process (median of 20 days for NAAT vs 6 days for LFT, p < 0.00001) ( Supplementary Fig. 1B). To assess the impact on time to extraction on outcomes, we compared results for each sample type independently. We did not find any significant difference  1D). Despite our lack of association of time to extraction on sequencing outcomes, we still aimed to rule out the effect of difference in time to extraction between NAAT and LFT swabs; we thus performed a sub-analysis by down-sampling based on time to extraction. We limited the subsample to samples with a time to extraction from 14 to 21 days. This resulted in 41 NAAT swabs and 44 LFT swabs, of which 35 NAAT and 38 LFT had detectable Ct values with no significant difference in failure by swab type (p = 0.6). After subsetting the data, the median time to extraction for both NAAT and LFT swabs was 16 days with no significant difference (p = 0.352) (Supplementary Fig. 2A). Further, there was no significant difference in time to extraction for samples that did not amplify for NAAT or LFT swabs ( Supplementary Fig. 2B). For the subsample, RT-qPCR Ct value were again not significantly different between NAAT and LFT swabs (median of NAAT 19.9 vs 20.9 for LFT, p = 0.404) (Supplementary Fig. 2C). Using a cutoff Ct value of ≤ 30, 35 (85%) NAAT and 38 (86%) LFT samples moved forward to sequencing. There was also no significant difference in the proportion of samples from the subset that failed sequencing or difference in sequencing coverage among those successfully sequenced ( Supplementary Fig. 2D). The statistical significance of the sub-analysis was unchanged when bootstrapping the sub-groups to generate groups of 100 for each comparison leading us to believe that the smaller sample sizes were not obfuscating significant changes.
To further examine the effect of time to extraction on coverage and RT-qPCR values, we performed a Spearman's rank-order correlation analysis. We did not identify any significant correlation between time to extraction and RT-qPCR CT values in the total data (R = − 0.02, p = 0.65) or the subset data (R = 0.09, p = 0.52). There was also no significant correlation between time to extraction and coverage in the total dataset (R = − 0.02, p = 0.7) or the subset data (R = − 0.22, p = 0.1).

Discussion
By sequencing samples derived from NAAT NP swabs and samples derived from positive BinaxNOW COVID-19 Ag Card swabs and comparing the proportions of successful sequencing, genome coverage, and RT-qPCR Ct values, we demonstrate that extraction reagents and sample processing do not significantly impact the ability to recover SARS-CoV-2 viral genomes. This suggests that positive LFT swabs could serve as a viable alternative for genomic surveillance. When comparing the sequencing results from LFT cards to NAAT swabs, there was no significant difference between the proportion of failed samples, genome coverage, or RT-qPCR Ct values. We did observe that NAAT samples had a significant, but marginal, longer time to extraction than the LFT samples. However, we did not observe a significant correlation between time to extraction and genome coverage or RT-qPCR Ct www.nature.com/scientificreports/ values, which implies that difference in time to extraction does not have an overt impact. These findings indicate that sequencing of positive LFT swabs could compliment traditional sequencing of NAAT swabs while yielding very similar sequencing quality. The increased ability to extract and amplify viral RNA from LFTs is consistent with their test performance, as previous studies have shown that they are more likely to report positive results with higher viral loads corresponding to RT-qPCR Ct values < 30. This may partially explain the high success in viral genome sequencing from positive LFT swabs. The ability to use swabs from RDTs for SARS-CoV-2 genome sequencing is important for future surveillance efforts. As RDTs such as the BinaxNOW COVID-19 Ag Cards become more accessible and ubiquitous, NP swabs will become increasingly limited to a clinical setting where NAATs are routinely employed. This change could potentially bias the genomic surveillance data towards more severe cases that require clinical intervention. Capturing samples from RDTs performed in the home or clinic setting would enable us to generate surveillance data that is more representative. In addition, by using clinical excess from previously collected swabs, we also eliminate the need for collection of a second swab, which can simplify IRB protocols for clinical studies and increase study participation. The future of over-the-counter RDTs will depend on the course of the pandemic. While the COVID-19 public health emergency declaration recently expired in May 2023, the EUA allowing their use remains in place. Henceforth, manufacturers will need apply for formal FDA approval for continued use. However, it seems that the widespread use of RDTs during the pandemic could signal a paradigm shift for the availability of at-home and clinic-based infectious disease testing, and we feel that our findings may inform surveillance strategies for epidemiologically similar pathogens for which RDTs are currently employed. Undeniably, the availability of over-the-counter RDTs has provided agency to the public, allowing individuals to use testing to manage their personal risk and aid in decision making. Home testing could conceivably be expanded to other respiratory pathogens such as influenza virus or respiratory syncytial virus (RSV), which are commonly diagnosed in the outpatient setting using rapid antigen tests. With this possibility in mind, we must rethink the future of viral genomic surveillance so that sampling of cases in the community remains robust.
One possible solution for obtaining samples from at-home testing would be to partner with the government's free at-home COVID-19 test program to provide a subsample of recipients with prepaid postage and mailing containers with viral transport media (VTM) that could be used to send positive samples to sequencing centers. Remuneration could also be considered to incentivize participation. While at-home storage and transport conditions may vary considerably, direct-to-consumer genetic testing through companies like 23andMe and AncestryDNA provide a model for collection and transport of samples with the intended application of sequencing. Further, several studies have extensively evaluated the stability of SARS-CoV-2 RNA in a number of storage and transport conditions with and without transport media and cold storage. In the study by Alfaro-Nunez et al., they found that viral RNA remained stable on dry non-buffered swabs for up to 26 days when left at room temperature 23 . Similar studies found that qRT-PCR Ct values remained stable among samples stored in phosphate-buffered saline or VTM at room temperature for up to 28 days regardless of viral loads [24][25][26][27] . While these studies have largely focused on qRT-PCR performance, the robustness of SARS-CoV-2 genome sequencing has been demonstrated through the ability to successfully reconstruct viral genomes from seemingly complex or low-quality samples including wastewater and environmental surfaces 28,29 . With the current level of at-home testing, even a modest sequencing failure rate of samples collected through a mail-in program would significantly improve community-based genomic surveillance. In the outpatient healthcare setting, primary care clinics performing RDTs are equipped to collect and store samples as described in this study and would provide a viable source for community-based sampling much like CDC's U.S. Outpatient Influenza-like Illness Surveillance Network (ILINet).
Our study is not without limitation. Due to the observational nature of our study, we are not able to directly compare sequencing success of different sample types from the same participant. Furthermore, we did not consider vaccine history or disease severity which may vary between settings (i.e., NAAT: hospital, RDT: clinic); however, the study population from which these samples were obtained was generally healthy and likely experienced mild disease. As a note, samples that fail sequencing may be due to technical errors in library preparation; however, we expect this effect to be independent of swab type. Further, we report a significant difference in the time to RNA extraction between the two groups. To mitigate this issue, we conducted our analysis using a sub-set of the total data in which the time to extraction was between 14 and 21 days. This subset resulted in a similar number of samples between the two groups with similar time to extraction. Finally, in our study, positive BinaxNOW COVID-19 Ag Card swabs were removed from the card, placed in transport media, and stored in a clinic refrigerator until transport to the laboratory. While this protocol may function in clinic and outpatient settings, it may not be well suited for at-home testing, leaving the question of real-world viability unanswered. Indeed, we did not systematically evaluate the effect of variation in transport and storage conditions on viral genome sequencings; however, the previous studies described above have demonstrated that viral RNA stability is robust to storage duration and condition 23,27,30 . While subsequent studies using parallel sampling from the same individual or a variety of currently marketed RDTs could resolve these limitations, we believe our current study demonstrates the ability to successfully sequence SARS-CoV-2 from swabs used for LFTs. Overall, we show that sequencing LFT swabs is not only possible, but also results in comparable RT-qPCR Ct values, genome coverage, and sequencing failure rates. These findings provide the foundation for community-based viral genomic surveillance, which will allow public health to maintain representative sampling cases as we continue pandemic mitigation efforts.

LFT vs NAAT performance comparison.
To evaluate the suitability of samples obtained from positive rapid antigen tests for use in viral genome sequencing, we compared viral RNA extraction, RT-qPCR, and sequencing success to samples collected from the clinical excess of positive NAATs. We first assessed for statistically significant differences between the date of collection and date of viral RNA extraction between the two samples. We then compared the frequency of samples that failed to amplify during RT-qPCR and the resulting cycle threshold (Ct) values among those that amplified. The Ct value is inversely proportional to the amount of viral target in the sample-lower Ct values are associated with a greater quantity of virus and higher values are associated with a lower quantity. Last, we assessed sequencing success (failed samples, viral genome coverage, and genomes passing sequencing QC) between the two groups. Chi squared statistic was used to compare frequencies between categories (e.g., pass/fail for NAAT vs LFT) and the Mann-Whitney U test 31 was used to determine if the values between two groups were significantly different sizes. Additionally, for the sub-analysis assessing the potential association of time to extraction on sequencing outcomes, we tested the robustness of the Mann-Whitney U test for our sample size by bootstrapping the sub-groups (41 and 44, respectively) to generate two groups of 100 for each comparison and re-running the statistical test and we found that the significance, as defined by a p-value < 0.05, was not impacted. All statistical analysis was performed using python 3.10.2 32 . All visualizations were produced using Rstudio running v 3.6.0 33 .
Ethics statement. This study was reviewed by the University of Central Florida Institutional Review Board and received a non-human subject determination.

Data availability
All data produced in the present study are available upon reasonable request to the authors. The datasets generated and/or analyzed for this current study are available in GISAID and the accession ID's are listed in Supplemental Table 1 along with additional metadata.