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. 2023 Sep 1;18(9):e0291120. doi: 10.1371/journal.pone.0291120

Quantitative SARS-CoV-2 subgenomic RNA as a surrogate marker for viral infectivity: Comparison between culture isolation and direct sgRNA quantification

Rossana Scutari 1,2,#, Silvia Renica 1,#, Valeria Cento 3,4, Alice Nava 5, Josè Camilla Sammartino 6, Alessandro Ferrari 6, Arianna Pani 5, Marco Merli 7, Diana Fanti 5, Chiara Vismara 5, Francesco Scaglione 1,5, Massimo Puoti 7, Alessandra Bandera 8,9, Andrea Gori 8,9, Antonio Piralla 6, Fausto Baldanti 6,10, Carlo Federico Perno 2, Claudia Alteri 1,2,*
Editor: Ahmed S Abdel-Moneim11
PMCID: PMC10473502  PMID: 37656746

Abstract

Detection of subgenomic (sg) SARS-CoV-2 RNAs are frequently used as a correlate of viral infectiousness, but few data about correlation between sg load and viable virus are available. Here, we defined concordance between culture isolation and E and N sgRNA quantification by ddPCR assays in 51 nasopharyngeal swabs collected from SARS-CoV-2 positive hospitalized patients. Among the 51 samples, 14 were SARS-CoV-2 culture-positive and 37 were negative. According to culture results, the sensitivity and specificity of E and N sgRNA assays were 100% and 100%, and 84% and 86%, respectively. ROC analysis showed that the best E and N cut-offs to predict positive culture isolation were 32 and 161 copies/mL respectively, with an AUC (95% CI) of 0.96 (0.91–1.00) and 0.96 (0.92–1.00), and a diagnostic accuracy of 88% and 92%, respectively. Even if no significant correlations were observed between sgRNA amount and clinical presentation, a higher number of moderate/severe cases and lower number of days from symptoms onset characterized patients with sgRNA equal to or higher than sgRNA cut-offs. Overall, this study suggests that SARS-CoV-2 sgRNA quantification could be helpful to estimate the replicative activity of SARS-CoV-2 and can represent a valid surrogate marker to efficiently recognize patients with active infection. The inclusion of this assay in available SARS-CoV-2 diagnostics procedure might help in optimizing fragile patients monitoring and management.

Introduction

In early 2020, SARS-CoV-2 appeared and quickly spread globally [1]. In order to promptly identify positive cases, its detection is rapidly committed to qualitative real-time reverse transcription PCRs (q-rtPCR), considered today the gold standard for SARS-CoV-2 diagnosis [2]. However, these methods are not designed to provide a quantitative SARS-CoV-2 RNA and cannot distinguish between replicating virus and residual genomic material [3, 4]. To date, the best indicator of replicating virus is SARS-CoV-2 culture isolation. However, this technique requires a biosafety level 3, highly specialized personnel, high costs, it is time-consuming and needs of at least 7 days to provide a certain negative result.

Due to limitations of q-rt-PCR and virus isolation methods, the first unable to assess active viral replication and the last characterized by long processing times, there is a strong need for a simple and rapid test that can provide accurate and rapid results on SARS-CoV-2 residual replication capacity, especially from the perspective of long-term positivity to SARS-CoV-2 and clinical management of SARS-CoV-2 positive patients.

Previous studies suggested that, in clinically resolved patients, the presence of persistently detectable SARS-CoV-2 by q-rt-PCR over two or more weeks might be related to the elimination of residual viral genomic material rather than to the actual replicative potential of the virus itself [5, 6].

Of note, SARS-CoV-2 has a complex replication cycle characterised by a discontinuous transcription process, resulting in subgenomic RNAs (sgRNAs) production [7]. These sgRNAs are susceptible to enzymatic degradation and are hardly present in virions [8]. Since the process of sgRNA formation only occurs during genomic replication and transcription, several studies suggested that sgRNA can be used as a correlate of viral infectiousness [9–16].

However, few data are available so far regarding the role of quantitative determination of these sgRNA and potential correlation with the SARS-CoV-2 infectivity [17].

Material and methods

Study population

The study was conducted between October 2020 and November 2021 at ASST Grande Ospedale Metropolitano Niguarda, Milano and Fondazione IRCCS Policlinico San Matteo, Pavia. During this period, a total of 110 nasopharyngeal swabs (UTMTM, Copan Italia, Brescia, Italy) (1 sample per patient) were tested for SARS-CoV-2 infectivity by culture isolation for diagnostic purposes. Swabs collected to a maximum of 14 days after symptoms onset (usually defined as the temporal window for the persistence of viral shedding in upper respiratory tract [18, 19] (n = 51, S1 Fig) were retrospectively selected to compare the culture results with SARS-CoV-2 genomic and sgRNA quantifications.

For each patient, demographic and clinical information such as age, gender, clinical manifestations and symptoms were retrieved and stored in an anonymous database ad hoc built for the study.

The severity of COVID-19 was classified, in according with WHO scale [20], into asymptomatic, mild and moderate/severe.

Ethical committee

The study protocol was approved by local Research Ethics Committee of the Niguarda and San Matteo hospitals (prot. 92–15032020 and P_20200029440). This study was conducted in accordance with the principles of the 1964 Declaration of Helsinki. Informed consent was waived in accordance with the regulations on observational retrospective studies.

SARS-CoV-2 load and subgenomic RNA quantification by ddPCR

SARS-CoV-2 genomic RNA and sgRNA were quantified by means of the QX200™ Droplet Digital™ PCR System (ddPCR, Bio-Rad Laboratories, Inc.). In detail, one home-made and two previously tested assays [21] targeting 3 different regions of RNA-dependent RNA-polymerase (RdRp) of SARS-CoV-2 were used to quantify SARS-CoV-2 genomic RNA. The assay targeting the RNAseP housekeeping gene was used as reference [22]. The sgRNAs were quantified using assays adapted for the ddPCR system and targeting the envelope and nucleocapsid transcripts [10, 23]. Primer and Probe used to detect and quantify genomic and subgenomic RNA are reported in S1 Table. SARS-CoV-2 viral load and sgRNA were expressed in number copies/mL of swab. Full protocol used to detect and quantify SARS-CoV-2 sgRNAs and viral load was reported in S1 File.

Culture isolation

For virus isolation, all samples were inoculated into a Vero E6 (VERO C1008 -Vero 76, clone E6, Vero E6; ATCC1 CRL-1586TM) confluent 24-well microplate between 8 and 24 h after positivity results. After 1 h incubation at 33°C in 5% CO2 in air, the inoculum was discarded and 1 mL of medium (Eagle’s minimum essential medium supplemented with 1% penicillin, streptomycin, and glutamine and trypsin at 5 mg/mL) was added to each well. Cells were incubated at 33°C in 5% CO2 in air. After incubation for 7 days, 200 μl of supernatant from a well showing a cytopathic effect was tested for the presence of SARS-CoV-2 by molecular assay (gene E real-time RT-PCR) [24].

Statistics and reproducibility

Descriptive statistics are expressed as median values and interquartile range (IQR) for continuous data and number (percentage) for categorical data. To assess significant differences Fisher exact and Mann–Whitney or Kruskal-Wallis tests were used for categorical and continuous variables, respectively. All quantifications were performed in duplicate.

To define the performance of in-house ddPCR assays, sensitivity, specificity, positive and negative predictive values (PPV and NPV) were assessed against the culture isolation, considered as the gold standard for SARS-CoV-2 active virus replication. A receiver operator characteristic (ROC) curve was performed to determine the optimal cut-off point to identify true-positive. Potential association between SARS-CoV-2 sgRNA and genomic RNA values and clinical presentation were also evaluated.

Statistical analyses were performed with SPSS software package for Windows (version 23.0, SPSS Inc., Chicago, IL) and Rgui (v.4.2.3). Figures were generated by GraphPad Prism 8. A p-value <0.05 was considered statistically significant.

Results

Patient’s characteristics

The demographic and clinical characteristics of 51 patients included in the study are reported in Table 1. Twenty-five patients were male (59.0%) with a median age of 59 (Interquartile range [IQR]: 41–69) years.

Table 1. Demographic and clinical characteristics of the study population.

Overall Culture isolation
SARS-CoV-2 Positive culture isolation SARS-CoV-2 Negative culture isolation
Patients, N 51 14 37
Males 25 (49.0) 9 (64.3) 16 (43.2)
Age (years) 59 (41–69) 60 (44–67) 58 (38–71)
SARS-CoV-2 PCR positivitya:
one gene target 24 (64.9) 12 (92.3) 12 (50.0)
>one gene target 13 (35.1) 1 (7.7) 12 (50.0)
Days from symptoms onset 8 (1–11) 2 (1–7) 10 (3–12)
COVID-19 manifestation at first positive nasopharyngeal swabb 
Asymptomatic 7 (41.2) 1 (25.0) 6 (46.2)
Mild 5 (29.4) 1 (25.0) 4 (30.7)
Moderate/severe 5 (29.4) 2 (50.0) 3 (23.1)
Specific symptoms at first nasopharyngeal swab b
Fever 4 (23.5) 0 (0.0) 4 (30.8)
Cough 1 (5.9) 1 (25.0) 0 (0.0)
Dyspnea 2 (11.8) 0 (0.0) 2 (15.4)
Evidence of interstitial pneumonia 5 (29.4) 2 (50.0) 3 (23.1)
Immunocompromised patients b 6 (35.3) 3 (75.0) 3 (23.1)
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Data are expressed as median (interquartile range, IQR), or N (%). COVID-19, Coronavirus Disease 2019

aAvailable for 37 patients

bAvailable for 17 patients.

At first SARS-CoV-2 positivity, clinical information related to COVID-19 was retrieved for 17 individuals. Among them, 7 (41.2%) were asymptomatic, 5 (29.4%) with moderate/severe infection and 5 (29.4%) with mild infection. Four patients reported fever (23.5%) and 5 (29.4%) had evidence of interstitial pneumonia. Immunocompromised status was observed in 6 (35.3%) patients. Median days from symptoms onset were 8 (IQR: 1–11).

Regarding SARS-CoV-2 isolation by cell culture, 14 (27.5%) nasopharyngeal swabs resulted to be SARS-CoV-2 positive at culture isolation, while the remaining 37 (72.5%) resulted to be SARS-CoV-2 negative.

SARS-CoV-2 subgenomic results against culture

E and N sgRNAs were detected in 20/51 (39.2%) and 19/51 (37.3%) nasopharyngeal swabs, respectively. The median (IQR) SgRNA was 1,295 (238–906,850) and 1,680 (325–254,240) copies/mL, respectively (S2 Table).

Stratifying the population according to culture result, E SgRNA was detected in all 14 culture positive swabs and only in 6/37 culture negative swabs (p-value<0.001) with a median (IQR) load of 140,700 (350–1,071,000) and 406 (210–770) copies/mL, respectively (Fig 1 Panel A and S2 Table). N sgRNA was detected in 14/14 culture positive swabs and only in 5/37 culture negative swabs (p-value<0.001), with a median (IQR) load of 34,069 (325–306,600) and 770 (630–980) copies/mL, respectively (Fig 1 Panel B and S2 Table).

Fig 1. SARS-CoV-2 subgenomic and genomic load against culture results.

Fig 1

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The dot plots represent the quantification of (A) E subgenomic, (B) N subgenomic, and (C) SARS-CoV-2 RNA load in positive and negative cultures. The dotted line represents the best cut-off, calculated by ROC analysis, to predict a positive culture isolation. The bars indicate the median and interquartile range values (IQR).

Direct quantification of genomic SARS-CoV-2 load revealed the presence of SARS-CoV-2 RNA in 37/51 samples, with a median (IQR) load of 5,899 (705–105,817) copies/mL. In line with the sgRNA results, SARS-CoV-2 load was detected in all 14 culture positive swabs and in 23/51 culture negative swabs (p-value = 0.005), with a higher viral load in culture positive respect to culture negative swabs (median, IQR: 3,174,612 [46,650–10,000,000] vs 1,913 [411–8,680] copies/mL, p-value<0.001) (Fig 1 Panel C and S2 Table).

According to culture isolation results, the sensitivity and specificity observed for the sgRNA E assay were 100% (95% CI: 77%-100%) and 84% (95%CI: 68%-94%), respectively with a PPV value of 70% (95%CI: 53%-83%) and NPV value of 100% (95%CI: 89%-100%). Similarly, the SgRNA N assay showed a sensitivity of 100% (95%CI: 77%-100%), a specificity of 86% (95%CI: 71%-95%), and PPV and NPV values of 74% (95%CI: 55%-86%) and 100% (95%CI: 89%-100%), respectively. The diagnostic accuracy was 88% (95%CI: 76%-96%) for sgRNA E and 90% (95%CI: 79%-97%) for sgRNA N.

As expected and due to the renowned ddPCR high sensitivity, genomic SARS-CoV-2 assay showed a sensitivity and specificity against culture of 100% (95%CI: 77%-100%) and 38% (95%CI: 22%-55%), respectively, with PPV value of 38% (95%CI: 32%-44%) and NPV value of 100% (95%CI: 77%-100%).

Concomitant RNAseP RNA quantification confirmed the high quality of all the 51 nasopharyngeal swabs (S2 Fig).

SARS-CoV-2 culture isolation vs SARS-CoV-2 SgRNA

By comparing culture isolation results and SgRNA detection, three categories were highlighted: negative concordant (negative culture isolation and negative sgRNA detection), positive concordant (positive culture isolation and positive sgRNA detection) and discordant (negative culture isolation and positive sgRNA detection). The characteristics of the population stratified against these categories is shown in S3 Table.

Out of the 37 negative culture swabs, 31 were confirmed negative to sgRNA detection (Concordant -/-), while 6 were tested positive (Discordant -/+). The 14 positive culture swabs were confirmed positive to sgRNA detection (Concordant +/+) (S3 Table). Of note, a clear trend of higher sgRNA values was found for +/+ samples respect to -/+ samples (sgRNA E, median [IQR] copies/mL: 140,700 [350–1,071,000] vs and 406 [210–770], p-value = 0.083; SgRNA N, median [IQR] copies/mL: 34,069 [325–306,600] vs 770 [630–980] copies/mL, p-value = 0.165) (Fig 2, Panel A and B).

Fig 2. SARS-CoV-2 subgenomic and genomic load against concordance between SARS-CoV-2 culture isolation and subgenomic RNA detection.

Fig 2

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The dot plots represent the quantification of (A) E subgenomic, (B) N subgenomic, (C) SARS-CoV-2 RNA load. Negative concordant is defined as negative culture isolation and negative sgRNA detection. Positive concordant is defined as positive culture isolation and positive sgRNA detection. Discordant is defined as negative culture isolation and positive sgRNA detection. SgRNA was considered positive (+) when at least one subgenomic RNA (N or E) was detectable. The dotted line represents the best cut-off, calculated by ROC curve analysis, to predict a positive culture isolation. *One-sided p-values comparing patients with concordant +/+ results and patients with discordant -/+ results were calculated by the Mann–Whitney test.

Most of the 31 concordant -/- samples had also a quite lower SARS-CoV-2 viral load compared to the discordant -/+ and concordant (+/+) samples (median [IQR] copies/mL: 161 [0–910] copies/mL vs. 3,174,612 [46,650–10,000,000] vs. 7,572 [2,543–13,650], p-value<0.001) (Fig 2, Panel C).

SARS-CoV-2 sgRNA load cut-off definition for viable virus

In order to define the best cut-off of sgRNA load to predict viable virus a ROC analysis was performed. Interestingly, ROC curve analysis identified 32 copies/mL for sgRNA E and 161 copies/mL for sgRNA N as the best cut-off to predict a positive culture isolation, with an AUC (95% CI) of 0.96 (0.91–1.00) for E sgRNA and 0.96 (0.92–1.00) for N sgRNA.

Regarding SARS-CoV-2 genomic load, the best cut-off to predict viable virus was 39,752 copies/mL, with an AUC (95% CI) of 0.93 (0.86–1.00).

By using the cut-off obtained with the ROC curve, the sensitivity and specificity against culture observed for the SgRNA E assay were 100% (95%CI: 77%-100%) and 84% (95%CI: 68%-94%), respectively with a PPV value of 70% (95%CI: 53%-83%) and NPV value of 100% (95%CI: 89%-100%). Similarly, the SgRNA N assay showed a sensitivity of 100% (95%CI: 77%-100%), a specificity of 90% (95%CI: 75%-97%), and PPV and NPV values of 78% (58%-90%) and 100% (95%CI: 89%-100%), respectively. The diagnostic accuracy shown by the assays applying the ROC cut-off was 88% (95%CI: 76%-96%) for sgRNA E and 92% (95%CI: 81%-98%) for sgRNA N.

Using the cut-off of 39,752 copies/mL, the genomic SARS-CoV-2 assay showed a sensitivity and specificity of 79% (95%CI: 49%-95%) and 97% (95%CI: 86%-100%), respectively, with PPV value of 92% (95%CI: 62%-100%) and NPV value of 92% (95%CI: 79%-98%) against culture.

Correlation with clinical presentation

By correlating SARS-CoV-2 sgRNA and genomic RNA values with available clinical information, 2 out 4 (50.0%) patients with E and N sgRNA values equal to or higher than 32 and 161 copies/mL, respectively, were characterized by moderate/severe COVID-19 manifestations respect to the 3/13 (23.1%) patients with E and N sgRNA values below the cut-offs. Median (IQR) days from the onset of symptoms to the nasopharyngeal swab were quite lower in patients with E and N sgRNA values equal to or higher than the cut-offs respect to patients with E and N sgRNA values below the cut-offs (days: 5 [1–11] vs. 10 [4–15]). Superimposable results were found for patients with SARS-CoV-2 RNA values equal to or higher than 39,752 copies/mL respect to patients with SARS-CoV-2 RNA values below the cut-off.

When clinical parameters were compared with SARS-CoV-2 culture isolation vs subgenomic RNA concordance, similar results were obtained (S3 Table).

Discussion

This study demonstrates that SARS-CoV-2 sgRNA quantification might help to distinguish active viral replication from residual viral genetic material, thus suggesting that subgenomic SARS-CoV-2 detection and quantification could be used as a correlate of infectious viral shedding [15, 16]. In particular, we found that E and N sgRNA were always characterized by high load in positive SARS-CoV-2 culture samples, while were rarely detectable (with low quantification values) in culture-negative samples.

A number of studies recognized the role of sgRNA as an indicator of active virus replication and as a promising tool for patients’ management [6, 10, 15, 16, 25], while others suggested that the detection of sgRNAs cannot represent a more useful marker in determining viability than genomic RNA, due to the similar decay of these two parameters [26, 27]. In some studies, specific sgRNAs can be detected at a very prolonged time from the onset of infection, even in non-immunocompromised individuals [28, 29], probably because tightly associated with membrane structures and thus protected from cellular RNases [30].

Our study aims to provide evidence that the quantification of sgRNAs, rather than their detection, can predict viable virus. In our study 32 copies/mL of sgRNA E and 161 copies/mL of sgRNA N were the best cut-off to predict culture isolation results, thus providing further confidence in applying direct sgRNA quantification assays to define risk of viable virus.

Regarding SARS-CoV-2 genomic load, the cut-off equal to 39,752 copies/mL showed a good specificity (97%) but a lower sensitivity than that observed for sgRNAs (79% vs. 100% of E and N sgRNA), thus confirming that the quantification of genomic RNA alone cannot adequately discriminate residual material from active replication.

In an exploratory analysis correlating sgRNA cut-offs with time from symptoms onset and disease manifestations, we observed that samples with sgRNA values equal or higher than the cut-offs estimated by ROC analyses had a sample date closer to symptoms onset and were characterized by more moderate/severe infections than samples with sgRNA values lower that the estimated cut-offs. Thus, quantification of sgRNA could be a useful surrogate for predicting not only active viral replication but also the duration of infectious viral shedding, as suggested by Perera et al. [6]. Worth of mention is that in fragile conditions like immunosuppression, duration of infectious viral shedding could be not only limited to the first days after the infection [31–33]. In line with this, in the subgroup of 59 nasopharyngeal swabs collected to more than 14 days from the symptoms onset and thus excluded by this analysis, four were positive for SARS-CoV-2 culture isolation and sgRNA quantification (median [IQR]: 11,320 [205–131,925] for N and 4,760 [1,917–15,873] for E). Three of these swabs were collected at 20-, 51- and 85-days post symptoms onset and belonged to immunocompromised individuals. Overall, these initial findings could suggest that application of these rapid sgRNA quantifications in clinical practice could help also in monitoring critically ill patients at high risk of severe manifestations.

Our study has some limitations. First, the sample size was small especially if considering samples with SARS-CoV-2 positive culture isolation. This limitation makes the results of the study exploratory. Therefore, more data on a larger number of clinical samples, and possibly from multicentre studies, are needed to further confirm the assays sensitivity, specificity, and reliability. Second, our results cannot be generalizable to the full pathway of SARS-CoV-2 sgRNAs because sgRNA of other genes like S or orf7a were not tested [27]. Another important limitation is that our results did not include samples by Omicron wave, that could be characterized by different sgRNA kinetics. This limitation avoided the possibility to confirm the performance of the ddPCR assays here described in the Omicron Clade, even if the designed assays target highly conserved SARS-CoV-2 regions, not affected by Omicron variability.

Conclusion

Overall, we have provided exploratory results demonstrating that sgRNA quantification with a molecular tool characterized by high sensitivity and accuracy could be helpful to estimate the replicative activity of SARS-CoV-2, and can represent a correlate of active infection. The inclusion of this assay in available SARS-CoV-2 diagnostics procedure might help in optimizing patients monitoring and management, at both community and hospital levels. Indeed, application of sgRNA quantification might help in the management of most fragile settings, like immunocompromised patients, known to be at risk for prolonged infection, and persistent SARS-CoV-2 RNA positivity.

Supporting information

S1 Fig. Selection criteria for the 51 nasopharyngeal swabs included in the study.

(PDF)

Click here for additional data file. (176.2KB, pdf)
S2 Fig. Quantasoft panel for RNAse P housekeeping gene of the 51 nasopharyngeal swabs (one well per patient).

In each panel, the first and second wells represent the negative and positive reaction control, respectively.

(PDF)

Click here for additional data file. (591.8KB, pdf)
S1 Table. Primers and probes used to quantify SARS-CoV-2 load and subgenomic RNA.

(DOCX)

Click here for additional data file. (16.6KB, docx)
S2 Table. SARS-CoV-2 genomic and subgenomic RNA load against culture isolation.

(DOCX)

Click here for additional data file. (16.8KB, docx)
S3 Table. Demographic and clinical characteristics of patients against SARS-CoV-2 culture isolation vs subgenomic RNA concordance.

(DOCX)

Click here for additional data file. (16.9KB, docx)
S1 File. Supplementary information reporting the full protocol used for the detection and quantification of SARS-CoV-2 subgenomic RNAs and viral load.

(DOCX)

Click here for additional data file. (27.5KB, docx)
S2 File. Supplementary information reporting data related to Figs 1, 2 and S2 Fig.

(XLSX)

Click here for additional data file. (20.1KB, xlsx)

Acknowledgments

We thank all the staff of the Microbiology and Virology Laboratory of ASST Grande Ospedale Metropolitano Niguarda and of the Microbiology and Virology Department, Fondazione IRCCS Policlinico San Matteo for outstanding technical support in processing swab samples, performing laboratory analyses and data management.

Data Availability

All relevant data are within the paper and its Supporting Information files.

Funding Statement

this work is supported by STOP-COVID project, founded by Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico. The funder had no role in study design, data collection, analysis, decision to publish, or preparation of the manuscript. The recipient of the fund is the corresponding author, Claudia Alteri.

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Decision Letter 0

Ahmed S Abdel-Moneim

6 Mar 2023

PONE-D-22-24987Quantitative SARS-CoV-2 subgenomic RNA as a surrogate marker for viral infectivity: comparison between culture isolation and direct sgRNA quantificationPLOS ONE

Dear Dr. Alteri,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

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Academic Editor

PLOS ONE

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Reviewers' comments:

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Comments to the Author

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Reviewer #1: Partly

Reviewer #2: Partly

Reviewer #3: Yes

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: No

Reviewer #2: Yes

Reviewer #3: Yes

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

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Reviewer #1: Yes

Reviewer #2: No

Reviewer #3: Yes

**********

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Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The duration of time since symptom onset is extraordinarily long in this study. Usually, it is not possible to culture replicable virus after 10 days since an initial positive test; the median time here is 19 days, and the longest duration was 51 days. The median duration of time since symptom onset was 37 days in the subgroup of patients with clinical information. It is extremely unusual, if not unheard of, to isolate replicable virus this long after symptom onset, even if some of the patients were immunocompromised (not a majority). This makes me wonder if something is wrong with the data or the description of the data, or if I am simply not understanding something.

Other specific comments follow:

--The sensitivity, specificity, NPV, and PPV estimates require confidence intervals-- particularly since they are the primary outcome measures of this study.

--The authors should address more fully the criticism that subgenomic RNAs persist in samples for a long period of time and are thus not suitable as a proxy for infectiousness. The durations since symptom onset presented in this study, however, appear to be much longer than those previously reported (see above).

--The ROC results should be presented before the main results, since the cutoffs obtained in the ROC results are used for all subsequent comparisons.

--It is an acknowledged but real limitation that this study was conducted prior to the emergence of the omicron variant, as subgenomic RNA .

--As noted by the authors, the sample size is quite small, with only 18 culture-positive patients. This renders the results of this study exploratory at best.

--I'm afraid I cannot recommend publication of this article in PLOS ONE owing to the questions I have about the long time between symptom onset and culture positivity, the lack of appropriate measures of uncertainty for sensitivity and specificity calculations, and the the small sample size.

Reviewer #2: The study presents the results of original research. Authors use an original methodical approach for measuring of SARS-CoV-2 sgRNA levels.

But there are some issues with the study design. The main problem is sample selection criteria. Authors mention that they collect nasopharyngeal swabs from SARS-CoV-2 positive patients on 37 day after symptom onset (median, IQR 18-67). Several studies (for example doi: 10.1186/s12916-020-01810-8 and doi: 10.1016/S2213-2600(22)00226-0) have shown that viral shedding in upper respiratory tract usually stops after 14 days post-symptom onset. So, obviously many of swabs (53/110) were PCR-negative and others (39/110) had low viral loads undetectable by virus isolation.

Authors don’t provide data of RNAse-P assay in genomic SARS-CoV-2 RNA-targeted RT-PCR which should act as the Internal Control and this absence doesn’t allow to judge about the quality of sample collection and RNA purification steps.

Also some typos were found: “In detail, genomic RNA assay targeted three different RNA-dependent RNA-polymerase (RdRp) of SARS-CoV-2 and the RNAseP housekeeping gene” (lines 103-105). Do the authors use three PCR assays targeted viral RdRp or do they use one which consists of three oligos targeted RdRp?

The reviewer would recommend to include in the study samples collected from patients within 0-14 days post-symptom onset with different viral loads and exclude samples which are negative on SARS-CoV-2 genome RT-PCR.

Reviewer #3: The manuscript presents convincing data on the possibility of application of sgRNA quantification to determine active viral replication of SARS-CoV-2. The authors present results on the correlation between viral load of genomic and subgenomic RNAs as well as with the culture isolation test and the clinical infection pattern of the patients.

Despite the conclusive data obtained, the authors are correct in pointing out the limitations of the presented work related to the small sample of patients and the inclusion of other genes sgRNA (particularly interesting is the S-protein gene). The authors also point out the possibility of applying this test to people with long-term positivity to SARS-CoV-2, although in this study nasopharyngeal swabs were taken from people with symptoms of the disease (acute infection).

Despite its simplicity, the present work makes a good impression.

A few questions and comments to help improve the manuscript.

1. Was the selected patient tested for the antigen (nucleocapsid protein) or the standard PCR test used in routine clinical practice? This data can be added to the manuscript (e.g., Table 1).

2 By analyzing the data in Table 1, the authors conclude that there is no difference between patients with SARS-CoV-2 positive and negative culture isolation. However, the last column (P-value) with such a random small sample of patients, in my opinion, is unnecessary.

3. The authors do not provide primers for genomic RNA and sgRNA PCR in the "Material and Methods" section. I recommend inserting them as a table in this section, because otherwise a number of questions arise. For example, is the cgRNA sequence part of the complete genomic RNA or not?

4. Since this work is to study the correlation between several parameters, I recommend presenting a graphical design of the study to make it easier to understand the progress of the work.

5. In the "Discussion" section, the results of other researchers on SARS-CoV-2 subgenomic RNA detection and their possible role as a surrogate-to marker of infectious viral shedding could be described in more detail.

**********

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PLoS One. 2023 Sep 1;18(9):e0291120. doi: 10.1371/journal.pone.0291120.r002

Author response to Decision Letter 0

25 Apr 2023

PONE-D-22-24987

Title: Quantitative SARS-CoV-2 subgenomic RNA as a surrogate marker for viral infectivity: comparison between culture isolation and direct sgRNA quantification

Journal: PLOS ONE

We would like to thank the reviewers for their time and for the constructive criticisms they arose.

The revisions of the manuscript in accordance with their comments are summarized in our responses below.

Response to Reviewers’ Comments

Reviewer #1:

1. The duration of time since symptom onset is extraordinarily long in this study. Usually, it is not possible to culture replicable virus after 10 days since an initial positive test; the median time here is 19 days, and the longest duration was 51 days. The median duration of time since symptom onset was 37 days in the subgroup of patients with clinical information. It is extremely unusual, if not unheard of, to isolate replicable virus this long after symptom onset, even if some of the patients were immunocompromised (not a majority). This makes me wonder if something is wrong with the data or the description of the data, or if I am simply not understanding something.

Answer: According with this comment and comments 1 and 4 of the in Reviewer#2, the revised version of the manuscript has been focused on samples belonging to patients with a time between symptom onset and sampling date equal or inferior to 14 days. Therefore, the new analyses included 51 patients (Supplementary Figure 1 and Page 3-4, Lines 85-90 of the main manuscript), characterized by a median time between symptom onset and swab sampling of 8 (1-11) days.

2. Other specific comments follow:

The sensitivity, specificity, NPV, and PPV estimates require confidence intervals-- particularly since they are the primary outcome measures of this study.

Answer: According with the reviewer’s comment we have included the confidence intervals of all parameters used to define assays accuracy (Page 6, Lines 168-178; Page 7, Lines 202-217).

3. The authors should address more fully the criticism that subgenomic RNAs persist in samples for a long period of time and are thus not suitable as a proxy for infectiousness. The durations since symptom onset presented in this study, however, appear to be much longer than those previously reported (see above).

Answer: According with the reviewer’s comment a deeper description of the criticism regarding the role of subgenomic RNAs in the proxy for infectiousness has been included in the new version of the manuscript (Page 9, Lines 238-244). As reported in point n. 1 of this revision, samples belonging to patients with a time between symptom onset and sampling date >14 days were excluded from the revised version of the manuscript. The analyses were extensively revised.

4. The ROC results should be presented before the main results, since the cutoffs obtained in the ROC results are used for all subsequent comparisons.

Answer: In our revised manuscript the ROC analysis was performed in order to define the best cut-off of sgRNA load to predict viable virus. The cut-offs estimated by the ROC analysis were then used to perform a speculative comparison with clinical presentation. In line with these considerations the paragraphs “SARS-CoV-2 sgRNA load cut-off definition for viable virus” and “Correlation with clinical presentation” are reported after the description of patients’ characteristics and after the description of SARS-CoV-2 subgenomic results against culture (Page 7, Lines 200-205).

5. It is an acknowledged but real limitation that this study was conducted prior to the emergence of the omicron variant, as subgenomic RNA.

Answer: We are aware that the absence of the Omicron variant in the study is a major limitation. In agreement with the reviewer's comment, we have stressed this limitation in the discussion of the new version of the manuscript (Page 9, Lines 276-279).

6. As noted by the authors, the sample size is quite small, with only 18 culture-positive patients. This renders the results of this study exploratory at best.

Answer: We agree with the reviewer that the sample size is rather small. We have stressed this limitation in the new version of the manuscript, acknowledging the exploratory nature of the results obtained (Page 9-10; Lines 270-271, 281-183).

7. I'm afraid I cannot recommend publication of this article in PLOS ONE owing to the questions I have about the long time between symptom onset and culture positivity, the lack of appropriate measures of uncertainty for sensitivity and specificity calculations, and the small sample size.

Answer: We would like to thank the reviewer for her/his time and the constructive criticisms she/he has given. All the comments have been carefully considered and addressed. We hope that in this revised version the manuscript can be considered again for potential publication in Plos One.

Reviewer #2:

The study presents the results of original research. Authors use an original methodical approach for measuring of SARS-CoV-2 sgRNA levels.

But there are some issues with the study design.

Answer: We thank the Reviewer for the appreciation of our work. We revised the study population and the whole manuscript to further improve quality and clarity.

1. The main problem is sample selection criteria. Authors mention that they collect nasopharyngeal swabs from SARS-CoV-2 positive patients on 37 day after symptom onset (median, IQR 18-67). Several studies (for example doi: 10.1186/s12916-020-01810-8 and doi: 10.1016/S2213-2600(22)00226-0) have shown that viral shedding in upper respiratory tract usually stops after 14 days post-symptom onset. So, obviously many of swabs (53/110) were PCR-negative and others (39/110) had low viral loads undetectable by virus isolation.

Answer: In accordance with this comment and comment 1 of the reviewer #1, samples belonging to patients with a time between symptom onset and sampling date longer than 14 days were excluded from the revised version of the manuscript. Therefore, the new analyses included 51 patients (Supplementary Figure 1 and Page 3-4, Lines 85-90 of the main manuscript). The new results showed a median time between symptom onset and swab sampling of 8 (1-11) days.

2. Authors don’t provide data of RNAse-P assay in genomic SARS-CoV-2 RNA-targeted RT-PCR which should act as the Internal Control and this absence doesn’t allow to judge about the quality of sample collection and RNA purification steps.

Answer: According with the reviewer’s comment, in the new version of the manuscript, we added the Supplementary Figure 2 reporting the Quantasoft panel for RNAse P housekeeping gene of the 51 nasopharyngeal swabs. In addition, in the uploaded supplementary material, we included the individual RNAse-P values of the 51 samples considered in the study. As stated in the manuscript (Page 6, Lines 179-180) RNAseP RNA quantification confirmed the high quality of all the 51 nasopharyngeal swabs.

3. Also some typos were found: “In detail, genomic RNA assay targeted three different RNA-dependent RNA-polymerase (RdRp) of SARS-CoV-2 and the RNAseP housekeeping gene” (lines 103-105). Do the authors use three PCR assays targeted viral RdRp or do they use one which consists of three oligos targeted RdRp?

Answer: In accordance with this comment and reviewer comment 3 of reviewer #3, we clarified this part of the manuscript (Page 4, Lines 106-114) and included a Supplementary Table 3 reporting the sequences of primers and probes used to quantify genomic RNA and sgRNA. In detail, one home-made and two previously tested assays (WHO. Real-Time RT-PCR Assays for the Detection of SARS-CoV-2;) targeting 3 different regions of RNA-dependent RNA-polymerase (RdRp) of SARS-CoV-2 were used to quantify SARS-CoV-2 genomic RNA. The assay targeting the RNAseP housekeeping gene was used as reference (CDC. CDC’s Influenza SARS-CoV-2 Multiplex Assay). The sgRNAs were quantified using assays adapted for the ddPCR system and targeting the envelope and nucleocapsid transcripts (Wölfel R. et al., 2020; Telwattw S. et al., 2022).

4. The reviewer would recommend to include in the study samples collected from patients within 0-14 days post-symptom onset with different viral loads and exclude samples which are negative on SARS-CoV-2 genome RT-PCR.

Answer: Thanks for this comment. In accordance with comment n. 1 of this revision and comment 1 of the reviewer #1, samples belonging to patients with a time between symptom onset and sampling date >14 days were excluded from the revised version of the manuscript.

Reviewer #3:

The manuscript presents convincing data on the possibility of application of sgRNA quantification to determine active viral replication of SARS-CoV-2. The authors present results on the correlation between viral load of genomic and subgenomic RNAs as well as with the culture isolation test and the clinical infection pattern of the patients.

Despite the conclusive data obtained, the authors are correct in pointing out the limitations of the presented work related to the small sample of patients and the inclusion of other genes sgRNA (particularly interesting is the S-protein gene). The authors also point out the possibility of applying this test to people with long-term positivity to SARS-CoV-2, although in this study nasopharyngeal swabs were taken from people with symptoms of the disease (acute infection).

Despite its simplicity, the present work makes a good impression.

A few questions and comments to help improve the manuscript.

Answer: We thank the reviewer for his/her positive and thoughtful comments.

1. Was the selected patient tested for the antigen (nucleocapsid protein) or the standard PCR test used in routine clinical practice? This data can be added to the manuscript (e.g., Table 1).

Answer: The patients selected for the study were not tested for antigen (nucleocapsid protein) but for presence of genomic RNA with the standard real-time PCR test used in routine clinical practice. In this regard, it was possible to retrieve information on positivity to the gene targets tested but not the individual CT values. The positivity information shown by the standard PCR at only one target or at multiple targets has been included in the new version of Table 1.

2. By analyzing the data in Table 1, the authors conclude that there is no difference between patients with SARS-CoV-2 positive and negative culture isolation. However, the last column (P-value) with such a random small sample of patients, in my opinion, is unnecessary.

Answer: According with the reviewer’s comment, in the new version of Table 1 we removed the p-values reported. Due to the small sample size, P-values in the Supplementary Table 3 and in the “Correlation with clinical presentation” paragraph were also removed.

3. The authors do not provide primers for genomic RNA and sgRNA PCR in the "Material and Methods" section. I recommend inserting them as a table in this section, because otherwise a number of questions arise. For example, is the cgRNA sequence part of the complete genomic RNA or not?

Answer: In accordance with this comment and comment 3 of reviewer #2, we clarified this part of the manuscript (Page 4, Lines 106-114) and included a Supplementary Table 3 reporting the sequences of primers and probes used to quantify genomic RNA and sgRNA. In detail, one home-made and two previously tested assays (WHO. Real-Time RT-PCR Assays for the Detection of SARS-CoV-2;) targeting 3 different regions of RNA-dependent RNA-polymerase (RdRp) of SARS-CoV-2 were used to quantify SARS-CoV-2 genomic RNA. The assay targeting the RNAseP housekeeping gene was used as reference (CDC. CDC’s Influenza SARS-CoV-2 Multiplex Assay). The sgRNAs were quantified using assays adapted for the ddPCR system and targeting the envelope and nucleocapsid transcripts (Wölfel R. et al., 2020; Telwattw S. et al., 2022).

4. Since this work is to study the correlation between several parameters, I recommend presenting a graphical design of the study to make it easier to understand the progress of the work.

Answer: In light of the comments of reviewers # 1 and #2, the study design was modified by including only samples belonging to patients with a time between symptoms and sampling collection ≤14 days. Based on these comments and the new selection criteria, a Supplementary Figure 1 describing the flowchart of the study population was added.

5. In the "Discussion" section, the results of other researchers on SARS-CoV-2 subgenomic RNA detection and their possible role as a surrogate-to marker of infectious viral shedding could be described in more detail.

Answer: According with this reviewer comment and point 3 of reviewer 1, a deeper discussion of the role of subgenomic RNAs in the proxy for infectiousness has been included in the new version of the manuscript (Page 9, Lines 257-268).

Attachment

Submitted filename: Responses_Reviewers_v.2.6.docx

Click here for additional data file. (26.2KB, docx)

Decision Letter 1

Ahmed S Abdel-Moneim

13 Jun 2023

PONE-D-22-24987R1Quantitative SARS-CoV-2 subgenomic RNA as a surrogate marker for viral infectivity: comparison between culture isolation and direct sgRNA quantificationPLOS ONE

Dear Dr. Alteri,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please submit your revised manuscript by Jul 28 2023 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

  • A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

  • A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

  • An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

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Academic Editor

PLOS ONE

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PLoS One. 2023 Sep 1;18(9):e0291120. doi: 10.1371/journal.pone.0291120.r004

Author response to Decision Letter 1

12 Jul 2023

PONE-D-22-24987R1

Title: Quantitative SARS-CoV-2 subgenomic RNA as a surrogate marker for viral infectivity: comparison between culture isolation and direct sgRNA quantification

Journal: PLOS ONE

We would like to thank academic editor for his time and for the constructive criticisms he arose.

The revisions of the manuscript in accordance with his comment are summarized in our responses below.

Response to Editor’ Comment

1. We recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorialemail&utm_source=authorletters&utm_campaign=protocols.

Answer: According with the editor’s comment, we provided the full protocol describing the detailed methodology used for the detection and quantification of SARS-CoV-2 subgenomic RNAs and viral load in the revised version of the manuscript as Supplementary File 1 (Page 4, Lines 114-115). We tried to deposit the protocol in protocols.io as the editor suggested, but we did not received the customer code required for the submission and requested to plosone@plos.org by email in June, 2023, following the lab protocol guidelines (available at https://journals.plos.org/plosone/s/submission-guidelines#loc-lab-protocols). We also added a funding and data availability statement to the revised manuscript (Page 11, lines 323-329).

Attachment

Submitted filename: EditorComment_Response_v.3.1.docx

Click here for additional data file. (18.8KB, docx)

Decision Letter 2

Ahmed S Abdel-Moneim

23 Aug 2023

Quantitative SARS-CoV-2 subgenomic RNA as a surrogate marker for viral infectivity: comparison between culture isolation and direct sgRNA quantification

PONE-D-22-24987R2

Dear Dr. Alteri,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Kind regards,

Ahmed S. Abdel-Moneim, Ph.D.

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #4: All comments have been addressed

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2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #4: Yes

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3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #4: Yes

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Reviewer #4: Yes

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Reviewer #4: Yes

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Reviewer #4: The text of the manuscript was modified according to the reviewers' comments. This revision version of the MS may be published in the journal PlosOne.

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Reviewer #4: No

**********

Acceptance letter

Ahmed S Abdel-Moneim

25 Aug 2023

PONE-D-22-24987R2

Quantitative SARS-CoV-2 subgenomic RNA as a surrogate marker for viral infectivity: comparison between culture isolation and direct sgRNA quantification

Dear Dr. Alteri:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Prof. Ahmed S. Abdel-Moneim

Academic Editor

PLOS ONE

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    S1 Fig. Selection criteria for the 51 nasopharyngeal swabs included in the study.

    (PDF)

    Click here for additional data file. (176.2KB, pdf)
    S2 Fig. Quantasoft panel for RNAse P housekeeping gene of the 51 nasopharyngeal swabs (one well per patient).

    In each panel, the first and second wells represent the negative and positive reaction control, respectively.

    (PDF)

    Click here for additional data file. (591.8KB, pdf)
    S1 Table. Primers and probes used to quantify SARS-CoV-2 load and subgenomic RNA.

    (DOCX)

    Click here for additional data file. (16.6KB, docx)
    S2 Table. SARS-CoV-2 genomic and subgenomic RNA load against culture isolation.

    (DOCX)

    Click here for additional data file. (16.8KB, docx)
    S3 Table. Demographic and clinical characteristics of patients against SARS-CoV-2 culture isolation vs subgenomic RNA concordance.

    (DOCX)

    Click here for additional data file. (16.9KB, docx)
    S1 File. Supplementary information reporting the full protocol used for the detection and quantification of SARS-CoV-2 subgenomic RNAs and viral load.

    (DOCX)

    Click here for additional data file. (27.5KB, docx)
    S2 File. Supplementary information reporting data related to Figs 1, 2 and S2 Fig.

    (XLSX)

    Click here for additional data file. (20.1KB, xlsx)
    Attachment

    Submitted filename: Responses_Reviewers_v.2.6.docx

    Click here for additional data file. (26.2KB, docx)
    Attachment

    Submitted filename: EditorComment_Response_v.3.1.docx

    Click here for additional data file. (18.8KB, docx)

    Data Availability Statement

    All relevant data are within the paper and its Supporting Information files.

    Articles from PLOS ONE are provided here courtesy of PLOS

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