Laboratory validation of an RNA/DNA hybrid tagmentation based mNGS workflow on SARS-CoV-2 and other respiratory RNA viruses detection

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1. 

   ScreenIT

   Jun 8, 2020

   SciScore for 10.1101/2020.05.12.20099754: (What is this?)

   Please note, not all rigor criteria are appropriate for all manuscripts.

   Table 1: Rigor

   Institutional Review Board Statement	IRB: Ethics statement: This study was reviewed and approved by the Ethics Committee of Beijing Youan Hospital, Capital Medical University.
   Randomization	not detected.
   Blinding	not detected.
   Power Analysis	not detected.
   Sex as a biological variable	not detected.
   Cell Line Authentication	not detected.

   Table 2: Resources

   Experimental Models: Cell Lines
   Sentences	Resources
   LOD were calculated in R (version 3.5.1) using probit regression analysis23 following approved guidelines of clinical and laboratory standards institute with 3 to 20 replicates performed at each concentration. 2) Precision: External PC and NTC samples were analyzed over 5 independent mNGS runs (inter-run …

   SciScore for 10.1101/2020.05.12.20099754: (What is this?)

   Please note, not all rigor criteria are appropriate for all manuscripts.

   Table 1: Rigor

   Institutional Review Board Statement	IRB: Ethics statement: This study was reviewed and approved by the Ethics Committee of Beijing Youan Hospital, Capital Medical University.
   Randomization	not detected.
   Blinding	not detected.
   Power Analysis	not detected.
   Sex as a biological variable	not detected.
   Cell Line Authentication	not detected.

   Table 2: Resources

   Experimental Models: Cell Lines
   Sentences	Resources
   LOD were calculated in R (version 3.5.1) using probit regression analysis23 following approved guidelines of clinical and laboratory standards institute with 3 to 20 replicates performed at each concentration. 2) Precision: External PC and NTC samples were analyzed over 5 independent mNGS runs (inter-run reproducibility) and as 3 independent sets over 1 run (intra-run reproducibility) and evaluated for quality control metrics and viral detection using established thresholds. 3) Interference: to evaluate the effect of human host background on mNGS assay performance, we spiked SARS-COV-2 and Influenza A virus (A/2009/H1N1) standards into low (1 × 104 cells/mL), medium (1×105 cells/mL), and high (1×106 cells/mL) titers of human A549 cell.	A549 suggested: NCI-DTP Cat# A549, RRID:CVCL_0023)

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   Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

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   Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:

   Second, our data showed that high host background was a fairly common limitation of mNGS. It inferred that negative findings of unbiased mNGS methods might be less useful for excluding infection in high host background samples11,16. We, third, explore accuracy of CATCH by clinical oropharyngeal swabs during COVID-19 pandemic. CATCH showed a well compatibility with concentration of input. Although there were 65.00% and 38.46% samples in qRT-PCR negative and positive samples cannot be measured a definite concentration (Figure S3), we still have a 100% success in library preparation (Data not shown). The overall accuracy of CATCH for SARS-CoV-2 detection relative to conventical qRT-PCR was 91.4%, with 84.5% sensitivity and 100% specificity. In dual-gene qRT-PCR positive samples, sensitivity increased to 93.7%. We suggest that integrity of viral RNA might impair pathogen detective efficiency of CATCH. Moreover, as we knew, CATCH or other RNA/DNA hybrid tagmentation method without optimization will have obvious 3’bias13. This feature might also decrease possibility to capture viral fragments in clinical samples. For further implementation, CATCH needs optimization for overcome this limitation. Last, we found that CATCH can detect enrichment of opportunistic pathogen in oropharyngeal swabs of COVID-19 patients comparing with healthy control. It indicated that we can expand application of CATCH in fungal or bacterial detection in the near future. We also found an interesting phenome...

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   Results from TrialIdentifier: No clinical trial numbers were referenced.

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   Results from Barzooka: We found bar graphs of continuous data. We recommend replacing bar graphs with more informative graphics, as many different datasets can lead to the same bar graph. The actual data may suggest different conclusions from the summary statistics. For more information, please see Weissgerber et al (2015).

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   Results from JetFighter: We did not find any issues relating to colormaps.

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   Results from rtransparent:

   • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
   • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
   • No protocol registration statement was detected.

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   Read the original source
2. 

   Version published to 10.1101/2020.05.12.20099754 on medRxiv

   May 14, 2020