Clinical validation of RCSMS: a rapid and sensitive CRISPR-Cas12a test for the molecular detection of SARS-CoV-2 from saliva
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Frequently Asked Questions (17)
Q2. What is the “gold standard” among COVID-19 molecular tests?
While antibody tests are recommended for seroprevalence and epidemiological studies, the “gold standard” among COVID-19 molecular tests is the quantitative reverse transcription-polymerase chain reaction (RT-qPCR) (5).
Q3. What is the importance of implementing early and massive testing strategies?
Given the rapid spread of the disease and the arrival of new pandemic waves, it remains urgent to implement early and massive SARS-CoV-2 testing strategies alongside with contact tracing and isolation (3).
Q4. How many copies of the virus were detected in a single assay?
RCSMS routinely detected 50 copies per 10 µl reaction in triplicate assays, occasionally reaching five copies in one or two replicates.
Q5. How many false positives were recorded between the two tests?
In addition, seven incongruencies (2.8%) were recorded between the two tests: two false positives (TFP=2.6%) and five false negatives (TFN=2.5%).
Q6. Why is a sharp decrease of PPV common to all diagnostic tests?
A sharp decrease of PPV in low prevalence settings is common to all diagnostic tests because of the higher probability of obtaining false positives (31).
Q7. What is the importance of obtaining high-quality diagnostic data?
In sum, obtaining high-quality diagnostic data is essential to correctly monitor the evolution of the epidemic, ensure the success of public health strategies and the transition to a new normality.
Q8. What is the effect of the RT-LAMP reaction on the ssDNA reporter?
Recognition of viral target sequences by the RNP complex triggers the collateral activity of Cas12a, resulting in the cleavage of ssDNA reporter probes.
Q9. What is the procedure for a lateral flow strip?
For immunocromatographyic (qualitative) readout, a lateral flow strip is then inserted into the CRISPR-Cas12a reaction tube or well.
Q10. What is the effect of the NPV of diagnostic tests in high prevalence settings?
the NPV of diagnostic tests is expected to drop in high prevalence settings, as the number of false negatives increase (31).
Q11. What is the way to ensure a low rate of false negatives?
Ensuring a low rate of false negatives (positive individuals being deemed negative) is especially desirable considering that COVID-19 is a serious, largely asymptomatic and contagious disease, for which early measures are advisable.
Q12. How many individuals did not record their date of symptom onset?
Ten individuals (3.6% of the total) did not record their date of symptom onset; therefore, their results were excluded from the analysis stratified by time of illness.
Q13. How many positive samples were found in one of the three rounds of analyses?
three rounds of analyses reproduced these results, with only two positive samples yielding a negative result in one of their three replicates.
Q14. How does the RCSMS simulation predict a high prevalence?
their statistical simulation for RCSMS using the currently available data (276 out of 350 samples analyzed, Fig. 7), predicts excellent NPVs >95% for prevalence scenarios as low as 1% and as high as 50%.
Q15. How many copies of the three viral genes were detected?
The limit of detection (LOD) for both viral genes was determined using serial dilutions of the synthetic RNA templates, covering the range from 250 to 1 viral copy per 10 µl RT-LAMP reaction.
Q16. What is the significance of the PPVs for RCSMS?
These PPV estimates are consistent with the results from their field study, where prevalence reached almost 30%, strengthening the conclusion that RCSMS is particularly well suited for the identification of positive cases during acute pandemic phases, such as the current second waves hitting Perú, India and Brazil.
Q17. What was the level of concordance between RT-qPCR and RCSMS?
the level of concordance (Cohen's Kappa coefficient) between RT-qPCR and RCSMS was calculated for both analytical and clinical validations, as well as sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), the area under the curve (AUC), accuracy of RCSMS, and PPV/ NPV simulations assuming various prevalence scenarios.