ArticleInternational journal of molecular sciences2024
Assessment of DNA/RNA Defend Pro: An Inactivating Sample Collection Buffer for Enhanced Stability, Extraction-Free PCR, and Rapid Antigen Testing of Nasopharyngeal Swab Samples.
Article in International journal of molecular sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
This study comprehensively evaluated the DNA/RNA Defend Pro (DRDP) sample collection buffer, designed to inactivate and stabilize patient samples. The primary objectives were to assess DRDP's efficacy in ensuring sample stability, facilitating extraction-free polymerase chain reaction (PCR), and ensuring compatibility with rapid antigen testing (RAT). Ninety-five diagnostic nasopharyngeal swab samples tested for influenza virus (influenza A), respiratory syncytial virus (RSV A), and/or severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) were 10-fold diluted with DRDP and anonymized. Initial characterization and retesting of these samples using cobas Liat confirmed 88 samples as positive, validating the presence of viral targets. Results from rapid antigen testing showed lower sensitivity compared to nucleic acid amplification testing (NAAT) but maintained perfect specificity, with 40 out of 88 positive samples by cobas Liat also testing positive for RAT. Direct RT-qPCR of DRDP-diluted samples demonstrated robust compatibility, with 72 out of 88 samples positive for cobas Liat also testing positive by direct RT-qPCR. Non-concordant results could be explained by the 200-fold lower input of extraction-free NAAT. Stability testing involved incubating 31 positive samples at 4 °C, 20 °C, and 37 °C for 7 days, with extraction-free NAAT. DRDP guaranteed viral RNA stability at all temperatures for influenza A, SARS-CoV-2, and RSV A, showing stability up to 7 days at 4 °C. In conclusion, DRDP is an effective stabilizing medium compatible with direct RT-qPCR and rapid antigen testing and shows great potential for optimizing diagnostic processes, particularly in resource-limited or time-sensitive scenarios.
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