Comparative evaluation of nucleic acid detection kits and nucleic acid extraction methods for SARS-CoV-2 using clinical samples / 国际药学研究杂志
Journal of International Pharmaceutical Research
; (6): 424-429, 2020.
Article
en Zh
| WPRIM
| ID: wpr-845167
Biblioteca responsable:
WPRO
ABSTRACT
Objective: To compare and analyze 7 new coronavirus nucleic acid detection kits and 5 nucleic acid extraction methods. Methods: After extracting nucleic acids from 44 positive coronavirus clinical samples, 7 SARS-CoV-2 nucleic acid detection kits were used for RT-PCR amplification experiments to compare the positive rate and Ct value;33 new coronavirus positive clinical samples were selected to compare the acid extraction methods. Five different nucleic acid extraction methods were used to extract the samples, and then RT-PCR amplification experiments were performed to compare the positive rate and Ct value. Results: The brand A nucleic acid extraction kit had the highest positive rate and the lowest rate of missed detection;comparison of nucleic acid extraction methods showed that the manual column extraction method had the highest positive rate, followed by the magnetic bead extraction method, and the one-step extraction method had the highest missed detection rate. Conclusion: The detection capabilities of the SARS-CoV-2 detection kits are uneven, so evaluation work needs to be done before the selection of the kit. The manual column extraction method showed best extraction efficiency but took a long time. Because of the possible combination with the automatic nucleic acid extraction instrument, the magnetic bead extraction method had a high extraction efficacy, which might be suitable for use in the ex- traction of large batches of samples. Although the one-step extraction method was easily operable, the method had a high missed detection rate, so this method was not recommended for clinical use.
Texto completo:
1
Índice:
WPRIM
Tipo de estudio:
Diagnostic_studies
/
Guideline
Idioma:
Zh
Revista:
Journal of International Pharmaceutical Research
Año:
2020
Tipo del documento:
Article