Bibliographic citations
Chavesta, P., Medrano, P. (2023). Diseño de primers del gen meca para detección de Staphylococcus aureus resistente a meticilina por Amplificación de Polimerasa y Recombinasa, Perú 2022. [Universidad Nacional de Trujillo]. https://hdl.handle.net/20.500.14414/20572
Chavesta, P., Medrano, P. Diseño de primers del gen meca para detección de Staphylococcus aureus resistente a meticilina por Amplificación de Polimerasa y Recombinasa, Perú 2022. []. PE: Universidad Nacional de Trujillo; 2023. https://hdl.handle.net/20.500.14414/20572
@misc{renati/1044907,
title = "Diseño de primers del gen meca para detección de Staphylococcus aureus resistente a meticilina por Amplificación de Polimerasa y Recombinasa, Perú 2022.",
author = "Medrano Alhuay, Princesa Alicia",
publisher = "Universidad Nacional de Trujillo",
year = "2023"
}
The aim of this research was to design in silico primers of the mecA gene that would allow detecting Peruvian strains of methicillin-resistant Staphylococcus aureus (MRSA) by Polymerase and Recombinase Amplification (RPA), verifying and validating that the desirable physical chemical characteristics of these primers were accomplished. Moreover, their specificity and in silico amplification capacity of were evaluated. Thus, letting pendent the evaluation of the amplification and diagnostic capacity that should be done at the laboratory level in the future. Thirtytwo mecA gene sequences from Peru were obtained from the RefSeq database of the National Center for Biotechnology Information (NCBI), integrating the information in a metadata. Primers were designed using the bioinformatics programs Primer-BLAST and Primer3Plus. The two best primer pairs for RPA were selected: pair Nº1 (mecA-RPA-F1 and mecA-RPA-R1) and pair Nº2 (mecA-RPAF2 and mecA-RPA-R2) by evaluating the thermodynamic parameters and secondary structures with the Oligoanalyzer Tool and Beacon Designer Free Edition programs. The in silico amplification capability of the Staphylococcus aureus mecA gene primers was verified using the In silico PCR amplification and PCR Test - Sequences Manipulation Suite (SMS) programs. This assessment was complemented by evaluating the specificity of the primers using the BLAST-N software that showed the ability of the proposed primers to identify the Peruvian strains of Staphylococcus aureus (with 100% identity), which represented the 62% of the total number of identified species, while the 38% were other Staphylococcus species.
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