Optimization of five qPCR protocols toward the detection and the quantification of antimicrobial resistance genes in environmental samples
Roberta Tolosi,
Lisa Carraro,
Andrea Laconi,
Alessandra Piccirillo
Affiliations
Roberta Tolosi
Department of Comparative Biomedicine and Food Science, University of Padua, Viale dell'Università 16, Legnaro, Padua 35020, Italy
Lisa Carraro
Department of Comparative Biomedicine and Food Science, University of Padua, Viale dell'Università 16, Legnaro, Padua 35020, Italy
Andrea Laconi
Corresponding author.; Department of Comparative Biomedicine and Food Science, University of Padua, Viale dell'Università 16, Legnaro, Padua 35020, Italy
Alessandra Piccirillo
Department of Comparative Biomedicine and Food Science, University of Padua, Viale dell'Università 16, Legnaro, Padua 35020, Italy
Here, we describe the optimization and validation of five quantitative PCR (qPCR) assays by employing the SYBRGreen chemistry paired with melting curve analysis to detect and quantify clinically relevant antimicrobial resistance genes (ARGs) (i.e. ermB, blaCTXM1-like, blaCMY-2, qnrA and qnrS) from environmental samples (i.e. soil and manure). These five protocols accurately detected and quantified the aforementioned ARGs in complex environmental matrices and represent useful tools for both diagnostic and monitoring activities of resistant bacteria and ARGs into the environment.
