Rapid detection of antibiotic resistance in Acinetobacter baumannii using quantitative real-time PCR

• Published in: Journal of antimicrobial chemotherapy 2013-07, Vol.68 (7), p.1572-1575
• Main Authors: Martín-Peña, Reyes, Domínguez-Herrera, Juan, Pachón, Jerónimo, McConnell, Michael J
• Format: Article
• Language: English
• Subjects: Acinetobacter baumannii; Acinetobacter baumannii - drug effects; Acinetobacter baumannii - genetics; Acinetobacter baumannii - growth & development; Antibiotics; Bioassays; Drug resistance; Drug Resistance, Bacterial; Drug therapy; Gram-negative bacteria; Humans; Microbial Sensitivity Tests - methods; Molecular Diagnostic Techniques - methods; Polymerase chain reaction; Real-Time Polymerase Chain Reaction - methods; Time Factors
• ISSN: 0305-7453; 1460-2091
• DOI: 10.1093/jac/dkt057

The rapid detection of antibiotic resistance in clinical isolates of Acinetobacter baumannii would shorten the period during which patients receive empirical therapy and facilitate the early initiation of directed antibiotic therapy. The objective of this study was to evaluate the ability of a real-time PCR assay to detect antibiotic resistance to four clinically relevant antibiotics from different antibiotic classes in clinical isolates of A. baumannii. The growth of 48 clinical isolates of A. baumannii with a broad range of MICs of imipenem, ciprofloxacin, colistin and amikacin was evaluated using a real-time PCR assay targeting a highly conserved region of the ompA gene. Fold changes in the number of copies of genomic DNA after 6 h of growth were used to determine resistance and the results were compared with those obtained using broth microdilution. The results obtained using the real-time PCR assay were concordant with broth microdilution for 184 of 192 determinations (95.8%). The global values for specificity (97.5%), sensitivity (92.9%), positive predictive value (95.6%) and negative predictive value (96.0%) indicated that the real-time PCR assay was able to reliably differentiate between resistant and non-resistant strains. The use of real-time PCR to monitor bacterial growth in the presence of antibiotics is effective for rapidly identifying antibiotic resistance in A. baumannii.