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</script>ABSTRACT In the treatment of serious bacterial infections, the rapid institution of appropriate antimicrobial chemotherapy may be lifesaving. Choosing the correct antibiotic or combination of antibiotics is becoming very important, as multidrug resistance is found in many pathogens. Using a collection of 75 well-characterized multidrug-resistant (MDR) Acinetobacter sp. isolates, we show that PCR followed by electrospray ionization mass spectrometry (PCR/ESI-MS) and base composition analysis of PCR amplification products can quickly and accurately identify quinolone resistance mediated by mutations in the quinolone resistance-determining regions of gyrA and parC , two essential housekeeping genes. Single point mutations detected by PCR/ESI-MS in parC (found in 55/75 of the isolates) and in gyrA (found in 66/75 of the isolates) correlated with susceptibility testing and sequencing. By targeting resistance determinants that are encoded by genes with highly conserved DNA sequences (e.g., gyrA and parC ), we demonstrate that PCR/ESI-MS can provide critical information for resistance determinant identification and can inform therapeutic decision making in the treatment of Acinetobacter sp. infections.
DNA Topoisomerase IV, DNA, Bacterial, Spectrometry, Mass, Electrospray Ionization, Acinetobacter, Base Sequence, Molecular Sequence Data, Mutation, Missense, Microbial Sensitivity Tests, Quinolones, Polymerase Chain Reaction, Bacterial Proteins, DNA Gyrase, Drug Resistance, Bacterial, Humans, Point Mutation
DNA Topoisomerase IV, DNA, Bacterial, Spectrometry, Mass, Electrospray Ionization, Acinetobacter, Base Sequence, Molecular Sequence Data, Mutation, Missense, Microbial Sensitivity Tests, Quinolones, Polymerase Chain Reaction, Bacterial Proteins, DNA Gyrase, Drug Resistance, Bacterial, Humans, Point Mutation
| citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 63 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
