Sensitive Screening Tests for Suspected Class A Carbapenemase Production in Species of Enterobacteriaceae

The detection of class A serine-carbapenemases among species of Enterobacteriaceae remains a challenging issue. Methods of identification for routine use in clinical microbiology laboratories have not been standardized to date. We developed a novel screening methodology suitable for countries with high basal levels of carbapenem resistance due to non-carbapenemase-mediated mechanisms and standardized several simple confirmatory methods that allow the recognition of bacteria producing class A carbapenemases, including KPC, Sme, IMI, NMC-A, and GES, by using boronic acid (BA) derivatives. A total of 28 genetically unrelated Enterobacteriaceae strains producing several class A carbapenemases were tested. Thirty-eight genetically unrelated negative controls were included. The isolates were tested against imipenem (IPM), meropenem (MEM), and ertapenem (ETP) by MIC and disk diffusion assays in order to select appropriate tools to screen for suspected carbapenemase production. It was possible to differentiate class A carbapenemase-producing bacteria from non-carbapenemase-producing bacteria by using solely the routine IPM susceptibility tests. The modified Hodge test was evaluated and found to be highly sensitive, although false-positive results were documented. Novel BA-based methods (a double-disk synergy test and combined-disk and MIC tests) using IPM, MEM, and ETP, in combination with 3-aminophenylboronic acid as an inhibitor, were designed as confirmatory tools. On the basis of the performance of these methods, a sensitive flow chart for suspicion and confirmation of class A carbapenemase production in species of Enterobacteriaceae was designed. By using this methodology, isolates producing KPC, GES, Sme, IMI, and NMC-A carbapenemases were successfully distinguished from those producing other classes of beta-lactamases (extended-spectrum beta-lactamases, AmpCs, and metallo-beta-lactamases, etc). These methods will rapidly provide useful information needed for targeting antimicrobial therapy and appropriate infection control.