Abstract
Colistin resistance is one of the major threats for global public health, requiring reliable and rapid susceptibility testing methods. The aim of this study was the evaluation of a MALDI-TOF mass spectrometry (MS) peak-based assay to distinguish colistin resistant (colR) from susceptible (colS) Escherichia coli strains. To this end, a classifying algorithm model (CAM) was developed, testing three different algorithms: Genetic Algorithm (GA), Supervised Neural Network (SNN) and Quick Classifier (QC). Among them, the SNN- and GA-based CAMs showed the best performances: recognition capability (RC) of 100% each one, and cross validation (CV) of 97.62% and 100%, respectively. Even if both algorithms shared similar RC and CV values, the SNN-based CAM was the best performing one, correctly identifying 67/71 (94.4%) of the E. coli strains collected: in point of fact, it correctly identified the greatest number of colS strains (42/43; 97.7%), despite its lower ability in identifying the colR strains (15/18; 83.3%). In conclusion, although broth microdilution remains the gold standard method for testing colistin susceptibility, the CAM represents a useful tool to rapidly screen colR and colS strains in clinical practice.
Highlights
Infections caused by resistant Gram-negative bacteria, such as Enterobacteriaceae, Pseudomonas aeruginosa and Acinetobacter baumannii, are a broad matter of concern, because of the ineffectiveness of conventional treatments and the lack of new antimicrobial agents against them [1,3]
We describe an alternative approach for the identification of colistin resistance in Gram-negative bacteria by proposing a MALDI-TOF mass spectrometry (MS)
According to the colistin susceptibility testing results, among all E. coli isolates, 48 (33 human and 15 animal strains) were colistin-susceptible and 23 (20 human and three animal strains) were colistin-resistant (MIC ≥ 4 mg/L). Both the colistin resistant (colR)-Escherichia coli (Ec) strains and the colS-Ec strains were correctly identified at the species level by MALDI-TOF MS, with score values above 2.0
Summary
Antimicrobial resistance is one of the major threats for global public health, since many pathogens are developing resistance mechanisms to almost all currently available antimicrobial drugs [1,2,3] This phenomenon is mostly related to the misuse and overuse of antimicrobials, which led to the emergence of multidrug-resistant (MDR), extensivelydrug-resistant (XDR) and pan-drug-resistant bacteria [4,5,6,7]. Colistin is considered a “last resort” antibiotic, namely a valid alternative to the classic antimicrobial agents ineffective against MDR Gram-negative pathogens [1,3,6,8].
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