Rapid Identification of Escherichia coli Colistin-Resistant Strains by MALDI-TOF Mass Spectrometry.

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

SUBMITTER: Calderaro A 

PROVIDER: S-EPMC8623207 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature