Background Carbapenem-resistant Klebsiella pneumoniae (CRKP) is emerging as a significant pathogen causing healthcare-associated infections. Matrix-assisted laser desorption/ionisation mass spectrometry time-of-flight mass spectrometry (MALDI-TOF MS) is used by clinical microbiology laboratories to address the need for rapid, cost-effective and accurate identification of microorganisms. We evaluated application of machine learning methods for differentiation of drug resistant bacteria from susceptible ones directly using the profile spectra of whole cells MALDI-TOF MS in 46 CRKP and 49 CSKP isolates. Methods We developed a two-step strategy for data preprocessing consisting of peak matching and a feature selection step before supervised machine learning analysis. Subsequently, five machine learning algorithms were used for classification. Results Random forest (RF) outperformed other four algorithms. Using RF algorithm, we correctly identified 93% of the CRKP and 100% of the CSKP isolates with an overall classification accuracy rate of 97% when 80 peaks were selected as input features. Conclusions We conclude that CRKPs can be differentiated from CSKPs through RF analysis. We used direct colony method, and only one spectrum for an isolate for analysis, without modification

BackgroundRapid identification of mycobacteria is important for timely treatment and the implementation of public health measures. The MGIT system ensures rapid detection of mycobacteria, but identification is usually delayed by days to weeks due to further subculture on solid medium. Matrix-assisted laser desorption time-of-flight mass spectrometry (MALDI-TOF MS) was demonstrated to effectively identify mycobacteria isolates subcultured from solid or liquid media. Reports of identification directly from MGIT broths of both sterile and non-sterile clinical specimens, omitting the subculture step, were limited and not satisfactory before. Our identification method dramatically shortened delay from detection to identification of mycobacteria.MethodologyWe assessed the performance of the Vitek MS IVD version 3.0 for direct identification of NTM and M.tuberculosis from primary MGIT cultures, and assessed two sample preparation methods.ResultsDirect identification of NTM from positive MGIT broths, using MALDI-TOF VITEK MS with IVD v.3.0, generated high rates of acceptable results reaching 96.4% (80/83), and up to 100% (83/83) for sample preparations including a 0.1% SDS washing step. The sensitivity of VITEK MS to identify M.tuberculosis from MGIT tubes was 58/72 (80.6%), when using immunochromatography (ICA) test as gold standard. A characteristic colony clumping, wool-like appearance was observed in 48, and all 58 (100%) were correctly identified as M.tuberculosis using MALDI-TOF. The detection rate of M.tuberculosis complex was low (10/24, 41.6%) in the 24 MGIT tubes that was polymicrobial. Our method significantly reduced both the reagent cost and turnaround time.ConclusionsBased on a simplified protocol, we showed that MALDI-TOF MS can be used for rapid identification of NTM directly from primary MGIT cultures within the routine clinical laboratory workflow. However, we recommend an initial ICA test to screen for M.tuberculosis complex, due to a low identification rate of M. tuberculosis in the presence of polymicrobial cultures using MALDI-TOF.

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BackgroundBile esculin azide with vancomycin (BEAV) medium is a sensitive, but slightly less specific method for vancomycin-resistant enterococci (VRE) screening. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) is a rapid method for identification of clinical pathogens. This study aimed to assess the performance of a novel combination screening test for VRE, using BEAV broth combined with MALDI-TOF MS.Materials and methodsClinical specimens were collected from patients at risk of VRE carriage, and tested by the novel combination method, using selective BEAV broth culture method followed by MALDI-TOF MS identification (SBEAVM). The reference method used for comparison was the ChromID VRE agar method.ResultsA total of 135 specimens were collected from 78 patients, and 63 specimens tested positive for VRE positive using the ChromID VRE method (positive rate 46.7%). The sensitivity, specificity, positive predictive value, and negative predictive value of SBEAVM method after an incubation period of 28 hours were 93.7%, 90.3%, 89.4%, and 94.2%, respectively. The SBEAVM method when compared to the ChromID VRE method had a shorter turnaround time (29 vs. 48–72 hours) and lower laboratory cost ($2.11 vs. $3.23 per test).ConclusionsThis study demonstrates that SBEAVM is a rapid, inexpensive, and accurate method for use in VRE screening.