Characterization of an outbreak caused by Elizabethkingia miricola using Fourier-transform infrared (FTIR) spectroscopy.

Fourier-transform infrared (FTIR) spectroscopy has the potential to be used for bacterial typing and outbreak characterization. We evaluated FTIR for the characterization of an outbreak caused by Elizabethkingia miricola. During the 2020-2021 period, 26 isolates (23 clinical and 3 environmental) were collected and analyzed by FTIR (IR Biotyper) and core-genome MLST (cgMLST), in addition to antimicrobial susceptibility testing. FTIR spectroscopy and cgMLST showed that 22 of the isolates were related to the outbreak, including the environmental samples, with only one discordance between both methods. Then, FTIR is useful for E. miricola typing and can be easily implemented in the laboratory.

Direct Detection of Carbapenemase-Producing Klebsiella pneumoniae by MALDI-TOF Analysis of Full Spectra Applying Machine Learning.

MALDI-TOF MS is considered to be an important tool for the future development of rapid microbiological techniques. We propose the application of MALDI-TOF MS as a dual technique for the identification of bacteria and the detection of resistance, with no extra hands-on procedures. We have developed a machine learning approach that uses the random forest algorithm for the direct prediction of carbapenemase-producing Klebsiella pneumoniae (CPK) isolates, based on the spectra of complete cells. For this purpose, we used a database of 4,547 mass spectra profiles, including 715 unduplicated clinical isolates that are represented by 324 CPK with 37 different ST. The impact of the culture medium was determinant in the CPK prediction, being that the isolates were tested and cultured in the same media, compared to the isolates used to build the model (blood agar). The proposed method has an accuracy of 97.83% for the prediction of CPK and an accuracy of 95.24% for the prediction of OXA-48 or KPC carriage. For the CPK prediction, the RF algorithm yielded a value of 1.00 for both the area under the receiver operating characteristic curve and the area under the precision-recall curve. The contribution of individual mass peaks to the CPK prediction was determined using Shapley values, which revealed that the complete proteome, rather than a series of mass peaks or potential biomarkers (as previously suggested), is responsible for the algorithm-based classification. Thus, the use of the full spectrum, as proposed here, with a pattern-matching analytical algorithm produced the best outcome. The use of MALDI-TOF MS coupled with machine learning algorithm processing enabled the identification of CPK isolates within only a few minutes, thereby reducing the time to detection of resistance.

Automatic Discrimination of Species within the Enterobacter cloacae Complex Using Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry and Supervised Algorithms.

The Enterobacter cloacae complex (ECC) encompasses heterogeneous clusters of species that have been associated with nosocomial outbreaks. These species may have different acquired antimicrobial resistance and virulence mechanisms, and their identification is challenging. This study aims to develop predictive models based on matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) profiles and machine learning for species-level identification. A total of 219 ECC and 118 Klebsiella aerogenes clinical isolates from three hospitals were included. The capability of the proposed method to differentiate the most common ECC species (Enterobacter asburiae, Enterobacter kobei, Enterobacter hormaechei, Enterobacter roggenkampii, Enterobacter ludwigii, and Enterobacter bugandensis) and K. aerogenes was demonstrated by applying unsupervised hierarchical clustering with principal-component analysis (PCA) preprocessing. We observed a distinctive clustering of E. hormaechei and K. aerogenes and a clear trend for the rest of the ECC species to be differentiated over the development data set. Thus, we developed supervised, nonlinear predictive models (support vector machine with radial basis function and random forest). The external validation of these models with protein spectra from two participating hospitals yielded 100% correct species-level assignment for E. asburiae, E. kobei, and E. roggenkampii and between 91.2% and 98.0% for the remaining ECC species; with data analyzed in the three participating centers, the accuracy was close to 100%. Similar results were obtained with the Mass Spectrometric Identification (MSI) database developed recently (https://msi.happy-dev.fr) except in the case of E. hormaechei, which was more accurately identified with the random forest algorithm. In short, MALDI-TOF MS combined with machine learning was demonstrated to be a rapid and accurate method for the differentiation of ECC species.

Rapid detection of KPC-producing Enterobacterales by using a modified Carba NP test with imipenem/relebactam.

INTRODUCTION: Here, we propose a novel modified Carba NP test for detecting KPC-producing Enterobacterales using imipenem/relebactam. MATERIAL AND METHODS: The test performance was evaluated in a random selection of 160 previously molecularly characterized clinical isolates carrying the 110 blaKPC, 1 blaGES, 12 blaVIM, 4 blaIMP, 3 blaNDM and 42 blaOXA-48-like genes. The proposed method relies on the detection of imipenem hydrolysis in an imipenem/relebactam antibiotic solution and subsequent visual interpretation by color change. RESULTS: All class A producing Enterobacterales (111/111) were detected using imipenem/relebactam as no visual appreciation of color change was perceived due to a nule hydrolysis of imipenem in the antibiotic solution. Overall, the assay showed 100% sensitivity (111/111) and specificity (69/69) for detecting class A KPC-producing Enterobacterales. DISCUSSION: The biochemical assay provides very reliable results for detecting KPC-producing Enterobacterales, with a turnaround time of less than 1 hour, minimum handling and no specialized equipment required.

Rapid and Reproducible MALDI-TOF-Based Method for the Detection of Vancomycin-Resistant Enterococcus faecium Using Classifying Algorithms.

Vancomycin-resistant Enterococcus faecium represents a health threat due to its ability to spread and cause outbreaks. MALDI-TOF MS has demonstrated its usefulness for E. faecium identification, but its implementation for antimicrobial resistance detection is still under evaluation. This study assesses the repeatability of MALDI-TOF MS for peak analysis and its performance in the discrimination of vancomycin-susceptible (VSE) from vancomycin-resistant isolates (VRE). The study was carried out on protein spectra from 178 E. faecium unique clinical isolates-92 VSE, 31 VanA VRE, 55 VanB VRE-, processed with Clover MS Data Analysis software. Technical and biological repeatability were assayed. Unsupervised (principal component analysis, (PCA)) and supervised algorithms (support vector machine (SVM), random forest (RF) and partial least squares-discriminant analysis (PLS-DA)) were applied. The repeatability assay was performed with 18 peaks common to VSE and VRE with intensities above 1.0% of the maximum peak intensity. It showed lower variability for normalized data and for the peaks within the 3000-9000 m/z range. It was found that 80.9%, 79.2% and 77.5% VSE vs. VRE discrimination was achieved by applying SVM, RF and PLS-DA, respectively. Correct internal differentiation of VanA from VanB VRE isolates was obtained by SVM in 86.6% cases. The implementation of MALDI-TOF MS and peak analysis could represent a rapid and effective tool for VRE screening. However, further improvements are needed to increase the accuracy of this approach.

Detection of azole resistance in Aspergillus fumigatus complex isolates using MALDI-TOF mass spectrometry.

OBJECTIVES: The main goal of this study was to accurately detect azole resistance in species of the Aspergillus fumigatus complex by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). METHODS: Identification of isolates (n = 868) was done with MALDI-TOF MS using both commercial and in-house libraries. To determine azole susceptibility, the EUCAST E.Def. 9.3.2 method was applied as the reference standard. Identification of resistant isolates was confirmed by DNA sequence analysis. Protein spectra obtained by MALDI-TOF MS were analysed to differentiate species within the A. fumigatus complex and to detect azole-resistant A. fumigatus sensu stricto isolates. RESULTS: Correct discrimination of A. fumigatus sensu stricto from cryptic species was accomplished in 100% of the cases applying principal component analysis (PCA) to protein spectra generated by MALDI-TOF MS. Furthermore, a specific peak (4586 m/z) was found to be present only in cryptic species. The application of partial least squares (PLS) discriminant analysis allowed 98.43% (±0.038) discrimination between susceptible and azole-resistant A. fumigatus sensu stricto isolates. Finally, based on PLS and SVM, A. fumigatus sensu stricto isolates with different cyp51A gene mutations were correctly clustered in 91.5% of the cases. CONCLUSIONS: MALDI-TOF MS combined with peak analysis is a novel tool that allows the differentiation of A. fumigatus sensu stricto from other species within the A. fumigatus complex, as well as the detection of azole-resistant A. fumigatus sensu stricto. Although further studies are still needed, the results reported here show the great potential of MALDI-TOF and machine learning for the rapid detection of azole-resistant Aspergillus fumigatus isolates from clinical origins.

Shared Mutations in Emerging SARS-CoV-2 Circulating Variants May Lead to Reverse Transcription-PCR (RT-PCR)-Based Misidentification of B.1.351 and P.1 Variants of Concern.

Reverse transcription-PCRs (RT-PCRs) targeting SARS-CoV-2 variant of concern (VOC) mutations have been developed to simplify their tracking. We evaluated an assay targeting E484K/N501Y to identify B.1.351/P1. Whole-genome sequencing (WGS) confirmed only 72 (59.02%) of 122 consecutive RT-PCR P.1/B.1.351 candidates. Prescreening RT-PCRs must target a wider set of mutations, updated from WGS data from emerging variants.

An Improved Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry Data Analysis Pipeline for the Identification of Carbapenemase-Producing Klebsiella pneumoniae.

The increasing emergence of carbapenemase-producing Klebsiella pneumoniae (CPK) isolates is a global health alarm. Rapid methods that require minimum sample preparation and rapid data analysis are urgently required. Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) has recently been used by clinical laboratories for identification of antibiotic-resistant bacteria; however, discrepancies have arisen regarding biological and technical issues. The aim of this study was to standardize an operating procedure and data analysis for identification of CPK by MALDI-TOF MS. To evaluate this approach, a series of 162 K. pneumoniae isolates (112 CPK and 50 non-CPK) were processed in the MALDI BioTyper system (Bruker Daltonik, Germany) following a standard operating procedure. The study was conducted in two stages; the first is denominated the "reproducibility stage" and the second "CPK identification." The first stage was designed to evaluate the biological and technical variation associated with the entire analysis of CPK and the second stage to assess the final accuracy of MALDI-TOF MS for the identification of CPK. Therefore, we present an improved MALDI-TOF MS data analysis pipeline using neural network analysis implemented in Clover MS Data Analysis Software (Clover Biosoft, Spain) that is designed to reduce variability, guarantee interlaboratory reproducibility, and maximize the information selected from the bacterial proteome. Using the random forest (RF) algorithm, 100% of CPK isolates were correctly identified when all the peaks in the spectra were selected as input features and total ion current (TIC) normalization was applied. Thus, we have demonstrated that real-time direct tracking of CPK is possible using MALDI-TOF MS.

Rapid detection of KPC-producing Enterobacterales by using a modified Carba NP test with imipenem/relebactam.

INTRODUCTION: Here, we propose a novel modified Carba NP test for detecting KPC-producing Enterobacterales using imipenem/relebactam. MATERIAL AND METHODS: The test performance was evaluated in a random selection of 160 previously molecularly characterized clinical isolates carrying the 110 blaKPC, 1 blaGES, 12 blaVIM, 4 blaIMP, 3 blaNDM and 42 blaOXA-48-like genes. The proposed method relies on the detection of imipenem hydrolysis in an imipenem/relebactam antibiotic solution and subsequent visual interpretation by color change. RESULTS: All class A producing Enterobacterales (111/111) were detected using imipenem/relebactam as no visual appreciation of color change was perceived due to a nule hydrolysis of imipenem in the antibiotic solution. Overall, the assay showed 100% sensitivity (111/111) and specificity (69/69) for detecting class A KPC-producing Enterobacterales. DISCUSSION: The biochemical assay provides very reliable results for detecting KPC-producing Enterobacterales, with a turnaround time of less than 1 hour, minimum handling and no specialized equipment required.

Multicenter Performance Evaluation of MALDI-TOF MS for Rapid Detection of Carbapenemase Activity in Enterobacterales: The Future of Networking Data Analysis With Online Software.

In this study, we evaluate the performance of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) for rapid detection of carbapenemase activity in Enterobacterales in clinical microbiology laboratories during a multicenter networking validation study. The study was divided into three different stages: "software design," "intercenter evaluation," and "clinical validation." First, a standardized procedure with an online software for data analysis was designed. Carbapenem resistance was detected by measuring imipenem hydrolysis and the results were automatically interpreted using the Clover MS data analysis software (Clover BioSoft, Spain). Second, a series of 74 genotypically characterized Enterobacterales (46 carbapenemase-producers and 28 non carbapenemase-producers) were analyzed in 8 international centers to ensure the reproducibility of the method. Finally, the methodology was evaluated independently in all centers during a 2-month period and results were compared with the reference standard for carbapenemase detection used in each center. The overall agreement rate relative to the reference method for carbapenemase resistance detection in clinical samples was 92.5%. The sensitivity was 93.9% and the specificity, 100%. Results were obtained within 60 min and accuracy ranged from 83.3 to 100% among the different centers. Further, our results demonstrate that MALDI-TOF MS is an outstanding tool for rapid detection of carbapenemase activity in Enterobacterales in clinical microbiology laboratories. The use of a simple in-house procedure with online software allows routine screening of carbapenemases in diagnostics, thereby facilitating early and appropriate antimicrobial therapy.

Evaluation of the Alfred AST® system for rapid antimicrobial susceptibility testing directly from positive blood cultures.

To assess the concordance of antimicrobial susceptibility testing results obtained by the Alfred AST® system performed directly from positive blood cultures in comparison with the standard susceptibility test results performed from isolated colonies by an automated broth microdilution method and to determine the applicability of Alfred AST® system in the routine of our blood culture laboratory. This system is based on the detection of growth by turbidimetry through a technology based on light scattering. Antimicrobial susceptibility testing was performed directly from positive bottles by the Alfred AST® system (Alifax, Padova, Italy). The broth microdilution method (MicroScan, Beckman Coulter, CA, USA) performed to the isolates was considered the standard for comparison. We evaluated 115 significant episodes of bacteremia produced by 51 Gram-negative Enterobacterales, 8 Pseudomonas spp., 2 non-fermenting Gram-negative rods, 7 Staphylococcus aureus, 23 coagulase-negative Staphylococcus, 12 Enterococcus spp., and 12 Streptococcus spp. We performed 828 susceptibility determinations with a categorical agreement with the standard method of 97.1%. Only 24 errors (2.9%) were detected. It should be pointed out that for staphylococci and glycopeptides the correlation was only 87% and for non-fermenting Gram-negative rods and piperacillin/tazobactam was only 88.9%. Time to get antibiogram results by Alfred AST® system was 5 versus 48 h for the standard microdilution method from the isolated colonies. The Alfred AST® system is a useful and rapid method to obtain antimicrobial susceptibility results within the same work shift after blood culture positivity.

Positron emission tomography: a false negative result in cystic encephalic mestastases from a small cell bronchial carcinoma.

Lung cancer represents one of the most common malignant diseases. Many investigations are used in the staging study including, most recently, PET. We present a case of cystic cerebral metastases (with no oedema) from a small cell carcinoma which were not detected by PET.