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.

Validation of an expanded, in-house library and an optimized preparation method for the identification of fungal isolates using MALDI-TOF mass spectrometry.

The goal of this study was to validate an optimized sample preparation method for filamentous fungal isolates coupled with the use of an in-house library for the identification of moulds using Matrix Assisted Laser Desorption/Ionization-Time of Flight Mass Spectrometry (MALDI-TOF MS) in a multicenter context. For that purpose, three Spanish microbiology laboratories participated in the identification of 97 fungal isolates using MALDI-TOF MS coupled with the Filamentous Fungi library 3.0 (Bruker Daltonics) and an in-house library containing 314 unique fungal references. The isolates analyzed belonged to 25 species from the genus Aspergillus, Fusarium, Scedosporium/Lomentospora, the Mucorales order and the Dermatophytes group. MALDI-TOF MS identification was carried out from hyphae resuspended in water and ethanol. After a high-speed centrifugation step, the supernatant was discarded and the pellet submitted to a standard protein extraction step. The protein extract was analyzed with the MBT Smart MALDI Biotyper system (Bruker Daltonics). The rate of accurate, species-level identification obtained ranged between 84.5% and 94.8% and the score values were 1.8 for 72.2-94.9% of the cases. Two laboratories failed to identify only one isolate of Syncephalastrum sp. and Trichophyton rubrum, respectively and three isolates could not be identified in the third center (F. proliferatum, n = 1; T.interdigitale, n = 2). In conclusion, the availability of an effective sample preparation method and an extended database allowed high rates of correct identification of fungal species using MALDI-TOF MS. Some species, such as Trichophyton spp. are still difficult to identify. Although further improvements are still required, the developed methodology allowed the reliable identification of most fungal species.

MALDI-TOF mass spectrometry has been improved as a diagnostic method for the rapid and reliable identification of filamentous fungi by means of the creation of an expanded database containing reference protein spectra of the most clinically impacting fungal species.

Identification of Mycobacterium abscessus Subspecies by MALDI-TOF Mass Spectrometry and Machine Learning.

Mycobacterium abscessus is one of the most common and pathogenic nontuberculous mycobacteria (NTM) isolated in clinical laboratories. It consists of three subspecies: M. abscessus subsp. abscessus, M. abscessus subsp. bolletii, and M. abscessus subsp. massiliense. Due to their different antibiotic susceptibility pattern, a rapid and accurate identification method is necessary for their differentiation. Although matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) has proven useful for NTM identification, the differentiation of M. abscessus subspecies is challenging. In this study, a collection of 325 clinical isolates of M. abscessus was used for MALDI-TOF MS analysis and for the development of machine learning predictive models based on MALDI-TOF MS protein spectra. Overall, using a random forest model with several confidence criteria (samples by triplicate and similarity values >60%), a total of 96.5% of isolates were correctly identified at the subspecies level. Moreover, an improved model with Spanish isolates was able to identify 88.9% of strains collected in other countries. In addition, differences in culture media, colony morphology, and geographic origin of the strains were evaluated, showing that the latter had an impact on the protein spectra. Finally, after studying all protein peaks previously reported for this species, two novel peaks with potential for subspecies differentiation were found. Therefore, machine learning methodology has proven to be a promising approach for rapid and accurate identification of subspecies of M. abscessus using MALDI-TOF MS.

Quality of MALDI-TOF mass spectra in routine diagnostics: results from an international external quality assessment including 36 laboratories from 12 countries using 47 challenging bacterial strains.

OBJECTIVES: Matrix assisted laser desorption ionization-time of flight (MALDI-TOF) mass spectrometry (MS) is a widely used method for bacterial species identification. Incomplete databases and mass spectral quality (MSQ) still represent major challenges. Important proxies for MSQ are the number of detected marker masses, reproducibility, and measurement precision. We aimed to assess MSQs across diagnostic laboratories and the potential of simple workflow adaptations to improve it. METHODS: For baseline MSQ assessment, 47 diverse bacterial strains, which are challenging to identify by MALDI-TOF MS, were routinely measured in 36 laboratories from 12 countries, and well-defined MSQ features were used. After an intervention consisting of detailed reported feedback and instructions on how to acquire MALDI-TOF mass spectra, measurements were repeated and MSQs were compared. RESULTS: At baseline, we observed heterogeneous MSQ between the devices, considering the median number of marker masses detected (range = [2-25]), reproducibility between technical replicates (range = [55%-86%]), and measurement error (range = [147 parts per million (ppm)-588 ppm]). As a general trend, the spectral quality was improved after the intervention for devices, which yielded low MSQs in the baseline assessment as follows: for four out of five devices with a high measurement error, the measurement precision was improved (p-values <0.001, paired Wilcoxon test); for six out of ten devices, which detected a low number of marker masses, the number of detected marker masses increased (p-values <0.001, paired Wilcoxon test). DISCUSSION: We have identified simple workflow adaptations, which, to some extent, improve MSQ of poorly performing devices and should be considered by laboratories yielding a low MSQ. Improving MALDI-TOF MSQ in routine diagnostics is essential for increasing the resolution of bacterial identification by MALDI-TOF MS, which is dependent on the reproducible detection of marker masses. The heterogeneity identified in this external quality assessment (EQA) requires further study.

Identification of Nocardia and non-tuberculous Mycobacterium species by MALDI-TOF MS using the VITEK MS coupled to IVD and RUO databases.

Identification of Nocardia and Mycobacterium species by matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) is still a challenging task that requires both suitable protein extraction procedures and extensive databases. This study aimed to evaluate the VITEK MS Plus system coupled with updated RUO (v4.17) and IVD (v3.2) databases for the identification of Nocardia spp. and Mycobacterium spp. clinical isolates. Sample preparation was carried out using the VITEK MS Mycobacterium/Nocardia kit for protein extraction. From 90 Nocardia spp. isolates analysed, 86 (95.6%) were correctly identified at species or complex level using IVD and 78 (86.7%) using RUO. Only two strains were misidentified as other species pertaining to the same complex. Among the 106 non-tuberculous Mycobacterium clinical isolates tested from a liquid culture medium, VITEK MS identified correctly at species or complex level 96 (90.6%) isolates in the IVD mode and 89 (84.0%) isolates in the RUO mode. No misidentifications were detected. Although the IVD mode was unable to differentiate members of the M. fortuitum complex, the RUO mode correctly discriminated M. peregrinum and M. septicum. The robustness and accuracy showed by this system allow its implementation for routine identification of these microorganisms in clinical laboratories.

Outbreak of Yersinia pseudotuberculosis in capybaras (Hydrochoerus hydrochaeris) kept in captivity.

On January 2020, an outbreak of acute mortality was detected in the capybara (Hydrochoerus hydrochaeris) population kept in the Cordoba Zoo Conservation Center (CZCC) in Spain. Morbidity and mortality rates were 71%, and the fatality rate was 100%. Macroscopic examination revealed multifocal nodular lesions with fibrinonecrotic exudate in lungs and mesenteric lymph nodes. Microscopic lesions were characterized as severe acute fibrinopurulent bronchopneumonia and generalized vascular changes. Cultures and biochemical analyses yielded Yersinia pseudotuberculosis (YPT). This species was confirmed by both PCR and MALDI-TOF. This report describes the first outbreak of fatal YPT infection in zoo animals in Spain and confirms that capybaras are highly susceptible to this pathogen, which could be of animal health, conservation, and public health concern. Future studies are warranted to determine potential sources of YTP infection in zoos to prevent future cases in susceptible species, including humans.

Evaluation of the Vitek Ms system for the identification of filamentous fungi.

The implementation of matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) for the identification of fungal isolates remains challenging and has been limited to experienced laboratories in sample preparation and in-house libraries construction. However, the development of commercial kits for standardized fungal sample preparation and updated reference libraries can fill this gap. This study aimed to evaluate the performance of the commercial VITEK MS Mould Kit (bioMérieux, Marcy l'Etoile, France) and the VITEK MS system (bioMérieux) for identification using a panel of fungal species of clinical interest. Overall, 200 isolates belonging to 13 genera and 43 fungal species were analyzed with the VITEK MS system equipped with the v3.2 IVD database. Overall, 89.0% of the isolates were correctly identified, 41.5 and 43.5% at species and complex level, respectively. For an additional 4.0% of the identifications, correlation at the genus level was reported. The remaining 21 isolates (10.5%) could not be identified among which 85.0% (18/21) were species not claimed in the database. One Syncephalastrum isolate was misidentified as Rhizopus microsporus complex. Specifically, 100% of the Scedosporium/Lomentospora, 97.1% of the Fusarium, 65.7% of the Mucorales and 86.4% of the Aspergillus isolates were correctly identified at the species and complex level. The methodology described allows for an easy implementation of MALDI-TOF MS for routine identification of fungal species in a fast and reliable manner. Although further improvement in the databases is still required, an important number of fungal species can be correctly identified at the species level using this method. LAY SUMMARY: The use of MALDI-TOF for fungal identification remains a challenge. In this study, using a commercial protein extraction kit and updated database, VITEK MS system was able to identify up to 89.0% of a diverse collection of 200 filamentous fungi representing 43 fungal species.

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.

Multicentre study on the reproducibility of MALDI-TOF MS for nontuberculous mycobacteria identification.

The ability of MALDI-TOF for the identification of nontuberculous mycobacteria (NTM) has improved recently thanks to updated databases and optimized protein extraction procedures. Few multicentre studies on the reproducibility of MALDI-TOF have been performed so far, none on mycobacteria. The aim of this study was to evaluate the reproducibility of MALDI-TOF for the identification of NTM in 15 laboratories in 9 European countries. A total of 98 NTM clinical isolates were grown on Löwenstein-Jensen. Biomass was collected in tubes with water and ethanol, anonymized and sent out to the 15 participating laboratories. Isolates were identified using MALDI Biotyper (Bruker Daltonics). Up to 1330 MALDI-TOF identifications were collected in the study. A score ≥ 1.6 was obtained for 100% of isolates in 5 laboratories (68.2-98.6% in the other). Species-level identification provided by MALDI-TOF was 100% correct in 8 centres and 100% correct to complex-level in 12 laboratories. In most cases, the misidentifications obtained were associated with closely related species. The variability observed for a few isolates could be due to variations in the protein extraction procedure or to MALDI-TOF system status in each centre. In conclusion, MALDI-TOF showed to be a highly reproducible method and suitable for its implementation for NTM identification.

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.

Determination of the ability of matrix-assisted laser desorption ionization time-of-flight mass spectrometry to identify high-biofilm-producing strains.

Background: The traditional method for assessing the capacity of a microorganism to produce biofilm is generally a static in vitro model in a multi-well plate using the crystal violet (CV) binding assay, which takes 96 h. Furthermore, while the method is simple to perform, its reproducibility is poor. Objective: We evaluated whether matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) could make it possible to differentiate between high-and low-biofilm-producing microorganisms on 24-h cultures of Staphylococcus aureus and Candida albicans. Methods: We included 157 strains of S. aureus and 91 strains of C. albicans obtained from the blood cultures of patients with bacteremia/candidemia. We tested biofilm production using the CV binding assay as the gold standard to classify strains as low or high biofilm producers. We then applied MALDI-TOF MS to create a machine learning-based predictive model using 40 strains of S. aureus and C. albicans, each with extreme absorbance values, and validated this approach with the remaining 117 and 51 strains using the random forest algorithm and the support vector machine algorithm, respectively. Results: Overall, 81.2% of the S. aureus strains (95/117) and 74.5% of the C. albicans strains (38/51) used for validation were correctly categorized, respectively, as low and high-biofilm-producing. Conclusion: Classification based on MALDI-TOF MS protein spectra enables us to predict acceptable information about the capacity of 24-h cultures of S. aureus and C. albicans to form biofilm.

Multicenter Evaluation of Rapid BACpro® II for the Accurate Identification of Microorganisms Directly from Blood Cultures Using MALDI-TOF MS.

The identification of microorganisms directly from blood cultures using MALDI-TOF MS has been shown to be the most impacting application of this methodology. In this study, a novel commercial method was evaluated in four clinical microbiology laboratories. Positive blood culture samples (n = 801) were processed using a rapid BACpro® II kit and then compared with the routine gold standard. A subset of monomicrobial BCs (n = 560) were analyzed in parallel with a Sepsityper® Kit (Bruker Daltonics, Bremen, Germany) and compared with the rapid BACpro® II kit. In addition, this kit was also compared with two different in-house methods. Overall, 80.0% of the monomicrobial isolates (609/761; 95% CI 71.5-88.5) were correctly identified by the rapid BACpro® II kit at the species level (92.3% of the Gram negative and 72.4% of the Gram positive bacteria). The comparison with the Sepsityper® Kit showed that the rapid BACpro® II kit generated higher rates of correct species-level identification for all categories (p > 0.0001), except for yeasts identified with score values > 1.7. It also proved superior to the ammonium chloride method (p > 0.0001), but the differential centrifugation method allowed for higher rates of correct identification for Gram negative bacteria (p > 0.1). The percentage of accurate species-level identification of Gram positive bacteria was particularly noteworthy in comparison with other commercial and in-house methods.

Whole-genome sequence-informed MALDI-TOF MS diagnostics reveal importance of Klebsiella oxytoca group in invasive infections: a retrospective clinical study.

BACKGROUND: Klebsiella spp. are opportunistic pathogens which can cause severe infections, are often multi-drug resistant and are a common cause of hospital-acquired infections. Multiple new Klebsiella species have recently been described, yet their clinical impact and antibiotic resistance profiles are largely unknown. We aimed to explore Klebsiella group- and species-specific clinical impact, antimicrobial resistance (AMR) and virulence. METHODS: We analysed whole-genome sequence data of a diverse selection of Klebsiella spp. isolates and identified resistance and virulence factors. Using the genomes of 3594 Klebsiella isolates, we predicted the masses of 56 ribosomal subunit proteins and identified species-specific marker masses. We then re-analysed over 22,000 Matrix-Assisted Laser Desorption Ionization - Time Of Flight (MALDI-TOF) mass spectra routinely acquired at eight healthcare institutions in four countries looking for these species-specific markers. Analyses of clinical and microbiological endpoints from a subset of 957 patients with infections from Klebsiella species were performed using generalized linear mixed-effects models. RESULTS: Our comparative genomic analysis shows group- and species-specific trends in accessory genome composition. With the identified species-specific marker masses, eight Klebsiella species can be distinguished using MALDI-TOF MS. We identified K. pneumoniae (71.2%; n = 12,523), K. quasipneumoniae (3.3%; n = 575), K. variicola (9.8%; n = 1717), "K. quasivariicola" (0.3%; n = 52), K. oxytoca (8.2%; n = 1445), K. michiganensis (4.8%; n = 836), K. grimontii (2.4%; n = 425) and K. huaxensis (0.1%; n = 12). Isolates belonging to the K. oxytoca group, which includes the species K. oxytoca, K. michiganensis and K. grimontii, were less often resistant to 4th-generation cephalosporins than isolates of the K. pneumoniae group, which includes the species K. pneumoniae, K. quasipneumoniae, K. variicola and "K. quasivariicola" (odds ratio = 0.17, p < 0.001, 95% confidence interval [0.09,0.28]). Within the K. pneumoniae group, isolates identified as K. pneumoniae were more often resistant to 4th-generation cephalosporins than K. variicola isolates (odds ratio = 2.61, p = 0.003, 95% confidence interval [1.38,5.06]). K. oxytoca group isolates were found to be more likely associated with invasive infection to primary sterile sites than K. pneumoniae group isolates (odds ratio = 2.39, p = 0.0044, 95% confidence interval [1.05,5.53]). CONCLUSIONS: Currently misdiagnosed Klebsiella spp. can be distinguished using a ribosomal marker-based approach for MALDI-TOF MS. Klebsiella groups and species differed in AMR profiles, and in their association with invasive infection, highlighting the importance for species identification to enable effective treatment options.

Azole-Resistant Aspergillus fumigatus Clinical Isolate Screening in Azole-Containing Agar Plates (EUCAST E.Def 10.1): Low Impact of Plastic Trays Used and Poor Performance in Cryptic Species.

Azole-containing agar is used in routine Aspergillus fumigatus azole resistance screening. We evaluated the impact of the type of plastic used to prepare in-house agar plates on the procedure's performance against A. fumigatus sensu stricto and cryptic species. A. fumigatus sensu stricto (n = 91) and cryptic species (n = 52) were classified as susceptible or resistant (EUCAST E.Def 9.3.2; clinical breakpoints v10). In-house azole-containing agar plates were prepared following EUCAST E.Def 10.1 on three types of multidish plates. We assessed the sensitivity, specificity, and agreement values of the agar plates to screen for azole resistance. Overall, sensitivity and specificity values of the agar screening method were 100% and 93.3%, respectively. The type of tray used did not affect these values. All isolates harboring TR34-L98H substitutions were classified as resistant to itraconazole and voriconazole by the agar method; however, false susceptibility (very major error) to posaconazole was not uncommon and happened in isolates with posaconazole MICs of 0.25 mg/liter. Isolates harboring G54R and TR46-Y121F-T289A substitutions were correctly classified by the agar method as itraconazole/posaconazole resistant and voriconazole resistant, respectively. False resistance (major error) occurred in isolates showing tiny fungal growth. Finally, agreements between both procedures against cryptic species were much lower. Azole-containing agar plates are a convenient and reliable tool to screen for resistance in A. fumigatus sensu stricto; the type of plastic tray used minimally affects the method. On the contrary, the performance against cryptic species is rather poor.

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.

Identifying Anaerobic Bacteria Using MALDI-TOF Mass Spectrometry: A Four-Year Experience.

Because of the special culture requirements of anaerobic bacteria, their low growth-rate and the difficulties to isolate them, MALDI-TOF MS has become a reliable identification tool for these microorganisms due to the little amount of bacteria required and the accuracy of MALDI-TOF MS identifications. In this study, the performance of MALDI-TOF MS for the identification of anaerobic isolates during a 4-year period is described. Biomass from colonies grown on Brucella agar was directly smeared onto the MALDI-TOF target plate and submitted to on-plate protein extraction with 1µl of 100% formic acid. Sequencing analysis of the 16S rRNA gene was used as a reference method for the identification of isolates unreliably or not identified by MALDI-TOF MS. Overall, 95.7% of the isolates were identified to the species level using the updated V6 database vs 93.8% with previous databases lacking some anaerobic species; 68.5% of the total were reliably identified with high-confidence score values (≥2.0) and 95.0% with low-confidence values (score value ≥1.7). Besides, no differences between Gram-positive and Gram-negative isolates were detected beyond a slight decrease of correct species assignment for gram positive cocci (94.1% vs 95.7% globally). MALDI-TOF MS has demonstrated its usefulness for the identification of anaerobes, with high correlation with phenotypic and conventional methods. Over the study period, only 2.1% of the isolates could not be reliably identified and required molecular methods for a final identification. Therefore, MALDI-TOF MS provided reliable identification of anaerobic isolates, allowing clinicians to streamline the most appropriate antibiotic therapy and manage patients accordingly.

MALDI-TOF mass spectrometry in the 21st century clinical microbiology laboratory / La espectrometría de masas MALDI-TOF en el laboratorio de Microbiología Clínica del siglo XXI

MALDI-TOF mass spectrometry has become a reference method for the routine identification of bacterial isolates in clinical microbiology laboratories around the world. Its high specificity, user-friendliness and cost-efficiency, together with its ability to provide reliable results in less than 5min have favoured its implementation and further development. The amount of microbial species that can be identified by MALDI-TOF routinely has increased in the last few years and now it is possible to reliably identify non-tuberculous mycobacteria or closely-related species of Nocardia spp. Yeasts, both belonging to Candida and non-Candida genera can also be identified by MALDI-TOF, as well as filamentous fungi. In the latter case, both sample preparation methods and the available databases have been important factors in achieving accurate identifications at the species level. The expertise acquired over time has allowed researchers to identify microorganisms directly from clinical samples, facilitating improved management of infected patients. This expertise has also been applied to the development of a MALDI-TOF-based methodology for the detection of different antimicrobial resistance mechanisms. Therefore, future applications such as bacterial strain typing, or the detection of virulence markers seems feasible to perform with this technology. Furthermore, other emerging mass spectrometry and spectroscopy technologies may assist MALDI-TOF in the near future to carry out important tasks that nowadays are performed by time-consuming and labour-intensive methods.(AU)

La espectrometría de masas MALDI-TOF se ha convertido en un método de referencia para la identificación de aislados bacterianos en la rutina de los laboratorios de microbiología clínica de todo el mundo. Su elevada especificidad, facilidad de aplicación y coste-eficacia, unido a su capacidad de facilitar resultados fiables en menos de 5min, han favorecido su implantación y desarrollo. La cantidad de especies microbianas que se pueden identificar mediante MALDI-TOF de forma rutinaria se ha ido incrementando en los últimos años, y actualmente es posible identificar de forma fiable micobacterias no tuberculosas o especies estrechamente relacionadas del género Nocardia. También se pueden identificar especies de levaduras —del género Candida y de otros géneros— y de hongos filamentosos. En este último caso, tanto los métodos de preparación de muestras como las bases de datos disponibles han sido factores importantes para conseguir identificaciones precisas hasta el nivel de especie. La experiencia adquirida durante todo este tiempo ha permitido a los investigadores identificar microorganismos directamente desde muestras clínicas, lo que facilita el manejo optimizado de pacientes infectados. El conocimiento adquirido se ha aplicado también a desarrollar una metodología basada en MALDI-TOF para detectar diferentes mecanismos de resistencia a antimicrobianos. Este hecho permite creer que en el futuro se podría aplicar esta tecnología para realizar tipado bacteriano o detección de marcadores de virulencia. Además, otras tecnologías emergentes basadas en la espectrometría de masas y espectroscopía podrían, en un futuro cercano, asistir a MALDI-TOF para llevar a cabo tareas importantes que en la actualidad requieren métodos lentos y trabajosos.(AU)