Bacteroides fragilis: A whole MALDI-based workflow from identification to confirmation of carbapenemase production for routine laboratories.

Bacteroides fragilis is a frequent anaerobic pathogen and can cause severe infections. Resistance to carbapenems, associated with the cfiA gene encoded carbapenemase, represents an emerging problem. To date, no rapid methods are available to detect and confirm this resistance mechanism in routine laboratories, and the missed recognition of carbapenemase-producing strains can lead to therapeutic failures. In this study we have investigated a whole MALDI-TOF MS-based workflow to detect carbapenemase-producing B. fragilis, using the largest set of B. fragilis clinical isolates ever tested. The presence of the cfiA gene was predicted by MALDI subtyping into Division I (cfiA-negative) or Division II (cfiA-positive). The carbapenemase activity in cfiA-positive strains was confirmed by a MALDI-TOF MS imipenem hydrolysis assay (MBT STAR-Carba, Bruker Daltonik, Germany), that was further used for a characterization of the strains in terms of cfiA expression level. The validity of MALDI subtyping was verified by PCR for the cfiA gene, while results of MALDI hydrolysis assay were compared to conventional methods for susceptibility testing and carbapenemase detection (Carba-NP and disk diffusion synergy test). A genetic analysis of the IS elements upstream cfiA was performed, for the evaluations regarding the expression level of cfiA. A total of 5300 B. fragilis isolates (406 from Bologna, Italy, and 4894 from Dortmund, Germany) were identified and subtyped by MALDI-TOF MS, yielding 41/406 (10.1%) strains from Bologna and 374/4894 (7.6%) from Dortmund to belong to Division II. Molecular verification by PCR for the cfiA gene on a subset of strains confirmed the MALDI typing results in all cases (sensitivity and specificity of 100%). MBT STAR-Carba assay detected the carbapenemase activity in all of the 70 cfiA-carrying strains tested. Moreover, it allowed distinct separation into slow (59) and fast (11) imipenem hydrolyzers corresponding to cfiA expression levels as well as to low or high MICs for carbapenems, respectively. Among the 11 cfiA-positive strains with high carbapenem MIC, only 7 harboured IS elements upstream the carbapenemase gene showing low expression level as well. The MALDI-TOF MS-based workflow was superior to the currently available phenotypic methods for carbapenemase detection as it proved to be more sensitive and accurate than Carba NP and disk diffusion synergy test. The whole MALDI-TOF MS-based workflow allows an accurate identification of B. fragilis clinical strains with reliable classification into Division I/II, and confirmation of the carbapenemase-production, together with estimation of carbapenemase activity, within less than 2 h. This may be of particular interest for early therapeutical decisions in life-threatening infections.

Microbiological profile and infection potential of different cryopreserved skull flaps after decompressive hemicraniectomy. Is cryopreservation at - 80 ℃ better?

OBJECTIVE: Patterns of cryopreservation of explanted skull bone flaps have long been a matter of debate, in particular the appropriate temperature of storage. To the best of our knowledge no study to date has compared the microbiological profile and the infection potential of skull bone flaps cryostored at the same institution at disparate degrees for neurosurgical purposes. In the context of our clinical trial DRKS00023283, we performed a bacterial culture of explanted skull bone flaps, which were cryopreserved lege artis at a temperature of either - 23 °C or - 80 °C after a decompressive hemicraniectomy. In a further step, we contaminated the bone fragments in a s uspension with specific pathogens (S. aureus, S. epidermidis and C. acnes, Colony forming unit CFU 103/ml) over 24 h and conducted a second culture. RESULTS: A total of 17 cryopreserved skull flaps (8: - 23 °C; 9: - 80 °C) explanted during decompressive hemicraniectomies performed between 2019 and 2020 as well as 2 computer-aided-designed skulls (1 vancomycin-soaked) were analyzed. Median duration of cryopreservation was 10.5 months (2-17 months). No microorganisms were detected at the normal bacterial culture. After active contamination of our skull flaps, all samples showed similar bacterial growth of above-mentioned pathogens; thus, our study did not reveal an influence of the storage temperature upon infectious dynamic of the skulls.

Machine learning-based typing of Salmonella enterica O-serogroups by the Fourier-Transform Infrared (FTIR) Spectroscopy-based IR Biotyper system.

BACKGROUND: Salmonella enterica is among the major burdens for public health at global level. Typing of salmonellae below the species level is fundamental for different purposes, but traditional methods are expensive, technically demanding, and time-consuming, and therefore limited to reference centers. Fourier transform infrared (FTIR) spectroscopy is an alternative method for bacterial typing, successfully applied for classification at different infra-species levels. AIM: This study aimed to address the challenge of subtyping Salmonella enterica at O-serogroup level by using FTIR spectroscopy. We applied machine learning to develop a novel approach for S. enterica typing, using the FTIR-based IR Biotyper® system (IRBT; Bruker Daltonics GmbH & Co. KG, Germany). We investigated a multicentric collection of isolates, and we compared the novel approach with classical serotyping-based and molecular methods. METHODS: A total of 958 well characterized Salmonella isolates (25 serogroups, 138 serovars), collected in 11 different centers (in Europe and Japan), from clinical, environmental and food samples were included in this study and analyzed by IRBT. Infrared absorption spectra were acquired from water-ethanol bacterial suspensions, from culture isolates grown on seven different agar media. In the first part of the study, the discriminatory potential of the IRBT system was evaluated by comparison with reference typing method/s. In the second part of the study, the artificial intelligence capabilities of the IRBT software were applied to develop a classifier for Salmonella isolates at serogroup level. Different machine learning algorithms were investigated (artificial neural networks and support vector machine). A subset of 88 pre-characterized isolates (corresponding to 25 serogroups and 53 serovars) were included in the training set. The remaining 870 samples were used as validation set. The classifiers were evaluated in terms of accuracy, error rate and failed classification rate. RESULTS: The classifier that provided the highest accuracy in the cross-validation was selected to be tested with four external testing sets. Considering all the testing sites, accuracy ranged from 97.0% to 99.2% for non-selective media, and from 94.7% to 96.4% for selective media. CONCLUSIONS: The IRBT system proved to be a very promising, user-friendly, and cost-effective tool for Salmonella typing at serogroup level. The application of machine learning algorithms proved to enable a novel approach for typing, which relies on automated analysis and result interpretation, and it is therefore free of potential human biases. The system demonstrated a high robustness and adaptability to routine workflows, without the need of highly trained personnel, and proving to be suitable to be applied with isolates grown on different agar media, both selective and unselective. Further tests with currently circulating clinical, food and environmental isolates would be necessary before implementing it as a potentially stand-alone standard method for routine use.

How to: identify non-tuberculous Mycobacterium species using MALDI-TOF mass spectrometry.

BACKGROUND: The implementation of MALDI-TOF MS for microorganism identification has changed the routine of the microbiology laboratories as we knew it. Most microorganisms can now be reliably identified within minutes using this inexpensive, user-friendly methodology. However, its application in the identification of mycobacteria isolates has been hampered by the structure of their cell wall. Improvements in the sample processing method and in the available database have proved key factors for the rapid and reliable identification of non-tuberculous mycobacteria isolates using MALDI-TOF MS. AIMS: The main objective is to provide information about the proceedings for the identification of non-tuberculous isolates using MALDI-TOF MS and to review different sample processing methods, available databases, and the interpretation of the results. SOURCES: Results from relevant studies on the use of the available MALDI-TOF MS instruments, the implementation of innovative sample processing methods, or the implementation of improved databases are discussed. CONTENT: Insight about the methodology required for reliable identification of non-tuberculous mycobacteria and its implementation in the microbiology laboratory routine is provided. IMPLICATIONS: Microbiology laboratories where MALDI-TOF MS is available can benefit from its capacity to identify most clinically interesting non-tuberculous mycobacteria in a rapid, reliable, and inexpensive manner.