Rapid and robust MALDI-TOF MS techniques for microbial identification: a brief overview of their diverse applications

Typing of clinical and reference strains of Saccharomyces cerevisiae using pulsed-field gel electrophoresis and MALDI-TOF MS

In recent years matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) has emerged as a rapid and reliable tool for microbial identification and diagnosis. However, its use for molecular typing of S. cerevisiae has been investigated in a limited number of studies, mainly based on brewing strains. The purpose of the study was to compare the results of the gold standard pulsed-field gel electrophoresis (PFGE) typing with MALDI-TOF MS on a subset of S. cerevisiae clinical and reference strains. The study comprised 50 clinical isolates, collected from single patients hospitalized in the Central Clinical Hospital of the Medical University of in Warsaw between 2014 and 2016. Furthermore eight reference strains i.e. three probiotic, four baker and one winery strains, were included. Strain typing was performed using PFGE and MALDI-TOF MS. PFGE split the study sample into six clusters and two unique profiles. Whereas MALDI-TOF MS typing produced five clusters. Overall, the results of PFGE and MALDI-TOF MS were congruent for all (49/50; 97%) but one clinical isolates. In both analyses, three probiotic strains, unlike baker's and winery strains, clustered only with clinical isolates. Although PFGE had a higher resolution capacity than MALDI-TOF MS, both methods allowed for a clear discrimination between clinically relevant (clinical & probiotic) and irrelevant (baker's and winery) strains. This is the first time that MALDI-TOF MS has proven useful in the epidemiological studies of S. cerevisiae.

Accelerating antimicrobial stewardship: An AI-CDSS approach to combating multidrug-resistant pathogens in the era of increasing resistance

OBJECTIVES

The World Health Organization has identified Klebsiella pneumoniae (KP) and Pseudomonas aeruginosa (PA) as significant public health threats owing to high antibiotic resistance. Traditional antibiotic susceptibility testing (AST) methods, crucial for determining the most suitable treatment regimen, typically require approximately 48-96 h (2-4 days) to yield results, including bacterial culture, rapid identification via matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS), and subsequent AST, which is too long for urgent clinical decisions. Here, we developed an artificial intelligence-clinical decision support system (AI-CDSS) utilizing machine learning to analyze MALDI-TOF MS data for antibiotic resistance prediction for these pathogens.

METHODS

From 165,299 bacterial specimens, we selected 12,967 KP and 9,429 PA cases. Predictive models, the core of the AI-CDSS, were built using advanced machine learning algorithms, such as the random forest classifier (RFC) and light gradient boosting machine (LGBM), with GridSearchCV and 5-fold cross-validation optimization and robustness.

RESULTS

Both the RFC and LGBM models demonstrated strong predictive performance, with area under the curve values predominantly ranging from 0.91 to 0.95. Sensitivity, specificity, positive predictive value, and negative predictive value primarily exceeded 80 %, ensuring reliable detection of resistance patterns. The AI-CDSS was designed to provide real-time, clinically actionable recommendations, enabling targeted antibiotic selection up to one day faster than conventional AST.

CONCLUSIONS

Integrating MALDI-TOF MS with machine learning in AI-CDSS significantly enhanced clinical decision-making, representing a major advancement in the rapid management of infectious diseases and antimicrobial stewardship.

Salmonella spp. detection in fresh and freeze-dried frog meat: a comparison of methods

This study examined the presence of Salmonella spp. in fresh frog meat and freeze-dried seasoned frog meat stored for up to 90 days at room temperature. The samples were analyzed in triplicate using the conventional official method, by polymerase chain reaction (PCR) and mass spectrometry technique (MALDI -TOF) - for a comparison of the results obtained by the three tested methods. Mass spectrometry analyses confirmed the presence of Salmonella spp. in 100% of the fresh frog meat samples. In the analysis by the conventional method, the percentages of detection were 67% and 100% in samples B2 and B3, whereas the PCR method indicated 100% and 67% presence of the bacteria in the respective samples. In the analyses of freeze-dried none of the three methods detected the presence of Salmonella spp. The different analysis methods tested in this study were efficient in determining the presence or absence of Salmonella spp. in the samples, and the comparison between methods revealed a high percentage of compatibility of results. Adoption of efficient detection methods, such as PCR and MALDI-TOF, is essential, not only for public health, but also for compliance with Brazilian regulations, ensuring that food products are free from Salmonella spp. contamination and safe for consumption.

Thermo-responsive 3D nanostructures for enhanced performance in food-poisoning bacterial analysis

The growing risk of bacterial food poisoning due to global warming has necessitated the development of methods for accurate detection of food-poisoning bacteria. Despite extensive efforts to develop enhanced bacterial-capture methods, challenges associated with the release of the captured bacteria have limited the sensitivity of bacterial detection. In this study, thermo-responsive intelligent 3D nanostructures to improve food-poisoning bacterial analysis performance were fabricated by introducing a thermo-responsive polymer onto an urchin-like 3D nanopillar substrate (URCHANO). A co-polymer of methacryloyl glycinamide and benzyl acrylate (MNAGA-Bn 5%) was introduced as a thermo-responsive co-polymer onto URCHANO using an electron-transfer atom-transfer radical-polymerization method to fabricate Thermo-URCHANO. A temperature-related analysis of the surface properties of Thermo-URCHANO revealed a hydrophobic-to-hydrophilic transition at 37 °C, which facilitated the release of bacteria captured within the nanostructure. In a one-pot analysis to capture and analyze various food-poisoning bacteria in kitchenware (gloves and aprons) and food items (eggs and sausages), mimicking real-life environments, specimens collected using Thermo-URCHANO showed lower Ct values than those collected with uncoated URCHANO, indicating greater bacterial detection. This method could effectively release captured bacteria through temperature changes, improving extraction efficiency during swab collection. While Thermo-URCHANO needs further optimization, it is expected to enhance bacterial analysis performance and sensitivity.

Comparative evaluation of BacT/ALERT VIRTUO and BACTEC FX400 blood culture systems for the detection of bloodstream infections

Bloodstream infections (BSI) pose significant threats to patient health, necessitating timely and accurate diagnostics to reduce mortality and morbidity. This study aimed to evaluate the clinical performance of the BacT/ALERT VIRTUO blood culture system with FANPlus bottles compared to the BACTEC FX400 system in detecting bloodstream pathogens. A total of 1,772 blood specimens were collected from various hospital wards. Specimen selection criteria were based on clinical suspicion of bloodstream infections, ensuring the inclusion of relevant and representative patient samples. These blood samples, collected from the same suspected sepsis patients, were cultured in parallel using both the BacT/ALERT VIRTUO and BACTEC FX400 systems. The diagnostic efficiency of both systems, including detection rates, time to detection (TTD), and sensitivity across different bacterial species, was assessed. In various application scenarios, the VIRTUO system demonstrates a higher positive detection rate, whether in the intensive care unit (ICU) (8.5% vs 6.4%, P = 0.028) or in general wards. Additionally, for different types of bacteria, the TVIRTUO system exhibits superior detection rates for anaerobic bacteria (5.9% vs 3.2%, P < 0.001) and aerobic bacteria (9.1% vs 7.2%, P = 0.043). Furthermore, it boasts a shorter median TTD of 14 hours compared to 16 hours, and a higher sensitivity for Gram-positive bacteria (2.8% vs 1.6%, P < 0.001). These findings emphasize VIRTUO's effectiveness in enhancing diagnostic accuracy, achieving faster time to detection, and expanding the spectrum of detected organisms, thereby facilitating the quicker initiation of appropriate therapies, supporting precise clinical decision-making, and ultimately improving patient outcomes.IMPORTANCEOur study conducted a critical evaluation of advanced blood culture technologies for managing bloodstream infections (BSI). A distinctive strength of our research is the large sample size and the concurrent testing of the same patients with two systems, a methodology rarely achieved in other studies. BSIs present severe health threats, necessitating prompt and accurate diagnostics to mitigate morbidity and mortality. The BacT/ALERT VIRTUO system, in comparison to the BACTEC FX400 system, demonstrated superior detection capabilities, emphasizing the critical role of advanced diagnostics in clinical settings.

Investigate the relationship between Bacillus coagulans and its inhibition of chemotherapy-induced lung cancer resistance

Lung cancer is a leading cause of death globally, with lung adenocarcinoma being the most common subtype. Despite advancements in targeted therapy, drug resistance remains a major challenge. This study investigated the impact of Bacillus coagulans on drug resistance in lung adenocarcinoma cells. The cells were pretreated with B. coagulans culture filtrate (BCCF), and functional assays were performed, including cell proliferation, cell cycle, apoptosis, and immunofluorescence staining. Results showed that BCCF induced cell cycle arrest at the S phase, reducing cell proliferation and suppressing drug resistance marker P-glycoprotein expression in BCCF-treated resistant cells rather than BCCF-treated control cells. Moreover, drug-resistant cells exhibited the ability for epithelial-mesenchymal transition, which could contribute to their necrosis through the iron-mediated cell death pathway upon BCCF treatment. Proteomic analysis identified downregulation of DNA mismatch repair protein PMS2 after BCCF treatment. These findings suggest that B. coagulans may modulate the DNA repair pathway, influencing drug resistance in lung adenocarcinoma cells. In conclusion, this study highlights the potential impact of B. coagulans on drug-resistant lung adenocarcinoma cells. Further investigation and understanding of the regulatory mechanisms by which B. coagulans modulates drug resistance in lung adenocarcinoma can aid in the development of more effective treatment strategies to improve the prognosis of lung cancer patients.

Pioneering Klebsiella Pneumoniae Antibiotic Resistance Prediction With Artificial Intelligence-Clinical Decision Support System-Enhanced Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry: Retrospective Study

BACKGROUND

The rising prevalence and swift spread of multidrug-resistant gram-negative bacteria (MDR-GNB), especially Klebsiella pneumoniae (KP), present a critical global health threat highlighted by the World Health Organization, with mortality rates soaring approximately 50% with inappropriate antimicrobial treatment.

OBJECTIVE

This study aims to advance a novel strategy to develop an artificial intelligence-clinical decision support system (AI-CDSS) that combines machine learning (ML) with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS), aiming to significantly improve the accuracy and speed of diagnosing antibiotic resistance, directly addressing the grave health risks posed by the widespread dissemination of pan drug-resistant gram-negative bacteria across numerous countries.

METHODS

A comprehensive dataset comprising 165,299 bacterial specimens and 11,996 KP isolates was meticulously analyzed using MALDI-TOF MS technology. Advanced ML algorithms were harnessed to sculpt predictive models that ascertain resistance to quintessential antibiotics, particularly levofloxacin and ciprofloxacin, by using the amassed spectral data.

RESULTS

Our ML models revealed remarkable proficiency in forecasting antibiotic resistance, with the random forest classifier emerging as particularly effective in predicting resistance to both levofloxacin and ciprofloxacin, achieving the highest area under the curve of 0.95. Performance metrics across different models, including accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and F1-score, were detailed, underlining the potential of these algorithms in aiding the development of precision treatment strategies.

CONCLUSIONS

This investigation highlights the synergy between MALDI-TOF MS and ML as a beacon of hope against the escalating threat of antibiotic resistance. The advent of AI-CDSS heralds a new era in clinical diagnostics, promising a future in which rapid and accurate resistance prediction becomes a cornerstone in combating infectious diseases. Through this innovative approach, we answered the challenge posed by KP and other multidrug-resistant pathogens, marking a significant milestone in our journey toward global health security.

Rapid bacterial identification through volatile organic compound analysis and deep learning

BACKGROUND

The increasing antimicrobial resistance caused by the improper use of antibiotics poses a significant challenge to humanity. Rapid and accurate identification of microbial species in clinical settings is crucial for precise medication and reducing the development of antimicrobial resistance. This study aimed to explore a method for automatic identification of bacteria using Volatile Organic Compounds (VOCs) analysis and deep learning algorithms.

RESULTS

AlexNet, where augmentation is applied, produces the best results. The average accuracy rate for single bacterial culture classification reached 99.24% using cross-validation, and the accuracy rates for identifying the three bacteria in randomly mixed cultures were SA:98.6%, EC:98.58% and PA:98.99%, respectively.

CONCLUSION

This work provides a new approach to quickly identify bacterial microorganisms. Using this method can automatically identify bacteria in GC-IMS detection results, helping clinical doctors quickly detect bacterial species, accurately prescribe medication, thereby controlling epidemics, and minimizing the negative impact of bacterial resistance on society.

Artificial intelligence-clinical decision support system for enhanced infectious disease management: Accelerating ceftazidime-avibactam resistance detection in Klebsiella pneumoniae

BACKGROUND

Effective and rapid diagnostic strategies are required to manage antibiotic resistance in Klebsiella pneumonia (KP). This study aimed to design an artificial intelligence-clinical decision support system (AI-CDSS) using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) and machine learning for the rapid detection of ceftazidime-avibactam (CZA) resistance in KP to improve clinical decision-making processes.

METHODS

Out of 107,721 bacterial samples, 675 specimens of KP with suspected multi-drug resistance were selected. These specimens were collected from a tertiary hospital and four secondary hospitals between 2022 and 2023 to evaluate CZA resistance. We used MALDI-TOF MS and machine learning to develop an AI-CDSS with enhanced speed of resistance detection.

RESULTS

Machine learning models, especially light gradient boosting machines (LGBM), exhibited an area under the curve (AUC) of 0.95, indicating high accuracy. The predictive models formed the core of our newly developed AI-CDSS, enabling clinical decisions quicker than traditional methods using culture and antibiotic susceptibility testing by a day.

CONCLUSIONS

The study confirms that MALDI-TOF MS, integrated with machine learning, can swiftly detect CZA resistance. Incorporating this insight into an AI-CDSS could transform clinical workflows, giving healthcare professionals immediate, crucial insights for shaping treatment plans. This approach promises to be a template for future anti-resistance strategies, emphasizing the vital importance of advanced diagnostics in enhancing public health outcomes.

Innovative strategies against superbugs: Developing an AI-CDSS for precise Stenotrophomonas maltophilia treatment

OBJECTIVES

The World Health Organization named Stenotrophomonas maltophilia (SM) a critical multi-drug resistant threat, necessitating rapid diagnostic strategies. Traditional culturing methods require up to 96 h, including 72 h for bacterial growth, identification with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) through protein profile analysis, and 24 h for antibiotic susceptibility testing. In this study, we aimed at developing an artificial intelligence-clinical decision support system (AI-CDSS) by integrating MALDI-TOF MS and machine learning to quickly identify levofloxacin and trimethoprim/sulfamethoxazole resistance in SM, optimizing treatment decisions.

METHODS

We selected 8,662 SM from 165,299 MALDI-TOF MS-analysed bacterial specimens, collected from a major medical centre and four secondary hospitals. We exported mass-to-charge values and intensity spectral profiles from MALDI-TOF MS .mzML files to predict antibiotic susceptibility testing results, obtained with the VITEK-2 system using machine learning algorithms. We optimized the models with GridSearchCV and 5-fold cross-validation.

RESULTS

We identified distinct spectral differences between resistant and susceptible SM strains, demonstrating crucial resistance features. The machine learning models, including random forest, light-gradient boosting machine, and XGBoost, exhibited high accuracy. We established an AI-CDSS to offer healthcare professionals swift, data-driven advice on antibiotic use.

CONCLUSIONS

MALDI-TOF MS and machine learning integration into an AI-CDSS significantly improved rapid SM resistance detection. This system reduced the identification time of resistant strains from 24 h to minutes after MALDI-TOF MS identification, providing timely and data-driven guidance. Combining MALDI-TOF MS with machine learning could enhance clinical decision-making and improve SM infection treatment outcomes.

Artificial Intelligence-Clinical Decision Support System in Infectious Disease Control: Combatting Multidrug-Resistant Klebsiella pneumoniae with Machine Learning

Purpose

The World Health Organization has identified Klebsiella pneumoniae (KP) as a significant threat to global public health. The rising threat of carbapenem-resistant Klebsiella pneumoniae (CRKP) leads to prolonged hospital stays and higher medical costs, necessitating faster diagnostic methods. Traditional antibiotic susceptibility testing (AST) methods demand at least 4 days, requiring 3 days on average for culturing and isolating the bacteria and identifying the species using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS), plus an extra day for interpreting AST results. This lengthy process makes traditional methods too slow for urgent clinical situations requiring rapid decision-making, potentially hindering prompt treatment decisions, especially for fast-spreading infections such as those caused by CRKP. This research leverages a cutting-edge diagnostic method that utilizes an artificial intelligence-clinical decision support system (AI-CDSS). It incorporates machine learning algorithms for the swift and precise detection of carbapenem-resistant and colistin-resistant strains.

Patients and Methods

We selected 4307 KP samples out of a total of 52,827 bacterial samples due to concerns about multi-drug resistance using MALDI-TOF MS and Vitek-2 systems for AST. It involved thorough data preprocessing, feature extraction, and machine learning model training fine-tuned with GridSearchCV and 5-fold cross-validation, resulting in high predictive accuracy, as demonstrated by the receiver operating characteristic and area under the curve (AUC) scores, laying the groundwork for our AI-CDSS.

Results

MALDI-TOF MS analysis revealed distinct intensity profiles differentiating CRKP and susceptible strains, as well as colistin-resistant Klebsiella pneumoniae (CoRKP) and susceptible strains. The Random Forest Classifier demonstrated superior discriminatory power, with an AUC of 0.96 for detecting CRKP and 0.98 for detecting CoRKP.

Conclusion

Integrating MALDI-TOF MS with machine learning in an AI-CDSS has greatly expedited the detection of KP resistance by approximately 1 day. This system offers timely guidance, potentially enhancing clinical decision-making and improving treatment outcomes for KP infections.

Probe-based mass spectrometry approaches for single-cell and single-organelle measurements

Exploring the chemical content of individual cells not only reveals underlying cell-to-cell chemical heterogeneity but is also a key component in understanding how cells combine to form emergent properties of cellular networks and tissues. Recent technological advances in many analytical techniques including mass spectrometry (MS) have improved instrumental limits of detection and laser/ion probe dimensions, allowing the analysis of micron and submicron sized areas. In the case of MS, these improvements combined with MS's broad analyte detection capabilities have enabled the rise of single-cell and single-organelle chemical characterization. As the chemical coverage and throughput of single-cell measurements increase, more advanced statistical and data analysis methods have aided in data visualization and interpretation. This review focuses on secondary ion MS and matrix-assisted laser desorption/ionization MS approaches for single-cell and single-organelle characterization, which is followed by advances in mass spectral data visualization and analysis.

Identification of Escherichia coli strains using MALDI-TOF MS combined with long short-term memory neural networks

The current study aims to develop a new technique for the precise identification of Escherichia coli strains, utilizing matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) combined with a long short-term memory (LSTM) neural network. A total of 48 Escherichia coli strains were isolated and cultured on tryptic soy agar medium for 24 hours for the generation of MALDI-TOF MS spectra. Eight hundred MALDI-TOF MS spectra were obtained per strain, resulting in a database of 38,400 spectra. Fifty percent of the data was utilized for LSTM neural network training, with fine-tuned parameters for strain-level identification. The other half served as the test set to assess model performance. Traditional PCA dimension reduction of MALDI-TOF MS spectra indicated 47 out of 48 strains to be unclassifiable. In contrast, the LSTM neural network demonstrated remarkable efficacy. After 20 training epochs, the model achieved a loss value of 0.0524, an accuracy of 0.999, a precision of 0.985, and a recall of 0.982. When tested on the unseen data, the model attained an overall accuracy of 92.24%. The integration of MALDI-TOF MS and LSTM neural network markedly enhances the identification of Escherichia coli strains. This innovative approach offers an effective and accurate tool for MALDI-TOF MS-based strain-level identification, thus expanding the analytical capabilities of microbial diagnostics.

Factors affecting the quality and reproducibility of MALDI-TOF MS identification for human Capnocytophaga species

Reproducibility and quality of MALDI-TOF MS spectra are critical in the identification process, however, information on the factors affecting the identification scores are scarce. Here, we studied the influence of various factors during the identification process of human oral Capnocytophaga species. The influence of two incubation times, plate-spotting reproducibility of two examiners, extraction technique, storage period of plates, and different laser repetition rates on the quality of MALDI-TOF MS identification of 34 human Capnocytophaga strains (including C. gingivalis, C. granulosa, C. haemolytica, C. leadbetteri, C. ochracea, C. sputigena, and Capnocytophaga genospecies AHN8471) was examined. The identification rate did not show a significant difference (P = 0.05) between the two incubation times, except that C. haemolytica needed a longer incubation time to be recognized at the genus level. The reproducibility of spotting between two examiners was ensured by following the manufacturer's instructions. At the species level, formic acid extraction improved the identification of species with limited representation in the database, such as C. haemolytica and C. granulosa. The storage of plates for one week decreased the identification scores. No significant difference (P = 0.39) was observed between the 60 Hz and 120 Hz laser repetition rates for identifying Capnocytophaga species to the genus or species level. In conclusion, the MALDI TOF MS offers a reliable Capnocytophaga identification after following the universal protocol, while the formic acid extraction is restricted to species with a limited number of strains in the database.

Revealing the genetic traits of the foodborne microbial genus hafnia: Implications for the human gut microbiome

The bacterial genus Hafnia has recently attracted attention due to its complex metabolic features and host-interaction capabilities, which are associated with health benefits, primarily weight loss. However, significant gaps remain in our understanding of the genomic characteristics of this emerging microbial group. In this study, we utilized all available high-quality genomes of Hafnia alvei and Hafnia paralvei to uncover the broad distribution of Hafnia in human and honeybee guts, as well as in dairy products, by analysing 1068 metagenomic datasets. We then investigated the genetic traits related to Hafnia's production of vitamins and short-chain fatty acids (SCFAs) through a comparative genomics analysis that included all dominant bacterial species in the three environments under study. Our findings underscore the extensive metabolic capabilities of Hafnia, particularly in the production of vitamins such as thiamine (B1), nicotinate (B3), pyridoxine (B6), biotin (B7), folate (B9), cobalamin (B12), and menaquinone (K2). Additionally, Hafnia demonstrated a conserved genetic makeup associated with SCFA production, including acetate, propanoate, and butanoate. These metabolic traits were further confirmed using RNAseq analyses of a newly isolated H. paralvei strain T10. Overall, our study illuminates the ecological distribution and genetic attributes of this bacterial genus, which is of increasing scientific and industrial relevance.

Origins, Technological Advancement, and Applications of Peptidomics

Peptidomics is the comprehensive characterization of peptides from biological sources instead of heading for a few single peptides in former peptide research. Mass spectrometry allows to detect a multitude of peptides in complex mixtures and thus enables new strategies leading to peptidomics. The term was established in the year 2001, and up to now, this new field has grown to over 3000 publications. Analytical techniques originally developed for fast and comprehensive analysis of peptides in proteomics were specifically adjusted for peptidomics. Although it is thus closely linked to proteomics, there are fundamental differences with conventional bottom-up proteomics. Fundamental technological advancements of peptidomics since have occurred in mass spectrometry and data processing, including quantification, and more slightly in separation technology. Different strategies and diverse sources of peptidomes are mentioned by numerous applications, such as discovery of neuropeptides and other bioactive peptides, including the use of biochemical assays. Furthermore, food and plant peptidomics are introduced similarly. Additionally, applications with a clinical focus are included, comprising biomarker discovery as well as immunopeptidomics. This overview extensively reviews recent methods, strategies, and applications including links to all other chapters of this book.

MALDI-TOF MS analysis for detection of bovine coronavirus with tryptic peptides from viral proteins

Bovine coronavirus (BCoV）, a significant cattle pathogen causing enteric and respiratory diseases, is primarily detected using reverse transcription-polymerase chain reaction. Our objective was to develop a novel detection method for BCoV by matrix-assisted laser desorption/ionization‒time-of-flight mass spectrometry (MALDI-TOF MS）. Peptide mass fingerprint analysis revealed that nucleocapsid (N）, membrane (M）, and hemagglutinin-esterase (HE) were three main BCoV proteins. Their tryptic peptides were used as target molecules for BCoV detection. When the tryptic digest of 107.0 viral copies was analyzed by MALDI-TOF MS, five peptides with relatively strong peaks were detected. The detection limit was between 105.0 and 106.0 copies per test for BCoV alone. To detect BCoV in the swab eluate, ultrafiltration purification achieved a detection limit between 106.0 and 107.0 copies per test, sufficient to detect BCoV-infected calves. Our findings offer valuable insights for BCoV detection by MALDI-TOF MS.

A novel biochemistry approach combined with MALDI-TOF MS to discriminate Escherichia coli and Shigella species

Escherichia coli and Shigella spp. are closely related, making it crucial to accurately identify them for disease control and prevention. In this study, we utilized MALDI-TOF MS to identify characteristic peaks of decarboxylation products of lysine and ornithine to distinguish between E. coli and Shigella spp. Our findings indicate that the peak at m/z 103.12 ± 0.1 of the product cadaverine from lysine decarboxylase is unique to E. coli, while all Shigella species lack the m/z 103.12 ± 0.1 peak. However, S. sonnei and S. boydii serotype C13 exhibit a specific peak at m/z 89.10 ± 0.1, which is the product of putrescine from ornithine decarboxylase. We were able to correctly identify 97.06% (132 of 136) of E. coli and Shigella isolates and 100% (8 of 8) of S. sonnei isolates using this biochemical-based MALDI-TOF MS detection system. This technology is advantageous for its high-throughput, high quality, and ease of operation, and is of significant value for the diagnosis of E. coli and Shigella-related diseases.

A comprehensive review of microbial contamination in the indoor environment: sources, sampling, health risks, and mitigation strategies

The quality of the indoor environment significantly impacts human health and productivity, especially given the amount of time individuals spend indoors globally. While chemical pollutants have been a focus of indoor air quality research, microbial contaminants also have a significant bearing on indoor air quality. This review provides a comprehensive overview of microbial contamination in built environments, covering sources, sampling strategies, and analysis methods. Microbial contamination has various origins, including human occupants, pets, and the outdoor environment. Sampling strategies for indoor microbial contamination include air, surface, and dust sampling, and various analysis methods are used to assess microbial diversity and complexity in indoor environments. The review also discusses the health risks associated with microbial contaminants, including bacteria, fungi, and viruses, and their products in indoor air, highlighting the need for evidence-based studies that can relate to specific health conditions. The importance of indoor air quality is emphasized from the perspective of the COVID-19 pandemic. A section of the review highlights the knowledge gap related to microbiological burden in indoor environments in developing countries, using India as a representative example. Finally, potential mitigation strategies to improve microbiological indoor air quality are briefly reviewed.

A Single-Laboratory Performance Evaluation of MALDI-TOF MS in Rapid Identification of Staphylococcus aureus, Cronobacter sakazakii, Vibrio parahaemolyticus, and Some Closely Related Bacterial Species of Public Health Importance

BACKGROUND

Staphylococcus is a genus of Gram-positive bacteria, known to cause food poisoning and gastrointestinal illness in humans. Additionally, the emergence of methicillin-resistant S. aureus (MRSA) strains has caused a major health care burden worldwide. Cronobacter is a group of Gram-negative bacteria that can survive in extreme dry conditions. Cronobacter sakazakii is known to contaminate powdered infant formula and cause life-threatening infections in neonates. Vibrio is a genus of human-pathogenic Gram-negative bacteria that can cause foodborne illness by consuming undercooked or raw seafood. Vibrio parahaemolyticus can cause serious gastrointestinal disease in humans. Thus, rapid identification of Staphylococcus spp., Cronobacter spp., and Vibrio spp. is crucial for the source tracking of contaminated food, as well as to measure the transmission dynamics of these bacterial pathogens causing foodborne diseases and outbreaks.

OBJECTIVE

This single-laboratory performance evaluation study used the VITEK MS system to evaluate the potential of MALDI-TOF MS technology for rapid identification of S. aureus-like, C. sakazakii-like, and V. parahaemolyticus-like isolates of public health importance.

METHOD

A total of 226 isolates recovered from various food, environmental surveillance samples, and other sources were identified by bioMérieux VITEK 2 and VITEK MS systems as Staphylococcus spp., Cronobacter spp., and Vibrio spp. Five American Type Culture Collection (ATCC) reference Gram-positive and Gram-negative bacterial isolates were also tested to complete the study. In addition, for some Staphylococcus spp. isolates, whole genome sequencing (WGS) and DNA sequencing of 16S rRNA partial region were also performed for species identification.

RESULTS

The VITEK MS system was able to provide species identification to all 96 isolates of Staphylococcus spp. and to all 29 isolates of Vibrio spp. examined with a high confidence value (99.9%). Similarly, species identification was observed for the majority of spots (245 of 303) for the 101 Cronobacter spp. isolates (∼82.0%) with a high confidence value (99.9%), and genus level identification was noticed for the rest of the Cronobacter spp. isolates (18.0%; 58 of the 303 spots) analyzed. Species identification data generated by VITEK 2 system were comparable to data obtained by the VITEK MS system.

CONCLUSIONS

The VITEK MS system is a reliable high-throughput platform that can rapidly identify Staphylococcus, Vibrio, and Cronobacter to the genus level, as well as S. aureus, C. sakazakii, V. parahaemolyticus, and other closely related foodborne isolates and bacterial isolates from additional sources, in most cases.

HIGHLIGHTS

The VITEK MS system can be used in the rapid genus and species identification of human-pathogenic Staphylococcus spp., Cronobacter spp., and Vibrio spp. isolates.

Mass Spectrometry Analysis for Clinical Applications: A Review

Mass spectrometry (MS) has become an attractive analytical method in clinical analysis due to its comprehensive advantages of high sensitivity, high specificity and high throughput. Separation techniques coupled MS detection (e.g., LC-MS/MS) have shown unique advantages over immunoassay and have developed as golden criterion for many clinical applications. This review summarizes the characteristics and applications of MS, and emphasizes the high efficiency of MS in clinical research. In addition, this review also put forward further prospects for the future of mass spectrometry technology, including the introduction of miniature MS instruments, point-of-care detection and high-throughput analysis, to achieve better development of MS technology in various fields of clinical application. Moreover, as ambient ionization mass spectrometry (AIMS) requires little or no sample pretreatment and improves the flux of MS, this review also summarizes its potential applications in clinic.

Identification of Vibrio metschnikovii and Vibrio injensis Isolated from Leachate Ponds: Characterization of Their Antibiotic Resistance and Virulence-Associated Genes

This study aimed to evaluate the antibiotic resistance of 22 environmental Vibrio metschnikovii isolates and 1 Vibrio injensis isolate from landfill leachates in southwestern Colombia. Isolates were identified by Matrix-Assisted Laser Desorption/Ionization-Time-Of-Flight (MALDI-TOF), and 16S ribosomal RNA gene sequencing. Analysis of the susceptibility to six antibacterial agents by the Kirby-Bauer method showed susceptibility of all the isolates to ciprofloxacin and imipenem. We recorded resistance to beta-lactams and aminoglycosides, but no multidrug resistance was observed. The genome of one of the isolates was sequenced to determine the pathogenic potential of V. injensis. Genes associated with virulence were identified, including for flagellar synthesis, biofilm formation, and hemolysins, among others. These results demonstrate that landfill leachates are potential reservoirs of antibiotic-resistant and pathogenic bacteria and highlight the importance of monitoring Vibrio species in different aquatic environments.

Recent Advances in Mass Spectrometry-Based Spatially Resolved Molecular Imaging of Drug Disposition and Metabolomics

Mass spectrometric imaging is a nontargeted, tag-free, high-throughput, and highly responsive analytical approach. The highly accurate molecular visualization detection technology enables qualitative and quantitative analyses of biologic tissues or cells scanned by mass spectrometry in situ, extracting known and unknown multiple compounds, and simultaneously assessing relative contents of targeting molecules by monitoring their molecular ions and pinpointing the spatial locations of those molecules distributed. Five mass spectrometric imaging techniques and their characteristics are introduced in the review, including matrix-assisted laser desorption ionization mass spectrometry, secondary ion mass spectrometry, desorption electrospray ionization mass spectrometry, laser ablation electrospray ionization mass spectrometry, and laser ablation inductively coupled plasma mass spectrometry. The mass spectrometry-based techniques provide the possibility for spatial metabolomics with the capability of high throughput and precision detection. The approaches have been widely employed to spatially image not only metabolome of endogenous amino acids, peptides, proteins, neurotransmitters, and lipids but also the disposition of exogenous chemicals, such as pharmaceutical agents, environmental pollutants, toxicants, natural products, and heavy metals. The techniques also provide us with spatial distribution imaging of analytes in single cells, tissue microregions, organs, and whole animals. SIGNIFICANCE STATEMENT: The review article includes an overview of five commonly used mass spectrometers for spatial imaging and describes the advantages and disadvantages of each. Examples of the technology applications cover drug disposition, diseases, and omics. Technical aspects of relative and absolute quantification by mass spectrometric imaging and challenges for future new applications are discussed as well. The reviewed knowledge may benefit the development of new drugs and provide a better understanding of biochemical processes related to physiology and diseases.

A Graphene-Coated Silicon Wafer Plate Improves the Sensitivity and Reproducibility of MALDI-TOF MS Analysis of Proteins

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) is widely used to analyze small and large molecules. However, proteins are difficult to analyze with MALDI-TOF MS in clinical applications because of their low ionization efficiency and heterogeneous crystallization with the matrix on the sample spots. Here, we investigate the potential of a customized graphene-coated silicon wafer (G/SiO2) plate for MALDI-TOF MS analysis of a clinically important protein, KPC-2, in comparison with a conventional stainless steel (SUS) plate. Our results demonstrate that the G/SiO2 plate outperforms the SUS plate in terms of sensitivity, reproducibility, and mass accuracy/precision across a wide range of molecular weights, even with highly complex samples. Furthermore, a five-day robustness test confirms the practical applicability of the G/SiO2 plate for the reliable identification of target protein(s) in MALDI-TOF MS analysis. Overall, our findings suggest that the use of the G/SiO2 plate holds great potential for improving the sensitivity and reproducibility of MALDI-TOF MS analysis for the identification of proteins, making it a promising tool for clinical applications.

Illuminating the oral microbiome and its host interactions: recent advancements in omics and bioinformatics technologies in the context of oral microbiome research

The oral microbiota has an enormous impact on human health, with oral dysbiosis now linked to many oral and systemic diseases. Recent advancements in sequencing, mass spectrometry, bioinformatics, computational biology, and machine learning are revolutionizing oral microbiome research, enabling analysis at an unprecedented scale and level of resolution using omics approaches. This review contains a comprehensive perspective of the current state-of-the-art tools available to perform genomics, metagenomics, phylogenomics, pangenomics, transcriptomics, proteomics, metabolomics, lipidomics, and multi-omics analysis on (all) microbiomes, and then provides examples of how the techniques have been applied to research of the oral microbiome, specifically. Key findings of these studies and remaining challenges for the field are highlighted. Although the methods discussed here are placed in the context of their contributions to oral microbiome research specifically, they are pertinent to the study of any microbiome, and the intended audience of this includes researchers would simply like to get an introduction to microbial omics and/or an update on the latest omics methods. Continued research of the oral microbiota using omics approaches is crucial and will lead to dramatic improvements in human health, longevity, and quality of life.

A novel strategy for screening mutations in the voltage-gated sodium channel gene of Aedes albopictus based on multiplex PCR-mass spectrometry minisequencing technology

BACKGROUND

The current prevention and control strategy for Aedes albopictus heavily relies on comprehensive management, such as environmental management and chemical control. However, the wide application of pyrethroids has facilitated the development of insecticide resistance, primarily via mutations in the voltage-gated sodium channel (VGSC) gene. This study aims to develop a novel strategy for detecting mutations in the VGSC gene in Ae. albopictus using multiplex PCR-mass spectrometry (MPCR-MS) minisequencing technology.

METHODS

We established a new strategy for detecting mutations in the VGSC gene in Ae. albopictus using MPCR-MS minisequencing technology. MPCR amplification and mass probe extension (MPE) were first used, followed by single nucleotide polymorphism (SNP) typing mass spectrometry, which allows the simultaneous detection of multiple mutation sites of the VGSC gene in 96 samples of Ae. albopictus. A total of 70 wild-collected Ae. albopictus were used to evaluate the performance of the method by comparing it with other methods.

RESULTS

Three target sites (1016, 1532, 1534) in the VGSC gene can be detected simultaneously by double PCR amplification combined with matrix-assisted laser desorption ionization-time-of-flight mass spectrometry, achieving a detection limit of 20 fg/μl. We applied this method to 70 wild-collected Ae. albopictus, and the obtained genotypes were consistent with the routine sequencing results, suggesting the accuracy of our method.

CONCLUSIONS

MPCR-MS minisequencing technology provides a sensitive and high-throughput approach to Ae. albopictus VGSC gene mutation screening. Compared with conventional sequencing, this method is economical and time-saving. It is of great value for insecticide resistance surveillance in areas with a high risk of vector-borne disease.

Evaluation of the Zybio EXS3000 mass spectrometry in routine identification of Clinical isolates

The matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) has been widely applied in routine clinical microbiology laboratories as an efficient and reliable technique for diagnostic purpose. In this work, we evaluated the performance of the newly developed Zybio EXS3000 (Zybio Inc., China) in microbial identification and compared it with VITEK MS (bioMérieux, France). For this study, a total of 1340 isolates from various clinical specimens were collected. These isolates were analyzed simultaneously on both EXS3000 and VITEK MS. The inconsistent or unidentifiable data were further identified using the help of either 16S rRNA gene or ITS region sequencing. During the study, we observed that EXS3000 and VITEK MS provided positive confirmatory diagnostics for 95.0% and 96.5% of the isolates, respectively, which were consistent with the sequencing results. However, it is worth noting that the EXS3000 system needs to improve the identification performance of Candida albicans in the follow-up. There are no significant differences between the two devices in terms of microbial identification performance. The advantage of EXS3000 over VITEK MS is in its ability to perform in significantly lesser time period. In conclusion, the results of this investigation showed that EXS3000 can be used to identify microorganisms in clinical microbiology laboratories.

Evaluating the microcystin-LR-degrading potential of bacteria growing in extreme and polluted environments

Inhabitants of extreme and polluted environments are attractive as candidates for environmental bioremediation. Bacteria growing in oil refinery effluents, tannery dumpsite soils, car wash effluents, salt pans and hot springs were screened for microcystin-LR biodegradation potentials. Using a colorimetric BIOLOG MT2 assay; Arthrobacter sp. B105, Arthrobacter junii, Plantibacter sp. PDD-56b-14, Acinetobacter sp. DUT-2, Salinivibrio sp. YH4, Bacillus sp., Bacillus thuringiensis and Lysinibacillus boronitolerans could grow in the presence of microcystin-LR at 1, 10 and 100 µg L^-1. Most bacteria grew optimally at 10 µg L^-1 microcystin-LR under alkaline pH (8 and 9). The ability of these bacteria to use MC-LR as a growth substrate depicts their ability to metabolize the toxin, which is equivalent to its degradation. Through PCR screening, these bacteria were shown to lack the mlr genes implying possible use of a unique microcystin-LR degradation pathway. The study highlights the wide environmental and taxonomic distribution of microcystin-LR degraders.

Analysis of Bacterial Pathogens Causing Complicating HAP in Patients with Secondary Peritonitis

Background: Diffuse peritonitis is an acute abdominal condition characterized by high mortality. The main treatment modality is surgery, requiring a subsequent prolonged hospital stay. These patients are, among other things, at risk of developing hospital-acquired pneumonia (HAP), which considerably worsens their treatment outcomes. This study aimed to extend the existing knowledge by providing more detailed microbiological characteristics of complicating HAP in patients with secondary peritonitis, including the identification of isolated bacterial pathogens and their potential sources. Methods: The 2015–2019 retrospective study comprised all patients with an intraoperatively confirmed diagnosis of secondary diffuse peritonitis who were classified in accordance with the quick Sepsis Related Organ Failure Assessment scoring system. Results: HAP developed in 15% of patients. The 90-day mortality rates were 53% and 24% in patients with and without HAP; respectively. The most frequent pathogens responsible for HAP were Pseudomonas aeruginosa, Klebsiella pneumoniae, Escherichia coli, Enterobacter cloacae complex and Enterococcus faecalis. Multidrug resistance to antibiotics was found in 38% of bacterial pathogens. Clonal spread of these bacterial pathogens among patients was not detected. Rather, the endogenous characteristic of HAP was confirmed. Conclusions: The initial antibiotic therapy of complicating HAP in patients with secondary peritonitis must be effective mainly against enterobacteria, including strains with the production of ESBL and AmpC beta-lactamases, Pseudomonas aeruginosa and Enterococcus faecalis. The study further highlighted the importance of monitoring the respiratory tract bacterial microflora in patients with secondary peritonitis. The results should be used for initial antibiotic treatment of complicating HAP instances.

Comparison of Small Biomolecule Ionization and Fragmentation in Pseudomonas aeruginosa Using Common MALDI Matrices

Different bacterial cell surface associated biomolecules can be analyzed by matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) mass spectrometry and coupled with collision induced dissociation (CID) for identification. Pseudomonas aeruginosa is an opportunistic, Gram-negative bacterium that causes acute or chronic biofilm infections. Cells of P. aeruginosa communicate through a system of signaling biomolecules known as quorum sensing (QS). The QS system can result in the production of biosurfactant rhamnolipids known to associate and alter the cellular membrane. MALDI-TOF utilizes a variety of matrices that can interact differently with biomolecules for selective ionization. We examined six common matrices to determine the optimal matrix specific to different molecule classes in P. aeruginosa associated with cell surfaces. Three major molecule classes (quinolones, rhamnolipids, and phospholipids) were observed to ionize selectively with the different matrices tested. Sodiated and protonated adducts differed between matrices utilized in our study. Isobaric ions were identified as different molecule classes depending on the matrix used. We highlight the role of matrix selection in MALDI-TOF identification of molecules within a complex biological mixture.

Comparison of Autof Ms1000 and EXS3000 MALDI-TOF MS Platforms for Routine Identification of Microorganisms

Purpose

Matrix-assisted laser desorption-ionization-time of flight mass spectrometry (MALDI-TOF) has recently been widely used in clinical microbiology laboratories, with the advantages of being reliable, rapid, and cost-effective. Here, we reported the performance of two MALDI-TOF MS instruments, EXS3000 (Zybio, China) and Autof ms1000 (Autobio, China), which are commonly used in clinical microbiology field.

Methods

A total of 209 common clinical common isolates, including 70 gram-negative bacteria strains, 58 gram-positive bacteria strains, 33 yeast strains, 15 anaerobic bacteria strains, and 33 mold strains, and 19 mycobacterial strains were tested. All strains were identified by EXS3000 (Zybio, China) and Autof ms1000 (Autobio, China). Sequence analysis of 16S rRNA or ITS regions was used to verify all strains.

Results

Current study found that species-level discrimination was found to be 191 (91.39%) and 190 (90.91%) by EXS3000 and Autof ms1000, respectively. Genus-level discrimination was 205 (98.09%) by the EXS3000 and 205 (98.09%) by the Autof ms1000, respectively. The correct results at species level of the EXS3000 were 91.43% (64/70) for gram-negative bacteria, 93.1% (54/58) for gram-positive cocci, 93.94% (31/33) for yeast, 100% (15/15) for anaerobes and 81.82% (27/33) for filamentous fungi. The correct results at species level of the Autof ms1000 were 92.86% (65/70) for gram-negative bacteria, 91.38% (53/58) for gram-positive cocci, 93.94% (31/33) for yeast, 100% (15/15) for anaerobes and 78.79% (26/33) for filamentous fungi.

Conclusion

Although the results show that the EXS3000 and Autof ms1000 systems are equally good choices in terms of analytical efficiency for routine procedures, the test result of EXS3000 is slightly better than Autof ms1000. It's worth mentioning that the target plate of the EXS 3000 instrument is reusable, but the target plate of the Autof ms1000 is disposable, making the EXS3000 more effective in reducing costs.

The transmittable through stinging microbiota differs between honeybees and wasps: a potentially greater microbial risk of the wasp sting for humans

The present research investigated whether accidental contact through stinging with honeybees, wasps, and hornets could represent a microbial hazard for humans. It has been previously suggested that such contact may transmit pathogens causing infections that could even be fatal for some susceptible individuals. Stinging simulation experiments were performed in the lab with live insects collected from the environment in Lemnos Island (north-eastern Greece), while different selective agar media targeting some clinically important bacteria (i.e., Staphylococcus aureus, Streptococcus pyogenes, Enterococcus faecalis/faecium, and Pseudomonas aeruginosa) were used as substrates for microbial recovery and identification. Results revealed none of the target pathogenic bacterial species in the honeybee samples, with bacilli, staphylococci, and micrococci dominating their surveyed microbiota. However, most of the suspect colonies isolated from wasps and hornets belonged to important hygienic indicators (i.e., enterococci, Proteus mirabilis, and coliforms), implying possible contact of these insects with fecal origin materials. To sum up, the microbiota that may be transmitted to humans through stinging appears to differ between honeybees and wasps/hornets, while the isolation from the latter samples of some other important opportunistic pathogens, such as Enterobacter spp. and Klebsiella spp., also known for multidrug resistance, could be an additional reason of concern.

Potential Probiotic Lactic Acid Bacteria with Anti-Penicillium expansum Activity from Different Species of Tunisian Edible Snails

This study aimed to isolate lactic acid bacteria (LAB) from the digestive tract, meat and slime of edible snails (Helix lucorum, Helix aspersa and Eobania vermiculata) and investigate their antagonistic activity against Penicillium expansum. They were then characterized for their probiotic potential. Among 900 bacterial isolates, 47 LAB exhibiting anti-P. expansum activity were identified through matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) as Levilactobacillus brevis (25), Lactococcus lactis (3), Enterococcus faecium (12), Enterococcus faecalis (4), Enterococcus casseliflavus (1), and Enterococcus mundtii (2). Sixty-two percent of the strains were tolerant to 100 mg/L of lysozyme. Seventy two percent of the isolates were able to survive at pH 3 and most of them tolerate 2.5% bile salt concentration. Moreover, 23% of the strains displayed bile salt hydrolase activity. Interestingly, all strains were biofilm strong producers. However, their auto- and co-aggregation properties were time and pH dependent with high aggregative potentiality at pH 4.5 after 24 h. Remarkably, 48.94% of the strains showed high affinity to chloroform. The safety assessment revealed that the 47 LAB had no hemolytic activity and 64% of them lacked mucin degradation activity. All isolated strains were susceptible to gentamycin, streptomycin, tetracycline, chloramphenicol, and trimethoprim-sulfamethoxazole. Overall, 43 LAB strains showed inhibitory activity against a broad spectrum of pathogenic Gram-positive and gram-negative bacteria, fungi, and yeast. Our findings suggest that L. brevis (EVM12 and EVM14) and Ent. faecium HAS34 strains could be potential candidates for probiotics with interesting antibacterial and anti-P. expansum activities.

Oral Microbiota-One Habitat or Diverse Niches? A Pilot Study of Sampling and Identification of Oral Bacterial and Fungal Biota in Patients with Type I Diabetes Mellitus Treated with Insulin Pump

OBJECTIVE

The oral microbiota is a very complex and dynamic microbial ecosystem. Alterations of its balance can result in oral and systemic diseases. We aimed to characterize the microbiota in particular niches of the oral cavity in adult type 1 diabetes patients treated with continuous infusion of insulin with insulin pump (IP). In addition, we aimed to determine optimal sites of oral microbiota sampling in studies of large research groups of patients with DM I.

DESIGN

In this pilot study, we sampled the buccal and soft palate mucosa, tongue, palatal and buccal dental surfaces and gingival pockets of adult DM I patients treated with IP.

RESULTS

In total, 23 patients were recruited. The oral microbiota was dominated by Streptococus and Neisseria, with a low incidence of cariogenic S. mutans and Lactobacillus, as well as periodontal pathogens such as Prevotella. There were significant differences in overall CFU counts of all strains, Gram-positive, Staphylococci, Streptococci and S. oralis strains between mucosal and dental surface sites. The overall CFU counts of all strains and Gram-positive strains were higher in dental sites vs. mucosal sites (both p < 0.001). CFU counts of S. oralis were significantly higher in dental sites vs. gingival pocket sites (p = 0.013). Candida species were rare. The mucosal sites on the buccae presented lower diversity and bacterial counts.

CONCLUSIONS

In the study group of adult DM I patients treated with IP, the microbiota in particular niches of the oral cavity was significantly different. Three distinct and optimally appropriate sampling sites for oral microflora were identified: buccal and palatal mucosa, dental surface and gingival pockets. The results of this study may be the basis for further studies of large groups of patients with DM I.

Ion Addition by Electrolysis to Improve the Quantitative Analysis of Bacteria with MALDI-TOF MS

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) is commonly applied to the identification of bacteria but rarely used for quantitative detection due to the inhomogeneous crystallization of the matrix leading to the unsatisfactory linear relationship between the sample amount and the mass spectrum signals. Herein, we proposed a noninterference ion addition (NIA) method by electrolysis to improve homogeneous crystallization during the evaporation progress of sample droplets on the target plates. The active metal wire was inserted in the droplet as the anode electrode, and metal ions were released through electrolysis. The directional migration of metal ions under the electric field can hinder the migration of matrix molecules to the boundary and homogenize the matrix crystals by forming spherical crystals. Simultaneously, trace cationic surfactant was added to the droplet for pinning the contact surface to define the circle crystallization region. The metal ions from the anode electrode wire were deposited on the surface of the target plates which served as the cathode. Therefore, ion addition has no interference effect on ionization during MALDI-MS detection. This NIA method benefits the homogeneous crystallization and so improves the quantitative analysis. NIA is suitable for biological samples with different matrices, and bacterial samples could be quantitatively analyzed.

Molecular epidemiology of antimicrobial-resistant Pseudomonas aeruginosa in a veterinary teaching hospital environment

This study aimed to investigate sites for colonization and molecular epidemiology of antimicrobial-resistant Pseudomonas aeruginosa in a veterinary teaching hospital. Bacterial specimens from surface and liquid samples (n = 165) located in five rooms were collected three times every 2 months, and antimicrobial susceptibility was subsequently determined by minimum inhibitory concentrations. The genomes of resistant strains were further analyzed using whole-genome sequencing. Among 19 P. aeruginosa isolates (11.5%, 19/165), sinks were the most frequent colonization site (53.3%), followed by rubber tubes (44.4%), and anesthesia-breathing circuit (33.3%). The highest resistance to gentamicin (47.4%), followed by piperacillin/tazobactam (36.8%), levofloxacin (36.8%), and ciprofloxacin (36.8%), was observed from 19 P. aeruginosa isolates, of which 10 were resistant strains. Of these 10 antimicrobial-resistant isolates, five were multidrug-resistant isolates, including carbapenem. From the multilocus sequence typing (MLST) analysis, five sequence types (STs), including a high-risk clone of human ST235 (n = 3), and ST244 (n = 3), ST606 (n = 2), ST485 (n = 1), and ST3405 (n = 1) were identified in resistant strains. Multiresistant genes were identified consistent with STs, except ST235. The MLST approach and single nucleotide polymorphism analysis revealed a link between resistant strains from ward rooms and those from examination, wound care, and operating rooms. The improvement of routine cleaning, especially of sink environments, and the continued monitoring of antimicrobial resistance of P. aeruginosa in veterinary hospitals are necessary to prevent the spread of resistant clones and ensure infection control.

Diagnostic test accuracy of an automated device for the MALDI target preparation for microbial identification

The objective of this study was to evaluate the performance of the Copan Colibrí™ against the manual preparation of the MALDI targets. We analyzed 416 (31 different species) non-duplicate strains covering the most important species identified in clinical routine. We also assessed the intra-strain repeatability between the comparable methods. We then analyzed the performance of this new method after implementation in routine on 12,253 aerobic bacterial isolates and yeasts, encompassing a total of 42 different species. Among the 416 strains analyzed, 6.3% (26/416) and 10.8% (45/416) had a score value < 2 when processed by the Colibri™ and manual method, respectively. Only 5.9% (9/152) of the Gram positive rods and cocci had a score values < 2 by the Colibri™ versus 20.4% (31/152) by the manual method. We confirmed that this relative superiority observed for the Colibri™ was due primarily in the use of the formic acid protocol. For the Gram-negative bacteria, the results of both methods were comparable; 6.6% (17/256) and 4.7% (12/256) had a score value < 2 by the Colibri™ and the manual method, respectively. After implementation in routine, the results according to the Biotyper score cut-off values were distributed as follows: < 1.70: 2.5% (304/12,253), 1.70-1.79: 1.9% (227/12,253), 1.80-1.89: 3.1% (377/12,253), 1.90-1.99: 6.7% (825/12,253), and ≥ 2: 85.9% (10,520/12,253). The Colibrí™ coupled to MALDI-TOF/MS revealed good performances and higher intra-strain repeatability as compared to the manual preparation of the MALDI targets.

Recent Advances and Potential Future Applications of MALDI-TOF Mass Spectrometry for Identification of Helminths

Helminth infections caused by nematodes, trematodes, and cestodes are major neglected tropical diseases and of great medical and veterinary relevance. At present, diagnosis of helminthic diseases is mainly based on microscopic observation of different parasite stages, but microscopy is associated with limited diagnostic accuracy. Against this background, recent studies described matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry as a potential, innovative tool for helminth identification and differentiation. MALDI-TOF mass spectrometry is based on the analysis of spectra profiles generated from protein extracts of a given pathogen. It requires an available spectra database containing reference spectra, also called main spectra profiles (MSPs), which are generated from well characterized specimens. At present, however, there are no commercially available databases for helminth identification using this approach. In this narrative review, we summarize recent developments and published studies between January 2019 and September 2022 that report on the use of MALDI-TOF mass spectrometry for helminths. Current challenges and future research needs are identified and briefly discussed.

MALDI-TOF MS database expansion for identification of Bacillus and related genera isolated from a pharmaceutical facility

Bacillus and related genera are among the main bacterial groups isolated from pharmaceutical production areas. The identification of Bacillus species and related genera by classical methods is particularly difficult, due to similarities between closely related species. The Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry (MALDI-TOF MS) is one of the most promising techniques for chemotaxonomic characterization of microorganisms, being an alternative to genotypic methods. This study aimed to identify Bacillus strains and related genera isolated from immunobiological production areas by phylogenetic analysis of housekeeping genes and expand the database associated with MALDI-TOF MS to improve their identification. In a previous study, 97 aerobic endospore-forming bacteria isolated from a pharmaceutical facility were analyzed by MALDI-TOF MS and 16S rRNA gene full-length sequencing. All strains were identified as Bacillus and related genera by the latest methodology. Among the 97 strains, 22 were unidentified and 2 strains were misidentified by MALDI-TOF MS. In the present study, these 24 strains were subjected to 16S rRNA gene phylogenetic analysis. Strains not identified at species level by this methodology were submitted to rpoB gene phylogenetic analysis. After identifying the strains, 19 of the 24 strains were incubated for 24, 48, and 72 h on Tryptic Soy Agar and Sheep Blood Agar and subjected to analysis by MALDI-TOF MS. A SuperSpectrum for each strain was created and entered into the equipment database. Finally, the 24 strains were again submitted to proteomic analysis by MALDI-TOF MS, and, at this time, all were correctly identified. The genotypic identification of in-house isolated strains and the introduction of these spectra in MALDI-TOF MS, in order to obtain a customized database, proved to be an extremely effective tool in the identification of Bacillus and related genera from pharmaceutical industry origin.

Airborne transmission of biological agents within the indoor built environment: a multidisciplinary review

The nature and airborne dispersion of the underestimated biological agents, monitoring, analysis and transmission among the human occupants into building environment is a major challenge of today. Those agents play a crucial role in ensuring comfortable, healthy and risk-free conditions into indoor working and leaving spaces. It is known that ventilation systems influence strongly the transmission of indoor air pollutants, with scarce information although to have been reported for biological agents until 2019. The biological agents' source release and the trajectory of airborne transmission are both important in terms of optimising the design of the heating, ventilation and air conditioning systems of the future. In addition, modelling via computational fluid dynamics (CFD) will become a more valuable tool in foreseeing risks and tackle hazards when pollutants and biological agents released into closed spaces. Promising results on the prediction of their dispersion routes and concentration levels, as well as the selection of the appropriate ventilation strategy, provide crucial information on risk minimisation of the airborne transmission among humans. Under this context, the present multidisciplinary review considers four interrelated aspects of the dispersion of biological agents in closed spaces, (a) the nature and airborne transmission route of the examined agents, (b) the biological origin and health effects of the major microbial pathogens on the human respiratory system, (c) the role of heating, ventilation and air-conditioning systems in the airborne transmission and (d) the associated computer modelling approaches. This adopted methodology allows the discussion of the existing findings, on-going research, identification of the main research gaps and future directions from a multidisciplinary point of view which will be helpful for substantial innovations in the field.

Clostridium subterminale infection in a patient with diffuse large B-cell lymphoma and haemophagocytic syndrome: A case report and literature review

Although uncommon, infection caused by Clostridium subterminale may be life threatening particularly in immunocompromised patients. We report here a rare presentation of a patient with diffuse large B-cell lymphoma and haemophagocytic syndrome associated with C. subterminale bacteraemia. The management of the patient is described as well as a review of medical literature. Infection by Clostridium species, including C. subterminale, should be considered in a febrile patient with a haematologic malignancy. The case highlights the importance of using gene sequencing for identification of this anaerobic organism.

MALDI-TOF MS: application in diagnosis, dereplication, biomolecule profiling and microbial ecology

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) has revolutionized scientific research over the past few decades and has provided a unique platform in ongoing technological developments. Undoubtedly, there has been a bloom chiefly in the field of biological sciences with this emerging technology, and has enabled researchers to generate critical data in the field of disease diagnoses, drug development, dereplication. It has received well acceptance in the field of microbial identification even at strain level, as well as diversified field like biomolecule profiling (proteomics and lipidomics) has evolved tremendously. Additionally, this approach has received a lot more attention over conventional technologies due to its high throughput, speed, and cost effectiveness. This review aims to provide a detailed insight regarding the application of MALDI-TOF MS in the context of medicine, biomolecule profiling, dereplication, and microbial ecology. In general, the expansion in the application of this technology and new advancements it has made in the field of science and technology has been highlighted.

Identification of ticks from an old collection by MALDI-TOF MS

Objective of this study is to find the optimal conditions for preparing the samples, resulting in quality, reproducible and specific MS spectra of the ticks, with a shelf life in 70% ethanol of more than ten years. Amblyomma (Am.) variegatum species which had been stored in alcohol for more than twenty years and for which numerous specimens were available were used to compare the performance of four protocols tested. Spectra of insufficient quality were obtained from Am. variegatum legs preserved in alcohol for long periods with the reference protocol, named DO that we had set up years ago. The same observation was made on the spectra from Am. variegatum legs from dry (evaporated alcohol, DO-mod protocol). With new protocols named ReDO and PReDO the spectra were of good quality with high intensities (> 3000 a.u.). Blind testing showed that 94%, and 93% of the spectra were correctly identified with relevant log score values (LSVs ≥1.8), respectively for ReDO and PReDO protocols. All soft ticks treated in this study by PReDO protocol exhibited low intensity spectra with background noise. This study revealed that MALDI-TOF MS is able to identify hard ticks stored during decades in alcohol or dry (evaporated alcohol). SIGNIFICANCE OF THE STUDY: The correct identification of ticks, including vectors responsible for the transmission of infectious diseases in humans and animals is essential for their control. MALDI-TOF MS, a proteomic tool that has emerged in recent years, has become an innovative, accurate and alternative tool for the identification of arthropods, including ticks. However, previous studies reported that preservation of arthropods in alcohol modified the MS spectra obtained from specimens of the same species freshly collected or frozenly stored. In this study, a standard protocol was established for the identification of tick collections which had been stored for more than ten years in alcohol. Four different protocols were assessed. The analysis of the results showed that among the four protocols tested, two protocols named ReDO (Rehydration and incubation of the legs in 40 μl of HPLC water for 12 h in a dry bath at 37°) and PreDO (Drying of the legs for 12 h in a dry bath at 37 °C followed by rehydration and incubation in 40 μl of HPLC water for 12 h.) seem to be more appropriate for the MALDI-TOF MS identification of ticks from old collections preserved in alcohol or dry. This study is promising for the future, as it will make it possible to create a MALDI-TOF MS database from a wide range of ticks which have been stored for a long time in alcohol or which are dry stored in laboratories and museums around the world.

Rummeliibacillus suwonensis: First Time Isolation from Human Feces by Culturomics

Gut microbiota is a complex ecosystem composed by trillions of microorganisms that are crucial for human health or disease status. Currently, there are two methodological options to explore its complexity: metagenomics and culturomics. Culturomics is an approach that uses multiple culture conditions (days of incubation, enrichment factors and growth temperature) and MALDI-TOF mass spectrometry for the identification of bacterial species and sequencing when this method fails. In this paper, we describe how Colturomic's protocol has allowed the first isolation in human sample of Rummeliibacillus suwonensis, a Gram positive, facultative anaerobe bacterium. The bacterium was isolated from feces of a 69 years old male with amyotrophic lateral sclerosis (ALS) recruited for a clinical trial assessing safety and efficacy of fecal microbiota transplantation in ALS. The first isolation of the microorganism dates back to 2013 from the soil of a South Korean mountain area. In this report, morphological description, biochemical characterization and antibiotic susceptibility tests were performed to outline the bacterial properties.

Classification of Environmental Strains from Order to Genus Levels Using Lipid and Protein MALDI-ToF Fingerprintings and Chemotaxonomic Network Analysis

During the last two decades, MALDI-ToF mass spectrometry has become an efficient and widely-used tool for identifying clinical isolates. However, its use for classification and identification of environmental microorganisms remains limited by the lack of reference spectra in current databases. In addition, the interpretation of the classical dendrogram-based data representation is more difficult when the quantity of taxa or chemotaxa is larger, which implies problems of reproducibility between users. Here, we propose a workflow including a concurrent standardized protein and lipid extraction protocol as well as an analysis methodology using the reliable spectra comparison algorithm available in MetGem software. We first validated our method by comparing protein fingerprints of highly pathogenic bacteria from the Robert Koch Institute (RKI) open database and then implemented protein fingerprints of environmental isolates from French Guiana. We then applied our workflow for the classification of a set of protein and lipid fingerprints from environmental microorganisms and compared our results to classical genetic identifications using 16S and ITS region sequencing for bacteria and fungi, respectively. We demonstrated that our protocol allowed general classification at the order and genus level for bacteria whereas only the Botryosphaeriales order can be finely classified for fungi.

MALDI-TOF Mass Spectrometry Analysis and Human Post-Mortem Microbial Community: A Pilot Study

Introduction: The human post-mortem microbiome (HPM) plays a major role in the decomposition process. Successional changes in post-mortem bacterial communities have been recently demonstrated using high throughput metagenomic sequencing techniques, showing great potential as a post-mortem interval (PMI) predictor. The aim of this study is to verify the application of the mass spectrometry technique, better known as MALDI-TOF MS (matrix-assisted laser desorption/ionization time-of-flight mass spectrometry), as a cheap and quick method for microbe taxonomic identification and for studying the PM microbiome. Methods: The study was carried out on 18 human bodies, ranging from 4 months to 82 years old and with a PMI range from 24 h up to 15 days. The storage time interval in the coolers was included in the final PMI estimates. Using the PMI, the sample study was divided into three main groups: seven cases with a PMI < 72 h; six cases with a PMI of 72−168 h and five cases with a PMI > 168 h. For each body, microbiological swabs were sampled from five external anatomical sites (eyes, ears, nose, mouth, and rectum) and four internal organs (brain, spleen, liver, and heart). Results: The HPM became increasingly different from the starting communities over time in the internal organs as well as at skin sites; the HPM microbiome was mostly dominated by Firmicutes and Proteobacteria phyla; and a PM microbial turnover existed during decomposition, evolving with the PMI. Conclusions: MALDI-TOF is a promising method for PMI estimation, given its sample handling, good reproducibility, and high speed and throughput. Although several intrinsic and extrinsic factors can affect the structure of the HPM, MALDI-TOF can detect the overall microbial community turnover of most prevalent phyla during decomposition. Limitations are mainly related to its sensitivity due to the culture-dependent method and bias in the identification of new isolates.

Differentiating between Enterococcusfaecium and Enterococcuslactis by Matrix-Assisted Laser Desorption Ionization Time-of-Flight Mass Spectrometry

Unlike Enterococcus faecium strains, some Enterococcus lactis strains are considered potential probiotic strains as they lack particular virulence and antibiotic resistance genes. However, these closely related species are difficult to distinguish via conventional taxonomic methods. Here, for the first time, we used matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) with BioTyper and in-house databases to distinguish between E. faecium and E. lactis. A total of 58 reference and isolated strains (89.2%) were correctly identified at the species level using MALDI-TOF MS with in-house databases. However, seven strains (10.8%) were not accurately differentiated as a single colony was identified as a different species with a similar score value. Specific mass peaks were identified by analyzing reference strains, and mass peaks at 10,122 ± 2 m/z, 3650 ± 1 m/z, and 7306 ± 1 m/z were unique to E. faecium and E. lactis reference strains, respectively. Mass peaks verified reproducibility in 60 isolates and showed 100% specificity, whereas 16S rRNA sequencing identified two different candidates for some isolates (E. faecium and E. lactis). Our specific mass peak method helped to differentiate two species, with high accuracy and high throughput, and provided a viable alternative to 16S rRNA sequencing.

Application of Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry for the Rapid Identification of Yeast Species From Polar Regions

Protein profiling based on matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry (MS) has proved to be a powerful tool for yeast identification. However, it is rarely used in the identification of yeast isolates from polar regions, which may be due to the limited data available for the differentiation of polar yeast species. The present study constructed a supplementary database of MALDI-TOF MS, including 33 yeast species from the Arctic and Antarctica. These yeast species were used to assess the accuracy and practicality of MALDI-TOF MS-based identification compared to the ribosomal DNA [internal transcribed spacer (ITS) and large subunit (LSU) gene regions] sequencing identification. Their dendrogram based on main spectra profiles (MSPs) in the supplementary database was somewhat consistent with their phylogenetic tree. The accuracy of MALDI-TOF MS identification was also compared by the ethanol-formic acid extraction method and the on-plate extraction method. In addition, peptide markers of some yeast species (e.g., Glaciozyma, Phenoliferia, Mrakia, and Vishniacozyma) were identified. It is concluded that the MALDI-TOF MS method can differentiate some closely related yeast species from polar regions, thus is suitable for the identification of polar yeasts.