Applications of MALDI-TOF mass spectrometry in clinical diagnostic microbiology

Characteristics and accurate identification of Pantoea dispersa with a case of spontaneous rupture of hepatocellular carcinoma in China: A case report

INTRODUCTION

Pantoea dispersa belongs to the genus Pantoea, which is isolated from Enterobacteriaceae. It has been reported to cause some kinds of infections, but there are few detailed studies on it, especially its characteristics and identification methods, which has caused a lot of trouble in clinical work.

PATIENT CONCERNS

A 51-year-old Chinese man was admitted to our hospital with a 7-hour history of progressive abdominal pain. He was previously diagnosed with liver cirrhosis secondary to chronic hepatitis B infection and hepatocellular carcinoma. An emergency hepatic artery embolization for hemostasis was performed under local anesthesia. Forty-eight hours later, the patient presented sudden onset of high fever up to 39.0 °C and chill.

DIAGNOSIS

Morphological and phenotypic profiles were performed for preliminary identification for P dispersa. The biochemical features were obtained by VITEK 2 Test Kit. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry analysis and 16S ribosomal RNA sequencing were performed to accurately identify P dispersa.

INTERVENTION

Antibiotic therapy of intravenous ceftazidime was started empirically. The antibiotic treatment was switched to intravenous cefepime at the same time because of suspected ceftazidime treatment failure and microbiological sensitivity.

OUTCOMES

The patient remained afebrile, and the second blood culture results were negative. Chest X-ray was normal as well. In order to control the progression of the hepatic lesion, transarterial chemoembolization was performed under local anesthesia. After completion of 14 days of antibiotic treatment, the patient was discharged with no signs of recurrence.

CONCLUSION

P dispersa, a gram-negative bacterium rod, were facultative anaerobic, which displayed yellow pigmentation, round, raised, smooth on culture plates. Conventional analysis was difficult to complete its identification. With biochemical tests, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry analysis and 16S ribosomal RNA sequencing, P dispersa can be accurately identified. It will help physicians understand the related clinical manifestations and make timely and effective treatment for patients.

Direct antimicrobial resistance prediction from clinical MALDI-TOF mass spectra using machine learning

Early use of effective antimicrobial treatments is critical for the outcome of infections and the prevention of treatment resistance. Antimicrobial resistance testing enables the selection of optimal antibiotic treatments, but current culture-based techniques can take up to 72 hours to generate results. We have developed a novel machine learning approach to predict antimicrobial resistance directly from matrix-assisted laser desorption/ionization-time of flight (MALDI-TOF) mass spectra profiles of clinical isolates. We trained calibrated classifiers on a newly created publicly available database of mass spectra profiles from the clinically most relevant isolates with linked antimicrobial susceptibility phenotypes. This dataset combines more than 300,000 mass spectra with more than 750,000 antimicrobial resistance phenotypes from four medical institutions. Validation on a panel of clinically important pathogens, including Staphylococcus aureus, Escherichia coli and Klebsiella pneumoniae, resulting in areas under the receiver operating characteristic curve of 0.80, 0.74 and 0.74, respectively, demonstrated the potential of using machine learning to substantially accelerate antimicrobial resistance determination and change of clinical management. Furthermore, a retrospective clinical case study of 63 patients found that implementing this approach would have changed the clinical treatment in nine cases, which would have been beneficial in eight cases (89%). MALDI-TOF mass spectra-based machine learning may thus be an important new tool for treatment optimization and antibiotic stewardship.

Molecular histoproteomy by MALDI mass spectrometry imaging to uncover markers of the impact of Nosema on Apis mellifera

Matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) is a powerful technology used to investigate the spatio-temporal distribution of a huge number of molecules throughout a body/tissue section. In this paper, we report the use of MALDI IMS to follow the molecular impact of an experimental infection of Apis mellifera with the microsporidia Nosema ceranae. We performed representative molecular mass fingerprints of selected tissues obtained by dissection. This was followed by MALDI IMS workflows optimization including specimen embedding and positioning as well as washing and matrix application. We recorded the local distribution of peptides/proteins within different tissues from experimentally infected versus non infected honeybees. As expected, a distinction in these molecular profiles between the two conditions was recorded from different anatomical sections of the gut tissue. More importantly, we observed differences in the molecular profiles in the brain, thoracic ganglia, hypopharyngeal glands, and hemolymph. We introduced MALDI IMS as an effective approach to monitor the impact of N. ceranae infection on A. mellifera. This opens perspectives for the discovery of molecular changes in peptides/proteins markers that could contribute to a better understanding of the impact of stressors and toxicity on different tissues of a bee in a single experiment.

Exploratory Study on Application of MALDI-TOF-MS to Detect SARS-CoV-2 Infection in Human Saliva

SARS-CoV-2 has caused a large outbreak since its emergence in December 2019. COVID-19 diagnosis became a priority so as to isolate and treat infected individuals in order to break the contamination chain. Currently, the reference test for COVID-19 diagnosis is the molecular detection (RT-qPCR) of the virus from nasopharyngeal swab (NPS) samples. Although this sensitive and specific test remains the gold standard, it has several limitations, such as the invasive collection method, the relative high cost and the duration of the test. Moreover, the material shortage to perform tests due to the discrepancy between the high demand for tests and the production capacities puts additional constraints on RT-qPCR. Here, we propose a PCR-free method for diagnosing SARS-CoV-2 based on matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) profiling and machine learning (ML) models from salivary samples. Kinetic saliva samples were collected at enrollment and ten and thirty days later (D0, D10 and D30), to assess the classification performance of the ML models compared to the molecular tests performed on NPS specimens. Spectra were generated using an optimized protocol of saliva collection and successive quality control steps were developed to ensure the reliability of spectra. A total of 360 averaged spectra were included in the study. At D0, the comparison of MS spectra from SARS-CoV-2 positive patients (n = 105) with healthy healthcare controls (n = 51) revealed nine peaks that significantly distinguished the two groups. Among the five ML models tested, support vector machine with linear kernel (SVM-LK) provided the best performance on the training dataset (accuracy = 85.2%, sensitivity = 85.1%, specificity = 85.3%, F1-Score = 85.1%). The application of the SVM-LK model on independent datasets confirmed its performances with 88.9% and 80.8% of correct classification for samples collected at D0 and D30, respectively. Conversely, at D10, the proportion of correct classification had fallen to 64.3%. The analysis of saliva samples by MALDI-TOF MS and ML appears as an interesting supplementary tool for COVID-19 diagnosis, despite the mitigated results obtained for convalescent patients (D10).

High-performance miniature linear time-of-flight mass spectrometry as an advantageous tool in a high mass-to-charge range

A newly developed miniature MALDI-TOF mass spectrometer provides superior performance in a high m/z range.

Identification of Circulating Biomarkers of COVID-19 Using MALDI-TOF Mass Spectrometry

Matrix-assisted laser desorption/ionization source coupled with time-of-flight mass analyzer mass spectrometry (MALDI-TOF MS) is being widely used to obtain proteomic profiles for clinical purposes, as a fast, low-cost, robust, and efficient technique. Here we describe a method for biofluid analysis using MALDI-TOF MS for rapid acquisition of proteomic signatures of COVID-19 infected patients. By using solid-phase extraction, the method allows the analysis of biofluids in less than 15 min.

Extended Bacteria Culture-Based Clustering Identifies a Phenotype Associating Increased Cough and Enterobacterales in Stable Chronic Obstructive Pulmonary Disease

Chronic obstructive pulmonary disease (COPD) is a chronic inflammatory lung disease characterized by airflow limitation. This chronic respiratory disease represents the third leading cause of death worldwide. Alteration of the airway microbiota has been reported to be associated with exacerbation frequency in COPD, but its role on the symptoms in patients at stable state is still incompletely described. This study aimed to determine whether bacteria isolated in sputum can be associated with the clinical features of COPD patients within stable state. Our study highlights, for the first time, that altered microbiota with Enterobacterales is associated with pejorative clinical symptoms in stable COPD patients. The airway microbiota of 38 patients was analyzed using an extended culture approach and mass spectrometry identification. Cluster analysis by principal coordinate analysis of the bacterial communities showed that the patients could be classified into three distinct clusters in our cohort. The clusters showed no differences in proportions of the phylum, but one of them was associated with a high prevalence of Enterobacterales (71.4% in cluster 1 vs. 0% in cluster 3), loss of microbiota diversity, and higher bacterial load (10⁷ vs. 10⁵ CFU/ml, respectively) and characterized by predominant cough and impact on mental health. These novel findings, supported by further studies, could lead to modifying the processing of COPD sputum in the everyday practice of clinical microbiology laboratories.

Antimicrobial Resistance of Staphylococcus sp. Isolated from Cheeses

S. aureus and some species of coagulase-negative staphylococci, including S. chromogenes and S. simulans, commonly cause intramammary infections. However, little attention was paid to the antimicrobial resistance of these species with respect to their occurrence in dairy products, for example, popular sheep and goat cheeses made from unpasteurized milk. The aim of this study was to investigate such sheep and goat cheeses for the occurrence and antimicrobial resistance of the relevant staphylococci species. The staphylococcal isolates were identified by polymerase chain reaction (130 isolates) and matrix assisted laser desorption/ionization time-of-flight mass spectrometry. The most common species of S. aureus (56 isolates) were identified, as well as S. chromogenes (16 isolates) and S. simulans (10 isolates). Antimicrobial resistance to penicillin, oxacilin, ceftaroline, teicoplanin, gentamicin, erythromycin, tetracycline and ofloxacin was subsequently determined in these species using the agar dilution method. The highest resistance was confirmed in all species, especially to penicillin (91%) and erythromycin (67%). The highest sensitivity was confirmed to ofloxacin (83%). Due to the high incidence of penicillin and oxacilin-resistant staphylococci, the mecA gene was detected by polymerase chain reaction, which was confirmed only in S. aureus isolates (19%). Our study shows that the tested strains (77%) were resistant to more than one antibiotic at a time.

Detection of Fusobacterium nucleatum subspecies in the saliva of pre-colorectal cancer patients, using tandem mass spectrometry

OBJECTIVE

Rising evidence links Fusobacterium nucleatum (F. nucleatum) with its four subspecies; nucleatum, polymorphum, animalis, and vincentii, with the development of colorectal cancer (CRC) and its precursor colorectal adenoma (CRA). This study aims to optimize a technique for and explore the capability of matrix-assisted laser-desorption ionization-tandem time-of-flight mass spectrometry (MALDI-TOF/TOF MS) to detect F. nucleatum subspecies directly from the saliva samples of CRA patients and controls without preculturing.

DESIGN

Saliva samples were collected from four CRA patients and eight controls. Proteins were extracted and subjected to solid-phase extraction fractionation, enzymatically digested, and analyzed by MALDI-TOF/TOF MS. F. nucleatum subspecies strains were cultured and used as a positive control.

RESULTS

A proteomics approach was developed to identify F. nucleatum subspecies directly from saliva samples. With this approach, the bacterial culturing step, which could take up to seven days, was bypassed. Overall, 157 F. nucleatum subspecies proteins were detected in the saliva samples. F. nucleatum subsp. nucleatum was absent in the patients while detected in half of the controls.

CONCLUSION

This study presents a novel technique for detecting F. nucleatum subspecies from saliva specimens that could later be employed to better understand a potential role of those subspecies in CRC development.

Characterization of Vegetative Bacillus cereus and Bacillus subtilis Strains Isolated from Processed Cheese Products in an Italian Dairy Plant

Processed cheese is a commercial product characterized by high microbiological stability and extended shelf life obtained through the application of severe heat treatment. However, spore-forming bacteria can survive through thermal processes. Among them, microorganisms belonging to Bacillus genus have been reported. In this study, we examined the microbiological population of the first hours' production of processed cheeses in an Italian dairy plant during two seasons, between June and October 2020. Matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) was used to identify bacteria colonies, allowing the isolation of Bacillus cereus and Bacillussubtilis strains. These results were further confirmed by amplification and sequencing of 16 rRNA bacterial region. A multi-locus sequence type (MLST) analysis was performed to assess the genetic similarity among a selection of isolates. The fourteen B. cereus strains showed two sequence types: ST-32 was observed in only one strain and the ST-371 in the remaining thirteen isolates. On the contrary, all twenty-one B. subtlis strains, included in the study, showed a new allelic profile for the pycA gene, resulting in a new sequence type: ST-249. For B. cereus strains, analysis of toxin genes was performed. All isolates were positive for nheABC, entFM, and cytK, while hblABCD, bceT, and ces were not detected. Moreover, the biofilm-forming ability of B. cereus and B. subtilis strains was assessed, and all selected isolates proved to be biofilm formers (most of them were stronger producers). Considering the genetical similarity between isolates, jointly with the capacity to produce biofilm, the presence of a recurring Bacillus population could be hypothesized.

A new approach to identifying pathogens, with particular regard to viruses, based on capillary electrophoresis and other analytical techniques

Fast determination, identification and characterization of pathogens is a significant challenge in many fields, from industry to medicine. Standard approaches (e.g., culture media and biochemical tests) are known to be very time-consuming and labor-intensive. Conversely, screening techniques demand a quick and low-cost grouping of microbial isolates, and current analysis call for broad reports of pathogens, involving the application of molecular, microscopy, and electromigration techniques, DNA fingerprinting and also MALDI-TOF methods. The present COVID-19 pandemic is a crisis that affects rich and poor countries alike. Detection of SARS-CoV-2 in patient samples is a critical tool for monitoring disease spread, guiding therapeutic decisions and devising social distancing protocols. The goal of this review is to present an innovative methodology based on preparative separation of pathogens by electromigration techniques in combination with simultaneous analysis of the proteome, lipidome, and genome using laser desorption/ionization analysis.

Clinically Applicable System for Rapidly Predicting Enterococcus faecium Susceptibility to Vancomycin

Enterococcus faecium is a clinically important pathogen that can cause significant morbidity and death. In this study, we aimed to develop a machine learning (ML) algorithm-based rapid susceptibility method to distinguish vancomycin-resistant E. faecium (VREfm) and vancomycin-susceptible E. faecium (VSEfm) strains. A predictive model was developed and validated to distinguish VREfm and VSEfm strains by analyzing the matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) mass spectrometry (MS) spectra of unique E. faecium isolates from different specimen types. The algorithm used 5,717 mass spectra, including 2,795 VREfm and 2,922 VSEfm mass spectra, and was externally validated with 2,280 mass spectra of isolates (1,222 VREfm and 1,058 VSEfm strains). A random forest-based algorithm demonstrated overall good classification performances for the isolates from the specimens, with mean accuracy, sensitivity, and specificity of 0.78, 0.79, and 0.77, respectively, with 10-fold cross-validation, timewise validation, and external validation. Furthermore, the algorithm provided rapid results, which would allow susceptibility prediction prior to the availability of phenotypic susceptibility results. In conclusion, an ML algorithm designed using mass spectra obtained from the routine workflow may be able to rapidly differentiate VREfm strains from VSEfm strains; however, susceptibility results must be confirmed by routine methods, given the demonstrated performance of the assay. IMPORTANCE A modified binning method was incorporated to cluster MS shifting ions into a set of representative peaks based on a large-scale MS data set of clinical VREfm and VSEfm isolates, including 2,795 VREfm and 2,922 VSEfm isolates. Predictions with the algorithm were significantly more accurate than empirical antibiotic use, the accuracy of which was 0.50, based on the local epidemiology. The algorithm improved the accuracy of antibiotic administration, compared to empirical antibiotic prescription. An ML algorithm designed using MALDI-TOF MS spectra obtained from the routine workflow accurately differentiated VREfm strains from VSEfm strains, especially in blood and sterile body fluid samples, and can be applied to facilitate the rapid and accurate clinical testing of pathogens.

An updated model of hydrocephalus in sheep to evaluate the performance of a device for ambulatory wireless monitoring of cerebral pressure through shunts

BACKGROUND

Cerebrospinal fluid (CSF) diversion by shunts is the most common surgical treatment for hydrocephalus. Though effective, shunts are associated with risk of dysfunction leading to multiple surgical revisions, affecting patient quality-of-life and incurring high healthcare costs. There is a need for ambulatory monitoring systems for life-long assessment of shunt status. The present study aimed to develop a preclinical model assessing the feasibility of our wireless device for continuous monitoring of cerebral pressure in shunts.

METHODS

We first adapted a previous hydrocephalus model in sheep, which used an intracisternal kaolin injection. Seven animals were used to establish the model, and 1 sheep with naturally dilated ventricles was used as control. Hydrocephalus was confirmed by clinical examination and brain imaging before inserting the ventriculoperitoneal shunts and the monitoring device allowing continuous measurement of the pressure through the shunt for a few days in 3 sheep. An external ventricular drain was used as gold-standard.

RESULTS

Our results showed that a reduction in kaolin dose associated to postoperative management was crucial to reduce morbidity and mortality rates in the model. Ventriculomegaly was confirmed by imaging 4 days after injection of 75 mg kaolin into the cisterna magna. For the implanted sheep, recordings revealed high sensitivity of our sensor in detecting fluctuations in cerebral pressure compared to conventional measurements.

CONCLUSIONS

This proof-of-concept study highlights the potential of this preclinical model for testing new shunt devices.

Bacterial species identification using MALDI-TOF mass spectrometry and machine learning techniques: A large-scale benchmarking study

Today machine learning methods are commonly deployed for bacterial species identification using MALDI-TOF mass spectrometry data. However, most of the studies reported in literature only consider very traditional machine learning methods on small datasets that contain a limited number of species. In this paper we present benchmarking results on an unprecedented scale for a wide range of machine learning methods, using datasets that contain almost 100,000 spectra and more than 1000 different species. The size and the diversity of the data allow to compare three important identification scenarios that are often not distinguished in literature, i.e., identification for novel biological replicates, novel strains and novel species that are not present in the training data. The results demonstrate that in all three scenarios acceptable identification rates are obtained, but the numbers are typically lower than those reported in studies with a more limited analysis. Using hierarchical classification methods, we also demonstrate that taxonomic information is in general not well preserved in MALDI-TOF mass spectrometry data. For the novel species scenario, we apply for the first time neural networks with Monte Carlo dropout, which have shown to be successful in other domains, such as computer vision, for the detection of novel species.

Protein Biomarker Identification for the Discrimination of Brucella melitensis Field Isolates From the Brucella melitensis Rev.1 Vaccine Strain by MALDI-TOF MS

Brucella melitensis Rev.1 is a live attenuated vaccine strain that is widely used to control brucellosis in small ruminants. For successful surveillance and control programs, rapid identification and characterization of Brucella isolates and reliable differentiation of vaccinated and naturally infected animals are essential prerequisites. Although MALDI-TOF MS is increasingly applied in clinical microbiology laboratories for the diagnosis of brucellosis, species or even strain differentiation by this method remains a challenge. To detect biomarkers, which enable to distinguish the B. melitensis Rev.1 vaccine strain from B. melitensis field isolates, we initially searched for unique marker proteins by in silico comparison of the B. melitensis Rev.1 and 16M proteomes. We found 113 protein sequences of B. melitensis 16M that revealed a homologous sequence in the B. melitensis Rev.1 annotation and 17 of these sequences yielded potential biomarker pairs. MALDI-TOF MS spectra of 18 B. melitensis Rev.1 vaccine and 183 Israeli B. melitensis field isolates were subsequently analyzed to validate the identified marker candidates. This approach detected two genus-wide unique biomarkers with properties most similar to the ribosomal proteins L24 and S12. These two proteins clearly discriminated B. melitensis Rev.1 from the closely related B. melitensis 16M and the Israeli B. melitensis field isolates. In addition, we verified their discriminatory power using a set of B. melitensis strains from various origins and of different MLVA types. Based on our results, we propose MALDI-TOF MS profiling as a rapid, cost-effective alternative to the traditional, time-consuming approach to differentiate certain B. melitensis isolates on strain level.

Rapid Identification of Escherichia coli Colistin-Resistant Strains by MALDI-TOF Mass Spectrometry

Colistin resistance is one of the major threats for global public health, requiring reliable and rapid susceptibility testing methods. The aim of this study was the evaluation of a MALDI-TOF mass spectrometry (MS) peak-based assay to distinguish colistin resistant (colR) from susceptible (colS) Escherichia coli strains. To this end, a classifying algorithm model (CAM) was developed, testing three different algorithms: Genetic Algorithm (GA), Supervised Neural Network (SNN) and Quick Classifier (QC). Among them, the SNN- and GA-based CAMs showed the best performances: recognition capability (RC) of 100% each one, and cross validation (CV) of 97.62% and 100%, respectively. Even if both algorithms shared similar RC and CV values, the SNN-based CAM was the best performing one, correctly identifying 67/71 (94.4%) of the E. coli strains collected: in point of fact, it correctly identified the greatest number of colS strains (42/43; 97.7%), despite its lower ability in identifying the colR strains (15/18; 83.3%). In conclusion, although broth microdilution remains the gold standard method for testing colistin susceptibility, the CAM represents a useful tool to rapidly screen colR and colS strains in clinical practice.

Rare Lelliottia nimipressuralis from a wound infection case report using whole genome sequencing-based bacterial identification

Identification of clinical bacterial isolates is an essential first step to provide guidelines for treatment of pathogenic bacterial infection. Infection occurred in a laceration along the medial aspect of left upper arm of a 71-year-old female. Conventional biochemical testing and MALDI-TOF MS identification failed to correctly identify a bacterial isolate. Using whole genome sequencing, the isolate was identified as Lelliottia nimipressuralis. WGS can overcome the limitations of conventional phenotypic and molecular identification methods and successfully identified a rare pathogen. This case is the first report of a human infection of L. nimipressuralis.

Evaluating Different Storage Media for Identification of Taenia saginata Proglottids Using MALDI-TOF Mass Spectrometry

Taenia saginata is a helminth that can cause taeniasis in humans and cysticercosis in cattle. A species-specific diagnosis and differentiation from related species (e.g., Taenia solium) is crucial for individual patient management and disease control programs. Diagnostic stool microscopy is limited by low sensitivity and does not allow discrimination between T. saginata and T. solium. Molecular diagnostic approaches are not routinely available outside research laboratories. Recently, matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry (MS) was proposed as a potentially suitable technique for species-specific helminth diagnosis. However, standardized protocols and commercial databases for parasite identification are currently unavailable, and pre-analytical factors have not yet been assessed. The purpose of this study was to employ MALDI-TOF MS for the identification of T. saginata proglottids obtained from a human patient, and to assess the effects of different sample storage media on the technique’s diagnostic accuracy. We generated T. saginata-specific main spectral profiles and added them to an in-house database for MALDI-TOF MS-based diagnosis of different helminths. Based on protein spectra, T. saginata proglottids could be successfully differentiated from other helminths, as well as bacteria and fungi. Additionally, we analyzed T. saginata proglottids stored in (i) LC–MS grade water; (ii) 0.45% sodium chloride; (iii) 70% ethanol; and (iv) 37% formalin after 2, 4, 6, 8, 12, and 24 weeks of storage. MALDI-TOF MS correctly identified 97.2–99.7% of samples stored in water, sodium chloride, and ethanol, with log-score values ≥2.5, thus indicating reliable species identification. In contrast, no protein spectra were obtained for samples stored in formalin. We conclude that MALDI-TOF-MS can be successfully employed for the identification of T. saginata, and that water, sodium chloride, and ethanol are equally effective storage solutions for prolonged periods of at least 24 weeks.

Rapid MRSA detection via tandem mass spectrometry of the intact 80 kDa PBP2a resistance protein

Treatment of antibiotic-resistant infections is dependent on the detection of specific bacterial genes or proteins in clinical assays. Identification of methicillin-resistant Staphylococcus aureus (MRSA) is often accomplished through the detection of penicillin-binding protein 2a (PBP2a). With greater dependence on mass spectrometry (MS)-based bacterial identification, complementary efforts to detect resistance have been hindered by the complexity of those proteins responsible. Initial characterization of PBP2a indicates the presence of glycan modifications. To simplify detection, we demonstrate a proof-of-concept tandem MS approach involving the generation of N-terminal PBP2a peptide-like fragments and detection of unique product ions during top-down proteomic sample analyses. This approach was implemented for two PBP2a variants, PBP2amecA and PBP2amecC, and was accurate across a representative panel of MRSA strains with different genetic backgrounds. Additionally, PBP2amecA was successfully detected from clinical isolates using a five-minute liquid chromatographic separation and implementation of this MS detection strategy. Our results highlight the capability of direct MS-based resistance marker detection and potential advantages for implementing these approaches in clinical diagnostics.

Antibiotic Resistance of Escherichia coli Isolated from Processing of Brewery Waste with the Addition of Bulking Agents

The aim of the study was to determine the drug resistance profile and to assess the presence of genes responsible for the production of extended-spectrum beta-lactamases in Escherichia coli isolated from energy-processed hop sediment with the addition of bulking agents. Antibiotic resistance was determined by the disk diffusion method and the PCR technique to detect genes determining the extended-spectrum beta-lactamases (ESBLs) mechanism. A total of 100 strains of E. coli were collected. The highest resistance was found to aztreonam, tetracycline, ampicillin, ticarcillin, and ceftazidime. The bacteria collected were most often resistant to even 10 antibiotics at the same time and 15 MDR strains were found. The ESBL mechanism was determined in 14 isolates. Among the studied genes responsible for beta-lactamase production, blaTEM was the most common (64%). The study revealed that the analysed material was colonised by multi-drug-resistant strains of E. coli, which pose a threat to public health. The obtained results encourage further studies to monitor the spread of drug resistance in E. coli.

Current Scenario and Challenges in the Direct Identification of Microorganisms Using MALDI TOF MS

MALDI TOF MS-based microbial identification significantly lowers the operational costs because of minimal requirements of substrates and reagents for extraction. Therefore, it has been widely used in varied applications such as clinical, food, military, and ecological research. However, the MALDI TOF MS method is laced with many challenges including its limitation of the reference spectrum. This review briefly introduces the background of MALDI TOF MS technology, including sample preparation and workflow. We have primarily discussed the application of MALDI TOF MS in the identification of microorganisms. Furthermore, we have discussed the current trends for bioaerosol detection using MALDI TOF MS and the limitations and challenges involved, and finally the approaches to overcome these challenges.

Identification of filamentous fungi including dermatophytes using MALDI-TOF mass spectrometry

Identification of filamentous fungi based on morphological features is the most available approach used in clinical mycology laboratories. However, MALDI-TOF mass spectrometry is currently invaluable for identification of microorganisms because of its rapidity, simplicity, and accuracy. This study aimed to find the optimal way of identifying filamentous fungi using MALDI-TOF MS.The sample comprised 193 isolates of filamentous fungi. The identification started with morphological assessment. Then isolates were identified using MALDI-TOF MS, both directly from culture and following culture in liquid media with extraction. Subsequently, identification of 20 selected isolates was compared by sequencing of the benA gene, ITS1-5,8-ITS2, and D1-D2 LSU regions.Based on morphological criteria, 17 genera of fungi were identified. With MALDI-TOF MS performed directly from culture, nine isolates were identified to the genus level and 184 to the species level, with a total of 75 species being noted. With the MALDI-TOF MS extraction method, 190 isolates were identified to the species level, with 43 species being noted. The rates of agreement between identification using morphology and the MALDI-TOF MS direct method were 58.55% at the genus level and 22.24% at the species level. The rates of agreement between identification using morphology and the MALDI-TOF MS extraction method were 84.97% at the genus level and 46.11% at the species level. Using sequencing, 87.5% agreement was found for identification with the MALDI-TOF MS extraction method, as compared with only 43.75% for the direct method.The results suggest that the optimal approach to identification of filamentous fungi is a combination of morphological features and MALDI-TOF MS using the extraction method.

Bacterial proteomics and its application for pathogenesis studies

Bacteria build their structures by implementing several macromolecules such as proteins, polysaccharides, phospholipids, and nucleic acids, which leads to preserve their lives and play an essential role in their pathogenesis. There are two genomic and proteomic methods to study various macromolecules of bacteria, which are complementary methods and provide comprehensive information. Proteomic approaches are used to identify proteins and their cell applications. Furthermore, to study bacterial proteins, macromolecules are involved in the bacteria's structures and functions. These protein-based methods provide comprehensive information about the cells, such as the external structures, internal compositions, post-translational modifications, and mechanisms of particular actions such as biofilm formation, antibiotic resistance, and adaptation to the environment, which are helpful in promoting bacterial pathogenesis. These methods use various devices such as MALDI-TOF MS, LC-MS, and two-dimensional electrophoresis, which are valuable tools for studying different structural and functional proteins of the bacteria and their mechanisms of pathogenesis that causes rapid, easy, and accurate diagnosis of the infections.

Accuracy of Broad-Panel PCR-Based Bacterial Identification for Blood Cultures in a Pediatric Oncology Population

Bloodstream infections are a major cause of morbidity and mortality and result in significant costs to health care systems. Rapid identification of the causative agent of bloodstream infections is critical for patient treatment and improved outcomes. Multiplex PCR systems that provide bacterial identification directly from the blood culture bottle allow for earlier detection of pathogens. The GenMark Dx ePlex blood culture identification (BCID) panels have an expanded number of targets for both identification and genotypic markers of antimicrobial resistance. The performance of the ePlex BCID Gram-negative (GN) and Gram-positive (GP) panels were evaluated in a predominantly pediatric oncology population. A total of 112 blood cultures were tested by the ePlex BCID GN and GP panels and results were compared to those from standard-of-care testing. Accuracy for on-panel organisms was 89% (CI, 76% to 95%) for the Gram-positive panel, with four misidentifications and one not detected, and 93% (CI, 82% to 98%) for the Gram-negative panel, with two misidentifications and one not detected. The results showed good overall performance of these panels for rapid, accurate detection of bloodstream pathogens in this high-risk population. IMPORTANCE Bloodstream infections are a major cause of morbidity and mortality and result in significant costs to health care systems. Rapid identification of the causative agent of bloodstream infections is critical for patient treatment and improved outcomes. Multiplex PCR systems that provide bacterial identification directly from the blood culture bottle allow for earlier characterization of pathogens. The GenMark Dx ePlex blood culture identification (BCID) panels, recently cleared by the FDA, have an expanded number of targets for both identification and resistance, much larger than other, automated, broad-panel PCR assays. The performance of the ePlex BCID Gram-negative and Gram-positive panels was evaluated in a predominantly pediatric oncology population, providing a unique look at its performance in a high-risk group, where rapid diagnostic information for bloodstream infections could be of particular value for clinical care providers.

Development of a sensitive liquid chromatography-tandem mass spectrometry method for quantification of human plasma arginine vasopressin

BACKGROUND AND AIMS

Direct measurement of arginine vasopressin (AVP) via immunoassays is not widely conducted, mainly because of technical constraints. Liquid chromatography-tandem mass spectrometry (LC/MS/MS) has been widely used as the gold standard in clinical chemistry. Here, we aimed to develop an MS-based assay to determine human plasma AVP and compare the results with those obtained using a conventional immunoassay.

MATERIALS AND METHODS

We developed a protocol using triple quadrupole MS coupled with LC for the measurement of human plasma AVP. Analytical evaluations of the method were performed, and the results obtained using LC/MS/MS and radioimmunoassay (RIA) were compared.

RESULTS

The lower limit of quantification (LLOQ) for plasma AVP obtained using LC/MS/MS and RIA were 0.2 and 0.4 pg/mL, respectively. Although there was a weak overall correlation between the results obtained using the two different methods, the RIA results did not agree with the LC/MS/MS results, particularly at low concentrations.

CONCLUSIONS

AVP detection through RIA is not satisfactory compared with that using LC/MS/MS. Diagnostic values of direct AVP measurements must be evaluated based on the results obtained via sensitive and accurate MS-based methods rather than those obtained through RIA.

Matrix-assisted laser desorption ionisation (MALDI) mass spectrometry (MS): basics and clinical applications

Background Matrix-assisted laser desorption ionisation (MALDI) mass spectrometry (MS) has been used for more than 30 years. Compared with other analytical techniques, it offers ease of use, high throughput, robustness, cost-effectiveness, rapid analysis and sensitivity. As advantages, current clinical techniques (e.g. immunoassays) are unable to directly measure the biomarker; rather, they measure secondary signals. MALDI-MS has been extensively researched for clinical applications, and it is set for a breakthrough as a routine tool for clinical diagnostics. Content This review reports on the principles of MALDI-MS and discusses current clinical applications and the future clinical prospects for MALDI-MS. Furthermore, the review assesses the limitations currently experienced in clinical assays, the advantages and the impact of MALDI-MS to transform clinical laboratories. Summary MALDI-MS is widely used in clinical microbiology for the screening of microbial isolates; however, there is scope to apply MALDI-MS in the diagnosis, prognosis, therapeutic drug monitoring and biopsy imaging in many diseases. Outlook There is considerable potential for MALDI-MS in clinic as a tool for screening, profiling and imaging because of its high sensitivity and specificity over alternative techniques.

Mass spectrometry and total laboratory automation: opportunities and drawbacks

The diffusion of laboratory automation, initiated nearly 50 years ago with consolidation of preanalytical, clinical chemistry and immunochemistry workstations, is now also gradually embracing mass spectrometry (MS). As for other diagnostic disciplines, the automation of MS carries many advantages, such as efficient personnel management (i.e. improving working atmosphere by decreasing manual activities, lowering health risks, simplifying staff training), better organization (i.e. reducing workloads, improving inventory handling, increasing analytical process standardization) and the possibility to reduce the number of platforms. The development and integration of different technologies into automated MS analyzers will also generate technical and practical advantages, such as prepackaged and ready-to-use reagents, automated dispensing, incubation and measurement, automated sample processing (e.g. system fit for many models of laboratory automation, bar code readers), multiplex testing, automatic data processing, also including quality control assessment, and automated validation/interpretation (e.g. autoverification). A new generation of preanalytical workstations, which can be directly connected to MS systems, will allow the automation of manual extraction and elimination of time-consuming activities, such as tube labeling and capping/decapping. The use of automated liquid-handling platform for pipetting samples, along with addition of internal standards, may then enable the optimization of some steps of extraction and protein precipitation, thus decreasing turnaround time and increasing throughput in MS testing. Therefore, this focused review is aimed at providing a brief update on the importance of consolidation and integration of MS platforms in laboratory automation.

Electrogenerated Chemiluminescence Biosensor Based on Functionalized Two-Dimensional Metal-Organic Frameworks for Bacterial Detection and Antimicrobial Susceptibility Assays

The emergence of antibiotic resistance has prompted the development of rapid antimicrobial susceptibility testing (AST) technologies to guide antibiotic prescription. A novel electrochemiluminescence (ECL) biosensor developed can quantitatively measure the binding between the lectin and lipopolysaccharide (LPS) on Gram-negative bacteria for bacterial determination and to characterize the antimicrobial activities of β-lactam and non-β-lactam antibiotics to normal and antibiotic-resistant bacteria. The biosensor utilizes ruthenium complex tagged concanavalin A (Ru-Con A) coated on NH₂-MIL-53(Al) interface for LPS binding measurements. The decreased ECL signal obtained was directly proportional to increasing Escherichia coli (E. coli) BL21 concentrations. The sensitivity displayed logarithmic dependence in the range of (50-5.0) × 10⁴ cells/mL, with a detection limit of 16 cells/mL. The minimum inhibitory concentration (MIC) values of antibiotics for normal E. coli BL21 were 0.02-0.2, 2-4, 0.002-0.02, and 0.2-1 mg/L for levofloxacin hydrochloride (LVX), tetracycline (TCY), imipenem (IPM), and cefpirome (CPO), respectively. The increased MIC values (8-16 and 4 mg/L for IMP and CPO, respectively) in New Delhi metallo-β-lactamase-1 expressing E. coli BL21 (NDM-1-E. coli BL21) indicated greater resistance to β-lactams in NDM-1-E. coli BL21 compared with normal E. coli BL21. Therefore, the changed ECL signal because of binding between LPS with the lectin has a relation with the type of antibiotic and bacterial strains, making the ECL biosensor promote clinical practicability and facilitate antibiotic stewardship.

MALDI-TOF Mass Spectrometry Technology as a Tool for the Rapid Diagnosis of Antimicrobial Resistance in Bacteria

Species identification by using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) is a routine diagnostic process for infectious diseases in current clinical settings. The rapid, low-cost, and simple to conduct methodology is expanding its application in clinical microbiology laboratories to diagnose the antimicrobial resistance (AMR) in microorganisms. Primarily, antimicrobial susceptibility testing is able to be carried out either by comparing the area under curve of MALDI spectra of bacteria grown in media with antimicrobial drugs or by identifying the shift peaks of bacteria grown in media including ¹³C isotope with antimicrobial drugs. Secondly, the antimicrobial resistance is able to be determined through identifying (i) the antimicrobial-resistant clonal groups based on the fingerprints of the clone, (ii) the shift peak of the modified antimicrobial drug, which is inactivated by the resistance determinant, (iii) the shift peak of the modified antimicrobial target, (iv) the peak specific for the antimicrobial determinant, and (v) the biomarkers that are coproduced proteins with AMR determinants. This review aims to present the current usage of the MALDI-TOF MS technique for diagnosing antimicrobial resistance in bacteria, varied approaches for AMR diagnostics using the methodology, and the future applications of the methods for the accurate and rapid identification of AMR in infection-causing bacterial pathogens.

Development of a Novel Method for Identification of Alaria alata Mesocercariae by Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry

Alaria (A.) alata mesocercariae (AM) have increasingly appeared as incidental findings during the mandatory inspection of wild boars for Trichinella in many European countries. An Alaria spp.-specific PCR is available for the identification of AM; however, it is time- and cost-intensive. Therefore, we propose a rapid and cost-efficient MALDI-TOF assay for the identification of AM in wild boar meat that can be applied in routine diagnostics. In this study, a fast and methodologically simple protocol for the protein extraction of AM from different host species in different countries was established, and an AM-specific reference spectra database was created as part of the ongoing development of an existing Trichinella spp. database. A formic acid protein extraction was performed after pooling 10 AM from the same host individual. In total, 61 main spectra profiles (MSPs) from different host individuals were stored in an AM-specific MSP library. The cluster analysis of these 61 MSPs indicated a possible variation within the A. alata species with a tentative association with the geographical origin of the host, but not the host species. This MALDI-TOF assay allows for a fast verification of the AM isolates, which is the next step in the development of a universal database for the identification of several parasites isolated from meat.

Vulvovaginal candidiasis and current perspectives: new risk factors and laboratory diagnosis by using MALDI TOF for identifying species in primary infection and recurrence

Vulvovaginal candidiasis (VVC), considered the second cause of genital infection among women, has pathogenic mechanisms still to be elucidated and unknown risk factors. Prevalence studies with laboratory diagnosis (at first diagnosis and recurrence) are uncommon, especially using MALDI TOF, used in this clinical, epidemiological, and laboratory study for evaluating candidiasis, and identifying unknown risk factors. To obtain clinical and epidemiological data, patients were questioned, and there was material collection. Samples collected were identified by using phenotypic and presumptive methods and confirmed by MALDI TOF. This study analyzed 278 patients, divided into symptomatic (n = 173) and asymptomatic (n = 105) groups. Regarding the main candidiasis symptoms (discharge, itching, and burning), only 50.3% of patients described these concomitant symptoms, showing a positive predictive value of 67.8%. Regarding the risk factors investigated, there was a statistical correlation between candidiasis and dairy products, gut transit, contraceptive use, respiratory allergy, and panty liners, describing new risk factors related to intestinal and vaginal dysbiosis. After Candida species analysis and confirmation, the primary prevalence was 80.9% (Candida albicans), 15.2% (non-albicans), 1% (Rhodotorula mucilaginosa), and 1.9% (unidentified species). In recurrence, the prevalence was 66.7% (C. albicans) and 33.3% (non-albicans). The presence of symptoms has low positive predictive value for the diagnosis of candidiasis, even when considering the classic triad of symptoms. Laboratory identification of yeast species is essential for correct treatment, preventing the resistance to antifungals and the high recurrence. In addition, dairy products and bowel habits, both related to intestinal and vaginal dysbiosis, may be associated with VVC.

Advances in Environmental Detection and Clinical Diagnostic Tests for Legionella Species

Legionella is a fastidious organism that is difficult to culture in the lab but is widely distributed in environmental, domestic, and hospital settings. The clinical manifestations due to Legionella infections range from mild fever to fatal pneumonia and multiorgan pathologies. Legionella outbreaks though prevalent globally are not reported in developing countries due to difficulties in isolating this organism and the lack of simple diagnostic protocols. Here, we review the literature from across countries to present various methods used to detect Legionella from environmental and clinical samples. We compare the sensitivity and the specificity of the conventional culture-based assays with the recent methods and discuss approaches to develop better detection and diagnostic tests. With better cost-effective detection techniques and regular monitoring of the susceptible sites, which may harbor Legionella colonies, most of the Legionella infections can be prevented. As a result, considerable burden, caused by Legionella infections, on the healthcare system, in especially economically weaker countries, can be mitigated.

An Improved Method for Rapid Detection of Mycobacterium abscessus Complex Based on Species-Specific Lipid Fingerprint by Routine MALDI-TOF

Rapid diagnostics of bacterial infection is the key to successful recovery and eradication of the disease. Currently, identification of bacteria is based on the detection of highly abundant proteins, mainly ribosomal proteins, by routine MALDI-TOF mass spectrometry. However, relying solely on proteins is limited in subspecies typing for some pathogens. This is the case for, for example, the mycobacteria belonging to the Mycobacterium abscessus (MABS) complex, which is classified into three subspecies, namely, M. abscessus subsp. abscessus, M. abscessus subsp. bolletii, and M. abscessus subsp. massiliense. Being able to detect bacteria accurately and rapidly at the subspecies level could not only reliably identify the pathogen causing the disease but also enable better antibiotic stewardship. For instance, M. abscessus subsp. abscessus and M. abscessus subsp. bolletii possess a functional erm41 (erythromycin ribosomal methylation gene 41) gene, whilst M. abscessus subsp. massiliense does not, resulting in differences in macrolide antibiotic (e.g., clarithromycin and azithromycin) susceptibilities. This presents a challenge for physicians when designing an appropriate treatment regimen. To address this challenge, in addition to proteins, species-specific lipids have now been considered as a game changer in clinical microbiology diagnostics. However, their extraction can be time-consuming, and analysis requires the use of apolar toxic organic solvents (e.g., chloroform). Here, we present a new method to accurately detect species and subspecies, allowing the discrimination of the mycobacteria within the MABS complex and relying on the use of ethanol. We found that a combination of the matrix named super-DHB with 25% ethanol with a bacterial suspension at McFarland 20 gave robust and reproducible data, allowing the discrimination of the bacteria within the MABS complex strains tested in this study (n = 9). Further investigations have to be conducted to validate the method on a larger panel of strains for its use in diagnostic laboratories.

Optimization and Standardization of Human Saliva Collection for MALDI-TOF MS

SARS-CoV-2 outbreak led to unprecedented innovative scientific research to preclude the virus dissemination and limit its impact on life expectancy. Waiting for the collective immunity by vaccination, mass-testing, and isolation of positive cases remain essential. The development of a diagnosis method requiring a simple and non-invasive sampling with a quick and low-cost approach is on demand. We hypothesized that the combination of saliva specimens with MALDI-TOF MS profiling analyses could be the winning duo. Before characterizing MS saliva signatures associated with SARS-CoV-2 infection, optimization and standardization of sample collection, preparation and storage up to MS analyses appeared compulsory. In this view, successive experiments were performed on saliva from healthy healthcare workers. Specimen sampling with a roll cotton of Salivette^® devices appeared the most appropriate collection mode. Saliva protein precipitation with organic buffers did not improved MS spectra profiles compared to a direct loading of samples mixed with acetonitrile/formic acid buffer onto MS plate. The assessment of sample storage conditions and duration revealed that saliva should be stored on ice until MS analysis, which should occur on the day of sampling. Kinetic collection of saliva highlighted reproducibility of saliva MS profiles over four successive days and also at two-week intervals. The intra-individual stability of saliva MS profiles should be a key factor in the future investigation for biomarkers associated with SARS-CoV-2 infection. However, the singularity of MS profiles between individuals will require the development of sophisticated bio-statistical analyses such as machine learning approaches. MALDI-TOF MS profiling of saliva could be a promising PCR-free tool for SARS-CoV-2 screening.

Phenotypic and Genetic Comparison of a Plant-Internalized and an Animal-Isolated Salmonella Choleraesuis Strain

Contamination of fresh produce with human pathogens poses an important risk for consumers, especially after raw consumption. Moreover, if microorganisms are internalized, no removal by means of further hygienic measures would be possible. Human pathogenic bacteria identified in these food items are mostly of human or animal origin and an adaptation to this new niche and particularly for internalization would be presumed. This study compares a plant-internalized and an animal-borne Salmonella enterica subsp. enterica serovar Choleraesuis aiming at the identification of adaptation of the plant-internalized strain to its original environment. For this purpose, a phenotypical characterization by means of growth curves under conditions resembling the indigenous environment from the plant-internalized strain and further analyses using Pulsed-field gel electrophoresis and Matrix-assisted laser desorption ionization time of flight spectrometry were assessed. Furthermore, comparative genomic analyses by means of single nucleotide polymorphisms and identification of present/absent genes were performed. Although some phenotypical and genetic differences could be found, no signs of a specific adaptation for colonization and internalization in plants could be clearly identified. This could suggest that any Salmonella strain could directly settle in this niche without any evolutionary process being necessary. Further comparative analysis including internalized strains would be necessary to assess this question. However, these kinds of strains are not easily available.

Application and Perspectives of MALDI-TOF Mass Spectrometry in Clinical Microbiology Laboratories

Early diagnosis of severe infections requires of a rapid and reliable diagnosis to initiate appropriate treatment, while avoiding unnecessary antimicrobial use and reducing associated morbidities and healthcare costs. It is a fact that conventional methods usually require more than 24–48 h to culture and profile bacterial species. Mass spectrometry (MS) is an analytical technique that has emerged as a powerful tool in clinical microbiology for identifying peptides and proteins, which makes it a promising tool for microbial identification. Matrix assisted laser desorption ionization–time of flight MS (MALDI–TOF MS) offers a cost- and time-effective alternative to conventional methods, such as bacterial culture and even 16S rRNA gene sequencing, for identifying viruses, bacteria and fungi and detecting virulence factors and mechanisms of resistance. This review provides an overview of the potential applications and perspectives of MS in clinical microbiology laboratories and proposes its use as a first-line method for microbial identification and diagnosis.

Matrix-Assisted Laser Desorption/Ionization Time of Flight Mass Spectrometry (MALDI-TOF MS) Analysis for the Identification of Pathogenic Microorganisms: A Review

Matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) has been used in the field of clinical microbiology since 2010. Compared with the traditional technique of biochemical identification, MALDI-TOF MS has many advantages, including convenience, speed, accuracy, and low cost. The accuracy and speed of identification using MALDI-TOF MS have been increasing with the development of sample preparation, database enrichment, and algorithm optimization. MALDI-TOF MS has shown promising results in identifying cultured colonies and rapidly detecting samples. MALDI-TOF MS has critical research applications for the rapid detection of highly virulent and drug-resistant pathogens. Here we present a scientific review that evaluates the performance of MALDI-TOF MS in identifying clinical pathogenic microorganisms. MALDI-TOF MS is a promising tool in identifying clinical microorganisms, although some aspects still require improvement.

Cloning, expression, and in silico structural modeling of cholesterol oxidase of Acinetobacter sp. strain RAMD in E. coli

Cholesterol oxidases (CHOXs) are flavin‐adenine dinucleotide‐dependent oxidoreductases with a range of biotechnological applications. There remains an urgent need to identify novel CHOX family members to meet the demands of enzyme markets worldwide. Here, we report the cloning, heterologous expression, and structural modeling of the cholesterol oxidase of Acinetobacter sp. strain RAMD. The cholesterol oxidase gene was cloned and expressed in pGEM®‐T and pET‐28a(+) vectors, respectively, using a gene‐specific primer based on the putative cholesterol oxidase ORF of Acinetobacter baumannii strain AB030 (GenBank [gb] locus tag: IX87_05230). The obtained nucleotide sequence (1671 bp, gb: MK575469.2), translated to a protein designated choxAB (556 amino acids), was overexpressed as inclusion bodies (IBs) (MW ˜ 62 kDa) in 1 mm IPTG‐induced Escherichia coli BL21 (DE3) Rosetta cells. The optimized expression conditions (1 mm IPTG with 2% [v/v] glycerol and at room temperature) yielded soluble active choxAB of 0.45 U·mL⁻¹, with 56.25‐fold enhancement. The recombinant choxAB was purified to homogeneity using Ni²⁺‐affinity agarose column with specific activity (0.054 U·mg⁻¹), yield (8.1%), and fold purification (11.69). Capillary isoelectric‐focusing indicated pI of 8.77 for choxAB. LC‐MS/MS confirmed the IBs (62 kDa), with 82.6% of the covered sequence being exclusive to A. baumannii cholesterol oxidase (UniProtKB: A0A0E1FG24). The 3D structure of choxAB was predicted using the LOMETS webtool with the cholesterol oxidase template of Streptomyces sp. SA‐COO (PDB: 2GEW). The predicted secondary structure included 18 α‐helices and 12 β‐strands, a predicted catalytic triad (E²²⁰, H³⁸⁰, and N⁵¹⁴), and a conserved FAD‐binding sequence (GSGFGGSVSACRLTEKG). Future studies should consider fusion to solubilization tags and switching to the expression host Pichia pastoris to reduce IB formation.

Screening of New Potential Probiotics Strains against Photobacterium damselae Subsp. piscicida for Marine Aquaculture

On intensive fish farms, 10% of the population dies exclusively from pathogens, and Photobacterium damselae subsp. Piscicida (Ph. damselae subsp. Piscicida), the bacteria causing pasteurellosis in marine aquaculture, is one of the major pathogens involved. The objective of this study was to obtain new probiotic strains against pasteurellosis in order to limit the use of chemotherapy, avoiding the environmental repercussions generated by the abusive use of these products. In this study, 122 strains were isolated from the gills and intestines of different marine fish species and were later evaluated in vitro to demonstrate the production of antagonistic effects, the production of antibacterial substances, adhesion and growth to mucus, resistance to bile and resistance to pH gradients, as well as its harmlessness and the dynamic of expression of immune-related genes by real-time PCR after administration of the potential probiotic in the fish diet. Only 1/122 strains showed excellent results to be considered as a potential probiotic strain and continue its characterization against Ph. damselae subsp. piscicida to determine its protective effect and elucidating in future studies its use as a possible probiotic strain for marine aquaculture.

Rapid and sensitive detection of Staphylococcus aureus and Klebsiella pneumonia based on bacitracin-modified Fe3O4@PDA magnetic beads combined with matrix-assisted laser desorption ionization-time of flight mass spectrometry

The highly effective detection of pathogens in complex biological samples is an attractive and critical topic of study. Bacitracin is a novel broad-spectrum antimicrobial peptide to enrich bacteria via interactions with the membrane surface of the different bacterial cells. In this study, for the first time, bacitracin was immobilized on the surface of Fe3O4@PDA magnetic nanoparticles for the enrichment of Staphylococcus aureus (G+) and Klebsiella pneumoniae (G-). Combined with matrix-assisted laser desorption ionization time-of-flight mass spectrometry, a rapid and sensitive detection method for these two bacteria was developed. In this method, the detectable concentration of bacteria was decreased by 2-3 orders of magnitude in unenriched samples. The enrichment and identification can be completed in one hour. All these results demonstrated that the bacitracin-functionalized magnetic composite has potential for use in the large-scale enrichment and isolation of target pathogens from complex biological samples, opening a new avenue for the rapid and sensitive detection of pathogens.

Metagenomics and Other Omics Approaches to Bacterial Communities and Antimicrobial Resistance Assessment in Aquacultures

The shortage of wild fishery resources and the rising demand for human nutrition has driven a great expansion in aquaculture during the last decades in terms of production and economic value. As such, sustainable aquaculture production is one of the main priorities of the European Union's 2030 agenda. However, the intensification of seafood farming has resulted in higher risks of disease outbreaks and in the increased use of antimicrobials to control them. The selective pressure exerted by these drugs provides the ideal conditions for the emergence of antimicrobial resistance hotspots in aquaculture facilities. Omics technology is an umbrella term for modern technologies such as genomics, metagenomics, transcriptomics, proteomics, culturomics, and metabolomics. These techniques have received increasing recognition because of their potential to unravel novel mechanisms in biological science. Metagenomics allows the study of genomes in microbial communities contained within a certain environment. The potential uses of metagenomics in aquaculture environments include the study of microbial diversity, microbial functions, and antibiotic resistance genes. A snapshot of these high throughput technologies applied to microbial diversity and antimicrobial resistance studies in aquacultures will be presented in this review.

Effective discrimination of Yersinia pestis and Yersinia pseudotuberculosis by MALDI-TOF MS using multivariate analysis

Separating Yersinia pseudotuberculosis and Yersinia pestis is an important issue in plague diagnosis but can be extremely difficult because of the high similarity between the two species. MALDI-TOF MS has grown as a diagnostic tool with great potential in bacterial identification. Its application in this field is largely enhanced by multivariate analysis, especially in extracting subtle spectral differences. In this study, we built a complete MALDI-TOF MS data pipeline and found a Y. pestis-specific biomarker at 3063 Da closely related to Y. pestis plasminogen activation factor. Based on this, we achieved almost perfect separation between Y. pseudotuberculosis and Y. pestis (AUC = 0.999) using a supervised linear discriminant analysis (LDA) model. This is significantly better than the conventionally applied unsupervised spectral similarity comparison methods, such as hierarchical clustering analysis (HCA), which gave a separation accuracy of 75.0%. This new computing method paves the way for automatic differentiation between the two highly similar bacterial species with high separation accuracy.

Mass spectrometry-based chemical mapping and profiling toward molecular understanding of diseases in precision medicine

Precision medicine has been strongly promoted in recent years. It is used in clinical management for classifying diseases at the molecular level and for selecting the most appropriate drugs or treatments to maximize efficacy and minimize adverse effects. In precision medicine, an in-depth molecular understanding of diseases is of great importance. Therefore, in the last few years, much attention has been given to translating data generated at the molecular level into clinically relevant information. However, current developments in this field lack orderly implementation. For example, high-quality chemical research is not well integrated into clinical practice, especially in the early phase, leading to a lack of understanding in the clinic of the chemistry underlying diseases. In recent years, mass spectrometry (MS) has enabled significant innovations and advances in chemical research. As reported, this technique has shown promise in chemical mapping and profiling for answering "what", "where", "how many" and "whose" chemicals underlie the clinical phenotypes, which are assessed by biochemical profiling, MS imaging, molecular targeting and probing, biomarker grading disease classification, etc. These features can potentially enhance the precision of disease diagnosis, monitoring and treatment and thus further transform medicine. For instance, comprehensive MS-based biochemical profiling of ovarian tumors was performed, and the results revealed a number of molecular insights into the pathways and processes that drive ovarian cancer biology and the ways that these pathways are altered in correspondence with clinical phenotypes. Another study demonstrated that quantitative biomarker mapping can be predictive of responses to immunotherapy and of survival in the supposedly homogeneous group of breast cancer patients, allowing for stratification of patients. In this context, our article attempts to provide an overview of MS-based chemical mapping and profiling, and a perspective on their clinical utility to improve the molecular understanding of diseases for advancing precision medicine.

Clonal Diversity of Klebsiella spp. and Escherichia spp. Strains Isolated from Patients with Ventilator-Associated Pneumonia

Ventilator-associated pneumonia (VAP) is one of the most severe complications affecting mechanically ventilated patients. The condition is caused by microaspiration of potentially pathogenic bacteria from the upper respiratory tract into the lower respiratory tract or by bacterial pathogens from exogenous sources such as healthcare personnel, devices, aids, fluids and air. The aim of our prospective, observational study was to confirm the hypothesis that in the etiology of VAP, an important role is played by etiological agents from the upper airway bacterial microflora. At the same time, we studied the hypothesis that the vertical spread of bacterial pathogens is more frequent than their horizontal spread among patients. A total of 697 patients required mechanical ventilation for more than 48 h. The criteria for VAP were met by 47 patients. Clonality of bacterial isolates from 20 patients was determined by comparing their macrorestriction profiles obtained by pulsed-field gel electrophoresis (PFGE). Among these 20 patients, a total of 29 PFGE pulsotypes of Klebsiella spp. and Escherichia spp. strains were observed. The high variability of clones proves that there was no circulation of bacterial pathogens among hospitalized patients. Our finding confirms the development of VAP as a result of bacterial microaspiration and therefore the endogenous origin of VAP.

Discrimination of Bacillus cereus Group Members by MALDI-TOF Mass Spectrometry

Matrix-Assisted Laser Desorption/Ionization Time Of Flight Mass Spectrometry (MALDI-TOF MS) technology is currently increasingly used in diagnostic laboratories as a cost effective, rapid and reliable routine technique for the identification and typing of microorganisms. In this study, we used MALDI-TOF MS to analyze a collection of 160 strains belonging to the Bacillus cereus group (57 B. anthracis, 49 B. cereus, 1 B. mycoides, 18 B. wiedmannii, 27 B. thuringiensis, 7 B. toyonensis and 1 B. weihenstephanensis) and to detect specific biomarkers which would allow an unequivocal identification. The Main Spectra Profiles (MSPs) were added to an in-house reference library, expanding the current commercial library which does not include B. toyonensis and B. wiedmannii mass spectra. The obtained mass spectra were statistically compared by Principal Component Analysis (PCA) that revealed seven different clusters. Moreover, for the identification purpose, were generated dedicate algorithms for a rapid and automatic detection of characteristic ion peaks after the mass spectra acquisition. The presence of specific biomarkers can be used to differentiate strains within the B. cereus group and to make a reliable identification of Bacillus anthracis, etiologic agent of anthrax, which is the most pathogenic and feared bacterium of the group. This could offer a critical time advantage for the diagnosis and for the clinical management of human anthrax even in case of bioterror attacks.

Chemically heterogeneous carbon dots enhanced cholesterol detection by MALDI TOF mass spectrometry

A binary system composed of carbon dots (CDs) and N-doped CDs (N-CDs) embedded in an organic matrix was used for the analysis of cholesterol by MALDI (matrix-assisted laser desorption and ionization time-of-flight) mass spectrometry, as a model for detection of small, biologically relevant molecules. The results showed that both CDs are sensitive to the cholesterol and can be used either alone or in a binary system with 2,5-dihydroxybenzoic acid (DHB) to enhance the detection process. It was found that both COOH and NH2 groups on CDs surface contributed to the enhancement in the cholesterol detection by MALDI mass spectrometry in the presence of inorganic cations. Nevertheless, in the presence of NaCl, N-CDs led to a better reproducibility of results. It was due to the coexistence of positive and negative charge on N-CDs surface that led to a homogeneous analyte/substrate distribution, which is an important detection parameter. The enhancing effect of carbon dots was linked to a negative Gibbs energy of the complex formation between CDs, Na+, cholesterol and DHB, and it was supported by theoretical calculations. Moreover, upon the addition of CDs/N-CDs, such features as a low ionization potential, vertical excitation, dipole moment and oscillator strength positively affected the cholesterol detection by MALDI in the presence of Na+.

Construction and Application of an In-House Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry (MALDI-TOF MS) Database Specific to Bacteria From Horses

Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) is used for identification of bacterial species isolated from horses. However, because of insufficiencies in the reference database, some bacterial species isolated from horses are difficult to identify with MALDI-TOF MS, and enriching the databases is expected to enhance the accuracy of MALDI-TOF MS identification. Here we created an in-house database including 271 bacterial isolates from horses. Furthermore, we used an enhanced database (our in-house database plus a commercially provided database) to examine 91 newly obtained isolates that could not be identified with MALDI-TOF MS using the commercially provided database. The enhanced database could identify 15 of those 91 isolates to the species level; including streptococcus (3/19), Gram-positive rod (4/17), Gram-negative rod (8/17) isolates. The enhanced database increased the average identification score of the 91 isolates (1.64-1.76). The in-house database increased the number of isolates that MALDI-TOF MS could identify to the species level and contributed to more accurate identification of bacterial isolates from horses.

The impact of a 'milking the COW' campaign in a regional hospital in Singapore

Background

Computerisation of various processes in hospitals and reliance on electronic devices raises the concern of contamination of these devices from the patient environment. We undertook this study to determine if an attached hand hygiene device that unlocks the screen of a computer on wheels (COW) on usage can be effective in decreasing the microbiological burden on computer keyboards.

Methods

An electronic hand sanitizer was integrated onto the COW. A prospective cohort study with a crossover design involving 2 control and 2 intervention wards was used. The study end point was the number of colony forming units found on the keyboards. Bacteria were classified into 4 main groups; pathogenic, skin flora, from the environment or those thought to be commensals in healthy individuals. We then used a mixed effects model for the statistical analysis to determine if there were any differences before and after the intervention.

Results

Thirty-nine keyboards were swabbed at baseline, day 7 and 14, with 234 keyboards cultured, colony forming units (CFUs) counted and organisms isolated. By mixed model analysis, the difference of mean bacteria count between intervention and control for week 1 was 32.74 (− 32.74, CI − 94.29 to 28.75, p = 0.29), for week 2 by 155.86 (− 155.86, CI − 227.45 to − 83.53, p < 0.0001), and after the 2-week period by 157.04 (− 157.04, CI − 231.53 to − 82.67, p < 0.0001). In the sub-analysis, there were significant differences of pathogenic bacteria counts for the Intervention as compared to the Control in contrast with commensal counts.

Conclusion

A hand hygiene device attached to a COW may be effective in decreasing the microbiological burden on computer keyboards.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13756-021-00948-1.

Effect of humidity during sample preparation on bacterial identification using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) is a highly reliable and efficient technology for the identification of microbial pathogens. We previously found that 40% humidity was the optimal condition for the preparation of samples (co-crystallization of the sample and matrix) for serum peptidomic analysis via MALDI-TOF MS profiling. This optimum temperature was applied to obtain the highest reproducibility and throughput and greatest number of peaks. We therefore hypothesized that humidity control was also essential for MALDI-TOF MS bacterial identification. In this study, we constructed a simple sample preparation device that enables humidity control and used it for co-crystallization of the sample and matrix. Identification scores for five Gram-negative bacteria and six Gram-positive bacteria were determined using the MALDI BioTyper® system at three humidity ranges (10-20%, 30-40%, and 50-60%). As a result, higher identification scores were obtained at 30-40% humidity than at 10-20% or 50-60% humidity. At 30-40% humidity, 517/550 (94.0%) isolates scored greater than 2.0, indicating the success of species-level identification. Similarly, 537/550 (97.6%) isolates scored greater than 1.7, indicating the success of genus-level identification. Thus, 30-40% humidity generated optimal MALDI-TOF MS identification scores and the highest percentage of correct identifications. These results could lead to further improvements in the accuracy of MALDI-TOF MS bacterial identification.

A large-scale investigation and identification of methicillin-resistant Staphylococcus aureus based on peaks binning of matrix-assisted laser desorption ionization-time of flight MS spectra

Recent studies have demonstrated that the matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) could be used to detect superbugs, such as methicillin-resistant Staphylococcus aureus (MRSA). Due to an increasingly clinical need to classify between MRSA and methicillin-sensitive Staphylococcus aureus (MSSA) efficiently and effectively, we were motivated to develop a systematic pipeline based on a large-scale dataset of MS spectra. However, the shifting problem of peaks in MS spectra induced a low effectiveness in the classification between MRSA and MSSA isolates. Unlike previous works emphasizing on specific peaks, this study employs a binning method to cluster MS shifting ions into several representative peaks. A variety of bin sizes were evaluated to coalesce drifted or shifted MS peaks to a well-defined structured data. Then, various machine learning methods were performed to carry out the classification between MRSA and MSSA samples. Totally 4858 MS spectra of unique S. aureus isolates, including 2500 MRSA and 2358 MSSA instances, were collected by Chang Gung Memorial Hospitals, at Linkou and Kaohsiung branches, Taiwan. Based on the evaluation of Pearson correlation coefficients and the strategy of forward feature selection, a total of 200 peaks (with the bin size of 10 Da) were identified as the marker attributes for the construction of predictive models. These selected peaks, such as bins 2410-2419, 2450-2459 and 6590-6599 Da, have indicated remarkable differences between MRSA and MSSA, which were effective in the prediction of MRSA. The independent testing has revealed that the random forest model can provide a promising prediction with the area under the receiver operating characteristic curve (AUC) at 0.8450. When comparing to previous works conducted with hundreds of MS spectra, the proposed scheme demonstrates that incorporating machine learning method with a large-scale dataset of clinical MS spectra may be a feasible means for clinical physicians on the administration of correct antibiotics in shorter turn-around-time, which could reduce mortality, avoid drug resistance and shorten length of stay in hospital in the future.