Direct MALDI-TOF MS Identification of Bacterial Mixtures

Immunoassay-mass spectrometry to identify Brucella melitensis

Two factors frequently impede accurate bacterial identification using matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS): inadequate bacterial abundance in real samples and bacterial combinations. For MALDI-TOF MS analysis and libraries for bacterial identification, time-consuming culture procedures are necessary to achieve sufficient concentration and isolation of a single bacterium. When dealing with hazardous bacteria like Brucella, which are more difficult to handle and cure, this problem becomes even more crucial. To overcome these obstacles, Fe3O4 magnetic nanoparticles (MNPs) linked with Brucella-specific antibodies and MALDI-TOF MS analysis have been used to create a quick and accurate technique for direct bacterial separation and identification in complex samples. This method allows MNPs to immune-selectively collect Brucella cells, which are then deactivated and ready for MALDI-TOF MS analysis by a formic acid/acetonitrile wash. Rabbits were used to manufacture brucella antibodies, which have effectively adsorbed onto the MNPs-protein A. Any particular Brucella bacteria found in the media might be absorbed by this MNPs-protein A-antibody immunoprobe. The concentration of Brucella bacterial cells increases the protein spectrum's visibility by a factor of 103, making it possible to quickly identify Brucella spp. without first growing them in cultural conditions. This method has been successfully used to achieve a limit of detection (LOD) of 50 CFU/mL in an aqueous medium and genuine sample-milk. The diagnostic time for this harmful bacterium is greatly decreased because the entire procedure from bacterial isolation to species identification is finished in less than 60 min. High sensitivity and specificity are demonstrated by the immunoassay-MS approach, as the spectral pattern it produces matches well-known databases like SPECLUST and Ribopeaks.

Direct analysis and identification of the intestinal microflora of shrimps for their geographical traceability via mass spectrometry and bacterial library searching

The expansion of the seafood market has led to an increased probability of food fraud. The development of rapid and reliable traceability methods for aquatic food products is of utmost importance. In this study, direct analysis and identification of the intestinal microbiota of aquatic foods were conducted. The validity of using BacteriaMS database searching for the identification of bacteria was assessed and demonstrated through analyzing prepared bacterial mixtures. We focused on shrimp as a model for aquatic food products and utilized matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) to analyze the intestinal microflora of Chinese shrimp (Fenneropenaeus chinensis) collected from three different aquaculture farms in China. It was found that the most dominant bacteria found in shrimps' intestines could serve as a basis for distinguishing shrimps' geographical origin. The most dominant bacteria in the intestines varied among shrimps from different origins but remained identical for shrimps from the same origin. The reliability of the method in tracing the geographic origin of aquatic products was further validated by analysis of black tiger shrimp (Penaeus monodon) from different origins. The findings show that the utilization of MALDI-TOF MS for the analysis of the microbial community in the intestines of shrimp samples combined with bacterial library searching can offer a rapid, accurate, and feasible method that can be employed for determining shrimps' geographical origin. The present protocol was successfully utilized for the traceability of origins of Chinese shrimp (Fenneropenaeus chinensis) and black tiger shrimp (Penaeus monodon). It is promising to extend the present protocol to other aquatic products with regional characteristics to help combat food fraud in the aquatic product market.

Application of Matrix-Assisted Laser Desorption Ionization Time-of-Flight Mass Spectrometry for Identification of Foodborne Pathogens: Current Developments and Future Trends

Foodborne pathogens have gained sustained public attention, exerted significant pressure on food manufacturers, and posed serious health risks to human. Matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) has been employed for quick and accurate identification of microorganisms in the prevention of foodborne epidemics in recent years. Herein, we first summarize the principle of MALDI and its workflow for foodborne pathogens. Subsequently, we review the recent progress and applications of MALDI-TOF MS in foodborne pathogen determination. Additionally, we outline the expanded utilization of MALDI-based techniques for the identification of closely related species. We also assess the current gaps and propose possible solutions to address the existing challenges. MALDI-TOF MS is a promising biotool for rapid and accurate identification of foodborne microbes at the species and genus level in food samples. Database expansion and direct quantification of spoilage microbes are two promising areas for future progress in MALDI-TOF MS applications.

Quantitative Analysis of Blended Oils Based on Intensity Ratios of Marker Ions in MALDI-MS Spectra

Determination of quantitative compositions of blended oils is an essential but challenging step for the quality control and safety assurance of blended oils. We herein report a method for the quantitative analysis of blended oils based on the intensity ratio of triacylglycerol marker ions, which could be obtained from the highly reproducible spectra acquired by using matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) to directly analyze blended oils in their oily states. We demonstrated that this method could provide good quantitative results to binary, ternary, and quaternary blended oils, with simultaneous quantitation of multiple compositions, and was applicable for quantitative analysis of commercial blended oil products. Moreover, the intensity ratio-based method could be used to rapidly measure the proportions of oil compositions in blended oils, only based on the spectra of the blended oils and related pure oils, making the method as a high-throughput approach to meet the sharply growing analytical demands of blended oils.

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.

Heterogeneous MXene Hybrid-Oriented Exosome Isolation and Metabolic Profiling for Early Screening, Subtyping and Follow-up Evaluation of Bladder Cancer

Exosome metabolite-based noninvasive liquid biopsy is an emerging research hotspot that tends to substitute current means in clinics. Nanostructure-based mass spectrometry enables continuous exosome isolation and metabolic profiling with superior analysis speed and high efficiency. Herein, we construct a heterogeneous MXene hybrid that possesses ternary binding sites for exosome capture and outstanding matrix performance for metabolite analysis. Upon optimizing experimental conditions, the average extraction of exosomes and their metabolic patterns from a 60 mL urine sample is completed within 45 s (40 samples per batch for 30 min). According to the exosomal metabolic patterns and the subsequently established biomarker panel, we distinguish early bladder cancer (BCa) from healthy controls with an area under the curve (AUC) value greater than 0.995 in model training and validation sets. As well, we realize subtype classification of BCa in the blind test on metabolic patterns, with an AUC value of 0.867. We also explore the significant biomarkers that are sensitive to follow-up patients, which indeed present reverse change levels compared with pathological progression. This study has the potential to guide the development of the liquid biopsy approach.

Silver Lactoferrin as Antimicrobials: Mechanisms of Action and Resistance Assessed by Bacterial Molecular Profiles

A diverse silver-lactoferrin (AgLTF) complex, comprising silver ions (Ag+) and silver nanoparticles, displayed a synergistic antibacterial effect while being almost five times more lethal than LTF alone. Gas chromatography-mass spectrometry and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry-in linear (LP) and reflectron (RP) positive modes-were used to comprehensively analyze metabolites and proteins profiles of bacteria (Staphylococcus aureus (SA), Pseudomonas aeruginosa (PA) and Enterococcus faecalis (EF)) treated using AgLTF complex versus exclusively Ag+. Although both agents resulted in similar metabolic shifts in bacteria, AgLTF significantly triggered the production of sulfides (related to bacterial stress resistance), ethanol, 2-butanol (indicating exhaustion of cell respiration), decanoic acid, and nonane (suggesting ongoing oxidative stress). Keto acids formation and fermentation pathways were enhanced by AgLTF and suppressed by Ag+. Furthermore, AgLTF appears to interact with proteins fraction of bacteria in a concentration-dependent manner. EF molecular profiles showed less changes between treated and untreated bacteria. On the other hand, SA and PA proteins and metabolic patterns were the most differentiated from untreated bacteria. In conclusion, our study may provide valuable insights regarding the molecular mechanisms involved in AgLTF antimicrobial action.

Fusion data from FT-IR and MALDI-TOF MS result in more accurate classification of specific microbiota

Microbes are usually present as a specific microbiota, and their classification remains a challenge. MALDI-TOF MS is particularly successful in library-based microbial identification at the species level as it analyzes the molecular weight of peptides and ribosomal proteins. FT-IR allows more accurate classification of bacteria at the subspecies level due to the high sensitivity, specificity and repeatability of FT-IR signals from bacteria, which is not achievable with MALDI-TOF MS. Previous studies have shown that more accurate identification results can be obtained by the fusion of FT-IR and MALDI-TOF MS spectral data. Here, we constructed 20 groups of model microbiota samples and used FT-IR, MALDI-TOF MS, and their fusion data to classify them. Hierarchical clustering analysis (HCA) showed that the classification accuracy of FT-IR, MALDI-TOF MS, and the fusion data was 85%, 90%, and 100%, respectively. These results indicate that both FT-IR and MALDI-TOF MS can effectively classify specific microbiota, and the fusion of their spectral data could improve the classification accuracy. The FT-IR and MALDI-TOF MS data fusion strategy may be a promising technology for specific microbiota classification.

Quantification of Multiplex miRNAs by Mass Spectrometry with Duplex-Specific Nuclease-Mediated Amplification

Early quantification of multiplex biomarkers such as microRNAs (miRNAs) is critical during disease pathologic development and therapy. To tackle challenges of low abundance and multiplexing, we herein report a mass-encoded biosensing approach with duplex-specific nuclease (DSN) mediated signal amplification. Magnetic Fe3O4 cores are coated with small gold nanoparticles (AuNPs), which are applied to achieve facile DNA immobilization subsequent separation. This biosensor integrates multiple mass reporters corresponding to different targets (five miRNAs as examples). Due to the excellent resolution of mass spectrometry, these targets can be successfully distinguished in a single spectrum. Wide detection ranges from 10 fM to 1 nM are achieved, and the limits of detection are estimated to be 10 fM. High selectivity is promised due to the enzyme activity of DSN, and practical application in human serum samples performs satisfactorily. The number of targets to be tested can be further expanded by designing different specific mass tags in theory. Therefore, the proposed method can be utilized as an important and valuable tool to quantify multiplex miRNAs for disease screening as well as biomedical investigations.

MALDI-TOF MS Is an Effective Technique To Classify Specific Microbiota

MALDI-TOF MS is well-recognized for single microbial identification and widely used in research and clinical fields due to its specificity, speed of analysis, and low cost of consumables. Multiple commercial platforms have been developed and approved by the U.S. Food and Drug Administration. Matrix-assisted laser desorption ionization-time-of-flight mass spectrometry (MALDI-TOF MS) has been used for microbial identification. However, microbes can present as a specific microbiota, and detection and classification remain a challenge. Here, we constructed several specific microbiotas and tried to classify them using MALDI-TOF MS. Different concentrations of nine bacterial strains (belonging to eight genera) constituted 20 specific microbiotas. Using MALDI-TOF MS, the overlap spectrum of each microbiota (MS spectra of nine bacterial strains with component percentages) could be classified by hierarchical clustering analysis (HCA). However, the real MS spectrum of a specific microbiota was different than that of the overlap spectrum of component bacteria. The MS spectra of specific microbiota showed excellent repeatability and were easier to classify by HCA, with an accuracy close to 90%. These results indicate that the widely used MALDI-TOF MS identification method for individual bacteria can be expanded to classification of microbiota. IMPORTANCE MALDI-TOF MS can be used to classify specific model microbiota. The actual MS spectrum of the model microbiota was not a simple superposition of every single bacterium in a certain proportion but had a specific spectral fingerprint. The specificity of this fingerprint can enhance the accuracy of microbiota classification.

Matrix-Assisted Laser Desorption Ionization Time of Flight (MALDI-TOF) as an Indispensable Tool in Diagnostic Bacteriology: A Comparative Analysis With Conventional Technique

INTRODUCTION

Owing to its accurate diagnosis, rapid turnaround time, cost effectivity, and less rates of error, Matrix-assisted Laser Desorption Ionization Time of Flight (MALDI-TOF) has replaced most of the phenotypic methods of identification. Thus, the objective of this study was to compare and evaluate MALDI-TOF MS to conventional biochemical-to identify bacterial microorganisms.

METHODS

Different bacterial species isolated from 2010 to 2018 (pre-MALDI-TOF era), using routine bio-chemicals were compared to bacterial species isolated from 2019 to August 2021 (post MALDI-TOF), using MALDI-TOF, in the microbiology laboratory of a tertiary care hospital in North India. Chi-Square test (χ2) was used for the evaluation of bacterial identification between biochemical tests and MALDI-TOF MS association with a 95% confidence interval, considering wrong identification in genera or at a species level.

RESULTS

Many different and new genera and species of bacteria could be identified using MALDI-TOF, which was not possible using only routine manual bio-chemicals like Kocuria rhizophilus, Rothia mucilaginosa, Enterococcus casseliflavus, Enterococcus gallinarum, Leuconostoc, Leclercia adecarboxylata, Raoultella ornithological, Cryseobacterium indologenes. Conclusion: Each of the newly identified bacteria played an important role in deciding treatment. Wide use of the MALDI-TOF system will not only strengthen diagnostic stewardship but also encourage antimicrobial stewardship programs.

Electrostatic Adsorption of Dense AuNPs onto Silica Core as High-Performance SERS Tag for Sensitive Immunochromatographic Detection of Streptococcus pneumoniae

Streptococcus pneumoniae (S. pneumoniae) is a prominent pathogen of bacterial pneumonia and its rapid and sensitive detection in complex biological samples remains a challenge. Here, we developed a simple but effective immunochromatographic assay (ICA) based on silica-Au core-satellite (SiO₂@20Au) SERS tags to sensitively and quantitatively detect S. pneumoniae. The high-performance SiO₂@20Au tags with superior stability and SERS activity were prepared by one-step electrostatic adsorption of dense 20 nm AuNPs onto 180 nm SiO₂ core and introduced into the ICA method to ensure the high sensitivity and accuracy of the assay. The detection limit of the proposed SERS-ICA reached 46 cells/mL for S. pneumoniae and was 100-fold more sensitive than the traditional AuNPs-based colorimetric ICA method. Further, considering its good stability, specificity, reproducibility, and easy operation, the SiO₂@20Au-SERS-ICA developed here has great potential to meet the demands of on-site and accurate detection of respiratory pathogens.

MALDI Mass Spectrometry Imaging: A Potential Game-Changer in a Modern Microbiology

Nowadays, matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF MS) is routinely implemented as the reference method for the swift and straightforward identification of microorganisms. However, this method is not flawless and there is a need to upgrade the current methodology in order to free the routine lab from incubation time and shift from a culture-dependent to an even faster independent culture system. Over the last two decades, mass spectrometry imaging (MSI) gained tremendous popularity in life sciences, including microbiology, due to its ability to simultaneously detect biomolecules, as well as their spatial distribution, in complex samples. Through this literature review, we summarize the latest applications of MALDI-MSI in microbiology. In addition, we discuss the challenges and avenues of exploration for applying MSI to solve current MALDI-TOF MS limits in routine and research laboratories.

MALDI-TOF Mass Spectrometry in Clinical Analysis and Research

In the decade after being awarded the Nobel Prize in Chemistry in 2002, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) has been widely used as an analytical chemistry tool for the detection of large and small molecules (e.g., polymers, proteins, peptides, nucleic acids, amino acids, lipids, etc.) and for clinical analysis and research (e.g., pathogen identification, genetic disorders screening, cancer diagnosis, etc.). In view of the fast development of MALDI-TOF MS in clinical usage, this review systematically summarizes the most important applications of MALDI-TOF MS in clinical analysis and research by analyzing MALDI TOF MS-related reviews collected in the Web of Science database. On the basis of the analysis of keyword co-occurrence of over 2000 review articles, four themes consisting of "pathogen identification", "disease diagnosis", "nucleic acids analysis", and "small molecules analysis" were found. For each theme, the review further outlined their application implications, analytical methods, and systems as well as limitations that need to be addressed. Overall, the review summarizes and elaborates on the clinical applications of MALDI-TOF MS, providing a comprehensive picture for researchers embarking on MALDI TOF MS-related clinical analysis and research.

Comparing the VITEK 2 ANC card, species-specific PCR, and MALDI-TOF mass spectrometry methods for identification of lactic acid bacteria

Lactic acid bacteria (LAB) are not only the most common probiotics in the food and feed industry but are also used as plant probiotics. Therefore, precise identification of LAB at the species level is required. In this study, we compared three different methods, the VITEK 2 ANC card, species-specific PCR, and MALDI-TOF MS, to identify six LAB (Lacticaseibacillus casei, Lacticaseibacillus paracasei, Lacticaseibacillus rhamnosus, Lactiplantibacillus plantarum, Lentilactobacillus buchneri, and Limosilactobacillus fermentum) species previously assigned to the genus Lactobacillus that are used as biofertilizers. Twenty-two strains of six LAB species were analyzed using the VITEK 2 ANC card, species-specific PCR, and MALDI-TOF MS, and identification rates at the species level were 45.5%, 95.5%, and 95.5%, respectively. There were cross-reactions between L. casei and L. parpacasei, and one strain of L. casei could not be identified by these three methods. PCR assays and MALDI-TOF MS were applicable for LAB identification. PRACTICAL APPLICATION: LAB are the most common probiotics in the food and feed industry, so precise identification and classification of LAB at the species level are required. This study aimed at comparing three different methods for the effective identification of six LAB species: biochemical testing using VITEK 2 ANC card, species-specific PCR, and MALDI-TOF MS analysis.

Compound Raman microscopy for rapid diagnosis and antimicrobial susceptibility testing of pathogenic bacteria in urine

Rapid identification and antimicrobial susceptibility testing (AST) of bacteria are key interventions to curb the spread and emergence of antimicrobial resistance. The current gold standard identification and AST methods provide comprehensive diagnostic information but often take 3 to 5 days. Here, a compound Raman microscopy (CRM), which integrates Raman spectroscopy and stimulated Raman scattering microscopy in one system, is presented and demonstrated for rapid identification and AST of pathogens in urine. We generated an extensive bacterial Raman spectral dataset and applied deep learning to identify common clinical bacterial pathogens. In addition, we employed stimulated Raman scattering microscopy to quantify bacterial metabolic activity to determine their antimicrobial susceptibility. For proof-of-concept, we demonstrated an integrated assay to diagnose urinary tract infection pathogens, S. aureus and E. coli. Notably, the CRM system has the unique ability to provide Gram-staining classification and AST results within ~3 h directly from urine samples and shows great potential for clinical applications.

Expression of Staphylococcal Virulence Genes In Situ in Human Skin and Soft Tissue Infections

BACKGROUND

Staphylococcus aureus, the most common pathogen in skin and soft tissue infections (SSTI), harbors many well-characterized virulence genes. However, the expression of many of them in SSTIs is unknown. In this study, S. aureus virulence genes expressed in SSTI were investigated.

METHODS

Fifty-three subjects presenting to the outpatient's care and emergency departments with a purulent SSTI at two medical centers in Wisconsin, USA, were enrolled in the study. Total mRNA was extracted from the purulent or swab materials, made into cDNA and sequenced on MiSeq platform. The relative cDNA counts to gmk and identifications of the transcripts were carried out with respect to USA300 reference genome and using SAMTOOLS v.1.3 and BWA, respectively.

RESULT

A significantly higher cDNA count was observed for many of the virulence and regulatory gene transcripts in the pus samples compared to the swab samples relative to the cDNA counts for gmk, a housekeeping gene. They were for lukS-PV (18.6 vs. 14.2), isaA (13.4 vs. 8.5), ssaA (4.8 vs. 3.1), hlgC (1.4 vs. 1.33), atl (17.7 vs. 8.33), clfA (3.9 vs. 0.83), eno (6.04 vs. 3.16), fnbA (5.93 vs. 0.33), saeS (6.3 vs. 1.33), saeR (5.4 vs. 3.33) and agrC (5.6 vs. 1.5).

CONCLUSIONS

A relative increase in the transcripts of several toxins, adhesion and regulatory genes with respect to a gmk in purulent materials suggests their role in situ during SSTIs, perhaps in an orchestrated manner.

Application of MALDI-TOF MS for identification of environmental bacteria: A review

Bacteria play a variety of roles in the environment. They maintain the balance in the ecosystem and provide different ecosystem services such as in biogeochemical cycling of nutrients, biodegradation of toxic pollutants, and others. Therefore, isolation and identification of different environmental bacteria are important to most environmental research. Due to the high cost and time associated with the conventional molecular techniques, matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) has gained considerable attention for routine identification of bacteria. This review aims to provide an overview of the application of MALDI-TOF MS in various environmental studies through bibliometric analysis and literature review. The bibliometric analysis helped to understand the time-variable application of MALDI-TOF MS in various environmental studies. The categorical literature review covers various environmental studies comprising areas like ecology, food microbiology, environmental biotechnology, agriculture, and plant sciences, which show the application of the technique for identification and characterization of pollutant-degrading, plant-associated, disease-causing, soil-beneficial, and other environmental bacteria. Further research should focus on bridging the gap between the phylogenetic identity of bacteria and their specific environmental functions or metabolic traits that can help in rapid advancements in environmental research, thereby, improving time and cost savings.

Rapid identification of bacterial mixtures in urine using MALDI-TOF MS-based algorithm profiling coupled with magnetic enrichment

Urinary tract infections (UTIs) are a severe public health problem caused by mono- or poly-bacteria. Culture-based methods are routinely used for the diagnosis of UTIs in clinical practice, but those are time consuming. Rapid and unambiguous identification of each pathogen in UTIs can have a significant impact on timely diagnoses and precise treatment. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) is an alternative method for the identification of pathogens in clinical laboratories. However, a certain number of pure bacteria are required for MALDI-TOF MS analysis. Here, we explored a strategy combining magnetic enrichment and MALDI-TOF MS for the rapid identification of pathogenic bacterial mixtures in urine. Fragment crystallizable mannose-binding lectin-modified Fe₃O₄ (Fc-MBL@Fe₃O₄) was used for rapid enrichment and the individual-peak-based similarity model as the analytical tool. Within 30 min, a mixture of the four most prevalent UTI-causing bacteria, Escherichia coli, Klebsiella pneumoniae, Staphylococcus aureus, and Pseudomonas aeruginosa, was successfully identified using this method. This rapid MALDI-TOF MS-based strategy has potential applications in the clinical identification of UTI pathogens.

Sample preparation and culture condition effects on MALDI-TOF MS identification of bacteria: A review

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) is an excellent tool for bacterial identification. It allows high throughput, sensitive and specific applications in clinical diagnostics and environmental research. Currently, there is no optimal standardized protocol for sample preparation and culture conditions to profile bacteria. The performance of MALDI-TOF MS is affected by several variables, such as sample preparation, culture media and culture conditions, incubation time/growth stage, incubation temperature, high salt content, blood in the culture media, and others. This review thus aims to clarify why a uniformed protocol is not plausible, to assess the effects these factors have on MALDI-TOF MS identification score, and discuss possible optimizations for its methodology, in relation to specific bacterial representatives and strain requirements.

Assessment of bacterial viability by laser desorption ionization mass spectrometry for antimicrobial susceptibility testing

Bacterial infection poses a serious threat to human health worldwide. Rapid antimicrobial susceptibility testing (AST) is essential for the clinical treatment of bacterial infection patients. However, the traditional AST relies on bacteria culture, which is time-consuming and limits the analysis to culturable species. Herein, we present a laser desorption ionization (LDI) mass spectrometry-based method for rapid bacterial viability assessment and AST by tracing the redox of resazurin (RS) by viable bacteria. RS as well as its reduction product, fluorescent resorufin (RF), can be directly detected by LDI-MS in the absence of matrix. The intensity ratio between RF and RS can be used to assess the viability of bacteria in specimens. We have demonstrated the high efficiency of the method using different bacterial species, including K. pneumoniae, S. aureus, E. coli, and P. aeruginosa, and various antibiotic drugs, such as ciprofloxacin, ampicillin, tetracycline, oxytetracycline, ciprofloxacin and levofloxacin. Compared to traditional methods based on optical absorption, the current method is faster and more sensitive. Furthermore, we applied the method to bacterial viability detection and AST using human body fluid samples, i.e. serum and urine, demonstrating that it can screen rapidly appropriate antibiotic drugs for timely clinical treatment of infectious diseases. With the advantages of simplicity in methodology as well as sensitivity and speed in analysis, the current method holds the potential of clinical usages.

A new glance at the chemosphere of macroalgal-bacterial interactions: In situ profiling of metabolites in symbiosis by mass spectrometry

Symbiosis is a dominant form of life that has been observed numerous times in marine ecosystems. For example, macroalgae coexist with bacteria that produce factors that promote algal growth and morphogenesis. The green macroalga Ulva mutabilis (Chlorophyta) develops into a callus-like phenotype in the absence of its essential bacterial symbionts Roseovarius sp. MS2 and Maribacter sp. MS6. Spatially resolved studies are required to understand symbiont interactions at the microscale level. Therefore, we used mass spectrometry profiling and imaging techniques with high spatial resolution and sensitivity to gain a new perspective on the mutualistic interactions between bacteria and macroalgae. Using atmospheric pressure scanning microprobe matrix-assisted laser desorption/ionisation high-resolution mass spectrometry (AP-SMALDI-HRMS), low-molecular-weight polar compounds were identified by comparative metabolomics in the chemosphere of Ulva. Choline (2-hydroxy-N,N,N-trimethylethan-1-aminium) was only determined in the alga grown under axenic conditions, whereas ectoine (1,4,5,6-tetrahydro-2-methyl-4-pyrimidinecarboxylic acid) was found in bacterial presence. Ectoine was used as a metabolic marker for localisation studies of Roseovarius sp. within the tripartite community because it was produced exclusively by these bacteria. By combining confocal laser scanning microscopy (cLSM) and AP-SMALDI-HRMS, we proved that Roseovarius sp. MS2 settled mainly in the rhizoidal zone (holdfast) of U. mutabilis. Our findings provide the fundament to decipher bacterial symbioses with multicellular hosts in aquatic ecosystems in an ecologically relevant context. As a versatile tool for microbiome research, the combined AP-SMALDI and cLSM imaging analysis with a resolution to level of a single bacterial cell can be easily applied to other microbial consortia and their hosts. The novelty of this contribution is the use of an in situ setup designed to avoid all types of external contamination and interferences while resolving spatial distributions of metabolites and identifying specific symbiotic bacteria.

Repository scale classification and decomposition of tandem mass spectral data

Various studies have shown associations between molecular features and phenotypes of biological samples. These studies, however, focus on a single phenotype per study and are not applicable to repository scale metabolomics data. Here we report MetSummarizer, a method for predicting (i) the biological phenotypes of environmental and host-oriented samples, and (ii) the raw ingredient composition of complex mixtures. We show that the aggregation of various metabolomic datasets can improve the accuracy of predictions. Since these datasets have been collected using different standards at various laboratories, in order to get unbiased results it is crucial to detect and discard standard-specific features during the classification step. We further report high accuracy in prediction of the raw ingredient composition of complex foods from the Global Foodomics Project.

A universal SERS-label immunoassay for pathogen bacteria detection based on Fe3O4@Au-aptamer separation and antibody-protein A orientation recognition

Rapid, reliable and sensitive detection methods for pathogenic bacteria are strongly demanded. Herein, we proposed a magnetically assisted surface enhanced Raman scattering (SERS)-label immunoassay for the sensitive detection of bacteria by using a universal approach based on free antibody labelling and staphylococcus proteins A (PA)-SERS tags orientation recognition. The SERS biosensor consists of two functional nanomaterials: aptamer-conjugated Fe₃O₄@Au magnetic nanoparticles (MNPs) as magnetic SERS platform for pathogen enrichment and PA modified-SERS tags (Au@DTNB@PA) as a universal probe for target bacteria quantitative detection. After target bacteria enriched, free antibody was used to specific marking target bacteria and provided numerous Fc fragment, which can guide the PA-SERS tags orientation-dependent binding. With this strategy, Fe₃O₄@Au/bacteria/SERS tags sandwich immunocomplexes for most bacteria (expect several species of Staphylococcus) were easy constructed. The limits of detection (LODs) of the proposed assay were found to be 10, 10, and 25 cells/mL for three common pathogens Escherichia coli (E. coli), Listeria monocytogenes (L. mono), and Salmonella typhimurium (S. typhi), respectively, in real food samples. The universal method also exhibits the advantages of rapid, robust, and easy to operate, suggesting its great potential for food safety monitoring and infectious diseases diagnosis.

A Critical Review of Analytical Methods for Comprehensive Characterization of Produced Water

Produced water is the largest waste stream associated with oil and gas production. It has a complex matrix composed of native constituents from geologic formation, chemical additives from fracturing fluids, and ubiquitous bacteria. Characterization of produced water is critical to monitor field operation, control processes, evaluate appropriate management practices and treatment effectiveness, and assess potential risks to public health and environment during the use of treated water. There is a limited understanding of produced water composition due to the inherent complexity and lack of reliable and standardized analytical methods. A comprehensive description of current analytical techniques for produced water characterization, including both standard and research methods, is discussed in this review. Multi-tiered analytical procedures are proposed, including field sampling; sample preservation; pretreatment techniques; basic water quality measurements; organic, inorganic, and radioactive materials analysis; and biological characterization. The challenges, knowledge gaps, and research needs for developing advanced analytical methods for produced water characterization, including target and nontarget analyses of unknown chemicals, are discussed.

Microdroplet Impact-Induced Spray Ionization Mass Spectrometry (MISI MS) for Online Reaction Monitoring and Bacteria Discrimination

Microdroplet impact-induced spray ionization (MISI) is demonstrated involving the impact of microdroplets produced from a paper and their impact on another, leading to the ionization of analytes deposited on the latter. This cascaded process is more advantageous in comparison to standard spray ionization as it performs reactions and ionization simultaneously in the absence of high voltage directly applied on the sample. In MISI, we apply direct current (DC) potential only to the terminal paper, used as the primary ion source. Charge transfer due to microdroplet/ion deposition on the flowing analyte solution on the second surface generates secondary charged microdroplets from it carrying the analytes, which ionize and get detected by a mass spectrometer. In this way, up to three cascaded spray sources could be assembled in series. We show the detection of small molecules and proteins in such ionization events. MISI provides a method to understand chemical reactions by droplet impact. The C-C bond formation reactions catalyzed by palladium and alkali metal ion encapsulation using crown ether were studied as our model reactions. To demonstrate the application of our ion source in a bioanalytical context, we studied the noninvasive in situ discrimination of bacteria samples under ambient conditions.

Releasing bacteria from functional magnetic beads is beneficial to MALDI-TOF MS based identification

Bacterial infections are the key cause of morbidity and mortality worldwide. Matrix-assisted laser desorption ionization time of flight mass spectrometry (MALDI-TOF MS)-based bacterial identification has been widely accepted in the clinic. Functional material, such as rabbit immunoglobulin G-modified Fe₃O₄ (IgG@Fe₃O₄) and fragment crystallizable mannose binding lectin-modified Fe₃O₄ (FcMBL@Fe₃O₄), is used to capture bacteria from biological samples for MALDI-TOF MS identification, and the bacteria MS signals are usually obtained by directly smearing enriched bacteria on a MALDI target with MALDI matrix solution. However, the accuracy of identification based on MALDI-TOF MS may be affected by the presence of functional molecules, especially proteins, resulting in errors in the comparison with the standard bacterial spectra in the database. Moreover, the long-term presence of the magnetic beads on the MALDI-TOF target may reduce the instrument service life. In this study, we constructed FcMBL@Fe₃O₄ and used it to capture bacteria from both aqueous solution and bovine blood, and the bacterial identification accuracy based on different target preparation methods was compared. In the presence of Ca²⁺, the similarity scores for bacteria identified with FcMBL@Fe₃O₄ were ~88% and ~82% for Staphylococcus. aureus and Escherichia coli, respectively. In the presence of ethylenediaminetetraacetic acid (EDTA), bacteria separate from FcMBL@Fe₃O₄, resulting in similarity scores of ~96% and ~92% for S. aureus and E. coli, respectively. These results indicate that the functional proteins on the surface of nanoparticles affect the accuracy of identification accuracy based on the MALDI-TOF MS database. Thus, the release of bacteria from the functional material could increase the identification accuracy and be beneficial for maintaining the instrument.

Fast and High-Throughput Evaluation of Photodynamic Effect by Monitoring Specific Protein Oxidation with MALDI-TOF Mass Spectrometry

In antibacterial practices by photodynamic treatment, bacteria are incubated with photosensitizers and then oxidized to death by generating reactive oxygen species (ROS) under light irradiation. Generally, Luria-Bertani (LB) agar colony is a conventional method to evaluate the photodynamic effect. However, this method is time consuming, easily disturbed by pollutants, and limited to the analysis of a pure bacteria sample. Herein, we introduce a novel method of photodynamic effect evaluation through in situ detection of specific protein oxidation by matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF MS) with only 1 μL of sample in a fast (less than 1 min per sample) and high-throughput (up to 384 samples per run) way. The oxidation rates of specific proteins stayed highly consistent with bactericidal rates and thus MALDI-TOF MS might be able to replace the LB agar colony to evaluate the photodynamic effect. With the present method, several experimental conditions including different photosensitizer types, dosage controls, and different illumination times were easily screened to optimize photodynamic effect. Photodynamic effects of various bacteria species, cancer cells, and even mixture samples were also evaluated. The results demonstrate the promising application of MALDI-TOF MS in evaluating the photodynamic effect of each component in a mixture sample without any separation or purification, which could not be achieved by the traditional LB agar colony method.

MGMS2: Membrane glycolipid mass spectrum simulator for polymicrobial samples

RATIONALE

Polymicrobial samples present unique challenges for mass spectrometric identification. A recently developed glycolipid technology has the potential to accurately identify individual bacterial species from polymicrobial samples. In order to develop and validate bacterial identification algorithms (e.g. machine learning) using this glycolipid technology, generating a large number of various polymicrobial samples can be beneficial, but it is costly and labor-intensive. Here, we propose an alternative cost-effective approach that generates realistic in silico polymicrobial glycolipid mass spectra.

METHODS

We introduce MGMS2 (membrane glycolipid mass spectrum simulator) as a simulation software package that generates in silico polymicrobial membrane glycolipid matrix-assisted laser desorption/ionization time-of-flight mass spectra. Unlike currently available simulation algorithms for polymicrobial mass spectra, the proposed algorithm considers errors in m/z values and variances of intensity values, occasions of missing signature ions, and noise peaks. To our knowledge, this is the first stand-alone bacterial membrane glycolipid mass spectral simulator. MGMS2 software and its manual are freely available as an R package. An interactive MGSM2 app that helps users explore various simulation parameter options is also available.

RESULTS

We demonstrated the performance of MGSM2 using six microbes. The software generated in silico glycolipid mass spectra that are similar to real polymicrobial glycolipid mass spectra. The maximum correlation between in silico mass spectra generated by MGMS2 and the real polymicrobial mass spectrum was about 87%.

CONCLUSIONS

We anticipate that MGMS2, which considers spectrum-to-spectrum variation, will advance the bacterial algorithm development for polymicrobial samples.

Prevalence and Antibiotic Resistance Patterns of Ocular Bacterial Strains Isolated from Pediatric Patients in University Hospital of Campania “Luigi Vanvitelli,” Naples, Italy

Eye infections caused by bacteria are a serious public health problem among pediatric patients. These diseases, if not properly treated, can cause blindness and impaired vision. The study aimed to evaluate the antimicrobial resistance profiles of the main pathogens involved in eye infections. This study involved pediatric patients enrolled at the “Luigi Vanvitelli” University Hospital of Campania in Naples, Italy, between 2017 and 2019. Of a total of 228 pediatric patients, 73 (32%) tested positive for bacterial infection. In terms of strain distribution, 85% were Gram-positive bacteria, while 15% were Gram-negative bacteria. The most frequently isolated strains were coagulase-negative Staphylococci (60.4%), followed by Staphylococcus aureus (16.4%). The isolated bacteria showed a significant percentage of resistance to multiple antibiotics. Therefore, the identification of the causal bacteria and antimicrobial sensitivity tests are mandatory to select the effective drug for the treatment of eye infections and prevent the development of antibiotic-resistant bacteria.

Determination and Identification of Antibiotic Drugs and Bacterial Strains in Biological Samples

Antibiotics were initially natural substances. However, nowadays, they also include synthetic drugs, which show their activity against bacteria, killing or inhibiting their growth and division. Thanks to these properties, many antibiotics have quickly found practical application in the fight against infectious diseases such as tuberculosis, syphilis, gastrointestinal infections, pneumonia, bronchitis, meningitis and septicemia. Antibiotic resistance is currently a detrimental problem; therefore, in addition to the improvement of antibiotic therapy, attention should also be paid to active metabolites in the body, which may play an important role in exacerbating the existing problem. Taking into account the clinical, cognitive and diagnostic purposes of drug monitoring, it is important to select an appropriate analytical method that meets all the requirements. The detection and identification of the microorganism responsible for the infection is also an essential factor in the implementation of appropriate antibiotic therapy. In recent years, clinical microbiology laboratories have experienced revolutionary changes in the way microorganisms are identified. The MALDI-TOF MS technique may be interesting, especially in some areas where a quick analysis is required, as is the case with clinical microbiology. This method is not targeted, which means that no prior knowledge of the infectious agent is required, since identification is based on a database match.

Fast Pathogen Identification Using Single-Cell Matrix-Assisted Laser Desorption/Ionization-Aerosol Time-of-Flight Mass Spectrometry Data and Deep Learning Methods

In diagnostics of infectious diseases, matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry (MALDI-TOF MS) can be applied for the identification of pathogenic microorganisms. However, to achieve a trustworthy identification from MALDI-TOF MS data, a significant amount of biomass should be considered. The bacterial load that potentially occurs in a sample is therefore routinely amplified by culturing, which is a time-consuming procedure. In this paper, we show that culturing can be avoided by conducting MALDI-TOF MS on individual bacterial cells. This results in a more rapid identification of species with an acceptable accuracy. We propose a deep learning architecture to analyze the data and compare its performance with traditional supervised machine learning algorithms. We illustrate our workflow on a large data set that contains bacterial species related to urinary tract infections. Overall we obtain accuracies up to 85% in discriminating five different species.

Identification to species level of live single microalgal cells from plankton samples with matrix-free laser/desorption ionization mass spectrometry

INTRODUCTION

Marine planktonic communities are complex microbial consortia often dominated by microscopic algae. The taxonomic identification of individual phytoplankton cells usually relies on their morphology and demands expert knowledge. Recently, a live single-cell mass spectrometry (LSC-MS) pipeline was developed to generate metabolic profiles of microalgae.

OBJECTIVE

Taxonomic identification of diverse microalgal single cells from collection strains and plankton samples based on the metabolic fingerprints analyzed with matrix-free laser desorption/ionization high-resolution mass spectrometry.

METHODS

Matrix-free atmospheric pressure laser-desorption ionization mass spectrometry was performed to acquire single-cell mass spectra from collection strains and prior identified environmental isolates. The computational identification of microalgal species was performed by spectral pattern matching (SPM). Three similarity scores and a bootstrap-derived confidence score were evaluated in terms of their classification performance. The effects of high and low-mass resolutions on the classification success were evaluated.

RESULTS

Several hundred single-cell mass spectra from nine genera and nine species of marine microalgae were obtained. SPM enabled the identification of single cells at the genus and species level with high accuracies. The receiver operating characteristic (ROC) curves indicated a good performance of the similarity measures but were outperformed by the bootstrap-derived confidence scores.

CONCLUSION

This is the first study to solve taxonomic identification of microalgae based on the metabolic fingerprints of the individual cell using an SPM approach.

Adaption of the Aristotle Classifier for Accurately Identifying Highly Similar Bacteria Analyzed by MALDI-TOF MS

MALDI-TOF MS has shown great utility for rapidly identifying microbial species. It can be used to successfully type bacteria and fungi from a variety of sources more rapidly and cost-effectively than traditional methods. One area where improvements are necessary is in the typing of highly similar samples, such as those samples from the same genus but different species or samples from within a single species but from different strains. One promising way to address this current limitation is by using advanced machine learning techniques. In this work, we adapt a newly developed machine learning tool, the Aristotle Classifier, to bacterial classification of MALDI-TOF MS data. This tool was originally developed for classifying glycomics and glycoproteomics data, so we modified it to be well-suited for assigning mass spectral data from bacterial proteins. The classifier exceeds existing benchmarks in classifying bacteria, and it shows particularly strong performance when the samples to be identified are highly similar. The combination of mass spectrometry data and tools like the Aristotle Classifier could ameliorate the ambiguities associated with challenging bacterial classification problems.

Rapid identification of respiratory bacterial pathogens from bronchoalveolar lavage fluid in cattle by MALDI-TOF MS

Respiratory tract infections are a major health problem and indication for antimicrobial use in cattle and in humans. Currently, most antimicrobial treatments are initiated without microbiological results, holding the risk of inappropriate first intention treatment. The main reason for this empirical treatment is the long turnaround time between sampling and availability of identification and susceptibility results. Therefore the objective of the present study was to develop a rapid identification procedure for pathogenic respiratory bacteria in bronchoalveolar lavage fluid (BALf) samples from cattle by MALDI-TOF MS, omitting the cultivation step on agar plates to reduce the turnaround time between sampling and identification of pathogens. The effects of two different liquid growth media and various concentrations of bacitracin were determined to allow optimal growth of Pasteurellaceae and minimise contamination. The best procedure was validated on 100 clinical BALf samples from cattle with conventional bacterial culture as reference test. A correct identification was obtained in 73% of the samples, with 59.1% sensitivity (Se) (47.2–71.0%) and 100% specificity (Sp) (100–100%) after only 6 hours of incubation. For pure and dominant culture samples, the procedure was able to correctly identify 79.2% of the pathogens, with a sensitivity (Se) of 60.5% (45.0–76.1%) and specificity (Sp) of 100% (100–100%). In mixed culture samples, containing ≥2 clinically relevant pathogens, one pathogen could be correctly identified in 57% of the samples with 57.1% Se (38.8–75.5%) and 100% Sp (100–100%). In conclusion, MALDI-TOF MS is a promising tool for rapid pathogen identification in BALf. This new technique drastically reduces turnaround time and may be a valuable decision support tool to rationalize antimicrobial use.

Monitoring of Bactericidal Effects of Silver Nanoparticles Based on Protein Signatures and VOC Emissions from Escherichia coli and Selected Salivary Bacteria

Escherichia coli and salivary Klebsiella oxytoca and Staphylococcus saccharolyticus were subjected to different concentrations of silver nanoparticles (AgNPs), namely: 12.5, 50, and 100 µg mL-1. Matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry (MALDI-TOF MS) spectra were acquired after specified periods: 0, 1, 4, and 12 h. For study of volatile metabolites, headspace solid-phase microextraction coupled to gas chromatography/mass spectrometry (HS-SPME-GC-MS) was employed-AgNPs were added to bacteria cultures and the headspace was analyzed immediately and after 12 h of incubation. Principal components analysis provided discrimination between clusters of protein profiles belonging to different strains. Canonical correlation, network analysis, and multiple linear regression approach revealed that dimethyl disulfide, dimethyl trisulfide, 2-heptanone, and dodecanal (related to the metabolism of sulfur-containing amino acids and fatty acids synthesis) are exemplary molecular indicators, whose response variation deeply correlated to the interaction with bacteria. Therefore, such species can serve as biomarkers of the agent's effectiveness. The present investigation pointed out that the used approaches can be useful in the monitoring of response to therapeutic treatment based on AgNPs. Furthermore, biochemical mechanisms enrolled in the bactericidal action of nanoparticles can be applied in the development of new agents with enhanced properties.

Identification performance of MALDI-ToF-MS upon mono- and bi-microbial cultures is cell number and culture proportion dependent

Biotyping using matrix-assisted laser desorption ionization-time of flight (MALDI-ToF) mass spectroscopy (MS) has revolutionized microbiology by allowing clinicians and scientists to rapidly identify microbes at genus and species levels. The present study extensively assesses the suitability and reliability of MALDI-ToF biotyping of 14 different aerobic and anaerobic bacterial species as pure and mixed cultures. Reliable identification at species level was possible from biomaterial of older colonies and even frozen biomaterial, although this was species dependent. Using standard instrument settings and direct application of biomaterial onto the MALDI-ToF target plates, it was determined that the cell densities necessary for completely reliable identification of pure cultures varied between 2.40 × 10⁸ and 1.10 × 10¹⁰ viable cell counts (VCCs) per mL, depending on the species. Evaluation of the mixed culture algorithm of the Bruker Biotyper^® software showed that the performance of the algorithm depends greatly on the targeted species, on their phylogenetic distance, and on their ratio of VCC per mL in the mixed culture. Hence, the use of MALDI-ToF-MS with incorporation of the mixed culture algorithm of the software is a useful pre-screening tool for early identification of contaminants, but due to the great variability in performance between different species and the usually unknown percentage of the possible contaminant in the mixture, it is advisable to combine this method with other microbiology methods.

An update on the routine application of MALDI-TOF MS in clinical microbiology

Introduction: Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) has entered clinical diagnostics and is today a generally accepted and integral part of the workflow for microbial identification. MALDI-TOF MS identification systems received approval from national and international institutions, such as the USA-FDA, and are continuously improved and adopted to other fields like veterinary and industrial microbiology. The question is whether MALDI-TOF MS also has the potential to replace other conventional and molecular techniques operated in routine diagnostic laboratories. Areas covered: We give an overview of new advancements of mass spectral analysis in the context of microbial diagnostics. In particular, the expansion of databases to increase the range of readily identifiable bacteria and fungi, the refined discrimination of species complexes, subspecies, and types, the testing for antibiotic resistance or susceptibility, progress in sample preparation including automation, and applications of other mass spectrometry techniques are discussed. Expert opinion: Although many new approaches of MALDI-TOF MS are still in the stage of proof of principle, it is expectable that MALDI-TOF MS will expand its role in the clinical microbiology laboratory of the future. New databases, instruments and analytical software modules will continue to be developed to further improve diagnostic efficacy.

MALDI-TOF mass spectrometry as a diagnostic tool in human and veterinary helminthology: a systematic review

BACKGROUND

Matrix-assisted laser desorption/ionization-time of flight (MALDI-TOF) mass spectrometry (MS) has become a widely used technique for the rapid and accurate identification of bacteria, mycobacteria and certain fungal pathogens in the clinical microbiology laboratory. Thus far, only few attempts have been made to apply the technique in clinical parasitology, particularly regarding helminth identification.

METHODS

We systematically reviewed the scientific literature on studies pertaining to MALDI-TOF MS as a diagnostic technique for helminths (cestodes, nematodes and trematodes) of medical and veterinary importance. Readily available electronic databases (i.e. PubMed/MEDLINE, ScienceDirect, Cochrane Library, Web of Science and Google Scholar) were searched from inception to 10 October 2018, without restriction on year of publication or language. The titles and abstracts of studies were screened for eligibility by two independent reviewers. Relevant articles were read in full and included in the systematic review.

RESULTS

A total of 84 peer-reviewed articles were considered for the final analysis. Most papers reported on the application of MALDI-TOF for the study of Caenorhabditis elegans, and the technique was primarily used for identification of specific proteins rather than entire pathogens. Since 2015, a small number of studies documented the successful use of MALDI-TOF MS for species-specific identification of nematodes of human and veterinary importance, such as Trichinella spp. and Dirofilaria spp. However, the quality of available data and the number of examined helminth samples was low.

CONCLUSIONS

Data on the use of MALDI-TOF MS for the diagnosis of helminths are scarce, but recent evidence suggests a potential role for a reliable identification of nematodes. Future research should explore the diagnostic accuracy of MALDI-TOF MS for identification of (i) adult helminths, larvae and eggs shed in faecal samples; and (ii) helminth-related proteins that are detectable in serum or body fluids of infected individuals.

Rapid dereplication of microbial isolates using matrix-assisted laser desorption ionization time-of-flight mass spectrometry: A mini-review

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MALDI-TOF MS is applicable as high-resolution and high-throughput tool.

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The classification and characterization of cultivable microorganisms is targeted.

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Advantageous are its simple sample preparation and short measurement time.

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It accelerates the dereplication of isolates from large-scale screening campaigns.

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Applications for studying microbial diversity and future trends are discussed.

Matrix-Assisted Laser Desorption Ionization Time-Of-Flight Mass Spectrometry (MALDI-TOF MS) has become one of the most popular methods for the rapid, cost-effective and accurate classification and characterization of cultivable microorganisms. Due to its simple sample preparation and short measurement time, MALDI-TOF MS is an excellent choice for the high-throughput study of microbial isolates from rhizospheres or plants grown under diverse environmental conditions. While clinical isolates have a higher identification rate than environmental isolates due to the focus of commercial mass spectral libraries on the former, no identification is necessary in the dereplication step of large environmental studies. The grouping of large sets of isolates according to their intact protein profiles can be performed without knowledge of their taxonomy. Thus, this method is easily applicable to environmental samples containing microorganisms from yet undescribed phylogenetic origins. The main strategies applied to achieve effective dereplication are, first, expanding existing mass spectral libraries and, second, using an additional statistical analysis step to group measured mass spectra and identify unique isolates. In this review, these aspects are addressed. It closes with a prospective view on how MALDI-TOF MS-based microbial characterisation can accelerate the exploitation of plant-associated microbiota.