FTIR-assisted MALDI-TOF MS for the identification and typing of bacteria

Chromatographic and spectroscopic methods for the detection of cocoa butter in cocoa and its derivatives: A review

Currently, there is fierce competition in the cocoa industry to develop products that possess distinctive sensory characteristics and flavours. This is because cocoa and its derivatives provide numerous health and functional advantages, which is essential to their economics. The fatty acid and triglyceride composition of cocoa determines its quality. This review emphasises the necessity of developing precise, adaptable analytical techniques to identify and quantify cocoa butter in cocoa and its derived products, from cocoa beans to chocolate bars. Key chromatographic and spectroscopic techniques play crucial roles in understanding the fundamental principles underlying the production of cocoa with desirable flavours. This significantly impacts the sustainability, traceability, and authenticity of cocoa products while also supporting the battle against adulteration.

MALDI glycotyping of O-antigens from a single colony of gram-negative bacteria

Polypeptide-targeted MALDI-TOF MS for microbial species identification has revolutionized microbiology. However, no practical MALDI-TOF MS identification method for O-antigen polysaccharides, a major indicator for epidemiological classification within a species of gram-negative bacteria, is available. We describe a simple MALDI glycotyping method for O-antigens that simultaneously identifies the molecular mass of the repeating units and the monosaccharide composition of the O-antigen. We analyzed the Escherichia coli O1, O6, and O157-type strains. Conventional species identification based on polypeptide patterns and O-antigen polysaccharide typing can be performed in parallel from a single colony using our MALDI-TOF MS workflow. Moreover, subtyping within the same O-antigen and parallel colony-specific O-antigen determination from mixed strains, including the simultaneous identification of multiple strains-derived O-antigens within selected colony, were performed. In MALDI glycotyping of two Enterobacteriaceae strains, a Citrobacter freundii strain serologically cross-reactive with E. coli O157 gave a MALDI spectral pattern identical to E. coli O157. On the other hand, an Edwardsiella tarda strain with no reported O-antigen cross-reactivity gave a MALDI spectral pattern of unknown O-antigen repeating units. The method described in this study allows the parallel and rapid identification of microbial genera, species, and serotypes of surface polysaccharides using a single MALDI-TOF MS instrument.

Development of a machine learning model for systematics of Aspergillus section Nigri using synchrotron radiation-based fourier transform infrared spectroscopy

Aspergillus section Nigri (black aspergilli) fungi are economically important food spoilage agents. Some species in this section also produce harmful mycotoxins in food. However, it is remarkably difficult to identify this fungal group at the species level using morphological and chemical characteristics. The molecular approach for classification is preferable; however, it is time-consuming, making it inappropriate for rapid testing of large numbers of samples. To address this, we explored synchrotron radiation-based Fourier transform infrared microspectroscopy (SR-FTIR) as a rapid method for obtaining data suitable for species classification. SR-FTIR data were obtained from the mycelia/conidia of 22 black aspergilli species. The Convolutional Neural Network (CNN) approach, a supervised deep learning algorithm, was used with SR-FTIR data to classify black aspergilli at the species level. A subset of the data was used to train the CNN model, and the model classification performance was evaluated using the validation data subsets. The model demonstrated a 95.97% accuracy in species classification on the testing (blind) data subset. The technique presented herein could be an alternative method for identifying problematic black aspergilli in the food industry.

Detection limit of FT-IR-based bacterial typing based on optimized sample preparation and typing model

Accurate and efficient bacterial typing methods are crucial to microbiology. Fourier transform infrared (FT-IR) spectroscopy enables highly distinguishable fingerprint identification of closely related bacterial strains by producing highly specific fingerprints of bacteria, which is increasingly being considered as an alternative to genotypic methods, such as pulsed field gel electrophoresis (PFGE) and whole genome sequencing (WGS), for bacterial typing. Compared with genotypic methods, FT-IR has significant advantages of convenient operation, fast speed, and low cost. Fundamental research into the detection limit based on optimized analytical conditions for FT-IR bacterial typing, which can avoid excessive bacterial culture time or sampling volume, is particularly important, especially in clinical practice. However, the corresponding parameters have not been fully investigated. In this study, we developed a simplified and reliable procedure for sample preparation, optimized the data analysis procedure, and evaluated the FT-IR detection limit based on the above conditions. In particular, we combined the film mold and calcium fluoride plate for sample preparation. We evaluated the detection limit (about 108 CFU/mL) after parameter optimization using hierarchical cluster analysis (HCA) and artificial neural network (ANN). The optimization and evaluation of these key fundamentals will better promote future application of FT-IR-based bacterial typing.

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

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

Applications of Fourier Transform-Infrared spectroscopy in microbial cell biology and environmental microbiology: advances, challenges, and future perspectives

Microorganisms play pivotal roles in shaping ecosystems and biogeochemical cycles. Their intricate interactions involve complex biochemical processes. Fourier Transform-Infrared (FT-IR) spectroscopy is a powerful tool for monitoring these interactions, revealing microorganism composition and responses to the environment. This review explores the diversity of applications of FT-IR spectroscopy within the field of microbiology, highlighting its specific utility in microbial cell biology and environmental microbiology. It emphasizes key applications such as microbial identification, process monitoring, cell wall analysis, biofilm examination, stress response assessment, and environmental interaction investigation, showcasing the crucial role of FT-IR in advancing our understanding of microbial systems. Furthermore, we address challenges including sample complexity, data interpretation nuances, and the need for integration with complementary techniques. Future prospects for FT-IR in environmental microbiology include a wide range of transformative applications and advancements. These include the development of comprehensive and standardized FT-IR libraries for precise microbial identification, the integration of advanced analytical techniques, the adoption of high-throughput and single-cell analysis, real-time environmental monitoring using portable FT-IR systems and the incorporation of FT-IR data into ecological modeling for predictive insights into microbial responses to environmental changes. These innovative avenues promise to significantly advance our understanding of microorganisms and their complex interactions within various ecosystems.

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.

One-step genotyping of α-thalassaemia by multiplex symmetric PCR melting curve

AIMS

Alpha-thalassaemia is one of the most common monogenic disorders worldwide. Due to high guanine-cytosine (GC) content and high mutation diversity in α-globin gene cluster, deletional and non-deletional mutations were usually separately detected with different methods. The aim of this study was to develop a novel one-step method for α-thalassaemia genotyping.

METHODS

A multiplex symmetric PCR melting curve strategy was designed for one-step α-thalassaemia genotyping. Based on this strategy, a novel method was developed to simultaneously detect four common deletional (-α3.7 , -α4.2 , _ _SEA , --THAI ) and five common non-deletional (αCD30(-GAG)α, αCD31(G>A)α, αWSα, αQSα, αCSα) α-thalassaemia mutations in a closed-tube reaction. This method was also evaluated by double-blind detection of 235 genotype-known samples and 1630 clinical samples.

RESULTS

All nine α-thalassaemia mutations could be accurately identified by this novel method within 3 hours. The evaluation results also showed a 100% concordance with comparison methods.

CONCLUSIONS

This method is rapid, accurate, low-cost and easy to operate, which can be used for molecular screening and genetic diagnosis of α-thalassaemia in clinical practice. The multiplex symmetric PCR melting curve strategy designed in this study can also provide an effective approach to the method development for high GC content templates and multiple mutations.

Single-cell rapid identification, in situ viability and vitality profiling, and genome-based source-tracking for probiotics products

Rapid expansion of the probiotics industry demands fast, sensitive, comprehensive, and low-cost strategies for quality assessment. Here, we introduce a culture-free, one-cell-resolution, phenome-genome-combined strategy called Single-Cell Identification, Viability and Vitality tests, and Source-tracking (SCIVVS). For each cell directly extracted from the product, the fingerprint region of D2O-probed single-cell Raman spectrum (SCRS) enables species-level identification with 93% accuracy, based on a reference SCRS database from 21 statutory probiotic species, whereas the C-D band accurately quantifies viability, metabolic vitality plus their intercellular heterogeneity. For source-tracking, single-cell Raman-activated Cell Sorting and Sequencing can proceed, producing indexed, precisely one-cell-based genome assemblies that can reach ~99.40% genome-wide coverage. Finally, we validated an integrated SCIVVS workflow with automated SCRS acquisition where the whole process except sequencing takes just 5 h. As it is >20-fold faster, >10-time cheaper, vitality-revealing, heterogeneity-resolving, and automation-prone, SCIVVS is a new technological and data framework for quality assessment of live-cell products.

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.

Antioxidant and antimicrobial characteristics of ethyl acetate polar fractions from walnut green husk

Walnut green husk (WGH) is rich in natural compounds and is valued as a potential source of antioxidant and antimicrobial properties. In this study, the antioxidant and antimicrobial activities of petroleum ether polar fraction, dichloromethane polar fraction, ethyl acetate polar fraction (EAPF), and n-butanol polar fraction from WGH were analyzed. The results showed that EAPF exhibited the highest total flavonoid content (65.74 ± 1.01 mg rutin equivalents [RE]/g dry weight [DW]) and total phenol content (48.73 ± 1.09 mg gallic acid equivalent [GAE]/g DW), with the highest 2,2-diphenyl-1-picrylhydrazyl, hydroxyl radical (•OH), and 2,2-azino-bis-3-ethylbenzothiazoline-6-sulfonate scavenging activity compared with other fractions. EAPF also showed good antibacterial activity against Escherichia coli and Bacillus cereus vegetative cells, with a diameter of inhibition zones of 33.5 and 37.6 mm, respectively, a minimum inhibitory concentration of 31.25 mg/ml and a minimum bactericidal concentration of 62.5 mg/ml, which inhibited the growth of both bacteria. Analysis of the antibacterial mechanism demonstrated that EAPF damaged the integrity of the cell membrane, increased the membrane permeability, and triggered the leakage of intracellular material. In addition, ultrahigh performance liquid chromatography-tandem with mass spectrometry analysis revealed that 8 polyphenols and 14 flavonoids were mainly present in EAPF, such as chlorogenic acid (C₁₆ H₁₈ O₉ ), gallic acid (C₇ H₆ O₅ ), vanillic acid (C₈ H₈ O₄ ), ferulic acid (C₁₀ H₁₀ O₄ ), epicatechin (C₁₅ H₁₄ O₆ ), catechin (C₁₅ H₁₄ O₆ ), hesperetin (C₁₆ H₁₄ O₆ ), naringenin (C₁₅ H₁₂ O₅ ), hyperin (C₂₁ H₂₀ O₁₂ ), luteolin (C1₅ H₁₀ O₆ ), and so on. Therefore, WGH had the potential to be developed as a natural antioxidant and antibacterial material. PRACTICAL APPLICATION: Our work indicates that WGH contains abundant flavonoids and polyphenols compounds. Therefore, the plant byproducts like WGH may have a promising application as a source of antimicrobial and antioxidant additives.

Exosomes in sarcoma: Prospects for clinical applications

Sarcoma is a group of rare and heterogeneous mesenchymal tumors, prone to late diagnosis and poor prognosis. Exosomes are cell-derived small extracellular vesicles found in most body fluids and contain nucleic acids, proteins, lipids, and other molecules. Qualitative and quantitative changes of exosomes and the contents are associated with sarcoma progression, exhibiting their potential as biomarkers. Exosomes possess the capacity of evading immune responses, bioactivity for trafficking, tumor tropism, and lesion residence. Thus, exosomes could be engineered as tumor-specific vehicles in drugs and RNA delivery systems. Exosomes might also serve as therapeutic targets in targeted therapy and immunotherapy and be involved in chemotherapy resistance. Here, we provide a comprehensive summary of exosome applications in liquid biopsy-based diagnosis and explore their implications in the delivery system, targeted therapy, and chemotherapy resistance of sarcoma. Moreover, challenges in exosome clinical applications are raised and some future research directions are proposed.

Evaluation of Proteomic and Lipidomic Changes in Aeromonas-Infected Trout Kidney Tissue with the Use of FT-IR Spectroscopy and MALDI Mass Spectrometry Imaging

Aeromonas species are opportunistic bacteria causing a vast spectrum of human diseases, including skin and soft tissue infections, meningitis, endocarditis, peritonitis, gastroenteritis, and finally hemorrhagic septicemia. The aim of our research was to indicate the molecular alterations in proteins and lipids profiles resulting from Aeromonas sobria and A. salmonicida subsp. salmonicida infection in trout kidney tissue samples. We successfully applied FT-IR (Fourier transform infrared) spectroscopy and MALDI-MSI (matrix-assisted laser desorption/ionization mass spectrometry imaging) to monitor changes in the structure and compositions of lipids, secondary conformation of proteins, and provide useful information concerning disease progression. Our findings indicate that the following spectral bands’ absorbance ratios (spectral biomarkers) can be used to discriminate healthy tissue from pathologically altered tissue, for example, lipids (CH2/CH3), amide I/amide II, amide I/CH2 and amide I/CH3. Spectral data obtained from 10 single measurements of each specimen indicate numerous abnormalities concerning proteins, lipids, and phospholipids induced by Aeromonas infection, suggesting significant disruption of the cell membranes. Moreover, the increase in the content of lysolipids such as lysophosphosphatidylcholine was observed. The results of this study suggest the application of both methods MALDI-MSI and FT-IR as accurate methods for profiling biomolecules and identifying biochemical changes in kidney tissue during the progression of Aeromonas infection.

Efficient classification of Escherichia coli and Shigella using FT-IR spectroscopy and multivariate analysis

Accurate and effective discrimination of E. coli and Shigella is an important clinical issue, and there are many limitations in traditional methods of analysis. FT-IR shows great potential in the classification of bacteria with high specificity and low cost. In this study, we evaluated the efficiency of this technique when combined with multivariate analysis for rapid classification of E. coli and Shigella, which is difficult using traditional analytical methods. Machine learning and statistical tools were employed in combination with FT-IR to classify 14 E. coli and 9 Shigella strains. The classification accuracies for select E. coli and Shigella strains from blood agar were 0.7826, 0.8696, and 0.9565 at the genus, species, and strain levels, respectively. In addition, we used the FT-IR data of select strains from three different culture media for cross-validation, yielding an accuracy of 0.3681 at the strain level. These results indicate that the bacterial culture conditions have a significant impact on the FT-IR patterns. Based on this, an improved strategy for training an ensemble classifier model considering bacterial culture factors was constructed, resulting in almost perfect separation with an accuracy of 0.9394 for strain-level classification. These results show the potential of FT-IR combined with multivariate analysis for more reliable bacterial classification.

Fast detection of bacterial contamination in fresh produce using FTIR and spectral classification

Screening for microbial contaminants in fresh produce is a lengthy process relative to their short shelf-life. The aim of this study is to develop a comprehensive assay which employs FTIR and spectral classification algorithm for detection of bacterial contamination of fresh produce. The procedure starts by soaking a sample of the fresh produce in broth for 5 h. Then, magnetic nanoparticles are added to capture bacteria which are then collected and prepared for FTIR scanning. The generated FTIR spectra are compared against an in-house database of different bacterial species (n = 6). The ability of the database to discriminate contaminated and uncontaminated samples and to identify the bacterial species was assessed. The compatibility of the FTIR procedures with subsequent DNA extraction and PCR was tested. The developed procedure was applied for assessment of bacterial contamination in fresh produce samples from the market (n = 78). Results were compared to the conventional culture methods. The generated FTIR database coupled to spectral classification was able to detect bacterial contamination with overall accuracy exceeding 90%. The sample processing did not alter the integrity of the bacterial DNA which was suitable for PCR. On application to fresh produce samples collected from the market, the developed method was able to detect bacterial contamination with 94% concordance with the culture method. In conclusion, the developed procedure can be applied for fast detection of microbial contamination in fresh produce with comparable accuracy to conventional microbiological assays and is compatible with subsequent molecular assays.

In situ imaging for tumor microbiome interactions via imaging mass cytometry on single-cell level

Co-detection of multiplex cancer subtypes and bacteria subtypes in situ is crucial for understanding tumor microbiome interactions in tumor microenvironment. Current standard techniques such as immunohistochemical staining and immunofluorescence staining are limited for their multiplicity. Simultaneously visualizing detailed cell subtypes and bacteria distribution across the same pathological section remains a major technical challenge. Herein, we developed a rapid semi-quantitative method for in situ imaging of bacteria and multiplex cell phenotypes on the same solid tumor tissue sections. We designed a panel of antibody probes labeled with mass tags, namely prokaryotic and eukaryotic cell hybrid probes for in situ imaging (PEHPSI). For application demonstration, PEHPSI stained two bacteria subtypes (lipopolysaccharides (LPS) for Gram-negative bacteria and lipoteichoic acid (LTA) for Gram-positive bacteria) simultaneously with four types of immune cells (leukocytes, CD8+T-cells, B-cells and macrophages) and four breast cancer subtypes (classified by a panel of 12 human proteins) on the same tissue section. We unveiled that breast cancer cells are commonly enriched with Gram-negative bacteria and almost absent of Gram-positive bacteria, regardless of the cancer subtypes (triple-negative breast cancer (TNBC), HER2+, Luminal A and Luminal B). Further analysis revealed that on the single-cell level, Gram-negative bacteria have a significant correlation with CD8+T-cells only in HER2+ breast cancer, while PKCD, ER, PR and Ki67 are correlated with Gram-negative bacteria in the other three subtypes of breast cancers. On the cell population level, in TNBC, CD19 expression intensity is up-regulated by approximately 25% in bacteria-enriched cells, while for HER2+, Luminal A and Luminal B breast cancers, the intensity of biomarkers associated with the malignancy, metastasis and proliferation of cancer cells (PKCD, ISG15 and IFI6) is down-regulated by 29-38%. The flexible and expandable PEHPSI system permits intuitive multiplex co-visualization of bacteria and mammalian cells, which facilitates future research on tumor microbiome and tumor pathogenesis. This article is protected by copyright. All rights reserved.

Capture and identification of bacteria from fish muscle based on immunomagnetic beads and MALDI-TOF MS

•

A protocol for the bacterial analysis in fish muscle was developed.

•

Anti-bacterial antibodies modified magnetic beads (MBs) were used to capture bacteria.

•

The bacterial identification accuracy from different complex food matrices was good.

•

The presence of 10 CFU/mL E. coli is still detectable.

•

It is promising to be applied in bacterial analysis to ensure muscle food safety.

In the present study, E. coli was taken as a model bacterium, anti-E. coli functionalized magnetic beads were constructed and used to capture E. coli from aqueous extracts of fish sarcoplasmic protein (FSP) and fish muscle protein of sablefish. The excellency of the reproducibility of the present protocol was demonstrated by capturing E. coli from sablefish FSP extracts. The presence of 10 CFU/mL E. coli is still detectable. A microbial safety test on the surface of fish muscle was successfully performed. The bacterial identification accuracy from samples with different matrices was found to be excellent with RSD = 3%. High specific detection of target bacteria in complex biological samples was testified by spiking Staphylococcus aureus and Klebsiella pneumoniae in samples as interference. Ten biomarker ions were discovered for E. coli’s recognition. It is promising to apply the present protocol in bacterial analysis in muscle food samples to ensure their safety.

Investigation and Identification of Food Poisoning Caused by Clostridium botulinum Type B1 in Shenzhen, China

Clostridium botulinum produces botulinum neurotoxins (BoNTs), which cause people who ingest them to become seriously ill and sometimes die. In recent years, sporadic food poisoning cases associated with C. botulinum have occurred across the world. In 2016, two men were admitted to our hospital in Shenzhen, China, with foodborne botulism. In this study, we report on these two typical C. botulinum-related food poisoning incidents and the steps taken to identify and characterize the causative pathogen. We characterized the bacterial pathogen isolated from the first patient using cooked meat medium and egg yolk agar bacterial cultures under anaerobic conditions, and morphologically identified the isolate using Gram staining. The in vivo bioassay results in mice showed that the minimum lethal dose of the BoNTs produced by our isolate was 0.001-0.0001 mg/mL (LD50 of the culture was estimated to be 1.5812 mg/kg). Whole genome sequencing (WGS) results showed that the isolate was identified as C. botulinum B1 Okra. The causative strain was successfully isolated from the intestinal lavage fluid collected from the initial patient.

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.

Diagnosis of Lung Cancer by FTIR Spectroscopy Combined With Raman Spectroscopy Based on Data Fusion and Wavelet Transform

Lung cancer is a fatal tumor threatening human health. It is of great significance to explore a diagnostic method with wide application range, high specificity, and high sensitivity for the detection of lung cancer. In this study, data fusion and wavelet transform were used in combination with Fourier transform infrared (FTIR) spectroscopy and Raman spectroscopy to study the serum samples of patients with lung cancer and healthy people. The Raman spectra of serum samples can provide more biological information than the FTIR spectra of serum samples. After selecting the optimal wavelet parameters for wavelet threshold denoising (WTD) of spectral data, the partial least squares–discriminant analysis (PLS-DA) model showed 93.41% accuracy, 96.08% specificity, and 90% sensitivity for the fusion data processed by WTD in the prediction set. The results showed that the combination of FTIR spectroscopy and Raman spectroscopy based on data fusion and wavelet transform can effectively diagnose patients with lung cancer, and it is expected to be applied to clinical screening and diagnosis in the future.

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.

Fast label-free identification of bacteria by synchronous fluorescence of amino acids

Fast identification of pathogenic bacteria is an essential need for patient's diagnostic in hospitals and environmental monitoring of water and air quality. Bacterial cells consist of a very high amount of biological molecules whose content changes in response to different environmental conditions. The similarity between the molecular compositions of different bacterial cells limits the possibility to find unique markers to enable differentiation among species. Although many biological molecules in the cells absorb at the UV-Vis region, only a few of them can be detected in whole cells by their intrinsic fluorescence. Among these molecules are the amino acids phenylalanine, tyrosine, and tryptophan. In this work, we develop a rapid method for bacterial identification by synchronous fluorescence. We show that we can quantify the concentration for the 3 amino acids without any significant interference from other fluorophores in the cells and that we can differentiate among 6 pathogenic bacterial species by using the concentrations of their amino acids as a bacterial fingerprint. Fluorescent amino acids exist in all living cells. Therefore, this method has the potential to be applicative for the rapid identification of cells from all kinds of organisms.

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.

A multiplex bacterial assay using an element-labeled strategy for 16S rRNA detection

A multiplex bacterial assay method that combines S1 nuclease pretreatment and ICP-MS-based elemental labels is presented in this work. Six intestinal related bacteria were identified at the species level and quantified simultaneously without isolation culturing. This method could be extended to assay a mixed bacterial community for point-of-care diagnosis.

Rapid identification of bacteria directly from blood cultures by Co-magnetic bead enrichment and MALDI-TOF MS profiling

Direct identification of bacteria in blood cultures using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) is interfered with by a variety of non-bacterial proteins derived from blood cells and culture media. Thus, appropriate pre-treatments are needed for successful identification. Here, the bacteria in blood culture bottles were enriched using co-magnetic beads and processed for MALDI-TOF MS profiling. In this strategy, the Fc-containing mannose-binding lectin-coated Fe₃O₄ (Fc-MBL@Fe₃O₄) is incorporated with human IgG-coated Fe₃O₄ (IgG@Fe₃O₄) to form co-magnetic beads, which can recognize both Gram-positive and Gram-negative bacteria. Compared to single magnetic beads Fc-MBL@Fe₃O₄ or IgG@Fe₃O₄, co-magnetic beads resulted in better bacterial capture efficiency and, therefore, could decrease the false-negative results. Our proposed strategy is much more suitable for enrichment of clinically unknown bacteria from blood culture bottles for MALDI-TOF MS database identification.

Application of MALDI-TOF MS Profiling Coupled With Functionalized Magnetic Enrichment for Rapid Identification of Pathogens in a Patient With Open Fracture

Posttraumatic infections can occur in orthopedic trauma patients, especially in open fractures. Rapid and accurate identification of pathogens in orthopedic trauma is important for clinical diagnosis and antimicrobial treatment. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) has been successfully used for first-line identification of pathogens grown on culture plates. However, for direct analysis of liquid clinical specimens, pre-purification of the sample is necessary. Herein, we investigated the feasibility of coupling Fc-MBL@Fe₃O₄ enrichment with MALDI-TOF MS profiling in the identification of pathogens in liquid-cultured samples. This method is successfully used for the identification of pathogens in a patient with an open-leg fracture obtained at sea. Pathogens were enriched by Fc-MBL@Fe₃O₄ from briefly pre-cultured liquid media and identified by MALDI-TOF MS. We identified an opportunistic pathogen, Vibrio alginolyticus, which is uncommon in clinical orthopedic trauma infection but exists widely in the sea. Therefore, combining Fc-MBL@Fe₃O₄ enrichment and MALDI-TOF MS profiling has great potential for direct identification of microbes in clinical samples.

Rapid detection and discrimination of food-related bacteria using IR-microspectroscopy in combination with multivariate statistical analysis

Spoilage microorganisms are of great concern for the food industry. While traditional culturing methods for spoilage microorganism detection are laborious and time-consuming, the development of early detection methods has gained a lot of interest in the last decades. In this work a rapid and non-destructive detection and discrimination method of eight important food-related microorganisms (Bacillus subtilis DSM 10, Bacillus coagulans DSM 1, Escherichia coli K12 DSM 498, Escherichia coli TOP10, Micrococcus luteus DSM 20030, Pseudomonas fluorescens DSM 4358, Pseudomonas fluorescens DSM 50090 and Bacillus thuringiensis israelensis DSM 5724) based on IR-microspectroscopy and chemometric evaluation was developed. Sampling was carried out directly from the surface to be tested, without the need for sample preparation such as purification, singulation, centrifugation and washing steps, as an efficient and inexpensive blotting technique using the sample carrier. IR spectra were recorded directly after the blotting from the surface of the sample carrier without any further pretreatments. A combination of data preprocessing, principal component analysis and canonical discriminant analysis was found to be suitable. The spectral range from 400 to 1750 cm^-1 of the IR-microspectrosopic data was determined to be highly sensitive to the time after incubation and sample thickness, resulting in a high standard deviation. Therefore, this area was excluded from the evaluation in favor of the meaningfulness of the chemometric model and, thus, only the spectral range of specific -CH/-NH/-OH excitations (2815-3680 cm^-1) was used for model development. This study showed that the differentiation of food-related microorganisms on genera, species and strain level is feasible. A leave-one-out cross-validation of the training data set showed 100% accuracy. The classification of the ungrouped test data showed with an accuracy of 94.5% that, despite the large biological variance of the analytes such as different times after incubation and the presented sampling (including its variance), a robust and meaningful model for the differentiation of food-related bacteria could be developed by data preprocessing and subsequent chemometric evaluation.

Evaluation of MALDI-TOF Mass Spectrometry in Diagnostic and Environmental Surveillance of Legionella Species: A Comparison With Culture and Mip-Gene Sequencing Technique

Legionella spp. are widespread bacteria in aquatic environments with a growing impact on human health. Between the 61 species, Legionella pneumophila is the most prevalent in human diseases; on the contrary, Legionella non-pneumophila species are less detected in clinical diagnosis or during environmental surveillance due to their slow growth in culture and the absence of specific and rapid diagnostic/analytical tools. Reliable and rapid isolate identification is essential to estimate the source of infection, to undertake containment measures, and to determine clinical treatment. Matrix-assisted laser desorption ionization–time-of-flight mass spectrometry (MALDI–TOF MS), since its introduction into the routine diagnostics of laboratories, represents a widely accepted method for the identification of different bacteria species, described in a few studies on the Legionella clinical and environmental surveillance. The focus of this study was the improvement of MALDI–TOF MS on Legionella non-pneumophila species collected during Legionella nosocomial and community surveillance. Comparative analysis with cultural and mip-gene sequencing results was performed. Moreover, a phylogenetic analysis was carried out to estimate the correlations amongst isolates. MALDI–TOF MS achieved correct species-level identification for 45.0% of the isolates belonging to the Legionella anisa, Legionella rubrilucens, Legionella feeleii, and Legionella jordanis species, displaying a high concordance with the mip-gene sequencing results. In contrast, less reliable identification was found for the remaining 55.0% of the isolates, corresponding to the samples belonging to species not yet included in the database. The phylogenetic analysis showed relevant differences inside the species, regruped in three main clades; among the Legionella anisa clade, a subclade with a divergence of 3.3% from the main clade was observed. Moreover, one isolate, identified as Legionella quinlivanii, displayed a divergence of 3.8% from the corresponding reference strain. However, these findings require supplementary investigation. The results encourage the implementation of MALDI–TOF MS in routine diagnostics and environmental Legionella surveillance, as it displays a reliable and faster identification at the species level, as well as the potential to identify species that are not yet included in the database. Moreover, phylogenetic analysis is a relevant approach to correlate the isolates and to track their spread, especially in unconventional reservoirs, where Legionella prevention is still underestimated.

Discrimination of bacteria using whole organism fingerprinting: the utility of modern physicochemical techniques for bacterial typing

This review compares and contrasts MALDI-MS, FT-IR spectroscopy and Raman spectroscopy for whole organism fingerprinting and bacterial typing.

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.

Identification and dereplication of endophytic Colletotrichum strains by MALDI TOF mass spectrometry and molecular networking

The chemical diversity of biologically active fungal strains from 42 Colletotrichum, isolated from leaves of the tropical palm species Astrocaryum sciophilum collected in pristine forests of French Guiana, was investigated. The collection was first classified based on protein fingerprints acquired by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) correlated with cytotoxicity. Liquid chromatography coupled to high-resolution tandem mass spectrometry (LC-HRMS/MS) data from ethyl acetate extracts were acquired and processed to generate a massive molecular network (MN) using the MetGem software. From five Colletotrichum strains producing cytotoxic specialized metabolites, we predicted the occurrence of peptide and cytochalasin analogues in four of them by MN, including a similar ion clusters in the MN algorithm provided by MetGem software. Chemoinformatics predictions were fully confirmed after isolation of three pentacyclopeptides (cyclo(Phe-Leu-Leu-Leu-Val), cyclo(Phe-Leu-Leu-Leu-Leu) and cyclo(Phe-Leu-Leu-Leu-Ile)) and two cytochalasins (cytochalasin C and cytochalasin D) exhibiting cytotoxicity at the micromolar concentration. Finally, the chemical study of the last active cytotoxic strain BSNB-0583 led to the isolation of four colletamides bearing an identical decadienamide chain.

Boric-acid-modified Fe3O4@PDA@UiO-66 for enrichment and detection of glucose by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry

Herein, boric-acid-modified multifunctional Zr-based metal-organic frameworks (denoted as Fe₃O₄@PDA@B-UiO-66) were synthesized by hydrothermal reaction and surface modification. Compared to traditional matrix, Fe₃O₄@PDA@B-UiO-66 has the advantages of high ionization efficiency, high surface area, low matrix background, porous structure, and numerous boric-acid-active sites. By combining matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS), Fe₃O₄@PDA@B-UiO-66 was used as an adsorbent and matrix for enrichment and detection of glucose, based on a specific reaction between boric acid and glucose. The limit of detection was 58.5 nM. The proposed method provides a simple and efficient approach for the sensitive and quantitative detection of glucose in complex samples based on MALDI-TOF MS. Design and synthesis of boric-acid-modified multifunctional magnetic metal-organic frameworks (designated as Fe₃O₄@PDA@B-UiO-66) applied as adsorbent and matrix for the matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) analysis of glucose in complex biosamples.