Liquid chromatography/mass spectrometry characterization of Escherichia coli and Shigella species

Discovery of novel serum peptide biomarkers for cholangiocarcinoma recurrence through MALDI-TOF MS and LC-MS/MS peptidome analysis

Cholangiocarcinoma (CCA) is an aggressive cancer originating from bile duct epithelial cells, with a high rate of recurrence following surgical resection. Recurrence is categorized as early linked to aggressive tumor biology than late recurrence. This study aimed to identify novel peptide mass fingerprints (PMFs) and potential biomarker panels in the serum of CCA patients with early and late recurrence using mass spectrometry. Serum samples of 81 CCA patients were analyzed using MALDI-TOF MS and LC-MS/MS, with statistical analysis correlating peptide profiles with clinical outcomes like disease-free survival (DFS) and overall survival (OS). A 365-day DFS cut-off effectively distinguished early from late recurrence, with early recurrence linked to poorer survival outcomes. The PMFs from MALDI-TOF MS differentiated recurrence types based on specific mass signatures. LC-MS/MS analysis identified 95 peptides associated with cancer progression in early recurrence and 60 in late recurrence. Distinct protein associations were found: ATR, POLA1, BLM, SP100, and PPP1R15A for early recurrence, and SERPINA1, TGFB2, SERPING1, and CAD for late recurrence, with strong interactions with chemotherapeutic drugs. This study successfully demonstrated the use of PMFs for rapid discrimination between early and late recurrence in CCA and identified potential serum peptide biomarkers to improve accuracy in recurrence classification.

Differentiation of Escherichia coli and Shigella flexneri by Metabolite Profiles Obtained Using Gold Nanoparticles-Based Surface-Assisted Laser Desorption/Ionization Mass Spectrometry

Escherichia coli and Shigella flexneri are challenging to differentiate using methods such as phenotyping, 16S rRNA sequencing, or protein profiling through matrix-assisted laser desorption/ionization mass spectrometry (MALDI MS) due to their close relatedness. This study explores the potential for identifying E. coli and S. flexneri by incorporating reference spectra of metabolite profiles, obtained via surface-assisted laser desorption/ionization mass spectrometry (SALDI MS) employing gold nanoparticles (AuNPs), into the Bruker Biotyper database. Metabolite extracts from E. coli and S. flexneri cells were prepared using liquid-liquid extraction in a chloroform-methanol-water system. The extracts were analyzed using Au-SALDI MS in positive ion mode, and reference spectra, compiled from 30 spectra for each bacterium, were added to the database. Identification of bacteria based on metabolite fingerprints in the Biotyper database produced correct results with scores exceeding 2.75. The results of Partial Least Squares-Discriminant Analysis (PLS-DA) demonstrated that the metabolomic approach could accurately differentiate the microorganisms under study. A panel of nine m/z values was also identified, each with an area under the ROC curve of above 0.8, enabling accurate identification of E. coli and S. flexneri. A search of metabolite databases allowed the following compounds to be assigned to the selected m/z values: N-acetylputrescine, arginine, 2-maleylacetate, benzoyl phosphate, N8-acetylspermidine, alanyl-glutamate, 4-hydroxy-2,3,4,5-tetrahydrodipicolinate, and sucrose. The analyses showed that identification of bacteria based on metabolite profiles obtained by the Au-SALDI MS method is feasible and can be useful for distinguishing closely related microorganisms that are difficult to differentiate by other techniques.

Deamidation analysis of therapeutic drugs using matrix-assisted laser desorption ionization mass spectrometry and a novel algorithm QuanDA

A robust deamidation quantification method, called QuanDA, was developed to quantify the spontaneous nonenzymatic deamidation of peptides based on the isotopic distribution change of peptides in matrix-assisted laser desorption ionization (MALDI) mass spectra and non-negative least squares calculation. The predictive model of QuanDA using theoretical spectra of pure un-deamidated and deamidated peptides for a series of simulated partial deamidated peptides is satisfying, with a coefficient of determination (R2) and root mean squared error (RMSE) of 0.9914 and 0.03356, respectively. It was applicable in cases where there is a lack of reference standards of un-deamidated and deamidated peptides. The only requirements were the chemical formulae of un-deamidated and deamidated peptides for isotopic pattern calculation. QuanDA provided a rapid, low-cost and easily accessible method for deamidation analysis in therapeutic drugs.

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.

Strain-Level Discrimination of Bacteria by Liquid Chromatography and Paper Spray Ion Mobility Mass Spectrometry

Determining bacterial identity at the strain level is critical for public health to enable proper medical treatments and reduce antibiotic resistance. Herein, we used liquid chromatography, ion mobility, and tandem MS (LC-IM-MS/MS) to distinguish Escherichia coli (E. coli) strains. Numerical multivariate statistics (principal component analysis, followed by linear discriminant analysis) showed the capability of this method to perform strain-level discrimination with prediction rates of 96.1% and 100% utilizing the negative and positive ion information, respectively. The tandem MS and LC separation proved effective in discriminating diagnostic lipid isomers in the negative mode, while IM separation was more effective in resolving lipid conformational biomarkers in the positive ion mode. Because of the clinical importance of early detection for rapid medical intervention, a faster technique, paper spray (PS)-IM-MS/MS, was used to discriminate the E. coli strains. The achieved prediction rates of the analysis of E. coli strains by PS-IM-MS/MS were 62.5% and 73.5% in the negative and positive ion modes, respectively. The strategy of numerical data fusion of negative and positive ion data increased the classification rates of PS-IM-MS/MS to 80.5%. Lipid isomers and conformers were detected, which served as strain-indicating biomarkers. The two complementary multidimensional techniques revealed biochemical differences between the E. coli strains confirming the results obtained from comparative genomic analysis. Moreover, the results suggest that PS-IM-MS/MS is a rapid, highly selective, and sensitive method for discriminating bacterial strains in environmental and food samples.

Biosensors for rapid detection of bacterial pathogens in water, food and environment

Conventional techniques (e.g., culture-based method) for bacterial detection typically require a central laboratory and well-trained technicians, which may take several hours or days. However, recent developments within various disciplines of science and engineering have led to a major paradigm shift in how microorganisms can be detected. The analytical sensors which are widely used for medical applications in the literature are being extended for rapid and on-site monitoring of the bacterial pathogens in food, water and the environment. Especially, within the low-resource settings such as low and middle-income countries, due to the advantages of low cost, rapidness and potential for field-testing, their use is indispensable for sustainable development of the regions. Within this context, this paper discusses analytical methods and biosensors which can be used to ensure food safety, water quality and environmental monitoring. In brief, most of our discussion is focused on various rapid sensors including biosensors and microfluidic chips. The analytical performances such as the sensitivity, specificity and usability of these sensors, as well as a brief comparison with the conventional techniques for bacteria detection, form the core part of the discussion. Furthermore, we provide a holistic viewpoint on how future research should focus on exploring the synergy of different sensing technologies by developing an integrated multiplexed, sensitive and accurate sensors that will enable rapid detection for food safety, water and environmental monitoring.

FTIR differentiation based on genomic DNA for species identification of Shigella isolates from stool samples

Shigellosis is one of the major public health concerns in developing and low-income countries caused by four species of Shigella. There is an apparent need to develop rapid, cost-effective, sensitive and specific methods for differentiation of Shigella species to be used in outbreaks and health surveillance systems. We developed a sensitive and specific Fourier-transform infrared spectroscopy (FTIR) based method followed by principal component analysis (PCA) and hierarchical clustering analysis (HCA) assays to differentiate four species of Shigella isolates from stool samples. The FTIR based method was evaluated by differentiation of 91 Shigella species from each other in clinical samples using both gold standards (culture-based and agglutination methods) and developed FTIR assay; eventually, the sensitivity and specificity of the developed method were calculated. In summary, four distinct FTIR spectra associated with four species of Shigella were obtained with wide variations in three definite regions, including 1800–1550 cm⁻¹, 1550–1100 cm⁻¹, and 1100–800 cm⁻¹ distinguish these species from each other. In this study, we found the FTIR method followed by PCA analysis with specificity, sensitivity, differentiation error and correct differentiation rate values of 100, 100, 0 and 100%, respectively, for identification and differentiation of all species of the Shigella in stool samples.

MALDI-TOF MS Using a Custom-Made Database, Biomarker Assignment, or Mathematical Classifiers Does Not Differentiate Shigella spp. and Escherichia coli

Shigella spp. and E. coli are closely related and cannot be distinguished using matrix-assisted laser desorption-ionization time-of-flight mass spectrometry (MALDI-TOF MS) with commercially available databases. Here, three alternative approaches using MALDI-TOF MS to identify and distinguish Shigella spp., E. coli, and its pathotype EIEC were explored and evaluated using spectra of 456 Shigella spp., 42 E. coli, and 61 EIEC isolates. Identification with a custom-made database resulted in >94% Shigella identified at the genus level and >91% S. sonnei and S. flexneri at the species level, but the distinction of S. dysenteriae, S. boydii, and E. coli was poor. With biomarker assignment, 98% S. sonnei isolates were correctly identified, although specificity was low. Discriminating markers for S. dysenteriae, S. boydii, and E. coli were not assigned at all. Classification models using machine learning correctly identified Shigella in 96% of isolates, but most E. coli isolates were also assigned to Shigella. None of the proposed alternative approaches were suitable for clinical diagnostics for identifying Shigella spp., E. coli, and EIEC, reflecting their relatedness and taxonomical classification. We suggest the use of MALDI-TOF MS for the identification of the Shigella spp./E. coli complex, but other tests should be used for distinction.

The diagnostic tools for viable but nonculturable pathogens in the food industry: Current status and future prospects

Viable but nonculturable (VBNC) microorganisms have been recognized as pathogenic contaminants in foods and environments. The failure of VBNC cells to form the visible colonies hinders the ability to use conventional media for their detection. Efficient and rapid detection of pathogens in the VBNC state is a prerequisite to ensure the food safety and public health. Despite their nonculturability, VBNC cells have distinct characteristics, such as morphology, metabolism, chemical composition, and gene and protein expression, that have been used as the basis for the development of abundant diagnostic tools. This review covers the current status and advances in various approaches for examining microorganisms in the VBNC state, including but not limited to the methodological aspects, advantages, and drawbacks of each technique. Existing methods, such as direct viable count, SYTO/PI dual staining, and propidium monoazide quantitative polymerase chain reaction (PCR), as well as some techniques with potential to be applied in the future, such as digital PCR, enhanced-surface Raman spectroscopy, and impedance-based techniques, are summarized in depth. Finally, future prospects for the one-step detection of VBNC bacteria are proposed and discussed. We believe that this review can provide more optional methods for researchers and promote the development of rapid, accurate detecting methods, and for inspectors, the diagnostic tools can provide data to undertake risk analysis of VBNC cells.

Detection and identification of a protein biomarker in antibiotic-resistant Escherichia coli using intact protein LC offline MALDI-MS and MS/MS

AIMS

The identification and differentiation of antibiotic-resistant bacteria by matrix-assisted laser desorption/ionization-time of flight-mass spectrometry (MALDI-TOF-MS) profiling remains a challenge due to the difficulty in detecting unique protein biomarkers associated with this trait. To expand the detectable proteome in antibiotic-resistant bacteria, we describe a method implementing offline LC protein separation/fractionation prior to MALDI-ToF-MS and top-down MALDI-ToF/ToF-MS (tandem MS or MS/MS) for the analysis of several antibiotic-resistant Escherichia coli isolates.

METHODS AND RESULTS

Coupling offline LC with MALDI-ToF-MS increased the number of detected protein signals in the typically analyzed mass regions (m/z 3000-20 000) by a factor of 13. Using the developed LC-MALDI-ToF-MS protocol in conjunction with supervised principal components analysis, we detected a protein biomarker at m/z 9355 which correlated to β-lactam resistance among the E. coli bacteria tested. Implementing a top-down MALDI-ToF/ToF-MS approach, the prefractionated protein biomarker was inferred as a DNA-binding HU protein, likely translated from the bla_CMY-2 gene (encoding AmpC-type β-lactamase) in the incompatibility plasmid complex A/C (IncA/C).

CONCLUSIONS

Our results demonstrate the utility of LC-MALDI-MS and MS/MS to extend the number of proteins detected and perform MALDI-accessible protein biomarker discovery in microorganisms.

SIGNIFICANCE AND IMPACT OF THE STUDY

This outcome is significant since it expands the detectable bacterial proteome via MALDI-ToF-MS.

Progress of electrospray ionization and rapid evaporative ionization mass spectrometric techniques for the broad-range identification of microorganisms

Electrospray ionization and rapid evaporative ionization mass spectrometric techniques have attracted much attention in the identification of microorganisms, and in the diagnosis of bacterial infections from clinical samples.

MALDI-TOF mass spectrometry: an emerging technology for microbial identification and diagnosis

Currently microorganisms are best identified using 16S rRNA and 18S rRNA gene sequencing. However, in recent years matrix assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) has emerged as a potential tool for microbial identification and diagnosis. During the MALDI-TOF MS process, microbes are identified using either intact cells or cell extracts. The process is rapid, sensitive, and economical in terms of both labor and costs involved. The technology has been readily imbibed by microbiologists who have reported usage of MALDI-TOF MS for a number of purposes like, microbial identification and strain typing, epidemiological studies, detection of biological warfare agents, detection of water- and food-borne pathogens, detection of antibiotic resistance and detection of blood and urinary tract pathogens etc. The limitation of the technology is that identification of new isolates is possible only if the spectral database contains peptide mass fingerprints of the type strains of specific genera/species/subspecies/strains. This review provides an overview of the status and recent applications of mass spectrometry for microbial identification. It also explores the usefulness of this exciting new technology for diagnosis of diseases caused by bacteria, viruses, and fungi.

Proteome-based bacterial identification using matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS): A revolutionary shift in clinical diagnostic microbiology

Rapid and accurate identification of microorganisms, a prerequisite for appropriate patient care and infection control, is a critical function of any clinical microbiology laboratory. Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) is a quick and reliable method for identification of microorganisms, including bacteria, yeast, molds, and mycobacteria. Indeed, there has been a revolutionary shift in clinical diagnostic microbiology. In the present review, the state of the art and advantages of MALDI-TOF MS-based bacterial identification are described. The potential of this innovative technology for use in strain typing and detection of antibiotic resistance is also discussed. This article is part of a Special Issue entitled: Medical Proteomics.

Proteomics boosts translational and clinical microbiology

The application of proteomics to translational and clinical microbiology is one of the most advanced frontiers in the management and control of infectious diseases and in the understanding of complex microbial systems within human fluids and districts. This new approach aims at providing, by dedicated bioinformatic pipelines, a thorough description of pathogen proteomes and their interactions within the context of human host ecosystems, revolutionizing the vision of infectious diseases in biomedicine and approaching new viewpoints in both diagnostic and clinical management of the patient. Indeed, in the last few years, many laboratories have matured a series of advanced proteomic applications, aiming at providing individual proteome charts of pathogens, with respect to their morph and/or cell life stages, antimicrobial or antimycotic resistance profiling, epidemiological dispersion. Herein, we aim at reviewing the current state-of-the-art on proteomic protocols designed and set-up for translational and diagnostic microbiological purposes, from axenic pathogens' characterization to microbiota ecosystems' full description. The final goal is to describe applications of the most common MALDI-TOF MS platforms to advanced diagnostic issues related to emerging infections, increasing of fastidious bacteria, and generation of patient-tailored phylotypes. This article is part of a Special Issue entitled: Trends in Microbial Proteomics.

Novel approach for differentiating Shigella species and Escherichia coli by matrix-assisted laser desorption ionization-time of flight mass spectrometry

Shigella species are so closely related to Escherichia coli that routine matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) cannot reliably differentiate them. Biochemical and serological methods are typically used to distinguish these species; however, "inactive" isolates of E. coli are biochemically very similar to Shigella species and thus pose a greater diagnostic challenge. We used ClinProTools (Bruker Daltonics) software to discover MALDI-TOF MS biomarker peaks and to generate classification models based on the genetic algorithm to differentiate between Shigella species and E. coli. Sixty-six Shigella spp. and 72 E. coli isolates were used to generate and test classification models, and the optimal models contained 15 biomarker peaks for genus-level classification and 12 peaks for species-level classification. We were able to identify 90% of E. coli and Shigella clinical isolates correctly to the species level. Only 3% of tested isolates were misidentified. This novel MALDI-TOF MS approach allows laboratories to streamline the identification of E. coli and Shigella species.

MALDI TOF MS profiling of bacteria at the strain level: a review

Since the advent of the use of matrix-assisted laser desorption/ionization (MALDI) time-of-flight mass spectrometry (TOF MS) as a tool for microbial characterization, efforts to increase the taxonomic resolution of the approach have been made. The rapidity and efficacy of the approach have suggested applications in counter-bioterrorism, prevention of food contamination, and monitoring the spread of antibiotic-resistant bacteria. Strain-level resolution has been reported with diverse bacteria, using library-based and bioinformatics-enabled approaches. Three types of characterization at the strain level have been reported: strain categorization, strain differentiation, and strain identification. Efforts to enhance the library-based approach have involved sample pre-treatment and data reduction strategies. Bioinformatics approaches have leveraged the ever-increasing amount of publicly available genomic and proteomic data to attain strain-level characterization. Bioinformatics-enabled strategies have facilitated strain characterization via intact biomarker identification, bottom-up, and top-down approaches. Rigorous quantitative and advanced statistical analyses have fostered success at the strain level with both approaches. Library-based approaches can be limited by effects of sample preparation and culture conditions on reproducibility, whereas bioinformatics-enabled approaches are typically limited to bacteria, for which genetic and/or proteomic data are available. Biological molecules other than proteins produced in strain-specific manners, including lipids and lipopeptides, might represent other avenues by which strain-level resolution might be attained. Immunological and lectin-based chemistries have shown promise to enhance sensitivity and specificity. Whereas the limits of the taxonomic resolution of MALDI TOF MS profiling of bacteria appears bacterium-specific, recent data suggest that these limits might not yet have been reached.

Rapid clinical bacteriology and its future impact

Clinical microbiology has always been a slowly evolving and conservative science. The sub-field of bacteriology has been and still is dominated for over a century by culture-based technologies. The integration of serological and molecular methodologies during the seventies and eighties of the previous century took place relatively slowly and in a cumbersome fashion. When nucleic acid amplification technologies became available in the early nineties, the predicted "revolution" was again slow but in the end a real paradigm shift did take place. Several of the culture-based technologies were successfully replaced by tests aimed at nucleic acid detection. More recently a second revolution occurred. Mass spectrometry was introduced and broadly accepted as a new diagnostic gold standard for microbial species identification. Apparently, the diagnostic landscape is changing, albeit slowly, and the combination of newly identified infectious etiologies and the availability of innovative technologies has now opened new avenues for modernizing clinical microbiology. However, the improvement of microbial antibiotic susceptibility testing is still lagging behind. In this review we aim to sketch the most recent developments in laboratory-based clinical bacteriology and to provide an overview of emerging novel diagnostic approaches.

Characterization of bacteria in ballast water using MALDI-TOF mass spectrometry

To evaluate a rapid and cost-effective method for monitoring bacteria in ballast water, several marine bacterial isolates were characterized by matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS). Since International Maritime Organization (IMO) regulations are concerned with the unintended transportation of pathogenic bacteria through ballast water, emphasis was placed on detecting species of Vibrio, enterococci and coliforms. Seawater samples collected from the North Sea were incubated in steel ballast tanks and the presence of potentially harmful species of Pseudomonas was also investigated. At the genus-level, the identification of thirty six isolates using MALDI-TOF MS produced similar results to those obtained by 16S rRNA gene sequencing. No pathogenic species were detected either by 16S rRNA gene analysis or by MALDI-TOF MS except for the opportunistically pathogenic bacterium Pseudomonas aeruginosa. In addition, in house software that calculated the correlation coefficient values (CCV) of the mass spectral raw data and their variation was developed and used to allow the rapid and efficient identification of marine bacteria in ballast water for the first time.

Advances in mass spectrometry for the identification of pathogens

Mass spectrometry (MS) has become an important technique to identify microbial biomarkers. The rapid and accurate MS identification of microorganisms without any extensive pretreatment of samples is now possible. This review summarizes MS methods that are currently utilized in microbial analyses. Affinity methods are effective to clean, enrich, and investigate microorganisms from complex matrices. Functionalized magnetic nanoparticles might concentrate traces of target microorganisms from sample solutions. Therefore, nanoparticle-based techniques have a favorable detection limit. MS coupled with various chromatographic techniques, such as liquid chromatography and capillary electrophoresis, reduces the complexity of microbial biomarkers and yields reliable results. The direct analysis of whole pathogenic microbial cells with matrix-assisted laser desorption/ionization MS without sample separation reveals specific biomarkers for taxonomy, and has the advantages of simplicity, rapidity, and high-throughput measurements. The MS detection of polymerase chain reaction (PCR)-amplified microbial nucleic acids provides an alternative to biomarker analysis. This review will conclude with some current applications of MS in the identification of pathogens.

Advances in subtyping methods of foodborne disease pathogens

Current subtyping methods for the detection of foodborne disease outbreaks have limitations that reduce their use by public health laboratories. Recent advances in subtyping of foodborne disease pathogens utilize techniques that identify nucleic acid polymorphisms. Recent methods of nucleic acid characterization such as microarrays and mass spectrometry (MS) may provide improvements such as increasing speed and data portability while decreasing labor compared to current methods. This article discusses multiple-locus variable-number tandem-repeat analysis, single-nucleotide polymorphisms, nucleic acid sequencing, whole genome sequencing, variable absent or present loci, microarrays and MS as potential subtyping methods to enhance our ability to detect foodborne disease outbreaks.

Characterization of Clostridium species utilizing liquid chromatography/mass spectrometry of intact proteins

A method for biomarker candidate discovery and strain level pathogen characterization using liquid chromatography/mass spectrometry (LC/MS) with electrospray ionization is described. This method was applied to two pathogenic Clostridium species: C. difficile and C. perfringens. Seven marker proteins per species (fourteen total) were successfully implemented to speciate unknowns during a blind study and could enhance serological and genetic approaches by serving as new targets for detection. Two sets of C. perfringens isolates that were 100% similar by pulsed-field gel electrophoresis (PFGE) were distinguished using LC/MS, demonstrating the high specificity of this approach. The use of LC/MS is less labor intensive than PFGE, affords greater specificity than real-time PCR, and requires no primers or antibodies.