Strain-level bacterial identification by CeO2-catalyzed MALDI-TOF MS fatty acid analysis and comparison to commercial protein-based methods

The Mass Spectrometry Revolution in Clinical Microbiology Part 2: Emerging Applications

In part 2 of this series, we highlight some of the exciting and emerging applications of mass spectrometry (MS) in pathogen detection, identification, and characterization. First, we review applications that have been recently introduced into the clinical microbiology laboratory such as direct matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) from positive blood cultures as well as its incorporation into laboratory automation. We then explore how current MALDI-TOF platforms are being developed to determine antimicrobial resistance and strain typing. Finally, we showcase some emerging approaches such as MS imaging and non-MALDI-based MS techniques such as ambient ionization and breath-based pathogen detection.

HILIC-IM-MS for Simultaneous Lipid and Metabolite Profiling of Bacteria

Although MALDI-ToF platforms for microbial identifications have found great success in clinical microbiology, the sole use of protein fingerprints for the discrimination of closely related species, strain-level identifications, and detection of antimicrobial resistance remains a challenge for the technology. Several alternative mass spectrometry-based methods have been proposed to address the shortcomings of the protein-centric approach, including MALDI-ToF methods for fatty acid/lipid profiling and LC-MS profiling of metabolites. However, the molecular diversity of microbial pathogens suggests that no single "ome" will be sufficient for the accurate and sensitive identification of strain- and susceptibility-level profiling of bacteria. Here, we describe the development of an alternative approach to microorganism profiling that relies upon both metabolites and lipids rather than a single class of biomolecule. Single-phase extractions based on butanol, acetonitrile, and water (the BAW method) were evaluated for the recovery of lipids and metabolites from Gram-positive and -negative microorganisms. We found that BAW extraction solutions containing 45% butanol provided optimal recovery of both molecular classes in a single extraction. The single-phase extraction method was coupled to hydrophilic interaction liquid chromatography (HILIC) and ion mobility-mass spectrometry (IM-MS) to resolve similar-mass metabolites and lipids in three dimensions and provide multiple points of evidence for feature annotation in the absence of tandem mass spectrometry. We demonstrate that the combined use of metabolites and lipids can be used to differentiate microorganisms to the species- and strain-level for four of the ESKAPE pathogens (Enterococcus faecium, Staphylococcus aureus, Acinetobacter baumannii, and Pseudomonas aeruginosa) using data from a single ionization mode. These results present promising, early stage evidence for the use of multiomic signatures for the identification of microorganisms by liquid chromatography, ion mobility, and mass spectrometry that, upon further development, may improve upon the level of identification provided by current methods.

Silver Nanoparticle Targets Fabricated Using Chemical Vapor Deposition Method for Differentiation of Bacteria Based on Lipidomic Profiles in Laser Desorption/Ionization Mass Spectrometry

The global threat of numerous infectious diseases creates a great need to develop new diagnostic methods to facilitate the appropriate prescription of antimicrobial therapy. More recently, the possibility of using bacterial lipidome analysis via laser desorption/ionization mass spectrometry (LDI-MS) as useful diagnostic tool for microbial identification and rapid drug susceptibility has received particular attention because lipids are present in large quantities and can be easily extracted similar to ribosomal proteins. Therefore, the main goal of the study was to evaluate the efficacy of two different LDI techniques-matrix-assisted (MALDI) and surface-assisted (SALDI) approaches-in the classification of the closely related Escherichia coli strains under cefotaxime addition. Bacterial lipids profiles obtained by using the MALDI technique with different matrices as well as silver nanoparticle (AgNP) targets fabricated using the chemical vapor deposition method (CVD) of different AgNP sizes were analyzed by the means of different multivariate statistical methods such as principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), sparse partial least squares discriminant analysis (sPLS-DA), and orthogonal projections to latent structures discriminant analysis (OPLS-DA). The analysis showed that the MALDI classification of strains was hampered by interference from matrix-derived ions. In contrast, the lipid profiles generated by the SALDI technique had lower background noise and more signals associated with the sample, allowing E. coli to be successfully classified into cefotaxime-resistant and cefotaxime-sensitive strains, regardless of the size of the AgNPs. AgNP substrates obtained using the CVD method were used for the first time for distinguishing closely related bacterial strains based on their lipidomic profiles and demonstrate high potential as a future diagnostic tool for the detection of antibiotic susceptibility.

“Omic” Approaches to Bacteria and Antibiotic Resistance Identification

The quick and accurate identification of microorganisms and the study of resistance to antibiotics is crucial in the economic and industrial fields along with medicine. One of the fastest-growing identification methods is the spectrometric approach consisting in the matrix-assisted laser ionization/desorption using a time-of-flight analyzer (MALDI-TOF MS), which has many advantages over conventional methods for the determination of microorganisms presented. Thanks to the use of a multiomic approach in the MALDI-TOF MS analysis, it is possible to obtain a broad spectrum of data allowing the identification of microorganisms, understanding their interactions and the analysis of antibiotic resistance mechanisms. In addition, the literature data indicate the possibility of a significant reduction in the time of the sample preparation and analysis time, which will enable a faster initiation of the treatment of patients. However, it is still necessary to improve the process of identifying and supplementing the existing databases along with creating new ones. This review summarizes the use of “-omics” approaches in the MALDI TOF MS analysis, including in bacterial identification and antibiotic resistance mechanisms analysis.

Metal Oxide Laser Ionization Mass Spectrometry Imaging of Fatty Acids and Their Double Bond Positional Isomers

We present a novel combination of a metal oxide laser ionization mass spectrometry imaging (MOLI MSI) technique with off-line lipid derivatization by ozone for the detection of fatty acids (FA) and their carbon-carbon double bond (C═C) positional isomers in biological tissues. MOLI MSI experiments were realized with CeO₂ and TiO₂ nanopowders using a vacuum matrix-assisted laser desorption/ionization time-of-flight (MALDI TOF) mass spectrometer in the negative mode. The catalytic properties of these metal oxides allow FA cleavage from phospholipids under UV laser irradiation. At the same time, fragile ozonides produced at the sites of unsaturation decomposed, yielding four diagnostic ions specific for the C═C positions. Advantageously, two MOLI MSI runs from a single tissue sprayed with the metal oxide suspension were performed. The first run prior to ozone derivatization revealed the distribution of FAs, while the second run after the reaction with ozone offered additional information about FA C═C isomers. The developed procedure was demonstrated on MSI of a normal mouse brain and human colorectal cancer tissues uncovering the differential distribution of FAs down to the isomer level. Compared to the histological analysis, MOLI MSI showed the distinct distribution of specific FAs in different functional parts of the brain and in healthy and cancer tissues pointing toward its biological relevance. The developed technique can be directly adopted by laboratories with MALDI TOF analyzers and help in the understanding of the local FA metabolism in tissues.

Rapid Characterization of Bacterial Lipids with Ambient Ionization Mass Spectrometry for Species Differentiation

Ambient ionization mass spectrometry (AIMS) is both labor and time saving and has been proven to be useful for the rapid delineation of trace organic and biological compounds with minimal sample pretreatment. Herein, an analytical platform of probe sampling combined with a thermal desorption–electrospray ionization/mass spectrometry (TD-ESI/MS) and multivariate statistical analysis was developed to rapidly differentiate bacterial species based on the differences in their lipid profiles. For comparison, protein fingerprinting was also performed with matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) to distinguish these bacterial species. Ten bacterial species, including five Gram-negative and five Gram-positive bacteria, were cultured, and the lipids in the colonies were characterized with TD-ESI/MS. As sample pretreatment was unnecessary, the analysis of the lipids in a bacterial colony growing on a Petri dish was completed within 1 min. The TD-ESI/MS results were further performed by principal component analysis (PCA) and hierarchical cluster analysis (HCA) to assist the classification of the bacteria, and a low relative standard deviation (5.2%) of the total ion current was obtained from repeated analyses of the lipids in a single bacterial colony. The PCA and HCA results indicated that different bacterial species were successfully distinguished by the differences in their lipid profiles as validated by the differences in their protein profiles recorded from the MALDI-TOF analysis. In addition, real-time monitoring of the changes in the specific lipids of a colony with growth time was also achieved with probe sampling and TD-ESI/MS. The developed analytical platform is promising as a useful diagnostic tool by which to rapidly distinguish bacterial species in clinical practice.

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

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

Bringing Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging to the Clinics

Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) is an emerging analytical technique that promises to change tissue-based diagnostics. This article provides a brief introduction to MALDI MSI as well as clinical diagnostic workflows and opportunities to apply this powerful approach. It describes various MALDI MSI applications, from more clinically mature applications such as cancer to emerging applications such as infectious diseases and drug distribution. In addition, it discusses the analytical considerations that need to be considered when bringing these approaches to different diagnostic problems and settings.

Mass Spectrometry and Microbial Diagnostics in the Clinical Laboratory

Over the past decade, matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry has revolutionized the practice of clinical microbiology and infectious disease diagnostics. Rapid advancement has occurred through the development and implementation of mass spectrometric protein profiling technologies that are widely available. Ease of sample preparation, rapid turnaround times, and high throughput accuracy have accelerated acceptance within the clinical laboratory. New mass spectrometric technologies centered on multiple microbial diagnostic markers are in development. Such new applications, reviewed in this article and on the near horizon, stand to greatly enhance the capabilities and utility for improved mass spectrometric microbial identification and patient care.

Detection of Species-Specific Lipids by Routine MALDI TOF Mass Spectrometry to Unlock the Challenges of Microbial Identification and Antimicrobial Susceptibility Testing

MALDI-TOF mass spectrometry has revolutionized clinical microbiology diagnostics by delivering accurate, fast, and reliable identification of microorganisms. It is conventionally based on the detection of intracellular molecules, mainly ribosomal proteins, for identification at the species-level and/or genus-level. Nevertheless, for some microorganisms (e.g., for mycobacteria) extensive protocols are necessary in order to extract intracellular proteins, and in some cases a protein-based approach cannot provide sufficient evidence to accurately identify the microorganisms within the same genus (e.g., Shigella sp. vs E. coli and the species of the M. tuberculosis complex). Consequently lipids, along with proteins are also molecules of interest. Lipids are ubiquitous, but their structural diversity delivers complementary information to the conventional protein-based clinical microbiology matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) based approaches currently used. Lipid modifications, such as the ones found on lipid A related to polymyxin resistance in Gram-negative pathogens (e.g., phosphoethanolamine and aminoarabinose), not only play a role in the detection of microorganisms by routine MALDI-TOF mass spectrometry but can also be used as a read-out of drug susceptibility. In this review, we will demonstrate that in combination with proteins, lipids are a game-changer in both the rapid detection of pathogens and the determination of their drug susceptibility using routine MALDI-TOF mass spectrometry systems.

Study on Molecular Profiles of Staphylococcus aureus Strains: Spectrometric Approach

Staphylococcus aureus remains a major health problem responsible for many epidemic outbreaks. Therefore, the development of efficient and rapid methods for studying molecular profiles of S. aureus strains for its further typing is in high demand. Among many techniques, matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI TOF MS) represents a timely, cost-effective, and reliable strain typing approach, which is still rarely used due to insufficient knowledge about the impact of sample preparation and analysis conditions on the molecular profiles and strain classification efficiency of S. aureus. The aim of this study was to evaluate the effect of the culture conditions and matrix type on the differentiation of molecular profiles of various S. aureus strains via the MALDI TOF MS analysis and different computational methods. The analysis revealed that by changing the culture conditions, matrix type, as well as a statistical method, the differentiation of S. aureus strains can be significantly improved. Therefore, to accelerate the incorporation of the MALDI-based strain typing in routine laboratories, further studies on the standardization and searching of optimal conditions on a larger number of isolates and bacterial species are of great need.

Metal Oxide Laser Ionization Mass Spectrometry Imaging (MOLI MSI) Using Cerium(IV) Oxide

Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI) is a powerful technique for spatially resolved metabolomics. A variation on MALDI, termed metal oxide laser ionization (MOLI), capitalizes on the unique property of cerium(IV) oxide (CeO2) to induce laser-catalyzed fatty acyl cleavage from lipids and has been utilized for bacterial identification. In this study, we present the development and utilization of CeO2 as an MSI catalyst. The method was developed using a MALDI TOF instrument in negative ion mode, equipped with a high frequency laser. Instrument parameters for MOLI MS fatty acid catalysis with CeO2 were optimized with phospholipid standards and fatty acid catalysis was confirmed using lipid extracts from reference bacterial strains, and sample preparation was optimized using mouse brain tissue. MOLI MSI was applied to the imaging of normal mouse brain revealing differentiable fatty acyl pools in myelinated and nonmyelinated regions. Similarly, MOLI MSI showed distinct fatty acyl composition in tumor regions of a patient derived xenograft mouse model of glioblastoma. To assess the potential of MOLI MSI to detect pathogens directly from tissue, a pseudoinfection model was prepared by spotting Escherichia coli lipid extracts on mouse brain tissue sections and imaged by MOLI MSI. The spotted regions were molecularly resolved from the supporting mouse brain tissue by the diagnostic odd-chained fatty acids and reflected control bacterial MOLI MS signatures. We describe MOLI MSI for the first time and highlight its potential for spatially resolved fatty acyl analysis, characterization of fatty acyl composition in tumors, and its potential for pathogen detection directly from tissue.

Pseudomonas aeruginosa bacteremia among liver transplant recipients

Pseudomonas aeruginosa bacteremia remains as a life-threatening complication after liver transplantation (LT) and is intractable because of the high rate of drug resistance to commonly used antibiotics. To better understand the characteristics of this postoperative complication, PubMed and Embase searches as well as reference mining was done for relevant literature from the start of the databases through August 2018. Among LT recipients, the incidence of P. aeruginosa bacteremia ranged from 0.5% to 14.4% and mortality rates were up to 40%. Approximately 35% of all episodes of bloodstream infections (BSIs) were P. aeruginosa bacteremia, of which 47% were multidrug resistant and 63% were extensively drug resistant. Several factors are known to affect the mortality of LT recipients with P. aeruginosa bacteremia, including hypotension, mechanical ventilation, and increasing severity of illness. In LT recipients with P. aeruginosa bacteremia, alteration in DNA gyrase A genes and overexpression of proteins involved in efflux systems, namely the expression of KPC-2-type carbapenemase, NDM-1, and VIM-2-type MBL, contribute to the high resistance of P. aeruginosa to a wide variety of antibiotics. Because of complicated mechanisms of drug resistance, P. aeruginosa causes high morbidity and mortality in bacteremic LT patients. Consequently, early detection and treatment with adequate early targeted coverage for P. aeruginosa BSI are of paramount importance in the early posttransplantation period to obtain a better prognosis for LT patients.

Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry (MALDI-TOF MS) Applications in Bacteriology: brazilian contributions

Among its innumerous applications in Bacteriology, the Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry (MALDI-TOF MS) technique is evolving as a powerful tool for bacterial identification and antimicrobial resistance investigation. Publications have evaluated the MALDI-TOF MS performance in the identification of a series of bacterial pathogens, including the most common severe infectious agents, emergent pathogens involved with outbreaks of healthcare-associated infections, rare pathogens, and those whose isolation in culture media is difficult. As compared to conventional methods of bacterial identification, MALDI-TOF MS has proven to be a fast, accurate and cost-effective technique. Currently, MALDI-TOF MS has been used in antimicrobial resistance studies, since it has shown to be an efficient tool in detecting specific resistance mechanisms in bacteria, such as beta-lactamases production, for example. Here, we describe the advances in this growing field of mass spectrometry applied to Bacteriology, including Brazilian contributions.

Characterization of microbial mixtures by mass spectrometry

MS applications in microbiology have increased significantly in the past 10 years, due in part to the proliferation of regulator-approved commercial MALDI MS platforms for rapid identification of clinical infections. In parallel, with the expansion of MS technologies in the "omics" fields, novel MS-based research efforts to characterize organismal as well as environmental microbiomes have emerged. Successful characterization of microorganisms found in complex mixtures of other organisms remains a major challenge for researchers and clinicians alike. Here, we review recent MS advances toward addressing that challenge. These include sample preparation methods and protocols, and established, for example, MALDI, as well as newer, for example, atmospheric pressure ionization (API) techniques. MALDI mass spectra of intact cells contain predominantly information on the highly expressed house-keeping proteins used as biomarkers. The API methods are applicable for small biomolecule analysis, for example, phospholipids and lipopeptides, and facilitate species differentiation. MS hardware and techniques, for example, tandem MS, including diverse ion source/mass analyzer combinations are discussed. Relevant examples for microbial mixture characterization utilizing these combinations are provided. Chemometrics and bioinformatics methods and algorithms, including those applied to large scale MS data acquisition in microbial metaproteomics and MS imaging of biofilms, are highlighted. Select MS applications for polymicrobial culture analysis in environmental and clinical microbiology are reviewed as well.

A new scheme for strain typing of methicillin-resistant Staphylococcus aureus on the basis of matrix-assisted laser desorption ionization time-of-flight mass spectrometry by using machine learning approach

Methicillin-resistant Staphylococcus aureus (MRSA), one of the most important clinical pathogens, conducts an increasing number of morbidity and mortality in the world. Rapid and accurate strain typing of bacteria would facilitate epidemiological investigation and infection control in near real time. Matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) mass spectrometry is a rapid and cost-effective tool for presumptive strain typing. To develop robust method for strain typing based on MALDI-TOF spectrum, machine learning (ML) is a promising algorithm for the construction of predictive model. In this study, a strategy of building templates of specific types was used to facilitate generating predictive models of methicillin-resistant Staphylococcus aureus (MRSA) strain typing through various ML methods. The strain types of the isolates were determined through multilocus sequence typing (MLST). The area under the receiver operating characteristic curve (AUC) and the predictive accuracy of the models were compared. ST5, ST59, and ST239 were the major MLST types, and ST45 was the minor type. For binary classification, the AUC values of various ML methods ranged from 0.76 to 0.99 for ST5, ST59, and ST239 types. In multiclass classification, the predictive accuracy of all generated models was more than 0.83. This study has demonstrated that ML methods can serve as a cost-effective and promising tool that provides preliminary strain typing information about major MRSA lineages on the basis of MALDI-TOF spectra.

Detection of antimicrobial resistance-associated proteins by titanium dioxide-facilitated intact bacteria mass spectrometry

Titanium dioxide-modified target plates were developed to enhance intact bacteria analysis by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. The plates were designed to photocatalytically destroy the bacterial envelope structure and improve the ionization efficiency of intracellular components, thereby promoting the measurable mass range and the achievable detection sensitivity. Accordingly, a method for rapid detection of antimicrobial resistance-associated proteins, conferring bacterial resistance against antimicrobial drugs, was established by mass spectrometric fingerprinting of intact bacteria without the need for any sample pre-treatment. With this method, the variations in resistance proteins' expression levels within bacteria were quickly measured from the relative peak intensities. This approach of resistance protein detection directly from intact bacteria by mass spectrometry is useful for fast discrimination of antimicrobial-resistant bacteria from their non-resistant counterparts whilst performing species identification. Also, it could be used as a rapid and convenient way for initial determination of the underlying resistance mechanisms.

Accurate and Rapid Differentiation of Acinetobacter baumannii Strains by Raman Spectroscopy: a Comparative Study

In recent years, matrix-assisted laser desorption ionization–time of flight mass spectrometry (MALDI-TOF MS) has become the standard for routine bacterial species identification due to its rapidity and low costs for consumables compared to those of traditional DNA-based methods. However, it has been observed that strains of some bacterial species, such as Acinetobacter baumannii strains, cannot be reliably identified using mass spectrometry (MS). Raman spectroscopy is a rapid technique, as fast as MALDI-TOF, and has been shown to accurately identify bacterial strains and species. In this study, we compared hierarchical clustering results for MS, genomic, and antimicrobial susceptibility test data to hierarchical clustering results from Raman spectroscopic data for 31 A. baumannii clinical isolates labeled according to their pulsed-field gel electrophoresis data for strain differentiation. In addition to performing hierarchical cluster analysis (HCA), multiple chemometric methods of analysis, including principal-component analysis (PCA) and partial least-squares discriminant analysis (PLSDA), were performed on the MS and Raman spectral data, along with a variety of spectral preprocessing techniques for best discriminative results. Finally, simple HCA algorithms were performed on all of the data sets to explore the relationships between, and natural groupings of, the strains and to compare results for the four data sets. To obtain numerical comparison values of the clustering results, the external cluster evaluation criteria of the Rand index of the HCA dendrograms were calculated. With a Rand index value of 0.88, Raman spectroscopy outperformed the other techniques, including MS (with a Rand index value of 0.58).

Can MALDI-TOF Mass Spectrometry Reasonably Type Bacteria?

Bacterial typing is crucial to tackle the spread of bacterial pathogens but current methods are time-consuming and costly. Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) has been recently integrated into the microbiology laboratory workflow for a quick and low-cost microbial species identification. Independent research groups have successfully redirected the original function of this technology from their primary purpose to discriminate subgroups within pathogen species. However, identical bacterial subgroups could be identified by unrelated peaks by independent methods, thus limiting their robustness and exportability. We propose several guidelines that could improve the performance of MALDI-TOF MS-based typing methods for use as a first-line epidemiological tool.

Current developments to use linear MALDI-TOF spectra for the identification and typing of bacteria and the characterization of other cells/organisms related to infectious diseases

Within the past few years identification of bacteria by MALDI-TOF MS has become a standard technique in bacteriological laboratories for good reasons. MALDI-TOF MS identification is rapid, robust, automatable, and the per-sample costs are low. Yet, the spectra are very informative and the reliable identification of bacterial species is usually possible. Recently, new MS-based approaches for the identification of bacteria are emerging that are based on the detailed analysis of the bacterial proteome by high-resolution MS. These "proteotyping" approaches are highly discriminative and outperform MALDI-TOF MS-based identification in terms of specificity, but require a laborious proteomic workflow and far more expertise and sophisticated instrumentation than identification on basis of MALDI-TOF MS spectra, which can be obtained with relative simple and uncostly linear MALDI-TOF mass spectrometers. Thus MALDI-TOF MS identification of bacteria remains an attractive option for routine diagnostics. Additionally, MALDI-TOF MS identification protocols have been extended and improved in many respects making linear MALDI-TOF MS a versatile tool that can be useful beyond the identification of a bacterial species, e.g. for the characterization of leucocytes and arthropod vectors of infectious diseases. This review focuses on such improvements and extensions of the typical MALDI-TOF MS workflow in the field of infectious diseases.

Strain-level Staphylococcus differentiation by CeO2-metal oxide laser ionization mass spectrometry fatty acid profiling

Background

The Staphylococcus genus is composed of 44 species, with S. aureus being the most pathogenic. Isolates of S. aureus are generally susceptible to β-lactam antibiotics, but extensive use of this class of drugs has led to increasing emergence of resistant strains. Increased occurrence of coagulase-negative staphylococci as well as S. aureus infections, some with resistance to multiple classes of antibiotics, has driven the necessity for innovative options for treatment and infection control. Despite these increasing needs, current methods still only possess species-level capabilities and require secondary testing to determine antibiotic resistance. This study describes the use of metal oxide laser ionization mass spectrometry fatty acid (FA) profiling as a rapid, simultaneous Staphylococcus identification and antibiotic resistance determination method.

Results

Principal component analysis was used to classify 50 Staphyloccocus isolates. Leave-one-spectrum-out cross-validation indicated 100 % correct assignment at the species and strain level. Fuzzy rule building expert system classification and self-optimizing partial least squares discriminant analysis, with more rigorous evaluations, also consistently achieved greater than 94 and 84 % accuracy, respectively. Preliminary analysis differentiating MRSA from MSSA demonstrated the feasibility of simultaneous determination of strain identification and antibiotic resistance.

Conclusion

The utility of CeO₂-MOLI MS FA profiling coupled with multivariate statistical analysis for performing strain-level differentiation of various Staphylococcus species proved to be a fast and reliable tool for identification. The simultaneous strain-level detection and antibiotic resistance determination achieved with this method should greatly improve outcomes and reduce clinical costs for therapeutic management and infection control.