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

Lipidomic approach to identify Escherichia coli and Shigella spp. by matrix-assisted laser desorption/ionization mass spectrometry

PURPOSE

Escherichia coli (E. coli) and Shigella species, being highly similar, present a challenge for differentiation using classical methods such as phenotyping, 16S rRNA sequencing, or protein profiling using matrix-assisted laser desorption/ionization mass spectrometry (MALDI MS). The paper proposes a method for identifying E. coli, S. flexneri, S. sonnei, and S. boydii by augmenting the Bruker Biotyper database with reference spectra of lipid profiles obtained using MALDI MS in the positive mode.

MATERIALS/METHODS

Lipid extracts were made from cultured E. coli, S. flexneri, S. sonnei and S. boydii using the Bligh & Dyer protocol. MALDI MS spectra in positive ion mode were performed for the extracts. Reference spectra were created from 30 spectra for each bacterium and added to the Bruker Biotyper database.

RESULTS

Identification of bacteria based on lipid profiles in the Biotyper database gave correct results with scores above 2.49. Statistical analysis of the results by Partial Least Squares-Discriminant Analysis (PLS-DA) showed that it is possible to correctly differentiate the microorganisms studied using the lipidomic approach. A panel of six m/z values was proposed for which the value of the area under the ROC curve is 1, thus enabling the identification of E. coli and S. flexneri with 100 ​% accuracy.

CONCLUSIONS

Identification of bacteria from lipid fingerprints obtained by the MALDI MS technique is possible and may become a useful tool in the future, especially for microorganisms that are difficult to distinguish by other methods.

AGuIX nanoparticle-nanobody bioconjugates to target immune checkpoint receptors

This article presents bioconjugates combining nanoparticles (AGuIX) with nanobodies (VHH) targeting Programmed Death-Ligand 1 (PD-L1, A12 VHH) and Cluster of Differentiation 47 (CD47, A4 VHH) for active tumor targeting. AGuIX nanoparticles offer theranostic capabilities and an efficient biodistribution/pharmacokinetic profile (BD/PK), while VHH's reduced size (15 kDa) allows efficient tumor penetration. Site-selective sortagging and click chemistry were compared for bioconjugation. While both methods yielded bioconjugates with similar functionality, click chemistry demonstrated higher yield and could be used for the conjugation of various VHH. The specific targeting of AGuIX@VHH has been demonstrated in both in vitro and ex vivo settings, paving the way for combined targeted immunotherapies, radiotherapy, and cancer imaging.

Challenges in the Detection of Polymyxin Resistance: From Today to the Future

Antimicrobial resistance is known to be one of the greatest global threats to human health, and is one of the main causes of death worldwide. In this scenario, polymyxins are last-resort antibiotics to treat infections caused by multidrug-resistant bacteria. Currently, the reference test to evaluate the susceptibility of isolates to polymyxins is the broth microdilution method; however, this technique has numerous complications and challenges for use in laboratory routines. Several phenotypic methods have been reported as being promising for implementation in routine diagnostics, including the BMD commercial test, rapid polymyxin NP test, polymyxin elution test, culture medium with polymyxins, and the Polymyxin Drop Test, which require materials for use in routines and must be easy to perform. Furthermore, Sensititre®, molecular tests, MALDI-TOF MS, and Raman spectroscopy present reliable results, but the equipment is not found in most microbiology laboratories. In this context, this review discusses the main laboratory methodologies that allow the detection of resistance to polymyxins, elucidating the challenges and perspectives.

Study of sample preparation influence on bacterial lipids profile in matrix-assisted laser desorption/ionization time-of-flight mass spectrometry

Lipids are one of the cell components therefore it is important to be able to accurately assess them. One of the analytical techniques used to study lipid profiles is matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI TOF MS). The present study attempted to select optimal conditions for sample preparation and MALDI MS analysis of bacterial lipidome in both positive and negative ion modes using different extraction protocols-Folch, Matyash, and Bligh & Dyer, solvents used to apply samples, and matrices such as 9-aminoacridine (9-AA), α-cyano-4-hydroxycinnamic acid (CHCA), 2,5-dihydroxybenzoic acid (DHB), 2-mercaptobenzothiazole (MBT), and 2,4,6-trihydroxyacetophenone (THAP). The obtained results allowed concluding that DHB or CHCA matrices are suitable for lipid analysis in the positive mode, and in the negative mode THAP or 9-AA. The most appropriate protocol for extracting lipids from bacterial cells was the Bligh & Dyer method in both ionization modes. The use of the solvent TA30, which was a mixture of acetonitrile and 0.1% trifluoroacetic acid in water, provided on the spectra a significant number of signals from lipids in all groups analyzed, such as fatty acyls, glycerolipids, and glycerophospholipids.

Lipidomics Characterization of the Microbiome in People with Diabetic Foot Infection Using MALDI-TOF MS

Lipidomic profiling has emerged as a powerful tool for the comprehensive characterization of bacterial species, particularly in the context of clinical diagnostics. Utilizing matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS), this study aims to elucidate the lipidomic landscapes of bacterial strains isolated from diabetic foot infections (DFI). Our analysis successfully identified a diverse array of lipids in the cellular membranes of both Gram-positive and Gram-negative bacteria, revealing a total of 108 unique fatty acid combinations. Specifically, we identified 26 LPG, 33 LPE, 43 PE, 114 PG, 89 TAG, and 120 CLP in Gram-positive bacteria and 10 LPG, 14 LPE, 124 PE, 37 PG, 13 TAG, and 22 CLP in Gram-negative strains. Key fatty acids, such as palmitic acid, palmitoleic acid, stearic acid, and oleic acid, were prominently featured. Univariate analysis further highlighted distinct lipidomic signatures among the bacterial strains, revealing elevated levels of phosphatidylethanolamine (PE) and phosphatidylglycerol (PG) in Gram-negative bacteria associated with DFI. In contrast, Gram-positive strains demonstrated increased or uniquely fluctuating levels of triglyceride (TAG) and cardiolipin (CLP). These findings not only underscore the utility of MALDI-TOF MS in bacterial lipidomics but also provide valuable insights into the lipidomic adaptations of bacteria in diabetic foot infections, thereby laying the groundwork for future studies aimed at constructing microbial lipid libraries for enhanced bacterial identification.

Determination of Pathogens by Electrophoretic and Spectrometric Techniques

In modern medical diagnostics, where analytical chemistry plays a key role, fast and accurate identification of pathogens is becoming increasingly important. Infectious diseases pose a growing threat to public health due to population growth, international air travel, bacterial resistance to antibiotics, and other factors. For instance, the detection of SARS-CoV-2 in patient samples is a key tool to monitor the spread of the disease. While there are several techniques for identifying pathogens by their genetic code, most of these methods are too expensive or slow to effectively analyze clinical and environmental samples that may contain hundreds or even thousands of different microbes. Standard approaches (e.g., culture media and biochemical assays) are known to be very time- and labor-intensive. The purpose of this review paper is to highlight the problems associated with the analysis and identification of pathogens that cause many serious infections. Special attention was paid to the description of mechanisms and the explanation of the phenomena and processes occurring on the surface of pathogens as biocolloids (charge distribution). This review also highlights the importance of electromigration techniques and demonstrates their potential for pathogen pre-separation and fractionation and demonstrates the use of spectrometric methods, such as MALDI-TOF MS, for their detection and identification.

A Five-Year Update on Matrix Compounds for MALDI-MS Analysis of Lipids

Matrix-assisted laser desorption and ionization (MALDI) is a widely used soft-ionization technique of modern mass spectrometry (MS). MALDI enables the analysis of nearly all chemical compounds—including polar and apolar (phospho)lipids—with a minimum extent of fragmentation. MALDI has some particular advantages (such as the possibility to acquire spatially-resolved spectra) and is competitive with the simultaneously developed ESI (electrospray ionization) MS. Although there are still some methodological aspects that need to be elucidated in more detail, it is obvious that the careful selection of an appropriate matrix plays the most important role in (lipid) analysis. Some lipid classes can be detected exclusively if the optimum matrix is used, and the matrix determines the sensitivity by which a particular lipid is detected within a mixture. Since the matrix is, thus, crucial for optimum results, we provide here an update on the progress in the field since our original review in this journal in 2018. Thus, only the development during the last five years is considered, and lipids are sorted according to increasing complexity, starting with free fatty acids and ending with cardiolipins and phosphoinositides.

Recent Advances and Potential Future Applications of MALDI-TOF Mass Spectrometry for Identification of Helminths

Helminth infections caused by nematodes, trematodes, and cestodes are major neglected tropical diseases and of great medical and veterinary relevance. At present, diagnosis of helminthic diseases is mainly based on microscopic observation of different parasite stages, but microscopy is associated with limited diagnostic accuracy. Against this background, recent studies described matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry as a potential, innovative tool for helminth identification and differentiation. MALDI-TOF mass spectrometry is based on the analysis of spectra profiles generated from protein extracts of a given pathogen. It requires an available spectra database containing reference spectra, also called main spectra profiles (MSPs), which are generated from well characterized specimens. At present, however, there are no commercially available databases for helminth identification using this approach. In this narrative review, we summarize recent developments and published studies between January 2019 and September 2022 that report on the use of MALDI-TOF mass spectrometry for helminths. Current challenges and future research needs are identified and briefly discussed.

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

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

“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.

Use of Fourier-Transform Infrared Spectroscopy With IR Biotyper® System for Legionella pneumophila Serogroups Identification

Legionella spp. are Gram-negative bacteria that inhabit freshwater environments representing a serious risk for human health. Legionella pneumophila (Lp) is the species most frequently responsible for a severe pneumonia known as Legionnaires' disease. Lp consists of 15 serogroups (Sgs), usually identified by monoclonal or polyclonal antibodies. With regard to Lp serogrouping, it is well known that phenotyping methods do not have a sufficiently high discriminating power, while genotypic methods although very effective, are expensive and laborious. Recently, mass spectrometry and infrared spectroscopy have proved to be rapid and successful approaches for the microbial identification and typing. Different biomolecules (e.g., lipopolysaccharides) adsorb infrared radiation originating from a specific microbial fingerprint. The development of a classification system based on the intra-species identification features allows a rapid and reliable typing of strains for diagnostic and epidemiological purposes. The aim of the study was the evaluation of Fourier Transform Infrared Spectroscopy using the IR Biotyper® system (Bruker Daltonik, Germany) for the identification of Lp at the serogroup (Sg) level for diagnostic purposes as well as in outbreak events. A large dataset of Lp isolates (n = 133) and ATCC reference strains representing the 15 Lp serogroups were included. The discriminatory power of the instrument's classifier, was tested by Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA). All isolates were classified as follows: 12/133 (9.0%) as Lp Sg1 and 115/133 (86.5%) as Lp Sg 2-15 (including both ATCC and environmental Lp serogroup). Moreover, a mis-classification for 2/133 (1.5%) isolates of Lp Sg 2-15 that returned as Lp Sg1 was observed, and 4/133 (3.0%) isolates were not classified. An accuracy of 95.49% and an error rate of 4.51% were calculated. IR Biotyper® is able provide a quick and cost-effective reliable Lp classification with advantages compared with agglutination tests that show ambiguous and unspecific results. Further studies including a larger number of isolates could be useful to implement the classifier obtaining a robust and reliable tool for the routine Lp serogrouping. IR Biotyper® could be a powerful and easy-to-use tool to identify Lp Sgs, especially during cluster/outbreak investigations, to trace the source of the infection and promptly adopt preventive and control strategies.

Model architectures for bacterial membranes

The complex composition of bacterial membranes has a significant impact on the understanding of pathogen function and their development towards antibiotic resistance. In addition to the inherent complexity and biosafety risks of studying biological pathogen membranes, the continual rise of antibiotic resistance and its significant economical and clinical consequences has motivated the development of numerous in vitro model membrane systems with tuneable compositions, geometries, and sizes. Approaches discussed in this review include liposomes, solid-supported bilayers, and computational simulations which have been used to explore various processes including drug-membrane interactions, lipid-protein interactions, host–pathogen interactions, and structure-induced bacterial pathogenesis. The advantages, limitations, and applicable analytical tools of all architectures are summarised with a perspective for future research efforts in architectural improvement and elucidation of resistance development strategies and membrane-targeting antibiotic mechanisms.

Combination of MALDI-TOF Mass Spectrometry and Machine Learning for Rapid Antimicrobial Resistance Screening: The Case of Campylobacter spp

While MALDI-TOF mass spectrometry (MS) is widely considered as the reference method for the rapid and inexpensive identification of microorganisms in routine laboratories, less attention has been addressed to its ability for detection of antimicrobial resistance (AMR). Recently, some studies assessed its potential application together with machine learning for the detection of AMR in clinical pathogens. The scope of this study was to investigate MALDI-TOF MS protein mass spectra combined with a prediction approach as an AMR screening tool for relevant foodborne pathogens, such as Campylobacter coli and Campylobacter jejuni. A One-Health panel of 224 C. jejuni and 116 C. coli strains was phenotypically tested for seven antimicrobial resistances, i.e., ciprofloxacin, erythromycin, tetracycline, gentamycin, kanamycin, streptomycin, and ampicillin, independently, and were submitted, after an on- and off-plate protein extraction, to MALDI Biotyper analysis, which yielded one average spectra per isolate and type of extraction. Overall, high performance was observed for classifiers detecting susceptible as well as ciprofloxacin- and tetracycline-resistant isolates. A maximum sensitivity and a precision of 92.3 and 81.2%, respectively, were reached. No significant prediction performance differences were observed between on- and off-plate types of protein extractions. Finally, three putative AMR biomarkers for fluoroquinolones, tetracyclines, and aminoglycosides were identified during the current study. Combination of MALDI-TOF MS and machine learning could be an efficient and inexpensive tool to swiftly screen certain AMR in foodborne pathogens, which may enable a rapid initiation of a precise, targeted antibiotic treatment.

A new update of MALDI-TOF mass spectrometry in lipid research

Matrix-assisted laser desorption and ionization (MALDI) mass spectrometry (MS) is an indispensable tool in modern lipid research since it is fast, sensitive, tolerates sample impurities and provides spectra without major analyte fragmentation. We will discuss some methodological aspects, the related ion-forming processes and the MALDI MS characteristics of the different lipid classes (with the focus on glycerophospholipids) and the progress, which was achieved during the last ten years. Particular attention will be given to quantitative aspects of MALDI MS since this is widely considered as the most serious drawback of the method. Although the detailed role of the matrix is not yet completely understood, it will be explicitly shown that the careful choice of the matrix is crucial (besides the careful evaluation of the positive and negative ion mass spectra) in order to be able to detect all lipid classes of interest. Two developments will be highlighted: spatially resolved Imaging MS is nowadays well established and the distribution of lipids in tissues merits increasing interest because lipids are readily detectable and represent ubiquitous compounds. It will also be shown that a combination of MALDI MS with thin-layer chromatography (TLC) enables a fast spatially resolved screening of an entire TLC plate which makes the method competitive with LC/MS.

Use of MALDI-TOF mass spectrometry for virus identification: a review

The possibilities of virus identification, including SARS-CoV-2, by MALDI-TOF mass spectrometry are discussed in this review.

Integrated mass spectrometry-based multi-omics for elucidating mechanisms of bacterial virulence

Despite being considered the simplest form of life, bacteria remain enigmatic, particularly in light of pathogenesis and evolving antimicrobial resistance. After three decades of genomics, we remain some way from understanding these organisms, and a substantial proportion of genes remain functionally unknown. Methodological advances, principally mass spectrometry (MS), are paving the way for parallel analysis of the proteome, metabolome and lipidome. Each provides a global, complementary assay, in addition to genomics, and the ability to better comprehend how pathogens respond to changes in their internal (e.g. mutation) and external environments consistent with infection-like conditions. Such responses include accessing necessary nutrients for survival in a hostile environment where co-colonizing bacteria and normal flora are acclimated to the prevailing conditions. Multi-omics can be harnessed across temporal and spatial (sub-cellular) dimensions to understand adaptation at the molecular level. Gene deletion libraries, in conjunction with large-scale approaches and evolving bioinformatics integration, will greatly facilitate next-generation vaccines and antimicrobial interventions by highlighting novel targets and pathogen-specific pathways. MS is also central in phenotypic characterization of surface biomolecules such as lipid A, as well as aiding in the determination of protein interactions and complexes. There is increasing evidence that bacteria are capable of widespread post-translational modification, including phosphorylation, glycosylation and acetylation; with each contributing to virulence. This review focuses on the bacterial genotype to phenotype transition and surveys the recent literature showing how the genome can be validated at the proteome, metabolome and lipidome levels to provide an integrated view of organism response to host conditions.