Model-Based Spectral Library Approach for Bacterial Identification via Membrane Glycolipids

Use of stable isotope combined with intact cell lipidomic by routine MALDI mass spectrometry analysis for rapid drug susceptibility assay in mycobacteria

RATIONALE

Rapid, accurate, and easy-to-perform diagnostic assays are required to address the current need for the diagnosis of resistant pathogens. That is particularly the case for mycobacteria, such as the human pathogen Mycobacterium tuberculosis, which requires up to 2 weeks for the determination of the drug susceptibility profile using the conventional broth microdilution method. To address this challenge, we investigated the incorporation of deuterium, the stable isotope of hydrogen, into lipids as a read out of the drug susceptibility profile.

METHODS

Deuterium is incorporated into newly synthesized proteins or lipids in place of hydrogen as bacterial cells grow, increasing the mass of the macromolecules, which can then be observed via matrix-assisted laser desorption ionization time of flight mass spectrometry (MALDI-TOF MS). As proof-of-concept, we used the non-pathogenic Mycobacterium smegmatis mc2155 strain, which is susceptible to the aminoglycoside antibiotic kanamycin, and M. smegmatis mc2155 containing the empty vector pVV16, which is kanamycin-resistant. Bacteria were incubated in a culture medium containing 50% of deuterium oxide (D2O) and either 1 or 2 times the minimal inhibitory concentration (MIC50) of kanamycin. Lipids were then analyzed using the MBT lipid Xtract matrix combined with routine MALDI mass spectrometry in the positive ion mode to evaluate the changes in the lipid profile.

RESULTS

Using this approach, we were able to distinguish susceptible from resistant bacteria in less than 5 h, a process that would take 72 h using the conventional broth microdilution method.

CONCLUSIONS

We therefore propose a solution for the rapid determination of drug susceptibility profiles using a phenotypic assay combining D2O stable isotope labelling and lipid analysis by routine MALDI mass spectrometry.

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.

Analysis of carbohydrates and glycoconjugates by matrix-assisted laser desorption/ionization mass spectrometry: An update for 2019-2020

This review is the tenth update of the original article published in 1999 on the application of matrix-assisted laser desorption/ionization (MALDI) mass spectrometry to the analysis of carbohydrates and glycoconjugates and brings coverage of the literature to the end of 2020. Also included are papers that describe methods appropriate to analysis by MALDI, such as sample preparation techniques, even though the ionization method is not MALDI. The review is basically divided into three sections: (1) general aspects such as theory of the MALDI process, matrices, derivatization, MALDI imaging, fragmentation, quantification and the use of arrays. (2) Applications to various structural types such as oligo- and polysaccharides, glycoproteins, glycolipids, glycosides and biopharmaceuticals, and (3) other areas such as medicine, industrial processes and glycan synthesis where MALDI is extensively used. Much of the material relating to applications is presented in tabular form. The reported work shows increasing use of incorporation of new techniques such as ion mobility and the enormous impact that MALDI imaging is having. MALDI, although invented nearly 40 years ago is still an ideal technique for carbohydrate analysis and advancements in the technique and range of applications show little sign of diminishing.

“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.

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.

Rapid glycosyl-inositol-phospho-ceramide fingerprint from filamentous fungal pathogens using the MALDI Biotyper Sirius system

RATIONALE

Glycosyl-inositol-phospho-ceramides (GIPCs) or glycosylphosphatidylinositol-anchored fungal polysaccharides are known to be major lipids in plant and fungal plasma membranes and to play an important role in stress adaption. However, their analysis remains challenging due to the several steps involved for their extractions and purifications prior to mass spectrometric analysis. To address this challenge, we developed a rapid and sensitive method to identify GIPCs from the four common fungal plant pathogens Botrytis cinerea, Fusarium graminearium, Neurospora crassa and Ustilago maydis.

METHODS

Fungal plant pathogens were cultured, harvested, heat-inactivated and washed three times with double-distilled water. Intact fungi were deposited on a matrix-assisted laser desorption ionization (MALDI) target plate, mixed with the matrix consisting of a 9:1 mixture of 2,5-dihydroxybenzoic acid and 2-hydroxy-5-methoxybenzoic acid solubilized at 10 mg/mL in chloroform-methanol (9:1 v/v) and analyzed using a Bruker MALDI Biotyper Sirius system in the linear negative ion mode. Mass spectra were acquired from m/z 700 to 2000.

RESULTS

MALDI time-of-flight (TOF) mass spectrometric analysis of cultured fungi showed clear signature of GIPCs in B. cinerea, F. graminearium, N. crassa and U. maydis.

CONCLUSIONS

We have demonstrated that routine MALDI-TOF in the linear negative ion mode combined with an apolar solvent system to solubilize the matrix is applicable to the detection of filamentous fungal GIPCs.

MGMS2: Membrane glycolipid mass spectrum simulator for polymicrobial samples

RATIONALE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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