Utility of gas chromatography for rapid identification of mycobacterial species frequently encountered in clinical laboratory

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.

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.

Direct detection of Mycobacterium tuberculosis in sputum: A validation study using solid phase extraction-gas chromatography-mass spectrometry

Tuberculosis (TB) remains a worldwide health problem, especially in developing countries. Correct identification of Mycobacterium tuberculosis (MTB) infection is extremely important for providing appropriate treatment and care to patients. Here we describe a solid phase extraction-gas chromatography-mass spectrometry method (SPE-THM-GC-MS) for the detection of five biomarkers for M. tuberculosis. The method for classification is developed and validated through the analysis of 112 sputum samples from patients suspected of having TB. Twenty of twenty-five MTB culture-positive sputum samples were correctly classified as positive by our improved SPE-THM-GC-MS method. Eighty-five of eighty-seven MTB culture-negative samples were also negative by SPE-THM-GC-MS. The overall sensitivity of the new SPE-THM-GC-MS method is 80% (20/25) and the specificity is 98% (85/87) compared with culture. The method proved to be reliable and, although complex in principle, easy to operate due to the high degree of automation.

Neglected diseases prioritized in Brazil under the perspective of metabolomics: A review

This review article compiles in a critical manner literature publications regarding seven neglected diseases (ND) prioritized in Brazil (Chagas disease, dengue, leishmaniasis, leprosy, malaria, schistosomiasis, and tuberculosis) under the perspective of metabolomics. Both strategies, targeted and untargeted metabolomics, were considered in the compilation. The majority of studies focused on biomarker discovery for diagnostic purposes, and on the search of novel or alternative therapies against the ND under consideration, although temporal progression of the infection at metabolic level was also addressed. Tuberculosis, followed by schistosomiasis, malaria and leishmaniasis are the diseases that received larger attention in terms of number of publications. Dengue and leprosy were the least studied and Chagas disease received intermediate attention. NMR and HPLC-MS technologies continue to predominate among the analytical platforms of choice in the metabolomic studies of ND. A plethora of metabolites were identified in the compiled studies, with expressive predominancy of amino acids, organic acids, carbohydrates, nucleosides, lipids, fatty acids, and derivatives.

Rapid diagnosis of TB using GC-MS and chemometrics

The search continues for a rapid diagnostic test for TB that has high sensitivity and specificity and is useable in sophisticated environments and in deprived regions with poor infrastructure. We discuss here the modern bioanalytical techniques that can be used to discover biomarkers of infection with Mycobacterium tuberculosis, focusing on techniques using GC. We will also discuss the use of GC-MS to identify volatile organic compounds in the headspace of bacterial culture or in samples of breath, serum or urine. Biomarkers discovered in the 'clean' environment of culture may differ from those in patients. A number of biomarkers have been found in patients, with little consistency in the various studies to date. Reproducibility is difficult; the impressive results found initially with a few patients are rarely repeatable when a larger sample series is tested. Mycobacterial lipids offer promise for distinguishing M. tuberculosis from nontuberculous mycobacteria directly in sputum.

A metabolomics approach to characterise and identify various Mycobacterium species

We investigated the potential use of gas chromatography mass spectrometry (GC-MS), in combination with multivariate statistical data processing, to build a model for the classification of various tuberculosis (TB) causing, and non-TB Mycobacterium species, on the basis of their characteristic metabolite profiles. A modified Bligh-Dyer extraction procedure was used to extract lipid components from Mycobacterium tuberculosis, Mycobacterium avium, Mycobacterium bovis, and Mycobacterium kansasii cultures. Principle component analyses (PCA) of the GC-MS generated data showed a clear differentiation between all the Mycobacterium species tested. Subsequently, the 12 compounds best describing the variation between the sample groups were identified as potential metabolite markers, using PCA and partial least-squares discriminant analysis (PLS-DA). These metabolite markers were then used to build a discriminant classification model based on Bayes' theorem, in conjunction with multivariate kernel density estimation. This model subsequently correctly classified 2 "unknown" samples for each of the Mycobacterium species analysed, with probabilities ranging from 72 to 100%. Furthermore, Mycobacterium species classification could be achieved in less than 16 h, and the detection limit for this approach was 1×10(3)bacteriamL(-1). This study proves the capacity of a GC-MS, metabolomics pattern recognition approach for its possible use in TB diagnostics and disease characterisation.

Rapid diagnostic testing for mycobacterial infections

Tests based on nucleic acid amplification can rapidly detect mycobacteria in clinical samples. These appear to be promising and may change how mycobacterial diseases are diagnosed in the future. Utilization of nucleic acid hybridization and DNA sequencing has enabled the identification of mycobacteria to the species level and detection of mutations associated with antimicrobial resistance. Combining nucleic acid amplification with genotypic identification methods allows detection and identification of mycobacteria directly in clinical samples and, to a limited extent, detection of antimicrobial resistance. IFN-gamma-based assays provide results faster than the tuberculin skin test and address many of its shortcomings, and are thus poised to replace the latter in the coming years.

Malignant mixed müllerian tumor of the uterus. Features favoring its origin from a common cell clone and an epithelial-to-mesenchymal transformation mechanism of histogenesis

AIMS AND BACKGROUND

Various histogenetic mechanisms have been postulated to explain the biphasic carcinomatous-sarcomatous appearance of malignant mixed mullerian tumors (MMMTs), but the nature of these uncommon neoplasms is still unclear. Some evidence would suggest that MMMT displays similarities with sarcomatoid carcinoma, a tumor arising in extragenital sites that also features a mixed appearance. To gain further insight into the histogenesis of this tumor, we have studied by immunohistochemistry a case of uterine MMMT showing an extensive rhabdomyosarcomatous component.

METHODS

A panel of antibodies including reactivity for p53, cytokeratin, vimentin, desmin, muscle actin, epithelial membrane antigen (EMA), myoglobin, type IV collagen, laminin, and tenascin was applied to paraffin tumor sections by means of the avidin-biotin complex technique.

RESULTS

p53 immunoreactivity was observed in approximately the same number of cells in carcinomatous and sarcomatous tissue. The former stained for vimentin, cytokeratin and EMA, while the latter, in addition to expressing vimentin, desmin, muscle actin and myoglobin, also exhibited immunoreactivity for epithelial markers such as cytokeratin and EMA. At the borders between carcinoma and sarcoma the basement membrane pattern, as seen by staining for type IV collagen and laminin, showed interruptions in correspondence with areas of transition between the two tissues. Antibody to tenascin strongly labeled the sarcomatous tissue immediately around carcinomatous elements.

CONCLUSIONS

A similar immunoreactivity for p53 in both carcinomatous and sarcomatous components, expression of epithelial markers in the sarcomatous cells, and disruption of the basement membrane profile in areas of transition between carcinomatous and sarcomatous tissue, would all suggest, as has been postulated for extragenital sarcomatoid carcinomas, an origin from a common epithelial clone and an epithelial-to-mesenchymal transformation-based mechanism of development for this MMMT. In addition, these findings provide further analogies between these categories of tumors, supporting a unifying nosological concept for MMMTs and sarcomatoid carcinomas of non-genital tract origin.