Mass Spectrometry Imaging Reveals Early Metabolic Priming of Cell Lineage in Differentiating Human-Induced Pluripotent Stem Cells

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 Gramnegative 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, Grampositive 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.

Section: Resultsmentioning

confidence: 99%

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

Walczak-Skierska,

Monedeiro,

Maślak

et al. 2023

“…Naturally, spectroscopic imaging has seamlessly integrated itself into biomedical analyses, affording the simultaneous acquisition of both molecular information and spatial distribution in complex biological tissues. Today, we encounter these imaging methodologies based on mass spectrometry (TOF-SIMS, MALDI , ), nuclear magnetic imaging (MRI , ), vibrational spectroscopy (MIR, , Raman , ), or fluorescence, , to name but a few. It is only logical that biomedical applications initially zeroed in on molecular information from tissues and cells.…”

Section: Introductionmentioning

confidence: 99%

Enhancing Diagnostic Capabilities for Occupational Lung Diseases Using LIBS Imaging on Biopsy Tissue

Ferreira,

Gardette,

Busser

et al. 2024

Laser-induced breakdown spectroscopy (LIBS) imaging continues to gain strength as an influential bioanalytical technique, showing intriguing potential in the field of clinical analysis. This is because hyperspectral LIBS imaging allows for rapid, comprehensive elemental analysis, covering elements from major to trace levels consistently year after year. In this study, we estimated the potential of a multivariate spectral data treatment approach based on a so-called convex envelope method to detect exotic elements (whether they are minor or in trace amounts) in biopsy tissues of patients with occupational exposure-related diseases. More precisely, we have developed an approach called Interesting Features Finder (IFF), which initially allowed us to identify unexpected elements without any preconceptions, considering only the set of spectra contained in a LIBS hyperspectral data cube. This task is, in fact, almost impossible with conventional chemometric tools, as it entails identifying a few exotic spectra among several hundred thousand others. Once this detection was performed, a second approach based on correlation was used to locate their distribution in the biopsies. Through this unique data analysis pipeline to processing massive LIBS spectroscopic data, it was possible to detect and locate exotic elements such as tin and rhodium in a patient's tissue section, ultimately leading to a possible reclassification of their lung condition as an occupational disease. This review will thus demonstrate the potential of this new diagnostic tool based on LIBS imaging in addressing the shortcomings of approaches developed thus far. The proposed data processing approach naturally transcends this specific framework and can be leveraged across various domains of analytical chemistry, where the detection of rare events is concealed within extensive data sets.

“…Visualization of metabolite changes in tissue regions of interest (ROI) contributes to the study of poorly understood biological processes and can add information to complementary modalities of spatial 'omics experiments and other imaging techniques. 1 Among its many applications, MSI has been leveraged to study metabolic disorders in tissue 2,3 and to better understand disease pathology. 4−6 Imperative to understanding any biological alterations in living systems is to determine the structural identity of the metabolites being imaged in as much detail as possible.…”

Section: ■ Introductionmentioning

confidence: 99%

Desorption Electrospray Ionization Cyclic Ion Mobility-Mass Spectrometry Imaging for Traumatic Brain Injury Spatial Metabolomics

Leontyev,

Olivos,

Shrestha

et al. 2024

Lipidomics focuses on investigating alterations in a wide variety of lipids that harness important information on metabolic processes and disease pathology. However, the vast structural diversity of lipids and the presence of isobaric and isomeric species creates serious challenges in feature identification, particularly in mass spectrometry imaging experiments that lack front-end separations. Ion mobility has emerged as a potential solution to address some of these challenges and is increasingly being utilized as part of mass spectrometry imaging platforms. Here, we present the results of a pilot mass spectrometry imaging study on rat brains subjected to traumatic brain injury (TBI) to evaluate the depth and quality of the information yielded by desorption electrospray ionization cyclic ion mobility mass spectrometry (DESI cIM MSI). Imaging data were collected with one and six passes through the cIM cell. Increasing the number of passes increased the ion mobility resolving power and the resolution of isobaric lipids, enabling the creation of more specific maps. Interestingly, drift time data enabled the recognition of multiply charged phosphoinositide species in the complex data set generated. These species have not been previously reported in TBI MSI studies and were found to decrease in the hippocampus region following injury. These changes were attributed to increased enzymatic activity after TBI, releasing arachidonic acid that is converted to eicosanoids to control inflammation. A substantial reduction in NAD and alterations in other adenine metabolites were also observed, supporting the hypothesis that energy metabolism in the brain is severely disrupted in TBI.