Combining imaging mass spectrometry and immunohistochemistry to analyse the lipidome of spinal cord inflammation.

Inflammation is a complex process that accompanies many pathologies. Actually, dysregulation of the inflammatory process is behind many autoimmune diseases. Thus, treatment of such pathologies may benefit from in-depth knowledge of the metabolic changes associated with inflammation. Here, we developed a strategy to characterize the lipid fingerprint of inflammation in a mouse model of spinal cord injury. Using lipid imaging mass spectrometry (LIMS), we scanned spinal cord sections from nine animals injected with lysophosphatidylcholine, a chemical model of demyelination. The lesions were demonstrated to be highly heterogeneous, and therefore, comparison with immunofluorescence experiments carried out in the same section scanned by LIMS was required to accurately identify the morphology of the lesion. Following this protocol, three main areas were defined: the lesion core, the peri-lesion, which is the front of the lesion and is rich in infiltrating cells, and the uninvolved tissue. Segmentation of the LIMS experiments allowed us to isolate the lipid fingerprint of each area in a precise way, as demonstrated by the analysis using classification models. A clear difference in lipid signature was observed between the lesion front and the epicentre, where the damage was maximized. This study is a first step to unravel the changes in the lipidome associated with inflammation in the context of diverse pathologies, such as multiple sclerosis.

Using the Synergy between HPLC-MS and MALDI-MS Imaging to Explore the Lipidomics of Clear Cell Renal Cell Carcinoma.

Lipid imaging mass spectrometry (LIMS) has been tested in several pathological contexts, demonstrating its ability to segregate and isolate lipid signatures in complex tissues, thanks to the technique's spatial resolution. However, it cannot yet compete with the superior identification power of high-performance liquid chromatography coupled to mass spectrometry (HPLC-MS), and therefore, very often, the latter is used to refine the assignment of the species detected by LIMS. Also, it is not clear if the differences in sensitivity and spatial resolution between the two techniques lead to a similar panel of biomarkers for a given disease. Here, we explore the capabilities of LIMS and HPLC-MS to produce a panel of lipid biomarkers to screen nephrectomy samples from 40 clear cell renal cell carcinoma patients. The same set of samples was explored by both techniques, and despite the important differences between them in terms of the number of detected and identified species (148 by LIMS and 344 by HPLC-MS in negative-ion mode) and the presence/absence of image capabilities, similar conclusions were reached: using the lipid fingerprint, it is possible to set up classifiers that correctly identify the samples as either healthy or tumor samples. The spatial resolution of LIMS enables extraction of additional information, such as the existence of necrotic areas or the existence of different tumor cell populations, but such information does not seem determinant for the correct classification of the samples, or it may be somehow compensated by the higher analytical power of HPLC-MS. Similar conclusions were reached with two very different techniques, validating their use for the discovery of lipid biomarkers.

Ferrostatin-1 modulates dysregulated kidney lipids in acute kidney injury.

Ferroptosis, a form of regulated necrosis characterized by peroxidation of lipids such as arachidonic acid-containing phosphatidylethanolamine (PE), contributes to the pathogenesis of acute kidney injury (AKI). We have characterized the kidney lipidome in an experimental nephrotoxic AKI induced in mice using folic acid and assessed the impact of the ferroptosis inhibitor Ferrostatin-1. Matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry (IMS) was used to assess kidney lipidomics and it discriminated between glomeruli, medulla, and cortex in control kidneys, AKI kidneys, and AKI + Ferrostatin-1 kidneys. Out of 139 lipid species from 16 classes identified, 29 (20.5%) showed significant differences between control and AKI at 48 h. Total PE and lyso-sulfatide species decreased, while phosphatidylinositol (PI) species increased in AKI. Dysregulated mRNA levels for Pemt, Pgs1, Cdipt, and Tamm41, relevant to lipid metabolism, were in line with the lipid changes observed. Ferrostatin-1 prevented AKI and some AKI-associated changes in lipid levels, such as the decrease in PE and lyso-sulfatide species, without changing the gene expression of lipid metabolism enzymes. In conclusion, changes in the kidney lipid composition during nephrotoxic AKI are associated with differential gene expression of lipid metabolism enzymes and are partially prevented by Ferrostatin-1. © 2022 The Pathological Society of Great Britain and Ireland.

Polyunsaturated Fatty Acid-Enriched Lipid Fingerprint of Glioblastoma Proliferative Regions Is Differentially Regulated According to Glioblastoma Molecular Subtype.

Glioblastoma (GBM) represents one of the deadliest tumors owing to a lack of effective treatments. The adverse outcomes are worsened by high rates of treatment discontinuation, caused by the severe side effects of temozolomide (TMZ), the reference treatment. Therefore, understanding TMZ's effects on GBM and healthy brain tissue could reveal new approaches to address chemotherapy side effects. In this context, we have previously demonstrated the membrane lipidome is highly cell type-specific and very sensitive to pathophysiological states. However, little remains known as to how membrane lipids participate in GBM onset and progression. Hence, we employed an ex vivo model to assess the impact of TMZ treatment on healthy and GBM lipidome, which was established through imaging mass spectrometry techniques. This approach revealed that bioactive lipid metabolic hubs (phosphatidylinositol and phosphatidylethanolamine plasmalogen species) were altered in healthy brain tissue treated with TMZ. To better understand these changes, we interrogated RNA expression and DNA methylation datasets of the Cancer Genome Atlas database. The results enabled GBM subtypes and patient survival to be linked with the expression of enzymes accounting for the observed lipidome, thus proving that exploring the lipid changes could reveal promising therapeutic approaches for GBM, and ways to ameliorate TMZ side effects.

High-Resolution Human Kidney Molecular Histology by Imaging Mass Spectrometry of Lipids.

For many years, traditional histology has been the gold standard for the diagnosis of many diseases. However, alternative and powerful techniques have appeared in recent years that complement the information extracted from a tissue section. One of the most promising techniques is imaging mass spectrometry applied to lipidomics. Here, we demonstrate the capabilities of this technique to highlight the architectural features of the human kidney at a spatial resolution of 10 µm. Our data demonstrate that up to seven different segments of the nephron and the interstitial tissue can be readily identified in the sections according to their characteristic lipid fingerprints and that such fingerprints are maintained among different individuals (n = 32). These results set the foundation for further studies on the metabolic bases of the diseases affecting the human kidney.

Matrix Sublimation Device for MALDI Mass Spectrometry Imaging.

Sublimation is a widely used method for matrix deposition in imaging mass spectrometry experiments. Still, most of the time, standard glass sublimators are used for this purpose, which do not enable optimal matrix deposition reproducibility, compromising inter-experiment comparison of the results. Here, we present an in-house designed stainless steel sublimator in which the parameters that have the strongest influence over matrix deposition reproducibility can be easily monitored. Using sections of human colon biopsies, we demonstrate the capabilities of this new prototype.

Lipid signature associated with chronic colon inflammation reveals a dysregulation in colonocyte differentiation process.

Inflammatory Bowel Disease (IBD) comprises a heterogeneous group of chronic inflammatory conditions of the gastrointestinal tract that include ulcerative colitis (UC) and Crohn's disease. Although the etiology is not well understood, IBD is characterized by a loss of the normal epithelium homeostasis that disrupts the intestinal barrier of these patients. Previous work by our group demonstrated that epithelial homeostasis along the colonic crypts involves a tight regulation of lipid profiles. To evaluate whether lipidomic profiles conveyed the functional alterations observed in the colonic epithelium of IBD, we performed matrix-assisted laser desorption ionization-mass spectrometry imaging (MALDI-MSI) analyses of endoscopic biopsies from inflamed and non-inflamed segments obtained from UC patients. Our results indicated that lipid profiling of epithelial cells discriminated between healthy and UC patients. We also demonstrated that epithelial cells of the inflamed mucosa were characterized by a decrease in mono- and di-unsaturated fatty acid-containing phospholipids and higher levels of arachidonic acid-containing species, suggesting an alteration of the lipid gradients occurring concomitantly to the epithelial differentiation. This result was reinforced by the immunofluorescence analysis of EPHB2 and HPGD, markers of epithelial cell differentiation, sustaining that altered lipid profiles were at least partially due to a faulty differentiation process. Overall, our results showed that lipid profiling by MALDI-MSI faithfully conveys molecular and functional alterations associated with the inflamed epithelium, providing the foundation for a novel molecular characterization of UC patients.

rMSIfragment: improving MALDI-MSI lipidomics through automated in-source fragment annotation.

Matrix-Assisted Laser Desorption Ionization Mass Spectrometry Imaging (MALDI-MSI) spatially resolves the chemical composition of tissues. Lipids are of particular interest, as they influence important biological processes in health and disease. However, the identification of lipids in MALDI-MSI remains a challenge due to the lack of chromatographic separation or untargeted tandem mass spectrometry. Recent studies have proposed the use of MALDI in-source fragmentation to infer structural information and aid identification. Here we present rMSIfragment, an open-source R package that exploits known adducts and fragmentation pathways to confidently annotate lipids in MALDI-MSI. The annotations are ranked using a novel score that demonstrates an area under the curve of 0.7 in ROC analyses using HPLC-MS and Target-Decoy validations. rMSIfragment applies to multiple MALDI-MSI sample types and experimental setups. Finally, we demonstrate that overlooking in-source fragments increases the number of incorrect annotations. Annotation workflows should consider in-source fragmentation tools such as rMSIfragment to increase annotation confidence and reduce the number of false positives.

Improving spatial resolution of a LTQ Orbitrap MALDI source.

Here we present a simple and cost effective procedure to improve the spatial resolution of the commercial MALDI source of a LTQ Orbitrap. Based in spatial filtering techniques, we demonstrate that, with minimal modifications of the original set up, the system resolution can be pushed forward to <10 µm. The improved system performance is demonstrated by means of MALDI imaging of human colon biopsies.

Influence of Lipid Fragmentation in the Data Analysis of Imaging Mass Spectrometry Experiments.

Imaging mass spectrometry (IMS) is becoming an essential technique in lipidomics. Still, many questions remain open, precluding it from achieving its full potential. Among them, identification of species directly from the tissue is of paramount importance. However, it is not an easy task, due to the abundance and variety of lipid species, their numerous fragmentation pathways, and the formation of a significant number of adducts, both with the matrix and with the cations present in the tissue. Here, we explore the fragmentation pathways of 17 lipid classes, demonstrating that in-source fragmentation hampers identification of some lipid species. Then, we analyze what type of adducts each class is more prone to form. Finally, we use that information together with data from on-tissue MS/MS and MS3 to refine the peak assignment in a real experiment over sections of human nevi, to demonstrate that statistical analysis of the data is significantly more robust if unwanted peaks due to fragmentation, matrix, and other species that only introduce noise in the analysis are excluded.