Kidney Lipidomics by Mass Spectrometry Imaging: A Focus on the Glomerulus

Monitoring lipid alterations in Drosophila heads in an amyotrophic lateral sclerosis model with time-of-flight secondary ion mass spectrometry

Lipid alterations in the brain are well-documented in disease and aging, but our understanding of their pathogenic implications remains incomplete. Recent technological advances in assessing lipid profiles have enabled us to intricately examine the spatiotemporal variations in lipid compositions within the complex brain characterized by diverse cell types and intricate neural networks. In this study, we coupled time-of-flight secondary ion mass spectrometry (ToF-SIMS) to an amyotrophic lateral sclerosis (ALS) Drosophila model, for the first time, to elucidate changes in the lipid landscape and investigate their potential role in the disease process, serving as a methodological and analytical complement to our prior approach that utilized matrix-assisted laser desorption/ionization mass spectrometry. The expansion of G4C2 repeats in the C9orf72 gene is the most prevalent genetic factor in ALS. Our findings indicate that expressing these repeats in fly brains elevates the levels of fatty acids, diacylglycerols, and ceramides during the early stages (day 5) of disease progression, preceding motor dysfunction. Using RNAi-based genetic screening targeting lipid regulators, we found that reducing fatty acid transport protein 1 (FATP1) and Acyl-CoA-binding protein (ACBP) alleviates the retinal degeneration caused by G4C2 repeat expression and also markedly restores the G4C2-dependent alterations in lipid profiles. Significantly, the expression of FATP1 and ACBP is upregulated in G4C2-expressing flies, suggesting their contribution to lipid dysregulation. Collectively, our novel use of ToF-SIMS with the ALS Drosophila model, alongside methodological and analytical improvements, successfully identifies crucial lipids and related genetic factors in ALS pathogenesis.

Lipidomics based on liquid chromatography-high resolution mass spectrometry reveals the protective role of peroxisome proliferator-activated receptor alpha on kidney stone formation in mice treated with glyoxylate

Few studies have examined the relationship between lipid metabolism and kidney stone formation, particularly the role of key lipid regulatory factors in kidney stone formation. We evaluated the effect of the lipid regulatory factor-peroxisome proliferator-activated receptor alpha on the formation of renal stones in mice by injecting them with glyoxylate followed by treatment with either a peroxisome proliferator-activated receptor alpha agonist fenofibrate or an antagonist GW6471 (GW). Liquid chromatography coupled with trapped ion mobility spectrometry-quadrupole-time-of-flight mass spectrometry-based lipidomics was used to determine the lipid profile in the mouse kidneys. Histological and biochemical analyses showed that the mice injected with glyoxylate exhibited crystal precipitation and renal dysfunction. Crystallization decreased significantly in the fenofibrate group, whereas it increased significantly in the GW group. A total of 184 lipids, including fatty acyls, glycerolipids, glycerophospholipids, and sphingolipids differed significantly between the mice in the model and control groups. Peroxisome proliferator-activated receptor alpha activity negatively correlated with glyoxylate-induced kidney stone formation in mice, which may be related to improved fatty acid oxidation, maintenance of ceramide/complex sphingolipids cycle balance, and alleviation of disorder in phospholipid metabolism.

Cell and tissue imaging by secondary ion mass spectrometry

This Tutorial focuses on the use of secondary ion mass spectrometry for the analysis of cellular and tissue samples. The Tutorial aims to cover the considerations in sample preparation analytical set up and some specific aspects of data interpretation associated with such analysis.

Recent Advances in Mass Spectrometry-Based Spatially Resolved Molecular Imaging of Drug Disposition and Metabolomics

Mass spectrometric imaging is a nontargeted, tag-free, high-throughput, and highly responsive analytical approach. The highly accurate molecular visualization detection technology enables qualitative and quantitative analyses of biologic tissues or cells scanned by mass spectrometry in situ, extracting known and unknown multiple compounds, and simultaneously assessing relative contents of targeting molecules by monitoring their molecular ions and pinpointing the spatial locations of those molecules distributed. Five mass spectrometric imaging techniques and their characteristics are introduced in the review, including matrix-assisted laser desorption ionization mass spectrometry, secondary ion mass spectrometry, desorption electrospray ionization mass spectrometry, laser ablation electrospray ionization mass spectrometry, and laser ablation inductively coupled plasma mass spectrometry. The mass spectrometry-based techniques provide the possibility for spatial metabolomics with the capability of high throughput and precision detection. The approaches have been widely employed to spatially image not only metabolome of endogenous amino acids, peptides, proteins, neurotransmitters, and lipids but also the disposition of exogenous chemicals, such as pharmaceutical agents, environmental pollutants, toxicants, natural products, and heavy metals. The techniques also provide us with spatial distribution imaging of analytes in single cells, tissue microregions, organs, and whole animals. SIGNIFICANCE STATEMENT: The review article includes an overview of five commonly used mass spectrometers for spatial imaging and describes the advantages and disadvantages of each. Examples of the technology applications cover drug disposition, diseases, and omics. Technical aspects of relative and absolute quantification by mass spectrometric imaging and challenges for future new applications are discussed as well. The reviewed knowledge may benefit the development of new drugs and provide a better understanding of biochemical processes related to physiology and diseases.

A multimodal atlas of tumour metabolism reveals the architecture of gene-metabolite covariation

Tumour metabolism is controlled by coordinated changes in metabolite abundance and gene expression, but simultaneous quantification of metabolites and transcripts in primary tissue is rare. To overcome this limitation and to study gene-metabolite covariation in cancer, we assemble the Cancer Atlas of Metabolic Profiles of metabolomic and transcriptomic data from 988 tumour and control specimens spanning 11 cancer types in published and newly generated datasets. Meta-analysis of the Cancer Atlas of Metabolic Profiles reveals two classes of gene-metabolite covariation that transcend cancer types. The first corresponds to gene-metabolite pairs engaged in direct enzyme-substrate interactions, identifying putative genes controlling metabolite pool sizes. A second class of gene-metabolite covariation represents a small number of hub metabolites, including quinolinate and nicotinamide adenine dinucleotide, which correlate to many genes specifically expressed in immune cell populations. These results provide evidence that gene-metabolite covariation in cellularly heterogeneous tissue arises, in part, from both mechanistic interactions between genes and metabolites, and from remodelling of the bulk metabolome in specific immune microenvironments.

Analyzing cell-type-specific dynamics of metabolism in kidney repair

A common drawback of metabolic analyses of complex biological samples is the inability to consider cell-to-cell heterogeneity in the context of an organ or tissue. To overcome this limitation, we present an advanced high-spatial-resolution metabolomics approach using matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) combined with isotope tracing. This method allows mapping of cell-type-specific dynamic changes in central carbon metabolism in the context of a complex heterogeneous tissue architecture, such as the kidney. Combined with multiplexed immunofluorescence staining, this method can detect metabolic changes and nutrient partitioning in targeted cell types, as demonstrated in a bilateral renal ischemia-reperfusion injury (bIRI) experimental model. Our approach enables us to identify region-specific metabolic perturbations associated with the lesion and throughout recovery, including unexpected metabolic anomalies in cells with an apparently normal phenotype in the recovery phase. These findings may be relevant to an understanding of the homeostatic capacity of the kidney microenvironment. In sum, this method allows us to achieve resolution at the single-cell level in situ and hence to interpret cell-type-specific metabolic dynamics in the context of structure and metabolism of neighboring cells.

The Role of Mass Spectrometry Imaging in Pharmacokinetic Studies

Although liquid chromatography-tandem mass spectrometry is the gold standard analytical platform for the quantification of drugs, metabolites, and biomarkers in biological samples, it cannot localize them in target tissues.The localization and quantification of drugs and/or their associated metabolites in target tissues is a more direct measure of bioavailability, biodistribution, efficacy, and regional toxicity compared to the traditional substitute studies using plasma.Therefore, combining high spatial resolution imaging functionality with the superior selectivity and sensitivity of mass spectrometry into one analytical technique will be a valuable tool for targeted localization and quantification of drugs, metabolites, and biomarkers.Mass spectrometry imaging (MSI) is a tagless analytical technique that allows for the direct localization and quantification of drugs, metabolites, and biomarkers in biological tissues, and has been used extensively in pharmaceutical research.The overall goal of this current review is to provide a detailed description of the working principle of MSI and its application in pharmacokinetic studies encompassing absorption, distribution, metabolism, excretion, and toxicity processes, followed by a discussion of the strategies for addressing the challenges associated with the functional utility of MSI in pharmacokinetic studies that support drug development.

Lipidomics characterization of the lipid metabolism profiles in a cystinuria rat model: Precalculus damage in the kidney of cystinuria

Cystinuria is a genetic disorder of cystine transport, including defective protein b^0,+AT (encoded by SLC7A9), and/or rBAT (encoded by SLC3A1). Patients present hyperexcretion of cystine in the urine, recurrent cystine lithiasis, and progressive decline in kidney function. Moreover, heterodimer transport is defective. To date, little omics data are accessible regarding this metabolic disease caused by membrane proteins. Since membrane function is closely related to changes in the lipidome, we decided to explore the changes in kidney tissue of a self-established cystinuria rat model by performing lipidomic analysis by LC-MS/MS. Our results demonstrated that Slc7a9 deficiency changed the lipid profile of the renal cortex and induced vital modifications in the lipidome, including major alterations in ChE, LPA, and PA. Among those alterations, this lipidomic study highlights the lipid changes that participate in inflammatory responses during cystinuria. As a result, lipid research, perhaps has great potential, for it may lead to the identification of novel therapeutic targets for the prevention and treatment of cystinuria.

Referenced Kendrick Mass Defect Annotation and Class-Based Filtering of Imaging MS Lipidomics Experiments

Because of their diverse functionalities in cells, lipids are of primary importance when characterizing molecular profiles of physiological and disease states. Imaging mass spectrometry (IMS) provides the spatial distributions of lipid populations in tissues. Referenced Kendrick mass defect (RKMD) analysis is an effective mass spectrometry (MS) data analysis tool for classification and annotation of lipids. Herein, we extend the capabilities of RKMD analysis and demonstrate an integrated method for lipid annotation and chemical structure-based filtering for IMS datasets. Annotation of lipid features with lipid molecular class, radyl carbon chain length, and degree of unsaturation allows image reconstruction and visualization based on each structural characteristic. We show a proof-of-concept application of the method to a computationally generated IMS dataset and validate that the RKMD method is highly specific for lipid components in the presence of confounding background ions. Moreover, we demonstrate an application of the RKMD-based annotation and filtering to matrix-assisted laser desorption/ionization (MALDI) IMS lipidomic data from human kidney tissue analysis.

The foundations and development of lipidomics

For over a century, the importance of lipid metabolism in biology was recognized but difficult to mechanistically understand due to the lack of sensitive and robust technologies for identification and quantification of lipid molecular species. The enabling technological breakthroughs emerged in the 1980s with the development of soft ionization methods (Electrospray Ionization and Matrix Assisted Laser Desorption/Ionization) that could identify and quantify intact individual lipid molecular species. These soft ionization technologies laid the foundations for what was to be later named the field of lipidomics. Further innovative advances in multistage fragmentation, dramatic improvements in resolution and mass accuracy, and multiplexed sample analysis fueled the early growth of lipidomics through the early 1990s. The field exponentially grew through the use of a variety of strategic approaches, which included direct infusion, chromatographic separation, and charge-switch derivatization, which facilitated access to the low abundance species of the lipidome. In this Thematic Review, we provide a broad perspective of the foundations, enabling advances, and predicted future directions of growth of the lipidomics field.

RECOGNITION AND AVOIDANCE OF ION SOURCE-GENERATED ARTIFACTS IN LIPIDOMICS ANALYSIS

Lipid research is attracting more and more attention as various key roles and novel biological functions of lipids have been demonstrated and discovered in the organism. Mass spectrometry (MS)-based lipidomics approaches are the most powerful and effective tools for analysis of cellular lipidomes with very high sensitivity and specificity. However, the artifacts generated from in-source fragmentation are always present in all kinds of ion sources, even soft ionization techniques (i.e., electrospray ionization and matrix-assisted laser desorption/ionization [MALDI]). These artifacts can cause many problems for lipidomics, especially when the fragment ions correspond to/are isomeric species of other endogenous lipid species in complex biological samples. These commonly observed artifacts could lead to misannotation, false identification, and consequently, incorrect attribution of phenotypes, and will have negative impact on any MS-based lipidomics research including but not limited to biomarker discovery, drug development, etc. Liquid chromatography-MS, shotgun lipidomics, and MALDI-MS imaging are three representative lipidomics approaches in which ion source-generated artifacts are all manifested and are comprehensively summarized in this article. The strategies on how to avoid/reduce the artifacts of in-source fragmentation on lipidomics analysis are also discussed in detail. We believe that with the recognition and avoidance of ion source-generated artifacts, MS-based lipidomics approaches will provide better accuracy on comprehensive analysis of biological samples and will make greater contribution to the research on metabolism and translational/precision medicine (collectively termed functional lipidomics). © 2020 John Wiley & Sons Ltd. Mass Spec Rev.

Lipidomic approaches to dissect dysregulated lipid metabolism in kidney disease

Dyslipidaemia is a hallmark of chronic kidney disease (CKD). The severity of dyslipidaemia not only correlates with CKD stage but is also associated with CKD-associated cardiovascular disease and mortality. Understanding how lipids are dysregulated in CKD is, however, challenging owing to the incredible diversity of lipid structures. CKD-associated dyslipidaemia occurs as a consequence of complex interactions between genetic, environmental and kidney-specific factors, which to understand, requires an appreciation of perturbations in the underlying network of genes, proteins and lipids. Modern lipidomic technologies attempt to systematically identify and quantify lipid species from biological systems. The rapid development of a variety of analytical platforms based on mass spectrometry has enabled the identification of complex lipids at great precision and depth. Insights from lipidomics studies to date suggest that the overall architecture of free fatty acid partitioning between fatty acid oxidation and complex lipid fatty acid composition is an important driver of CKD progression. Available evidence suggests that CKD progression is associated with metabolic inflexibility, reflecting a diminished capacity to utilize free fatty acids through β-oxidation, and resulting in the diversion of accumulating fatty acids to complex lipids such as triglycerides. This effect is reversed with interventions that improve kidney health, suggesting that targeting of lipid abnormalities could be beneficial in preventing CKD progression.

Gangliosides in Podocyte Biology and Disease

Gangliosides constitute a subgroup of glycosphingolipids characterized by the presence of sialic acid residues in their structure. As constituents of cellular membranes, in particular of raft microdomains, they exert multiple functions, some of them capital in cell homeostasis. Their presence in cells is tightly regulated by a balanced expression and function of the enzymes responsible for their biosynthesis, ganglioside synthases, and their degradation, glycosidases. The dysregulation of their abundance results in rare and common diseases. In this review, we make a point on the relevance of gangliosides and some of their metabolic precursors, such as ceramides, in the function of podocytes, the main cellular component of the glomerular filtration barrier, as well as their implications in podocytopathies. The results presented in this review suggest the pertinence of clinical lipidomic studies targeting these metabolites.

Distinctive lipid signatures of bronchial epithelial cells associated with cystic fibrosis drugs, including Trikafta

In recent years, a number of drugs have been approved for the treatment of cystic fibrosis (CF). Among them, newly released Trikafta, a combination of 3 drugs (VX-661/VX-445/VX-770), holds great promise to radically improve the quality of life for a large portion of patients with CF carrying 1 copy of F508del, the most frequent CF transmembrane conductance regulator (CFTR) mutation. Currently available disease-modifying CF drugs work by rescuing the function of the mutated CFTR anion channel. Recent research has shown that membrane lipids, and the cell lipidome in general, play a significant role in the mechanism of CFTR-defective trafficking and, on the other hand, its rescue. In this paper, by using untargeted lipidomics on CFBE41o- cells, we identified distinctive changes in the bronchial epithelial cell lipidome associated with treatment with Trikafta and other CF drugs. Particularly interesting was the reduction of levels of ceramide, a known molecular player in the induction of apoptosis, which appeared to be associated with a decrease in the susceptibility of cells to undergo apoptosis. This evidence could account for additional beneficial roles of the triple combination of drugs on CF phenotypes.

TLR2 Expression on Select Lymphocyte Subsets as a New Marker in Glomerulonephritis

Toll-like receptor (TLR) signaling may be involved in autoimmune kidney disorders and has been implicated in proliferative and non-proliferative glomerulonephritis (PGN and NPGN). In this study, we investigated the expression of TLR2 on T and B lymphocytes in relation to selected clinical parameters in patients with PGN and NPGN. We collected peripheral blood from the ulnar vein of patients with PGN (n = 15) or NPGN (n = 22) and healthy volunteers (n = 20). The percentage of peripheral blood mononuclear cells expressing TLR2 was determined with flow cytometry. TLR2 expression on T and B lymphocytes was increased in PGN patients compared with NPGN patients and controls (p ≤ 0.001). In patients with PGN, TLR2 expression correlated negatively with the serum concentrations of IgG and albumin and positively with urine protein excretion. Receiver operating characteristic (ROC) analysis indicated that TLR2 expression is a highly specific marker to distinguish PGN patients from NPGN patients and controls, especially on CD4+ T lymphocytes. Its use as a non-invasive marker of disease should be further investigated.

"Lipidomics": Mass spectrometric and chemometric analyses of lipids

Lipids are ubiquitous in the human organism and play essential roles as components of cell membranes and hormones, for energy storage or as mediators of cell signaling pathways. As crucial mediators of the human metabolism, lipids are also involved in metabolic diseases, cardiovascular and renal diseases, cancer and/or hepatological and neurological disorders. With rapidly growing evidence supporting the impact of lipids on both the genesis and progression of these diseases as well as patient wellbeing, the characterization of the human lipidome has gained high interest and importance in life sciences and clinical diagnostics within the last 15 years. This is mostly due to technically advanced molecular identification and quantification methods, mainly based on mass spectrometry. Mass spectrometry has become one of the most powerful tools for the identification of lipids. New lipidic mediators or biomarkers of diseases can be analysed by state-of-the art mass spectrometry techniques supported by sophisticated bioinformatics and biostatistics. The lipidomic approach has developed dramatically in the realm of life sciences and clinical diagnostics due to the available mass spectrometric methods and in particular due to the adaptation of biostatistical methods in recent years. Therefore, the current knowledge of lipid extraction methods, mass-spectrometric approaches, biostatistical data analysis, including workflows for the interpretation of lipidomic high-throughput data, are reviewed in this manuscript.