Matrix-assisted laser desorption/ionization imaging mass spectrometry reveals changes of phospholipid distribution in induced pluripotent stem cell colony differentiation

A Critical Overview of HPLC-MS-Based Lipidomics in Determining Triacylglycerol and Phospholipid in Foods

With the current advancement in mass spectrometry (MS)-based lipidomics, the knowledge of lipidomes and their diverse roles has greatly increased, enabling a deeper understanding of the action of bioactive lipid molecules in plant- and animal-based foods. This review provides in-depth information on the practical use of MS techniques in lipidomics, including lipid extraction, adduct formation, MS analysis, data processing, statistical analysis, and bioinformatics. Moreover, this contribution demonstrates the effectiveness of MS-based lipidomics for identifying and quantifying diverse lipid species, especially triacylglycerols and phospholipids, in foods. Further, it summarizes the wide applications of MS-based lipidomics in food science, such as for assessing food processing methods, detecting food adulteration, and measuring lipid oxidation in foods. Thus, MS-based lipidomics may be a useful method for identifying the action of individual lipid species in foods.

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

Induced pluripotent stem cells (iPSCs) hold great promise in regenerative medicine; however, few algorithms of quality control at the earliest stages of differentiation have been established. Despite lipids having known functions in cell signaling, their role in pluripotency maintenance and lineage specification is underexplored. We investigated the changes in iPSC lipid profiles during the initial loss of pluripotency over the course of spontaneous differentiation using the co-registration of confocal microscopy and matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging. We identified phosphatidylethanolamine (PE) and phosphatidylinositol (PI) species that are highly informative of the temporal stage of differentiation and can reveal iPS cell lineage bifurcation occurring metabolically. Several PI species emerged from the machine learning analysis of MS data as the early metabolic markers of pluripotency loss, preceding changes in the pluripotency transcription factor Oct4. The manipulation of phospholipids via PI 3-kinase inhibition during differentiation manifested in the spatial reorganization of the iPS cell colony and elevated expression of NCAM-1. In addition, the continuous inhibition of phosphatidylethanolamine N-methyltransferase during differentiation resulted in the enhanced maintenance of pluripotency. Our machine learning analysis highlights the predictive power of lipidomic metrics for evaluating the early lineage specification in the initial stages of spontaneous iPSC differentiation.

Cellular and Molecular Control of Lipid Metabolism in Idiopathic Pulmonary Fibrosis: Clinical Application of the Lysophosphatidic Acid Pathway

Idiopathic pulmonary fibrosis (IPF) is a representative disease that causes fibrosis of the lungs. Its pathogenesis is thought to be characterized by sustained injury to alveolar epithelial cells and the resultant abnormal tissue repair, but it has not been fully elucidated. IPF is currently difficult to cure and is known to follow a chronic progressive course, with the patient's survival period estimated at about three years. The disease occasionally exacerbates acutely, leading to a fatal outcome. In recent years, it has become evident that lipid metabolism is involved in the fibrosis of lungs, and various reports have been made at the cellular level as well as at the organic level. The balance among eicosanoids, sphingolipids, and lipid composition has been reported to be involved in fibrosis, with particularly close attention being paid to a bioactive lipid "lysophosphatidic acid (LPA)" and its pathway. LPA signals are found in a wide variety of cells, including alveolar epithelial cells, vascular endothelial cells, and fibroblasts, and have been reported to intensify pulmonary fibrosis via LPA receptors. For instance, in alveolar epithelial cells, LPA signals reportedly induce mitochondrial dysfunction, leading to epithelial damage, or induce the transcription of profibrotic cytokines. Based on these mechanisms, LPA receptor inhibitors and the metabolic enzymes involved in LPA formation are now considered targets for developing novel means of IPF treatment. Advances in basic research on the relationships between fibrosis and lipid metabolism are opening the path to new therapies targeting lipid metabolism in the treatment of IPF.

Changes of Mass Spectra Patterns on a Brain Tissue Section Revealed by Deep Learning with Imaging Mass Spectrometry Data

The characteristic patterns of mass spectra in imaging mass spectrometry (IMS) strongly reflect the tissue environment. However, the boundaries formed where different tissue environments collide have not been visually assessed. In this study, IMS and convolutional neural network (CNN), one of the deep learning methods, were applied to the extraction of characteristic mass spectra patterns from training brain regions on rodents' brain sections. CNN produced classification models with high accuracy and low loss rate in any test data sets of mouse coronal sections measured by desorption electrospray ionization (DESI)-IMS and of mouse and rat sagittal sections by matrix-assisted laser desorption (MALDI)-IMS. On the basis of the extracted mass spectra pattern features, the histologically plausible segmentation and classification score imaging of the brain sections were obtained. The boundary imaging generated from classification scores showed the extreme changes of mass spectra patterns between the tissue environments, with no significant buffer zones for the intermediate state. The CNN-based analysis of IMS data is a useful tool for visually assessing the changes of mass spectra patterns on a tissue section, and it will contribute to a comprehensive view of the tissue environment.

Metabolic changes induced by TGF-β1 via reduced expression of phosphatidylserine decarboxylase during myofibroblast transition

Metabolic alteration is increasingly recognized as an important pathogenic process that underlies fibrosis across many organ types, and metabolically targeted therapies could become important strategies for reducing fibrosis. In present study, target enzymes that are involved in changes in phospholipid metabolism during fibroblast-to-myofibroblast transition induced by transforming growth factor beta 1 (TGF-β1) were examined. Different amounts of phospholipids were found in the 2 groups. In response to TGF-β1 stimulation, 17 lipids decreased and 17 increased. The latter included the phospholipids phosphatidylcholine (PC), phosphatidylserine (PS), and phosphatidylethanolamine (PE). Furthermore, among the rate-limiting enzymes that regulate these phospholipids, phosphatidylserine decarboxylase (PISD), which controls conversion of PS to PE and is localized in mitochondria, decreased in response to TGF-β1. Knockdown of PISD alone without TGF-β1 stimulation increased expression of α-smooth muscle actin mRNA and production of total collagen. Taken together, these results indicate that PISD is involved in the mechanism of fibrogenesis by regulating phospholipid metabolism.

Imaging of lysophosphatidylcholine in an induced pluripotent stem cell-derived endothelial cell network

Introduction

Vascular endothelial cell disorders are closely related to cardiovascular disease (CVD) and pulmonary diseases. Abnormal lipid metabolism in the endothelium leads to changes in cell signalling, and the expression of genes related to immunity and inflammation. It is therefore important to investigate the pathophysiology of vascular endothelial disorders in terms of lipid metabolism, using a disease model of endothelium.

Methods

Human induced pluripotent stem cell-derived endothelial cells (iECs) were cultured on a matrigel to form an iEC network. Lipids in the iEC network were investigated by matrix-assisted laser desorption/ionization (MALDI) time-of-flight (TOF) imaging mass spectrometry (IMS) analysis. Ion fragments obtained by mass spectrometry were analysed using an infusion method, involving precursor ion scanning with fragment ion.

Results

The MALDI TOF IMS analysis revealed co-localized intensity of peaks at m/z 592.1 and 593.1 in the iEC network. Tandem mass spectrometry (MS/MS) analysis by MALDI-imaging, in conjunction with precursor ion scanning using an infusion method with lipid extracts, identified that these precursor ions were lysophosphatidylcholine (LPC) (22:5) and its isotype.

Conclusion

The MALDI-imaging analysis showed that LPC (22:5) was abundant in an iEC network. As an in vitro test model for disease and potential therapy, present analysis methods using MALDI-imaging combined with, for example, mesenchymal stem cells (MSC) to a disease derived iEC network may be useful in revealing the changes in the amount and distribution of lipids under various stimuli.

A Co-registration Pipeline for Multimodal MALDI and Confocal Imaging Analysis of Stem Cell Colonies

Multimodal mass spectrometry imaging (MSI) data presents unique big data challenges in handling and analysis. Here, we present a pipeline for co-registering matrix-assisted laser desorption/ionization MSI and confocal immunofluorescence imaging data for extracting single-cell metabolite signatures. We further describe methods and introduce software for the simultaneous analysis of these concatenated data sets, which are designed to establish a connection between cell traits of interest (shape metrics, position within sample) and the cells' own metabolic signatures.

Phospholipid remodeling is critical for stem cell pluripotency by facilitating mesenchymal-to-epithelial transition

Metabolic reprogramming has emerged as a key regulator of cell fate decisions. Roles of glucose and amino acid metabolism have been extensively documented, whereas lipid metabolism in pluripotency remains largely unexplored. Using a high-coverage lipidomics approach, we reveal dynamic changes in phospholipids occurring during reprogramming and show that the CDP-ethanolamine (CDP-Etn) pathway for phosphatidylethanolamine (PE) synthesis is required at the early stage of reprogramming. Mechanistically, the CDP-Etn pathway inhibits NF-κB signaling and mesenchymal genes in a Pebp1-dependent manner, without affecting autophagy, resulting in accelerated mesenchymal-to-epithelial transition (MET) and enhanced reprogramming. Furthermore, PE binding to Pebp1 enhances the interaction of Pebp1 with IKKα/β and reduces the phosphorylation of IKKα/β. The CDP-Etn-Pebp1 axis is associated with EMT/MET in hepatocyte differentiation, indicating that Etn/PE is a broad-spectrum MET/EMT-regulating metabolite. Collectively, our study reveals an unforeseen connection between phospholipids, cell migration, and pluripotency and highlights the importance of phospholipids in cell fate transitions.

Unsupervised machine learning using an imaging mass spectrometry dataset automatically reassembles grey and white matter

Current histological and anatomical analysis techniques, including fluorescence in situ hybridisation, immunohistochemistry, immunofluorescence, immunoelectron microscopy and fluorescent fusion protein, have revealed great distribution diversity of mRNA and proteins in the brain. However, the distributional pattern of small biomolecules, such as lipids, remains unclear. To this end, we have developed and optimised imaging mass spectrometry (IMS), a combined technique incorporating mass spectrometry and microscopy, which is capable of comprehensively visualising biomolecule distribution. We demonstrated the differential distribution of phospholipids throughout the cell body and axon of neuronal cells using IMS analysis. In this study, we used solarix XR, a high mass resolution and highly sensitive MALDI-FT-ICR-MS capable of detecting higher number of molecules than conventional MALDI-TOF-MS instruments, to create a molecular distribution dataset. We examined the diversity of biomolecule distribution in rat brains using IMS and hypothesised that unsupervised machine learning reconstructs brain structures such as the grey and white matters. We have demonstrated that principal component analysis (PCA) can reassemble the grey and white matters without assigning brain anatomical regions. Hierarchical clustering allowed us to classify the 10 groups of observed molecules according to their distributions. Furthermore, the group of molecules specifically localised in the cerebellar cortex was estimated to be composed of phospholipids.

Qualitative analysis of phospholipids and their oxidised derivatives - used techniques and examples of their applications related to lipidomic research and food analysis

Phospholipids (PLs) are important biomolecules that not only constitute structural building blocks and scaffolds of cell and organelle membranes but also play a vital role in cell biochemistry and physiology. Moreover, dietary exogenous PLs are characterised by high nutritional value and other beneficial health effects, which are confirmed by numerous epidemiological studies. For this reason, PLs are of high interest in lipidomics that targets both the analysis of membrane lipid distribution as well as correlates composition of lipids with their effects on functioning of cells, tissues and organs. Lipidomic assessments follow-up the changes occurring in living organisms, such as free radical attack and oxidative modifications of the polyunsaturated fatty acids (PUFAs) build in PL structures. Oxidised PLs (oxPLs) can be generated exogenously and supplied to organisms with processed food or formed endogenously as a result of oxidative stress. Cellular and tissue oxPLs can be a biomarker predictive of the development of numerous diseases such as atherosclerosis or neuroinflammation. Therefore, suitable high-throughput analytical techniques, which enable comprehensive analysis of PL molecules in terms of the structure of hydrophilic group, fatty acid (FA) composition and oxidative modifications of FAs, have been currently developed. This review addresses all aspects of PL analysis, including lipid isolation, chromatographic separation of PL classes and species, as well as their detection. The bioinformatic tools that enable handling of a large amount of data generated during lipidomic analysis are also discussed. In addition, imaging techniques such as confocal microscopy and mass spectrometry imaging for analysis of cellular lipid maps, including membrane PLs, are presented.

Induced Pluripotent Stem Cells for Regenerative Medicine: Quality Control Based on Evaluation of Lipid Composition

Clinical application of induced pluripotent stem cells (iPSCs), which can be differentiated into a wide variety of functional cells, is underway and some clinical trials have already been performed or are ongoing. On the other hand, the risk of carcinogenesis is an issue and the mechanism of cellular reprograming remains unknown. When iPSCs and differentiated cells are used for medical applications, quality control is also important. Here we discuss the possibility of performing quality control of iPSCs by evaluation of phospholipids, which are not just structural components of lipid bilayer membranes, but also have multiple physiological functions. Recently, methods for analysis of lipids have become more widely available and easier to perform. This article reviews the role of iPSCs in regenerative medicine and examines the possibility of using phospholipids for quality control of iPSCs and differentiated cells.

Changes of plasmalogen phospholipid levels during differentiation of induced pluripotent stem cells 409B2 to endothelial phenotype cells

Endothelial cells (EC) are involved in regulating several aspects of lipid metabolism, with recent research revealing the clinicopathological significance of interactions between EC and lipids. Induced pluripotent stem cells (iPSC) have various possible medical uses, so understanding the metabolism of these cells is important. In this study, endothelial phenotype cells generated from human iPSC formed cell networks in co-culture with fibroblasts. Changes of plasmalogen lipids and sphingomyelins in endothelial phenotype cells generated from human iPSC were investigated by reverse-phase ultra-high-pressure liquid chromatography mass spectrometry (UHPLC-MS/MS) analysis. The levels of plasmalogen phosphatidylethanolamines (38:5) and (38:4) increased during differentiation of EC, while sphingomyelin levels decreased transiently. These changes of plasmalogen lipids and sphingomyelins may have physiological significance for EC and could be used as markers of differentiation.

Imaging mass spectrometry identifies prognostic ganglioside species in rodent intracranial transplants of glioma and medulloblastoma

Matrix-assisted laser desorption ionization (MALDI) imaging mass spectrometry (MALDI-MSI) allows us to investigate the distribution of lipid molecules within tissues. We used MALDI-MSI to identify prognostic gangliosides in tissue sections of rat intracranial allografts of rat glioma and mouse intracranial xenografts of human medulloblastoma. In the healthy adult rodent brain, GM1 and GD1 were the main types of glycolipids. Both gangliosides were absent in both intracranial transplants. The ganglioside GM3 was not present in the healthy adult brain but was highly expressed in rat glioma allografts. In combination with tandem mass spectrometry GM3 (d18:1/C24:0) was identified as the most abundant ganglioside species in the glioma allotransplant. By contrast, mouse xenografts of human medulloblastoma were characterized by prominent expression of the ganglioside GM2 (d18:0/C18:0). Together, these data demonstrate that tissue-based MALDI-MSI of gangliosides is able to discriminate between different brain tumors and may be a useful clinical tool for their classification and grading.