A lipidomic cell-based assay for studying drug-induced phospholipidosis and steatosis

1H NMR spectroscopic characterisation of HepG2 cells as a model metabolic system for toxicology studies

The immortalised human hepatocellular HepG2 cell line is commonly used for toxicology studies as an alternative to animal testing due to its characteristic liver-distinctive functions. However, little is known about the baseline metabolic changes within these cells upon toxin exposure. We have applied 1H Nuclear Magnetic Resonance (NMR) spectroscopy to characterise the biochemical composition of HepG2 cells at baseline and post-exposure to hydrogen peroxide (H2O2). Metabolic profiles of live cells, cell extracts, and their spent media supernatants were obtained using 1H high-resolution magic angle spinning (HR-MAS) NMR and 1H NMR spectroscopic techniques. Orthogonal partial least squares discriminant analysis (O-PLS-DA) was used to characterise the metabolites that differed between the baseline and H2O2 treated groups. The results showed that H2O2 caused alterations to 10 metabolites, including acetate, glutamate, lipids, phosphocholine, and creatine in the live cells; 25 metabolites, including acetate, alanine, adenosine diphosphate (ADP), aspartate, citrate, creatine, glucose, glutamine, glutathione, and lactate in the cell extracts, and 22 metabolites, including acetate, alanine, formate, glucose, pyruvate, phenylalanine, threonine, tryptophan, tyrosine, and valine in the cell supernatants. At least 10 biochemical pathways associated with these metabolites were disrupted upon toxin exposure, including those involved in energy, lipid, and amino acid metabolism. Our findings illustrate the ability of NMR-based metabolic profiling of immortalised human cells to detect metabolic effects on central metabolism due to toxin exposure. The established data sets will enable more subtle biochemical changes in the HepG2 model cell system to be identified in future toxicity testing.

Label-Free Screening of Drug-Induced Liver Injury Using Stimulated Raman Scattering Microscopy and Spectral Phasor Analysis

Hepatic toxicity is a leading cause of the termination of clinical trials and the withdrawal of therapeutics following regulatory approval. The detection of drug-induced liver injury (DILI) is therefore of importance to ensure patient safety and the effectiveness of novel small molecules and drugs. DILI encompasses drug-induced steatosis (DIS) and drug-induced phospholipidosis (DIPL) which involve the accumulation of excess intracellular lipids. Here, we develop hyperspectral stimulated Raman scattering (SRS) microscopy as a label-free methodology for discriminating DIS and DIPL in mammalian cell culture. We demonstrate that hyperspectral SRS imaging in tandem with spectral phasor analysis is capable of discriminating DIS and DIPL based on the nature and distribution of intracellular lipids resulting from each process. To demonstrate the practical application of this methodology, we develop a panel of alkyne-tagged propranolol analogues that display varying DILI effects. Using hyperspectral SRS imaging together with spectral phasor analysis, our label-free methodology corroborated the standard fluorescence-based assay for DILI. As a label-free screening method, it offers a convenient and expedient methodology for visualizing hepatotoxicity in cell cultures which could be integrated into the early stages of the drug development process for screening new chemical entities for DILI.

New Pathophysiological Insights from Serum Proteome Profiling in Equine Atypical Myopathy

Equine atypical myopathy (AM) is a severe environmental intoxication linked to the ingestion of protoxins contained in seeds and seedlings of the sycamore maple (Acer pseudoplatanus) in Europe. The toxic metabolites cause a frequently fatal rhabdomyolysis syndrome in grazing horses. Since these toxic metabolites can also be present in cograzing horses, it is still unclear as to why, in a similar environmental context, some horses show signs of AM, whereas others remain clinically healthy. Label-free proteomic analyses on the serum of 26 diseased AM, 23 cograzers, and 11 control horses were performed to provide insights into biological processes and pathways. A total of 43 and 44 differentially abundant proteins between "AM vs cograzing horses" and "AM vs control horses" were found. Disease-linked changes in the proteome of different groups were found to correlate with detected amounts of toxins, and principal component analyses were performed to identify the 29 proteins representing a robust AM signature. Among the pathway-specific changes, the glycolysis/gluconeogenesis pathway, the coagulation/complement cascade, and the biosynthesis of amino acids were affected. Sycamore maple poisoning results in a combination of inflammation, oxidative stress, and impaired lipid metabolism, which is trying to be counteracted by enhanced glycolysis.

The effect of tacrolimus-induced toxicity on metabolic profiling in target tissues of mice

Tacrolimus (Tac) is a common immunosuppressant that used in organ transplantation. However, its therapeutic index is narrow, and it is prone to adverse side effects, along with an increased risk of toxicity, namely, cardio-, nephro-, hepato-, and neurotoxicity. Prior metabolomic investigations involving Tac-driven toxicity primarily focused on changes in individual organs. However, extensive research on multiple matrices is uncommon. Hence, in this research, the authors systemically evaluated Tac-mediated toxicity in major organs, namely, serum, brain, heart, liver, lung, kidney, and intestines, using gas chromatography-mass spectrometry (GC-MS). The authors also employed multivariate analyses, including orthogonal projections to the latent structure (OPLS) and t-test, to screen 8 serum metabolites, namely, D-proline, glycerol, D-fructose, D-glucitol, sulfurous acid, 1-monopalmitin (MG (16:0/0:0/0:0)), glycerol monostearate (MG (0:0/18:0/0:0)), and cholesterol. Metabolic changes within the brain involved alterations in the levels of butanamide, tartronic acid, aminomalonic acid, scyllo-inositol, dihydromorphine, myo-inositol, and 11-octadecenoic acid. Within the heart, the acetone and D-fructose metabolites were altered. In the liver, D-glucitol, L-sorbose, palmitic acid, myo-inositol, and uridine were altered. In the lung, L-lactic acid, L-5-oxoproline, L-threonine, phosphoric acid, phosphorylethanolamine, D-allose, and cholesterol were altered. Lastly, in the kidney, L-valine and D-glucose were altered. Our findings will provide a systematic evaluation of the metabolic alterations in target organs within a Tac-driven toxicity mouse model.

Preliminary study to classify mechanisms of mitochondrial toxicity by in vitro metabolomics and bioinformatics

AIM

Mitochondrial toxicity is one of the causes for drug-induced liver injury, and the classification of phenotypes or mitochondrial toxicity are highly required though there are no molecular-profiling approaches for classifying mitochondrial toxicity. Therefore, the aim of this study was to classify the mechanisms of mitochondrial toxicity by metabolic profiling in vitro and bioinformatics.

MAIN METHODS

We applied an established gas chromatography tandem mass spectrometry-based metabolomics to human hepatoma grade 2 (HepG2) cells that were exposed to mitochondrial toxicants, whose mechanisms are different, such as rotenone (0.1 μM), carbonyl cyanide-3-chlorophenylhydrazone (CCCP, 0.5 μM), nefazodone (20 μM), perhexiline (6.25 μM), or digitonin (positive cytotoxic substance, 4 μM). These concentrations were determined by the Mitochondrial ToxGlo Assay. Galactose medium was used for suppressing the Warburg effect in HepG2 cells, and the metabolome analysis successfully identified 125 metabolites in HepG2 cells. Multivariate, metabolic pathway and network analyses were performed by the R software.

KEY FINDINGS

Metabolic profiling enabled the classifying the mitochondrial toxicity mechanisms of RCC inhibition and uncoupling. The metabolic profiles of respiratory chain complex (RCC) inhibitors (rotenone and nefazodone) and an uncoupler (CCCP) were fully differentiated from those of other compounds. The metabolic pathway analysis revealed that the RCC inhibitors and the uncoupler mainly disrupted TCA-cycle and related metabolic pathways. In addition, the correlation-based network analysis revealed that succinic acid, β-alanine, and glutamic acid were potential metabolic indicators for RCC inhibition and uncoupling.

SIGNIFICANCE

Our results provided new insights into classifying mechanisms of mitochondrial toxicity by in vitro metabolomics.

In Vitro Models for Studying Chronic Drug-Induced Liver Injury

Drug-induced liver injury (DILI) is a major clinical problem in terms of patient morbidity and mortality, cost to healthcare systems and failure of the development of new drugs. The need for consistent safety strategies capable of identifying a potential toxicity risk early in the drug discovery pipeline is key. Human DILI is poorly predicted in animals, probably due to the well-known interspecies differences in drug metabolism, pharmacokinetics, and toxicity targets. For this reason, distinct cellular models from primary human hepatocytes or hepatoma cell lines cultured as 2D monolayers to emerging 3D culture systems or the use of multi-cellular systems have been proposed for hepatotoxicity studies. In order to mimic long-term hepatotoxicity in vitro, cell models, which maintain hepatic phenotype for a suitably long period, should be used. On the other hand, repeated-dose administration is a more relevant scenario for therapeutics, providing information not only about toxicity, but also about cumulative effects and/or delayed responses. In this review, we evaluate the existing cell models for DILI prediction focusing on chronic hepatotoxicity, highlighting how better characterization and mechanistic studies could lead to advance DILI prediction.

Lipidomics of Cell Secretome Combined with the Study of Selected Bioactive Lipids in an In Vitro Model of Osteoarthritis

Analytical advancements in lipidomics have enabled large-scale investigations of lipid biology. Herein, we focused on four bioactive lipid families, namely polyunsaturated fatty acids, eicosanoids, endocannabinoids, and N-acylethanolamines, and their involvement in the mesenchymal stem cells (MSC)-related inflammatory scenario. Since MSC secretome may represent a valid therapeutic alternative, here, the complete secretome and its vesicular component from adipose- and bone marrow-derived MSC and dermal fibroblasts were characterized by targeted mass spectrometry lipidomics. The 2-arachidonoylglycerol (2AG) and the palmitoylethanolamide (PEA), previously quantified in the MSC's secretome, were further investigated by assessing hypothetical effects in an in vitro model of osteoarthritis (OA) based on human primary articular chondrocytes (CH) stimulated with tumor necrosis factor alpha (TNFα). TNFα enhances the release of the inflammatory lipid prostaglandin E2 (PGE2), and an additional increment was observed when CH were treated with both TNFα and 2AG. In contrast, PEA downmodulates the PGE2 release to the levels of unstimulated CH suggesting a protective effect. TNFα also increases the expression of cyclooxygenase 2 (COX2), in particular when combined with 2AG, while PEA partly blunts TNFα-induced COX2 expression. In addition, TNFα-stimulated CH produce significantly higher levels of the inflammatory mediator nitric oxide (NO) both in the presence and in the absence of 2AG, and PEA was able to partially reduce NO release. Our results show a first partial lipidomic profile of MSC and DF secretome and suggest a possible implication of bioactive lipids in the OA scenario and in the future use of these cell-free products as innovative therapeutics.

Cell Models and Omics Techniques for the Study of Nonalcoholic Fatty Liver Disease: Focusing on Stem Cell-Derived Cell Models

Nonalcoholic fatty liver disease (NAFLD) is now the leading cause of chronic liver disease in western countries. The molecular mechanisms leading to NAFLD are only partially understood, and effective therapeutic interventions are clearly needed. Therefore, preclinical research is required to improve knowledge about NAFLD physiopathology and to identify new therapeutic targets. Primary human hepatocytes, human hepatic cell lines, and human stem cell-derived hepatocyte-like cells exhibit different hepatic phenotypes and have been widely used for studying NAFLD pathogenesis. In this paper, apart from employing the different in vitro cell models for the in vitro assessment of NAFLD, we also reviewed other approaches (metabolomics, transcriptomics, and high-content screening). We aimed to summarize the characteristics of different cell types and methods and to discuss their major advantages and disadvantages for NAFLD modeling.

Bioactive Lipids in MSCs Biology: State of the Art and Role in Inflammation

Lipidomics is a lipid-targeted metabolomics approach that aims to the comprehensive analysis of lipids in biological systems in order to highlight the specific functions of lipid species in health and disease. Lipids play pivotal roles as they are major structural components of the cellular membranes and energy storage molecules but also, as most recently shown, they act as functional and regulatory components of intra- and intercellular signaling. Herein, emphasis is given to the recently highlighted roles of specific bioactive lipids species, as polyunsaturated fatty acids (PUFA)-derived mediators (generally known as eicosanoids), endocannabinoids (eCBs), and lysophospholipids (LPLs), and their involvement in the mesenchymal stem cells (MSCs)-related inflammatory scenario. Indeed, MSCs are a heterogenous population of multipotent cells that have attracted much attention for their potential in regulating inflammation, immunomodulatory capabilities, and reparative roles. The lipidomics of the inflammatory disease osteoarthritis (OA) and the influence of MSCs-derived lipids have also been addressed.

Lipid Mediated Regulation of Adult Stem Cell Behavior

Adult stem cells constitute an important reservoir of self-renewing progenitor cells and are crucial for maintaining tissue and organ homeostasis. The capacity of stem cells to self-renew or differentiate can be attributed to distinct metabolic states, and it is now becoming apparent that metabolism plays instructive roles in stem cell fate decisions. Lipids are an extremely vast class of biomolecules, with essential roles in energy homeostasis, membrane structure and signaling. Imbalances in lipid homeostasis can result in lipotoxicity, cell death and diseases, such as cardiovascular disease, insulin resistance and diabetes, autoimmune disorders and cancer. Therefore, understanding how lipid metabolism affects stem cell behavior offers promising perspectives for the development of novel approaches to control stem cell behavior either in vitro or in patients, by modulating lipid metabolic pathways pharmacologically or through diet. In this review, we will first address how recent progress in lipidomics has created new opportunities to uncover stem-cell specific lipidomes. In addition, genetic and/or pharmacological modulation of lipid metabolism have shown the involvement of specific pathways, such as fatty acid oxidation (FAO), in regulating adult stem cell behavior. We will describe and compare findings obtained in multiple stem cell models in order to provide an assessment on whether unique lipid metabolic pathways may commonly regulate stem cell behavior. We will then review characterized and potential molecular mechanisms through which lipids can affect stem cell-specific properties, including self-renewal, differentiation potential or interaction with the niche. Finally, we aim to summarize the current knowledge of how alterations in lipid homeostasis that occur as a consequence of changes in diet, aging or disease can impact stem cells and, consequently, tissue homeostasis and repair.

Chemometrics-assisted optimization of liquid chromatography-quadrupole-time-of-flight mass spectrometry analysis for targeted metabolomics

Mass spectrometry-based metabolomics is characterized by a vast number of variables leading to a great degree of complexity. In this work, we aimed to simplify this process with a stepped chemometric optimization of the both funnel technology (funnel exit DC, FDC; funnel RF LP, FLC; funnel RF HP, FRP) and ion source parameters (Octopolo, Oct; and Fragmentor, Frag) of a quadrupole-time of flight (qTOF) for a human urinary metabolites. The workflow comprised a Box-Behnken experimental design with 47 experiments followed by the identification and quantification of a set of metabolites using high-resolution full-scan MS mode and feature extraction with an inclusion list. Metabolite peak areas were grouped according to abundance (high and low) and modeled by Random Forest regression (variance explained >85%). The full three-level factorial design consisting in 243 experiments was predicted and top 10 solutions for desirability function and those comprising the Pareto front were extracted and investigated. To guarantee the quality of results, we compared the Pareto front solutions with those achieved by standard instrumental parameters suggested by the manufacturer. A set of five solutions were identified that increased the mean peak area by 56-59% and 17%, for high- and low-abundance metabolites, respectively. The optimal parameters were determined to be: FLP, 100 V; FDC, 40 and 30 V; Frag, 275 and 400 V; and Oct, 600 and 800 V. The methodology applied throughout this work represents a flexible strategy to optimize instrumental parameters and exploit the performance of a qTOF MS detector.

An Integrative Overview of Non-Amyloid and Non-Tau Pathologies in Alzheimer's Disease

Alzheimer's disease (AD) is a neurodegenerative disease that devastates the lives of its victims, and challenges the family members and health care infrastructures that care for them. Clinically, attempts to understand AD have focused on trying to predict the presence of, and more recently demonstrate the presence of, its characteristic amyloid plaque and neurofibrillary tangle pathologies. Fundamental research has also traditionally focused on understanding the generation, content, and pathogenicity of plaques and tangles, but in addition to this there is now an emerging independent interest in other molecular phenomena including apolipoprotein E, lipid metabolism, neuroinflammation, and mitochondrial function. While studies emphasizing the role of these phenomena have provided valuable AD insights, it is interesting that at the molecular level these entities extensively intertwine and interact. In this review, we provide a brief overview of why apolipoprotein E, lipid metabolism, neuroinflammation, and mitochondrial research have become increasingly ascendant in the AD research field, and present the case for studying these phenomena from an integrated perspective.

LipidMS: An R Package for Lipid Annotation in Untargeted Liquid Chromatography-Data Independent Acquisition-Mass Spectrometry Lipidomics

High resolution LC-MS untargeted lipidomics using data independent acquisition (DIA) has the potential to increase lipidome coverage, as it enables the continuous and unbiased acquisition of all eluting ions. However, the loss of the link between the precursor and the product ions combined with the high dimensionality of DIA data sets hinder accurate feature annotation. Here, we present LipidMS, an R package aimed to confidently identify lipid species in untargeted LC-DIA-MS. To this end, LipidMS combines a coelution score, which links precursor and fragment ions with fragmentation and intensity rules. Depending on the MS evidence reached by the identification function survey, LipidMS provides three levels of structural annotations: (i) "subclass level", e.g., PG(34:1); (ii) "fatty acyl level", e.g., PG(16:0_18:1); and (iii) "fatty acyl position level", e.g., PG(16:0/18:1). The comparison of LipidMS with freely available data dependent acquisition (DDA) and DIA identification tools showed that LipidMS provides significantly more accurate and structural informative lipid identifications. Finally, to exemplify the utility of LipidMS, we investigated the lipidomic serum profile of patients diagnosed with nonalcoholic steatohepatitis (NASH), which is the progressive form of nonalcoholic fatty liver disease, a disorder underlying a strong lipid dysregulation. As previously published, a significant decrease in lysophosphatidylcholines, phosphatidylcholines and cholesterol esters and an increase in phosphatidylethanolamines were observed in NASH patients. Remarkably, LipidMS allowed the identification of a new set of lipids that may be used for NASH diagnosis. Altogether, LipidMS has been validated as a tool to assist lipid identification in the LC-DIA-MS untargeted analysis of complex biological samples.

Lipidomics unveils the complexity of the lipidome in metabolic diseases

Dysregulation of lipid metabolism is responsible for pathologies of human diseases including metabolic diseases. Recent advances in lipidomics analysis allow for the targeted and untargeted identification of lipid species and for their quantification in normal and diseased conditions. Herein, this review provides a brief introduction to lipidomics, highlights its application to characterize the lipidome at the cellular and physiological levels under different biological conditions, and discusses the potential for the use of lipidomics in the discovery of biomarkers.