Tailored liquid chromatography–mass spectrometry analysis improves the coverage of the intracellular metabolome of HepaRG cells

A multidimensional chromatography/high-resolution mass spectrometry approach for the in-depth metabolites characterization of two Astragalus species

To address the chemical complexity is indispensable in a number of research fields. Herb metabolome is typically composed by more than one class of structure analogs produced via different biosynthetic pathways. Multidimensional chromatography (MDC), due to the greatly enhanced separation space, offers the potential solution to comprehensive characterization of herbal metabolites. Here, we presented a strategy, by integrating MDC and quadrupole time-of-flight mass spectrometry (QTOF-MS), to accomplish the in-depth herbal metabolites characterization. Using the metabolome of two Astragalus species (A. membranaceus var. mongholicus,AMM; A. membranaceus, AM) as the case, an off-line three-dimensional liquid chromatography (3D-LC) system was established: hydrophilic interaction chromatography using an XAmide column as the first dimension (¹D) for fractionating the total extract, on-line reversed-phase × reversed-phase liquid chromatography separately configuring a CSH Fluoro-Phenyl column and a Cosmocore C18 column as the second dimension (²D) and the third dimension (³D) of chromatography to enable the explicit separation of three well fractionated samples. Moreover, the negative-mode collision-induced dissociation by QTOF-MS under the optimized condition could provide diversified fragments that were useful for the structural elucidation of AMM and AM. An in-house library (composed by 247 known compounds) and comparison with 43 reference standards were utilized to assist more reliable characterization. We could characterize 513 compounds from two Astragalus species (344 from AMM and 323 from AM), including 236 flavonoids, 150 triterpenoids, 18 organic acids, and 109 others. Conclusively, the established MDC approach gained excellent performance favoring the analogs-oriented in-depth characterization of herbal metabolites, but received uncompromising analytical efficiency.

Mass Spectrometry-Based Untargeted Metabolomics and Lipidomics Platforms to Analyze Cell Culture Extracts

Metabolites represent the most downstream level of the cellular organization. Hence, an in vitro untargeted metabolomics approach is extremely valuable to deepen the understanding of how endogenous metabolites in cells are altered under a given biological condition. This chapter describes a robust liquid chromatography-high-resolution mass spectrometry-based metabolomics and lipidomics platform applied to cell culture extracts. The analytical workflow includes an optimized sample preparation procedure to cover a wide range of metabolites using liquid-liquid extraction and validated instrumental operation procedures with the implementation of comprehensive quality assurance and quality control measures to ensure high reproducibility. The lipidomics platform is based on reversed-phase liquid chromatography for the separation of slightly polar to apolar metabolites and covers a broad range of lipid classes, while the metabolomics platform makes use of two hydrophilic interaction liquid chromatography methods for the separation of polar metabolites, such as organic acids, amino acids, and sugars. The chapter focuses on the analysis of cultured HepaRG cells that are derived from a human hepatocellular carcinoma; however, the sample preparation and analytical platforms can easily be adapted for other types of cells.

Lipidomics profiling of zebrafish liver through untargeted liquid chromatography-high resolution mass spectrometry

Lipidomics analysis of zebrafish tissues has shown promising results to understand disease-related outcomes of exposure to toxic substances at molecular level. However, knowledge about their lipidome is limited, as most untargeted studies only identify the lipids that are statistically significant in their setup. In this work, liquid chromatography-high resolution mass spectrometry was used to study different aspects of the analytical workflow, i.e., extraction solvents (methanol/chloroform/water (3/2/2, v/v/v), methanol/dichloromethane/water (2/3/2, v/v/v) and methanol/methyl-tert-butyl ether/water (3/10/2.5, v/v/v), instrumental response, and strategies used for lipid annotation. The number of high-quality features (relative standard deviation of the intensity values ≤ 10% in the range 10³ -10⁷ counts) was affected by the dilution of lipid extracts, indicating that it is an important parameter for developing untargeted methods. The workflows used allowed the selection of a dilution factor to annotate 712 lipid species (507 bulk lipids) in zebrafish liver using four software (LipidMatch, LipidHunter, MS-DIAL and Lipostar). Retention time mapping was a valuable tool to filter lipid annotations obtained from automatic software annotations. The lipid profiling of zebrafish livers will help in a better understanding of the true constitution of their lipidome at the species level, as well as in the use of zebrafish in toxicological studies. This article is protected by copyright. All rights reserved.

Protective Mechanism of Gandou Decoction in a Copper-Laden Hepatolenticular Degeneration Model: In Vitro Pharmacology and Cell Metabolomics

Gandou decoction (GDD) is a classic prescription for the treatment of hepatolenticular degeneration (HLD) in China; however, the liver-protecting mechanism of this prescription needs further evaluation. In the present study, we explored the protective mechanisms of GDD in a copper-laden HLD model using integrated pharmacology and cellular metabolomics in vitro. The results revealed that GDD could significantly promote copper excretion in copper-laden HLD model cells and improve the ultrastructural changes in hepatocytes. In addition, GDD could decrease the extent of lipid peroxidation, levels of reactive oxygen species, and the release rate of lactate dehydrogenase while increasing the activity of superoxide dismutase and the ratio of glutathione to oxidized glutathione in the copper-laden HLD model cells. On conducting statistical analysis of significant metabolic changes, 47 biomarkers and 30 related metabolic pathways were screened as pharmacological reactions induced by GDD in HLD model cells. d-glutamate and d-glutamine metabolic pathways showed the highest importance and significance among the 30 metabolic pathways, and the differential expression levels of the glutamine synthetase (GS) and the renal type and liver type GLS (GLS1 and GLS2) proteins were verified by Western blotting. Collectively, our data established the underlying mechanism of GDD therapy, such as the promotion of copper excretion and improvement in oxidative stress by regulating the expressions of GS, GLS1, and GLS2 protein to protect hepatocytes from injury.

Optimization of a liquid chromatography-ion mobility-high resolution mass spectrometry platform for untargeted lipidomics and application to HepaRG cell extracts

Analytical methods to evaluate the lipidome of biological samples need to provide high data quality to ensure comprehensive profiling and reliable structural elucidation. In this perspective, liquid chromatography-high resolution mass spectrometry (LC-HRMS) is the state-of-the-art technique for lipidomic analysis of biological samples. There are thousands of lipids in most biological samples, and therefore separation methods before introduction to the mass spectrometer is key for relative quantitation and identification. Chromatographic methods differ across laboratories, without any consensus on the best methodologies. Therefore, we designed an experiment to determine the optimal LC methodology, and assessed the value of ion mobility for an additional dimension of separation. To apply an untargeted method for hypothesis generation focused on lipidomics, LC-HRMS parameters were optimized based on the measurement of 50 panel lipids covering key human metabolic pathways. Reversed-phase liquid chromatography columns were compared based on a quality scoring system considering the signal-to-noise ratio, peak shape, and retention factor. Furthermore, drift tube ion mobility spectrometry (DTIMS) was implemented to increase peak capacity and confidence during annotation by providing collision cross section (CCS) values for the analytes under investigation. However, hyphenating DTIMS to LC-HRMS may result in a reduced sensitivity due to impaired duty cycles. To increase the signal intensity, a Box-Behnken design (BBD) was used to optimize four key factors, i.e. drift entrance voltage, drift exit voltage, rear funnel entrance, and rear funnel exit voltages. Application of a maximized desirability function provided voltages for the above-mentioned parameters resulting in higher signal intensity compared to each combination of parameters used during the BBD. In addition, the influence of single pulse and Hadamard 4-bit multiplexed modes on signal intensity was explored and different trap filling and release times of ions were evaluated. The optimized LC-DTIM-HRMS platform was applied to extracts from HepaRG cells and resulted in 3912 high-quality features (<30% median relative standard deviation; n = 6, t = 24 h). From these features, 436 lipid species could be annotated (i.e., matching based on accurate mass <5 ppm, isotopic pattern, in-silico MS/MS fragmentation, and in-silico CCS database matching <3%). The application of LC-DTIM-HRMS for untargeted analysis workflows is growing and the platform optimization, as described here, can be used to guide the method development and CCS database comparison for high confidence lipid annotation.

Mass Spectrometry-Based Zebrafish Toxicometabolomics: A Review of Analytical and Data Quality Challenges

Metabolomics has achieved great progress over the last 20 years, and it is currently considered a mature research field. As a result, the number of applications in toxicology, biomarker, and drug discovery has also increased. Toxicometabolomics has emerged as a powerful strategy to provide complementary information to study molecular-level toxic effects, which can be combined with a wide range of toxicological assessments and models. The zebrafish model has gained importance in recent decades as a bridging tool between in vitro assays and mammalian in vivo studies in the field of toxicology. Furthermore, as this vertebrate model is a low-cost system and features highly conserved metabolic pathways found in humans and mammalian models, it is a promising tool for toxicometabolomics. This short review aims to introduce zebrafish researchers interested in understanding the effects of chemical exposure using metabolomics to the challenges and possibilities of the field, with a special focus on toxicometabolomics-based mass spectrometry. The overall goal is to provide insights into analytical strategies to generate and identify high-quality metabolomic experiments focusing on quality management systems (QMS) and the importance of data reporting and sharing.

An exploratory approach for an oriented development of an untargeted hydrophilic interaction liquid chromatography-mass spectrometry platform for polar metabolites in biological matrices

The analysis of polar metabolites based on liquid chromatography-mass spectrometry (LC-MS) methods should take into consideration the complexity of interactions in LC columns to be able to cover a broad range of metabolites of key biological pathways. Therefore, in this study, different chromatographic columns were tested for polar metabolites including reversed-phase and hydrophilic interaction liquid chromatography (HILIC) columns. Based on a column screening, two new generations of zwitterionic HILIC columns were selected for further evaluation. A tree-based method optimization was applied to investigate the chromatographic factors affecting the retention mechanisms of polar metabolites with zwitterionic stationary phases. The results were evaluated based on a scoring system which was applied for more than 80 polar metabolites with a high coverage of key human metabolic pathways. The final optimized methods showed high complementarity to analyze a wide range of metabolic classes including amino acids, small peptides, sugars, amino sugars, phosphorylated sugars, organic acids, nucleobases, nucleosides, nucleotides and acylcarnitines. Optimized methods were applied to analyze different biological matrices, including human urine, plasma and liver cell extracts using an untargeted approach. The number of high-quality features (< 30% median relative standard deviation) ranged from 3,755 for urine to 5,402 for the intracellular metabolome of liver cells, showing the potential of the methods for untargeted purposes.

Confirmation of neurometabolic diagnoses using age-dependent cerebrospinal fluid metabolomic profiles

Timely diagnosis is essential for patients with neurometabolic disorders to enable targeted treatment. Next-Generation Metabolic Screening (NGMS) allows for simultaneous screening of multiple diseases and yields a holistic view of disturbed metabolic pathways. We applied this technique to define a cerebrospinal fluid (CSF) reference metabolome and validated our approach with patients with known neurometabolic disorders. Samples were measured using ultra-high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry followed by (un)targeted analysis. For the reference metabolome, CSF samples from patients with normal general chemistry results and no neurometabolic diagnosis were selected and grouped based on sex and age (0-2/2-5/5-10/10-15 years). We checked the levels of known biomarkers in CSF from seven patients with five different neurometabolic disorders to confirm the suitability of our method for diagnosis. Untargeted analysis of 87 control CSF samples yielded 8036 features for semiquantitative analysis. No sex differences were found, but 1782 features (22%) were different between age groups (q < 0.05). We identified 206 diagnostic metabolites in targeted analysis. In a subset of 20 high-intensity metabolites and 10 biomarkers, 17 (57%) were age-dependent. For each neurometabolic patient, ≥1 specific biomarker(s) could be identified in CSF, thus confirming the diagnosis. In two cases, age-matching was essential for correct interpretation of the metabolomic profile. In conclusion, NGMS in CSF is a powerful tool in defining a diagnosis for neurometabolic disorders. Using our database with many (age-dependent) features in CSF, our untargeted approach will facilitate biomarker discovery and further understanding of mechanisms of neurometabolic disorders.

Exposure of HepaRG Cells to Sodium Saccharin Underpins the Importance of Including Non-Hepatotoxic Compounds When Investigating Toxicological Modes of Action Using Metabolomics

Metabolites represent the most downstream information of the cellular organisation. Hence, metabolomics experiments are extremely valuable to unravel the endogenous pathways involved in a toxicological mode of action. However, every external stimulus can introduce alterations in the cell homeostasis, thereby obscuring the involved endogenous pathways, biasing the interpretation of the results. Here we report on sodium saccharin, which is considered to be not hepatotoxic and therefore can serve as a reference compound to detect metabolic alterations that are not related to liver toxicity. Exposure of HepaRG cells to high levels of sodium saccharin (>10 mM) induced cell death, probably due to an increase in the osmotic pressure. Yet, a low number (n = 15) of significantly altered metabolites were also observed in the lipidome, including a slight decrease in phospholipids and an increase in triacylglycerols, upon daily exposure to 5 mM sodium saccharin for 72 h. The observation that a non-hepatotoxic compound can affect the metabolome underpins the importance of correct experimental design and data interpretation when investigating toxicological modes of action via metabolomics.

Integrating a generalized data analysis workflow with the Single-probe mass spectrometry experiment for single cell metabolomics

We conducted single cell metabolomics studies of live cancer cells through online single cell mass spectrometry (SCMS) experiments combined with a generalized comprehensive data analysis workflow. The SCMS experiments were carried out using the Single-probe device coupled with a mass spectrometer to measure molecular profiles of cells in response to two mitotic inhibitors, taxol and vinblastine, under a series of treatment conditions. SCMS metabolomic data were analyzed using a comprehensive approach, including data pre-treatment, visualization, statistical analysis, machine learning, and pathway enrichment analysis. For comparative studies, traditional liquid chromatography-MS (LC-MS) experiments were conducted using lysates prepared from bulk cell samples. Metabolomic profiles of single cells were visualized through Partial Least Square-Discriminant Analysis (PLS-DA), and the phenotypic biomarkers associated with emerging phenotypes induced by drug treatment were discovered and compared through a series of rigorous statistical analysis. Species of interest were further identified at both the single cell and population levels. In addition, four biological pathways potentially involved in the drug treatment were determined through pathway enrichment analysis. Our work demonstrated the capability of comprehensive pipeline studies of single cell metabolomics. This method can be potentially applied to broader types of SCMS datasets for future pharmaceutical and chemotherapeutic research.

Untargeted liquid chromatography-mass spectrometry metabolomics to assess drug-induced cholestatic features in HepaRG® cells

Cholestasis is a liver disease associated with retention of bile in the liver, which leads to local hepatic inflammation and severe liver damage. In order to investigate the mode of action of drug-induced cholestasis, in vitro models have shown to be able to recapitulate important elements of this disease. In this study, we applied untargeted metabolomics to investigate the metabolic perturbances in HepaRG® cells exposed for 24 h and 72 h to bosentan, a cholestatic reference toxicant. Intracellular profiles were extracted and analysed with liquid chromatography and accurate-mass spectrometry. Metabolites of interest were selected using partial least-squares discriminant analysis and random forest classifier models. The observed metabolic patterns associated with cholestasis in vitro were complex. Acute (24 h) exposure revealed metabolites related to apoptosis, such as ceramide and triglyceride accumulation, in combination with phosphatidylethanolamine, choline and carnitine depletion. Metabolomic alterations during exposure to lower dosages and a prolonged exposure (72 h) included carnitine upregulation and changes in the polyamine metabolism. These metabolites were linked to changes in phospholipid metabolism, mitochondrial pathways and energy homeostasis. The metabolic changes confirmed the mitotoxic effects of bosentan and revealed the potential involvement of phospholipid metabolism as part of the mode of action of drug-induced cholestasis.

In-vitro metabolomics to evaluate toxicity of particulate matter under environmentally realistic conditions

In this pilot study three fractions of particulate matter (PM_0.25, PM_2.5-0.25, and PM_10-2.5) were collected in three environments (classroom, home, and outdoors) in a village located nearby an industrial complex. Time-activity pattern of 20 students attending the classroom was obtained, and the dose of particles reaching the children's lungs under actual environmental conditions (i.e. real dose) was calculated via dosimetry model. The highest PM concentrations were reached in the classroom. Simulations showed that heavy intensity outdoor activities played a major role in PM deposition, especially in the upper part of the respiratory tract. The mass of PM_10-2.5 reaching the alveoli was minor, while PM_2.5-0.25 and PM_0.25 apportion for most of the PM mass retained in the lungs. Consequently, PM_2.5-0.25 and PM_0.25 were the only fractions used in two subsequent toxicity assays onto alveolar cells (A549). First, a cytotoxicity dose-response assay was performed, and doses corresponding to 5% mortality (LC₅) were estimated. Afterwards, two LC-MS metabolomic assays were conducted: one applying LC₅, and another applying real dose. A lower estimated LC₅ value was obtained for PM_0.25 than PM_2.5-0.25 (8.08 and 73.7 ng/mL respectively). The number of altered features after LC₅ exposure was similar for both fractions (39 and 38 for PM_0.25 and PM_2.5-0.25 respectively), while after real dose exposure these numbers differed (10 and 5 for PM_0.25 and PM_2.5-0.25 respectively). The most metabolic changes were related to membrane and lung surfactant lipids. This study highlights the capacity of PM to alter metabolic profile of lung cells at conventional environmental levels.

Integrated transcriptomics and metabolomics reveal signatures of lipid metabolism dysregulation in HepaRG liver cells exposed to PCB 126

Chemical pollutant exposure is a risk factor contributing to the growing epidemic of non-alcoholic fatty liver disease (NAFLD) affecting human populations that consume a western diet. Although it is recognized that intoxication by chemical pollutants can lead to NAFLD, there is limited information available regarding the mechanism by which typical environmental levels of exposure can contribute to the onset of this disease. Here, we describe the alterations in gene expression profiles and metabolite levels in the human HepaRG liver cell line, a validated model for cellular steatosis, exposed to the polychlorinated biphenyl (PCB) 126, one of the most potent chemical pollutants that can induce NAFLD. Sparse partial least squares classification of the molecular profiles revealed that exposure to PCB 126 provoked a decrease in polyunsaturated fatty acids as well as an increase in sphingolipid levels, concomitant with a decrease in the activity of genes involved in lipid metabolism. This was associated with an increased oxidative stress reflected by marked disturbances in taurine metabolism. A gene ontology analysis showed hallmarks of an activation of the AhR receptor by dioxin-like compounds. These changes in metabolome and transcriptome profiles were observed even at the lowest concentration (100 pM) of PCB 126 tested. A decrease in docosatrienoate levels was the most sensitive biomarker. Overall, our integrated multi-omics analysis provides mechanistic insight into how this class of chemical pollutant can cause NAFLD. Our study lays the foundation for the development of molecular signatures of toxic effects of chemicals causing fatty liver diseases to move away from a chemical risk assessment based on in vivo animal experiments.

Next-generation metabolic screening: targeted and untargeted metabolomics for the diagnosis of inborn errors of metabolism in individual patients

The implementation of whole-exome sequencing in clinical diagnostics has generated a need for functional evaluation of genetic variants. In the field of inborn errors of metabolism (IEM), a diverse spectrum of targeted biochemical assays is employed to analyze a limited amount of metabolites. We now present a single-platform, high-resolution liquid chromatography quadrupole time of flight (LC-QTOF) method that can be applied for holistic metabolic profiling in plasma of individual IEM-suspected patients. This method, which we termed "next-generation metabolic screening" (NGMS), can detect >10,000 features in each sample. In the NGMS workflow, features identified in patient and control samples are aligned using the "various forms of chromatography mass spectrometry (XCMS)" software package. Subsequently, all features are annotated using the Human Metabolome Database, and statistical testing is performed to identify significantly perturbed metabolite concentrations in a patient sample compared with controls. We propose three main modalities to analyze complex, untargeted metabolomics data. First, a targeted evaluation can be done based on identified genetic variants of uncertain significance in metabolic pathways. Second, we developed a panel of IEM-related metabolites to filter untargeted metabolomics data. Based on this IEM-panel approach, we provided the correct diagnosis for 42 of 46 IEMs. As a last modality, metabolomics data can be analyzed in an untargeted setting, which we term "open the metabolome" analysis. This approach identifies potential novel biomarkers in known IEMs and leads to identification of biomarkers for as yet unknown IEMs. We are convinced that NGMS is the way forward in laboratory diagnostics of IEMs.

Metabolomics profiling of steatosis progression in HepaRG® cells using sodium valproate

Non-alcoholic Fatty Liver Disease (NAFLD) is a frequently encountered Drug-Induced Liver Injury (DILI). Although this stage of the disease is reversible, it can lead to irreversible damage provoked by non-alcoholic steatohepatitis (NASH), fibrosis and cirrhosis. Therefore, the assessment of NAFLD is a paramount objective in toxicological screenings of new drug candidates. In this study, a metabolomic fingerprint of NAFLD induced in HepaRG^® cells at four dosing schemes by a reference toxicant, sodium valproate (NaVPA), was obtained using liquid-liquid extraction followed by liquid chromatography and accurate mass-mass spectrometry (LC-AM/MS). The combination of a strict design of experiment with a robust detection method, applied on sodium valproate, validated the possibilities of untargeted metabolomics in hepatic toxicological research. Distinctive patterns between exposed and control cells were consistently observed, multivariate analyses selected up to 200 features of interest, revealing hallmark NAFLD-biomarkers, such as diacylglycerol and triglyceride accumulation and carnitine deficiency. Initial toxic responses show increased levels of S-adenosylmethionine and mono-acetylspermidine in combination with only a moderate increase in triglycerides. New specific markers of toxicity have been observed, such as spermidines, creatine, and acetylcholine. The described design of experiment provides a valuable metabolomics platform for mechanistic research of toxicological hazards and identified new markers for steatotic progression.