Investigating the Potential of Drift Tube Ion Mobility for the Analysis of Oxidized Lipids.

Epilipids, a subset of the lipidome that comprises oxidized, nitrated, and halogenated lipid species, show important biochemical activity in the regulation of redox lipid metabolism by influencing cell fate decisions, including death, health, and aging. Due to the large chemical diversity, reversed-phase liquid chromatography-high-resolution mass spectrometry (RPLC-HRMS) methods have only a limited ability to separate numerous isobaric and isomeric epilipids. Ion mobility spectrometry (IMS) is a gas-phase separation technique that can be combined with LC-HRMS to improve the overall peak capacity of the analytical platform. Here, we illustrate the advantages and discuss the current limitations of implementing IMS in LC-HRMS workflows for the analysis of oxylipins and oxidized complex lipids. Using isomeric mixtures of oxylipins, we demonstrated that while deprotonated ions of eicosanoids were poorly resolved by IMS, sodium acetate and metal adducts (e.g., Li, Na, Ag, Ba, K) of structural isomers often showed ΔCCS% above 1.4% and base peak separation with high-resolution demultiplexing (HRDm). The knowledge of the IM migration order was also used as a proof of concept to help in the annotation of oxidized complex lipids using HRDm and all-ion fragmentation spectra. Additionally, we used a mixture of deuterium-labeled lipids for a routine system suitability test with the purpose of improving harmonization and interoperability of IMS data sets in (epi)lipidomics.

Untargeted hair lipidomics: comprehensive evaluation of the hair-specific lipid signature and considerations for retrospective analysis.

Lipidomics investigates the composition and function of lipids, typically employing blood or tissue samples as the primary study matrices. Hair has recently emerged as a potential complementary sample type to identify biomarkers in early disease stages and retrospectively document an individual's metabolic status due to its long detection window of up to several months prior to the time of sampling. However, the limited coverage of lipid profiling presented in previous studies has hindered its exploitation. This study aimed to evaluate the lipid coverage of hair using an untargeted liquid chromatography-high-resolution mass spectrometry lipidomics platform. Two distinct three-step exhaustive extraction experiments were performed using a hair metabolomics one-phase extraction technique that has been recently optimized, and the two-phase Folch extraction method which is recognized as the gold standard for lipid extraction in biological matrices. The applied lipidomics workflow improved hair lipid coverage, as only 99 species could be annotated using the one-phase extraction method, while 297 lipid species across six categories were annotated with the Folch method. Several lipids in hair were reported for the first time, including N-acyl amino acids, diradylglycerols, and coenzyme Q10. The study suggests that hair lipids are not solely derived from de novo synthesis in hair, but are also incorporated from sebum and blood, making hair a valuable matrix for clinical, forensic, and dermatological research. The improved understanding of the lipid composition and analytical considerations for retrospective analysis offers valuable insights to contextualize untargeted hair lipidomic analysis and facilitate the use of hair in translational studies.

Metabolic signature of HepaRG cells exposed to ethanol and tumor necrosis factor alpha to study alcoholic steatohepatitis by LC-MS-based untargeted metabolomics.

Despite the high prevalence of alcoholic liver disease, its identification and characterization remain poor, especially in early stages such as alcoholic fatty liver disease and alcoholic steatohepatitis. This latter implies diagnostic difficulties, few therapeutic options and unclear mechanisms of action. To elucidate the metabolic alterations and pinpoint affected biochemical pathways, alcoholic steatohepatitis was simulated in vitro by exposing HepaRG cells to ethanol (IC10, 368 mM) and tumor necrosis factor alpha (TNF-α, 50 ng/mL) for 24 h. This combined exposure was compared to solely ethanol-exposed as well as -nonexposed cells. Four different metabolomics platforms were used combining liquid chromatography, high-resolution mass spectrometry and drift tube ion mobility to elucidate both intracellular and extracellular metabolic alterations. Some of the key findings include the influence of TNF-α in the upregulation of hepatic triglycerides and the downregulation of hepatic phosphatidylethanolamines and phosphatidylcholines. S-Adenosylmethionine showed to play a central role in the progression of alcoholic steatohepatitis. In addition, fatty acyl esters of hydroxy fatty acid (FAHFA)-containing triglycerides were detected for the first time in human hepatocytes and their alterations showed a potentially important role during the progression of alcoholic steatohepatitis. Ethoxylated phosphorylcholine was identified as a potential new biomarker of ethanol exposure.

Metabolic Signature of Ethanol-Induced Hepatotoxicity in HepaRG Cells by Liquid Chromatography-Mass Spectrometry-Based Untargeted Metabolomics.

Alcoholic liver disease is highly prevalent but poorly identified and characterized, leading to knowledge gaps, which impairs early diagnosis. Excessive alcohol consumption is known to alter lipid metabolism, followed by progressive intracellular lipid accumulation, resulting in alcoholic fatty liver disease. In this study, HepaRG cells were exposed to ethanol at IC10 and 1/10 IC10 for 24 and 48 h. Metabolic alterations were investigated intra- and extracellularly with liquid chromatography-high-resolution mass spectrometry. Ion mobility was added as an extra separation dimension for untargeted lipidomics to improve annotation confidence. Distinctive patterns between exposed and control cells were consistently observed, with intracellular upregulation of di- and triglycerides, downregulation of phosphatidylcholines and phosphatidylethanolamines, sphingomyelins, and S-adenosylmethionine, among others. Several intracellular metabolic patterns could be related to changes in the extracellular environment, such as increased intracellular hydrolysis of sphingomyelins, leading to increased phosphorylcholine secretion. Carnitines showed alterations depending on the size of their carbon chain, which highlights the interplay between ß-oxidation in mitochondria and peroxisomes. Potential new biomarkers of ethanol-induced hepatotoxicity have been observed, such as ceramides with a sphingadienine backbone, octanoylcarnitine, creatine, acetylcholine, and ethoxylated phosphorylcholine. The combination of the metabolic fingerprint and footprint enabled a comprehensive investigation of the pathophysiology behind ethanol-induced hepatotoxicity.

Guidelines and considerations for building multidimensional libraries for untargeted MS-based metabolomics.

INTRODUCTION: Feature annotation is crucial in untargeted metabolomics but remains a major challenge. The large pool of metabolites collected under various instrumental conditions is underrepresented in publicly available databases. Retention time (RT) and collision cross section (CCS) measurements from liquid chromatography ion mobility high-resolution mass spectrometers can be employed in addition to MS/MS spectra to improve the confidence of metabolite annotation. Recent advancements in machine learning focus on improving the accuracy of predictions for CCS and RT values. Therefore, high-quality experimental data are crucial to be used either as training datasets or as a reference for high-confidence matching. METHODS: This manuscript provides an easy-to-use workflow for the creation of an in-house metabolite library, offers an overview of alternative solutions, and discusses the challenges and advantages of using open-source software. A total of 100 metabolite standards from various classes were analyzed and subjected to the described workflow for library generation. RESULTS AND DISCUSSION: The outcome was an open-access available NIST format metabolite library (.msp) with multidimensional information. The library was used to evaluate CCS prediction tools, MS/MS spectra heterogeneities (e.g., multiple adducts, in-source fragmentation, radical fragment ions using collision-induced dissociation), and the reporting of RT.

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 a 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, that is, 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.

Incorporating 'reason for use' into the prescribing process of medication: a survey on the opinion of patients in Flanders, Belgium.

BACKGROUND: A longstanding debate exists about including a 'reason for use' on prescriptions for medication. Little is known, however, about patients' opinions on this subject. METHODS: An internet-based questionnaire, consisting mainly of Likert scale questions, was distributed online to the general public in Belgium. Results from 1034 responses were analyzed using descriptive statistics. RESULTS: Opinions from patients toward including a 'reason for use' on medication prescriptions were generally positive. A clear majority of 62% increased to 74% after providing information about the possible link between indication and medication dose. A majority of the participants expressed a positive attitude regardless of the pathology involved, although sexually transmitted diseases were of greatest concern. Other important aspects differentiating the opinion positively was the transmission of this information in an electronic-only form and limiting it to the regular pharmacist excluding further use by third parties such as other pharmacies or insurance companies. Patients using multiple medicines and those frequenting the same pharmacy also had a more favorable opinion about including the reason for use. In addition, analysis of physician and pharmacist questionnaire responses, explicitly excluded from the main analysis, confirmed the known contrasting opinions in these subgroups. CONCLUSIONS: Patients have strong support for transferring information on the 'reason for use' of their prescriptions to their regular pharmacy if this is done in a secure and privacy-conscious way enabling increased patient safety and improved pharmaceutical care.

The Metabolic and Lipidomic Fingerprint of Torin1 Exposure in Mouse Embryonic Fibroblasts Using Untargeted Metabolomics.

Torin1, a selective kinase inhibitor targeting the mammalian target of rapamycin (mTOR), remains widely used in autophagy research due to its potent autophagy-inducing abilities, regardless of its unspecific properties. Recognizing the impact of mTOR inhibition on metabolism, our objective was to develop a reliable and thorough untargeted metabolomics workflow to study torin1-induced metabolic changes in mouse embryonic fibroblast (MEF) cells. Crucially, our quality assurance and quality control (QA/QC) protocols were designed to increase confidence in the reported findings by reducing the likelihood of false positives, including a validation experiment replicating all experimental steps from sample preparation to data analysis. This study investigated the metabolic fingerprint of torin1 exposure by using liquid chromatography-high resolution mass spectrometry (LC-HRMS)-based untargeted metabolomics platforms. Our workflow identified 67 altered metabolites after torin1 exposure, combining univariate and multivariate statistics and the implementation of a validation experiment. In particular, intracellular ceramides, diglycerides, phosphatidylcholines, phosphatidylethanolamines, glutathione, and 5'-methylthioadenosine were downregulated. Lyso-phosphatidylcholines, lyso-phosphatidylethanolamines, glycerophosphocholine, triglycerides, inosine, and hypoxanthine were upregulated. Further biochemical pathway analyses provided deeper insights into the reported changes. Ultimately, our study provides a valuable workflow that can be implemented for future investigations into the effects of other compounds, including more specific autophagy modulators.

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.

Occurrence and contamination profile of legacy and emerging per- and polyfluoroalkyl substances (PFAS) in Belgian wastewater using target, suspect and non-target screening approaches.

With the growing concern regarding the health risks of per- and polyfluoroalkyl substances (PFAS), there is an increasing demand for the identification of emerging PFAS. This study provides a comprehensive investigation of legacy and emerging PFAS in 16 wastewater treatment plants (WWTPs) in Belgium using target, suspect, and non-target screening methods. Perfluorobutanoic acid (PFBA) and perfluoropentanoic acid (PFPeA) were the dominant compounds in most locations, whereas perfluorooctanoic acid (PFOA) was the most predominant PFAS in WWTP Deurne (Antwerp region). Using a suspect screening approach, 14 PFAS were annotated as confidence level (CL) of 4 or higher and 4 PFAS were annotated as CL 2a and 2b, including aqueous film forming foam (AFFF)-derived PFAS. The compound group of n:3 unsaturated fluorotelomer carboxylic acid was found using non-target screening in the wastewater from WWTP Deurne. Population exposure in a catchment area estimated using population-normalized mass loads (PNML) showed the highest value in the catchment area of WWTP Deurne, implying a potentially higher exposure to PFAS in this community.

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.

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.

Optimization of an in vitro gut microbiome biotransformation platform with chlorogenic acid as model compound: From fecal sample to biotransformation product identification.

Recent data clearly show that the gut microbiota plays a significant role in the biotransformation of many endogenous molecules and xenobiotics, leading to a potential influence of this microbiotic metabolism on activation, inactivation and possible toxicity of these compounds. To study the colonic biotransformation of xenobiotics by the gut microbiome, in vitro models are often used as they allow dynamic and multiple sampling overtime. However, the pre-analytical phase should be carefully optimized to enable biotransformation product identification representative for the in vivo situation. During this study, chlorogenic acid was used as a model compound to optimize a ready-to-use gut microbiome biotransformation platform using an in vitro gastrointestinal dialysis-model with colon phase together with an instrumental platform using liquid chromatography coupled to high resolution mass spectrometry (LC-QTOF-MS). Identification of the biotransformation products of chlorogenic acid was performed using complementary suspect and non-targeted data analysis approaches (MZmine + R and MPP workflow). Concerning the pre-analytical phase, (i) the influence of different incubation media (Wilkins-Chalgren Anaerobic Broth (WCB) and (versus) phosphate buffer) and different incubation times (prior to implementation in the colonic stage of the dialysis model) on fecal bacterial composition and concentration were investigated and (ii) four different sample preparation methods (centrifugation, extraction, sonication and freeze-drying) were evaluated targeting colonic biotransformation of chlorogenic acid. WCB as incubation medium showed to introduce substantial variation in the bacterial composition of the fecal samples, while the sterile phosphate buffer guaranteed a closer resemblance to the in vivo composition. Furthermore, incubation during 24 h in sterile phosphate buffer as medium showed no significant increase or decrease in anaerobic bacterial concentration, concluding that incubation prior to the colonic stage is not needed. Concerning sample preparation, centrifugation, sonication and extraction gave similar results, while freeze-drying appeared to be inferior. The extraction method was selected as an optimal sample preparation method given the quick execution together with a good instrumental sensitivity. This study optimized a ready-to-use platform to investigate colonic biotransformation of xenobiotics by using chlorogenic acid as a model compound. This platform can be used in the future to study differences in colonic biotransformation of xenobiotics using fecal samples of different patient groups.