Comparison of simple monophasic versus classical biphasic extraction protocols for comprehensive UHPLC-MS/MS lipidomic analysis of Hela cells

Fast urine metabolomics for the assessment of Zopiclone effects on insomnia

Insomnia is a common symptom of many diseases and is closely associated with neurodegenerative diseases. Zopiclone is one of several clinical hypnotics for treating insomnia. However, some patients are sensitive to this drug treatment, whereas others are not, and the underlying mechanisms remain unclear, causing confusion for making therapeutic regimens and prolong the course of the disease. In present work, we developed a fast urine metabolomics' method for evaluating the sensitivity of insomnia patients to Zopiclone treatment. Firstly, we extracted urine metabolome using methanol-water solutions of different ratios. Secondly, the extracts were either directly injected into LC-MS analysis or dried and resuspended using methanol-water solutions of different concentrations for LC-MS analysis. Then, the total abundance and chromatographic behaviors of urine metabolome from different extraction methods were compared with each other. The optimal extraction method is to mix 50 μl of urine with an equal volume of methanol and 150 μl of water for LC-MS analysis. Finally, the developed method was applied to a metabolomics study of urine from patients with insomnia to evaluate the effectiveness of Zopiclone in treating insomnia. The results showed that there were significant statistical differences in the levels of acylcarnitines, β-hydroxybutyrate (BHB), 4-hydroxybutyric acid (GHB), 3-hydroxyisovaleric acid, citrate, leucine, isoleucine, and valine between the sensitive and insensitive groups treated with Zopiclone. Furthermore, alterations in levels of GHB, valine, and isoleucine were closely correlated with Pittsburgh Sleep Quality Index (PSQI) scores, which may be potential biomarkers for assessing the sensitivity of insomnia patients to Zopiclone treatment, and guiding therapy adjustment.

Comprehensive tissue homogenization and metabolite extraction for application in clinical metabolomics

BACKGROUND

Metabolomics and lipidomics analysis of various biological samples offer insights into potential mechanisms of health and disease development. Tissue samples, compared to other biological samples, are less elucidated due to challenges in sample collection and lack of standardized sample preparation protocols for reproducible tissue homogenization and broad-range metabolite extraction.

RESULTS

Pork tissue samples were homogenized with six different solvent mixtures with increasing lipophilicity, followed by metabolites extraction using methanol for polar and methyl-tert-butyl ether (MTBE) in methanol (MeOH) for highly lipophilic compounds. Metabolite profiles of supernatant and homogenate extraction for three extract volumes were compared. Solvent dependent pipette tip blockage was addressed by introduction of a prewetting correction factor for non-polar homogenization solutions and low volume tissue homogenate pipetting. Upset plots were applied for multi-dimensional metabolite extraction efficiency evaluation for 24 different sample preparation conditions. The best-performing homogenization solution was PBS; MeOH (1:1; v/v), combined with a two-step polar metabolite and lipid extraction using MeOH and 75 % MTBE in MeOH employing the tissue homogenate. The optimized experimental conditions were applied on mouse pancreas tissues, providing evidence of varying metabolic pathway activities across different anatomical regions of an organ.

SIGNIFICANCE

This study introduces a comprehensive tissue sample preparation and metabolite quantification workflow, covering highly polar to highly lipophilic metabolites using targeted high performance liquid chromatography electrospray ionization triple quadrupole-linear ion trap mass spectrometer (HPLC-ESI-QTRAP-MS/MS) for absolute quantitation of amino acids, organic acids and keto-acids, acyl-carnitines, and phospho-choline lipids.

Direct Current Stimulation (DCS) Modulates Lipid Metabolism and Intercellular Vesicular Trafficking in SHSY-5Y Cell Line: Implications for Parkinson's Disease

The modulation of the brain's electrical activity for therapeutic purposes has recently gained attention, supported by the promising results obtained through the non-invasive application of transcranial direct current stimulation (tDCS) in the treatment of neurodegenerative and neurological diseases. To optimize therapeutic efficacy, it is crucial to investigate the cellular and molecular effects of tDCS. This will help to identify important biomarkers, predict patient's response and develop personalized treatments. In this study, we applied direct current stimulation (DCS) to a neural cell line, using mild currents over short periods of time (0.5 mA, 20 min), with 24-h intervals. We observed that DCS induced changes in the cellular lipidome, with transient effects observed after a single stimulation (lasting 24 h) and more significant, long-lasting effects (up to 72 h) after repeated stimulation cycles. In neural cells, multiple DCS treatment modulated structural membrane lipids (PE, PS, PI), downregulated glycerol lipids with ether-linked fatty acids and pro-inflammatory lipids (ceramides and lyso-glycerophospholipids) (p ≤ 0.005). Multiple DCS sessions altered transcriptional activity by decreasing the expression of inflammatory cytokines (TNF-α, p ≤ 0.05; IL-1β, p ≤ 0.01), while increasing the expression of neuroprotective factors such as heme oxygenase-1 (p ≤ 0.0001) and brain-derived neurotrophic factor (p ≤ 0.05), as well as proteins involved in vesicular transport (SNARE, sorting nexins and seipin and α-synuclein; p ≤ 0.05). In addition, DCS enhanced the release of extracellular vesicles, with repeated stimulations significantly increasing the release of exosomes threefold. In conclusion, while a single electrical stimulation induces transient metabolic changes with limited phenotypic effects, repeated applications induce a broader and deeper modulation of lipid species. This may lead to a neuroprotective and neuroplasticity-focussed transcriptional profile, potentially supporting the therapeutic effects of tDCS at the cellular and molecular level in patients..

Pentachlorophenol increases diabetes risk by damaging β-cell secretion and disrupting gut microbial-related amino acids and fatty acids biosynthesis

Pentachlorophenol (PCP), a ubiquitous environmental pollutant, has been reported as a possible contributor to diabetes. However, evidence for general population is scarce while related mechanisms are largely unknown. Using a representative population-based case-control study in Beijing (n = 1796), we found a positive association between PCP exposure and diabetes risk with the odds ratio reaching 1.68 (95 % confidence interval: 1.30 to 2.18). A further rat experiment revealed that low-dose PCP mimicking real-world human exposure can significantly impair glycemic homeostasis by inducing pancreatic β-cell dysfunction, with non-linear dose-response relationships. Subsequent multi-omics analysis suggested that low-dose PCP led to notable gut microbiota dysbiosis (especially the species from genus Prevotella, such as intermedia, dentalis, ruminicola, denticola, melaninogenica, and oris), decreased serum amino acids (L-phenylalanine, L-tyrosine, and L-tryptophan) and increased serum fatty acids (oleic and palmitic acid) in rats, while strong correlations were observed among alterations of gut microbes, serum metabolites and glycemic-related biomarkers (e.g., fasting blood glucose and insulin). Collectively, these results imply PCP may increase diabetes risk by disrupting gut microbial-related amino acids and fatty acids biosynthesis. This will help guide future in-depth studies on the roles of PCP in the development of human diabetes.

Clinical advances in analytical profiling of signature lipids: implications for severe non-communicable and neurodegenerative diseases

BACKGROUND

Lipids play key roles in numerous biological processes, including energy storage, cell membrane structure, signaling, immune responses, and homeostasis, making lipidomics a vital branch of metabolomics that analyzes and characterizes a wide range of lipid classes. Addressing the complex etiology, age-related risk, progression, inflammation, and research overlap in conditions like Alzheimer's Disease, Parkinson's Disease, Cardiovascular Diseases, and Cancer poses significant challenges in the quest for effective therapeutic targets, improved diagnostic markers, and advanced treatments. Mass spectrometry is an indispensable tool in clinical lipidomics, delivering quantitative and structural lipid data, and its integration with technologies like Liquid Chromatography (LC), Magnetic Resonance Imaging (MRI), and few emerging Matrix-Assisted Laser Desorption Ionization- Imaging Mass Spectrometry (MALDI-IMS) along with its incorporation into Tissue Microarray (TMA) represents current advances. These innovations enhance lipidomics assessment, bolster accuracy, and offer insights into lipid subcellular localization, dynamics, and functional roles in disease contexts.

AIM OF THE REVIEW

The review article summarizes recent advancements in lipidomic methodologies from 2019 to 2023 for diagnosing major neurodegenerative diseases, Alzheimer's and Parkinson's, serious non-communicable cardiovascular diseases and cancer, emphasizing the role of lipid level variations, and highlighting the potential of lipidomics data integration with genomics and proteomics to improve disease understanding and innovative prognostic, diagnostic and therapeutic strategies.

KEY SCIENTIFIC CONCEPTS OF REVIEW

Clinical lipidomic studies are a promising approach to track and analyze lipid profiles, revealing their crucial roles in various diseases. This lipid-focused research provides insights into disease mechanisms, biomarker identification, and potential therapeutic targets, advancing our understanding and management of conditions such as Alzheimer's Disease, Parkinson's Disease, Cardiovascular Diseases, and specific cancers.

Differential Lipid Accumulation on HepG2 Cells Triggered by Palmitic and Linoleic Fatty Acids Exposure

Lipid metabolism pathways such as β-oxidation, lipolysis and, lipogenesis, are mainly associated with normal liver function. However, steatosis is a growing pathology caused by the accumulation of lipids in hepatic cells due to increased lipogenesis, dysregulated lipid metabolism, and/or reduced lipolysis. Accordingly, this investigation hypothesizes a selective in vitro accumulation of palmitic and linoleic fatty acids on hepatocytes. After assessing the metabolic inhibition, apoptotic effect, and reactive oxygen species (ROS) generation by linoleic (LA) and palmitic (PA) fatty acids, HepG2 cells were exposed to different ratios of LA and PA to study the lipid accumulation using the lipophilic dye Oil Red O. Lipidomic studies were also carried out after lipid isolation. Results revealed that LA was highly accumulated and induced ROS production when compared to PA. Lipid profile modifications were observed after LA:PA 1:1 (v/v) exposure, which led to a four-fold increase in triglycerides (TGs) (mainly in linoleic acid-containing species), as well as a increase in cholesterol and polyunsaturated fatty acids (PUFA) content when compared to the control cells. The present work highlights the importance of balancing both PA and LA fatty acids concentrations in HepG2 cells to maintain normal levels of free fatty acids (FFAs), cholesterol, and TGs and to minimize some of the observed in vitro effects (i.e., apoptosis, ROS generation and lipid accumulation) caused by these fatty acids.

Nutritional lipidomics for the characterization of lipids in food

Lipids represent one out of three major macronutrient classes in the human diet. It is estimated to account for about 15-20% of the total dietary intake. Triacylglycerides comprise the majority of them, estimated 90-95%. Other lipid classes include free fatty acids, phospholipids, cholesterol, and plant sterols as minor components. Various methods are used for the characterization of nutritional lipids, however, lipidomics approaches become increasingly attractive for this purpose due to their wide coverage, comprehensiveness and holistic view on composition. In this chapter, analytical methodologies and workflows utilized for lipidomics profiling of food samples are outlined with focus on mass spectrometry-based assays. The chapter describes common lipid extraction protocols, the distinct instrumental mass-spectrometry based analytical platforms for data acquisition, chromatographic and ion-mobility spectrometry methods for lipid separation, briefly mentions alternative methods such as gas chromatography for fatty acid profiling and mass spectrometry imaging. Critical issues of important steps of lipidomics workflows such as structural annotation and identification, quantification and quality assurance are discussed as well. Applications reported over the period of the last 5years are summarized covering the discovery of new lipids in foodstuff, differential profiling approaches for comparing samples from different origin, species, varieties, cultivars and breeds, and for food processing quality control. Lipidomics as a powerful tool for personalized nutrition and nutritional intervention studies is briefly discussed as well. It is expected that this field is significantly growing in the near future and this chapter gives a short insight into the power of nutritional lipidomics approaches.

An Optimised Monophasic Faecal Extraction Method for LC-MS Analysis and Its Application in Gastrointestinal Disease

Liquid chromatography coupled with mass spectrometry (LC-MS) metabolomic approaches are widely used to investigate underlying pathogenesis of gastrointestinal disease and mechanism of action of treatments. However, there is an unmet requirement to assess faecal metabolite extraction methods for large-scale metabolomics studies. Current methods often rely on biphasic extractions using harmful halogenated solvents, making automation and large-scale studies challenging. The present study reports an optimised monophasic faecal extraction protocol that is suitable for untargeted and targeted LC-MS analyses. The impact of several experimental parameters, including sample weight, extraction solvent, cellular disruption method, and sample-to-solvent ratio, were investigated. It is suggested that a 50 mg freeze-dried faecal sample should be used in a methanol extraction (1:20) using bead beating as the means of cell disruption. This is revealed by a significant increase in number of metabolites detected, improved signal intensity, and wide metabolic coverage given by each of the above extraction parameters. Finally, we addressed the applicability of the method on faecal samples from patients with Crohn's disease (CD) and coeliac disease (CoD), two distinct chronic gastrointestinal diseases involving metabolic perturbations. Untargeted and targeted metabolomic analysis demonstrated the ability of the developed method to detect and stratify metabolites extracted from patient groups and healthy controls (HC), highlighting characteristic changes in the faecal metabolome according to disease. The method developed is, therefore, suitable for the analysis of patients with gastrointestinal disease and can be used to detect and distinguish differences in the metabolomes of CD, CoD, and HC.

Suitability of Solvent-Assisted Extraction for Recovery of Lipophilic Phytochemicals in Sugarcane Straw and Bagasse

Sugarcane is primarily harvested to meet up to 80% of global sugar demand. Recently, lipids recovered from their biomass (straw and bagasse) have attracted much attention due to their possible utilisation in biofuel production but also by the presence of health-promoting compounds as phytosterols (i.e., improvement of cardiovascular function) or 1-octacosanol (i.e., anti-obesity). Although this fraction is commonly obtained through solid–liquid isolation, there is scarce information about how different solvents affect the composition of the extracts. This research work aimed to study whether, in sugarcane straw and bagasse samples, Soxtec extraction with widely used dichloromethane (DCM) would be suitable to recover most of the lipid classes when compared to other available solvents such as food grade ethanol (EtOH) or solvents without regulation restrictions for food and drug applications (i.e., acetone and ethyl acetate). The obtained results allow concluding that sugarcane waxes from straw and bagasse are complex lipid mixtures of polar and non-polar compounds. According to the extraction yield, the best results were obtained with ethanol (5.12 ± 0.30% and 1.97 ± 0.31%) for both straw and bagasse, respectively. The extractant greatly influenced the lipid composition of the obtained product. Thus, DCM enriched the isolates in glycerolipids (mono-, di- and triglycerides), free fatty acids, fatty alcohols, fatty aldehydes, phytosterols and hydrocarbons. On the other hand, EtOH resulted in polar isolates rich in glycolipids. Therefore, depending on the application and objectives of future research studies, the solvent to recover such lipids needs to be carefully selected.

Comparison of extraction methods for intracellular metabolomics of human tissues

Analyses of metabolic compounds inside cells or tissues provide high information content since they represent the endpoint of biological information flow and are a snapshot of the integration of many regulatory processes. However, quantification of the abundance of metabolites requires their careful extraction. We present a comprehensive study comparing ten extraction protocols in four human sample types (liver tissue, bone marrow, HL60, and HEK cells) aiming to detect and quantify up to 630 metabolites of different chemical classes. We show that the extraction efficiency and repeatability are highly variable across protocols, tissues, and chemical classes of metabolites. We used different quality metrics including the limit of detection and variability between replicates as well as the sum of concentrations as a global estimate of analytical repeatability of the extraction. The coverage of extracted metabolites depends on the used solvents, which has implications for the design of measurements of different sample types and metabolic compounds of interest. The benchmark dataset can be explored in an easy-to-use, interactive, and flexible online resource (R/shiny app MetaboExtract: http://www.metaboextract.shiny.dkfz.de) for context-specific selection of the optimal extraction method. Furthermore, data processing and conversion functionality underlying the shiny app are accessible as an R package: https://cran.r-project.org/package=MetAlyzer.

Deep Metabolic Profiling Assessment of Tissue Extraction Protocols for Three Model Organisms

Metabolic profiling harbors the potential to better understand various disease entities such as cancer, diabetes, Alzheimer's, Parkinson's disease or COVID-19. To better understand such diseases and their intricate metabolic pathways in human studies, model animals are regularly used. There, standardized rearing conditions and uniform sampling strategies are prerequisites towards a successful metabolomic study that can be achieved through model organisms. Although metabolomic approaches have been employed on model organisms before, no systematic assessment of different conditions to optimize metabolite extraction across several organisms and sample types has been conducted. We address this issue using a highly standardized metabolic profiling assay analyzing 630 metabolites across three commonly used model organisms (Drosophila, mouse, and zebrafish) to find an optimal extraction protocol for various matrices. Focusing on parameters such as metabolite coverage, concentration and variance between replicates we compared seven extraction protocols. We found that the application of a combination of 75% ethanol and methyl tertiary-butyl ether (MTBE), while not producing the broadest coverage and highest concentrations, was the most reproducible extraction protocol. We were able to determine up to 530 metabolites in mouse kidney samples, 509 in mouse liver, 422 in zebrafish and 388 in Drosophila and discovered a core overlap of 261 metabolites in these four matrices. To enable other scientists to search for the most suitable extraction protocol in their experimental context and interact with this comprehensive data, we have integrated our data set in the open-source shiny app "MetaboExtract". Hereby, scientists can search for metabolites or compound classes of interest, compare them across the different tested extraction protocols and sample types as well as find reference concentration values.

Comparison of one-phase and two-phase extraction methods for porcine tissue lipidomics applying a fast and reliable tentative annotation workflow

Lipidomics has great potential for the discovery of biomarkers, elucidation of metabolic processes and identifying dysregulations in complex biological systems. Concerning biofluids like plasma or cerebrospinal fluid, several studies for the comparison of lipid extraction solvents have already been conducted. With respect to tissues, which can differ significantly in terms of dry matter content and composition, only few studies are available. The proper selection of an extraction method that covers the complexity and individuality of different tissues is challenging. The goal of this work was to provide a systematic overview on the potential of different extraction methods for a broad applicability. This study covers six different extraction procedures and four different reconstitution solvents applied to ten different porcine tissues. To get an overview of the individual lipid profiles, a workflow was developed for a fast and reliable tentative lipid annotation. Therefore, several machine learning tools were utilized, like the prediction of collision cross sections to support the tentative lipid identification in case of untargeted lipidomics. In terms of data evaluation, unsupervised (e.g. principal component analysis) and supervised (e.g. partial least square - discriminant analysis) methods were applied to visualize and subsequently interpret all generated information. Furthermore, the influence of the tissue composition on the extraction performance was investigated. It could be shown that the ten porcine tissues can be distinguished based on their lipid profile with the applied workflow and that the methyl-tert-butyl ether (MTBE) based extraction method (two-phase) showed the best overall performance for the 16 examined lipid species. With this method the highest number of features (428 in lung tissue) could be annotated. Upcoming one-phase extractions also showed a high potential concerning total number of extracted lipids. Methanol/MTBE/chloroform (MMC) extracted slightly less lipids (393 in lung and liver) than MTBE but turned out to be the best one-phase extraction method. Additionally, the numbers of extracted lipids obtained by isopropanol/water 90:10 (IPA90) (399 in stomach) and by isopropanol/methanol/chloroform (IMC) (395 in stomach) were similar to those of the modified Folch method (402 in stomach). One-phase extractions can therefore clearly be seen as preferable when a high throughput is needed.

Assessment of Biphasic Extraction Methods of Mouse Fecal Metabolites for Liquid Chromatography-Mass Spectrometry-Based Metabolomic Studies

With the increasing knowledge about the important roles of gut microbiota on the biological system, a systematic strategy to profile the fecal metabolome is urgently needed. Thus, an unbiased, efficient, and reproducible fecal metabolite extraction protocol needs to be established; however, the effect of biphasic extraction methods for the fecal samples remains unclear. In this study, five different methods were assessed in the extraction of polar and non-polar metabolites for the liquid chromatography-mass spectrometry (LC-MS)-based mouse fecal metabolomic study. First, the detection coverage of two extraction systems, the Bligh and Dyer extraction method (M1, chloroform/methanol/water, 2/2/1.8) and Matyash method (M2, methyl tert-butyl ether (MTBE)/methanol/water, 10/3/2.5), was compared; then, MTBE/methanol/water system with different solvent ratios (M3, 2.6/2.0/2.4; M4, 4.5/1/2.5; and M5, 3/2.5/2.5) were further evaluated. The results showed that M2 showed higher detection coverage than M1. For the MTBE/methanol/water system with different solvent ratios, M3 showed the largest detection coverage based on peak numbers and numbers of putatively annotated metabolites, while M4 presented the least overlap between two phases, higher peak intensities of metabolites, and superior reproducibility. Based on the above evidence, M4 was recommended for the biphasic extraction of fecal metabolites in the LC-MS-based mouse fecal metabolomic study.

Untargeted UHPLC-ESI-QTOF-MS/MS analysis with targeted feature extraction at precursor and fragment level for profiling of the platelet lipidome with ex vivo thrombin-activation

Lipids play a major role in platelet signaling and activation. In this study, we analyzed the platelet lipidome in an untargeted manner by reversed-phase UHPLC for lipid species separation coupled to high-resolution QTOF-MS/MS in data-independent acquisition (DIA) mode with sequential window acquisition of all theoretical fragment ion mass spectra (SWATH) for compound detection. Lipid identification and peak picking was supported by the characteristic regular elution pattern of lipids differing in carbon and double bond numbers. It was primarily based on post-acquisition targeted feature extraction from the SWATH data. Multiple extracted ion chromatograms (EICs) from SWATH data of diagnostic ions on MS1 and MS2 level from both positive and negative ion mode allowed to distinguish between poorly resolved isomeric lipids based on their distinct fragment ions, which were used for relative quantification at a molecular lipid species level. It supports assay specificity for relative lipid quantitation via multiple quantifiably ions unlike to data-dependent acquisition methods which rely on precursor ions only. This approach was used to analyze human platelet samples. 457 lipids were annotated. Concentrations of lipids were estimated by stable isotope-labelled lipid class-specific internal standards as surrogate calibrants. Heatmaps of lipid concentrations in dependence on carbon and double bond numbers for the distinct lipid classes revealed a snapshot of the platelet lipidome in the resting state with lipid species distributions within classes supporting some functional interpretations. As expected, activation of the platelets by thrombin has led to significant alterations in the platelet lipidome as proven by univariate (volcano plot) and multivariate (PLS-DA) statistics. Several lipids were significantly up-regulated (lysophosphatidylinositols, oxylipins such as thromboxane B2 (TXB2), hydroxyheptadecatrienoic acid (HHT), hydroxyeicosatetraenoic acid (HETE), hydroxyoctadecadienoic acid (HODE), sphingoid-bases, (very) long chain saturated fatty acids) or down-regulated (lysophosphatidylethanolamines, polyunsaturated fatty acids, phosphatidylinositols). Several of them are well known as biomarkers of platelet activation while others may provide some further insights into pathways of platelet activation and platelet metabolism.

Acute coronary syndrome is associated with a substantial change in the platelet lipidome

AIMS

Platelets play a key role in the pathophysiology of coronary artery disease (CAD) and patients with enhanced platelet activation are at increased risk to develop adverse cardiovascular events. Beyond reliable cardiovascular risk factors such as dyslipoproteinaemia, significant changes of platelet lipids occur in patients with CAD. In this study, we investigate the platelet lipidome by untargeted liquid chromatography-mass spectrometry, highlighting significant changes between acute coronary syndrome (ACS) and chronic coronary syndrome (CCS) patients. Additionally, we classify the platelet lipidome, spotlighting specific glycerophospholipids as key players in ACS patients. Furthermore, we examine the impact of significantly altered lipids in ACS on platelet-dependent thrombus formation and aggregation.

METHODS AND RESULTS

In this consecutive study, we characterized the platelet lipidome in a CAD cohort (n = 139) and showed significant changes of lipids between patients with ACS and CCS. We found that among 928 lipids, 7 platelet glycerophospholipids were significantly up-regulated in ACS, whereas 25 lipids were down-regulated compared to CCS. The most prominent up-regulated lipid in ACS, PC18:0 (PC 10:0-8:0), promoted platelet activation and ex vivo platelet-dependent thrombus formation.

CONCLUSIONS

Our results reveal that the platelet lipidome is altered in ACS and up-regulated lipids embody primarily glycerophospholipids. Alterations of the platelet lipidome, especially of medium chain lipids, may play a role in the pathophysiology of ACS.

Remodeling of Arctic char (Salvelinus alpinus) lipidome under a stimulated scenario of Arctic warming

Arctic warming associated with global climate change poses a significant threat to populations of wildlife in the Arctic. Since lipids play a vital role in adaptation of organisms to variations in temperature, high-resolution mass-spectrometry-based lipidomics can provide insights into adaptive responses of organisms to a warmer environment in the Arctic and help to illustrate potential novel roles of lipids in the process of thermal adaption. In this study, we studied an ecologically and economically important species-Arctic char (Salvelinus alpinus)-with a detailed multi-tissue analysis of the lipidome in response to chronic shifts in temperature using a validated lipidomics workflow. In addition, dynamic alterations in the hepatic lipidome during the time course of shifts in temperature were also characterized. Our results showed that early life stages of Arctic char were more susceptible to variations in temperature. One-year-old Arctic char responded to chronic increases in temperature with coordinated regulation of lipids, including headgroup-specific remodeling of acyl chains in glycerophospholipids (GP) and extensive alterations in composition of lipids in membranes, such as less lyso-GPs, and more ether-GPs and sphingomyelin. Glycerolipids (e.g., triacylglycerol, TG) also participated in adaptive responses of the lipidome of Arctic char. Eight-week-old Arctic char exhibited rapid adaptive alterations of the hepatic lipidome to stepwise decreases in temperature while showing blunted responses to gradual increases in temperature, implying an inability to adapt rapidly to warmer environments. Three common phosphatidylethanolamines (PEs) (PE 36:6|PE 16:1_20:5, PE 38:7|PE 16:1_22:6, and PE 40:7|PE 18:1_22:6) were finally identified as candidate lipid biomarkers for temperature shifts via machine learning approach. Overall, this work provides additional information to a better understanding of underlying regulatory mechanisms of the lipidome of Arctic organisms in the face of near-future warming.

Molecular Basis of Rhodomyrtone Resistance in Staphylococcus aureus

Rhodomyrtone (Rom) is a plant-derived broad-spectrum antibiotic active against many Gram-positive pathogens. A single point mutation in the regulatory farR gene (farR*) confers resistance to Rom in Staphylococcus aureus (RomR). The mutation in farR* alters the activity of the regulator, FarR*, in such a way that not only its own gene, farR*, but also the divergently transcribed farE gene and genes controlled by the global regulator, agr, are highly upregulated. Here, we show that mainly the upregulation of the fatty acid efflux pump FarE causes the RomR phenotype, as farE deletion in either the parent or the RomR strain (RomR ΔfarE) yielded hypersensitivity to Rom. Comparative lipidome analysis of the supernatant (exolipidomics) and the pellet fraction revealed that the RomR strain excreted about 10 times more phospholipids (PGs) than the parent strain or the ΔfarE mutants. Since the PG content in the supernatant (2,244 ng/optical density [OD]) was more than 100-fold higher than that of fatty acids (FA), we assumed that PG interacts with Rom, thereby abrogating its antimicrobial activity. Indeed, by static and dynamic light scattering (SLS and DLS) and isothermal titration calorimetry (ITC) analyses, we could demonstrate that both PG and Rom were vesicular and reacted with each other in milliseconds to form a 1:1.49 [Rom-PG(32:0), where PG(32:0) is PG with C32:0 lipids] complex. The binding is entropically driven and hence hydrophobic and of low specificity in nature. Our results indicate that the cytoplasmic membrane is the actual target of Rom, which is also in agreement with Rom's induced rapid collapse of the membrane potential and decreased membrane integrity. IMPORTANCE Antibiotic resistance is a growing public health problem, and alternative antibiotics are urgently needed. Rhodomyrtone (Rom), an antimicrobial compound originally isolated from Rhodomyrtus tomentosa, is active against multidrug-resistant Gram-positive pathogens. However, Rom-resistant (RomR) mutants occur with low frequency. In this study, we unraveled the underlying resistance mechanism, which is based on a point mutation in the farR regulator gene, causing overexpression of FarE, which most likely acts as a phospholipid (PG) efflux pump, as large amounts of PG were found in the supernatant and the pellet fraction. We show that PG can bind to Rom, thereby abrogating its antimicrobial activity. The direct interaction of Rom with PG suggests that Rom's actual target is the cytoplasmic membrane. Antibiotics that interact with PG are rare. Since Rom can be chemically synthesized, it serves as a lead compound for synthesis of improved variants.

Single-Step Extraction Coupled with Targeted HILIC-MS/MS Approach for Comprehensive Analysis of Human Plasma Lipidome and Polar Metabolome

Expanding metabolome coverage to include complex lipids and polar metabolites is essential in the generation of well-founded hypotheses in biological assays. Traditionally, lipid extraction is performed by liquid-liquid extraction using either methyl-tert-butyl ether (MTBE) or chloroform, and polar metabolite extraction using methanol. Here, we evaluated the performance of single-step sample preparation methods for simultaneous extraction of the complex lipidome and polar metabolome from human plasma. The method performance was evaluated using high-coverage Hydrophilic Interaction Liquid Chromatography-ESI coupled to tandem mass spectrometry (HILIC-ESI-MS/MS) methodology targeting a panel of 1159 lipids and 374 polar metabolites. The criteria used for method evaluation comprised protein precipitation efficiency, and relative MS signal abundance and repeatability of detectable lipid and polar metabolites in human plasma. Among the tested methods, the isopropanol (IPA) and 1-butanol:methanol (BUME) mixtures were selected as the best compromises for the simultaneous extraction of complex lipids and polar metabolites, allowing for the detection of 584 lipid species and 116 polar metabolites. The extraction with IPA showed the greatest reproducibility with the highest number of lipid species detected with the coefficient of variation (CV) < 30%. Besides this difference, both IPA and BUME allowed for the high-throughput extraction and reproducible measurement of a large panel of complex lipids and polar metabolites, thus warranting their application in large-scale human population studies.

Comprehensive lipid analysis of green Arabica coffee beans by LC-HRMS/MS

Lipids play an important role in coffee bean development, coffee brew and in the effects of coffee on human health. They account for around 17% of the dry bean weight and encompass different classes and subclasses, mostly triacylglycerols (TAG) and a minor quantity of phospholipids (PL) and ^βN-alkanoyl-5-hydroxytryptamides (C-5HT). To comprehensive profile these different lipids, it is important to evaluate extraction methods that provide high lipid coverage and to analyze the lipids in high-resolution techniques. In this work, liquid chromatography-high resolution tandem mass spectrometry (LC-HRMS/MS) was employed to comprehensive profile lipids from green Arabica coffee beans and to evaluate the extraction efficiency and lipid coverage of three methods: Bligh-Dyer (BD), Folch (FO), and Matyash (MA). The MA method yielded the greatest number of annotated compounds (131 lipids) compared to the other methods. In the positive electrospray ionization (ESI) mode, the main difference among extraction methods was observed for TAG and diacylglycerols, whereas for the negative ESI it was observed differences for phosphatidylinositol (PI), lysophosphatidylinositol and phosphatidic acid (p < 0.05). The analysis of coffees from different maturation stages and/or post-harvest processes were also performed using the MA method. Immature beans were discriminated from mature and overripe beans by its lower levels of C-5HT, PI, phosphatidylcholine, lysophosphatidylcholine, phosphatidylethanolamine, and lysophosphatidylethanolamine. These results can help to better understand the coffee lipid composition and its association with coffee quality.

Characterization of Monophasic Solvent-Based Tissue Extractions for the Detection of Polar Metabolites and Lipids Applying Ultrahigh-Performance Liquid Chromatography-Mass Spectrometry Clinical Metabolic Phenotyping Assays

Metabolic phenotyping of tissues uses metabolomics and lipidomics to measure the relative polar and nonpolar (lipid) metabolite levels in biological samples. This approach aims to understand disease biochemistry and identify biochemical markers of disease. Sample preparation methods must be reproducible, sensitive (high metabolite and lipid yield), and ideally rapid. We evaluated three biphasic methods for polar and nonpolar compound extraction (chloroform/methanol/water, dichloromethane/methanol/water, and methyl tert-butyl ether [MTBE]/methanol/water), a monophasic method for polar compound extraction (acetonitrile/methanol/water), and a monophasic method for nonpolar compound extraction (isopropanol/water). All methods were applied to mammalian heart, kidney, and liver tissues. Polar extracts were analyzed by hydrophilic interaction chromatography (HILIC) ultrahigh-performance liquid chromatography-mass spectrometry (UHPLC-MS) and nonpolar extracts by C₁₈ reversed-phase UHPLC-MS. Method reproducibility and yield were assessed using multiple annotated endogenous compounds (putatively and MS/MS annotated). Monophasic methods had the highest yield and high reproducibility for both polar (positive ion: median relative standard deviation (RSD) < 18%; negative ion: median RSD < 28%) and nonpolar (positive and negative ion: median RSD < 15%) extractions for heart, kidneys, and liver. The polar monophasic method extracted higher levels of lipid than biphasic polar extractions, and these lipids caused minimal detection suppression for other compounds during HILIC UHPLC-MS. The nonpolar monophasic method had similar or greater detection responses of all detected lipid classes compared to biphasic methods (including increased phosphatidylinositol, phosphatidylserine, and cardiolipin responses). Monophasic methods are quicker and simpler than biphasic methods and are therefore most suited for future automation.

Advances in lipidomics

The present article examines recently published literature on lipids, mainly focusing on research involving glycero-, glycerophospho- and sphingo-lipids. The primary aim is identification of distinct profiles in biologic lipidomic systems by ultra-high-performance liquid chromatography (UHPLC) coupled with mass spectrometry (MS, tandem MS) with multivariate data analysis. This review specifically targets lipid biomarkers and disease pathway mechanisms in humans and artificial targets. Different specimen matrices such as primary blood derivatives (plasma, serum, erythrocytes, and blood platelets), faecal matter, urine, as well as biologic tissues (liver, lung and kidney) are highlighted.

Exploring the Lipidome: Current Lipid Extraction Techniques for Mass Spectrometry Analysis

In recent years, high-throughput lipid profiling has contributed to understand the biological, physiological and pathological roles of lipids in living organisms. Across all kingdoms of life, important cell and systemic processes are mediated by lipids including compartmentalization, signaling and energy homeostasis. Despite important advances in liquid chromatography and mass spectrometry, sample extraction procedures remain a bottleneck in lipidomic studies, since the wide structural diversity of lipids imposes a constrain in the type and amount of lipids extracted. Differences in extraction yield across lipid classes can induce a bias on down-stream analysis and outcomes. This review aims to summarize current lipid extraction techniques used for untargeted and targeted studies based on mass spectrometry. Considerations, applications, and limitations of these techniques are discussed when used to extract lipids in complex biological matrices, such as tissues, biofluids, foods, and microorganisms.

Lipidomic profiling of non-mineralized dental plaque and biofilm by untargeted UHPLC-QTOF-MS/MS and SWATH acquisition

Dental plaque is a structurally organized biofilm which consists of diverse microbial colonies and extracellular matrix. Its composition may change when pathogenic microorganisms become dominating. Therefore, dental biofilm or plaque has been frequently investigated in the context of oral health and disease. Furthermore, its potential as an alternative matrix for analytical purposes has also been recognized in other disciplines like archeology, food sciences, and forensics. Thus, a careful in-depth characterization of dental plaque is worthwhile. Most of the conducted studies focused on the screening of microbial populations in dental plaque. Their lipid membranes, on the other hand, may significantly impact substance (metabolite) exchange within microbial colonies as well as xenobiotics uptake and incorporation into teeth. Under this umbrella, a comprehensive lipidomic profiling for determination of lipid compositions of in vivo dental plaque samples and of in vitro cultivated biofilm as surrogate matrix to be used for analytical purposes has been performed in this work. An untargeted lipidomics workflow utilizing a ultra-high-performance liquid chromatography (UHPLC)-quadrupole-time-of-flight (QTOF) platform together with comprehensive SWATH (sequential window acquisition of all theoretical fragment ion mass spectra) acquisition and compatible software (MS-DIAL) that comprises a vast lipid library has been adopted to establish an extensive lipidomic fingerprint of dental plaque. The main lipid components in dental plaque were identified as triacylglycerols, followed by cholesterol, cholesteryl esters as well as diacylglycerols, and various phospholipid classes. In vivo plaque is a rare matrix which is usually available in very low amounts. When higher quantities for specific research assays are required, efficient ways to produce an appropriate surrogate matrix are mandatory. A potential surrogate matrix substituting dental plaque was prepared by cultivation of in vitro biofilm from saliva and similarities and differences in the lipidomics profile to in vivo plaque were mapped by statistical evaluation post-analysis. It was discovered that most lipid classes were highly elevated in the in vitro biofilm samples, in particular diacylglycerols, phosphatidylglycerols, and phosphatidylethanolamines (PEs). Furthermore, an overall shift from even-chain lipid species to odd-chain lipids was observed in the cultivated biofilms. On the other hand, even-chain phosphatidylcholines (PCs), lysoPCs, cholesteryl esters, and cholesterol-sulfate were shown to be specifically increased in plaque samples.

Comprehensive lipidomics of mouse plasma using class-specific surrogate calibrants and SWATH acquisition for large-scale lipid quantification in untargeted analysis

Lipidomics has gained rising attention in recent years. Several strategies for lipidomic profiling have been developed, with targeted analysis of selected lipid species, typically utilized for lipid quantification by low-resolution triple quadrupole MS/MS, and untargeted analysis by high-resolution MS instruments, focusing on hypothesis generation for prognostic, diagnostic and/or disease-relevant biomarker discovery. The latter methodologies generally yield relative quantification data with limited inter-assay comparability. In this work we aimed to combine untargeted analysis and absolute quantification to enhance data quality and to obtain independent results for optimum comparability to previous studies or database entries. For the lipidomic analysis of mouse plasma, RP-UHPLC hyphenated to a high-resolution quadrupole TOF mass spectrometer in comprehensive data-independent SWATH acquisition mode was employed. This way, quantifiable data on the MS and the MS/MS level were recorded, which increases assay specificity and quantitative performance. Due to the lack of an appropriate blank matrix for untargeted lipidomics, we herein established a sophisticated strategy for lipid class-specific calibration with stable isotope labeled standards (surrogate calibrants). LLOQs were in the range between 10 and 50 ng mL^-1 for LPC, LPE, PI, PS, PG, SM, PC, PE, DAG) or 100-700 ng mL^-1 (MAG, TAG), except for cholesterol and CE (1-20 μg mL^-1). Acceptable values for accuracy and precision well below ±15% bias were reached for the majority of surrogate calibrants. However, to achieve sufficient accuracy for target lipids, response factors to corresponding surrogate calibrants are required. An approach to estimate response factors via a standard reference material (NIST SRM 1950) was therefore conducted. Furthermore, a useful workflow for post-acquisition re-calibration, involving response factor determination and iteratively built libraries, is suggested. In comparison to single-point calibration, the presented surrogate calibrant method was shown to yield results with improved accuracy that are largely in accordance with standard addition. Quantitative results of real samples (high-fat diet vs control diet) were then compared to two previously published dietary mouse plasma studies that provided absolute lipid levels and showed similar trends.

Study on the Material Basis of Houpo Wenzhong Decoction by HPLC Fingerprint, UHPLC-ESI-LTQ-Orbitrap-MS, and Network Pharmacology

Houpo Wenzhong Decoction (HWD) as a classical prescription has been widely used for hundreds of years. However, the quality of HWDs is difficult to control because of its herb materials from different regions. It is a new idea to use HPLC fingerprints, LTQ-ESI-Orbitrap-MS, and network pharmacology in combination to screen common components (CCs) as potential quality control indicators. In this paper, the fingerprints of HWDs were established, which were used to determine HWDs compounded from different sources of traditional Chinese medicines (TCMs). Through the similarity analysis, 45 CCs were selected. UHPLC-LTQ-ESI-Orbitrap-MS was used to carry out the chemical composition analysis of HWD. Seventy-three chemical constituents were distinguished, and 30 CCs were identified. Through network pharmacology, networks of candidate CCs, diseases, and candidate targets were constructed. Finally, four CCs were screened as potential active ingredient markers of HWD, and a method for content determination of these four components was established. A rapid, reasonable, and effective method for quality evaluation and control of HWDs was established. It provides a reference for the further development and research of HWDs and a new way of thinking for the research of other Chinese medicine prescriptions.

Challenges and Opportunities in Cancer Metabolomics

Challenges in metabolomics for a given spectrum of disease are more or less comparable, ranging from the accurate measurement of metabolite abundance, compound annotation, identification of unknown constituents, and interpretation of untargeted and analysis of high throughput targeted metabolomics data leading to the identification of biomarkers. However, metabolomics approaches in cancer studies specifically suffer from several additional challenges and require robust ways to sample the cells and tissues in order to tackle the constantly evolving cancer landscape. These constraints include, but are not limited to, discriminating the signals from given cell types and those that are cancer specific, discerning signals that are systemic and confounded, cell culture-based challenges associated with cell line identities and media standardizations, the need to look beyond Warburg effects, citrate cycle, lactate metabolism, and identifying and developing technologies to precisely and effectively sample and profile the heterogeneous tumor environment. This review article discusses some of the current and pertinent hurdles in cancer metabolomics studies. In addition, it addresses some of the most recent and exciting developments in metabolomics that may address some of these issues. The aim of this article is to update the oncometabolomics research community about the challenges and potential solutions to these issues.