LC-MS Lipidomics Research Articles

Highly reliable LC-MS lipidomics database for efficient human plasma profiling based on NIST SRM 1950

Liquid chromatography coupled to high resolution mass spectrometry (LC-HRMS)-based methods have become the gold standard methodology for the comprehensive profiling of the human plasma lipidome. However, both the complexity of lipid chemistry and LC-HRMS-associated data pose challenges to the characterization of this biological matrix. In accordance with the current consensus of quality requirements for LC-HRMS lipidomics data, we aimed to characterize the NIST® Standard Reference Material for Human Plasma (SRM 1950) using an LC-ESI(+/−)-MS method compatible with high-throughput lipidome profiling. We generated a highly curated lipid database with increased coverage, quality, and consistency, including additional quality assurance procedures involving adduct formation, within-method m/z evaluation, retention behavior of species within lipid chain isomers, and expert-driven resolution of isomeric and isobaric interferences. As a proof-of-concept, we showed the utility of our in-house LC-MS lipidomic database—consisting of 592 lipid entries—for the fast, comprehensive, and reliable lipidomic profiling of the human plasma from healthy human volunteers. We are confident that the implementation of this robust resource and methodology will have a significant impact by reducing data redundancy and the current delays and bottlenecks in untargeted plasma lipidomic studies.

Common data models to streamline metabolomics processing and annotation, and implementation in a Python pipeline.

To standardize metabolomics data analysis and facilitate future computational developments, it is essential to have a set of well-defined templates for common data structures. Here we describe a collection of data structures involved in metabolomics data processing and illustrate how they are utilized in a full-featured Python-centric pipeline. We demonstrate the performance of the pipeline, and the details in annotation and quality control using large-scale LC-MS metabolomics and lipidomics data and LC-MS/MS data. Multiple previously published datasets are also reanalyzed to showcase its utility in biological data analysis. This pipeline allows users to streamline data processing, quality control, annotation, and standardization in an efficient and transparent manner. This work fills a major gap in the Python ecosystem for computational metabolomics.

Systemic analysis of lipid metabolism from individuals to multi-organism systems.

Lipid metabolism is recognised as being central to growth, disease and health. Lipids, therefore, have an important place in current research on globally significant topics such as food security and biodiversity loss. However, answering questions in these important fields of research requires not only identification and measurement of lipids in a wider variety of sample types than ever before, but also hypothesis-driven analysis of the resulting 'big data'. We present a novel pipeline that can collect data from a wide range of biological sample types, taking 1 000 000 lipid measurements per 384 well plate, and analyse the data systemically. We provide evidence of the power of the tool through proof-of-principle studies using edible fish (mackerel, bream, seabass) and colonies of Bombus terrestris. Bee colonies were found to be more like mini-ecosystems and there was evidence for considerable changes in lipid metabolism in bees through key developmental stages. This is the first report of either high throughput LCMS lipidomics or systemic analysis in individuals, colonies and ecosystems. This novel approach provides new opportunities to analyse metabolic systems at different scales at a level of detail not previously feasible, to answer research questions about societally important topics.

High-Throughput Microbore LC-MS Lipidomics to Investigate APOE Phenotypes.

Microflow liquid chromatography interfaced with mass spectrometry (μLC-MS/MS) is increasingly applied for high-throughput profiling of biological samples and has been proven to have an acceptable trade-off between sensitivity and reproducibility. However, lipidomics applications are scarce. We optimized a μLC-MS/MS system utilizing a 1 mm inner diameter × 100 mm column coupled to a triple quadrupole mass spectrometer to establish a sensitive, high-throughput, and robust single-shot lipidomics workflow. Compared to conventional lipidomics methods, we achieve a ∼4-fold increase in response, facilitating quantification of 351 lipid species from a single iPSC-derived cerebral organoid during a 15 min LC-MS analysis. Consecutively, we injected 303 samples over ∼75 h to prove the robustness and reproducibility of the microflow separation. As a proof of concept, μLC-MS/MS analysis of Alzheimer's disease patient-derived iPSC cerebral organoid reveals differential lipid metabolism depending on APOE phenotype (E3/3 vs E4/4). Microflow separation proves to be an environmentally friendly and cost-effective method as it reduces the consumption of harmful solvents. Also, the data demonstrate robust, in-depth, high-throughput performance to enable routine clinical or biomedical applications.

The main nutritional components in colored rice grains

Colored rice grains contain rich nutrients. To investigate the differences in nutrient composition among different colored rice varieties, LC-MS non-targeted lipidomics and targeted amino acid profiling were used to study the lipid and amino acid composition in four colored rice grains. The study analyzed the relationship between amino acids, mineral elements, crude protein (CP), crude fat (CF), carotenoids (CAROT), vitamin C (ASA), ATP, total sugar (TS), soluble protein (SP), and metabolites. A total of 505 lipid metabolites were identified. The results depicted that YZ6H had the highest levels of Arg, Asn, Met, Orn, and Try. HN had the highest levels of GABA, His, Lys, Thr, Tyr, Val, and Tau, which were significantly higher than those in YZ6H, YJN818, and YCN1H. PC (16:0/16:1,16:1/18:2,18:1/14:1,18:1/14:0,18:1/18:1,18:0/18:1), TG (16:0/18:3/22:2,22:4/18:2/18:2,16:0/20:2/20:4), and PE(20:4e/15:0) were significantly negatively correlated with GABA, Leu, Lys, Thr, Tyr, Val, Gln, His, and Ile. TG(18:2/17:1/18:2,15:0/18:2/18:2,15:0/18:2/18:3,15:0/16:0/18:2,15:0/18:1/18:2,18:1/17:1/18:2,18:1/17:1/18:1,18:1/10:1/18:1) was significantly positively correlated with Pro and Tau. YZ6H had the highest levels of ASA, SP, TS, CAROT, and ATP content. PG(28:0/18:1), MLCL(14:2/16:0/16:0), Cer(t18:0/26:0+O,d18:2/16:0,t18:0/26:0), and LPC(16:0) TG(20:4e/18:3/20:1) were significantly negatively correlated with SP, CAROT. Hex1Cer(t18:1/24:0+O), MLCL(14:2/16:0/16:0), Cer(t18:0/26:0+O,d18:2/16:0,t18:0/26:0), LPC(16:0), TG(16:0/20:2/20:4,20:4e/18:3/20:1), and DG(18:1/14:0), which are key lipid metabolites involved in the synthesis of nutritional components in colored rice grains.

Effect of statin treatment on metabolites, lipids and prostanoids in patients with Statin Associated Muscle Symptoms (SAMS).

Between 5-10% of patients discontinue statin therapy due to statin-associated adverse reactions, primarily statin associated muscle symptoms (SAMS). The absence of a clear clinical phenotype or of biomarkers poses a challenge for diagnosis and management of SAMS. Similarly, our incomplete understanding of the pathogenesis of SAMS hinders the identification of treatments for SAMS. Metabolomics, the profiling of metabolites in biofluids, cells and tissues is an important tool for biomarker discovery and provides important insight into the origins of symptomatology. In order to better understand the pathophysiology of this common disorder and to identify biomarkers, we undertook comprehensive metabolomic and lipidomic profiling of plasma samples from patients with SAMS who were undergoing statin rechallenge as part of their clinical care. We report our findings in 67 patients, 28 with SAMS (cases) and 39 statin-tolerant controls. SAMS patients were studied during statin rechallenge and statin tolerant controls were studied while on statin. Plasma samples were analyzed using untargeted LC-MS metabolomics and lipidomics to detect differences between cases and controls. Differences in lipid species in plasma were observed between cases and controls. These included higher levels of linoleic acid containing phospholipids and lower ether lipids and sphingolipids. Reduced levels of acylcarnitines and altered amino acid profile (tryptophan, tyrosine, proline, arginine, and taurine) were observed in cases relative to controls. Pathway analysis identified significant increase of urea cycle metabolites and arginine and proline metabolites among cases along with downregulation of pathways mediating oxidation of branched chain fatty acids, carnitine synthesis, and transfer of acetyl groups into mitochondria. The plasma metabolome of patients with SAMS exhibited reduced content of long chain fatty acids and increased levels of linoleic acid (18:2) in phospholipids, altered energy production pathways (β-oxidation, citric acid cycle and urea cycles) as well as reduced levels of carnitine, an essential mediator of mitochondrial energy production. Our findings support the hypothesis that alterations in pro-inflammatory lipids (arachidonic acid pathway) and impaired mitochondrial energy metabolism underlie the muscle symptoms of patients with statin associated muscle symptoms (SAMS).

Crystalline silica-induced proinflammatory eicosanoid storm in novel alveolar macrophage model quelled by docosahexaenoic acid supplementation.

Phagocytosis of inhaled crystalline silica (cSiO2) particles by tissue-resident alveolar macrophages (AMs) initiates generation of proinflammatory eicosanoids derived from the ω-6 polyunsaturated fatty acid (PUFA) arachidonic acid (ARA) that contribute to chronic inflammatory disease in the lung. While supplementation with the ω-3 PUFA docosahexaenoic acid (DHA) may influence injurious cSiO2-triggered oxylipin responses, in vitro investigation of this hypothesis in physiologically relevant AMs is challenging due to their short-lived nature and low recovery numbers from mouse lungs. To overcome these challenges, we employed fetal liver-derived alveolar-like macrophages (FLAMs), a self-renewing surrogate that is phenotypically representative of primary lung AMs, to discern how DHA influences cSiO2-induced eicosanoids. We first compared how delivery of 25 µM DHA as ethanolic suspensions or as bovine serum albumin (BSA) complexes to C57BL/6 FLAMs impacts phospholipid fatty acid content. We subsequently treated FLAMs with 25 µM ethanolic DHA or ethanol vehicle (VEH) for 24h, with or without LPS priming for 2h, and with or without cSiO2 for 1.5 or 4h and then measured oxylipin production by LC-MS lipidomics targeting for 156 oxylipins. Results were further related to concurrent proinflammatory cytokine production and cell death induction. DHA delivery as ethanolic suspensions or BSA complexes were similarly effective at increasing ω-3 PUFA content of phospholipids while decreasing the ω-6 PUFA arachidonic acid (ARA) and the ω-9 monounsaturated fatty acid oleic acid. cSiO2 time-dependently elicited myriad ARA-derived eicosanoids consisting of prostaglandins, leukotrienes, thromboxanes, and hydroxyeicosatetraenoic acids in unprimed and LPS-primed FLAMs. This cSiO2-induced eicosanoid storm was dramatically suppressed in DHA-supplemented FLAMs which instead produced potentially pro-resolving DHA-derived docosanoids. cSiO2 elicited marked IL-1α, IL-1β, and TNF-α release after 1.5 and 4h of cSiO2 exposure in LPS-primed FLAMs which was significantly inhibited by DHA. DHA did not affect cSiO2-triggered death induction in unprimed FLAMs but modestly enhanced it in LPS-primed FLAMs. FLAMs are amenable to lipidome modulation by DHA which suppresses cSiO2-triggered production of ARA-derived eicosanoids and proinflammatory cytokines. FLAMs are a potential in vitro alternative to primary AMs for investigating interventions against early toxicant-triggered inflammation in the lung.

Non-target ROIMCR LC–MS analysis of the disruptive effects of TBT over time on the lipidomics of Daphnia magna

IntroductionThis study has investigated the temporal disruptive effects of tributyltin (TBT) on lipid homeostasis in Daphnia magna. To achieve this, the study used Liquid Chromatography–Mass Spectrometry (LC–MS) analysis to analyze biological samples of Daphnia magna treated with TBT over time. The resulting data sets were multivariate and three-way, and were modeled using bilinear and trilinear non-negative factor decomposition chemometric methods. These methods allowed for the identification of specific patterns in the data and provided insight into the effects of TBT on lipid homeostasis in Daphnia magna.ObjectivesInvestigation of how are the changes in the lipid concentrations of Daphnia magna pools when they were exposed with TBT and over time using non-targeted LC–MS and advanced chemometric analysis.MethodsThe simultaneous analysis of LC–MS data sets of Daphnia magna samples under different experimental conditions (TBT dose and time) were analyzed using the ROIMCR method, which allows the resolution of the elution and mass spectra profiles of a large number of endogenous lipids. Changes obtained in the peak areas of the elution profiles of these lipids caused by the dose of TBT treatment and the time after its exposure are analyzed by principal component analysis, multivariate curve resolution-alternative least square, two-way ANOVA and ANOVA-simultaneous component analysis.Results87 lipids were identified. Some of these lipids are proposed as Daphnia magna lipidomic biomarkers of the effects produced by the two considered factors (time and dose) and by their interaction. A reproducible multiplicative effect between these two factors is confirmed and the optimal approach to model this dataset resulted to be the application of the trilinear factor decomposition model.ConclusionThe proposed non-targeted LC–MS lipidomics approach resulted to be a powerful tool to investigate the effects of the two factors on the Daphnia magna lipidome using chemometric methods based on bilinear and trilinear factor decomposition models, according to the type of interaction between the design factors.

UV and visible light exposure to hair leads to widespread changes in the hair lipidome.

Scalp hair is among the most exposed parts of the human body, yet the impact of visible and UV light on hair lipids, an important structural component of hair, is poorly researched. We have used lipidomics, a broad-based approach to measure lipids in samples, which has hitherto not been applied to UV-exposed hair in the published literature, and could allow for a wider understanding of how UV light impacts on specific hair lipids. Mixed blonde Caucasian hair switches were divided into two groups of five, with half of the hair switches exposed to UV and visible light mimicking normal daytime exposure and half left unexposed. LC-MS lipidomics was used to profile the lipids in the hair samples. A total of 791 lipids and 32 lipid classes with tentative identifications were detected in the hair samples. Nineteen lipid classes and 397 lipids differed between UV-treated and non-treated hair. The main lipid classes that differed were vitamin A fatty acid esters, sterol esters, several ceramides, mono-, di- and triglycerides, phosphatidylethanolamines (all decreased in UV-exposed hair) and bismonoacylglycerolphosphates, acylcarnitines and acylglycines (all increased in UV-exposed hair). Most detected lipids were decreased in UV-exposed hair, supporting earlier work that has found that UV exposure causes oxidation of lipids which would result in a decrease in most lipid classes. Light exposure to hair has a widespread impact on the hair lipidome. This study also adds to the emerging literature on the hair lipidome, broadening the range of lipid classes reported in hair.

Abstract 356: Phospholipid Profile Of Cerebral Thrombi In Acute Ischemic Stroke

Background and Purpose: The University of Washington Clot Bank (UWCB) has established a tissue banking protocol optimized for “omic” analysis for cerebral thrombi retrieved during standard-of-care thrombectomy. Thrombi from cerebral arteries of acute ischemic stroke (AIS) patients are a novel resource that allow for the evaluation of lipid biological markers present at the time of ictus. The pathophysiological processes following AIS are complex, and involve ischemia, inflammation, and disturbances of lipid metabolism. The purpose of this study was to characterize the lipid profile from cerebral thrombi in AIS patients. Methods: The UWCB study is a non-probability, convenience sampling of adult subjects (> 18 years of age) who undergo thrombectomy for vascular occlusion. Lipidomics analysis was performed using LC-MS of untargeted lipids on thrombi taken from cerebral arteries of AIS subjects who underwent thrombectomy. Random forest, a supervised machine learning method, was employed to identify lipids associated with cerebral thrombi. Results: Five subjects (age = 53 ± 26.4, 3 males) were included from the UWCB registry. The most common comorbid conditions were atrial fibrillation (40%) and hypertension (40%). The top 10 metabolites identified from the random forest analysis, were of phosphatidylethanolamine molecular species. Phospholipids are involved in structural and functional integrity of cellular membranes and mediate host inflammatory responses. They are a key component of bacterial membranes. Changes in the structure or function of membrane phospholipids of host or relevant human microbiota may lead to alterations in membrane permeability and contribute to pathology of diseases such as neurodegeneration. Conclusion: An untargeted LC-MS lipidomics approach was used to identify lipids in cerebral thrombi at the time of mechanical thrombectomy. The top 10 lipids present in cerebral thrombi were identified, which included significant concentrations of phosphatidylethanolamine species. Because phospholipids play a key regulatory role in complex downstream cellular function, these findings may be of great significance in understanding AIS pathophysiology that has the potential to inform personalized preventive strategies.

LC-MS lipidomics of renal biopsies for the diagnosis of Fabry disease

IntroductionLipidomics analysis or lipid profiling is a system-based analysis of all lipids in a sample to provide a comprehensive understanding of lipids within a biological system. In the last few years, lipidomics has made it possible to better understand the metabolic processes associated with several rare disorders and proved to be a powerful tool for their clinical investigation. Fabry disease is a rare X-linked lysosomal storage disorder (LSD) caused by a deficiency in α-galactosidase A (α-GAL A). This deficiency results in the progressive accumulation of glycosphingolipids, mostly globotriaosylceramide (Gb3), globotriaosylsphingosine (lyso-Gb3), as well as galabiosylceramide (Ga2) and their isoforms/analogs in the vascular endothelium, nerves, cardiomyocytes, renal glomerular podocytes, and biological fluids. ObjectivesThe primary objective of this study was to evaluate lipidomic signatures in renal biopsies to help understand variations in Fabry disease markers that could be used in future diagnostic tests. MethodsLipidomic analysis was performed by ultra-high pressure liquid chromatography-high-resolution mass spectrometry (UHPLC-HRMS) on kidney biopsies that were left over after clinical pathology analysis to diagnose Fabry disease. ResultsWe employed UHPLC-HRMS lipidomics analysis on the renal biopsy of a patient suspicious for Fabry disease. Our result confirmed α-GAL A enzyme activity declined in this patient since a Ga2-related lipid biomarker was substantially higher in the patient's renal tissue biopsy compared with two controls. This suggests this patient has a type of LSD that could be non-classical Fabry disease. ConclusionThis study shows that lipidomics analysis is a valuable tool for rare disorder diagnosis, which can be conducted on leftover tissue samples without disrupting normal patient care.

NO● Represses the Oxygenation of Arachidonoyl PE by 15LOX/PEBP1: Mechanism and Role in Ferroptosis.

We recently discovered an anti-ferroptotic mechanism inherent to M1 macrophages whereby high levels of NO● suppressed ferroptosis via inhibition of hydroperoxy-eicosatetraenoyl-phosphatidylethanolamine (HpETE-PE) production by 15-lipoxygenase (15LOX) complexed with PE-binding protein 1 (PEBP1). However, the mechanism of NO● interference with 15LOX/PEBP1 activity remained unclear. Here, we use a biochemical model of recombinant 15LOX-2 complexed with PEBP1, LC-MS redox lipidomics, and structure-based modeling and simulations to uncover the mechanism through which NO● suppresses ETE-PE oxidation. Our study reveals that O2 and NO● use the same entry pores and channels connecting to 15LOX-2 catalytic site, resulting in a competition for the catalytic site. We identified residues that direct O2 and NO● to the catalytic site, as well as those stabilizing the esterified ETE-PE phospholipid tail. The functional significance of these residues is supported by in silico saturation mutagenesis. We detected nitrosylated PE species in a biochemical system consisting of 15LOX-2/PEBP1 and NO● donor and in RAW264.7 M2 macrophages treated with ferroptosis-inducer RSL3 in the presence of NO●, in further support of the ability of NO● to diffuse to, and react at, the 15LOX-2 catalytic site. The results provide first insights into the molecular mechanism of repression of the ferroptotic Hp-ETE-PE production by NO●.

Vitamin A and D Absorption in Adults with Metabolic Syndrome versus Healthy Controls: A Pilot Study Utilizing Targeted and Untargeted LC-MS Lipidomics.

Persons with metabolic syndrome (MetS) absorb less vitamin E than healthy controls. It is hypothesized that absorption of fat-soluble vitamins (FSV) A and D2 would also decrease with MetS status and that trends would be reflected in lipidomic responses between groups. Following soymilk consumption (501 IU vitamin A, 119 IU vitamin D2 ), the triglyceride-rich lipoprotein fractions (TRL) from MetS and healthy subjects (n = 10 age- and gender-matched subjects/group) are assessed using LC-MS/MS. Absorption is calculated using area under the time-concentration curves (AUC) from samples collected at 0, 3, and 6 h post-ingestion. MetS subjects have ≈6.4-fold higher median vitamin A AUC (retinyl palmitate) versus healthy controls (P = 0.07). Vitamin D2 AUC is unaffected by MetS status (P = 0.48). Untargeted LC-MS lipidomics reveals six phospholipids and one cholesterol ester with concentrations correlating (r = 0.53-0.68; P <0.001) with vitamin A concentration. The vitamin A-phospholipid association suggests increased hydrolysis by PLB, PLRP2, and/or PLA2 IB may be involved in the trend in higher vitamin A bioavailability in MetS subjects. Previously observed differences in circulating levels of these vitamins are likely not due to absorption. Alternate strategies should be investigated to improve FSV status in MetS.

LC–MS Lipidomics: Exploiting a Simple High-Throughput Method for the Comprehensive Extraction of Lipids in a Ruminant Fat Dose-Response Study

Typical lipidomics methods incorporate a liquid–liquid extraction with LC–MS quantitation; however, the classic sample extraction methods are not high-throughput and do not perform well at extracting the full range of lipids especially, the relatively polar species (e.g., acyl-carnitines and glycosphingolipids). In this manuscript, we present a novel sample extraction protocol, which produces a single phase supernatant suitable for high-throughput applications that offers greater performance in extracting lipids across the full spectrum of species. We applied this lipidomics pipeline to a ruminant fat dose–response study to initially compare and validate the different extraction protocols but also to investigate complex lipid biomarkers of ruminant fat intake (adjoining onto simple odd chain fatty acid correlations). We have found 100 lipids species with a strong correlation with ruminant fat intake. This novel sample extraction along with the LC–MS pipeline have shown to be sensitive, robust and hugely informative (>450 lipids species semi-quantified): with a sample preparation throughput of over 100 tissue samples per day and an estimated ~1000 biological fluid samples per day. Thus, this work facilitating both the epidemiological involvement of ruminant fat, research into odd chain lipids and also streamlining the field of lipidomics (both by sample preparation methods and data presentation).

Hydrogen/Deuterium Exchange Aiding Compound Identification for LC-MS and MALDI Imaging Lipidomics.

We present a novel approach for the increasing reliability of compound identification for LC-MS and MALDI imaging lipidomics. Our approach is based on the characterization of compounds not only by the elution time, accurate mass, and fragmentation spectra but also by the number of labile hydrogens that can be measured using the hydrogen/deuterium (H/D) exchange approach. The number of labile hydrogens (those from -OH and -NH groups) serves as an additional structural descriptor used when performing a database search. For LC-MS experiment, the H/D exchange was performed in the heating capillary of the modified electrospray ionization (ESI) source, while for MALDI imaging, the exchange was performed in the ion funnel at 10 Torr pressure. It was observed that such an approach allowed one to achieve a considerable degree of deuteration, enough to unambiguously distinguish between different classes of lipids. The proposed analytical approach may be successfully used for the identification not only of lipids but also of peptides and metabolites. A special software for the automatic filtration of molecules based on the number of functional groups was also developed.

Rational selection of reverse phase columns for high throughput LC-MS lipidomics.

Natural lipidomes are characterized by extremely high complexity and dynamic range of lipid concentrations. Furthermore, high diversity of lipid physicochemical properties requires high resolving powers for both chromatographic and mass spectrometric analytical platforms. Reverse-phase chromatography coupled with data-dependent MS/MS acquisition is one of the most popular techniques in untargeted lipidomics. Optimal method should provide good chromatographic separation and resolution, reproducibility, selectivity and sensitivity. Here, we developed and set-up a RPLC-MS/MS workflow capable of resolving complex mixtures of lipids in 32 min of analysis. Human blood plasma was chosen as a representative complex natural lipidome with large variance of lipid classes, species and lipid concentrations. Lipids were separated by RPLC on five different reverse phase columns with different types of stationary phase particles, size and chemistry. High mass accuracy MS analysis and data-dependent MS/MS analysis were performed using a Q Exactive™ HF Hybrid Quadrupole-Orbitrap™ Mass Spectrometer to identify individual lipid molecular species. This workflow was applied to evaluate the separation capability of each column and to identify the lipidomics profile in highly complex biological samples. As a result, we report more than 600 lipid species covering 18 lipid classes in human blood plasma and provide suggestions to the selection of the appropriate reverse phase column for the analysis of specific lipidomes.

Abstract P2-02-15: All-trans retinoic acid perturbs the lipidomic profiles of luminal breast cancer cells characterized by sensitivity to the anti-proliferative activity of the retinoid

Abstract Background: All-trans retinoic acid (ATRA) is the active metabolite of vitamin A and a promising agent in the prevention and treatment of breast cancer. We recently demonstrated that approximately 70% of estrogen-receptor-positive (ER+) breast cancer cell lines and primary tumors are sensitive to the anti-proliferative effects of ATRA (1,2). In contrast only 10-20% of the HER2-positive and triple-negative counterparts respond to the retinoid. The significance of lipids in the growth, progression and drug sensitivity of specific types of solid tumors, including breast cancer, is largely overlooked. In particular the role, if any, of specific lipids in the anti-tumor action of ATRA in breast cancer has never been studied. Aims and Approach: The principal aim of the present work was to evaluate the specific perturbations induced by ATRA on the homeostasis of lipids in breast cancer cells characterized by sensitivity to the anti-proliferative action of the retinoid. To this purpose, we took a high-throughput approach and defined the lipidomic profiles of 16 breast cancer cell lines in basal conditions and following challenge with ATRA (1 μM) for 48 hours. The panel consisted of eight cell lines characterized by a luminal phenotype and eight cell lines with a basal phenotype. Four ATRA-sensitive cell lines (SKBR3, HCC1500, CAMA1 and MDAMB361) and 4 ATRA-resistant counterparts (HCC202, MDAMB175VII, ZR75.1 and HCC1419) were included in the luminal group. Similarly, the basal group contained 4 ATRA-sensitive (HCC1599, MB157, MDAMB157 and Hs578T) and 4 ATRA-resistant (MDAMB231, CAL851, HCC1187 and MDAMB436) cell types. Results: Using Lipostar, a unique and recently developed software for high-throughput LC-MS lipidomics analysis (3), we identified lipid species whose levels were modified by ATRA in each cell line. This resulted in the generation of a lipid fingerprint consisting of 530 elements. We observed that ATRA reduced the amounts of cardiolipins in luminal and ATRA-sensitive breast cancer cell lines specifically. Similar effects were not observed in luminal and ATRA-resistant cells. ATRA-dependent reduction in the amounts of cardiolipins were never observed in basal cells, regardless of their sensitivity to the retinoid. Given the role played by cardiolipins in the homeostasis of the mitochondria, we evaluated the action of ATRA on the functional activity of these organelles in the luminal and ATRA-sensitive or ATRA-resistant cell lines. In SKBR3 and the other sensitive cell lines, we observed that ATRA modulated mitochondria-dependent oxygen consumption and ATP production. These effects were accompanied by an increase in mitochondrial membrane fluidity, which is consistent with the effects exerted by ATRA on the cellular content of cardiolipins. ATRA-dependent action on cardiolipins and mitochondrial homeostasis precedes maximal growth inhibition. The results provide new insights on the mechanisms underlying the anti-tumor action of ATRA. References : 1) Centritto F. et al. EMBO Mol Med. 2015 Jul;7(7):950-72. 2) Bolis M et al.. Ann Oncol. 2017 Mar 1;28(3):611-621. 3) Goracci, L. et al., Anal Chem 2017, 89 (11), 6258-6265. Citation Format: Terao M, Celestini V, Kurosaki M, Vallerga A, Bolis M, Fratelli M, Paroni G, Di Veroli A, Cruciani G, Goracci L, Garattini E. All-trans retinoic acid perturbs the lipidomic profiles of luminal breast cancer cells characterized by sensitivity to the anti-proliferative activity of the retinoid [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P2-02-15.

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

In this study, two monophasic isopropanol-water mixtures (IPA:H2O 75:25 v/v and IPA:H2O 90:10 v/v) were compared with traditionally employed biphasic methods of Bligh & Dyer and Matyash et al. as extraction systems for lipidomics analysis in Hela cells. Samples were analyzed by UHPLC-ESI-QTOF-MS/MS in positive and negative mode using sequential window acquisition of all theoretical fragment ion spectra (SWATH) and a relatively new software (MS-DIAL) was employed for the processing of the data which includes detection of peaks, MS/MS spectra deconvolution, identification of detected lipids and alignment of peaks through the analyzed samples.The studied performance parameters such as precision, recoveries of isotopically labeled internal standards and endogenous lipids, number of extracted lipids, and complexity of employed procedure showed that extraction with IPA:H2O 90:10 v/v performs similar to the Matyash protocol and better than Bligh & Dyer as well as IPA:H2O 75:25 v/v. However, less complex monophasic protocol which is simpler to implement and can be executed in plastic rather than glass, make the monophasic IPA:H2O 90:10 v/v protocol an excellent alternative to the classical biphasic protocols for reversed phase LC-MS lipidomics studies.

Unbiased Lipidomic Profiling of Triple-Negative Breast Cancer Tissues Reveals the Association of Sphingomyelin Levels with Patient Disease-Free Survival.

The reprogramming of lipid metabolism is a hallmark of many cancers that has been shown to promote breast cancer progression. While several lipid signatures associated with breast cancer aggressiveness have been identified, a comprehensive lipidomic analysis specifically targeting the triple-negative subtype of breast cancer (TNBC) may be required to identify novel biomarkers and therapeutic targets for this most aggressive subtype of breast cancer that still lacks effective therapies. In this current study, our global LC-MS-based lipidomics platform was able to measure 684 named lipids across 15 lipid classes in 70 TNBC tumors. Multivariate survival analysis found that higher levels of sphingomyelins were significantly associated with better disease-free survival in TNBC patients. Furthermore, analysis of publicly available gene expression datasets identified that decreased production of ceramides and increased accumulation of sphingoid base intermediates by metabolic enzymes were associated with better survival outcomes in TNBC patients. Our LC-MS lipidomics profiling of TNBC tumors has, for the first time, identified sphingomyelins as a potential prognostic marker and implicated enzymes involved in sphingolipid metabolism as candidate therapeutic targets that warrant further investigation.

Quantification of run order effect on chromatography - mass spectrometry profiling data

Chromatographic systems coupled with mass spectrometry detection are widely used in biological studies investigating how levels of biomolecules respond to different internal and external stimuli. Such changes are normally expected to be of low magnitude and therefore all experimental factors that can influence the analysis need to be understood and minimized. Run order effect is commonly observed and constitutes a major challenge in chromatography-mass spectrometry based profiling studies that needs to be addressed before the biological evaluation of measured data is made. So far there is no established consensus, metric or method that quickly estimates the size of this effect. In this paper we demonstrate how orthogonal projections to latent structures (OPLS®) can be used for objective quantification of the run order effect in profiling studies. The quantification metric is expressed as the amount of variation in the experimental data that is correlated to the run order. One of the primary advantages with this approach is that it provides a fast way of quantifying run-order effect for all detected features, not only internal standards. Results obtained from quantification of run order effect as provided by the OPLS can be used in the evaluation of data normalization, support the optimization of analytical protocols and identification of compounds highly influenced by instrumental drift. The application of OPLS for quantification of run order is demonstrated on experimental data from plasma profiling performed on three analytical platforms: GCMS metabolomics, LCMS metabolomics and LCMS lipidomics.