Development of a lipid profiling system using reverse-phase liquid chromatography coupled to high-resolution mass spectrometry with rapid polarity switching and an automated lipid identification software

Seasonal variation in non-volatile flavor substances of fresh tea leaves (Camellia sinensis) by integrated lipidomics and metabolomics using UHPLC-Q-Exactive mass spectrometry

Harvest season exerts great influence on tea quality. Herein, the variations in non-volatile flavor substances in spring and summer fresh tea leaves of four varieties were comprehensively investigated by integrating UHPLC-Q-Exactive based lipidomics and metabolomics. A total of 327 lipids and 99 metabolites were detected, among which, 221 and 58 molecules were significantly differential. The molecular species of phospholipids, glycolipids and acylglycerolipids showed most prominent and structure-dependent seasonal changes, relating to polar head, unsaturation and total acyl length. Particularly, spring tea contained higher amount in aroma precursors of highly unsaturated glycolipids and phosphatidic acids. The contents of umami-enhancing amino acids and phenolic acids, e.g., theanine, theogallin and gallotannins, were increased in spring. Besides, catechins, theaflavins, theasinensins and flavone/flavonol glycosides showed diverse changes. These phytochemical differences covered key aroma precursors, tastants and colorants, and may confer superior flavor of black tea processed using spring leaves, which was verified by sensory evaluation.

Effects of different processing methods on the lipid composition of seabuckthorn fruit oil based on lipidomics

Employing lipidomics, this study investigated the lipid composition of seabuckthorn fruit oil processed via supercritical CO2 extraction and centrifugal separation. Qualitative analysis showed that a total of 2861 lipid molecules were identified in seabuckthorn fruit oil. Quantitative analysis showed that the content of lipids in seabuckthorn fruit oil extracted by supercritical CO2 extraction (927,539.84 µg/mL) was significantly higher than that in centrifugal-separated seabuckthorn fruit oil (735,717.63 µg/mL), with 17 distinct lipid classes and 215 lipid molecules differentiated through multivariate statistical analysis. Lipid molecules, such as diacylglycerol (DG), ceramides (Cer), monohexosyl ceramide, phosphatidylglycerol, phosphatidylinositol, phosphatidylethanolamine, and monogalactosyl DG, were predominantly found in the oil extracted using supercritical CO2. In contrast, monogalactosyl monoacylglycerol, diglycosyl ceramide, and Cer phosphate were significantly present in the oil extracted by centrifugal separation. These findings contribute new insights into how processing methods affect the quality and composition of seabuckthorn fruit oil and provide a basis for detecting oil adulteration.

Discovery of Plasma Lipids as Potential Biomarkers Distinguishing Breast Cancer Patients from Healthy Controls

The development of a sensitive and specific blood test for the early detection of breast cancer is crucial to improve screening and patient outcomes. Existing methods, such as mammography, have limitations, necessitating the exploration of alternative approaches, including circulating factors. Using 598 prospectively collected blood samples, a multivariate plasma-derived lipid biomarker signature was developed that can distinguish healthy control individuals from those with breast cancer. Liquid chromatography with high-resolution and tandem mass spectrometry (LC-MS/MS) was employed to identify lipids for both extracellular vesicle-derived and plasma-derived signatures. For each dataset, we identified a signature of 20 lipids using a robust, statistically rigorous feature selection algorithm based on random forest feature importance applied to cross-validated training samples. Using an ensemble of machine learning models, the plasma 20-lipid signature generated an area under the curve (AUC) of 0.95, sensitivity of 0.91, and specificity of 0.79. The results from this study indicate that lipids extracted from plasma can be used as target analytes in the development of assays to detect the presence of early-stage breast cancer.

Development of a robust non-targeted analysis approach for fast identification of endocrine disruptors and their metabolites in human urine for exposure assessment

Endocrine disrupting chemicals are of concern because of possible human health effects, thus they are frequently included in biomonitoring studies. Current analytical methods are focused on known chemicals and are incapable of identifying or quantifying other unknown chemicals and their metabolites. Non-targeted analysis (NTA) methods are advantageous since they allow for broad chemical screening, which provides a more comprehensive characterization of human chemical exposure, and can allow elucidation of metabolic pathways for unknown chemicals. There are still many challenges associated with NTA, which can impact the results obtained. The chemical space, i.e., the group of known and possible compounds within the scope of the method, must clearly be defined based on the sample preparation, as this is critical in identifying chemicals with confidence. Data acquisition modes and mobile phase additives used with liquid chromatography coupled to high-resolution mass-spectrometry can affect the chemicals ionized and structural identification based on the spectral quality. In this study, a sample preparation method was developed using a novel clean-up approach with CarbonS cartridges, for endocrine-disrupting chemicals in urine, including new bisphenol A analogues and benzophenone-based UV filters, like methyl bis (4-hydroxyphenyl acetate). The study showed that data dependent acquisition (DDA) had a lower identification rate (40%) at low spiking levels, i.e., 1 ng/mL, compared to data independent acquisition (DIA) (57%), when Compound Discoverer was used. In DDA, more compounds were identified using Compound Discoverer, with an identification rate of 95% when ammonium acetate was compared to acetic acid (82%) as a mobile phase additive. TraceFinder software had an identification rate of 53% at 1 ng/mL spiking level using the DDA data, compared to 40% using the DIA data. Using the developed method, 2,4 bisphenol F was identified for the first time in urine samples. The results show how NTA can provide human exposure information for risk assessment and regulatory action but standardized reporting of procedures is needed to ensure study results are reproducible and accurate. His Majesty the King in Right of Canada, as represented by the Minister of Health, 2024.

Lipidomic and Fatty Acid Biomarkers in Whole Blood Can Predict the Dietary Intake of Eicosapentaenoic and Docosahexaenoic Acids in a Danish Population

BACKGROUND

The intake of eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) have been associated with health benefits. Blood levels of these fatty acids, measured by gas chromatography (GC), are associated with their dietary intake, but the relationships with lipidomic measurements are not well defined.

OBJECTIVES

This study aimed to determine the lipidomic biomarkers in whole blood that predict intakes of EPA + DHA and examine the relationship between lipidomic and GC-based n-3 polyunsaturated fatty acid (n-3 PUFA) biomarkers.

METHODS

Lipidomic and fatty acid analyses were completed on 120 whole blood samples collected from Danish participants. Dietary intakes were completed using a web-based 7-d food diary. Stepwise multiple linear regression was used to identify the fatty acid and lipidomic variables that predict intakes of EPA + DHA and to determine lipidomic species that predict commonly used fatty acid biomarkers.

RESULTS

Stepwise regression selected lipidomic variables with an R2 = 0.52 for predicting EPA + DHA intake compared to R2 = 0.40 for the selected fatty acid GC-based variables. More predictive models were generated when the lipidomic variables were selected for females only (R2 = 0.62, n = 68) and males only (R2 = 0.72, n = 52). Phosphatidylethanolamine plasmalogen species containing EPA or DHA tended to be the most predictive lipidomic variables. Stepwise regression also indicated that selected lipidomic variables can predict commonly used fatty acid GC-based n-3 PUFA biomarkers as the R2 values ranged from 0.84 to 0.91.

CONCLUSIONS

Both fatty acid and lipidomic data can be used to predict EPA + DHA intakes, and fatty acid GC-based biomarkers can be emulated by lipidomic species. Lipidomic-based biomarkers appear to be influenced by sex differences, probably in n-3 PUFA and lipoprotein metabolism. These results improve our ability to understand the relationship between novel lipidomic data and GC fatty acid data and will increase our ability to apply lipidomic methods to fatty acid and lipid nutritional research.

Altered myocardial lipid regulation in junctophilin-2-associated familial cardiomyopathies

Myocardial lipid metabolism is critical to normal heart function, whereas altered lipid regulation has been linked to cardiac diseases including cardiomyopathies. Genetic variants in the JPH2 gene can cause hypertrophic cardiomyopathy (HCM) and, in some cases, dilated cardiomyopathy (DCM). In this study, we tested the hypothesis that JPH2 variants identified in patients with HCM and DCM, respectively, cause distinct alterations in myocardial lipid profiles. Echocardiography revealed clinically significant cardiac dysfunction in both knock-in mouse models of cardiomyopathy. Unbiased myocardial lipidomic analysis demonstrated significantly reduced levels of total unsaturated fatty acids, ceramides, and various phospholipids in both mice with HCM and DCM, suggesting a common metabolic alteration in both models. On the contrary, significantly increased di- and triglycerides, and decreased co-enzyme were only found in mice with HCM. Moreover, mice with DCM uniquely exhibited elevated levels of cholesterol ester. Further in-depth analysis revealed significantly altered metabolites from all the lipid classes with either similar or opposing trends in JPH2 mutant mice with HCM or DCM. Together, these studies revealed, for the first time, unique alterations in the cardiac lipid composition-including distinct increases in neutral lipids and decreases in polar membrane lipids-in mice with HCM and DCM were caused by distinct JPH2 variants. These studies may aid the development of novel biomarkers or therapeutics for these inherited disorders.

MMD collaborates with ACSL4 and MBOAT7 to promote polyunsaturated phosphatidylinositol remodeling and susceptibility to ferroptosis

Ferroptosis is a form of regulated cell death with roles in degenerative diseases and cancer. Excessive iron-catalyzed peroxidation of membrane phospholipids, especially those containing the polyunsaturated fatty acid arachidonic acid (AA), is central in driving ferroptosis. Here, we reveal that an understudied Golgi-resident scaffold protein, MMD, promotes susceptibility to ferroptosis in ovarian and renal carcinoma cells in an ACSL4- and MBOAT7-dependent manner. Mechanistically, MMD physically interacts with both ACSL4 and MBOAT7, two enzymes that catalyze sequential steps to incorporate AA in phosphatidylinositol (PI) lipids. Thus, MMD increases the flux of AA into PI, resulting in heightened cellular levels of AA-PI and other AA-containing phospholipid species. This molecular mechanism points to a pro-ferroptotic role for MBOAT7 and AA-PI, with potential therapeutic implications, and reveals that MMD is an important regulator of cellular lipid metabolism.

Development and application of lipidomics for food research

Lipidomics is an emerging and promising omics derived from metabolomics to comprehensively analyze all of lipid molecules in biological matrices. The purpose of this chapter is to introduce the development and application of lipidomics for food research. First, three aspects of sample preparation are introduced: food sampling, lipid extraction, and transportation and storage. Second, five types of instruments for data acquisition are summarized: direct infusion-mass spectrometry (MS), chromatographic separation-MS, ion mobility-MS, MS imaging, and nuclear magnetic resonance spectroscopy. Third, data acquisition and analysis software are described for the lipidomics software development. Fourth, the application of lipidomics for food research is discussed such as food origin and adulteration analysis, food processing research, food preservation research, and food nutrition and health research. All the contents suggest that lipidomics is a powerful tool for food research based on its ability of lipid component profile analysis.

Lipid droplets and peroxisomes are co-regulated to drive lifespan extension in response to mono-unsaturated fatty acids

Dietary mono-unsaturated fatty acids (MUFAs) are linked to longevity in several species. But the mechanisms by which MUFAs extend lifespan remain unclear. Here we show that an organelle network involving lipid droplets and peroxisomes is critical for MUFA-induced longevity in Caenorhabditis elegans. MUFAs upregulate the number of lipid droplets in fat storage tissues. Increased lipid droplet number is necessary for MUFA-induced longevity and predicts remaining lifespan. Lipidomics datasets reveal that MUFAs also modify the ratio of membrane lipids and ether lipids-a signature associated with decreased lipid oxidation. In agreement with this, MUFAs decrease lipid oxidation in middle-aged individuals. Intriguingly, MUFAs upregulate not only lipid droplet number but also peroxisome number. A targeted screen identifies genes involved in the co-regulation of lipid droplets and peroxisomes, and reveals that induction of both organelles is optimal for longevity. Our study uncovers an organelle network involved in lipid homeostasis and lifespan regulation, opening new avenues for interventions to delay aging.

Parental factors that impact the ecology of human mammary development, milk secretion, and milk composition-a report from "Breastmilk Ecology: Genesis of Infant Nutrition (BEGIN)" Working Group 1

The goal of Working Group 1 in the Breastmilk Ecology: Genesis of Infant Nutrition (BEGIN) Project was to outline factors influencing biological processes governing human milk secretion and to evaluate our current knowledge of these processes. Many factors regulate mammary gland development in utero, during puberty, in pregnancy, through secretory activation, and at weaning. These factors include breast anatomy, breast vasculature, diet, and the lactating parent's hormonal milieu including estrogen, progesterone, placental lactogen, cortisol, prolactin, and growth hormone. We examine the effects of time of day and postpartum interval on milk secretion, along with the role and mechanisms of lactating parent-infant interactions on milk secretion and bonding, with particular attention to the actions of oxytocin on the mammary gland and the pleasure systems in the brain. We then consider the potential effects of clinical conditions including infection, pre-eclampsia, preterm birth, cardiovascular health, inflammatory states, mastitis, and particularly, gestational diabetes and obesity. Although we know a great deal about the transporter systems by which zinc and calcium pass from the blood stream into milk, the interactions and cellular localization of transporters that carry substrates such as glucose, amino acids, copper, and the many other trace metals present in human milk across plasma and intracellular membranes require more research. We pose the question of how cultured mammary alveolar cells and animal models can help answer lingering questions about the mechanisms and regulation of human milk secretion. We raise questions about the role of the lactating parent and the infant microbiome and the immune system during breast development, secretion of immune molecules into milk, and protection of the breast from pathogens. Finally, we consider the effect of medications, recreational and illicit drugs, pesticides, and endocrine-disrupting chemicals on milk secretion and composition, emphasizing that this area needs much more research attention.

Comprehensive lipidome of human plasma using minimal sample manipulation by liquid chromatography coupled with mass spectrometry

RATIONALE

The present work shows comprehensive chromatographic methods and MS conditions that have been developed based on the chemical properties of each lipid subclass to detect low-abundance molecular species. This study shows that the developed methods can detect low- and/or very-low-abundant lipids like phosphatidic acid (PA) in the glycerophospholipid (GP) method; dihydroceramide (dhCer) and dihydrosphingosine/sphinganine (dhSPB) in the sphingolipid (SP) method; and lysophosphatidic acid (LPA), LPI, LPG and sphingosine-1-phosphate (SPBP) in the lysolipid method.

METHODS

An optimised method for the extraction of lysolipids in plasma is used in addition to Folch extraction. Then, four chromatographic methods coupled with mass spectrometry using targeted and untargeted approaches are described here. Three of the methods use a tertiary pumping system to enable the inclusion of a gradient for analyte separation (pumps A and B) and an isocratic wash (pump C). This wash solution elutes interfering compounds that could cause background signal in the subsequent injections, reducing column lifetime.

RESULTS

Semi-quantitative values for 37 lipid subclasses are reported for a plasma sample (NIST SRM 1950). Furthermore, the methods presented here enabled the identification of 338 different lipid molecular species for GPs (mono- and diacyl-phospholipds), SPs, sterols and glycerolipids. The methods have been validated, and the reproducibility is presented here.

CONCLUSIONS

The comprehensive analysis of the lipidome addressed here of glycerolipids, GPs, sterols and SPs is in good agreement with previously reported results, in the NIST SRM 1950 sample, by other laboratories. Ten lipid subclasses LPS, LPI, alkyl-lysophosphatidic acid/alkenyl-lysophosphatidic acid, alkyl-lysophosphatidylethanolamine/alkenyl-lysophosphatidylethanolamine, dhCer (d18:0), SPB (d18:1), dhSPB (d18:0) and SPBP (d18:2) have been detected using this comprehensive method and are uniquely reported here.

Omics Profiles of Non-GM Tubers from Transgrafted Potato with a GM Scion

"Transgrafting" is a grafting procedure whereby a transgenic plant body is grafted to a non-transgenic plant body. It is a novel plant breeding technology that allows non-transgenic plants to obtain benefits usually conferred to transgenic plants. Many plants regulate flowering by perceiving the day-length cycle via expression of FLOWERING LOCUS T (FT) in the leaves. The resulting FT protein is translocated to the shoot apical meristem via the phloem. In potato plants, FT is involved in the promotion of tuber formation. Here we investigated the effects of a genetically modified (GM) scion on the edible parts of the non-GM rootstock by using potato plants transformed with StSP6A, a novel potato homolog of the FT gene. Scions prepared from GM or control (wild-type) potato plants were grafted to non-GM potato rootstocks; these were designated as TN and NN plants, respectively. After tuber harvest, we observed no significant differences in potato yield between TN and NN plants. Transcriptomic analysis revealed that only one gene-with unknown function-was differentially expressed between TN and NN plants. Subsequent proteomic analysis indicated that several members of protease inhibitor families, known as anti-nutritional factors in potato, were slightly more abundant in TN plants. Metabolomic analysis revealed a slight increase in metabolite abundance in NN plants, but we observed no difference in the accumulation of steroid glycoalkaloids, toxic metabolites found in potato. Finally, we found that TN and NN plants did not differ in nutrient composition. Taken together, these results indicate that FT expression in scions had a limited effect on the metabolism of non-transgenic potato tubers.

Identification of a Fatty Acid for Diagnosing Non-Alcoholic Steatohepatitis in Patients with Severe Obesity Undergoing Metabolic Surgery

The prevalence of nonalcoholic steatohepatitis (NASH) in severely obese Japanese patients is extremely high. However, there are currently no methods other than liver biopsy to assess hepatic steatosis and fibrosis. The purpose of this study was to comprehensively analyze changes in fatty acid (FA) and serum-free fatty acid (FFA) metabolism in severely obese Japanese patients to determine whether these could be surrogate markers. In this study, we enrolled 20 Japanese patients who underwent laparoscopic sleeve gastrectomy (LSG) for severe obesity and intraoperative liver biopsy. Serum FFAs were analyzed with liquid chromatography-mass spectrometry, and FAs in liver tissue were assessed using matrix-assisted laser desorption/ionization-imaging mass spectrometry to determine FAs that may be indicative of a positive NASH diagnosis. All patients showed significant weight loss and metabolic improvement following LSG. Regarding weight loss and metabolic improvement indices, 23 FFAs showed significant correlations with the baseline data. Narrowing down the phospholipids to commonly detected FAs detected in liver tissue, PC(18:1e_20:4) was significantly changed in the NASH group, suggesting that it could be used as a surrogate marker for NASH diagnosis. The results suggest that specific postoperative changes in blood phospholipids could be used as surrogate markers for NASH treatment.

Deficiency of the frontotemporal dementia gene GRN results in gangliosidosis

Haploinsufficiency of GRN causes frontotemporal dementia (FTD). The GRN locus produces progranulin (PGRN), which is cleaved to lysosomal granulin polypeptides. The function of lysosomal granulins and why their absence causes neurodegeneration are unclear. Here we discover that PGRN-deficient human cells and murine brains, as well as human frontal lobes from GRN-mutation FTD patients have increased levels of gangliosides, glycosphingolipids that contain sialic acid. In these cells and tissues, levels of lysosomal enzymes that catabolize gangliosides were normal, but levels of bis(monoacylglycero)phosphates (BMP), lipids required for ganglioside catabolism, were reduced with PGRN deficiency. Our findings indicate that granulins are required to maintain BMP levels to support ganglioside catabolism, and that PGRN deficiency in lysosomes leads to gangliosidosis. Lysosomal ganglioside accumulation may contribute to neuroinflammation and neurodegeneration susceptibility observed in FTD due to PGRN deficiency and other neurodegenerative diseases.

Rapid Acid/Base Switching in Flow Injection Analysis and Isocratic Elution Liquid Chromatography with Mass Spectrometric Detection for Improved Sensitivity

Ion signals in electrospray ionization (ESI) mass spectrometry (MS) are affected by addition of acid or base. Acids or bases are typically added to samples to enhance detection of analytes in positive- or negative-ion mode, respectively. To carry out simultaneous monitoring of analytes with different ionogenic moieties by ESI-MS, a rapid acid/base switching system was developed. The system was further coupled with flow injection analysis (FIA) and liquid chromatography (LC) MS. The two variants enable detection of separated analytes immediately after alternating addition of acid and base. The methods were tested using a set of phospholipids (PLs) as analytes. The rapid acid/base switching enhanced signals of some of the PL analytes in both ion modes of MS. Both FIA-MS and LC-MS with acid/base switching show signal enhancements (∼1.3-23.2 times) of some analyte signals when compared with analysis conducted without acid/base switching. The proposed methods are suitable for simultaneous analysis of cationic and anionic analytes. The FIA-MS and LC-MS methods with acid/base switching were also applied in analysis of lipid extract from real samples (sausage and porcine liver). However, the FIA-MS results were affected by ionization competition and isobaric interference due to the complexity of the sample matrix and diversity of PL species. In contrast, the LC-MS mode provides adequate selectivity to observe signal enhancement for specific analyte ions. Overall, alternating addition of acid and base immediately before the ESI source can improve analytical performance without the need to carry out separate analyses targeting different types of analytes.

CLN3 is required for the clearance of glycerophosphodiesters from lysosomes

Lysosomes have many roles, including degrading macromolecules and signalling to the nucleus1. Lysosomal dysfunction occurs in various human conditions, such as common neurodegenerative diseases and monogenic lysosomal storage disorders (LSDs)2-4. For most LSDs, the causal genes have been identified but, in some, the function of the implicated gene is unknown, in part because lysosomes occupy a small fraction of the cellular volume so that changes in lysosomal contents are difficult to detect. Here we develop the LysoTag mouse for the tissue-specific isolation of intact lysosomes that are compatible with the multimodal profiling of their contents. We used the LysoTag mouse to study CLN3, a lysosomal transmembrane protein with an unknown function. In children, the loss of CLN3 causes juvenile neuronal ceroid lipofuscinosis (Batten disease), a lethal neurodegenerative LSD. Untargeted metabolite profiling of lysosomes from the brains of mice lacking CLN3 revealed a massive accumulation of glycerophosphodiesters (GPDs)-the end products of glycerophospholipid catabolism. GPDs also accumulate in the lysosomes of CLN3-deficient cultured cells and we show that CLN3 is required for their lysosomal egress. Loss of CLN3 also disrupts glycerophospholipid catabolism in the lysosome. Finally, we found elevated levels of glycerophosphoinositol in the cerebrospinal fluid of patients with Batten disease, suggesting the potential use of glycerophosphoinositol as a disease biomarker. Our results show that CLN3 is required for the lysosomal clearance of GPDs and reveal Batten disease as a neurodegenerative LSD with a defect in glycerophospholipid metabolism.

Gut microbiota production of trimethyl-5-aminovaleric acid reduces fatty acid oxidation and accelerates cardiac hypertrophy

Numerous studies found intestinal microbiota alterations which are thought to affect the development of various diseases through the production of gut-derived metabolites. However, the specific metabolites and their pathophysiological contribution to cardiac hypertrophy or heart failure progression still remain unclear. N,N,N-trimethyl-5-aminovaleric acid (TMAVA), derived from trimethyllysine through the gut microbiota, was elevated with gradually increased risk of cardiac mortality and transplantation in a prospective heart failure cohort (n = 1647). TMAVA treatment aggravated cardiac hypertrophy and dysfunction in high-fat diet-fed mice. Decreased fatty acid oxidation (FAO) is a hallmark of metabolic reprogramming in the diseased heart and contributes to impaired myocardial energetics and contractile dysfunction. Proteomics uncovered that TMAVA disturbed cardiac energy metabolism, leading to inhibition of FAO and myocardial lipid accumulation. TMAVA treatment altered mitochondrial ultrastructure, respiration and FAO and inhibited carnitine metabolism. Mice with γ-butyrobetaine hydroxylase (BBOX) deficiency displayed a similar cardiac hypertrophy phenotype, indicating that TMAVA functions through BBOX. Finally, exogenous carnitine supplementation reversed TMAVA induced cardiac hypertrophy. These data suggest that the gut microbiota-derived TMAVA is a key determinant for the development of cardiac hypertrophy through inhibition of carnitine synthesis and subsequent FAO.

Intestinal microbiota alterations may affect heart function through the production of gut-derived metabolites. Here the authors found that gut microbiota-derived TMAVA is a key determinant for the development of cardiac hypertrophy through inhibition of carnitine synthesis and subsequent fatty acid oxidation.

Transcriptome and metabolome analyses revealed that narrowband 280 and 310 nm UV-B induce distinctive responses in Arabidopsis

In plants, the UV-B photoreceptor UV RESISTANCE LOCUS8 (UVR8) perceives UV-B and induces UV-B responses. UVR8 absorbs a range of UV-B (260–335 nm). However, the responsiveness of plants to each UV-B wavelength has not been intensively studied so far. Here, we performed transcriptome and metabolome analyses of Arabidopsis using UV light emitting diodes (LEDs) with peak wavelengths of 280 and 310 nm to investigate the differences in the wavelength-specific UV-B responses. Irradiation with both UV-LEDs induced gene expression of the transcription factor ELONGATED HYPOCOTYL 5 (HY5), which has a central role in the UVR8 signaling pathway. However, the overall transcriptomic and metabolic responses to 280 and 310 nm UV-LED irradiation were different. Most of the known UV-B-responsive genes, such as defense-related genes, responded only to 280 nm UV-LED irradiation. Lipids, polyamines and organic acids were the metabolites most affected by 280 nm UV-LED irradiation, whereas the effect of 310 nm UV-LED irradiation on the metabolome was considerably less. Enzymatic genes involved in the phenylpropanoid pathway upstream in anthocyanin biosynthesis were up-regulated only by 280 nm UV-LED irradiation. These results revealed that the responsivenesses of Arabidopsis to 280 and 310 nm UV-B were significantly different, suggesting that UV-B signaling is mediated by more complex pathways than the current model.

16pdel lipid changes in iPSC-derived neurons and function of FAM57B in lipid metabolism and synaptogenesis

The complex 16p11.2 deletion syndrome (16pdel) is accompanied by neurological disorders, including epilepsy, autism spectrum disorder, and intellectual disability. We demonstrated that 16pdel iPSC differentiated neurons from affected people show augmented local field potential activity and altered ceramide-related lipid species relative to unaffected. FAM57B, a poorly characterized gene in the 16p11.2 interval, has emerged as a candidate tied to symptomatology. We found that FAM57B modulates ceramide synthase (CerS) activity, but is not a CerS per se. In FAM57B mutant human neuronal cells and zebrafish brain, composition and levels of sphingolipids and glycerolipids associated with cellular membranes are disrupted. Consistently, we observed aberrant plasma membrane architecture and synaptic protein mislocalization, which were accompanied by depressed brain and behavioral activity. Together, these results suggest that haploinsufficiency of FAM57B contributes to changes in neuronal activity and function in 16pdel syndrome through a crucial role for the gene in lipid metabolism.

Advances in Analyzing the Breast Cancer Lipidome and Its Relevance to Disease Progression and Treatment

Abnormal lipid metabolism is common in breast cancer with the three main subtypes, hormone receptor (HR) positive, human epidermal growth factor 2 (HER2) positive, and triple negative, showing common and distinct lipid dependencies. A growing body of studies identify altered lipid metabolism as impacting breast cancer cell growth and survival, plasticity, drug resistance, and metastasis. Lipids are a class of nonpolar or polar (amphipathic) biomolecules that can be produced in cells via de novo synthesis or acquired from the microenvironment. The three main functions of cellular lipids are as essential components of membranes, signaling molecules, and nutrient storage. The use of mass spectrometry-based lipidomics to analyze the global cellular lipidome has become more prevalent in breast cancer research. In this review, we discuss current lipidomic methodologies, highlight recent breast cancer lipidomic studies and how these findings connect to disease progression and therapeutic development, and the potential use of lipidomics as a diagnostic tool in breast cancer. A better understanding of the breast cancer lipidome and how it changes during drug resistance and tumor progression will allow informed development of diagnostics and novel targeted therapies.

The Hitchhiker's Guide to Untargeted Lipidomics Analysis: Practical Guidelines

Lipidomics is a newly emerged discipline involving the identification and quantification of thousands of lipids. As a part of the omics field, lipidomics has shown rapid growth both in the number of studies and in the size of lipidome datasets, thus, requiring specific and efficient data analysis approaches. This paper aims to provide guidelines for analyzing and interpreting lipidome data obtained using untargeted methods that rely on liquid chromatography coupled with mass spectrometry (LC-MS) to detect and measure the intensities of lipid compounds. We present a state-of-the-art untargeted LC-MS workflow for lipidomics, from study design to annotation of lipid features, focusing on practical, rather than theoretical, approaches for data analysis, and we outline possible applications of untargeted lipidomics for biological studies. We provide a detailed R notebook designed specifically for untargeted lipidome LC-MS data analysis, which is based on xcms software.

Retention dependences support highly confident identification of lipid species in human plasma by reversed-phase UHPLC/MS

Reversed-phase ultrahigh-performance liquid chromatography-mass spectrometry (RP-UHPLC/MS) method was developed with the aim to unambiguously identify a large number of lipid species from multiple lipid classes in human plasma. The optimized RP-UHPLC/MS method employed the C18 column with sub-2-μm particles with the total run time of 25 min. The chromatographic resolution was investigated with 42 standards from 18 lipid classes. The UHPLC system was coupled to high-resolution quadrupole-time-of-flight (QTOF) mass analyzer using electrospray ionization (ESI) measuring full-scan and tandem mass spectra (MS/MS) in positive- and negative-ion modes with high mass accuracy. Our identification approach was based on m/z values measured with mass accuracy within 5 ppm tolerance in the full-scan mode, characteristic fragment ions in MS/MS, and regularity in chromatographic retention dependences for individual lipid species, which provides the highest level of confidence for reported identifications of lipid species including regioisomeric and other isobaric forms. The graphs of dependences of retention times on the carbon number or on the number of double bond(s) in fatty acyl chains were constructed to support the identification of lipid species in homologous lipid series. Our list of identified lipid species is also compared with previous publications investigating human blood samples by various MS-based approaches. In total, we have reported more than 500 lipid species representing 26 polar and nonpolar lipid classes detected in NIST Standard reference material 1950 human plasma.

An improved strategy for analysis of lipid molecules utilising a reversed phase C30 UHPLC column and scheduled MS/MS acquisition

Measuring physiochemically diverse molecules (including lipids) which vary significantly in their concentrations poses a great analytical challenge. In untargeted lipidomics studies, reversed phase chromatography coupled with data-dependent MS/MS acquisition (DDA) is frequently applied. The optimal assay should deliver a high number of detected compounds with associated fragmentation data. In this work, we introduce novel 30 and 50 min UHPLC assays utilising lipid separation on a C30 stationary phase with a modified DDA strategy using smaller precursor m/z ranges scheduled for different lipid classes across the retention time range (defined as scheduled MS/MS). To evaluate the efficiency of the novel assays, mammalian tissue extracts (lamb liver, kidney and heart) were analysed and data were compared to a 15 min reversed phase C18 assay with multiple traditional DDA injections. The 30 min C30 assay detected double the number of detected compounds compared to the 15 min C18 assay. Applying the scheduled MS/MS DDA strategy with a single injection, a similar number of annotated lipids were reported compared to the traditional DDA strategy applied with five replicate injections on a C18 column. A longer 50 min C30 chromatographic assay did not result in an expected improvement in the chromatographic separation of overlapping isomer peaks compared to the 30 min method but did result in loss of accuracy of peak picking algorithms. We recommend the 30 min C30 assay with scheduled MS/MS acquisition as an efficient tool to analyse complex biological matrices and to annotate lipid species based on MS/MS data.

Lipid profiles and differential lipids in serum related to severity of community-acquired pneumonia: A pilot study

This study aimed to characterize the lipidomic responses to community-acquired pneumonia (CAP) and provide new insight into the underlying mechanisms of pathogenesis and potential avenues for diagnostic and therapeutic treatments. This study was performed from January 2017 to October 2018. Lipidomic profiles were generated using ultra high-performance liquid chromatography with tandem mass spectrometry (UHPLC-MS/MS) platform. Spearman's rank correlation test and multiple linear regression analysis were applied to explore the correlation between changes in the relative abundance of lipids and clinical parameters. Kaplan-Meier methods were used to build 30-day survival curves. From the UHPLC-MS/MS results, a total of 509 and 195 lipid species were detected in the positive and negative ionization mode respectively. Positive ionization covered six lipid classes (glycerol-phospholipids, glycerolipids, sphingolipids, sterol-lipids, prenol-lipids, and fatty acid), whilst negative ionization covered three (glycerol-phospholipids, sphingolipids, fatty acid). Four lipids were selected as targets: PC (16:0_18:1), PC (18:2_20:4), PC (36:4), and PC (38:6). The relative increase of the areas under the curves for all four lipids were superior to the pneumonia severity index and CURB-65 (confusion, urea, respiratory rate, blood pressure, and age ≥65 years old) for discriminating severe CAP from CAP. Decreasing relative levels of PC (18:2_20:4), PC (38:6), and PC (36:4) were negatively related to fraction of inspiration O2; Changes in the relative abundance of PC (16:0_18:1) and PC (18:2_20:4) had significantly linear relationship with procalcitonin. Patients with an elevated level of PC (16:0_18:1) had significantly longer duration of hospital stays. As the relative abundance of PC (18:2_20:4), PC (36:4), and PC (38:6) decreased, the length of hospitalization days and 30-day mortality rate increased significantly (all log-rank p<0.05). Therefore, using the UHPLC-MS/MS platform's serum lipidomic approach can help reveal changes in lipid abundance during CAP and establish lipid profiles related to disease severity.

Metabolic determinants of cancer cell sensitivity to canonical ferroptosis inducers

Cancer cells rewire their metabolism and rely on endogenous antioxidants to mitigate lethal oxidative damage to lipids. However, the metabolic processes that modulate the response to lipid peroxidation are poorly defined. Using genetic screens, we compared metabolic genes essential for proliferation upon inhibition of cystine uptake or glutathione peroxidase-4 (GPX4). Interestingly, very few genes were commonly required under both conditions, suggesting that cystine limitation and GPX4 inhibition may impair proliferation via distinct mechanisms. Our screens also identify tetrahydrobiopterin (BH4) biosynthesis as an essential metabolic pathway upon GPX4 inhibition. Mechanistically, BH4 is a potent radical-trapping antioxidant that protects lipid membranes from autoxidation, alone and in synergy with vitamin E. Dihydrofolate reductase catalyzes the regeneration of BH4, and its inhibition by methotrexate synergizes with GPX4 inhibition. Altogether, our work identifies the mechanism by which BH4 acts as an endogenous antioxidant and provides a compendium of metabolic modifiers of lipid peroxidation.

Uncovering the complexity of the yeast lipidome by means of nLC/NSI-MS/MS

Saccharomyces cerevisiae is a eukaryotic model organism widely used for the investigation of fundamental cellular processes and disease mechanisms. Consequently, the lipid landscape of yeast has been extensively investigated and up to this day the lipidome is considered as rather basic. Here, we used a nLC/NSI-MS/MS method combined with a semi-autonomous data analysis workflow for an in-depth evaluation of the steady state yeast lipidome. We identified close to 900 lipid species across 26 lipid classes, including glycerophospholipids, sphingolipids, glycerolipids and sterol lipids. Most lipid classes are dominated by few high abundant species, with a multitude of lower abundant lipids contributing to the overall complexity of the yeast lipidome. Contrary to previously published datasets, odd-chain and diunsaturated fatty acyl moieties were found to be commonly incorporated in multiple lipid classes. Careful data evaluation furthermore revealed the presence of putative new lipid species such as MMPSs (mono-methylated phosphatidylserine), not yet described in yeast. Overall, our analysis achieved a more than 4-fold increase in lipid identifications compared to previous approaches, underscoring the use of nLC/NSI-MS/MS methods for the in-depth investigation of lipidomes.

Differential postprandial incorporation of 20:5n-3 and 22:6n-3 into individual plasma triacylglycerol and phosphatidylcholine molecular species in humans

The mechanisms by which digested fat is absorbed and transported in the circulation are well documented. However, it is uncertain whether the molecular species composition of dietary fats influences the molecular species composition of meal-derived lipids in blood. This may be important because enzymes that remove meal-derived fatty acids from the circulation exhibit differential activities towards individual lipid molecular species. To determine the effect of consuming oils with different molecular compositions on the incorporation of 20:5n-3 and 22:6n-3 into plasma lipid molecular species. Men and women (18-30 years) consumed standardised meals containing 20:5n-5 and 22:6n-3 (total 450 mg) provided by an oil from transgenic Camelina sativa (CSO) or a blended fish oil (BFO) which differed in the composition of 20:5n-3 and 22:6n-3 - containing molecular species. Blood was collected during the subsequent 8 h. Samples were analysed by liquid chromatography-mass spectrometry. The molecular species composition of the test oils was distinct from the composition of plasma triacylglycerol (TG) or phosphatidylcholine (PC) molecular species at baseline and at 1.5 or 6 h after the meal. The rank order by concentration of both plasma PC and TG molecular species at baseline was maintained during the postprandial period. 20:5n-3 and 22:6n-3 were incorporated preferentially into plasma PC compared to plasma TG. Together these findings suggest that the composition of dietary lipids undergoes extensive rearrangement after absorption, such that plasma TG and PC maintain their molecular species composition, which may facilitate lipase activities in blood and/or influence lipoprotein structural stability and function.

Triphenyl phosphate modulated saturation of phospholipids: Induction of endoplasmic reticulum stress and inflammation

Although triphenyl phosphate (TPHP) has been reported to disrupt lipid metabolism, the effect of TPHP on lipid saturation remains unexplored. In this study, a lipidomic analysis demonstrated decreases in the levels of poly-unsaturated phosphatidylcholine (PC), phosphatidylethanolamine (PE), and phosphatidylserine (PS) in RAW264.7 murine macrophage cells exposed to 10 μM TPHP. The expression of the gene encoding lysophosphatidylcholine acyltransferase 3 (Lpcat3) was significantly downregulated by 0.76 ± 0.03 and 0.70 ± 0.08-fold in 10 and 20 μM TPHP exposure groups, relative to the control group. This finding explains the observed decrease in lipid saturation. Correspondingly, exposure to 10 and 20 μM TPHP induced endoplasmic reticulum (ER) stress and inflammatory responses, which have been linked to metabolic dysfunction such as insulin resistance and hypertriglyceridemia. Therefore, TPHP may pose a risk to human health by promoting metabolic diseases.

QSRR Automator: A Tool for Automating Retention Time Prediction in Lipidomics and Metabolomics

The use of retention time is often critical for the identification of compounds in metabolomic and lipidomic studies. Standards are frequently unavailable for the retention time measurement of many metabolites, thus the ability to predict retention time for these compounds is highly valuable. A number of studies have applied machine learning to predict retention times, but applying a published machine learning model to different lab conditions is difficult. This is due to variation between chromatographic equipment, methods, and columns used for analysis. Recreating a machine learning model is likewise difficult without a dedicated bioinformatician. Herein we present QSRR Automator, a software package to automate retention time prediction model creation and demonstrate its utility by testing data from multiple chromatography columns from previous publications and in-house work. Analysis of these data sets shows similar accuracy to published models, demonstrating the software's utility in metabolomic and lipidomic studies.

Comprehensive Characterization of Bovine Milk Lipids: Triglycerides

A comprehensive survey on triglycerides (TAGs) of bovine milk was conducted by a combination of exhaustive liquid chromatography (LC) separation, high-resolution mass spectrometry (MS) detection, and automated lipid molecular feature extraction. A total of 220 groups (a series of species having the same chemical formula and mass) and 3454 molecular species of TAGs were identified based on the accurate mass of the parent ion as well as MS2 information. Sixty-five different fatty acids (FAs) were found across these TAG species; C4:0, C6:0, C8:0, C10:0, C12:0, C14:0, C16:0, C18:0, and C18:1 were the most frequent FAs, whereas C11:3, C11:4, C27:0, C27:1, C28:0, and C28:1 were rare FAs in TAG molecules. The number of species identified represents only a small portion of total TAG molecules that can be theoretically synthesized from 65 FAs. Each TAG group contains on average 15-16 isomeric species (species with different FA composition), but positional isomers do not seem to be widespread. As the isomeric species cannot be completely resolved chromatographically, quantification of TAG was conducted at the group level. The most abundant TAG groups in bovine milk include TAG 34:0, TAG 36:0, TAG 38:1, TAG 38:0, and TAG 40:1. This study provides the most comprehensive milk TAG inventory so far that can be used as a reference for studying milk lipids.

Human GDPD3 overexpression promotes liver steatosis by increasing lysophosphatidic acid production and fatty acid uptake

The glycerol phosphate pathway produces more than 90% of the liver triacylglycerol (TAG). LysoPA, an intermediate in this pathway, is produced by glycerol-3-phosphate acyltransferase. Glycerophosphodiester phosphodiesterase domain containing 3 (GDPD3), whose gene was recently cloned, contains lysophospholipase D activity, which produces LysoPA from lysophospholipids. Whether human GDPD3 plays a role in hepatic TAG homeostasis is unknown. We hypothesized that human GDPD3 increases LysoPA production and availability in the glycerol phosphate pathway, promoting TAG biosynthesis. To test our hypothesis, we infected C57BL/6J mice with adeno-associated virus encoding a hepatocyte-specific albumin promoter that drives GFP (control) or FLAG-tagged human GDPD3 overexpression and fed the mice chow or a Western diet to induce hepatosteatosis. Hepatic human GDPD3 overexpression induced LysoPA production and increased FA uptake and incorporation into TAG in mouse hepatocytes and livers, ultimately exacerbating Western diet-induced liver steatosis. Our results also showed that individuals with hepatic steatosis have increased GDPD3 mRNA levels compared with individuals without steatosis. Collectively, these findings indicate that upregulation of GDPD3 expression may play a key role in hepatic TAG accumulation and may represent a molecular target for managing hepatic steatosis.

Inhibition of sphingolipid synthesis improves outcomes and survival in GARP mutant wobbler mice, a model of motor neuron degeneration

Numerous mutations that impair retrograde membrane trafficking between endosomes and the Golgi apparatus lead to neurodegenerative diseases. For example, mutations in the endosomal retromer complex are implicated in Alzheimer's and Parkinson's diseases, and mutations of the Golgi-associated retrograde protein (GARP) complex cause progressive cerebello-cerebral atrophy type 2 (PCCA2). However, how these mutations cause neurodegeneration is unknown. GARP mutations in yeast, including one causing PCCA2, result in sphingolipid abnormalities and impaired cell growth that are corrected by treatment with myriocin, a sphingolipid synthesis inhibitor, suggesting that alterations in sphingolipid metabolism contribute to cell dysfunction and death. Here we tested this hypothesis in wobbler mice, a murine model with a homozygous partial loss-of-function mutation in Vps54 (GARP protein) that causes motor neuron disease. Cytotoxic sphingoid long-chain bases accumulated in embryonic fibroblasts and spinal cords from wobbler mice. Remarkably, chronic treatment of wobbler mice with myriocin markedly improved their wellness scores, grip strength, neuropathology, and survival. Proteomic analyses of wobbler fibroblasts revealed extensive missorting of lysosomal proteins, including sphingolipid catabolism enzymes, to the Golgi compartment, which may contribute to the sphingolipid abnormalities. Our findings establish that altered sphingolipid metabolism due to GARP mutations contributes to neurodegeneration and suggest that inhibiting sphingolipid synthesis might provide a useful strategy for treating these disorders.

Inter-Laboratory Comparison of Metabolite Measurements for Metabolomics Data Integration

BACKGROUND

One of the current problems in the field of metabolomics is the difficulty in integrating data collected using different equipment at different facilities, because many metabolomic methods have been developed independently and are unique to each laboratory.

METHODS

In this study, we examined whether different analytical methods among 12 different laboratories provided comparable relative quantification data for certain metabolites. Identical samples extracted from two cell lines (HT-29 and AsPc-1) were distributed to each facility, and hydrophilic and hydrophobic metabolite analyses were performed using the daily routine protocols of each laboratory.

RESULTS

The results indicate that there was no difference in the relative quantitative data (HT-29/AsPc-1) for about half of the measured metabolites among the laboratories and assay methods. Data review also revealed that errors in relative quantification were derived from issues such as erroneous peak identification, insufficient peak separation, a difference in detection sensitivity, derivatization reactions, and extraction solvent interference.

CONCLUSION

The results indicated that relative quantification data obtained at different facilities and at different times would be integrated and compared by using a reference materials shared for data normalization.

Engineering the stereoisomeric structure of seed oil to mimic human milk fat

Human milk fat substitute (HMFS) is a class of structured lipid that is widely used as an ingredient in infant formulas. Like human milk fat, HMFS is characterized by enrichment of palmitoyl (C16:0) groups specifically at the middle (sn-2 or β) position on the glycerol backbone, and there is evidence that triacylglycerol (TAG) with this unusual stereoisomeric structure provides nutritional benefits. HMFS is currently made by in vitro enzyme-based catalysis because there is no appropriate biological alternative to human milk fat. Most of the fat currently used in infant formulas is obtained from plants, which exclude C16:0 from the middle position. In this study, we have modified the metabolic pathway for TAG biosynthesis in the model oilseed Arabidopsis thaliana to increase the percentage of C16:0 at the middle (vs. outer) positions by more than 20-fold (i.e., from ∼3% in wild type to >70% in our final iteration). This level of C16:0 enrichment is comparable to human milk fat. We achieved this by relocating the C16:0-specific chloroplast isoform of the enzyme lysophosphatidic acid acyltransferase (LPAT) to the endoplasmic reticulum so that it functions within the cytosolic glycerolipid biosynthetic pathway to esterify C16:0 to the middle position. We then suppressed endogenous LPAT activity to relieve competition and knocked out phosphatidylcholine:diacylglycerol cholinephosphotransferase activity to promote the flux of newly made diacylglycerol directly into TAG. Applying this technology to oilseed crops might provide a source of HMFS for infant formula.

Evaluation of the Performance of Lipidyzer Platform and Its Application in the Lipidomics Analysis in Mouse Heart and Liver

Lipids play important roles in cell signaling, energy storage, and as major structural components of cell membranes. To date, little work has been conducted to show the extent of tissue specificity of lipid compositions. Here, the recently acquired Lipidyzer platform was employed in this pilot study: (i) to assess the performance of the Lipidyzer platform, (ii) to explore lipid profiles in liver and cardiac tissue in mice, (iii) to examine sex-specific differences in lipids in the liver tissue, and (iv) to evaluate biological variances in lipidomes present in animals. In total, 787 lipid species from 13 lipid classes were measured in the liver and heart. Lipidomics data from the Lipidyzer platform were very reproducible with the coefficient of variations of the quality control (QC) samples, ∼10%. The total concentration of the cholesterol esters (CE) lipid class, and specifically CE(16:1) and CE(18:1) species, showed sex differences in the liver. Cardiac tissue had higher levels of phospholipids containing docosahexaenoic acid, which could be related to heart health status and function. Our results demonstrate the usefulness of the Lipidyzer platform in identifying differences in lipid profile at the tissue level and between male and female mice in specific tissues.

Accelerating Lipidomic Method Development through in Silico Simulation

Judicious selection of mass spectrometry (MS) acquisition parameters is essential for effectively profiling the broad diversity and dynamic range of biomolecules. Typically, acquisition parameters are individually optimized to maximally characterize analytes from each new sample matrix. This time-consuming process often ignores the synergistic relationship between MS method parameters, producing suboptimal results. Here we detail the creation of an algorithm which accurately simulates LC-MS/MS lipidomic data acquisition performance for a benchtop quadrupole-Orbitrap MS system. By coupling this simulation tool with a genetic algorithm for constrained parameter optimization, we demonstrate the efficient identification of LC-MS/MS method parameter sets individually suited for specific sample matrices. Finally, we utilize the in silico simulation to examine how continued developments in MS acquisition speed and sensitivity will further increase the power of MS lipidomics as a vital tool for impactful biochemical analysis.

Dual Polarity Ion Confinement and Mobility Separations

Here, we present simulations and describe the initial implementation of a device capable of performing simultaneous ion mobility (IM) separations of positive and negative ions based upon the structures for lossless ion manipulations (SLIM). To achieve dual polarity ion confinement, the DC fields used for lateral confinement in previous SLIM were replaced with RF fields. Concurrent ion transport and mobility separation in the SLIM device are shown possible due to the nature of the traveling wave (TW) voltage profile which has potential minima at opposite sides of the wave for each ion polarity. We explored the potential for performing simultaneous IM separations of cations and anions over the same SLIM path and the impacts on the achievable IM resolution and resolving power. Initial results suggest comparable IM performance with previous single-polarity SLIM separations can be achieved. We also used ion trajectory simulations to investigate the capability to manipulate the spatial distributions of ion populations based on their polarities by biasing the RF fields and TW potentials on each SLIM surface so as to limit the interactions between opposite polarity ions. Graphical Abstract.

Current Progress of Lipid Analysis in Metabolic Diseases by Mass Spectrometry Methods

BACKGROUND

Obesity, insulin resistance, diabetes, and metabolic syndrome are associated with lipid alterations, and they affect the risk of long-term cardiovascular disease. A reliable analytical instrument to detect changes in the composition or structures of lipids and the tools allowing to connect changes in a specific group of lipids with a specific disease and its progress, is constantly lacking. Lipidomics is a new field of medicine based on the research and identification of lipids and lipid metabolites present in human organism. The primary aim of lipidomics is to search for new biomarkers of different diseases, mainly civilization diseases.

OBJECTIVE

We aimed to review studies reporting the application of mass spectrometry for lipid analysis in metabolic diseases.

METHOD

Following an extensive search of peer-reviewed articles on the mass spectrometry analysis of lipids the literature has been discussed in this review article.

RESULTS

The lipid group contains around 1.7 million species; they are totally different, in terms of the length of aliphatic chain, amount of rings, additional functional groups. Some of them are so complex that their complex analyses are a challenge for analysts. Their qualitative and quantitative analysis of is based mainly on mass spectrometry.

CONCLUSION

Mass spectrometry techniques are excellent tools for lipid profiling in complex biological samples and the combination with multivariate statistical analysis enables the identification of potential diagnostic biomarkers.

Probing the Global Cellular Responses to Lipotoxicity Caused by Saturated Fatty Acids

Excessive levels of saturated fatty acids are toxic to cells, although the basis for this lipotoxicity remains incompletely understood. Here, we analyzed the transcriptome, lipidome, and genetic interactions of human leukemia cells exposed to palmitate. Palmitate treatment increased saturated glycerolipids, accompanied by a transcriptional stress response, including upregulation of the endoplasmic reticulum (ER) stress response. A comprehensive genome-wide short hairpin RNA (shRNA) screen identified >350 genes modulating lipotoxicity. Among previously unknown genetic modifiers of lipotoxicity, depletion of RNF213, a putative ubiquitin ligase mutated in Moyamoya vascular disease, protected cells from lipotoxicity. On a broader level, integration of our comprehensive datasets revealed that changes in di-saturated glycerolipids, but not other lipid classes, are central to lipotoxicity in this model. Consistent with this, inhibition of ER-localized glycerol-3-phosphate acyltransferase activity protected from all aspects of lipotoxicity. Identification of genes modulating the response to saturated fatty acids may reveal novel therapeutic strategies for treating metabolic diseases linked to lipotoxicity.

CHP1 Regulates Compartmentalized Glycerolipid Synthesis by Activating GPAT4

Cells require a constant supply of fatty acids to survive and proliferate. Fatty acids incorporate into membrane and storage glycerolipids through a series of endoplasmic reticulum (ER) enzymes, but how these enzymes are regulated is not well understood. Here, using a combination of CRISPR-based genetic screens and unbiased lipidomics, we identified calcineurin B homologous protein 1 (CHP1) as a major regulator of ER glycerolipid synthesis. Loss of CHP1 severely reduces fatty acid incorporation and storage in mammalian cells and invertebrates. Mechanistically, CHP1 binds and activates GPAT4, which catalyzes the initial rate-limiting step in glycerolipid synthesis. GPAT4 activity requires CHP1 to be N-myristoylated, forming a key molecular interface between the two proteins. Interestingly, upon CHP1 loss, the peroxisomal enzyme, GNPAT, partially compensates for the loss of ER lipid synthesis, enabling cell proliferation. Thus, our work identifies a conserved regulator of glycerolipid metabolism and reveals plasticity in lipid synthesis of proliferating cells.

Squalene accumulation in cholesterol auxotrophic lymphomas prevents oxidative cell death

Cholesterol is essential for cells to grow and proliferate. Normal mammalian cells meet their need for cholesterol through its uptake or de novo synthesis¹, but the extent to which cancer cells rely on each of these pathways remains poorly understood. Here, using a competitive proliferation assay on a pooled collection of DNA-barcoded cell lines, we identify a subset of cancer cells that is auxotrophic for cholesterol and thus highly dependent on its uptake. Through metabolic gene expression analysis, we pinpoint the loss of squalene monooxygenase expression as a cause of cholesterol auxotrophy, particularly in ALK⁺ anaplastic large cell lymphoma (ALCL) cell lines and primary tumours. Squalene monooxygenase catalyses the oxidation of squalene to 2,3-oxidosqualene in the cholesterol synthesis pathway and its loss results in accumulation of the upstream metabolite squalene, which is normally undetectable. In ALK⁺ ALCLs, squalene alters the cellular lipid profile and protects cancer cells from ferroptotic cell death, providing a growth advantage under conditions of oxidative stress and in tumour xenografts. Finally, a CRISPR-based genetic screen identified cholesterol uptake by the low-density lipoprotein receptor as essential for the growth of ALCL cells in culture and as patient-derived xenografts. This work reveals that the cholesterol auxotrophy of ALCLs is a targetable liability and, more broadly, that systematic approaches can be used to identify nutrient dependencies unique to individual cancer types.

MITO-Tag Mice enable rapid isolation and multimodal profiling of mitochondria from specific cell types in vivo

Mitochondria are metabolic organelles that are essential for mammalian life, but the dynamics of mitochondrial metabolism within mammalian tissues in vivo remains incompletely understood. While whole-tissue metabolite profiling has been useful for studying metabolism in vivo, such an approach lacks resolution at the cellular and subcellular level. In vivo methods for interrogating organellar metabolites in specific cell types within mammalian tissues have been limited. To address this, we built on prior work in which we exploited a mitochondrially localized 3XHA epitope tag (MITO-Tag) for the fast isolation of mitochondria from cultured cells to generate MITO-Tag Mice. Affording spatiotemporal control over MITO-Tag expression, these transgenic animals enable the rapid, cell-type-specific immunoisolation of mitochondria from tissues, which we verified using a combination of proteomic and metabolomic approaches. Using MITO-Tag Mice and targeted and untargeted metabolite profiling, we identified changes during fasted and refed conditions in a diverse array of mitochondrial metabolites in hepatocytes and found metabolites that behaved differently at the mitochondrial versus whole-tissue level. MITO-Tag Mice should have utility for studying mitochondrial physiology, and our strategy should be generally applicable for studying other mammalian organelles in specific cell types in vivo.

Global analysis of osteosarcoma lipidomes reveal altered lipid profiles in metastatic versus nonmetastatic cells

Osteosarcoma (OS) is the most common form of primary bone cancer in humans. The early detection and subsequent control of metastasis has been challenging in OS. Lipids are important constituents of cells that maintain structural integrity that can be converted into lipid-signaling molecules and are reprogrammed in cancerous states. Here, we investigate the global lipidomic differences in metastatic (143B) and nonmetastatic (HOS) human OS cells as compared with normal fetal osteoblast cells (FOB) using lipidomics. We detect 15 distinct lipid classes in all three cell lines that included over 1,000 lipid species across various classes including phospholipids, sphingolipids and ceramides, glycolipids, and cholesterol. We identify a key class of lipids, diacylglycerols, which are overexpressed in metastatic OS cells as compared with their nonmetastatic or nontumorigenic counterparts. As a proof of concept, we show that blocking diacylglycerol synthesis reduces cellular viability and reduces cell migration in metastatic OS cells. Thus, the differentially regulated lipids identified in this study might aid in biomarker discovery, and the synthesis and metabolism of specific lipids could serve as future targets for therapeutic development.