Mass-spectrometry-based lipidomics

Evolutionary origin and gradual accumulation with plant evolution of the LACS family

BACKGROUND

LACS (long-chain acyl-CoA synthetase) genes are widespread in organisms and have multiple functions in plants, especially in lipid metabolism. However, the origin and evolutionary dynamics of the LACS gene family remain largely unknown.

RESULTS

Here, we identified 1785 LACS genes in the genomes of 166 diverse plant species and identified the clades (I, II, III, IV, V, VI) of six clades for the LACS gene family of green plants through phylogenetic analysis. Based on the evolutionary history of plant lineages, we found differences in the origins of different clades, with Clade IV originating from chlorophytes and representing the origin of LACS genes in green plants. The structural characteristics of different clades indicate that clade IV is relatively independent, while the relationships between clades (I, II, III) and clades (V, VI) are closer. Dispersed duplication (DSD) and transposed duplication (TRD) are the main forces driving the evolution of plant LACS genes. Network clustering analysis further grouped all LACS genes into six main clusters, with genes within each cluster showing significant co-linearity. Ka/Ks results suggest that LACS family genes underwent purifying selection during evolution. We analyzed the phylogenetic relationships and characteristics of six clades of the LACS gene family to explain the origin, evolutionary history, and phylogenetic relationships of different clades and proposed a hypothetical evolutionary model for the LACS family of genes in plants.

CONCLUSIONS

Our research provides genome-wide insights into the evolutionary history of the LACS gene family in green plants. These insights lay an important foundation for comprehensive functional characterization in future research.

Identification of multiple plasma lipids as diagnostic biomarkers of hypercholesterolemia and the underlying mechanisms based on pseudo-targeted lipidomics

RATIONALE

Hypercholesterolemia is an important risk factor for cardiovascular diseases and death. This study performed pseudo-targeted lipidomics to identify differentially expressed plasma lipids in hypercholesterolemia, to provide a scientific basis for the diagnosis and pathogenesis of hypercholesterolemia.

METHODS

Pseudo-targeted lipidomic analyses of plasma lipids from 20 patients with hypercholesterolemia and 20 normal control subjects were performed using liquid chromatography-mass spectrometry. Differentially expressed lipids were identified by principal component analysis and orthogonal partial least squares discriminant analysis. Receiver operating characteristic curves were used to identify differentially expressed lipids with high diagnostic value. The Kyoto Encyclopedia of Genes and Genomes pathway database was used to identify enriched metabolic pathways.

RESULTS

We identified 13 differentially expressed lipids in hypercholesterolemia using variable importance of projection > 1 and p < 0.05 as threshold parameters. The levels of eight sphingomyelins and cholesterol sulfate were higher and those of three triacylglycerols and lysophosphatidylcholine were reduced in hypercholesterolemia. Seven differentially expressed plasma lipids showed high diagnostic value for hypercholesterolemia. Functional enrichment analyses showed that pathways related to necroptosis, sphingolipid signaling, sphingolipid metabolism, and steroid hormone biosynthesis were enriched.

CONCLUSIONS

This pseudo-targeted lipidomics study demonstrated that multiple sphingomyelins and cholesterol sulfate were differentially expressed in the plasma of patients with hypercholesterolemia. We also identified seven plasma lipids, including six sphingomyelins and cholesterol sulfate, with high diagnostic value.

OsGELP77, a QTL for broad-spectrum disease resistance and yield in rice, encodes a GDSL-type lipase

Lipids and lipid metabolites have essential roles in plant-pathogen interactions. GDSL-type lipases are involved in lipid metabolism modulating lipid homeostasis. Some plant GDSLs modulate lipid metabolism altering hormone signal transduction to regulate host-defence immunity. Here, we functionally characterized a rice lipase, OsGELP77, promoting both immunity and yield. OsGELP77 expression was induced by pathogen infection and jasmonic acid (JA) treatment. Overexpression of OsGELP77 enhanced rice resistance to both bacterial and fungal pathogens, while loss-of-function of osgelp77 showed susceptibility. OsGELP77 localizes to endoplasmic reticulum and is a functional lipase hydrolysing universal lipid substrates. Lipidomics analyses demonstrate that OsGELP77 is crucial for lipid metabolism and lipid-derived JA homeostasis. Genetic analyses confirm that OsGELP77-modulated resistance depends on JA signal transduction. Moreover, population genetic analyses indicate that OsGELP77 expression level is positively correlated with rice resistance against pathogens. Three haplotypes were classified based on nucleotide polymorphisms in the OsGELP77 promoter where OsGELP77Hap3 is an elite haplotype. Three OsGELP77 haplotypes are differentially distributed in wild and cultivated rice, while OsGELP77Hap3 has been broadly pyramided for hybrid rice development. Furthermore, quantitative trait locus (QTL) mapping and resistance evaluation of the constructed near-isogenic line validated OsGELP77, a QTL for broad-spectrum disease resistance. In addition, OsGELP77-modulated lipid metabolism promotes JA accumulation facilitating grain yield. Notably, the hub defence regulator OsWRKY45 acts upstream of OsGELP77 by initiating the JA-dependent signalling to trigger immunity. Together, OsGELP77, a QTL contributing to immunity and yield, is a candidate for breeding broad-spectrum resistant and high-yielding rice.

Lipid Isobaric Mass Tagging for Enhanced Relative Quantification of Unsaturated sn-Positional Isomers

Changes in the levels of lipid sn-positional isomers are associated with perturbation of the physiological environment within the biological system. Consequently, knowing the concentrations of these lipids holds significant importance for unraveling their involvement in disease diagnosis and pathological mechanisms. However, existing methods for lipid quantification often fall short in accuracy due to the structural diversity and isomeric forms of lipids. To address this challenge, we have developed an aziridine-based isobaric tag labeling strategy that allows (i) differentiation and (ii) enhanced relative quantification of lipid sn-positional isomers from distinct samples in a single run. The methodology enabled by aziridination, isobaric tag labeling, and lithiation has been applied to various phospholipids, enabling the determination of the sn-positions of fatty acyl chains and enhanced relative quantification. The analysis of Escherichia coli lipid extracts demonstrated the enhanced determination of the concentration ratios of lipid isomers by measuring the intensity ratios of mass reporters released from sn-positional diagnostic ions. Moreover, we applied the method to the analysis of human colon cancer plasma. Intriguingly, 17 PC lipid sn-positional isomers were identified and quantified simultaneously, and among them, 7 showed significant abundance changes in the colon cancer plasma, which can be used as potential plasma markers for diagnosis of human colon cancer.

Lipid metabolism analysis in esophageal cancer and associated drug discovery

Esophageal cancer is an upper gastrointestinal malignancy with a bleak prognosis. It is still being explored in depth due to its complex molecular mechanisms of occurrence and development. Lipids play a crucial role in cells by participating in energy supply, biofilm formation, and signal transduction processes, and lipid metabolic reprogramming also constitutes a significant characteristic of malignant tumors. More and more studies have found esophageal cancer has obvious lipid metabolism abnormalities throughout its beginning, progress, and treatment resistance. The inhibition of tumor growth and the enhancement of antitumor therapy efficacy can be achieved through the regulation of lipid metabolism. Therefore, we reviewed and analyzed the research results and latest findings for lipid metabolism and associated analysis techniques in esophageal cancer, and comprehensively proved the value of lipid metabolic reprogramming in the evolution and treatment resistance of esophageal cancer, as well as its significance in exploring potential therapeutic targets and biomarkers.

Chemical tagging mass spectrometry: an approach for single-cell omics

Single-cell (SC) analysis offers new insights into the study of fundamental biological phenomena and cellular heterogeneity. The superior sensitivity, high throughput, and rich chemical information provided by mass spectrometry (MS) allow MS to emerge as a leading technology for molecular profiling of SC omics, including the SC metabolome, lipidome, and proteome. However, issues such as ionization suppression, low concentration, and huge span of dynamic concentrations of SC components lead to poor MS response for certain types of molecules. It is noted that chemical tagging/derivatization has been adopted in SCMS analysis, and this strategy has been proven an effective solution to circumvent these issues in SCMS analysis. Herein, we review the basic principle and general strategies of chemical tagging/derivatization in SCMS analysis, along with recent applications of chemical derivatization to single-cell metabolomics and multiplexed proteomics, as well as SCMS imaging. Furthermore, the challenges and opportunities for the improvement of chemical derivatization strategies in SCMS analysis are discussed.

Unraveling the Double Bond Position of Fatty Acids by GC-MS Using Electron Capture APCI and In-Source Fragmentation Patterns

The position of double bonds in unsaturated fatty acids is strongly connected to their biological effects, but their analytical characterization is still challenging. However, the ionization of unsaturated fatty acids by a GC-APCI leads to regiospecific in-source fragment ions, which can be used to identify the double bond position. The fragment ions are oxidized species that occur mostly at the double bond closest to the carboxylic acid group. This effect can be further promoted by using benzaldehyde as a gas-phase reactant. This allows the identification of the Δ-notation of the fatty acid, and based on additional information such as m/z and retention time, it is possible to annotate the corresponding fatty acid. The developed method also enables the quantification of fatty acids in one step with high selectivity and sensitivity. Moreover, rare fatty acids can be identified in suspected target approaches that are often not available as standards. This was demonstrated by analyzing fish oil samples that provide a complex mixture of highly unsaturated fatty acids and by identifying rare fatty acids such as hexadecatetraenoic acid (FA 16:4 Δ6).

Lipid Signatures and Inter-Cellular Heterogeneity of Naı̈ve and Lipopolysaccharide-Stimulated Human Microglia-like Cells

Microglia are non-neuronal cells, which reside in the central nervous system and are known to play an important role in health and disease. We investigated the lipidomic phenotypes of human naı̈ve and stimulated microglia-like cells by atmospheric-pressure scanning microprobe matrix-assisted laser desorption/ionization mass spectrometry imaging (AP-SMALDI MSI). With lateral resolutions between 5 and 1.5 μm pixel size, we were able to chart lipid compositions of individual cells, enabling differentiation of cell lines and stimulation conditions. This allowed us to reveal local lipid heterogeneities in naı̈ve and lipopolysaccharide (LPS)-stimulated cells. We were able to identify individual cells with elevated triglyceride (TG) levels and could show that the number of these TG-enriched cells increased with LPS stimulation as a hallmark for a proinflammatory phenotype. Additionally, the observed local abundance alterations of specific phosphatidylinositols (PIs) indicate a cell specific regulation of the PI metabolism.

Integrative metabolomics science in Alzheimer's disease: Relevance and future perspectives

Alzheimer's disease (AD) is determined by various pathophysiological mechanisms starting 10-25 years before the onset of clinical symptoms. As multiple functionally interconnected molecular/cellular pathways appear disrupted in AD, the exploitation of high-throughput unbiased omics sciences is critical to elucidating the precise pathogenesis of AD. Among different omics, metabolomics is a fast-growing discipline allowing for the simultaneous detection and quantification of hundreds/thousands of perturbed metabolites in tissues or biofluids, reproducing the fluctuations of multiple networks affected by a disease. Here, we seek to critically depict the main metabolomics methodologies with the aim of identifying new potential AD biomarkers and further elucidating AD pathophysiological mechanisms. From a systems biology perspective, as metabolic alterations can occur before the development of clinical signs, metabolomics - coupled with existing accessible biomarkers used for AD screening and diagnosis - can support early disease diagnosis and help develop individualized treatment plans. Presently, the majority of metabolomic analyses emphasized that lipid metabolism is the most consistently altered pathway in AD pathogenesis. The possibility that metabolomics may reveal crucial steps in AD pathogenesis is undermined by the difficulty in discriminating between the causal or epiphenomenal or compensatory nature of metabolic findings.

Integrated lipidomic and transcriptomic analysis reveals clarithromycin-induced alteration of glycerophospholipid metabolism in the cerebral cortex of mice

Clarithromycin (CLA) has been widely used in the treatment of bacterial infection. Research reveals the adverse effects on the central nervous system among patients receiving CLA treatment; whereas, a relevant underlying mechanism remains considerably unclear. According to our research, an integrated lipidomic and transcriptomic analysis was applied to explore the effect of CLA on neurobehavior. CLA treatment caused anxiety-like behaviors dose-dependently during open field as well as elevated plus maze trials on mice. Transcriptomes and LC/MS-MS-based metabolomes were adopted for investigating how CLA affected lipidomic profiling as well as metabolic pathway of the cerebral cortex. CLA exposure greatly disturbed glycerophospholipid metabolism and the carbon chain length of fatty acids. By using whole transcriptome sequencing, we found that CLA significantly downregulated the mRNA expression of CEPT1 and CHPT1, two key enzymes involved in the synthesis of glycerophospholipids, supporting the findings from the lipidomic profiling. Also, CLA causes changes in neuronal morphology and function in vitro, which support the existing findings concerning neurobehavior in vivo. We speculate that altered glycerophospholipid metabolism may be involved in the neurobehavioral effect of CLA. Our findings contribute to understanding the mechanisms of CLA-induced adverse effects on the central nervous system. 1. Clarithromycin treatment caused anxiety-like behavior with dose-dependent response both in the open field and elevated plus maze test in mice; 2. Clarithromycin exposing predominately disturbed the metabolism of glycerophospholipids in the cerebral cortex of mice; 3. Clarithromycin application remarkably attenuated CEPT1 and CHPT1 gene expression, which participate in the last step in the synthesis of glycerophospholipids; 4. The altered glycerophospholipid metabolomics may be involved in the abnormal neurobehavior caused by clarithromycin.

Biomarker Reproducibility Challenge: A Review of Non-Nucleotide Biomarker Discovery Protocols from Body Fluids in Breast Cancer Diagnosis

Breast cancer has now become the most commonly diagnosed cancer, accounting for one in eight cancer diagnoses worldwide. Non-invasive diagnostic biomarkers and associated tests are superlative candidates to complement or improve current approaches for screening, early diagnosis, or prognosis of breast cancer. Biomarkers detected from body fluids such as blood (serum/plasma), urine, saliva, nipple aspiration fluid, and tears can detect breast cancer at its early stages in a minimally invasive way. The advancements in high-throughput molecular profiling (omics) technologies have opened an unprecedented opportunity for unbiased biomarker detection. However, the irreproducibility of biomarkers and discrepancies of reported markers have remained a major roadblock to clinical implementation, demanding the investigation of contributing factors and the development of standardised biomarker discovery pipelines. A typical biomarker discovery workflow includes pre-analytical, analytical, and post-analytical phases, from sample collection to model development. Variations introduced during these steps impact the data quality and the reproducibility of the findings. Here, we present a comprehensive review of methodological variations in biomarker discovery studies in breast cancer, with a focus on non-nucleotide biomarkers (i.e., proteins, lipids, and metabolites), highlighting the pre-analytical to post-analytical variables, which may affect the accurate identification of biomarkers from body fluids.

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.

Lipidomic landscape of circulating extracellular vesicles isolated from adolescents exposed to ethanol intoxication: a sex difference study

BACKGROUND

Lipids represent essential components of extracellular vesicles (EVs), playing structural and regulatory functions during EV biogenesis, release, targeting, and cell uptake. Importantly, lipidic dysregulation has been linked to several disorders, including metabolic syndrome, inflammation, and neurological dysfunction. Our recent results demonstrated the involvement of plasma EV microRNAs as possible amplifiers and biomarkers of neuroinflammation and brain damage induced by ethanol intoxication during adolescence. Considering the possible role of plasma EV lipids as regulatory molecules and biomarkers, we evaluated how acute ethanol intoxication differentially affected the lipid composition of plasma EVs in male and female adolescents and explored the participation of the immune response.

METHODS

Plasma EVs were extracted from humans and wild-type (WT) and Toll-like receptor 4 deficient (TLR4-KO) mice. Preprocessing and exploratory analyses were conducted after the extraction of EV lipids and data acquisition by mass spectrometry. Comparisons between ethanol-intoxicated and control human female and male individuals and ethanol-treated and untreated WT and TLR4-KO female and male mice were used to analyze the differential abundance of lipids. Annotation of lipids into their corresponding classes and a lipid set enrichment analysis were carried out to evaluate biological functions.

RESULTS

We demonstrated, for the first time, that acute ethanol intoxication induced a higher enrichment of distinct plasma EV lipid species in human female adolescents than in males. We observed a higher content of the PA, LPC, unsaturated FA, and FAHFA lipid classes in females, whereas males showed enrichment in PI. These lipid classes participate in the formation, release, and uptake of EVs and the activation of the immune response. Moreover, we observed changes in EV lipid composition between ethanol-treated WT and TLR4-KO mice (e.g., enrichment of glycerophosphoinositols in ethanol-treated WT males), and the sex-based differences in lipid abundance are more notable in WT mice than in TLR4-KO mice. All data and results generated have been made openly available on a web-based platform ( http://bioinfo.cipf.es/sal ).

CONCLUSIONS

Our results suggest that binge ethanol drinking in human female adolescents leads to a higher content of plasma EV lipid species associated with EV biogenesis and the propagation of neuroinflammatory responses than in males. In addition, we discovered greater differences in lipid abundance between sexes in WT mice compared to TLR4-KO mice. Our findings also support the potential use of EV-enriched lipids as biomarkers of ethanol-induced neuroinflammation during adolescence.

Separation and Simultaneous Trapping of Multiply Charged and Singly Charged Ions for Mass Spectrometry: Application to Lipid Mixtures

Conventional electrospray ionization (ESI) of mixtures can give rise to singly and multiply charged analyte species that overlap in mass-to-charge (m/z) ratios, which can complicate the analysis of individual components. The overlap in m/z for ions of different mass and charge is particularly problematic when ions of low relative abundance are of interest. For example, cardiolipins (CLs) are structurally complex phospholipids present in low relative abundance in the lipidome but play crucial roles in mitochondrial metabolism and various regulatory processes. ESI of CLs in negative ion mode shows abundant doubly deprotonated ions and minor singly deprotonated ions. In the ESI of lipid extracts, highly abundant singly charged phospholipids extensively overlap in m/z space with CL dianions of much lesser abundance, thereby complicating the study of the CLs. To address this challenge, we employed a gas-phase approach to separate singly charged ions from a population of ions of mixed charge states while allowing for the storage of one or both of the separated ion populations. Herein, we describe the considerations for applying enhanced singly charged (ESC) and enhanced multiply charged (EMC) scans to perform a gas-phase separation of singly charged lipids from doubly charged lipids in an Escherichia coli extract. This method allows for improved signal-to-noise (S/N) ratio of low abundance ions with minimal overall signal loss, removal of "chemical noise" arising from singly charged ions, and allows for retention of spatially separated ions within a mass spectrometer.

Solvent effects of N,N-dimethylformamide and methanol on mass spectrometry imaging by tapping-mode scanning probe electrospray ionization

Mass spectrometry imaging (MSI) is an effective technique for visualizing the distribution of lipids in tissues. The direct extraction-ionization methods using minute volumes of solvent for local components have the advantage of rapid measurement without any sample pretreatment. For effective MSI of tissues, it is necessary to understand the effect of solvent physicochemical properties on ion images. In this study, we report solvent effects on the lipid imaging of mouse brain tissue by tapping-mode scanning probe electrospray ionization (t-SPESI) which is capable of extraction-ionization using sub-pL solvents. To precisely measure lipid ions, we developed a measurement system incorporating a quadrupole-time-of-flight mass spectrometer. The differences in signal intensity and spatial resolution of lipid ion images were investigated using N,N-dimethylformamide (non-protic polar solvent), methanol (protic polar solvent) and their mixture. The mixed solvent was suitable for the protonation of lipids, and it provided high spatial resolution MSI. Results indicate that the mixed solvent improves the extractant transfer efficiency and minimizes charged droplets from an electrospray. The solvent selectivity study revealed the importance of solvent selection based on physicochemical properties for the advancement of MSI by t-SPESI.

Expanding the Molecular Disturbances of Lipoproteins in Cardiometabolic Diseases: Lessons from Lipidomics

The increasing global burden of cardiometabolic diseases highlights the urgent clinical need for better personalized prediction and intervention strategies. Early diagnosis and prevention could greatly reduce the enormous socio-economic burden posed by these states. Plasma lipids including total cholesterol, triglycerides, HDL-C, and LDL-C have been at the center stage of the prediction and prevention strategies for cardiovascular disease; however, the bulk of cardiovascular disease events cannot be explained sufficiently by these lipid parameters. The shift from traditional serum lipid measurements that are poorly descriptive of the total serum lipidomic profile to comprehensive lipid profiling is an urgent need, since a wealth of metabolic information is currently underutilized in the clinical setting. The tremendous advances in the field of lipidomics in the last two decades has facilitated the research efforts to unravel the lipid dysregulation in cardiometabolic diseases, enabling the understanding of the underlying pathophysiological mechanisms and identification of predictive biomarkers beyond traditional lipids. This review presents an overview of the application of lipidomics in the study of serum lipoproteins in cardiometabolic diseases. Integrating the emerging multiomics with lipidomics holds great potential in moving toward this goal.

Lipidomics and proteomics: An integrative approach for early diagnosis of dementia and Alzheimer's disease

Alzheimer's disease (AD) is the most common neurodegenerative disorder and considered to be responsible for majority of worldwide prevalent dementia cases. The number of patients suffering from dementia are estimated to increase up to 115.4 million cases worldwide in 2050. Hence, AD is contemplated to be one of the major healthcare challenge in current era. This disorder is characterized by impairment in various signaling molecules at cellular and nuclear level including aggregation of Aβ protein, tau hyper phosphorylation altered lipid metabolism, metabolites dysregulation, protein intensity alteration etc. Being heterogeneous and multifactorial in nature, the disease do not has any cure or any confirmed diagnosis before the onset of clinical manifestations. Hence, there is a requisite for early diagnosis of AD in order to downturn the progression/risk of the disorder and utilization of newer technologies developed in this field are aimed to provide an extraordinary assistance towards the same. The lipidomics and proteomics constitute large scale study of cellular lipids and proteomes in biological matrices at normal stage or any stage of a disease. The study involves high throughput quantification and detection techniques such as mass spectrometry, liquid chromatography, nuclear mass resonance spectroscopy, fluorescence spectroscopy etc. The early detection of altered levels of lipids and proteins in blood or any other biological matrices could aid in preventing the progression of AD and dementia. Therefore, the present review is designed to focus on the recent techniques and early diagnostic criteria for AD, revealing the role of lipids and proteins in this disease and their assessment through different techniques.

Pharmacometabolomics for the Study of Lipid-Lowering Therapies: Opportunities and Challenges

Lipid-lowering therapies are widely used to prevent the development of atherosclerotic cardiovascular disease (ASCVD) and related mortality worldwide. "Omics" technologies have been successfully applied in recent decades to investigate the mechanisms of action of these drugs, their pleiotropic effects, and their side effects, aiming to identify novel targets for future personalized medicine with an improvement of the efficacy and safety associated with the treatment. Pharmacometabolomics is a branch of metabolomics that is focused on the study of drug effects on metabolic pathways that are implicated in the variation of response to the treatment considering also the influences from a specific disease, environment, and concomitant pharmacological therapies. In this review, we summarized the most significant metabolomic studies on the effects of lipid-lowering therapies, including the most commonly used statins and fibrates to novel drugs or nutraceutical approaches. The integration of pharmacometabolomics data with the information obtained from the other "omics" approaches could help in the comprehension of the biological mechanisms underlying the use of lipid-lowering drugs in view of defining a precision medicine to improve the efficacy and reduce the side effects associated with the treatment.

Lipid Spectrum Generator: A Simple Script for the Generation of Accurate In Silico Lipid Fragmentation Spectra

Due to the complexity of lipids in nature, the use of in silico generated spectral libraries to identify lipid species from mass spectral data has become an integral part of many lipidomic workflows. However, many in silico libraries are either limited in usability or their capacity to represent lipid species. Here, we introduce Lipid Spectrum Generator, an open-source in silico spectral library generator specifically designed to aid in the identification of lipids in liquid chromatography-tandem mass spectrometry analysis.

Lipidomic and transcriptomic profiles of glycerophospholipid metabolism during Hemerocallis citrina Baroni flowering

BACKGROUND

Hemerocallis citrina Baroni (daylily) is a horticultural ornamental plant and vegetable with various applications as a raw material in traditional Chinese medicine and as a flavouring agent. Daylily contains many functional substances and is rich in lecithin, which is mostly composed of glycerophospholipids. To study the comprehensive dynamic changes in glycerophospholipid during daylily flowering and the underlying signalling mechanisms, we performed comprehensive, time-resolved lipidomic and transcriptomic analyses of 'Datong Huanghua 6' daylily.

RESULTS

Labelling with PKH67 fluorescent antibodies clearly and effectively helped visualise lipid changes in daylily, while relative conductivity and malonaldehyde content detection revealed that the early stages of flowering were controllable processes; however, differences became non-significant after 18 h, indicating cellular damage. In addition, phospholipase D (PLD) and lipoxygenase (LOX) activities increased throughout the flowering process, suggesting that lipid hydrolysis and oxidation had intensified. Lipidomics identified 558 lipids that changed during flowering, with the most different lipids found 12 h before and 12 h after flowering. Transcriptome analysis identified 13 key functional genes and enzymes in the glycerophospholipid metabolic pathway. The two-way orthogonal partial least squares analysis showed that diacylglycerol diphosphate phosphatase correlated strongly and positively with phosphatidic acid (PA)(22:0/18:2), PA(34:2), PA(34:4), and diacylglycerol(18:2/21:0) but negatively with phospholipase C. In addition, ethanolamine phosphotransferase gene and phospholipid-N-methyltransferase gene correlated positively with phosphatidylethanolamine (PE)(16:0/18:2), PE(16:0/18:3), PE(33:2), and lysophosphatidylcholine (16:0) but negatively with PE(34:1).

CONCLUSIONS

Overall, this study elucidated changes in the glycerophospholipid metabolism pathway during the daylily flowering process, as well as characteristic genes, thus providing a basis for future studies of glycerophospholipids and signal transduction in daylilies.

High-Resolution Liquid Chromatography-Mass Spectrometry for Lipidomics

Liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) is a powerful tool for identification and classification of lipids. Ultra-high performance liquid chromatography (UHPLC) allows for robust separations of complex mixtures, while high-resolution mass spectrometry (HRMS) identifies compounds with efficiency and accuracy (Zullig T and Kofeler HC, Mass Spectrom Rev 40:162-176, 2021). The high specificity and sensitivity of mass spectrometry makes it the method of choice when analyzing lipids (Kofeler HC, J Lipid Res 62:100138, 2021). Untargeted mass spectrometry identifies all lipids within a sample and is useful for identification and further discovery. This chapter describes the use of a Q Exactive mass spectrometer to perform an untargeted LC-MS/MS lipidomics analysis.

Defining atherosclerotic plaque biology by mass spectrometry-based omics approaches

Atherosclerosis is the principal cause of vascular diseases and one of the leading causes of worldwide death. Even though several insights into its natural course, risk factors and interventions have been identified, it is still an ongoing global pandemic. Since the structure and biochemical composition of the plaques show high heterogeneity, a comprehensive understanding of the intraplaque composition, its microenvironment, and the mechanisms of the progression and instability across different vascular beds at their progression stages is crucial for better risk stratification and treatment modalities. Even though several cell-based studies, animal studies, and extensive multicentric population studies have been conducted concerning cardiovascular diseases for assessing the risk factors and plaque biology, the studies on human clinical samples are very limited. New novel approaches utilize samples from percutaneous coronary interventions, which could possibly gain more access to clinical samples at different stages of the diseases without complex invasive resections. As an emerging technological platform in disease discovery research, mass spectrometry-based omics technologies offer capabilities for a comprehensive understanding of the mechanisms linked to several vascular diseases. Here, we discuss the cellular and molecular processes of atherosclerosis, different mass spectrometry-based omics approaches, and the studies mostly done on clinical samples of atheroma plaque using mass spectrometry-based proteomics, metabolomics and lipidomics approaches.

Chemical derivatization strategy for mass spectrometry-based lipidomics

Lipids, serving as the structural components of cellular membranes, energy storage, and signaling molecules, play the essential and multiple roles in biological functions of mammals. Mass spectrometry (MS) is widely accepted as the first choice for lipid analysis, offering good performance in sensitivity, accuracy, and structural characterization. However, the untargeted qualitative profiling and absolute quantitation of lipids are still challenged by great structural diversity and high structural similarity. In recent decade, chemical derivatization mainly targeting carboxyl group and carbon-carbon double bond of lipids have been developed for lipidomic analysis with diverse advantages: (i) offering more characteristic structural information; (ii) improving the analytical performance, including chromatographic separation and MS sensitivity; (iii) providing one-to-one chemical isotope labeling internal standards based on the isotope derivatization regent in quantitative analysis. Moreover, the chemical derivatization strategy has shown great potential in combination with ion mobility mass spectrometry and ambient mass spectrometry. Herein, we summarized the current states and advances in chemical derivatization-assisted MS techniques for lipidomic analysis, and their strengths and challenges are also given. In summary, the chemical derivatization-based lipidomic approach has become a promising and reliable technique for the analysis of lipidome in complex biological samples.

Measuring the Content of Endocannabinoid-Like Compounds in Biological Fluids: A Critical Overview of Sample Preparation Methodologies

Different mass spectrometric techniques have been used over the past decade to quantify endocannabinoids (eCBs) and related lipids. Even with the level of molecular fingerprinting accuracy of an instrument like the most advanced triple quadrupole mass spectrometer, if one is not getting the most optimized sample to the detector in a way that this improved technology can be of use, then advancements can be stymied. Here, our focus is on review and discussion of sample preparation methodologies used to isolate the eCB anandamide and its close congeners N-acyl ethanolamines and structural congeners (i.e., lipo amino acids, lipoamines, N-acyl amides) in biological fluids. Most of our focus will be on the analysis of these lipids in plasma/serum, but we will also discuss how the same techniques can be used for the analysis of saliva and breast milk.

Differential Kendrick's Plots as an Innovative Tool for Lipidomics in Complex Samples: Comparison of Liquid Chromatography and Infusion-Based Methods to Sample Differential Study

Lipidomics has developed rapidly over the past decade. Nontargeted lipidomics from biological samples remains a challenge due to the high structural diversity, the concentration range of lipids, and the complexity of biological samples. We introduce here the use of differential Kendrick's plots as a rapid visualization tool for a qualitative nontargeted analysis of lipids categories and classes from data generated by either liquid chromatography-mass spectrometry (LC-MS) or direct infusion (nESI-MS). Each lipid class is easily identified by comparison with the theoretical Kendrick plot pattern constructed from exact mass measurements and by using MSKendrickFilter, an in-house Python software. The lipids are identified with the LIPID MAPS database. In addition, in LC-MS, the software based on the Kendrick plots returns the retention time from all the lipids belonging to the same series. Lipid extracts from a yeast (Saccharomyces cerevisiae) are used as a model. An on/off case comparing Kendrick plots from two cell lines (prostate cancer cell lines treated or not with a DGAT2 inhibition) clearly shows the effect of the inhibition. Our study demonstrates the good performance of direct infusion as a fast qualitative screening method as well as for the analysis of chromatograms. A fast screening semiquantitative approach is also possible, while the targeted mode remains the golden standard for precise quantitative analysis.

Evaluation of lipidomic change in goat sperm after cryopreservation

The current study aimed to detect the relationship between the spermatozoa cryotolerance and the post-thawed sperm lipidome. Ejaculates from 20 goats, and performed a uniform frozen-thawed procedure in this study. According to the total motility of thawed sperm of goats, semen samples were classified into HF group (High Freezers, n = 8) with >60% total motility and LF group (Low Freezers, n = 8) with < 45% total motility. The lipidomic analysis based on UHPLC-MS/MS was utilized to investigate the relationship between sperm cryotolerance and their lipid metabolites expression. The results showed that the cryotolerance of sperm from different individual goats were in great variation. The total motility of post-thawed sperm in HF group (60.93 ± 2.43%) is significantly higher than that in LF group (34.04 ± 3.41%, P < 0.01). And the post-thawed sperm in HF group exhibited significantly higher plasma membrane (59.06 ± 2.34%) and acrosome integrity (62.93 ± 1.15%) than that in LF group (34.06 ± 4.85%, 44.92 ± 2.19% respectively, P < 0.01). The total of 29 lipid subclasses and 1,133 lipid molecules in the post-thawed goat sperm were identified by lipidomics analysis. The lipid content of thawed sperm in HF group was higher than that in LF group, the lipid profile in HF group was significantly separated from LF group, which indicated that the difference in lipid composition and lipid metabolism mode of sperm between the two groups was existed, especially the expression of phosphatidylcholine and triglyceride molecules. In conclusion, the cryotolerance of sperm from different individual goats were in great variation. Sperm with high cryotolerance may be able to uptake more lipids during cryopreservation. The increase in phosphatidylcholine and triglyceride content of thawed. Sperm may relate to more active lipid anabolic processes.

Rapid Evaporative Ionization Mass Spectrometry-Based Lipidomics for Identification of Canine Mammary Pathology

The present work proposes the use of a fast analytical platform for the mass spectrometric (MS) profiling of canine mammary tissues in their native form for the building of a predictive statistical model. The latter could be used as a novel diagnostic tool for the real-time identification of different cellular alterations in order to improve tissue resection during veterinary surgery, as previously validated in human oncology. Specifically, Rapid Evaporative Ionization Mass Spectrometry (REIMS) coupled with surgical electrocautery (intelligent knife—iKnife) was used to collect MS data from histologically processed mammary samples, classified into healthy, hyperplastic/dysplastic, mastitis and tumors. Differences in the lipid composition enabled tissue discrimination with an accuracy greater than 90%. The recognition capability of REIMS was tested on unknown mammary samples, and all of them were correctly identified with a correctness score of 98–100%. Triglyceride identification was increased in healthy mammary tissues, while the abundance of phospholipids was observed in altered tissues, reflecting morpho-functional changes in cell membranes, and oxidized species were also tentatively identified as discriminant features. The obtained lipidomic profiles represented unique fingerprints of the samples, suggesting that the iKnife technique is capable of differentiating mammary tissues following chemical changes in cellular metabolism.

Lipidomics: An excellent tool for chronic disease detection

It has been known as almost all the cells consists a lipid molecule which has a considerable impact in various biological processes. Lipids have been investigated with a potential role for the formation of cellular membrane and thereby maintaining the structural integrity. Omics has placed as a combined technologies utilized for an exploaration of mechanistic actions in several kinds of molecules that make up the cells of an organism. Lipidomics has been recognized as a newly emerged branch of omics technology. This technology has the captivating factors to classify and characterize almost all the cellular lipids with the help of various analytical techniques and computational biological plateform. In lipidomics studies, structural display of several lipid biomarkers could also be analyzed and considered for actual disease diagnosis procedures. This could also replace certain traditional diagnostics method at all over the globe. Our review focuses how important this lipidomics particularly in disease diagnosis and also covers various analytical techniques and computational methods or bioinformatics tools in for the diagnosis of disease. In addtion, we also pinponted the possible role of lipids in several kinds of cellular disorders including cancer, neurodegenerative diseases, cardiovascular diseases, diabetes and obesity in human population. .

“Omic” Approaches to Bacteria and Antibiotic Resistance Identification

The quick and accurate identification of microorganisms and the study of resistance to antibiotics is crucial in the economic and industrial fields along with medicine. One of the fastest-growing identification methods is the spectrometric approach consisting in the matrix-assisted laser ionization/desorption using a time-of-flight analyzer (MALDI-TOF MS), which has many advantages over conventional methods for the determination of microorganisms presented. Thanks to the use of a multiomic approach in the MALDI-TOF MS analysis, it is possible to obtain a broad spectrum of data allowing the identification of microorganisms, understanding their interactions and the analysis of antibiotic resistance mechanisms. In addition, the literature data indicate the possibility of a significant reduction in the time of the sample preparation and analysis time, which will enable a faster initiation of the treatment of patients. However, it is still necessary to improve the process of identifying and supplementing the existing databases along with creating new ones. This review summarizes the use of “-omics” approaches in the MALDI TOF MS analysis, including in bacterial identification and antibiotic resistance mechanisms analysis.

Potential Serum Biomarkers Associated with Premature Rupture of Fetal Membranes in the First Trimester

Premature rupture of the fetal membranes (PROM) is a common and important obstetric complication with increased risk of adverse consequences for both mothers and fetuses. An accurate and timely method to predict the occurrence of PROM is needed for ensuring maternal and fetal safety. Untargeted metabolomics was applied to characterize metabolite profiles related to PROM in early pregnancy. 41 serum samples from pregnant women who developed PROM later in gestation and 106 from healthy pregnant women as a control group, were analyzed. Logistic regression analysis was adjusted to analyze a PROM prediction model in the first trimester. A WISH amniotic cell viability assay was applied to explore the underlying mechanisms involved in PROM, mediated by C8-dihydroceramide used to mimic a potential biomarker (Cer 40:0; O2). Compared with healthy controls, 13 serum metabolites were identified. The prediction model comprising four compounds (Cer 40:0; O2, sphingosine, isohexanal and PC O-38:4) had moderate accuracy to predict PROM events with the maximum area under the curve of a receiver operating characteristics curve of approximately 0.70. Of these four compounds, Cer 40:0; O2 with an 1.81-fold change between PROM and healthy control serum samples was defined as a potential biomarker and inhibited the viability of WISH cells. This study sheds light on predicting PROM in early pregnancy and on understanding the underlying mechanism of PROM.

Trial Registration: This study protocol has been registered at www.ClinicalTrials.gov, CT03651934, on 29 August 2018 (prior to recruitment).

Liquid Chromatography-Dielectric Barrier Discharge Ionization Mass Spectrometry for the analysis of neutral lipids of archaeological interest

Dielectric barrier discharge ionization has gained attention in the last few years due to its versatility and the vast array of molecules that can be ionized. In this study, we report on the assessment of liquid chromatography coupled to dielectric barrier discharge ionization with mass spectrometry for neutral lipid analysis. A set of different neutral lipid subclasses (triacylglycerides, diacylglycerides, and sterols) were selected for the study. The main species detected from our ionization source were [M‐H₂O+H]⁺, [M+H]⁺ or [M‐R‐H₂O+H]⁺, attributed to sterol dehydration, protonation or the fragmentation of an acyl chain accompanied by a water loss of the glycerolipids, respectively. In terms of sensitivity, the dielectric barrier discharge displayed overall improved abundances and comparable or better limits of quantitation than atmospheric pressure chemical ionization for both acylglycerols and sterols. As a case study, different archaeological samples with variable content in neutral lipids, particularly triacylglycerides, were studied. The identification was carried out by combining accurate mass and the tentative formula associated with the exact mass, retention time matching with standards, and additional structural information from in‐source fragmentation. The high degree of unsaturation and the presence of sterols revealed the potential vegetal origin of the material stored in the analyzed samples.

Lipidomics Profiling of HepG2 Cells and Interference by Mycotoxins Based on UPLC-TOF-IMS

Discovering the fungus-infected or mycotoxin-contaminated biomarkers is significant for systems biology since the metabolites in biological samples have significant polarity differences in both stochastic gene expression and microenvironmental change. Here, we aim to establish a comprehensive method for a lipidome by ion mobility mass spectrometry (IMS) merged with chemometrics to accurately find out the more scientific markers of cell interference by mycotoxins and for pathogenesis exploration and drug development. The differences in the abundances of several small molecules found in these metabolites were explored through multivariate statistical analysis, including principal component analysis (PCA) and orthogonal partial least-squares discriminant analysis (OPLS-DA), to further screen biomarkers. Good applicability and predictability were demonstrated by R²(X) and Q² (R² = 0.959, Q² = 0.999). Five compounds with m/z values of 512.502 8, 540.5343, 722.525 8, 787.667 5, and 813.683 0 were selected as markers, and four of them were further confirmed by chemical standards (i.e., MSMS of m/z 813.683 0 covering m/z 86.0978, 125.0008, 184.0745, and 185.0781). In summary, we demonstrated the integration of UPLC-TOF-IMS and the chemometrics approach to elucidate identified biomarkers, which also provides a new way of thinking for covering lipid biomarkers or prognostic indicators for mycotoxins.

Helminth lipidomics: Technical aspects and future prospects

Lipidomics is a relatively recent molecular research field, and explores lipids (fats) and their biology using advanced mass spectrometry technologies. Although this field has expanded significantly in biomedical and biotechnological disciplines, it is still in its infancy in molecular parasitology. Our goal here is to review and discuss technical aspects of MS-based lipidomics and its recent applications to parasitic worms, as well as challenges and future directions for worm lipid research. In a multi-omic paradigm, we expect that the exploration of lipidomic data for parasitic worms will yield important insights into lipid-associated biological pathways and processes, including the regulation of essential signalling pathways, parasite invasion, establishment, adaptation and development.

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Lipids are involved in critical biological functions in parasitic worms.

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Lipidomics is an emerging research field in molecular helminthology.

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This article covers technological advances and applications to parasitic worms.

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It also discusses challenges and future directions for lipidomic research.

Structure and function of glycosphingolipids on small extracellular vesicles

Extracellular vesicles (EVs) are membrane-delineated particles secreted by most types of cells under both normal and pathophysiological conditions. EVs are believed to mediate intercellular communication by serving as carriers of different bioactive ingredients, including proteins, nucleic acids and lipids. Glycoconjugates are complex molecules consisting of covalently linked carbohydrate with proteins or lipids. These glycoconjugates play essential roles in the sorting of vesicular protein and the uptake of small extracellular vesicles (30–100 nm, sEVs) into recipient cells. Glycosphingolipids (GSLs), one subtype of glycolipids, which are ubiquitous membrane components in almost all living organisms, are also commonly distributed on sEVs. However, the study of functional roles of GSLs on sEVs are far behind than other functional cargos. The purpose of this review is to highlight the importance of GSLs on sEVs. Initially, we described classification and structure of GSLs. Then, we briefly introduced the essential functions of GSLs, which are able to interact with functional membrane proteins, such as growth factor receptors, integrins and tetraspanins, to modulate cell growth, adhesion and cell motility. In addition, we discussed analytical methods for studying GSLs on sEVs. Finally, we focused on the function of GSLs on sEVs, including regulating the aggregation of extracellular α-synuclein (α-syn) or extracellular amyloid-β (Aβ) and influencing tumor cell malignancy.

Mulberry (Morus alba L.) leaf polysaccharide ameliorates insulin resistance- and adipose deposition-associated gut microbiota and lipid metabolites in high-fat diet-induced obese mice

Dietary supplements are currently being used to ameliorate metabolic alterations via maintaining gut microflora balance. Mulberry leaf is known as medicine homologous food for its glucose- and lipid-modulating properties. However, the effects of mulberry leaf polysaccharide (MP) on metabolic dysbiosis and gut microbiota are still poorly understood. After extraction and characterization, the beneficial effects of water-soluble MP were evaluated in high-fat diet-induced obese mice. MP treatment could reduce adipose tissue, improve insulin resistance, and alleviate the pathological lesions in colon. Investigation of the underlying mechanism showed that MP modulated gut microbial community by 16S rRNA analysis and reversed the elevation of lipid indexes by plasma lipidomics analysis. Correlation analysis indicated that the abundance of seven key bacterial species and six lipids were closely associated with the metabolic traits, respectively. Overall, MP could ameliorate metabolic disorders, and modify the gut microbiota and lipids. This would greatly facilitate the utilization of MP as a functional food.

Candidate Circulating Biomarkers of Spontaneous Miscarriage After IVF-ET Identified via Coupling Machine Learning and Serum Lipidomics Profiling

Spontaneous miscarriage is a common pregnancy complication. Multiple etiologies have been proposed such as genetic aberrations, endocrinology disorder, and immunologic derangement; however, the relevance of circulating lipidomes to the specific condition remains unclear. In the present study, lipidomics profiling was examined on serum of women with spontaneous miscarriage after in vitro fertilization and embryo transfer (IVF-ET). Screening and analysis of differential lipid levels were conducted using a machine learning approach to verify the stability and validity of potential serum biomarkers. Seven lipid species presented significant differences between the abortion and term birth patients, including three types of sphingomyelins (SMs), two types of diglycerides (DGs), one phosphatidylcholine (PC), and one lysophosphatidylethanolamine (LPE). All the SMs presented with a fold change of > 1, while both the PC and LPE had a fold change of < 1. The DG containing two saturated fatty acyl chains was decreased, but that containing two unsaturated fatty acyl chains was increased in the miscarriage group compared to the control group. This study reveals the relevance of lipid profiles to spontaneous abortion after IVF-ET, providing potential biomarkers and therapeutic targets for the specific clinical scenario.

A Comparison of Lipid Contents in Different Types of Peanut Cultivars Using UPLC-Q-TOF-MS-Based Lipidomic Study

Peanuts are a rich dietary source of lipids, which are essential for human health. In this study, the lipid contents of 13 peanut cultivars were analyzed using UPLC-Q-TOF-MS and GC–MS. The OXITEST reactor was used to test their lipid oxidation stabilities. A total of 27 subclasses, 229 individual lipids were detected. The combined analysis of lipid and oxidation stability showed that lipid unsaturation was inversely correlated with oxidation stability. Moreover, lipid profiles differed significantly among the different peanut cultivars. A total of 11 lipid molecules (TG 18:2/18:2/18:2, TG 24:0/18:2/18:3, TG 20:5/14:1/18:2, TG 18:2/14:1/18:2, PE 17:0/18:2, BisMePA 18:2/18:2, PG 38:5, PMe 18:1/18:1, PC 18:1/18:1, MGDG 18:1/18:1, TG 10:0/10:1/18:1) might be employed as possible indicators to identify high oleic acid (OA) and non-high OA peanut cultivars, based on the PLS-DA result of lipid molecules with a VIP value greater than 2. This comprehensive analysis will help in the rational selection and application of peanut cultivars.

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

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Fabry is an X-linked lysosomal storage disease with deficiency in α-galactosidase.

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This deficiency results in the accumulation of glycosphinogolipids.

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Diagnosis is often made by analysis of globotriaosylceramide in fluids and tissues.

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Fabry is often misdiagnosed in female patients due to residual enzyme activity.

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Lipidomics by LC-HRMS enables identification of new biomarkers in Fabry.

Introduction

Lipidomics 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.

Objectives

The 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.

Methods

Lipidomic 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.

Results

We 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.

Conclusion

This 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.

Lipidomic profiling reveals biosynthetic relationships between phospholipids and diacylglycerol ethers in the deep-sea soft coral Paragorgia arborea

The cold-water gorgonian coral Paragorgia arborea is considered as a foundation species of deep-sea ecosystems in the northern Atlantic and Pacific oceans. To advance lipidomic studies of deep-sea corals, molecular species compositions of diacylglycerol ethers (DAGE), which are specific storage lipids of corals, and structural glycerophospholipids (GPL) including ethanolamine, choline, inositol and serine GPL (PE, PC, PI, and PS, respectively) were analyzed in P. arborea by HPLC and tandem mass spectrometry. In DAGE molecules, alkyl groups (16:0, 14:0, and 18:1), polyunsaturated fatty acids (PUFA), and monounsaturated FA are mainly substituted the glycerol moiety at position sn-1, sn-2, and sn-3, respectively. The ether form (1-O-alkyl-2-acyl) predominates in PE and PC, while PI is comprised of the 1,2-diacyl form. Both ether and diacyl forms were observed in PS. At position sn-2, C₂₀ PUFA are mainly attached to PC, but C₂₄ PUFA, soft coral chemotaxonomic markers, concentrate in PS, PI, and PE. A comparison of non-polar parts of molecules has shown that DAGE, ether PE, and ether PC can originate from one set of 1-O-alkyl-2-acyl-sn-glycerols. Ether PE may be converted to ether PS by the base-exchange reaction. A diacylglycerol unit generated from phosphatidic acid can be a precursor for diacyl PS, PC, and PI. Thus, a lipidomic approach has confirmed the difference in biosynthetic origins between ether and diacyl lipids of deep-sea gorgonians.

Free amino acid, 5'-Nucleotide, and lipid distribution in different tissues of blue mussel (Mytilis edulis L.) determined by mass spectrometry based metabolomics

Blue mussel (Mytilus edulis L.) is a popular, nutritional, and tasty mollusk. To better understand the composition of nutrients and improve further processing of the mussels, metabolomic approaches were used to analyze the free amino acids, 5'-nucleotides, and lipid compositions of different tissues. Our results showed that the viscera and gonad were rich in glutamine and glycine. Adenosine 5'-monophosphate, uridine 5'-monophosphate, guanosine 5'-monophosphate, and inosine 5'-monophosphate were abundant in the mantle, foot, and adductor muscle. Three main types of lipids, phospholipids (PLs), glycerides, and fatty acids (FAs), were semi-quantified. PLs were mainly distributed in the gonad of male mussels and viscera, gonad, and mantles of female mussels. FAs were relatively high in the viscera of males and in the gonad and viscera of females. The viscera of females were rich in phosphatidylcholine, such as 16:0/22:6 and 16:0/20:5. Triglycerides were the key lipids for distinguishing different tissues, especially 16:0/18:1/18:3 and 16:0/18:4/20:5.

Lipidomic profiling reveals distinct differences in plasma lipid composition in overweight or obese adolescent students

INTRODUCTION

The relationship between dyslipidemia and obesity has been widely reported, but the global lipid profiles associated with the development of obesity still need to be clarified. An investigation into the association between the lipidomic plasma profile and adolescent obesity may provide new insights into the development of obesity.

METHODS

Mass spectrometry coupled with liquid chromatography was applied to detect the global lipidome in the fasting plasma from 90 Chinese adolescents, including 34 obese adolescents, 26 overweight adolescents, and 30 adolescents with a normal body mass index (BMI). All participants underwent anthropometric measurements by using InBody. Clinical biochemical indicators were measured by Cobas Elecsys.

RESULTS

Both qualitative and quantitative analyses revealed a gradual change in plasma lipid features among obese students, exhibiting characteristics close to overweight students, but differing significantly from normal students. Compared with normal and overweight students, levels of triglyceride (TG), 18-hydroxycortisol, isohumulinone A, and 11-dihydro-12-norneoquassin were up-regulated in the obese group, while phosphatidylcholine (PC), phosphatidylethanolamine (PE), lysoPC (LPC), lysoPE (LPE), and phosphatidylinositol (PI) were significantly down-regulated in the obese group. Then, we conducted Venn diagrams and selected 8 significant metabolites from the 3 paired comparisons. Most of the selected features were significantly correlated with the anthropometric measurements.

CONCLUSIONS

This study demonstrated evidence for a relationship between the eight significant metabolites with obese adolescents. These lipid features may provide a basis for evaluating risk and monitoring the development of obesity.

Metabolomics for Crop Breeding: General Considerations

The development of new, more productive varieties of agricultural crops is becoming an increasingly difficult task. Modern approaches for the identification of beneficial alleles and their use in elite cultivars, such as quantitative trait loci (QTL) mapping and marker-assisted selection (MAS), are effective but insufficient for keeping pace with the improvement of wheat or other crops. Metabolomics is a powerful but underutilized approach that can assist crop breeding. In this review, basic methodological information is summarized, and the current strategies of applications of metabolomics related to crop breeding are explored using recent examples. We briefly describe classes of plant metabolites, cellular localization of metabolic pathways, and the strengths and weaknesses of the main metabolomics technique. Among the commercialized genetically modified crops, about 50 with altered metabolic enzyme activities have been identified in the International Service for the Acquisition of Agri-biotech Applications (ISAAA) database. These plants are reviewed as encouraging examples of the application of knowledge of biochemical pathways. Based on the recent examples of metabolomic studies, we discuss the performance of metabolic markers, the integration of metabolic and genomic data in metabolic QTLs (mQTLs) and metabolic genome-wide association studies (mGWAS). The elucidation of metabolic pathways and involved genes will help in crop breeding and the introgression of alleles of wild relatives in a more targeted manner.

Effect of Sampling Rate and Data Pretreatment for Targeted and Nontargeted Analysis by Means of Liquid Chromatography Coupled to Drift Time Ion Mobility Quadruple Time-of-Flight Mass Spectrometry

Ion mobility as an additional separation dimension can help to resolve and annotate metabolite and lipid biomarkers and provides important information about the components in a sample. Identifying relevant information in the resulting data is challenging because of the complexity of the data and data evaluation strategies for both targeted or nontargeted workflows. Frequently, feature analysis is used as a first step to search for differences between samples in discovery workflows. However, follow-up experimentation often leads to more targeted data extraction methods. In both cases, optimizing data sets for data extraction can make an important contribution to the overall results. In this work, we evaluate the effect of experimental conditions including acquisition sampling rate and data pretreatment on lipid standards and lipid extracts as examples of complex biological samples analyzed by liquid chromatography coupled to drift time ion mobility quadrupole time-of-flight mass spectrometry. The results show that a reduction of both peak variation and background noise can be achieved by optimizing the sampling rate. The use of data pretreatment including data smoothing, intensity thresholding, and spike removal also play an important role in improving detection and annotation of analytes from complex biological samples, whereas nonoptimal data sampling rates and preprocessing can lead to adverse effects including the loss or alternation of small, or closely eluting, low-abundant peaks.

On-tissue chemical derivatization reagents for matrix-assisted laser desorption/ionization mass spectrometry imaging

Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI) is a key tool for the analysis of biological tissues. It provides spatial and quantitative information about different types of analytes within tissue sections. Despite the increasing improvements of this technique, the low detection sensitivity of some compounds remains an important challenge to overcome. Poor sensitivity is related to weak ionization efficiency, low abundance of analytes and matrix ions, or endogenous interferences. On-tissue chemical derivatization (OTCD) has proven to be an important solution to these issues and is increasingly employed in MALDI MSI studies. OTCD reagents, synthesized or commercially available, have been essentially used for the detection of small exogenous or endogenous molecules within tissues. Optimally, an OTCD reaction is performed in mild conditions, in an acceptable range of time, preserves the integrity of the tissues, and prevents the delocalization. In addition to their reactivity with a targeted chemical function, some OTCD reagents can also be used as a matrix, which simplifies the sample preparation procedure. In this review, we present an exhaustive overview of OTCD reagents and methods used in MALDI MSI studies.

Phospholipids: Identification and Implication in Muscle Pathophysiology

Phospholipids (PLs) are amphiphilic molecules that were essential for life to become cellular. PLs have not only a key role in compartmentation as they are the main components of membrane, but they are also involved in cell signaling, cell metabolism, and even cell pathophysiology. Considered for a long time to simply be structural elements of membranes, phospholipids are increasingly being viewed as sensors of their environment and regulators of many metabolic processes. After presenting their main characteristics, we expose the increasing methods of PL detection and identification that help to understand their key role in life processes. Interest and importance of PL homeostasis is growing as pathogenic variants in genes involved in PL biosynthesis and/or remodeling are linked to human diseases. We here review diseases that involve deregulation of PL homeostasis and present a predominantly muscular phenotype.

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

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

Targeted analysis of eicosanoids derived from cytochrome P450 pathway by high-resolution multiple-reaction monitoring mass spectrometry

Cytochrome P450 (CYP450) pathway is one of the critical enzymatic via eicosanoid biosynthesis. Nevertheless, their metabolites are far less explored. This pathway plays a crucial role in converting arachidonic acid to hydroxyeicosatetraenoic (HETEs), epoxyeicosatrienoic (EETs), dihydroxyeicosatetraenoic acids (DiHETEs), and dihydroxyeicosatrienoic acids (DiHETrEs), which mediate several physiological and pathological functions. However, CYP450-derived eicosanoids are structurally complex, making those analyses a challenge in lipidomics studies. Herein, a high-resolution multiple-reaction monitoring (MRM^HR ) method has been proposed as a powerful tool for the simultaneous analysis of CYP450-eicosanoids on different biological samples. The developed liquid chromatography (LC)-MRM^HR method was partially validated according to the Food and Drug Administration (FDA) criteria, demonstrating adequate specificity, linearity, precision, and accuracy. Besides, several biological samples were analyzed to guarantee the feasibility of the method. The proposed strategy may improve the understanding of CYP450-derived eicosanoids in biological systems, which could be fundamental to reveal new aspects of those in physiologic and pathologic conditions.

Dynamic binning peak detection and assessment of various lipidomics liquid chromatography-mass spectrometry pre-processing platforms

Liquid chromatography-mass spectrometry (LC-MS)-based lipidomics generates large datasets that need to be interpreted using high-performance data pre-processing tools such as XCMS, mzMine, and Progenesis. These pre-processing tools rely heavily on accurate peak detection, which depends on proper setting of the peak detection mass tolerance (PDMT). The PDMT is usually set with a fixed value in either ppm or Da units. However, this fixed value may result in duplicates or missed peak detection and inaccurate peak quantification. To improve the accuracy of peak detection, we developed the dynamic binning method, which considers peak broadening described by the physics of ion separation and sets the PDMT dynamically in function of m/z. In our method, the PDMT is proportional to (mz)² for Fourier-transform ion cyclotron resonance (FTICR), to (mz)^1.5 for Orbitrap and to m/z for Quadrupole time-of-flight (Q-TOF), and is a constant for Quadrupole mass analyzer. The dynamic binning method was implemented in XCMS [1,2], and the adopted source code is available in GitHub at https://github.com/xiaodfeng/DynamicXCMS. We have compared the performance of the XCMS implemented dynamic binning with different popular lipidomics pre-processing tools to find differential compounds. We generated set samples with 43 lipid internal standards that were differentially spiked to aliquots of one human plasma lipid sample using Orbitrap LC-MS/MS. The performance of various pipelines using matched parameter sets was quantified by a quality score system that reflects the ability of a pre-processing pipeline to detect differential peaks spiked at various concentrations. The quality score indicated that our dynamic binning method improves the quantification performance of XCMS (maximum p-value 9.8·10^-3 of two-sample Wilcoxon test) over its original implementation. We also showed that the XCMS with dynamic binning found differential spiked-in lipids better or with similar performance as mzMine and Progenesis do.

A map of mass spectrometry-based in silico fragmentation prediction and compound identification in metabolomics

Metabolomics, the comprehensive study of the metabolome, and lipidomics-the large-scale study of pathways and networks of cellular lipids-are major driving forces in enabling personalized medicine. Complicated and error-prone data analysis still remains a bottleneck, however, especially for identifying novel metabolites. Comparing experimental mass spectra to curated databases containing reference spectra has been the gold standard for identification of compounds, but constructing such databases is a costly and time-demanding task. Many software applications try to circumvent this process by utilizing cutting-edge advances in computational methods-including quantum chemistry and machine learning-and simulate mass spectra by performing theoretical, so called in silico fragmentations of compounds. Other solutions concentrate directly on experimental spectra and try to identify structural properties by investigating reoccurring patterns and the relationships between them. The considerable progress made in the field allows recent approaches to provide valuable clues to expedite annotation of experimental mass spectra. This review sheds light on individual strengths and weaknesses of these tools, and attempts to evaluate them-especially in view of lipidomics, when considering complex mixtures found in biological samples as well as mass spectrometer inter-instrument variability.