Lipidomics: a mass spectrometry based systems level analysis of cellular lipids

Inactivation of Lipopolysaccharide-Biosynthesizing Genes Altered Lipids Composition and Intensity in Cronobacter sakazakii

Gram-negative bacteria possess an asymmetric outer membrane, where the outer leaflet consists of LPSs and the inner leaflet comprises phospholipids. Cronobacter sakazakii, an opportunistic milk-borne pathogen that causes severe neonatal meningitis and bacteremia, displays diverse lipopolysaccharide (LPS) structures. As a barrier of the bacterial cell, LPSs likely influenced C. sakazakii resistance to environment stresses; however, there are no research reports on this aspect, hindering the development of novel bactericidal strategies overcoming the pathogen's resilience. In the present study, therefore, C. sakazakii BAA894 and two LPS mutants (ΔlpxM and ΔwaaC) were employed to investigate its influences. The ΔwaaC mutant showed lower resistance to acidic, alkali, oxidative, and osmotic stresses compared to the wild-type strain BAA894, and the ΔlpxM mutant exhibited lower desiccation resistance but higher osmotic resistance. To uncover potential reasons for these differences, comparative lipidomics was conducted. The results showed that compared to BAA894, both mutants showed drastic changes in lipid quantity, and many changed lipids were unsaturated. Additionally, eleven lipid classes exhibited significant variation in the relative content. In particular, the polyunsaturated TGs with double bonds at 5, 7, 12, and 14 displayed significant variation between the wild type and two mutants. Our study is the first to reveal that the changes in the LPS structure of C. sakazakii resulted in altered lipid profiles and intensities, which may be a critical biochemical basis for bacterial resistance to harsh stresses.

Exploring lipid signaling in plant physiology: From cellular membranes to environmental adaptation

Lipids have evolved as versatile signaling molecules that regulate a variety of physiological processes in plants. Convincing evidence highlights their critical role as mediators in a wide range of plant processes required for survival, growth, development, and responses to environmental conditions such as water availability, temperature changes, salt, pests, and diseases. Understanding lipid signaling as a critical process has helped us expand our understanding of plant biology by explaining how plants sense and respond to environmental cues. Lipid signaling pathways constitute a complex network of lipids, enzymes, and receptors that coordinate important cellular responses and stressing plant biology's changing and adaptable traits. Plant lipid signaling involves a wide range of lipid classes, including phospholipids, sphingolipids, oxylipins, and sterols, each of which contributes differently to cellular communication and control. These lipids function not only as structural components, but also as bioactive molecules that transfer signals. The mechanisms entail the production of lipid mediators and their detection by particular receptors, which frequently trigger downstream cascades that affect gene expression, cellular functions, and overall plant growth. This review looks into lipid signaling in plant physiology, giving an in-depth look and emphasizing its critical function as a master regulator of vital activities.

Extracellular vesicles as mediators of cell-cell communication in ovarian cancer and beyond - A lipids focus

Extracellular vesicles (EVs) are messengers that carry information in the form of proteins, lipids, and nucleic acids and are not only essential for intercellular communication but also play a critical role in the progression of various pathologies, including ovarian cancer. There has been recent substantial research characterising EV cargo, specifically, the lipid profile of EVs. Lipids are involved in formation and cargo sorting of EVs, their release and cellular uptake. Numerous lipidomic studies demonstrated the enrichment of specific classes of lipids in EVs derived from cancer cells suggesting that the EV associated lipids can potentially be employed as minimally invasive biomarkers for early diagnosis of various malignancies, including ovarian cancer. In this review, we aim to provide a general overview of the heterogeneity of EV, biogenesis, their lipid content, and function in cancer progression focussing on ovarian cancer.

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.

Identification of Monomethyl Branched-Chain Lipids by a Combination of Liquid Chromatography Tandem Mass Spectrometry and Charge-Switching Chemistries

While various mass spectrometric approaches have been applied to lipid analysis, unraveling the extensive structural diversity of lipids remains a significant challenge. Notably, these approaches often fail to differentiate between isomeric lipids─a challenge that is particularly acute for branched-chain fatty acids (FAs) that often share similar (or identical) mass spectra to their straight-chain isomers. Here, we utilize charge-switching strategies that combine ligated magnesium dications with deprotonated fatty acid anions. Subsequent activation of these charge inverted anions yields mass spectra that differentiate anteiso-branched- from straight-chain and iso-branched-chain FA isomers with the predictable fragmentation enabling de novo assignment of anteiso branch points. The application of these charge-inversion chemistries in both gas- and solution-phase modalities is demonstrated to assign the position of anteiso-methyl branch-points in FAs and, with the aid of liquid chromatography, can be extended to de novo assignment of additional branching sites via predictable fragmentation patterns as methyl branching site(s) move closer to the carboxyl carbon. The gas-phase approach is shown to be compatible with top-down structure elucidation of complex lipids such as phosphatidylcholines, while the integration of solution-phase charge-inversion with reversed phase liquid chromatography enables separation and unambiguous identification of FA structures within isomeric mixtures. Taken together, the presented charge-switching MS-based technique, in combination with liquid chromatography, enables the structural identification of branched-chain FA without the requirement of authentic methyl-branched FA reference standards.

Lipidomics-Assisted GWAS (lGWAS) Approach for Improving High-Temperature Stress Tolerance of Crops

High-temperature stress (HT) over crop productivity is an important environmental factor demanding more attention as recent global warming trends are alarming and pose a potential threat to crop production. According to the Sixth IPCC report, future years will have longer warm seasons and frequent heat waves. Thus, the need arises to develop HT-tolerant genotypes that can be used to breed high-yielding crops. Several physiological, biochemical, and molecular alterations are orchestrated in providing HT tolerance to a genotype. One mechanism to counter HT is overcoming high-temperature-induced membrane superfluidity and structural disorganizations. Several HT lipidomic studies on different genotypes have indicated the potential involvement of membrane lipid remodelling in providing HT tolerance. Advances in high-throughput analytical techniques such as tandem mass spectrometry have paved the way for large-scale identification and quantification of the enormously diverse lipid molecules in a single run. Physiological trait-based breeding has been employed so far to identify and select HT tolerant genotypes but has several disadvantages, such as the genotype-phenotype gap affecting the efficiency of identifying the underlying genetic association. Tolerant genotypes maintain a high photosynthetic rate, stable membranes, and membrane-associated mechanisms. In this context, studying the HT-induced membrane lipid remodelling, resultant of several up-/down-regulations of genes and post-translational modifications, will aid in identifying potential lipid biomarkers for HT tolerance/susceptibility. The identified lipid biomarkers (LIPIDOTYPE) can thus be considered an intermediate phenotype, bridging the gap between genotype–phenotype (genotype–LIPIDOTYPE–phenotype). Recent works integrating metabolomics with quantitative genetic studies such as GWAS (mGWAS) have provided close associations between genotype, metabolites, and stress-tolerant phenotypes. This review has been sculpted to provide a potential workflow that combines MS-based lipidomics and the robust GWAS (lipidomics assisted GWAS-lGWAS) to identify membrane lipid remodelling related genes and associations which can be used to develop HS tolerant genotypes with enhanced membrane thermostability (MTS) and heat stable photosynthesis (HP).

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 and Redox Lipidomics Indicate Early Stage Alcohol-Induced Liver Damage

Alcoholic fatty liver disease (AFLD) is characterized by lipid accumulation and inflammation and can progress to cirrhosis and cancer in the liver. AFLD diagnosis currently relies on histological analysis of liver biopsies. Early detection permits interventions that would prevent progression to cirrhosis or later stages of the disease. Herein, we have conducted the first comprehensive time-course study of lipids using novel state-of-the art lipidomics methods in plasma and liver in the early stages of a mouse model of AFLD, i.e., Lieber-DeCarli diet model. In ethanol-treated mice, changes in liver tissue included up-regulation of triglycerides (TGs) and oxidized TGs and down-regulation of phosphatidylcholine, lysophosphatidylcholine, and 20-22-carbon-containing lipid-mediator precursors. An increase in oxidized TGs preceded histological signs of early AFLD, i.e., steatosis, with these changes observed in both the liver and plasma. The major lipid classes dysregulated by ethanol play important roles in hepatic inflammation, steatosis, and oxidative damage. Conclusion: Alcohol consumption alters the liver lipidome before overt histological markers of early AFLD. This introduces the exciting possibility that specific lipids may serve as earlier biomarkers of AFLD than those currently being used.

Short communication: Distribution of phospholipids in parotid cancer by matrix-assisted laser desorption/ionization imaging mass spectrometry

Background

Parotid cancer is relatively rare, and malignancy varies; therefore, novel markers are needed to predict prognosis. Recent advances in matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI-IMS), useful for visualization of lipid molecules, have revealed the relationship between cancer and lipid metabolism, indicating the potential of lipids as biomarkers. However, the distribution and importance of phospholipids in parotid cancer remain unclear.

Objective

This study aimed to use MALDI-IMS to comprehensively investigate the spatial distribution of phospholipids characteristically expressed in human parotid cancer tissues.

Methods

Tissue samples were surgically collected from two patients with parotid cancer (acinic cell carcinoma and mucoepidermoid carcinoma). Frozen sections of the samples were assessed using MALDI-IMS in both positive and negative ion modes, with an m/z range of 600–1000. The mass spectra obtained in the tumor and non-tumor regions were compared and analyzed. Ion images corresponding to the peak characteristics of the tumor regions were visualized.

Results

Several candidate phospholipids with significantly different expression levels were detected between the tumor and non-tumor regions. The number of unique lipid peaks with significantly different intensities between the tumor and non-tumor regions was 95 and 85 for Cases 1 and 2, respectively, in positive ion mode, and 99 and 97 for Cases 1 and 2, respectively, in negative ion mode. Imaging differentiated the characteristics that phospholipids were heterogeneously distributed in the tumor regions.

Conclusion

Phospholipid candidates that are characteristically expressed in human parotid cancer tissues were found, demonstrating the localization of their expression. These findings are notable for further investigation of alterations in lipid metabolism of parotid cancer and may have potential for the development of phospholipids as biomarkers.

A pipeline for making 31P NMR accessible for small- and large-scale lipidomics studies

Detailed molecular analysis is of increasing importance in research into the regulation of biochemical pathways, organismal growth and disease. Lipidomics in particular is increasingly sought after as it provides insight into molecular species involved in energy storage, signalling and fundamental cellular structures. This has led to the use of a range of tools and techniques to acquire lipidomics data. 31P NMR for lipidomics offers well-resolved head group/lipid class analysis, structural data that can be used to inform and strengthen interpretation of mass spectrometry data and part of a priori structural determination. In the present study, we codify the use of 31P NMR for lipidomics studies to make the technique more accessible to new users and more useful for a wider range of questions. The technique can be used in isolation (phospholipidomics) or as a part of determining lipid composition (lipidomics). We describe the process from sample extraction to data processing and analysis. This pipeline is important because it allows greater thoroughness in lipidomics studies and increases scope for answering scientific questions about lipid-containing systems.

Triboelectric Nanogenerator Ion Mobility-Mass Spectrometry for In-Depth Lipid Annotation

Lipids play a critical role in cell membrane integrity, signaling, and energy storage. However, in-depth structural characterization of lipids is still challenging and not routinely possible in lipidomics experiments. Techniques such as collision-induced dissociation (CID) tandem mass spectrometry (MS/MS), ion mobility (IM) spectrometry, and ultrahigh-performance liquid chromatography are not yet capable of fully characterizing double-bond and sn-chain position of lipids in a high-throughput manner. Herein, we report on the ability to structurally characterize lipids using large-area triboelectric nanogenerators (TENG) coupled with time-aligned parallel (TAP) fragmentation IM-MS analysis. Gas-phase lipid epoxidation during TENG ionization, coupled to mobility-resolved MS3 via TAP IM-MS, enabled the acquisition of detailed information on the presence and position of lipid C═C double bonds, the fatty acyl sn-chain position and composition, and the cis/trans geometrical C═C isomerism. The proposed methodology proved useful for the shotgun lipidomics analysis of lipid extracts from biological samples, enabling the detailed annotation of numerous lipid isobars.

Bifidobacterium bifidum strains synergize with immune checkpoint inhibitors to reduce tumour burden in mice

The gut microbiome can influence the development of tumours and the efficacy of cancer therapeutics^1-5; however, the multi-omics characteristics of antitumour bacterial strains have not been fully elucidated. In this study, we integrated metagenomics, genomics and transcriptomics of bacteria, and analyses of mouse intestinal transcriptome and serum metabolome data to reveal an additional mechanism by which bacteria determine the efficacy of cancer therapeutics. In gut microbiome analyses of 96 samples from patients with non-small-cell lung cancer, Bifidobacterium bifidum was abundant in patients responsive to therapy. However, when we treated syngeneic mouse tumours with commercial strains of B. bifidum to establish relevance for potential therapeutic uses, only specific B. bifidum strains reduced tumour burden synergistically with PD-1 blockade or oxaliplatin treatment by eliciting an antitumour host immune response. In mice, these strains induced tuning of the immunological background by potentiating the production of interferon-γ, probably through the enhanced biosynthesis of immune-stimulating molecules and metabolites.

A simple self modelling curve resolution (SMCR) method for two-component systems

Multivariate self-modeling curve resolution (SMCR) methods are the best choice for analyzing chemical data when there is not any prior knowledge about the chemical or physical model of the process under investigation [[1Q3: The reference '1' is only cited in the abstract and not in the text. Please introduce a citation in the text.]]. However, the rotational ambiguity is the main problem of SMCR methods, yielding a range of feasible solutions. It is, therefore, important to determine the range of all feasible solutions of SMCR methods. Different methods have been presented in the literature to find feasible solutions of two, three, and four component systems. Here, a novel simple SMCR method is presented for calculating the boundaries of feasible solutions of two-component systems. At first, the simple strategy is presented for calculating the feasible solutions of two-component systems. Next, four different experimental two-component systems are analyzed in detail for calculating the boundaries of feasible solutions in both spaces, including complex formation equilibrium, keto-enol tautomerization kinetic, lipidomics data, and a case for quantification of an analyte in gray systems. In all cases, the boundaries of range of feasible solutions are properly determined by the proposed simple strategy.

Chromatographic Profiling with Machine Learning Discriminates the Maturity Grades of Nicotiana tabacum L. Leaves

Nicotiana tabacum L. (NTL) is an important agricultural and economical crop. Its maturity is one of the key factors affecting its quality. Traditionally, maturity is discriminated visually by humans, which is subjective and empirical. In this study, we concentrated on detecting as many compounds as possible in NTL leaves from different maturity grades using ultra-performance liquid chromatography ion trap time-of-flight mass spectrometry (UPLC-IT-TOF/MS). Then, the low-dimensional embedding of LC-MS dataset by t-distributed stochastic neighbor embedding (t-SNE) clearly showed the separation of the leaves from different maturity grades. The discriminant models between different maturity grades were established using orthogonal partial least squares discriminant analysis (OPLS-DA). The quality metrics of the models are R2Y = 0.939 and Q2 = 0.742 (unripe and ripe), R2Y = 0.900 and Q2 = 0.847 (overripe and ripe), and R2Y = 0.972 and Q2 = 0.930 (overripe and unripe). The differential metabolites were screened by their variable importance in projection (VIP) and p-Values. The existing tandem mass spectrometry library of plant metabolites, the user-defined library of structures, and MS-FINDER were combined to identify these metabolites. A total of 49 compounds were identified, including 12 amines, 14 lipids, 10 phenols, and 13 others. The results can be used to discriminate the maturity grades of the leaves and ensure their quality.

A new perspective of the chemistry and kinetics of inactivation of COVID -19 coronavirus aerosols

In this paper we present a new approach to the mechanism of inactivation of enveloped virus aerosols. The analysis is in terms of oxidation of the lipid bilayer of the viral envelope through a free radical chain reaction. The rate kinetics of the process for various enveloped viruses have been compared and the indications are that the inactivations are closely related. Promoting virus inactivation with UV light is briefly reviewed and discussed as an extension of the chain reaction mechanism, which with physicochemical analyses give insights into the process and of reaction complexities. An outline of a practical method of achieving a 3-log10 level of deactivation in 1 min is described with purified air being returned to healthcare environments.

High-dimensional super-resolution imaging reveals heterogeneity and dynamics of subcellular lipid membranes

Lipid membranes are found in most intracellular organelles, and their heterogeneities play an essential role in regulating the organelles' biochemical functionalities. Here we report a Spectrum and Polarization Optical Tomography (SPOT) technique to study the subcellular lipidomics in live cells. Simply using one dye that universally stains the lipid membranes, SPOT can simultaneously resolve the membrane morphology, polarity, and phase from the three optical-dimensions of intensity, spectrum, and polarization, respectively. These high-throughput optical properties reveal lipid heterogeneities of ten subcellular compartments, at different developmental stages, and even within the same organelle. Furthermore, we obtain real-time monitoring of the multi-organelle interactive activities of cell division and successfully reveal their sophisticated lipid dynamics during the plasma membrane separation, tunneling nanotubules formation, and mitochondrial cristae dissociation. This work suggests research frontiers in correlating single-cell super-resolution lipidomics with multiplexed imaging of organelle interactome.

Localization of Double Bonds in Bacterial Glycerophospholipids Using 193 nm Ultraviolet Photodissociation in the Negative Mode

The need for detailed structural characterization of glycerophospholipids (GPLs) for many types of biologically motivated applications has led to the development of novel mass spectrometry-based methodologies that utilize alternative ion activation methods. Ultraviolet photodissociation (UVPD) has shown great utility for localizing sites of unsaturation within acyl chains and to date has predominantly been used for positive mode analysis of GPLs. In the present work, UVPD is used to localize sites of unsaturation in GPL anions. Similar to UVPD mass spectra of GPL cations, UVPD of deprotonated or formate-adducted GPLs yields diagnostic fragment ions spaced 24 Da apart. This method was integrated into a liquid chromatography workflow and used to evaluate profiles of sites of unsaturation of lipids in Escherichia coli (E. coli) and Acinetobacter baumannii (A. baumannii). When assigning sites of unsaturation, E. coli was found to contain all unsaturation elements at the same position relative to the terminal methyl carbon of the acyl chain; the first carbon participating in a site of unsaturation was consistently seven carbons along the acyl chain when counting carbons from the terminal methyl carbon. GPLs from A. baumannii exhibited more variability in locations of unsaturation. For GPLs containing sites of unsaturation in both acyl chains, an MS3 method was devised to assign sites to specific acyl chains.

A PI(4,5)P2-derived "gasoline engine model" for the sustained B cell receptor activation

To efficiently initiate activation responses against rare ligands in the microenvironment, lymphocytes employ sophisticated mechanisms involving signaling amplification. Recently, a signaling amplification mechanism initiated from phosphatidylinositol (PI) 4, 5-biphosphate [PI(4,5)P2] hydrolysis and synthesis for sustained B cell activation has been reported. Antigen and B cell receptor (BCR) recognition triggered the prompt reduction of PI(4,5)P2 density within the BCR microclusters, which led to the positive feedback for the synthesis of PI(4,5)P2 outside of the BCR microclusters. At single molecule level, the diffusion of PI(4,5)P2 was slow, allowing for the maintenance of a PI(4,5)P2 density gradient between the inside and outside of the BCR microclusters and the persistent supply of PI(4,5)P2 from outside to inside of the BCR microclusters. Here, we review studies that have contributed to uncovering the molecular mechanisms of PI(4,5)P2-derived signaling amplification model. Based on these studies, we proposed a "gasoline engine model" in which the activation of B cell signaling inside the microclusters is similar to the working principle of burning gasoline within the engine chamber of a gasoline engine. We also discuss the evidences showing the potential universality of this model and future prospects.

redLips: a comprehensive mechanistic model of the lipid metabolic network of yeast

Over the last decades, yeast has become a key model organism for the study of lipid biochemistry. Because the regulation of lipids has been closely linked to various physiopathologies, the study of these biomolecules could lead to new diagnostics and treatments. Before the field can reach this point, however, sufficient tools for integrating and analyzing the ever-growing availability of lipidomics data will need to be developed. To this end, genome-scale models (GEMs) of metabolic networks are useful tools, though their large size and complexity introduces too much uncertainty in the accuracy of predicted outcomes. Ideally, therefore, a model for studying lipids would contain only the pathways required for the proper analysis of these biomolecules, but would not be an ad hoc reduction. We hereby present a metabolic model that focuses on lipid metabolism constructed through the integration of detailed lipid pathways into an already existing GEM of Saccharomyces cerevisiae. Our model was then systematically reduced around the subsystems defined by these pathways to provide a more manageable model size for complex studies. We show that this model is as consistent and inclusive as other yeast GEMs regarding the focus and detail on the lipid metabolism, and can be used as a scaffold for integrating lipidomics data to improve predictions in studies of lipid-related biological functions.

Mass spectrometry imaging to detect lipid biomarkers and disease signatures in cancer

BACKGROUND

Current methods to identify, classify, and predict tumor behavior mostly rely on histology, immunohistochemistry, and molecular determinants. However, better predictive markers are required for tumor diagnosis and evaluation. Due, in part, to recent technological advancements, metabolomics and lipid biomarkers have become a promising area in cancer research. Therefore, there is a necessity for novel and complementary techniques to identify and visualize these molecular markers within tumors and surrounding tissue.

RECENT FINDINGS

Since its introduction, mass spectrometry imaging (MSI) has proven to be a powerful tool for mapping analytes in biological tissues. By adding the label-free specificity of mass spectrometry to the detailed spatial information of traditional histology, hundreds of lipids can be imaged simultaneously within a tumor. MSI provides highly detailed lipid maps for comparing intra-tumor, tumor margin, and healthy regions to identify biomarkers, patterns of disease, and potential therapeutic targets. In this manuscript, recent advancement in sample preparation and MSI technologies are discussed with special emphasis on cancer lipid research to identify tumor biomarkers.

CONCLUSION

MSI offers a unique approach for biomolecular characterization of tumor tissues and provides valuable complementary information to histology for lipid biomarker discovery and tumor classification in clinical and research cancer applications.

Ins and Outs of Interpreting Lipidomic Results

Membrane lipids are essential for life; however, research on how cells regulate cell lipid composition has been falling behind for quite some time. One reason was the difficulty in establishing analytical methods able to cope with the cell lipid repertoire. Development of a diversity of mass spectrometry-based technologies, including imaging mass spectrometry, has helped to demonstrate beyond doubt that the cell lipidome is not only greatly cell type dependent but also highly sensitive to any pathophysiological alteration such as differentiation or tumorigenesis. Interestingly, the current popularization of metabolomic studies among numerous disciplines has led many researchers to rediscover lipids. Hence, it is important to underscore the peculiarities of these metabolites and their metabolism, which are both radically different from protein and nucleic acid metabolism. Once differences in lipid composition have been established, researchers face a rather complex scenario, to investigate the signaling pathways and molecular mechanisms accounting for their results. Thus, a detail often overlooked, but of crucial relevance, is the complex networks of enzymes involved in controlling the level of each one of the lipid species present in the cell. In most cases, these enzymes are redundant and promiscuous, complicating any study on lipid metabolism, since the modification of one particular lipid enzyme impacts simultaneously on many species. Altogether, this review aims to describe the difficulties in delving into the regulatory mechanisms tailoring the lipidome at the activity, genetic, and epigenetic level, while conveying the numerous, stimulating, and sometimes unexpected research opportunities afforded by this type of studies.

Software tool for internal standard based normalization of lipids, and effect of data-processing strategies on resulting values

Background

Lipidomics, the comprehensive measurement of lipids within a biological system or substrate, is an emerging field with significant potential for improving clinical diagnosis and our understanding of health and disease. While lipids diverse biological roles contribute to their clinical utility, the diversity of lipid structure and concentrations prove to make lipidomics analytically challenging. Without internal standards to match each lipid species, researchers often apply individual internal standards to a broad range of related lipids. To aid in standardizing and automating this relative quantitation process, we developed LipidMatch Normalizer (LMN) http://secim.ufl.edu/secim-tools/ which can be used in most open source lipidomics workflows.

Results

LMN uses a ranking system (1–3) to assign lipid standards to target analytes. A ranking of 1 signifies that both the lipid class and adduct of the internal standard and target analyte match, while a ranking of 3 signifies that neither the adduct or class match. If multiple internal standards are provided for a lipid class, standards with the closest retention time to the target analyte will be chosen. The user can also signify which lipid classes an internal standard represents, for example indicating that ether-linked phosphatidylcholine can be semi-quantified using phosphatidylcholine. LMN is designed to work with any lipid identification software and feature finding software, and in this study is used to quantify lipids in NIST SRM 1950 human plasma annotated using LipidMatch and MZmine.

Conclusions

LMN can be integrated into an open source workflow which completes all data processing steps including feature finding, annotation, and quantification for LC-MS/MS studies. Using LMN we determined that in certain cases the use of peak height versus peak area, certain adducts, and negative versus positive polarity data can have major effects on the final concentration obtained.

Electronic supplementary material

The online version of this article (10.1186/s12859-019-2803-8) contains supplementary material, which is available to authorized users.

Lipidomic consequences of phospholipid synthesis defects in Escherichia coli revealed by HILIC-ion mobility-mass spectrometry

Our understanding of phospholipid biosynthesis in Gram-positive and Gram-negative bacteria is derived from the prototypical Gram-negative organism Escherichia coli. The inner and outer membranes of E. coli are largely composed of phosphatidylethanolamine (PE), minor amounts of phosphatidylglycerol (PG) and cardiolipin (CL). We report here the utility of hydrophilic interaction liquid chromatography (HILIC) paired with ion mobility-mass spectrometry (IM-MS) for the comprehensive analysis of the E. coli lipidome. Using strains with chromosomal deletions in the PG and CL synthesis genes pgsA and clsABC, respectively, we show that defective phospholipid biosynthesis in E. coli results in fatty-acid specific changes in select lipid classes and the presence of the minor triacylated phospholipids, acylphosphatidyl glycerol (acylPG) and N-acylphosphatidylethanolamine (N-acylPE). Notably, acylPGs were accumulated in the clsABC-KO strain, but were absent in other mutant strains. The separation of 1-lyso and 2-lyso-phosphatidylethanolamines (lysoPEs) is demonstrated in both the HILIC and IM dimensions. Using our previously validated calibration method, collision cross section values of nearly 200 phospholipids found in E. coli were determined on a traveling wave IM-MS platform, including newly reported values for cardiolipins, positional isomers of lysoPEs, acylPGs and N-acylPEs.

Quantitative analysis of 10 classes of phospholipids by ultrahigh-performance liquid chromatography tandem triple-quadrupole mass spectrometry

We have developed fast and sensitive label-free quantitation with normalization of acyl chain length to quantify 10 classes of phospholipids by UHPLC-MS.

Quantification of Lipids: Model, Reality, and Compromise

Lipids are key molecules in various biological processes, thus their quantification is a crucial point in a lot of studies and should be taken into account in lipidomics development. This family is complex and presents a very large diversity of structures, so analyzing and quantifying all this diversity is a real challenge. In this review, the different techniques to analyze lipids will be presented: from nuclear magnetic resonance (NMR) to mass spectrometry (with and without chromatography) including universal detectors. First of all, the state of the art of quantification, with the definitions of terms and protocol standardization, will be presented with quantitative lipidomics in mind, and then technical considerations and limitations of analytical chemistry's tools, such as NMR, mass spectrometry and universal detectors, will be discussed, particularly in terms of absolute quantification.

Optimization of Folch, Bligh-Dyer, and Matyash sample-to-extraction solvent ratios for human plasma-based lipidomics studies

In order to profile the lipidome for untargeted lipidomics applications, analysis by ultra-high performance liquid chromatography - high resolution mass spectrometry (UHPLC-HRMS) typically requires the extraction of lipid content from sample matrices using matrix-specific conditions. The Folch, Bligh-Dyer, and Matyash extraction methods, while promising approaches, were originally tailored to specific matrices (brain tissue, fish muscle, and E. coli, respectively). Each of these methods have specific solvent ratios that must be adhered to achieve optimal extraction. Thus, the sample-to-solvent ratios for these methods should be optimized for the sample matrix of interest prior to employment. This study evaluated the appropriate sample-to-extraction solvent ratios for human plasma-based lipidomics studies. An advantage of employing biphasic lipid extractions is the ability to investigate both the aqueous and organic layers for increased analyte coverage in untargeted studies. Therefore, this work also evaluated the multi-omic capability of each lipid extraction method for plasma in an effort to provide a workflow capable of increasing analyte coverage in a single extraction, thus providing a more complete understanding of complex biological systems. In plasma, a decrease in sample-to-solvent ratios from 1:4, 1:10, 1:20, to 1:100 (v/v) resulted in a gradual increase in the peak area of a diverse range of metabolite (aqueous layer) and lipid (organic layer) species for each extraction method up to the 1:20(v/v) sample-to-solvent ratio. The Bligh-Dyer and Folch methods yielded the highest peak areas at every plasma sample-to-solvent ratios for both metabolite and lipid species. Depending on the lipid class of interest, the Folch or Bligh-Dyer method is best suited for analysis of human plasma at a 1:20 (v/v) sample to total solvent ratio.

Membrane fluidity is regulated by the C. elegans transmembrane protein FLD-1 and its human homologs TLCD1/2

Dietary fatty acids are the main building blocks for cell membranes in animals, and mechanisms must therefore exist that compensate for dietary variations. We isolated C. elegans mutants that improved tolerance to dietary saturated fat in a sensitized genetic background, including eight alleles of the novel gene fld-1 that encodes a homolog of the human TLCD1 and TLCD2 transmembrane proteins. FLD-1 is localized on plasma membranes and acts by limiting the levels of highly membrane-fluidizing long-chain polyunsaturated fatty acid-containing phospholipids. Human TLCD1/2 also regulate membrane fluidity by limiting the levels of polyunsaturated fatty acid-containing membrane phospholipids. FLD-1 and TLCD1/2 do not regulate the synthesis of long-chain polyunsaturated fatty acids but rather limit their incorporation into phospholipids. We conclude that inhibition of FLD-1 or TLCD1/2 prevents lipotoxicity by allowing increased levels of membrane phospholipids that contain fluidizing long-chain polyunsaturated fatty acids.

Editorial note

This article has been through an editorial process in which the authors decide how to respond to the issues raised during peer review. The Reviewing Editor's assessment is that all the issues have been addressed (see decision letter).

Properties, metabolism and roles of sulfogalactosylglycerolipid in male reproduction

Sulfogalactosylglycerolipid (SGG, aka seminolipid) is selectively synthesized in high amounts in mammalian testicular germ cells (TGCs). SGG is an ordered lipid and directly involved in cell adhesion. SGG is indispensable for spermatogenesis, a process that greatly depends on interaction between Sertoli cells and TGCs. Spermatogenesis is disrupted in mice null for Cgt and Cst, encoding two enzymes essential for SGG biosynthesis. Sperm surface SGG also plays roles in fertilization. All of these results indicate the significance of SGG in male reproduction. SGG homeostasis is also important in male fertility. Approximately 50% of TGCs become apoptotic and phagocytosed by Sertoli cells. SGG in apoptotic remnants needs to be degraded by Sertoli lysosomal enzymes to the lipid backbone. Failure in this event leads to a lysosomal storage disorder and sub-functionality of Sertoli cells, including their support for TGC development, and consequently subfertility. Significantly, both biosynthesis and degradation pathways of the galactosylsulfate head group of SGG are the same as those of sulfogalactosylceramide (SGC), a structurally related sulfoglycolipid important for brain functions. If subfertility in males with gene mutations in SGG/SGC metabolism pathways manifests prior to neurological disorder, sperm SGG levels might be used as a reporting/predicting index of the neurological status.

Discovery of Lipidome Alterations Following Traumatic Brain Injury via High-Resolution Metabolomics

Traumatic brain injury (TBI) can occur across wide segments of the population, presenting in a heterogeneous manner that makes diagnosis inconsistent and management challenging. Biomarkers offer the potential to objectively identify injury status, severity, and phenotype by measuring the relative concentrations of endogenous molecules in readily accessible biofluids. Through a data-driven, discovery approach, novel biomarker candidates for TBI were identified in the serum lipidome of adult male Sprague-Dawley rats in the first week following moderate controlled cortical impact (CCI). Serum samples were analyzed in positive and negative modes by ultraperformance liquid chromatography-mass spectrometry (UPLC-MS). A predictive panel for the classification of injured and uninjured sera samples, consisting of 26 dysregulated species belonging to a variety of lipid classes, was developed with a cross-validated accuracy of 85.3% using omniClassifier software to optimize feature selection. Polyunsaturated fatty acids (PUFAs) and PUFA-containing diacylglycerols were found to be upregulated in sera from injured rats, while changes in sphingolipids and other membrane phospholipids were also observed, many of which map to known secondary injury pathways. Overall, the identified biomarker panel offers viable molecular candidates representing lipids that may readily cross the blood-brain barrier (BBB) and aid in the understanding of TBI pathophysiology.

Comprehensive study of rodent olfactory tissue lipid composition

The peripheral olfactory tissue (OT) plays a primordial role in the detection and transduction of olfactory information. Recent proteomic and transcriptomic studies have provided valuable insight into proteins and RNAs expressed in this tissue. Paradoxically, there is little information regarding the lipid composition of mammalian OT. To delve further into this issue, using a set of complementary state-of-the-art techniques, we carried out a comprehensive analysis of OT lipid composition in rats and mice fed with standard diets. The results showed that phospholipids are largely predominant, the major classes being phosphatidylcholine and phosphatidylethanolamine. Two types of plasmalogens, plasmenyl-choline and plasmenyl-ethanolamine, as well as gangliosides were also detected. With the exception of sphingomyelin, substantial levels of n-3 polyunsaturated fatty acids, mainly docosahexaenoic acid (22:6n-3; DHA), were found in the different phospholipid classes. These findings demonstrate that the rodent OT shares several features in common with other neural tissues, such as the brain and retina.

Plasma phospholipid profiling of a mouse model of anxiety disorder by hydrophilic interaction liquid chromatography coupled to high-resolution mass spectrometry

Glycerophospholipids (PLs), as amphipathic small molecules and the main constituents of biological membranes, play an important role in several cellular processes, even though their accurate identification from complex biological samples remains a challenge. In this paper, we report a fast and comprehensive HILIC-ESI-MS method for the analysis of glycerophospholipid classes using high-resolution mass spectrometry in negative mode. The final method enabled the quantitative analysis of 130 endogenous PL species in mouse plasma. The application of the method developed was to find differences of plasma PL composition in a mouse model of anxiety disorder. In the case of four PL classes and 35 PL species, significant differences were observed comparing low anxiety-related behavior with high anxiety-related behavior groups. The most characteristic trend was up-regulation in both the PL classes and PL species, and decreases were only detected in two phosphatidylcholines among 35 species in mice having elevated anxiety.

Probing molecular forces in multi-component physiological membranes

Biological membranes are remarkably heterogeneous, composed of diverse lipid mixtures with distinct chemical structure and composition. By combining molecular dynamics simulations and the newly developed Lipid-Force Distribution Analysis (L-FDA), we explore force transmission in complex multi-component membrane models mimicking eukaryotic organelles. We found that the chemical-moiety based segmentation at membrane interfaces revealed a distinctive distribution of bonded and non-bonded forces in diverse membrane environment. Our molecular stress analysis could have far-reaching implications in describing the relationship between membrane mechanical properties and functional states of chemically distinct lipids.

Selection of internal standards for accurate quantification of complex lipid species in biological extracts by electrospray ionization mass spectrometry-What, how and why?

Lipidomics is rapidly expanding because of the great facilitation of recent advances in, and novel applications of, electrospray ionization mass spectrometry techniques. The greatest demands have been for successful quantification of lipid classes, subclasses, and individual molecular species in biological samples at acceptable accuracy. This review addresses the selection of internal standards in different methods for accurate quantification of individual lipid species. The principles of quantification with electrospray ionization mass spectrometry are first discussed to recognize the essentials for quantification. The basics of different lipidomics approaches are overviewed to understand the variables that need to be considered for accurate quantification. The factors that affect accurate quantification are extensively discussed, and the solutions to resolve these factors are proposed-largely through addition of internal standards. Finally, selection of internal standards for different methods is discussed in detail to address the issues of what, how, and why related to internal standards. We believe that thorough discussion of the topics related to internal standards should aid in quantitative analysis of lipid classes, subclasses, and individual molecular species and should have big impacts on advances in lipidomics. © 2016 Wiley Periodicals, Inc. Mass Spec Rev 36:693-714, 2017.

Structure Annotation and Quantification of Wheat Seed Oxidized Lipids by High-Resolution LC-MS/MS

Lipid oxidation is a process ubiquitous in life, but the direct and comprehensive analysis of oxidized lipids has been limited by available analytical methods. We applied high-resolution liquid chromatography-mass spectrometry (LC-MS) and tandem mass spectrometry (MS/MS) to quantify oxidized lipids (glycerides, fatty acids, phospholipids, lysophospholipids, and galactolipids) and implemented a platform-independent high-throughput-amenable analysis pipeline for the high-confidence annotation and acyl composition analysis of oxidized lipids. Lipid contents of 90 different naturally aged wheat (Triticum aestivum) seed stocks were quantified in an untargeted high-resolution LC-MS experiment, resulting in 18,556 quantitative mass-to-charge ratio features. In a posthoc liquid chromatography-tandem mass spectrometry experiment, high-resolution MS/MS spectra (5 mD accuracy) were recorded for 8,957 out of 12,080 putatively monoisotopic features of the LC-MS data set. A total of 353 nonoxidized and 559 oxidized lipids with up to four additional oxygen atoms were annotated based on the accurate mass recordings (1.5 ppm tolerance) of the LC-MS data set and filtering procedures. MS/MS spectra available for 828 of these annotations were analyzed by translating experimentally known fragmentation rules of lipids into the fragmentation of oxidized lipids. This led to the identification of 259 nonoxidized and 365 oxidized lipids by both accurate mass and MS/MS spectra and to the determination of acyl compositions for 221 nonoxidized and 295 oxidized lipids. Analysis of 15-year aged wheat seeds revealed increased lipid oxidation and hydrolysis in seeds stored in ambient versus cold conditions.

Label-free measurement of the yeast short chain TAG lipase activity by ESI-MS after one-step esterification

Triacylglycerol (TAG) lipases hydrolyze ester bonds in TAG and release diacylglycerol (DAG), monoacylglycerol (MAG), and FA. We present a one-step chemical derivatization method for label-free quantification of a mixture of TAG, DAG, and MAG following lipase assay by ESI-MS. Because the ionization efficiencies of TAG, DAG, and MAG are not identical, lipase reaction products, DAG and MAG, are derivatized to TAG species by esterifying their hydroxyl groups using acyl chloride, whose acyl chain contains one less (or one more) -CH₂ group than that of substrate TAG. This resulted in three TAG species that were separated by 14 Da from one another and exhibited similar ion responses representing their molar amounts in the mass spectra. A good linear correlation was observed between peak intensity ratios and molar ratios in calibration curve. This method enables simultaneous quantification of TAG, DAG, and MAG in lipase assay and, in turn, allows stoichiometric determination of the concentrations of FAs released from TAG and DAG separately. By applying this strategy to measure both TAG and DAG lipolytic activities of the yeast Tgl2 lipase, we demonstrated its usefulness in studying enzymatic catalysis, as lipase enzymes often show dissimilar activities toward these lipids.

The translation of lipid profiles to nutritional biomarkers in the study of infant metabolism

INTRODUCTION

Links between early life exposures and later health outcomes may, in part, be due to nutritional programming in infancy. This hypothesis is supported by observed long-term benefits associated with breastfeeding, such as better cognitive development in childhood, and lower risks of obesity and high blood pressure in later life. However, the possible underlying mechanisms are expected to be complex and may be difficult to disentangle due to the lack of understanding of the metabolic processes that differentiate breastfed infants compared to those receiving just formula feed.

OBJECTIVE

Our aim was to investigate the relationships between infant feeding and the lipid profiles and to validate specific lipids in separate datasets so that a small set of lipids can be used as nutritional biomarkers.

METHOD

We utilized a direct infusion high-resolution mass spectrometry method to analyse the lipid profiles of 3.2 mm dried blood spot samples collected at age 3 months from the Cambridge Baby Growth Study (CBGS-1), which formed the discovery cohort. For validation two sample sets were profiled: Cambridge Baby Growth Study (CBGS-2) and Pregnancy Outcome Prediction Study (POPS). Lipidomic profiles were compared between infant groups who were either exclusively breastfed, exclusively formula-fed or mixed-fed at various levels. Data analysis included supervised Random Forest method with combined classification and regression mode. Selection of lipids was based on an iterative backward elimination procedure without compromising the class error in the classification mode.

CONCLUSION

From this study, we were able to identify and validate three lipids: PC(35:2), SM(36:2) and SM(39:1) that can be used collectively as biomarkers for infant nutrition during early development. These biomarkers can be used to determine whether young infants (3-6 months) are breast-fed or receive formula milk.

Hydrophilic interaction and reversed phase mixed-mode liquid chromatography coupled to high resolution tandem mass spectrometry for polar lipids analysis

A hydrophilic interaction liquid chromatography (HILIC) fused-core column (150×2.1mm ID, 2.7μm particle size) and a short reversed-phase liquid chromatography (RPLC) column (20mm×2.1mm ID, 1.9μm) were serially coupled to perform mixed-mode chromatography (MMC) on complex mixtures of phospholipids (PL). Mobile phase composition and gradient elution program were, preliminarily, optimized using a mixture of phosphatidylcholines (PC), phosphatidylethanolamines (PE), their corresponding lyso-forms (LPC and LPE), and sphingomyelins (SM). Thus a mixture of PC extracted from soybean was characterized by MMC coupled to electrospray ionization (ESI) high-resolution Fourier-transform mass spectrometry (FTMS) using an orbital trap analyzer. Several previously undiscovered PC, including positional isomers (i.e. 16:0/19:1 and 19:1/16:0) of PC 35:1 and skeletal isomers (i.e. 18:1/18:2 and 18:0/18:3) of PC 36:3 were identified. Therefore, high-resolution MS/MS spectra unveiled the occurrence of isomers for several overall side chain compositions. The proposed MMC-ESI-FTMS/MS approach revealed an unprecedented capability in disclosing complexity of an actual lipid extract, thus representing a very promising approach to lipidomics.

In vitro toxicity assessment of oral nanocarriers

The fascinating properties of nanomaterials opened new frontiers in medicine. Nanocarriers are useful systems in transporting drugs to site-specific targets. The unique physico-chemical characteristics making nanocarriers promising devices to treat diseases may also be responsible for potential adverse effects. In order to develop functional nano-based drug delivery systems, efficacy and safety should be carefully evaluated. To date, no common testing strategy to address nanomaterial toxicological challenges has been generated. Different cell culture models are currently used to evaluate nanocarrier safety using conventional in vitro assays, but overall they have generated a huge amount of conflicting data. In this review we describe state-of-the-art approaches for in vitro testing of orally administered nanocarriers, highlighting the importance of developing harmonized and validated standard operating procedures. These procedures should be applied in a safe-by-design context with the aim to reduce and/or eliminate the uncertainties and risks associated with nanomedicine development.

Loss-of-function screens of druggable targetome against cancer stem-like cells

Cancer stem–like cells (CSLCs) contribute to the initiation and recurrence of tumors and to their resistance to conventional therapies. In this study, small interfering RNA (siRNA)-based screening of ∼4800 druggable genes in 3-dimensional CSLC cultures in comparison to 2-dimensional bulk cultures of U87 glioma cells revealed 3 groups of genes essential for the following: survival of the CSLC population only, bulk-cultured population only, or both populations. While diverse biologic processes were associated with siRNAs reducing the bulk-cultured population, CSLC-eliminating siRNAs were enriched in a few functional categories, such as lipid metabolism, protein metabolism, and gene expression. Interestingly, siRNAs that selectively reduced CSLC only were found to target genes for cholesterol and unsaturated fatty acid synthesis. The lipidomic profile of CSLCs revealed increased levels of monounsaturated lipids. Pharmacologic blockage of these target pathways reduced CSLCs, and this effect was eliminated by addition of downstream metabolite products. The present CSLC-sensitive target categories provide a useful resource that can be exploited for the selective elimination of CSLCs.—Song, M., Lee, H., Nam, M.-H., Jeong, E., Kim, S., Hong, Y., Kim, N., Yim, H. Y., Yoo, Y.-J., Kim, J. S., Kim, J.-S., Cho, Y.-Y., Mills, G. B., Kim, W.-Y., Yoon, S. Loss-of-function screens of druggable targetome against cancer stem–like cells.

Lipidomic investigation of eggs' yolk: Changes in lipid profile of eggs from different conditions

Eggs are one of the main foods eaten worldwide. Nutritionally they are one of the main sources of dietary lipids, impacting human health. Egg yolk lipid composition changes depending on different conditions associated with hens raising. Therefore, the purpose of our work was to use a lipidomic approach as a tool to evaluate if different diets (vegetable versus animal) and raising environments (free range versus indoor) interfere in the triacylglycerol (TAG) and phospholipid (PL) profiles of eggs' yolks and to use such differences to differentiate eggs according to their origin. To achieve that goal, total lipid extracts were obtained and then fractionated by solid-phase chromatography. TAGs fraction was analysed by ESI-MS and PLs fraction by HILIC-LC-MS/MS. TAG and five PL classes were identified, namely PC, LPC, PE, LPE and SM. Fatty acids (FA) esterified to the glycerol backbone of PL ranged between C16:0 and C22:6. On the other hand, FA esterified to TAG ranged from C14:0 to C20:0. Major differences on the PL profile were observed regarding eggs from free-range hens and fed with vegetable origin food and eggs from the remaining conditions, once the former presented higher levels of PC (O-34:0), PC (34:1) and PE (34:1). Eggs from hens fed with animal origin food contained PL and TAG molecular species richer in n-6 FA, according to GC-MS and to LC-MS/MS data. The lipidomic approach used herein proved to be promising in differentiating eggs from hens with different raising conditions.