Imputation of missing values in lipidomic datasets.

Lipidomic data often exhibit missing data points, which can be categorized as missing completely at random (MCAR), missing at random, or missing not at random (MNAR). In order to utilize statistical methods that require complete datasets or to improve the identification of potential effects in statistical comparisons, imputation techniques can be employed. In this study, we investigate commonly used methods such as zero, half-minimum, mean, and median imputation, as well as more advanced techniques such as k-nearest neighbor and random forest imputation. We employ a combination of simulation-based approaches and application to real datasets to assess the performance and effectiveness of these methods. Shotgun lipidomics datasets exhibit high correlations and missing values, often due to low analyte abundance, characterized as MNAR. In this context, k-nearest neighbor approaches based on correlation and truncated normal distributions demonstrate best performance. Importantly, both methods can effectively impute missing values independent of the type of missingness, the determination of which is nearly impossible in practice. The imputation methods still control the type I error rate.

Differential lipid analysis of oxaliplatin-sensitive and resistant HCT116 cells reveals different levels of drug-induced lipid droplet formation.

Lipid droplets (LDs) are intracellular storage vesicles composed of a neutral lipid core surrounded by a glycerophospholipid membrane. LD accumulation is associated with different stages of cancer progression and stress responses resulting from chemotherapy. In previous work, a novel dual nano-electrospray ionization source and data-dependent acquisition method for measuring the relative abundances of lipid species between two extracts were described and validated. Here, this same source and method were used to determine if oxaliplatin-sensitive and resistant cells undergo similar lipid profile changes, with the goal of identifying potential signatures that could predict the effectiveness of an oxaliplatin-containing treatment. Oxaliplatin is commonly used in the treatment of colorectal cancer. When compared to a no-drug control, oxaliplatin dosing caused significant increases in triglyceride (TG) and cholesterol ester (CE) species. These increases were more pronounced in the oxaliplatin-sensitive cells than in oxaliplatin-resistant cells. The increased neutral lipid abundance correlated with LD formation, as confirmed by confocal micrographs of Nile Red-stained cells. Untargeted proteomic analyses also support LD formation after oxaliplatin treatment, with an increased abundance of LD-associated proteins in both the sensitive and resistant cells.

FACS-assisted single-cell lipidome analysis of phosphatidylcholines and sphingomyelins in cells of different lineages.

Recent advances in single-cell genomics and transcriptomics technologies have transformed our understanding of cellular heterogeneity in growth, development, ageing, and disease; however, methods for single-cell lipidomics have comparatively lagged behind in development. We have developed a method for the detection and quantification of a wide range of phosphatidylcholine and sphingomyelin species from single cells that combines fluorescence-assisted cell sorting with automated chip-based nanoESI and shotgun lipidomics. We show herein that our method is capable of quantifying more than 50 different phosphatidylcholine and sphingomyelin species from single cells and can easily distinguish between cells of different lineages or cells treated with exogenous fatty acids. Moreover, our method can detect more subtle differences in the lipidome between cell lines of the same cancer type. Our approach can be run in parallel with other single-cell technologies to deliver near-complete, high-throughput multi-omics data on cells with a similar phenotype and has the capacity to significantly advance our current knowledge on cellular heterogeneity.

Elevated lipid class concentrations in females with anorexia nervosa before and after intensive weight restoration treatment-A lipidomics study.

OBJECTIVE: To study the plasma lipidome of patients with anorexia nervosa (AN) before and after weight restoration treatment and report associations with AN subtypes and oral contraceptive pill (OCP) usage. METHODS: Quantitative shotgun lipidomics analysis was used to study plasma lipids of 50 female patients with AN before and after weight restoration treatment and 50 healthy female controls (HC). The AN group was assessed with blood samples and questionnaires before and after weight restoration. RESULTS: In total we quantified 260 lipid species representing 26 lipid classes of which 13 lipid class concentrations were elevated in patients with AN at admission compared with HC. Lipid classes remained elevated after weight restoration treatment of 84 days (median; interquartile range 28), and only the concentration of the ceramide lipid class increased between pre- and post-treatment (p = .03), whereas lysophosphatidylcholine (LPC, p = .02), ether-linked Phosphatidylcholine (LPCO, p = .02), and lysophosphatidylethanolamine (LPE, p = .009) decreased. CONCLUSION: In AN, 13 out of 26 lipid class concentrations were elevated at admission and remained elevated post-treatment. Ceramides increased further between pre- and post-weight restoration treatment, which could be related to the rapid weight gain during re-nutrition. Further research is needed to elucidate the effects of weight restoration treatment on short- and long-term lipid profiles in individuals with AN. PUBLIC SIGNIFICANCE STATEMENT: Lipidomics research can increase the understanding of AN, a complex and potentially life-threatening eating disorder. By analyzing lipids, or fats, in the body, we can identify biological markers that may inform diagnosis and develop more effective treatments. This research can also shed light on the underlying mechanisms of the disorder, leading to a better understanding of the processes involved in eating behavior.

Can cardiolipins be used as a biomarker for arbuscular mycorrhizal fungi?

Specific biomarker molecules are increasingly being used for detection and quantification in plant and soil samples of arbuscular mycorrhizal (AM) fungi, an important and widespread microbial guild heavily implicated in transfers of nutrients and carbon between plants and soils and in the maintenance of soil physico-chemical properties. Yet, concerns have previously been raised as to the validity of a range of previously used approaches (e.g., microscopy, AM-specific fatty acids, sterols, glomalin-like molecules, ribosomal DNA sequences), justifying further research into novel biomarkers for AM fungal abundance and/or functioning. Here, we focused on complex polar lipids contained in pure biomass of Rhizophagus irregularis and in nonmycorrhizal and mycorrhizal roots of chicory (Cichorium intybus), leek (Allium porrum), and big bluestem (Andropogon gerardii). The lipids were analyzed by shotgun lipidomics using a high-resolution hybrid mass spectrometer. Size range between 1350 and 1550 Da was chosen for the detection of potential biomarkers among cardiolipins (1,3-bis(sn-3'-phosphatidyl)-sn-glycerols), a specific class of phospholipids. The analysis revealed a variety of molecular species, including cardiolipins containing one or two polyunsaturated fatty acids with 20 carbon atoms each, i.e., arachidonic and/or eicosapentaenoic acids, some of them apparently specific for the mycorrhizal samples. Although further verification using a greater variety of AM fungal species and samples from various soils/ecosystems/environmental conditions is needed, current results suggest the possibility to identify novel biochemical signatures specific for AM fungi within mycorrhizal roots. Whether they could be used for quantification of both root and soil colonization by the AM fungi merits further scrutiny.

The foundations and development of lipidomics.

For over a century, the importance of lipid metabolism in biology was recognized but difficult to mechanistically understand due to the lack of sensitive and robust technologies for identification and quantification of lipid molecular species. The enabling technological breakthroughs emerged in the 1980s with the development of soft ionization methods (Electrospray Ionization and Matrix Assisted Laser Desorption/Ionization) that could identify and quantify intact individual lipid molecular species. These soft ionization technologies laid the foundations for what was to be later named the field of lipidomics. Further innovative advances in multistage fragmentation, dramatic improvements in resolution and mass accuracy, and multiplexed sample analysis fueled the early growth of lipidomics through the early 1990s. The field exponentially grew through the use of a variety of strategic approaches, which included direct infusion, chromatographic separation, and charge-switch derivatization, which facilitated access to the low abundance species of the lipidome. In this Thematic Review, we provide a broad perspective of the foundations, enabling advances, and predicted future directions of growth of the lipidomics field.

Nonalcoholic fatty liver disease stratification by liver lipidomics.

Nonalcoholic fatty liver disease (NAFLD) is a common metabolic dysfunction leading to hepatic steatosis. However, NAFLD's global impact on the liver lipidome is poorly understood. Using high-resolution shotgun mass spectrometry, we quantified the molar abundance of 316 species from 22 major lipid classes in liver biopsies of 365 patients, including nonsteatotic patients with normal or excessive weight, patients diagnosed with NAFL (nonalcoholic fatty liver) or NASH (nonalcoholic steatohepatitis), and patients bearing common mutations of NAFLD-related protein factors. We confirmed the progressive accumulation of di- and triacylglycerols and cholesteryl esters in the liver of NAFL and NASH patients, while the bulk composition of glycerophospho- and sphingolipids remained unchanged. Further stratification by biclustering analysis identified sphingomyelin species comprising n24:2 fatty acid moieties as membrane lipid markers of NAFLD. Normalized relative abundance of sphingomyelins SM 43:3;2 and SM 43:1;2 containing n24:2 and n24:0 fatty acid moieties, respectively, showed opposite trends during NAFLD progression and distinguished NAFL and NASH lipidomes from the lipidome of nonsteatotic livers. Together with several glycerophospholipids containing a C22:6 fatty acid moiety, these lipids serve as markers of early and advanced stages of NAFL.

Restoring mitochondrial superoxide levels with elamipretide (MTP-131) protects db/db mice against progression of diabetic kidney disease.

Exposure to chronic hyperglycemia because of diabetes mellitus can lead to development and progression of diabetic kidney disease (DKD). We recently reported that reduced superoxide production is associated with mitochondrial dysfunction in the kidneys of mouse models of type 1 DKD. We also demonstrated that humans with DKD have significantly reduced levels of mitochondrion-derived metabolites in their urine. Here we examined renal superoxide production in a type 2 diabetes animal model, the db/db mouse, and the role of a mitochondrial protectant, MTP-131 (also called elamipretide, SS-31, or Bendavia) in restoring renal superoxide production and ameliorating DKD. We found that 18-week-old db/db mice have reduced renal and cardiac superoxide levels, as measured by dihydroethidium oxidation, and increased levels of albuminuria, mesangial matrix accumulation, and urinary H2O2 Administration of MTP-131 significantly inhibited increases in albuminuria, urinary H2O2, and mesangial matrix accumulation in db/db mice and fully preserved levels of renal superoxide production in these mice. MTP-131 also reduced total renal lysocardiolipin and major lysocardiolipin subspecies and preserved lysocardiolipin acyltransferase 1 expression in db/db mice. These results indicate that, in type 2 diabetes, DKD is associated with reduced renal and cardiac superoxide levels and that MTP-131 protects against DKD and preserves physiological superoxide levels, possibly by regulating cardiolipin remodeling.

Mass Spectrometry-Based Shotgun Lipidomics for Cancer Research.

Shotgun lipidomics is an analytical approach for large-scale and systematic analysis of the composition, structure, and quantity of cellular lipids directly from lipid extracts of biological samples by mass spectrometry. This approach possesses advantages of high throughput and quantitative accuracy, especially in absolute quantification. As cancer research deepens at the level of quantitative biology and metabolomics, the demand for lipidomics approaches such as shotgun lipidomics is becoming greater. In this chapter, the principles, approaches, and some applications of shotgun lipidomics for cancer research are overviewed.

Lipidomics: Techniques, Applications, and Outcomes Related to Biomedical Sciences.

Lipidomics is a newly emerged discipline that studies cellular lipids on a large scale based on analytical chemistry principles and technological tools, particularly mass spectrometry. Recently, techniques have greatly advanced and novel applications of lipidomics in the biomedical sciences have emerged. This review provides a timely update on these aspects. After briefly introducing the lipidomics discipline, we compare mass spectrometry-based techniques for analysis of lipids and summarize very recent applications of lipidomics in health and disease. Finally, we discuss the status of the field, future directions, and advantages and limitations of the field.

Strategies to Improve/Eliminate the Limitations in Shotgun Lipidomics.

Direct infusion-based shotgun lipidomics is one of the most powerful and useful tools in comprehensive analysis of lipid species from lipid extracts of various biological samples with high accuracy/precision. However, despite many advantages, the classical shotgun lipidomics suffers some general dogmas of limitations, such as ion suppression, ambiguous identification of isobaric/isomeric lipid species, and ion source-generated artifacts, restraining the applications in analysis of low-abundance lipid species, particularly those less ionizable or isomers that yield almost identical fragmentation patterns. This article reviews the strategies (such as modifier addition, prefractionation, chemical derivatization, charge feature utilization) that have been employed to improve/eliminate these limitations in modern shotgun lipidomics approaches (e.g., high mass resolution mass spectrometry-based and multidimensional mass spectrometry-based shotgun lipidomics). Therefore, with the enhancement of these strategies for shotgun lipidomics, comprehensive analysis of lipid species including isomeric/isobaric species is achieved in a more accurate and effective manner, greatly substantiating the aberrant lipid metabolism, signaling trafficking, and homeostasis under pathological conditions.

Lipidomics from sample preparation to data analysis: a primer.

Lipids are amongst the most important organic compounds in living organisms, where they serve as building blocks for cellular membranes as well as energy storage and signaling molecules. Lipidomics is the science of the large-scale determination of individual lipid species, and the underlying analytical technology that is used to identify and quantify the lipidome is generally mass spectrometry (MS). This review article provides an overview of the crucial steps in MS-based lipidomics workflows, including sample preparation, either liquid-liquid or solid-phase extraction, derivatization, chromatography, ion-mobility spectrometry, MS, and data processing by various software packages. The associated concepts are discussed from a technical perspective as well as in terms of their application. Furthermore, this article sheds light on recent advances in the technology used in this field and its current limitations. Particular emphasis is placed on data quality assurance and adequate data reporting; some of the most common pitfalls in lipidomics are discussed, along with how to circumvent them.

Recent progresses of derivatization approaches in the targeted lipidomics analysis by mass spectrometry.

Lipidomics plays an essential role in the development of an improved understanding of lipids metabolism and the identification of new biomarkers or therapeutic targets of related diseases. The strong analytical power of mass spectrometry and its rapid developments in the respect of instruments and techniques have significantly accelerated the emerging lipidomics and related application fields in biology, medicine, and pharmacy. The strategy of chemical derivatization can remarkably improve the shortcomings of mass spectrometric analytical technologies of shotgun lipidomics and liquid chromatography mass spectrometry, and in the past decade many related studies have been reported for fatty acids, glycerophospholipids, sphingomyelins, monoglycerides, diacylglycerols, long-chain bases, steroids, and so on. Therefore, this review will focus on new chemical derivatization approaches about the research progresses of shotgun-based and liquid chromatography mass spectrometry-based targeted lipidomics (from 2005 to July 2019, most of reports emerged in the past 5 years), and put forward the problems and prospects in this field. It is expected to be helpful for the design and synthesis of new derivatization reagents, especially the outstanding stable isotope labeling derivatization reagents, and the development and application of new chemical derivatization strategies and matched mass spectrometric analysis methods.

Ceramide subclasses identified as novel lipid biomarker elevated in women with polycystic ovary syndrome: a pilot study employing shotgun lipidomics.

This study aimed to identify potential lipid biomarkers in women with polycystic ovary syndrome (PCOS) and determine their predictive value for PCOS. Eighteen women with PCOS and 17 healthy controls were enrolled. A multi-dimensional mass spectrometry-based shotgun lipidomics approach was employed to analyze serum lipid profiles. Shotgun lipidomics revealed that the concentrations of ceramide (Cer) and phosphatidylcholine (PC) were higher (PC: 831.6 ± 217.4 vs. 605.2 ± 164.2 µmol/l; Cer: 3,387.6 ± 829.9 vs. 2,552.2 ± 679.4 nmol/l, respectively), whereas that of lysophosphatidylcholine was lower, in PCOS women than in healthy controls (82.02 ± 39.49 vs. 133.62 ± 65.36 µmol/l, respectively). Receiver operating characteristic analysis showed that the combination of Cer (OH_N16:0/N18:0) and Cer (N22:0) had the greatest discriminatory power to differentiate between women with and without PCOS (area under the curve: 0.889, 95% confidence interval: 0.784-0.994). These results indicate that the combination of Cer (OH_N16:0/N18:0) and Cer (N22:0) may represent a novel lipid predictor of PCOS.

Cytochrome c is an oxidative stress-activated plasmalogenase that cleaves plasmenylcholine and plasmenylethanolamine at the sn-1 vinyl ether linkage.

Plasmalogens are phospholipids critical for cell function and signaling that contain a vinyl ether linkage at the sn-1 position and are highly enriched in arachidonic acid (AA) at the sn-2 position. However, the enzyme(s) responsible for the cleavage of the vinyl ether linkage in plasmalogens has remained elusive. Herein, we report that cytochrome c, in the presence of either cardiolipin (CL), O2 and H2O2, or oxidized CL and O2, catalyzes the oxidation of the plasmalogen vinyl ether linkage, promoting its hydrolytic cleavage and resultant production of 2-AA-lysolipids and highly reactive α-hydroxy fatty aldehydes. Using stable isotope labeling in synergy with strategic chemical derivatizations and high-mass-accuracy MS, we deduced the chemical mechanism underlying this long sought-after reaction. Specifically, labeling with either 18O2 or H218O, but not with H218O2, resulted in M + 2 isotopologues of the α-hydroxyaldehyde, whereas reactions with both 18O2 and H218O identified the M + 4 isotopologue. Furthermore, incorporation of 18O from 18O2 was predominantly located at the α-carbon. In contrast, reactions with H218O yielded 18O linked to the aldehyde carbon. Importantly, no significant labeling of 2-AA-lysolipids with 18O2, H218O, or H218O2 was present. Intriguingly, phosphatidylinositol phosphates (PIP2 and PIP3) effectively substituted for cardiolipin. Moreover, cytochrome c released from myocardial mitochondria subjected to oxidative stress cleaved plasmenylcholine in membrane bilayers, and this was blocked with a specific mAb against cytochrome c Collectively, these results identify the first plasmalogenase in biology, reveal the production of previously unanticipated signaling lipids by cytochrome c, and present new perspectives on cellular signaling during oxidative stress.

Novel strategies for enhancing shotgun lipidomics for comprehensive analysis of cellular lipidomes.

Shotgun lipidomics is one of the most powerful tools in analysis of cellular lipidomes in lipidomics, which directly analyzes lipids from lipid extracts of diverse biological samples with high accuracy/precision. However, despite its great advances in high throughput analysis of cellular lipidomes, low coverage of poorly ionized lipids, especially those species in very low abundance, and some types of isomers within complex lipid extracts by shotgun lipidomics remains a huge challenge. In the past few years, many strategies have been developed to enhance shotgun lipidomics for comprehensive analysis of lipid species. Chemical derivatization represents one of the most attractive and effective strategies, already receiving considerable attention. This review focuses on novel advanced derivatization strategies for enhancing shotgun lipidomics. It is anticipated that with the development of enhanced strategies, shotgun lipidomics can make greater contributions to biological and biomedical research.

Analytical challenges of shotgun lipidomics at different resolution of measurements.

The essence of shotgun lipidomics is to maintain consistency of the chemical environment of lipid samples during mass spectrometry acquisition. This strategy is suitable for large-scale quantitative analysis. This strategy also allows sufficient time to collect data to improve the signal-to-noise ratio. The initial approach of shotgun lipidomics was the electrospray ionization (ESI)-based direct infusion mass spectrometry strategy. With development of mass spectrometry for small molecules, shotgun lipidomics methods have been extended to matrix-assisted laser desorption/ionization mass spectrometry (MALDI MS) and ambient mass spectrometry, including MS imaging methods. Furthermore, the object of analysis has extended from organ and body fluid levels to tissue and cell levels with technological developments. In this article, we summarize the status and technical challenges of shotgun lipidomics at different resolution of measurements from the mass spectrometry perspective.

The evolution of lipidomics through space and time.

Although the foundations of mass spectrometry-based lipidomics have been practiced for over 30 years, recent technological advances in ionization modalities in conjunction with robust increases in mass accuracy and resolution have greatly accelerated the emergence, growth and importance of the field of lipidomics. Moreover, advances in the separation sciences, bioinformatic strategies and the availability of robust databases have been synergistically integrated into modern lipidomic technologies leading to unprecedented improvements in the depth, penetrance and precision of lipidomic analyses and identification of their biological and mechanistic significance. The purpose of this "opinion" article is to briefly review the evolution of lipidomics, critique the platforms that have evolved and identify areas that are likely to emerge in the years to come. Through seamlessly integrating a rich repertoire of mass spectrometric, chemical and bioinformatic strategies, the chemical identities and quantities of tens of thousands to hundreds of thousands of different lipid molecular species and their metabolic alterations during physiologic or pathophysiologic perturbations can be obtained. Thus, the field of lipidomics which already has a distinguished history of exciting new discoveries in many disease states holds unparalleled potential to identify the pleiotropic roles of lipids in health and disease at the chemical level. This article is part of a Special Issue entitled: BBALIP_Lipidomics Opinion Articles edited by Sepp Kohlwein.

The lipidome associated with the γ-secretase complex is required for its integrity and activity.

γ-Secretase is a multi-subunit membrane protease complex that catalyses the final intramembrane cleavage of the ß-amyloid precursor protein (APP) during the neuronal production of amyloid-ß peptides (Aß), which are implicated as the causative agents of Alzheimer's disease (AD). In the present study, we report the reconstitution of a highly purified, active γ-secretase complex into proteoliposomes without exogenous lipids and provide the first direct evidence for the existence of a microenvironment of 53 molecular species from 11 major lipid classes specifically associated with the γ-secretase complex, including phosphatidylcholine and cholesterol. Importantly, we demonstrate that the pharmacological modulation of certain phospholipids abolishes both the integrity and the enzymatic activity of the intramembrane protease. Together, our findings highlight the importance of a specific lipid microenvironment for the structure and function of γ-secretase.

Quantitation of isobaric phosphatidylcholine species in human plasma using a hybrid quadrupole linear ion-trap mass spectrometer.

Phosphatidylcholine (PC) species in human plasma are used as biomarkers of disease. PC biomarkers are often limited by the inability to separate isobaric PCs. In this work, we developed a targeted shotgun approach for analysis of isobaric and isomeric PCs. This approach is comprised of two MS methods: a precursor ion scanning (PIS) of mass m/z 184 in positive mode (PIS m/z +184) and MS3 fragmentation in negative mode, both performed on the same instrument, a hybrid triple quadrupole ion-trap mass spectrometer. The MS3 experiment identified the FA composition and the relative abundance of isobaric and sn-1, sn-2 positional isomeric PC species, which were subsequently combined with absolute quantitative data obtained by PIS m/z +184 scan. This approach was applied to the analysis of a National Institute of Standards and Technology human blood plasma standard reference material (SRM 1950). We quantified more than 70 PCs and confirmed that a majority are present in isobaric and isomeric mixtures. The FA content determined by this method was comparable to that obtained using GC with flame ionization detection, supporting the quantitative nature of this MS method. This methodology will provide more in-depth biomarker information for clinical and mechanistic studies.