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.     

Comprehensive Metabolomic,Lipidomic and Microscopic Profiling of Yarrowia lipolytica during Lipid Accumulation Identifies Targets for Increased Lipogenesis

Yarrowia lipolytica is an oleaginous ascomycete yeast that accumulates large amounts of lipids and has potential as a biofuel producing organism. Despite a growing scientific literature focused on lipid production by Y. lipolytica, there remain significant knowledge gaps regarding the key biological processes involved. We applied a combination of metabolomic and lipidomic profiling approaches as well as microscopic techniques to identify and characterize the key pathways involved in de novo lipid accumulation from glucose in batch cultured, wild-type Y. lipolytica. We found that lipids accumulated rapidly and peaked at 48 hours during the five day experiment, concurrent with a shift in amino acid metabolism. We also report that exhaustion of extracellular sugars coincided with thickening of the cell wall, suggesting that genes involved in cell wall biogenesis may be a useful target for improving the efficiency of lipid producing yeast strains.     

Top-down lipidomics of low density lipoprotein reveal altered lipid profiles in advanced chronic kidney disease

This study compared the molecular lipidomic profile of LDL in patients with nondiabetic advanced renal disease and no evidence of CVD to that of age-matched controls, with the hypothesis that it would reveal proatherogenic lipid alterations. LDL was isolated from 10 normocholesterolemic patients with stage 4/5 renal disease and 10 controls, and lipids were analyzed by accurate mass LC/MS. Top-down lipidomics analysis and manual examination of the data identified 352 lipid species, and automated comparative analysis demonstrated alterations in lipid profile in disease. The total lipid and cholesterol content was unchanged, but levels of triacylglycerides and N-acyltaurines were significantly increased, while phosphatidylcholines, plasmenyl ethanolamines, sulfatides, ceramides, and cholesterol sulfate were significantly decreased in chronic kidney disease (CKD) patients. Chemometric analysis of individual lipid species showed very good discrimination of control and disease sample despite the small cohorts and identified individual unsaturated phospholipids and triglycerides mainly responsible for the discrimination. These findings illustrate the point that although the clinical biochemistry parameters may not appear abnormal, there may be important underlying lipidomic changes that contribute to disease pathology. The lipidomic profile of CKD LDL offers potential for new biomarkers and novel insights into lipid metabolism and cardiovascular risk in this disease.     

Differential Network Analysis with Multiply Imputed Lipidomic Data

The importance of lipids for cell function and health has been widely recognized, e.g., a disorder in the lipid composition of cells has been related to atherosclerosis caused cardiovascular disease (CVD). Lipidomics analyses are characterized by large yet not a huge number of mutually correlated variables measured and their associations to outcomes are potentially of a complex nature. Differential network analysis provides a formal statistical method capable of inferential analysis to examine differences in network structures of the lipids under two biological conditions. It also guides us to identify potential relationships requiring further biological investigation. We provide a recipe to conduct permutation test on association scores resulted from partial least square regression with multiple imputed lipidomic data from the LUdwigshafen RIsk and Cardiovascular Health (LURIC) study, particularly paying attention to the left-censored missing values typical for a wide range of data sets in life sciences. Left-censored missing values are low-level concentrations that are known to exist somewhere between zero and a lower limit of quantification. To make full use of the LURIC data with the missing values, we utilize state of the art multiple imputation techniques and propose solutions to the challenges that incomplete data sets bring to differential network analysis. The customized network analysis helps us to understand the complexities of the underlying biological processes by identifying lipids and lipid classes that interact with each other, and by recognizing the most important differentially expressed lipids between two subgroups of coronary artery disease (CAD) patients, the patients that had a fatal CVD event and the ones who remained stable during two year follow-up.     

Exploring the lipoprotein composition using Bayesian regression on serum lipidomic profiles

MOTIVATION: Serum lipids have been traditionally studied in the context of lipoprotein particles. Today's emerging lipidomics technologies afford sensitive detection of individual lipid molecular species, i.e. to a much greater detail than the scale of lipoproteins. However, such global serum lipidomic profiles do not inherently contain any information on where the detected lipid species are coming from. Since it is too laborious and time consuming to routinely perform serum fractionation and lipidomics analysis on each lipoprotein fraction separately, this presents a challenge for the interpretation of lipidomic profile data. An exciting and medically important new bioinformatics challenge today is therefore how to build on extensive knowledge of lipid metabolism at lipoprotein levels in order to develop better models and bioinformatics tools based on high-dimensional lipidomic data becoming available today. RESULTS: We developed a hierarchical Bayesian regression model to study lipidomic profiles in serum and in different lipoprotein classes. As a background data for the model building, we utilized lipidomic data for each of the lipoprotein fractions from 5 subjects with metabolic syndrome and 12 healthy controls. We clustered the lipid profiles and applied a regression model within each cluster separately. We found that the amount of a lipid in serum can be adequately described by the amounts of lipids in the lipoprotein classes. In addition to improved ability to interpret lipidomic data, we expect that our approach will also facilitate dynamic modelling of lipid metabolism at the individual molecular species level.     

A Lipidomic Study of the Effects of N-methyl-N′-nitro-N-nitrosoguanidine on Sphingomyelin Metabolism

Systems biology is a new and rapidly developing research area in which,by quantitativelydescribing the interaction among all the individual components of a cell,a systems-level understanding of abiological response can be achieved.Therefore,it requires high-throughput measurement technologies forbiological molecules,such as genomic and proteomic approaches for DNA/RNA and protein,respectively.Recently,a new concept,lipidomics,which utilizes the mass spectrometry(MS)method for lipid analysis,has been proposed.Using this lipidomic approach,the effects of N-methyl-N'-nitro-N-nitrosoguanidine(MNNG)on sphingomyelin metabolism,a major class of sphingolipids,were evaluated.Sphingomyelin moleculeswere extracted from cells and analyzed by matrix-assisted laser desorption ionization-time of flight MS.Itwas found that MNNG induced profound changes in sphingomyelin metabolism,including the appearance ofsome new sphingomyelin species and the disappearance of some others,and the concentrations of severalsphmgomyelin species also changed.This was accompanied by the redistribution of acid sphingomyelinase(ASM),a key player in sphingomyelin metabolism.On the other hand,imipramine,an inhibitor of ASM,caused the accumulation of sphingomyelin.It also prevented some of the effects of MNNG,as well as theredistribution of ASM.Taken together,these data suggested that the lipidomic approach is highly effectivefor the systematic analysis of cellular lipids metabolism.     

A Lipidomic Study of the Effects of N-methyl-N＇-nitro-N-nitrosoguanidine on Sphingomyelin Metabolism

Systems biology is a new and rapidly developing research area in which, by quantitatively describing the interaction among all the individual components of a cell, a systems-level understanding of a biological response can be achieved. Therefore, it requires high-throughput measurement technologies for biological molecules, such as genomic and proteomic approaches for DNA/RNA and protein, respectively.Recently, a new concept, lipidomics, which utilizes the mass spectrometry （MS） method for lipid analysis,has been proposed. Using this lipidomic approach, the effects of N-methyl-N＇-nitro-N-nitrosoguanidine （MNNG） on sphingomyelin metabolism, a major class of sphingolipids, were evaluated. Sphingomyelin molecules were extracted from cells and analyzed by matrix-assisted laser desorption ionization-time of flight MS. It was found that MNNG induced profound changes in sphingomyelin metabolism, including the appearance of some new sphingomyelin species and the disappearance of some others, and the concentrations of several sphingomyelin species also changed. This was accompanied by the redistribution of acid sphingomyelinase （ASM）, a key player in sphingomyelin metabolism. On the other hand, imipramine, an inhibitor of ASM,caused the accumulation of sphingomyelin. It also prevented some of the effects of MNNG, as well as the redistribution of ASM. Taken together, these data suggested that the lipidomic approach is highly effective for the systematic analysis of cellular lipids metabolism.     

The influence of citrate, EDTA, and heparin anticoagulants to human plasma LC–MS lipidomic profiling

Lipid profiling of human plasma by liquid chromatography-electrospray ionization coupled to mass spectrometry (LC–ESI-MS) is being used to identify biomarkers of health, disease, and treatment efficacy. However, there is no consensus on the choice of anticoagulant to perform and compare lipidomic measurements. This study assessed the effect of the anticoagulants citrate, EDTA, and heparin, on eight synthetic and 80 plasma lipids, and compared lipidomic data among anticoagulants. Lipid extraction was affected distinctively by the anticoagulant of choice likely due to the different physico-chemical properties among anticoagulants. Peak areas of seventy endogenous lipids showed significant differences between citrate–heparin and EDTA–heparin comparisons similar to those observed for synthetic lipids. Only ten endogenous lipid species showed comparable peak areas among the three anticoagulants. Correction by a structurally related internal standard only partly eliminated differences among anticoagulants (ANOVA, P value <0.001). However, comparisons among anticoagulants were possible for most endogenous lipids after correction of peak areas by the sum of areas of its lipid class. Our observations indicate that the choice of anticoagulant distinctively impact the peak response of most lipid species by LC–ESI-MS. Lipidomic data from plasma obtained with different anticoagulants should address differences in matrix effects and extraction procedures since ion strength, plasma pH, and different physicochemical properties among anticoagulants influence lipid extraction and LC–ESI-MS analysis.     

The developmental lipidome of Haemonchus contortus

Lipids play crucial roles in the biology of organisms, particularly relating to cellular membranes, energy storage, and intra- or inter-cellular signalling. Despite the recent expansion of the lipidomics field, very little is known about the biology of lipids in metzoan pathogens, and, to date, there has been no global lipidomic study of a parasitic nematode. Using Haemonchus contortus (barber's pole worm) as a model, we describe the first known global lipidome for a parasitic nematode via high throughput LC–MS/MS-based lipidomics. We identified a total of 554 lipid species across four lipid categories, and 18 lipid classes exhibited alterations among six developmental stages (eggs; L3 and exsheathed L3 (xL3) and L4 larval stages; female and male adults) of H. contortus. The lipid composition and abundance of H. contortus changed significantly during the transition from free-living (egg, L3 and xL3) to parasitic (L4 and adult) stages. The three main changes observed were: (i) decreased synthesis of triradylglycerols; (ii) increased glycerophospholipids (predominantly glycerophosphoethanolamines and glycerophosphocholines); and (iii) a ‘cooperative’ modulation of ether-linked lipids and saturated fatty acids. These changes suggest specific adaptations, in terms of nutrient acquisition, metabolism and development, as the nematode makes its transition to the parasitic stage inside the host animal. This lipidomic data set serves as a stimulus for studies to understand lipid biology in parasitic worms, and their roles in parasite–host interactions and disease processes.     

基于脂质组学技术研究急性缺血性脑卒中临床诊断标志物

目的:急性缺血性脑卒中(Acute ischemic stroke, AIS)是由于血流减少导致的脑功能突然丧失。由于AIS发病机制是异质性和多因素的,我们建立全面的脂质组学方法来阐明AIS进程相关的脂质变化和复杂的脂质代谢网络。方法:选取26例AIS患者血液标本和27例健康志愿者血清作为研究对象,进行总脂抽提,通过基于LC-MS策略的非靶向脂质组学方法进行规模性、整体性的脂质组学分析。结果:对AIS患者和健康志愿者血浆进行大规模脂质定性定量分析,通过Progenesis~? QI软件分析Xevo~? G2-XS QTOF质谱系统MSE采集的子离子数据,精确定量到1054个脂质特征差异,准确定性得到368个脂质分子,多变量统计分析中差异脂质组成能将AIS患者和健康志愿者区分开来,通路富集分析图显示差异脂质主要参与甘油磷脂代谢的紊乱。结论:AIS患者血浆脂质组成与健康志愿者存在显著差异,差异表达的脂质可能与AIS发生有关。这些发现有助于开发新的诊断标志物和AIS治疗靶点。     

Lipidomic Analysis of Chlamydomonas reinhardtii under Nitrogen and Sulfur Deprivation

Chlamydomonas reinhardtii accumulates lipids under complete nutrient starvation conditions while overall growth in biomass stops. In order to better understand biochemical changes under nutrient deprivation that maintain production of algal biomass, we used a lipidomic assay for analyzing the temporal regulation of the composition of complex lipids in C. reinhardtii in response to nitrogen and sulfur deprivation. Using a chip-based nanoelectrospray direct infusion into an ion trap mass spectrometer, we measured a diversity of lipid species reported for C. reinhardtii, including PG phosphatidylglycerols, PI Phosphatidylinositols, MGDG monogalactosyldiacylglycerols, DGDG digalactosyldiacylglycerols, SQDG sulfoquinovosyldiacylglycerols, DGTS homoserine ether lipids and TAG triacylglycerols. Individual lipid species were annotated by matching mass precursors and MS/MS fragmentations to the in-house LipidBlast mass spectral database and MS2Analyzer. Multivariate statistics showed a clear impact on overall lipidomic phenotypes on both the temporal and the nutrition stress level. Homoserine-lipids were found up-regulated at late growth time points and higher cell density, while triacyclglycerols showed opposite regulation of unsaturated and saturated fatty acyl chains under nutritional deprivation.     

Phosphatidylcholine and sphingomyelin containing an elaidoyl fatty acid can form cholesterol-rich lateral domains in bilayer membranes

Elaidic acid is a trans-fatty acid found in many food products and implicated for having potentially health hazardous effects in humans. Elaidic acid is readily incorporated into membrane lipids in vivo and therefore affects processes regulating membrane physical properties. In this study the membrane properties of sphingomyelin and phosphatidylcholine containing elaidic acid (N-E-SM and PEPC) were determined in bilayer membranes with special emphasis on their interaction with cholesterol and participation in ordered domain formation. In agreement with previous studies the melting temperatures were found to be about 20 °C lower for the elaidoyl than for the corresponding saturated lipids. The trans-unsaturation increased the polarity at the membrane-water interface as reported by Laurdan fluorescence. Fluorescence quenching experiments using cholestatrienol as a probe showed that both N-E-SM and PEPC were incorporated in lateral membrane domains with sterol and saturated lipids. At low temperatures the elaidoyl lipids were even able to form sterol-rich domains without any saturated lipids present in the bilayer. We conclude from this study that the ability of N-E-SM and PEPC to form ordered domains together with cholesterol and saturated phospho- and sphingolipids in model membranes indicates that they might have an influence on raft formation in biological membranes.     

鸟枪脂组学研究进展及其应用

继基因组学之后,针对各种代谢物的组学研究蓬勃兴起,鸟枪脂组学(shotgun lipidom ics)作为脂类研究的重要新兴手段,在创立和初期发展的过程中便已经展示出惊人的潜力,随着相关技术的进一步完善和发展,必将成为系统生物学的组成部分,在生物医学的研究和应用中发挥难以替代的重要作用。鸟枪脂组学利用质谱技术对全部或单一脂类及其相关分子进行系统分析,研究其改变对生物体所产生的作用并探讨其作用机制。传统脂类分析中的瓶颈问题在以电喷射离子质谱为基础的脂组学方法出现后获得了突破,使脂类分析进入高通量、高精度和高效能的时代。脂类在生物体内分布广泛、种类众多,并且与人类疾病密切相关。将脂组学分析方法运用于疾病相关的特异脂类标志物的发现并揭示其在疾病发生发展等复杂过程中的作用,可能为疾病的诊断治疗提供新的思路和策略。     

A computational framework for integration of lipidomics data into metabolic pathways

Lipids are important compounds for human physiology and as renewable resources for fuels and chemicals. In lipid research, there is a big gap between the currently available pathway-level representations of lipids and lipid structure databases in which the number of compounds is expanding rapidly with high-throughput mass spectrometry methods.In this work, we introduce a computational approach to bridge this gap by making associations between metabolic pathways and the lipid structures discovered increasingly thorough lipidomics studies. Our approach, called NICELips (Network Integrated Computational Explorer for Lipidomics), is based on the formulation of generalized enzymatic reaction rules for lipid metabolism, and it employs the generalized rules to postulate novel pathways of lipid metabolism. It further integrates all discovered lipids in biological networks of enzymatic reactions that consist their biosynthesis and biodegradation pathways.We illustrate the utility of our approach through a case study of bis(monoacylglycero)phosphate (BMP), a biologically important glycerophospholipid with immature synthesis and catabolic route(s). Using NICELips, we were able to propose various synthesis and degradation pathways for this compound and several other lipids with unknown metabolism like BMP, and in addition several alternative novel biosynthesis and biodegradation pathways for lipids with known metabolism. NICELips has potential applications in designing therapeutic interventions for lipid-associated disorders and in the metabolic engineering of model organisms for improving the biobased production of lipid-derived fuels and chemicals.     

Associations of ApoE4 status and DHA supplementation on plasma and CSF lipid profiles and entorhinal cortex thickness

Apolipoprotein ε allele 4 (APOE4) influences the metabolism of polyunsaturated fatty acids (PUFAs) such as docosahexaenoic acid (DHA). The entorhinal cortex (EC) in the brain is affected early in Alzheimer's disease and is rich in DHA. The purpose of this study is to identify the effect of APOE4 and DHA lipid species on the EC. Plasma and cerebrospinal fluid (CSF) lipidomic measurements were obtained from the DHA Brain Delivery Pilot, a randomized clinical trial of DHA supplementation (n = 10) versus placebo (n = 12) for six months in nondemented older adults stratified by APOE4 status. Wild-type C57B6/J mice were fed a high or low DHA diet for 6 months followed by plasma and brain lipidomic analysis. Levels of phosphatidylcholine DHA (PC 38:6) and cholesterol ester DHA (CE 22:6) had the largest increases in CSF following supplementation (P < 0.001). DHA within triglyceride (TG) lipids in CSF strongly correlated with corresponding plasma TG lipids, and differed by APOE4, with carriers having a lower increase than noncarriers. Changes in plasma PC DHA had the strongest association with changes in EC thickness in millimeters, independent of APOE4 status (P = 0.007). In mice, a high DHA diet increased PUFAs within brain lipids. Our findings demonstrate an exchange of DHA at the CSF-blood barrier and into the brain within all lipid species with APOE having the strongest effect on DHA-containing TGs. The correlation of PC DHA with EC suggests a functional consequence of DHA accretion in high density lipoprotein for the brain.     

Role of palmitate-induced sphingoid base-1-phosphate biosynthesis in INS-1 β-cell survival

Sphingoid base-1-phosphates represent a very low portion of the sphingolipid pool but are potent bioactive lipids in mammals. This study was undertaken to determine whether these lipids are produced in palmitate-treated pancreatic β cells and what role they play in palmitate-induced β cell apoptosis. Our lipidomic analysis revealed that palmitate at low and high glucose supplementation increased (dihydro)sphingosine-1-phosphate levels in INS-1 β cells. This increase was associated with an increase in sphingosine kinase 1 (SphK1) mRNA and protein levels. Over-expression of SphK1 in INS-1 cells potentiated palmitate-induced accumulation of dihydrosphingosine-1-phosphate. N,N-dimethyl-sphingosine, a potent inhibitor of SphK, potentiated β-cell apoptosis induced by palmitate whereas over-expression of SphK1 significantly reduced apoptosis induced by palmitate with high glucose. Endoplasmic reticulum (ER)-targeted SphK1 also partially inhibited apoptosis induced by palmitate. Inhibition of INS-1 apoptosis by over-expressed SphK1 was independent of sphingosine-1-phosphate receptors but was associated with a decreased formation of pro-apoptotic ceramides induced by gluco-lipotoxicity. Moreover, over-expression of SphK1 counteracted the defect in the ER-to-Golgi transport of proteins that contribute to the ceramide-dependent ER stress observed during gluco-lipotoxicity. In conclusion, our results suggest that activation of palmitate-induced SphK1-mediated sphingoid base-1-phosphate formation in the ER of β cells plays a protective role against palmitate-induced ceramide-dependent apoptotic β cell death.     

Multi-dimensional mass spectrometry-based shotgun lipidomics and the altered lipids at the mild cognitive impairment stage of Alzheimer's disease

Multi-dimensional mass spectrometry-based shotgun lipidomics (MDMS-SL) is a well-developed technology for global lipid analysis, which identifies and quantifies individual lipid molecular species directly from lipid extracts of biological samples. By using this technology, we have revealed three marked changes of lipids in brain samples of subjects with mild cognitive impairment of Alzheimer's disease including sulfatides, ceramides, and plasmalogens. Further studies using MDMS-SL lead us to the identification of the potential biochemical mechanisms responsible for the altered lipids at the disease state, which are thoroughly discussed in this minireview. Specifically, in studies to identify the causes responsible for sulfatide depletion at the mild cognitive impairment stage of Alzheimer's disease, we have found that apolipoprotein E is associated with sulfatide transport and mediates sulfatide homeostasis in the nervous system through lipoprotein metabolism pathways and that alterations in apolipoprotein E-mediated sulfatide trafficking can lead to sulfatide depletion in the brain. Collectively, the results obtained from lipidomic analyses of brain samples provide important insights into the biochemical mechanisms underlying the pathogenesis of Alzheimer's disease.     

Detecting distant homologs using phylogenetic tree-based HMMs

It is often desired to identify further homologs of a family of biological sequences from the ever-growing sequence databases. Profile hidden Markov models excel at capturing the common statistical features of a group of biological sequences. With these common features, we can search the biological database and find new homologous sequences. Most general profile hidden Markov model methods, however, treat the evolutionary relationships between the sequences in a homologous group in an ad-hoc manner. We hereby introduce a method to incorporate phylogenetic information directly into hidden Markov models, and demonstrate that the resulting model performs better than most of the current multiple sequence-based methods for finding distant homologs.     

signatureSearch: environment for gene expression signature searching and functional interpretation

signatureSearch is an R/Bioconductor package that integrates a suite of existing and novel algorithms into an analysis environment for gene expression signature (GES) searching combined with functional enrichment analysis (FEA) and visualization methods to facilitate the interpretation of the search results. In a typical GES search (GESS), a query GES is searched against a database of GESs obtained from large numbers of measurements, such as different genetic backgrounds, disease states and drug perturbations. Database matches sharing correlated signatures with the query indicate related cellular responses frequently governed by connected mechanisms, such as drugs mimicking the expression responses of a disease. To identify which processes are predominantly modulated in the GESS results, we developed specialized FEA methods combined with drug-target network visualization tools. The provided analysis tools are useful for studying the effects of genetic, chemical and environmental perturbations on biological systems, as well as searching single cell GES databases to identify novel network connections or cell types. The signatureSearch software is unique in that it provides access to an integrated environment for GESS/FEA routines that includes several novel search and enrichment methods, efficient data structures, and access to pre-built GES databases, and allowing users to work with custom databases.