Lipidomics informatics for life-science

Plasma Lipidomic Profiling Using Mass Spectrometry for Multiple Sclerosis Diagnosis and Disease Activity Stratification (LipidMS)

This investigation explores the potential of plasma lipidomic signatures for aiding in the diagnosis of Multiple Sclerosis (MS) and evaluating the clinical course and disease activity of diseased patients. Plasma samples from 60 patients with MS (PwMS) were clinically stratified to either a relapsing-remitting (RRMS) or a chronic progressive MS course and 60 age-matched controls were analyzed using state-of-the-art direct infusion quantitative shotgun lipidomics. To account for potential confounders, data were filtered for age and BMI correlations. The statistical analysis employed supervised and unsupervised multivariate data analysis techniques, including a principal component analysis (PCA), a partial least squares discriminant analysis (oPLS-DA) and a random forest (RF). To determine whether the significant absolute differences in the lipid subspecies have a relevant effect on the overall composition of the respective lipid classes, we introduce a class composition visualization (CCV). We identified 670 lipids across 16 classes. PwMS showed a significant increase in diacylglycerols (DAG), with DAG 16:0;0_18:1;0 being proven to be the lipid with the highest predictive ability for MS as determined by RF. The alterations in the phosphatidylethanolamines (PE) were mainly linked to RRMS while the alterations in the ether-bound PEs (PE O-) were found in chronic progressive MS. The amount of CE species was reduced in the CPMS cohort whereas TAG species were reduced in the RRMS patients, both lipid classes being relevant in lipid storage. Combining the above mentioned data analyses, distinct lipidomic signatures were isolated and shown to be correlated with clinical phenotypes. Our study suggests that specific plasma lipid profiles are not merely associated with the diagnosis of MS but instead point toward distinct clinical features in the individual patient paving the way for personalized therapy and an enhanced understanding of MS pathology.

Global analysis of putative phospholipases in Plasmodium falciparum reveals an essential role of the phosphoinositide-specific phospholipase C in parasite maturation

For its replication within red blood cells, the malaria parasite depends on a highly active and regulated lipid metabolism. Enzymes involved in lipid metabolic processes such as phospholipases are, therefore, potential drug targets. Here, using reverse genetics approaches, we show that only 1 out of the 19 putative phospholipases expressed in asexual blood stages of Plasmodium falciparum is essential for proliferation in vitro, pointing toward a high level of redundancy among members of this enzyme family. Using conditional mislocalization and gene disruption techniques, we show that this essential phosphoinositide-specific phospholipase C (PI-PLC, PF3D7_1013500) has a previously unrecognized essential role during intracellular parasite maturation, long before its previously perceived role in parasite egress and invasion. Subsequent lipidomic analysis suggests that PI-PLC mediates cleavage of phosphatidylinositol bisphosphate (PIP2) in schizont-stage parasites, underlining its critical role in regulating phosphoinositide levels in the parasite. IMPORTANCE The clinical symptoms of malaria arise due to repeated rounds of replication of Plasmodium parasites within red blood cells (RBCs). Central to this is an intense period of membrane biogenesis. Generation of membranes not only requires de novo synthesis and acquisition but also the degradation of phospholipids, a function that is performed by phospholipases. In this study, we investigate the essentiality of the 19 putative phospholipase enzymes that the human malaria parasite Plasmodium falciparum expresses during its replication within RBCs. We not only show that a high level of functional redundancy exists among these enzymes but, at the same time, also identify an essential role for the phosphoinositide-specific phospholipase C in parasite development and cleavage of the phospholipid phosphatidylinositol bisphosphate.

Are n-3 PUFAs from Microalgae Incorporated into Membrane and Storage Lipids in Pig Muscle Tissues?-A Lipidomic Approach

For the study of molecular mechanisms of to lipid transport and storage in relation to dietary effects, lipidomics has been rarely used in farm animal research. A feeding study with pigs (German Landrace sows) and supplementation of microalgae (Schizochytrium sp.) was conducted. The animals were allocated to the control group (n = 15) and the microalgae group (n = 16). Shotgun lipidomics was applied. This study enabled us to identify and quantify 336 lipid species from 15 different lipid classes in pig skeletal muscle tissues. The distribution of the lipid classes was significantly altered by microalgae supplementation, and ether lipids of phosphatidylcholine (PC), phosphatidylethanolamine (PE), and phosphatidic acid (PA) were significantly decreased. The total concentration of triacylglycerides (TAGs) was not affected. TAGs with high degree of unsaturation (TAG 56:7, TAG 56:6, TAG 54:6) were increased in the microalgae group, and major abundant species like TAG 52:2 and TAG 52:1 were not affected by the diet. Our results confirmed that dietary DHA and EPA are incorporated into storage and membrane lipids of pig muscles, which further led to systemic changes in the lipidome composition.

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

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

The role of lipids in exosome biology and intercellular communication: Function, analytics and applications

Exosomes are extracellular vesicles that in recent years have received special attention for their regulatory functions in numerous biological processes. Recent evidence suggests a correlation between the composition of exosomes in body fluids and the progression of some disorders, such as cancer, diabetes and neurodegenerative diseases. In consequence, numerous studies have been performed to evaluate the composition of these vesicles, aiming to develop new biomarkers for diagnosis and to find novel therapeutic targets. On their part, lipids represent one of the most important components of exosomes, with important structural and regulatory functions during exosome biogenesis, release, targeting and cellular uptake. Therefore, exosome lipidomics has emerged as an innovative discipline for the discovery of novel lipid species with biomedical applications. This review summarizes the current knowledge about exosome lipids and their roles in exosome biology and intercellular communication. Furthermore, it presents the state-of-the-art analytical procedures used in exosome lipidomics while emphasizing how this emerging discipline is providing new insights for future applications of exosome lipids in biomedicine.

LAMP3 deficiency affects surfactant homeostasis in mice

Lysosome-associated membrane glycoprotein 3 (LAMP3) is a type I transmembrane protein of the LAMP protein family with a cell-type-specific expression in alveolar type II cells in mice and hitherto unknown function. In type II pneumocytes, LAMP3 is localized in lamellar bodies, secretory organelles releasing pulmonary surfactant into the extracellular space to lower surface tension at the air/liquid interface. The physiological function of LAMP3, however, remains enigmatic. We generated Lamp3 knockout mice by CRISPR/Cas9. LAMP3 deficient mice are viable with an average life span and display regular lung function under basal conditions. The levels of a major hydrophobic protein component of pulmonary surfactant, SP-C, are strongly increased in the lung of Lamp3 knockout mice, and the lipid composition of the bronchoalveolar lavage shows mild but significant changes, resulting in alterations in surfactant functionality. In ovalbumin-induced experimental allergic asthma, the changes in lipid composition are aggravated, and LAMP3-deficient mice exert an increased airway resistance. Our data suggest a critical role of LAMP3 in the regulation of pulmonary surfactant homeostasis and normal lung function.

LAMP3 is a protein of unknown molecular function with highest expression in alveolar type II cells. In alveolar type II cells, LAMP3 localizes to lamellar bodies, specific lysosome-related organelles that play an important role in secreting pulmonary surfactant, a mixture of hydrophobic proteins and lipids lowering the surface tension between the gas and the liquid phase of the lung in order to prevent alveoli from collapsing. To decipher the physiological function of LAMP3, we generated Lamp3 knockout mice, which are viable and show no apparent phenotype. Under basal conditions, both the protein and lipid composition of pulmonary surfactant are altered, but do not affect the physiological function of the lung. However, under diseased conditions of experimental allergic asthma, changes in the lipid composition are aggravated and are associated with an impaired lung function, suggesting an important role of LAMP3 in the homeostasis of pulmonary surfactant.

A normalized signal calibration with a long-term reference improves the robustness of RPLC-MRM/MS lipidomics in plasma

Improving the reliability of quantification in lipidomic analyses is crucial for its successful application in the discovery of new biomarkers or in clinical practice. In this study, we propose a workflow to improve the accuracy and precision of lipidomic results issued by the laboratory. Lipid species from 11 classes were analyzed by a targeted RPLC-MRM/MS method. The peak areas of species were used to estimate concentrations by an internal standard calibration approach (IS-calibration) and by an alternative normalization signal calibration schema (NS-calibration). The latter uses a long-term reference plasma material as a matrix-matched external calibrator whose accuracy was compared to the NIST SRM-1950 mean consensus values reported by the Interlaboratory Lipidomics Comparison Exercise. The bias of lipid concentrations showed a good accuracy for 69 of 89 quantified lipids. The quantitation of species by the NS-calibration schema improved the within- and between-batch reproducibility in quality control samples, in comparison to the usual IS-calibration approach. Moreover, the NS-calibration workflow improved the robustness of the lipidomics measurements reducing the between-batch variability (relative standard deviation <10% for 95% of lipid species) in real conditions tested throughout the analysis of 120 plasma samples. In addition, we provide a free access web tool to obtain the concentration of lipid species by the two previously mentioned quantitative approaches, providing an easy follow-up of quality control tasks related to lipidomics.

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

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

SMITER-A Python Library for the Simulation of LC-MS/MS Experiments

SMITER (Synthetic mzML writer) is a Python-based command-line tool designed to simulate liquid-chromatography-coupled tandem mass spectrometry LC-MS/MS runs. It enables the simulation of any biomolecule amenable to mass spectrometry (MS) since all calculations are based on chemical formulas. SMITER features a modular design, allowing for an easy implementation of different noise and fragmentation models. By default, SMITER uses an established noise model and offers several methods for peptide fragmentation, and two models for nucleoside fragmentation and one for lipid fragmentation. Due to the rich Python ecosystem, other modules, e.g., for retention time (RT) prediction, can easily be implemented for the tailored simulation of any molecule of choice. This facilitates the generation of defined gold-standard LC-MS/MS datasets for any type of experiment. Such gold standards, where the ground truth is known, are required in computational mass spectrometry to test new algorithms and to improve parameters of existing ones. Similarly, gold-standard datasets can be used to evaluate analytical challenges, e.g., by predicting co-elution and co-fragmentation of molecules. As these challenges hinder the detection or quantification of co-eluents, a comprehensive simulation can identify and thus, prevent such difficulties before performing actual MS experiments. SMITER allows the creation of such datasets easily, fast, and efficiently.

Bioactive Lipids in MSCs Biology: State of the Art and Role in Inflammation

Lipidomics is a lipid-targeted metabolomics approach that aims to the comprehensive analysis of lipids in biological systems in order to highlight the specific functions of lipid species in health and disease. Lipids play pivotal roles as they are major structural components of the cellular membranes and energy storage molecules but also, as most recently shown, they act as functional and regulatory components of intra- and intercellular signaling. Herein, emphasis is given to the recently highlighted roles of specific bioactive lipids species, as polyunsaturated fatty acids (PUFA)-derived mediators (generally known as eicosanoids), endocannabinoids (eCBs), and lysophospholipids (LPLs), and their involvement in the mesenchymal stem cells (MSCs)-related inflammatory scenario. Indeed, MSCs are a heterogenous population of multipotent cells that have attracted much attention for their potential in regulating inflammation, immunomodulatory capabilities, and reparative roles. The lipidomics of the inflammatory disease osteoarthritis (OA) and the influence of MSCs-derived lipids have also been addressed.

Comparative Analysis of Milk Triglycerides Profile between Jaffarabadi Buffalo and Holstein Friesian Cow

Milk lipids are known for a variety of biological functions, however; little is known about compositional variation across breeds, especially for Jaffarabadi buffalo, an indigenous Indian breed. Systematic profiling of extracted milk lipids was performed by mass spectrometry across summer and winter in Holstein Friesian cow and Jaffarabadi buffalo. Extensive MS/MS spectral analysis for the identification (ID) of probable lipid species using software followed by manual verification and grading of each assigned lipid species enabled ID based on (a) parent ion, (b) head group, and (c) partial/full acyl characteristic ions for comparative profiling of triacylglycerols between the breeds. Additionally, new triacylglycerol species with short-chain fatty acids were reported by manual interpretation of MS/MS spectra and comparison with curated repositories. Collectively, 1093 triacylglycerol species belonging to 141 unique sum compositions between the replicates of both the animal groups were identified. Relative quantitation at sum composition level followed by statistical analyses revealed changes in relative abundances of triacylglycerol species due to breed, season, and interaction effect of the two. Significant changes in triacylglycerols were observed between breeds (81%) and seasons (59%). When the interaction effect is statistically significant, a higher number of triacylglycerols species in Jaffarabadi has lesser seasonal variation than Holstein Friesian.

A Comprehensive Functional Characterization of Escherichia coli Lipid Genes

Lipid membranes are the border between living cells and their environments. The membrane's lipid composition defines fluidity, thickness, and protein activity and is controlled by the intricate actions of lipid gene-encoded enzymes. However, a comprehensive analysis of each protein's contribution to the lipidome is lacking. Here, we present such a comprehensive and functional overview of lipid genes in Escherichia coli by individual overexpression or deletion of these genes. We developed a high-throughput lipidomic platform, combining growth analysis, one-step lipid extraction, rapid LC-MS, and bioinformatic analysis into one streamlined procedure. This allowed the processing of more than 300 samples per day and revealed interesting functions of known enzymes and distinct effects of individual proteins on the phospholipidome. Our data demonstrate the plasticity of the phospholipidome and unexpected relations between lipid classes and cell growth. Modeling of lipidomic responses to short-chain alcohols provides a rationale for targeted membrane engineering.

LION/web: a web-based ontology enrichment tool for lipidomic data analysis

BACKGROUND

A major challenge for lipidomic analyses is the handling of the large amounts of data and the translation of results to interpret the involvement of lipids in biological systems.

RESULTS

We built a new lipid ontology (LION) that associates >50,000 lipid species to biophysical, chemical, and cell biological features. By making use of enrichment algorithms, we used LION to develop a web-based interface (LION/web, www.lipidontology.com) that allows identification of lipid-associated terms in lipidomes. LION/web was validated by analyzing a lipidomic dataset derived from well-characterized sub-cellular fractions of RAW 264.7 macrophages. Comparison of isolated plasma membranes with the microsomal fraction showed a significant enrichment of relevant LION-terms including "plasma membrane", "headgroup with negative charge", "glycerophosphoserines", "above average bilayer thickness", and "below average lateral diffusion". A second validation was performed by analyzing the membrane fluidity of Chinese hamster ovary cells incubated with arachidonic acid. An increase in membrane fluidity was observed both experimentally by using pyrene decanoic acid and by using LION/web, showing significant enrichment of terms associated with high membrane fluidity ("above average", "very high", and "high lateral diffusion" and "below average transition temperature").

CONCLUSIONS

The results demonstrate the functionality of LION/web, which is freely accessible in a platform-independent way.

The de.NBI / ELIXIR-DE training platform - Bioinformatics training in Germany and across Europe within ELIXIR

The German Network for Bioinformatics Infrastructure (de.NBI) is a national and academic infrastructure funded by the German Federal Ministry of Education and Research (BMBF). The de.NBI provides (i) service, (ii) training, and (iii) cloud computing to users in life sciences research and biomedicine in Germany and Europe and (iv) fosters the cooperation of the German bioinformatics community with international network structures. The de.NBI members also run the German node (ELIXIR-DE) within the European ELIXIR infrastructure. The de.NBI / ELIXIR-DE training platform, also known as special interest group 3 (SIG 3) ‘Training & Education’, coordinates the bioinformatics training of de.NBI and the German ELIXIR node. The network provides a high-quality, coherent, timely, and impactful training program across its eight service centers. Life scientists learn how to handle and analyze biological big data more effectively by applying tools, standards and compute services provided by de.NBI. Since 2015, more than 300 training courses were carried out with about 6,000 participants and these courses received recommendation rates of almost 90% (status as of July 2020). In addition to face-to-face training courses, online training was introduced on the de.NBI website in 2016 and guidelines for the preparation of e-learning material were established in 2018. In 2016, ELIXIR-DE joined the ELIXIR training platform. Here, the de.NBI / ELIXIR-DE training platform collaborates with ELIXIR in training activities, advertising training courses via TeSS and discussions on the exchange of data for training events essential for quality assessment on both the technical and administrative levels. The de.NBI training program trained thousands of scientists from Germany and beyond in many different areas of bioinformatics.

Overview of Lipid Mass Spectrometry and Lipidomics

Mass spectrometry has played a critical role in the identification and quantitation of lipids present in biological extracts. Various strategies have emerged in order to carry out lipidomic studies. These include both shotgun approaches as well as those engaging liquid chromatographic separation of lipid species prior to mass spectrometric analysis. Nonetheless challenges remain at every level of the lipidomic experiment, including extraction of lipids, identification of specific species, and quantitation of the vast array of lipids present in the sample extract. New strategies have emerged to address some of these issues; however, precise quantitation remains a significant challenge. The use of the ratio of the abundance of the molecular ion species to that of an internal standard enables quite accurate assessment of fold changes within complex lipid species without the need for exact quantitation. Challenges continue to remain in terms of availability of reference standard material as well as relevant internal standards.

Role of dyslipidemia in preeclampsia-A review of lipidomic analysis of blood, placenta, syncytiotrophoblast microvesicles and umbilical cord artery from women with preeclampsia

Preeclampsia is a complex disorder and the pathogenesis of it is still not fully understood. The most commonly accepted theory of pathogenesis assumes that there occurs impaired trophoblastic invasion and failure in spiral artery remodeling. Nowadays, obesity becomes one of the most important, modifiable risk factors for the development of preeclampsia. Despite research into the condition, predicting which women with risk factors will develop preeclampsia remains problematic. Emerging evidence suggests that dysregulation of maternal and placental lipid metabolism are involved in the pathogenesis of the condition. Hence, researchers are focused on finding a lipid fingerprint, which contains information about the lipid composition and abundance of individual lipids by using new methods in the field of lipidomics. In this review we aimed to discuss the role of dyslipidemia in the pathogenesis of preeclampsia. In addition, on the basis of current research, we attempted to find a specific lipid profile of different tissues in women with preeclampsia.

A novel sample preparation strategy for shotgun lipidomics of phospholipids employing multilamellar vesicles

The identification of lipids in biological samples is gaining importance. The advent of mass spectrometry-based lipidomics accelerated the field allowing nowadays for identification and quantification of complete lipidomes. However, due to solubility difficulties and varying properties of different lipid classes, sample preparation for lipidomics is still an issue. Of the many lipid classes, phospholipids are the major components of biological membranes. In solution, they spontaneously form lipid vesicles of various structures such as liposomes. They are therefore often used as membrane mimics when studying biological membranes and membrane proteins. Here, we present a novel sample preparation strategy for shotgun lipidomics employing liposomes prepared from lipid standards or lipid mixtures allowing the analysis of phospholipids directly from lipid bilayers. We validated our strategy for lipid identification by tandem mass spectrometry in positive or negative ion mode using different phospholipid species from various classes. We further tested our strategy for relative quantification by mixing different ratios of phospholipid species as well as determining the distribution of lipid species in a natural lipid extract.

Graphical abstract