High-resolution Lipidomics Research Articles

Integrated untargeted and targeted lipidomics discovers LPE 16:0 as a protector against respiratory syncytial virus infection

Respiratory Syncytial Virus (RSV) is a leading cause of acute lower respiratory infections, imposing a substantial burden on healthcare systems globally. While lipid disorders have been observed in the lungs of infants and young children with RSV pneumonia, the specific characterization of these lipids and their roles in the development and progression of RSV pneumonia remain largely unexplored. To address this tissue, we established a non-targeted high-resolution lipidomics platform using UHPLC-Q-Exactive-MS to analyze lipid profiles in bronchoalveolar lavage fluid (BALF) obtained from mice infected with RSV. Through the lipidomics analysis, a total of 72 lipids species were identified, with 40 lipids were significantly changed. Notably, the primary changes were observed in ether phospholipids and lysophospholipids. Furthermore, a targeted lipidomics analysis utilizing UHPLC-QQQ-MS/MS was developed to specifically assess the levels of lysophospholipids, including lysophosphocholine 16:0 (LPC 16:0), lysophosphoethanolamine 16:0 (LPE 16:0) and lysophosphoglycerol 16:0 (LPG 16:0), in RSV-infected mice compared to control mice. Animal experiments revealed that LPE 16:0, rather than LPC 16:0 or LPG 16:0, provided protection against RSV-induced weight loss, reduced lung viral load, regulated immune cells and mitigated lung injury in mice afflicted with RSV pneumonia. In summary, our findings suggested that the host responses to RSV infection pathology are closely with various lipid metabolic. Additionally, our results elucidated novel biological functions of LPE 16:0 and offering new avenues for drug development against RSV pneumonia.

High-Resolution Lipidomics Reveals Influence of Biomass and Pretreatment Process on the Composition of Extracted Algae Oils As Feedstock for Sustainable Aviation Fuels.

The increasing demand for sustainable aviation fuel (SAF) creates a need for innovative biomass and lipid sources with compositions that are compatible with refineries. Algae-derived oils present an opportunity to supply a process-compatible lipid feedstock at yields higher than those of conventional oilseed crops. With few documented reports on chemical composition, the process readiness remains elusive. We present data on extraction efficiency, yield, and purity of lipids from algae with and without the application of a low-concentration sulfuric acid pretreatment of the biomass. The pretreatment process increased the oil yield and positively impacted the quality of the extracted oils. Results from fatty acid and lipidomics analysis revealed that the low-lipid biomass sources extracted 70-80% of the available lipids, and the non-fatty acid co-extractants exceeded 40% of the extracted oils. For a high-lipid algae sample, derived from a genetically engineered strain, we show >90% extraction yield with >85% FAME purity. This work provides insights into the composition of algae-derived oils and quality metrics that are essential to determining the viability of lipid hydroprocessing to SAF.

Imputation of plasma lipid species to facilitate integration of lipidomic datasets

Recent advancements in plasma lipidomic profiling methodology have significantly increased specificity and accuracy of lipid measurements. This evolution, driven by improved chromatographic and mass spectrometric resolution of newer platforms, has made it challenging to align datasets created at different times, or on different platforms. Here we present a framework for harmonising such plasma lipidomic datasets with different levels of granularity in their lipid measurements. Our method utilises elastic-net prediction models, constructed from high-resolution lipidomics reference datasets, to predict unmeasured lipid species in lower-resolution studies. The approach involves (1) constructing composite lipid measures in the reference dataset that map to less resolved lipids in the target dataset, (2) addressing discrepancies between aligned lipid species, (3) generating prediction models, (4) assessing their transferability into the targe dataset, and (5) evaluating their prediction accuracy. To demonstrate our approach, we used the AusDiab population-based cohort (747 lipid species) as the reference to impute unmeasured lipid species into the LIPID study (342 lipid species). Furthermore, we compared measured and imputed lipids in terms of parameter estimation and predictive performance, and validated imputations in an independent study. Our method for harmonising plasma lipidomic datasets will facilitate model validation and data integration efforts.

Early pregnancy associated changes in systemic lipid profiles of mares revealed by high resolution mass spectrometry

Early pregnancy in the mare presents a risk of embryo loss, with little known of the systemic lipid dynamics that contribute to a successful or failed pregnancy. Observations in horses and other species suggest that pregnancy is characterized by an anabolic (i.e. fat deposition) lipid profile initially, followed by a catabolic (lipid mobilization) profile toward the end of gestation. There have been no investigations of lipid metabolism in the very early stages of pregnancy, leading up to and during the time of maternal recognition. High resolution lipidomics presents an unprecedented opportunity to map the changes in lipid profiles of pregnant mares, to examine metabolic pathways contributing to establishment of pregnancy and to identify biomarkers for detection and monitoring of early pregnancy and pregnancy loss. Blood samples were collected from Thoroughbred mares in a commercial breeding operation at day 7 and day 14 following ovulation. Mares were live-covered, and pregnancy tested by transrectal ultrasound at day 14, hereby designated pregnant or non-pregnant. High resolution lipidomics analysis was performed on isolated plasma to compare profiles of pregnant (7P, 14P) and non-pregnant (7NP, 14NP) mares at day 7 and day 14 (total n = 72, split evenly in groups). Lipids were extracted using ice-cold butanol/methanol (1:1 v/v) with 10 mM ammonium acetate containing internal standards.LC separation was performed on a Phenomenex Kinetex C18 Column (2.6 µm, 100 Å, 100 × 2.1 mm) using 5 µL injection volume. The samples were analyzed in data dependent mode using Zeno EAD IDA on the ZenoTOF 7600 system. All data were analyzed using MS-DIAL 5.1. The analysis yielded a total of 10034 unique lipid species across all samples. A total of 277 and 1722 lipids were significantly altered (p<0.05) in pregnant vs non-pregnant animals at day 7 and day 14, respectively. Phosphatidylcholines (PC) were significantly increased in 7P vs 7NP, and phosphatidylethanolamines (PE) were significantly decreased in 7P vs 7NP, with similar trends observed at day 14. Lysophosphatidylcholines (LPC) were increased in 14P vs 14NP. PC and LPC concentrations also increased from day 7 to day 14, but only in pregnant animals. Collectively, these observations point to a major role for phospholipid metabolism in early pregnancy and are consistent with PE being a substrate for methylation to PC, which is a key source of choline crucial for early embryonic development. The roles of PC biosynthesis and supplementation in early equine pregnancy warrant further investigation. Furthermore, alterations in the lipid profile of mares at day 7 post-ovulation challenge the current paradigm that no systemic changes occur in the pregnant mare prior to classical maternal recognition and luteal maintenance.

Deep Lipidomics in Human Plasma: Cardiometabolic Disease Risk and Effect of Dietary Fat Modulation.

Background:In blood and tissues, dietary and endogenously generated fatty acids (FAs) occur in free form or as part of complex lipid molecules that collectively represent the lipidome of the respective tissue. We assessed associations of plasma lipids derived from high-resolution lipidomics with incident cardiometabolic diseases and subsequently tested if the identified risk-associated lipids were sensitive to dietary fat modification.Methods:The EPIC Potsdam cohort study (European Prospective Investigation into Cancer and Nutrition) comprises 27 548 participants recruited within an age range of 35 to 65 years from the general population around Potsdam, Germany. We generated 2 disease-specific case cohorts on the basis of a fixed random subsample (n=1262) and all respective cohort-wide identified incident primary cardiovascular disease (composite of fatal and nonfatal myocardial infarction and stroke; n=551) and type 2 diabetes (n=775) cases. We estimated the associations of baseline plasma concentrations of 282 class-specific FA abundances (calculated from 940 distinct molecular species across 15 lipid classes) with the outcomes in multivariable-adjusted Cox models. We tested the effect of an isoenergetic dietary fat modification on risk-associated lipids in the DIVAS randomized controlled trial (Dietary Intervention and Vascular Function; n=113). Participants consumed either a diet rich in saturated FAs (control), monounsaturated FAs, or a mixture of monounsaturated and n-6 polyunsaturated FAs for 16 weeks.Results:Sixty-nine lipids associated (false discovery rate<0.05) with at least 1 outcome (both, 8; only cardiovascular disease, 49; only type 2 diabetes, 12). In brief, several monoacylglycerols and FA16:0 and FA18:0 in diacylglycerols were associated with both outcomes; cholesteryl esters, free fatty acids, and sphingolipids were largely cardiovascular disease specific; and several (glycero)phospholipids were type 2 diabetes specific. In addition, 19 risk-associated lipids were affected (false discovery rate<0.05) by the diets rich in unsaturated dietary FAs compared with the saturated fat diet (17 in a direction consistent with a potential beneficial effect on long-term cardiometabolic risk). For example, the monounsaturated FA-rich diet decreased diacylglycerol(FA16:0) by 0.4 (95% CI, 0.5–0.3) SD units and increased triacylglycerol(FA22:1) by 0.5 (95% CI, 0.4–0.7) SD units.Conclusions:We identified several lipids associated with cardiometabolic disease risk. A subset was beneficially altered by a dietary fat intervention that supports the substitution of dietary saturated FAs with unsaturated FAs as a potential tool for primary disease prevention.

HIGH RESOLUTION MASS SPECTROMETRY IN LIPIDOMICS.

The boost of research output in lipidomics during the last decade is tightly linked to improved instrumentation in mass spectrometry. Associated with this trend is the shift from low resolution—toward high‐resolution lipidomics platforms. This review article summarizes the state of the art in the lipidomics field with a particular focus on the merits of high mass resolution. Following some theoretical considerations on the benefits of high mass resolution in lipidomics, it starts with a historical perspective on lipid analysis by sector instruments and moves further to today's instrumental approaches, including shotgun lipidomics, liquid chromatography–mass spectrometry, matrix‐assisted laser desorption ionization‐time‐of‐flight, and imaging lipidomics. Subsequently, several data processing and data analysis software packages are critically evaluated with all their pros and cons. Finally, this article emphasizes the importance and necessity of quality standards as the field evolves from its pioneering phase into a mature and robust omics technology and lists various initiatives for improving the applicability of lipidomics. © 2020 The Authors. Mass Spectrometry Reviews published by John Wiley & Sons Ltd. Mass Spec Rev

Membrane Rearrangements in the Maturation of Circulating Human Reticulocytes.

Red blood cells (RBCs) begin their circulatory life as reticulocytes (Retics) after their egress from the bone marrow where, as R1 Retics, they undergo significant rearrangements in their membrane and intracellular components, via autophagic, proteolytic, and vesicle-based mechanisms. Circulating, R2 Retics must complete this maturational process, which involves additional loss of significant amounts of membrane and selected membrane proteins. Little is known about the mechanism(s) at the basis of this terminal differentiation in the circulation, which culminates with the production of a stable biconcave discocyte. The membrane of R1 Retics undergoes a selective remodeling through the release of exosomes that are enriched in transferrin receptor and membrane raft proteins and lipids, but are devoid of Band 3, glycophorin A, and membrane skeletal proteins. We wondered whether a similar selective remodeling occurred also in the maturation of R2 Retics. Peripheral blood R2 Retics, isolated by an immunomagnetic method, were compared with mature circulating RBCs from the same donor and their membrane protein and lipid content was analyzed. Results show that both Band 3 and spectrin decrease from R2 Retics to RBCs on a “per cell” basis. Looking at membrane proteins that are considered as markers of membrane rafts, flotillin-2 appears to decrease in a disproportionate manner with respect to Band 3. Stomatin also decreases but in a more proportionate manner with respect to Band 3, hinting at a heterogeneous nature of membrane rafts. High resolution lipidomics analysis, on the contrary, revealed that those lipids that are typically representative of the membrane raft phase, sphingomyelin and cholesterol, are enriched in mature RBCs with respct to Retics, relative to total cell lipids, strongly arguing in favor of the selective retention of at least certain subclasses of membrane rafts in RBCs as they mature from Retics. Our hypothesis that rafts serve as additional anchoring sites for the lipid bilayer to the underlying membrane-skeleton is corroborated by the present results. It is becoming ever more clear that a proper lipid composition of the reticulocyte is necessary for the production of a normal mature RBC.

Abstract 22: Novel Plasma Lipids Predict Risk of Diabetes: A Longitudinal Lipidomics Study in American Indians

Background: American Indians (AIs) suffer disproportionately high rate of type 2 diabetes (T2D). Traditional biomarkers have limited value in predicting and tracking early onset and progression of T2D. There is an urgent need for early biomarkers in this high-risk but understudied minority population. Objective: To identify novel lipids predictive of T2D onset among American Indians, independent of standard risk factors. Methods: We studied 2,000 American Indians attending two clinical exams (2001-2003, 2006-2009, average 5-yr apart) in the Strong Heart Family Study (SHFS). Fasting plasma lipids were repeatedly measured by untargeted lipidomics using LC-MS/MS. All participants were free of overt CVD at baseline (2001-2003) and followed through 2017 (average 16-yr follow-up). Cox regression with frailty model was used to identify lipids predictive of T2D onset, adjusting for traditional risk factors including age, sex, smoking, BMI, triglyceride, HDL, insulin resistance, eGFR and dietary intake of protein. Longitudinal analysis was conducted by regressing changes in lipids on changes in T2D-related traits (e.g., fasting glucose, HbA1c, or insulin resistance) between baseline and 5-yr follow-up, adjusting for changes in BMI, triglyceride, HDL, and eGFR. Incremental prognostic value of lipids in diabetes risk prediction above traditional risk factors was estimated using area under the curve (AUC). Network analysis was conducted to examine the dynamic changes in lipid networks between baseline and 5-yr follow-up. Multiple testing was controlled by FDR. Results: Of 1,628 non-diabetic participants at baseline (mean age 39.8, 62% women), 189 and 359 individuals developed incident T2D after 5-yr and 16-yr follow-up, respectively. Our high-resolution lipidomics detected 1,826 lipids, of which 1,119 lipids (460 known, 659 unknown) passed stringent quality control. Seven lipids with known structures significantly predict over 30% increased (FA(18:1), FA(20:2), FA(22:2), SM(d34:0) ) or 19% decreased (PC(37:4), PC(37:5), PC(38:4)) risk of T2D onset at both follow-ups. Nine unknown lipids also predicted T2D onset. Longitudinal changes in CE(20:2), CE(22:6), PC(32:0) and two unknowns explain about 6.4% changes in fasting plasma glucose. These newly identified lipids significantly improve the performance of risk prediction over traditional risk factors (AUC increased from 0.787 to 0.803, P=0.002). Network topology analysis revealed that the network connectivity among lipids was much stronger in participants who developed new T2D compared to those who didn’t (degree of network connectivity, 4.2 vs 2.5, P&lt;0.001). Conclusion: We identified several novel plasma lipids significantly predictive of incident T2D, independent of traditional risk factors. These findings highlight the importance of identifying novel lipid markers in early diabetes risk prediction.

High-Resolution Lipidomics of the Early Life Stages of the Red Seaweed Porphyra dioica.

Porphyra dioica is a commercial seaweed consumed all over the world, mostly in the shape of nori sheets used for “sushi” preparation. It is a well-known part of the Asian diet with health benefits, which have been associated, among others, to the high levels of n-3 and n-6 fatty acids in this red alga. However, other highly valued lipids of Porphyra are polar lipids that remain largely undescribed and can have both nutritional value and bioactivity, thus could contribute to the valorization of this seaweed. In this context, the present work aims to identify the lipidome of two life cycle stages of the Atlantic species Porphyra dioica: the early life stage conchocelis produced in an indoor-nursery, and young blades produced outdoors using an integrated multitrophic aquaculture (IMTA) framework. Both the blades (gametophyte) and conchocelis (sporophyte) are commercialized in the food and cosmetics sectors. Liquid chromatography coupled to Q–Exactive high resolution-mass spectrometry (MS) platform was used to gain insight into the lipidome of these species. Our results allowed the identification of 110 and 100 lipid molecular species in the lipidome of the blade and conchocelis, respectively. These lipid molecular species were distributed as follows (blade/conchocelis): 14/15 glycolipids (GLs), 93/79 phospholipids (PLs), and 3/6 betaine lipids. Both life stages displayed a similar profile of GLs and comprised 20:4(n-6) and 20:5(n-3) fatty acids that contribute to n-3 and n-6 fatty acid pool recorded and rank among the molecular species with higher potential bioactivity. PLs’ profile was different between the two life stages surveyed, mainly due to the number and relative abundance of molecular species. This finding suggests that differences between both life stages were more likely related with shifts in the lipids of extraplastidial membranes rather than in plastidial membranes. PLs contained n-6 and n-3 precursors and in both life stages of Porphyra dioica the n-6/n-3 ratio recorded was less than 2, highlighting the potential benefits of using these life stages in human diet to prevent chronic diseases. Atherogenic and thrombogenic indexes of blades (0.85 and 0.49, respectively) and conchocelis (0.34 and 0.30, respectively) are much lower than those reported for other Rhodophyta, which highlights their potential application as food or as functional ingredients. Overall, MS-based platforms represent a powerful tool to characterize lipid metabolism and target lipids along different life stages of algal species displaying complex life cycles (such as Porphyra dioica), contributing to their biotechnological application.

High-resolution lipidomics reveals dysregulation of lipid metabolism in respiratory syncytial virus pneumonia mice.

Respiratory syncytial virus (RSV) is a leading viral pathogen responsible for lower respiratory tract infections, particularly in children under five years worldwide, often resulting in hospitalization. At present, the molecular-level interactions between RSV and its host and the underlying mechanisms of RSV-induced inflammation are poorly understood. Herein, we describe an untargeted high-resolution lipidomics platform based on UHPLC-Q-Exactive-MS to assess the lipid alterations of lung tissues and plasma from a mouse model of RSV pneumonia. Untargeted lipidomics using LC-MS with multivariate analysis was applied to describe the lipidomic profiling of the lung tissues and plasma in RSV pneumonia mice. Lipid identification was conducted via an in silico MS/MS LipidBlast library using the MS-DIAL software. We observed distinct compartmental lipid signatures in the mice lung tissues and plasma and significant lipid profile changes between the systematic and localized host responses to RSV. A total of 87 and 68 differential lipids were captured in the mice lung tissue and plasma, respectively, including phospholipids, sphingolipids, acylcarnitine, and fatty acids. Some of these lipids belong to pulmonary surfactants, illustrating that RSV pneumonia-induced aberrations of the pulmonary surfactant system may play a vital role in the etiology of respiratory inflammation. Our findings reveal that the host responses to RSV and various lipid metabolic pathways were linked to disease pathology. Furthermore, our findings could provide mechanistic insights into RSV pneumonia.

Extension of least squares spectral resolution algorithm to high-resolution lipidomics data

Lipidomics, which focuses on the global study of molecular lipids in biological systems, has been driven tremendously by technical advances in mass spectrometry (MS) instrumentation, particularly high-resolution MS. This requires powerful computational tools that handle the high-throughput lipidomics data analysis. To address this issue, a novel computational tool has been developed for the analysis of high-resolution MS data, including the data pretreatment, visualization, automated identification, deconvolution and quantification of lipid species. The algorithm features the customized generation of a lipid compound library and mass spectral library, which covers the major lipid classes such as glycerolipids, glycerophospholipids and sphingolipids. Next, the algorithm performs least squares resolution of spectra and chromatograms based on the theoretical isotope distribution of molecular ions, which enables automated identification and quantification of molecular lipid species. Currently, this methodology supports analysis of both high and low resolution MS as well as liquid chromatography-MS (LC-MS) lipidomics data. The flexibility of the methodology allows it to be expanded to support more lipid classes and more data interpretation functions, making it a promising tool in lipidomic data analysis.

Purity matters: A workflow for the valid high-resolution lipid profiling of mitochondria from cell culture samples.

Subcellular lipidomics is a novel field of research that requires the careful combination of several pre-analytical and analytical steps. To define a reliable strategy for mitochondrial lipid profiling, we performed a systematic comparison of different mitochondria isolation procedures by western blot analyses and comprehensive high-resolution lipidomics. Using liver-derived HepG2 cells, we compared three common mitochondria isolation methods, differential centrifugation (DC), ultracentrifugation (UC) and a magnetic bead-assisted method (MACS). In total, 397 lipid species, including 32 cardiolipins, could be quantified in only 100 μg (by protein) of purified mitochondria. Mitochondria isolated by UC showed the highest enrichment in the mitochondria-specific cardiolipins as well as their precursors, phosphatidylglycerols. Mitochondrial fractions obtained by the commonly used DC and the more recent MACS method contained substantial contaminations by other organelles. Employing these isolation methods when performing lipidomics analyses from cell culture mitochondria may lead to inaccurate results. To conclude, we present a protocol how to obtain reliable mitochondria-specific lipid profiles from cell culture samples and show that quality controls are indispensable when performing mitochondria lipidomics.