The lipidomics reporting checklist a framework for transparency of lipidomic experiments and repurposing resource data.

The rapid increase in lipidomic studies has led to a collaborative effort within the community to establish standards and criteria for producing, documenting, and disseminating data. Creating a dynamic easy-to-use checklist that condenses key information about lipidomic experiments into common terminology will enhance the field's consistency, comparability, and repeatability. Here, we describe the structure and rationale of the established Lipidomics Minimal Reporting Checklist to increase transparency in lipidomics research.

Ex vivo instability of lipids in whole blood: preanalytical recommendations for clinical lipidomics studies.

Reliability, robustness, and interlaboratory comparability of quantitative measurements is critical for clinical lipidomics studies. Lipids' different ex vivo stability in blood bears the risk of misinterpretation of data. Clear recommendations for the process of blood sample collection are required. We studied by UHPLC-high resolution mass spectrometry, as part of the "Preanalytics interest group" of the International Lipidomics Society, the stability of 417 lipid species in EDTA whole blood after exposure to either 4°C, 21°C, or 30°C at six different time points (0.5 h-24 h) to cover common daily routine conditions in clinical settings. In total, >800 samples were analyzed. 325 and 288 robust lipid species resisted 24 h exposure of EDTA whole blood to 21°C or 30°C, respectively. Most significant instabilities were detected for FA, LPE, and LPC. Based on our data, we recommend cooling whole blood at once and permanent. Plasma should be separated within 4 h, unless the focus is solely on robust lipids. Lists are provided to check the ex vivo (in)stability of distinct lipids and potential biomarkers of interest in whole blood. To conclude, our results contribute to the international efforts towards reliable and comparable clinical lipidomics data paving the way to the proper diagnostic application of distinct lipid patterns or lipid profiles in the future.

LipidSpace: Simple Exploration, Reanalysis, and Quality Control of Large-Scale Lipidomics Studies.

Lipid analysis gained significant importance due to the enormous range of lipid functions, e.g., energy storage, signaling, or structural components. Whole lipidomes can be quantitatively studied in-depth thanks to recent analytical advancements. However, the systematic comparison of thousands of distinct lipidomes remains challenging. We introduce LipidSpace, a standalone tool for analyzing lipidomes by assessing their structural and quantitative differences. A graph-based comparison of lipid structures is the basis for calculating structural space models and subsequently computing lipidome similarities. When adding study variables such as body weight or health condition, LipidSpace can determine lipid subsets across all lipidomes that describe these study variables well by utilizing machine-learning approaches. The user-friendly GUI offers four built-in tutorials and interactive visual interfaces with pdf export. Many supported data formats allow an efficient (re)analysis of data sets from different sources. An integrated interactive workflow guides the user through the quality control steps. We used this suite to reanalyze and combine already published data sets (e.g., one with about 2500 samples and 576 lipids in one run) and made additional discoveries to the published conclusions with the potential to fill gaps in the current lipid biology understanding. LipidSpace is available for Windows or Linux (https://lifs-tools.org).

Toward Omics-Scale Quantitative Mass Spectrometry Imaging of Lipids in Brain Tissue Using a Multiclass Internal Standard Mixture.

Mass spectrometry imaging (MSI) has accelerated our understanding of lipid metabolism and spatial distribution in tissues and cells. However, few MSI studies have approached lipid imaging quantitatively and those that have focused on a single lipid class. We overcome this limitation by using a multiclass internal standard (IS) mixture sprayed homogeneously over the tissue surface with concentrations that reflect those of endogenous lipids. This enabled quantitative MSI (Q-MSI) of 13 lipid classes and subclasses representing almost 200 sum-composition lipid species using both MALDI (negative ion mode) and MALDI-2 (positive ion mode) and pixel-wise normalization of each lipid species in a manner analogous to that widely used in shotgun lipidomics. The Q-MSI approach covered 3 orders of magnitude in dynamic range (lipid concentrations reported in pmol/mm2) and revealed subtle changes in distribution compared to data without normalization. The robustness of the method was evaluated by repeating experiments in two laboratories using both timsTOF and Orbitrap mass spectrometers with an ∼4-fold difference in mass resolution power. There was a strong overall correlation in the Q-MSI results obtained by using the two approaches. Outliers were mostly rationalized by isobaric interferences or the higher sensitivity of one instrument for a particular lipid species. These data provide insight into how the mass resolving power can affect Q-MSI data. This approach opens up the possibility of performing large-scale Q-MSI studies across numerous lipid classes and subclasses and revealing how absolute lipid concentrations vary throughout and between biological tissues.

Validation of a multiplexed and targeted lipidomics assay for accurate quantification of lipidomes.

A major challenge of lipidomics is to determine and quantify the precise content of complex lipidomes to the exact lipid molecular species. Often, multiple methods are needed to achieve sufficient lipidomic coverage to make these determinations. Multiplexed targeted assays offer a practical alternative to enable quantitative lipidomics amenable to quality control standards within a scalable platform. Herein, we developed a multiplexed normal phase liquid chromatography-hydrophilic interaction chromatography multiple reaction monitoring method that quantifies lipid molecular species across over 20 lipid classes spanning wide polarities in a single 20-min run. Analytical challenges such as in-source fragmentation, isomer separations, and concentration dynamics were addressed to ensure confidence in selectivity, quantification, and reproducibility. Utilizing multiple MS/MS product ions per lipid species not only improved the confidence of lipid identification but also enabled the determination of relative abundances of positional isomers in samples. Lipid class-based calibration curves were applied to interpolate lipid concentrations and guide sample dilution. Analytical validation was performed following FDA Bioanalytical Method Validation Guidance for Industry. We report repeatable and robust quantitation of 900 lipid species measured in NIST-SRM-1950 plasma, with over 700 lipids achieving inter-assay variability below 25%. To demonstrate proof of concept for biomarker discovery, we analyzed plasma from mice treated with a glucosylceramide synthase inhibitor, benzoxazole 1. We observed expected reductions in glucosylceramide levels in treated animals but, more notably, identified novel lipid biomarker candidates from the plasma lipidome. These data highlight the utility of this qualified lipidomic platform for enabling biological discovery.

Benchmarking One-Phase Lipid Extractions for Plasma Lipidomics.

A key element of successful lipidomics analysis is a sufficient extraction of lipid molecules typically by two-phase systems such as chloroform-based Bligh and Dyer (B&D). However, numerous metabolomics and lipidomics studies today apply easy to use one-phase extractions. In this work, quantitative flow injection analysis high-resolution mass spectrometry was applied to benchmark the lipid recovery of popular one-phase extraction methods for human plasma samples. The following organic solvents were investigated: methanol (MeOH), ethanol (EtOH), 2-propanol (IPA), 1-butanol (BuOH), acetonitrile (ACN) and the solvent mixtures BuOH/MeOH (3:1) and MeOH/ACN (1:1). The recovery of polar lysophospholipids was sufficient for all tested solvents. However, nonpolar lipid classes such as triglycerides (TG) and cholesteryl esters (CE) revealed extraction efficiencies less than 5% due to precipitation in polar solvents EtOH, MeOH, MeOH/ACN, and ACN. Sample pellets also contained a substantial amount of phospholipids, for example, more than 75% of total phosphatidylcholine and sphingomyelin for ACN. The loss of lipids by precipitation was directly related to the polarity of solvents and lipid classes. Although, lipid recovery increased with the volume of organic solvent, recovery in polar MeOH remains incomplete also for less polar lipid classes such as ceramides. Addition of stable isotope-labeled internal standards prior to lipid extraction could compensate for insufficient lipid recovery for polar lipid classes including lysolipids and phospholipids but not for nonpolar CE and TG. In summary, application of one-phase extractions should be limited to polar lipid classes unless sufficient recovery/solubility of nonpolar lipids has been demonstrated. The presented data reveal that appropriate lipid extraction efficiency is fundamental to achieve accurate lipid quantification.

Recommendations for good practice in MS-based lipidomics.

In the last 2 decades, lipidomics has become one of the fastest expanding scientific disciplines in biomedical research. With an increasing number of new research groups to the field, it is even more important to design guidelines for assuring high standards of data quality. The Lipidomics Standards Initiative is a community-based endeavor for the coordination of development of these best practice guidelines in lipidomics and is embedded within the International Lipidomics Society. It is the intention of this review to highlight the most quality-relevant aspects of the lipidomics workflow, including preanalytics, sample preparation, MS, and lipid species identification and quantitation. Furthermore, this review just does not only highlights examples of best practice but also sheds light on strengths, drawbacks, and pitfalls in the lipidomic analysis workflow. While this review is neither designed to be a step-by-step protocol by itself nor dedicated to a specific application of lipidomics, it should nevertheless provide the interested reader with links and original publications to obtain a comprehensive overview concerning the state-of-the-art practices in the field.

Development of an On-Tissue Derivatization Method for MALDI Mass Spectrometry Imaging of Bioactive Lipids Containing Phosphate Monoester Using Phos-tag.

Matrix-assisted laser desorption ionization-mass spectrometry imaging (MALDI-MSI) is an emerging label-free method for mapping the distribution of diverse molecular species in tissue sections. Despite recent progress in MALDI-MSI analyses of lipids, it is still difficult to visualize minor bioactive lipids including lysophosphatidic acid (LPA) and sphingosine-1-phosphate (S1P). Here, we have developed a novel on-tissue derivatization method using Phos-tag, a zinc complex that specifically binds to a phosphate monoester group. MALDI-MSI with Phos-tag derivatization made it possible to image LPA and S1P in the murine brain. Furthermore, we were able to visualize other low-abundance lipids containing phosphate monoester, such as phosphatidic acid and ceramide-1-phosphate. Compared with conventional MALDI-MS, this derivatization produced LPA images with high spatial accuracy discriminating LPA artificially produced during MALDI-MS analysis. In mice with deficiencies in enzymes that degrade LPA and S1P, we observed marked S1P and/or LPA accumulation in specific regions of the brain. Thus, the present study provides a simple and optimal way to reveal the spatial localization of potent bioactive lipid phosphates such as LPA and S1P in tissues.

Correction of Isobaric Overlap Resulting from Sodiated Ions in Lipidomics.

Lipidomic analyses aim for absolute quantification of lipid species profiles in biological samples. In past years, mass spectrometry (MS) methods based on high resolution accurate masses (HRAM) have increasingly been applied to identify and quantify lipid species on the MS level. This strategy requires consideration of isobaric overlaps which may also result from various adduct ions. Generally applied solvent additives favor the formation of protonated and ammoniated ions in positive ion mode, yet sodiated ions are also frequently observed. These sodiated ions interfere with protonated ions of the species of the same lipid class with two additional CH2 and three double bonds (Δm/z = 0.0025) and the first isotopic peak overlaps with ammoniated ions of a species with one additional CH2 and four double bonds (Δm/z = 0.0057). In this work, we present an algorithm based on the sodiated to protonated/ammoniated adduct ion ratios of applied internal standards to correct for these interferences. We could demonstrate that these ratios differ significantly between lipid classes but are affected by neither chain length nor number of double bonds within a lipid class. Finally, the algorithm is demonstrated for correcting human serum samples analyzed by Fourier-transform mass spectrometry (FTMS). Here, the application of sodium correction significantly reduced overestimations and misidentifications.

hiPSC-derived hepatocytes closely mimic the lipid profile of primary hepatocytes: A future personalised cell model for studying the lipid metabolism of the liver.

Hepatocyte-like cells (HLCs) differentiated from human-induced pluripotent stem cells offer an alternative platform to primary human hepatocytes (PHHs) for studying the lipid metabolism of the liver. However, despite their great potential, the lipid profile of HLCs has not yet been characterized. Here, we comprehensively studied the lipid profile and fatty acid (FA) metabolism of HLCs and compared them with the current standard hepatocyte models: HepG2 cells and PHHs. We differentiated HLCs by five commonly used methods from three cell lines and thoroughly characterized them by gene and protein expression. HLCs generated by each method were assessed for their functionality and the ability to synthesize, elongate, and desaturate FAs. In addition, lipid and FA profiles of HLCs were investigated by both mass spectrometry and gas chromatography and then compared with the profiles of PHHs and HepG2 cells. HLCs resembled PHHs by expressing hepatic markers: secreting albumin, lipoprotein particles, and urea, and demonstrating similarities in their lipid and FA profile. Unlike HepG2 cells, HLCs contained low levels of lysophospholipids similar to the content of PHHs. Furthermore, HLCs were able to efficiently use the exogenous FAs available in their medium and simultaneously modify simple lipids into more complex ones to fulfill their needs. In addition, we propose that increasing the polyunsaturated FA supply of the culture medium may positively affect the lipid profile and functionality of HLCs. In conclusion, our data showed that HLCs provide a functional and relevant model to investigate human lipid homeostasis at both molecular and cellular levels.

Reshaping Lipid Biochemistry by Pushing Barriers in Structural Lipidomics.

Lipidomics is a rapidly growing field with numerous examples showing the importance of lipid molecules throughout biology. It has also shed light onto the vast and complex functions performed by many lipids that possess an immense diversity in molecular structures. Mass spectrometry (MS) is the tool of choice for analyzing lipids and has been the key catalyst driving the field forward. However, MS does not yet permit true molecular lipidomics wherein the identification and quantification of lipids having defined molecular structures can be routinely achieved. Here we describe recent advances in MS-based lipidomics that allow access to higher levels of molecular information in lipidomics experiments. These advances will form a key piece of the puzzle as the field moves towards systems characterization of lipids at the molecular level.

MS-based lipidomics of human blood plasma: a community-initiated position paper to develop accepted guidelines.

Human blood is a self-regenerating lipid-rich biological fluid that is routinely collected in hospital settings. The inventory of lipid molecules found in blood plasma (plasma lipidome) offers insights into individual metabolism and physiology in health and disease. Disturbances in the plasma lipidome also occur in conditions that are not directly linked to lipid metabolism; therefore, plasma lipidomics based on MS is an emerging tool in an array of clinical diagnostics and disease management. However, challenges exist in the translation of such lipidomic data to clinical applications. These relate to the reproducibility, accuracy, and precision of lipid quantitation, study design, sample handling, and data sharing. This position paper emerged from a workshop that initiated a community-led process to elaborate and define a set of generally accepted guidelines for quantitative MS-based lipidomics of blood plasma or serum, with harmonization of data acquired on different instrumentation platforms across independent laboratories as an ultimate goal. We hope that other fields may benefit from and follow such a precedent.

Lipidomic Analysis.

The state-of-art in the lipidomic analysis is summarized here to provide the overview of available sample preparation strategies, mass spectrometry (MS)-based methods for the qualitative analysis of lipids, and the quantitative MS approaches for high-throughput clinical workflows. Major challenges in terms of widely accepted best practices for lipidomic analysis, nomenclature, and standards for data reporting are discussed as well.

Proteomics and Lipidomics in Inflammatory Bowel Disease Research: From Mechanistic Insights to Biomarker Identification.

Inflammatory bowel disease (IBD) represents a group of progressive disorders characterized by recurrent chronic inflammation of the gut. Ulcerative colitis and Crohn's disease are the major manifestations of IBD. While our understanding of IBD has progressed in recent years, its etiology is far from being fully understood, resulting in suboptimal treatment options. Complementing other biological endpoints, bioanalytical "omics" methods that quantify many biomolecules simultaneously have great potential in the dissection of the complex pathogenesis of IBD. In this review, we focus on the rapidly evolving proteomics and lipidomics technologies and their broad applicability to IBD studies; these range from investigations of immune-regulatory mechanisms and biomarker discovery to studies dissecting host⁻microbiome interactions and the role of intestinal epithelial cells. Future studies can leverage recent advances, including improved analytical methodologies, additional relevant sample types, and integrative multi-omics analyses. Proteomics and lipidomics could effectively accelerate the development of novel targeted treatments and the discovery of complementary biomarkers, enabling continuous monitoring of the treatment response of individual patients; this may allow further refinement of treatment and, ultimately, facilitate a personalized medicine approach to IBD.

Interdigitation of long-chain sphingomyelin induces coupling of membrane leaflets in a cholesterol dependent manner.

It has been a long-standing question how the two leaflets in a lipid bilayer modulate each others' physical properties. In this paper, we discuss how this interaction may take place through interdigitation. We use atomistic molecular dynamics simulations to consider asymmetric lipid membrane models whose compositions are based on the lipidomics data determined for exosomes released by PC-3 prostate cancer cells. The simulations show interdigitation to be exceptionally strong for long-chain sphingomyelin (SM) molecules. In asymmetric membranes the amide-linked chain of SM is observed to extend deep into the opposing membrane leaflet. Interestingly, we find that the conformational order of the amide-linked SM chain increases the deeper it penetrates to the opposing leaflet. Analysis of this finding reveals that the amide-linked SM chain interacts favorably with the lipid chains in the opposite leaflet, and that cholesterol modulates the effect of SM interdigitation by influencing the conformational order of lipid hydrocarbon chains in the opposing (cytosolic) leaflet.

ARAP2 promotes GLUT1-mediated basal glucose uptake through regulation of sphingolipid metabolism.

Lipid droplet formation, which is driven by triglyceride synthesis, requires several droplet-associated proteins. We identified ARAP2 (an ADP-ribosylation factor 6 GTPase-activating protein) in the lipid droplet proteome of NIH-3T3 cells and showed that knockdown of ARAP2 resulted in decreased lipid droplet formation and triglyceride synthesis. We also showed that ARAP2 knockdown did not affect fatty acid uptake but reduced basal glucose uptake, total levels of the glucose transporter GLUT1, and GLUT1 levels in the plasma membrane and the lipid micro-domain fraction (a specialized plasma membrane domain enriched in sphingolipids). Microarray analysis showed that ARAP2 knockdown altered expression of genes involved in sphingolipid metabolism. Because sphingolipids are known to play a key role in cell signaling, we performed lipidomics to further investigate the relationship between ARAP2 and sphingolipids and potentially identify a link with glucose uptake. We found that ARAP2 knockdown increased glucosylceramide and lactosylceramide levels without affecting ceramide levels, and thus speculated that the rate-limiting enzyme in glycosphingolipid synthesis, namely glucosylceramide synthase (GCS), could be modified by ARAP2. In agreement with our hypothesis, we showed that the activity of GCS was increased by ARAP2 knockdown and reduced by ARAP2 overexpression. Furthermore, pharmacological inhibition of GCS resulted in increases in basal glucose uptake, total GLUT1 levels, triglyceride biosynthesis from glucose, and lipid droplet formation, indicating that the effects of GCS inhibition are the opposite to those resulting from ARAP2 knockdown. Taken together, our data suggest that ARAP2 promotes lipid droplet formation by modifying sphingolipid metabolism through GCS.

Reporting of lipidomics data should be standardized.

This article highlights, to our opinion, some of the most pertinent issues related to producing high quality lipidomics data. These issues include pitfalls related to sample collection and storage, lipid extraction, the use of shotgun and LC-MS-based lipidomics approaches, and the identification, annotation and quantification of lipid species. We hope that highlighting these issues will help stimulate efforts to implement reporting standards for dissemination of lipidomics data. This article is part of a Special Issue entitled: BBALIP_Lipidomics Opinion Articles edited by Sepp Kohlwein.

Circulating Ceramides Predict Cardiovascular Outcomes in the Population-Based FINRISK 2002 Cohort.

OBJECTIVE: Ceramides are molecular lipids implicated in apoptosis, inflammation, obesity, and insulin resistance. An earlier study reported that ceramides were associated with fatal outcome among patients with coronary heart disease. Here, we examined whether ceramides are associated with major adverse cardiovascular events (MACEs) among apparently healthy individuals. APPROACH AND RESULTS: FINRISK 2002 is a population-based risk factor survey, which recruited men and women aged 25 to 74 years. The cohort was followed up until the end of 2014. We quantified 4 circulating ceramides, Cer(d18:1/16:0), Cer(d18:1/18:0), Cer(d18:1/24:0), and Cer(d18:1/24:1), in 8101 serum samples by a targeted liquid chromatography-tandem mass spectrometry assay. Primary outcome of interest was incident MACE (n=813). Secondary analyses were performed for MACE death (n=116) without previous nonfatal MACE and for recurrent MACE (n=226) among survivors of a previous incident MACE. We used Cox proportional hazard models adjusted for the Framingham covariates to determine the association of ceramides with the outcomes. Of the ceramide species, Cer(d18:1/18:0) had the strongest association with incident MACE and the highest unadjusted hazard ratio of 1.31 (95% confidence interval, 1.21-1.41), which remained significant at 1.21 (95% confidence interval, 1.11-1.33) after Framingham risk factor adjustments. The hazard ratios were generally stronger for recurrent and fatal events than for first events. Clinical net reclassification improvement was 7.5% (P=6.9×10-5) for Cer(d18:1/18:0). CONCLUSIONS: Distinct serum ceramides are associated with the risk of incident MACE in apparently healthy individuals. These results should encourage more detailed analyses of ceramides in cardiovascular pathobiology and suggest new biomarkers of MACE risk.

Plasma ceramides predict cardiovascular death in patients with stable coronary artery disease and acute coronary syndromes beyond LDL-cholesterol.

AIMS: The aim was to study the prognostic value of plasma ceramides (Cer) as cardiovascular death (CV death) markers in three independent coronary artery disease (CAD) cohorts. METHODS AND RESULTS: Corogene study is a prospective Finnish cohort including stable CAD patients (n = 160). Multiple lipid biomarkers and C-reactive protein were measured in addition to plasma Cer(d18:1/16:0), Cer(d18:1/18:0), Cer(d18:1/24:0), and Cer(d18:1/24:1). Subsequently, the association between high-risk ceramides and CV mortality was investigated in the prospective Special Program University Medicine-Inflammation in Acute Coronary Syndromes (SPUM-ACS) cohort (n = 1637), conducted in four Swiss university hospitals. Finally, the results were validated in Bergen Coronary Angiography Cohort (BECAC), a prospective Norwegian cohort study of stable CAD patients. Ceramides, especially when used in ratios, were significantly associated with CV death in all studies, independent of other lipid markers and C-reactive protein. Adjusted odds ratios per standard deviation for the Cer(d18:1/16:0)/Cer(d18:1/24:0) ratio were 4.49 (95% CI, 2.24-8.98), 1.64 (1.29-2.08), and 1.77 (1.41-2.23) in the Corogene, SPUM-ACS, and BECAC studies, respectively. The Cer(d18:1/16:0)/Cer(d18:1/24:0) ratio improved the predictive value of the GRACE score (net reclassification improvement, NRI = 0.17 and ΔAUC = 0.09) in ACS and the predictive value of the Marschner score in stable CAD (NRI = 0.15 and ΔAUC = 0.02). CONCLUSIONS: Distinct plasma ceramide ratios are significant predictors of CV death both in patients with stable CAD and ACS, over and above currently used lipid markers. This may improve the identification of high-risk patients in need of more aggressive therapeutic interventions.