Quantitative Fragmentation Model for Bottom-Up Shotgun Lipidomics

Accurate Sphingolipid Quantification Reducing Fragmentation Bias by Nonlinear Models

Quantitative sphingolipid analysis is crucial for understanding the roles of these bioactive molecules in various physiological and pathological contexts. Molecular sphingolipid species are typically quantified using sphingoid base-derived fragments relative to a class-specific internal standard. However, the commonly employed "one standard per class" strategy fails to account for fragmentation differences presented by the structural diversity of sphingolipids. To address this limitation, we developed a novel approach for quantitative sphingolipid analysis. This approach utilizes fragmentation models to correct for structural differences and thus overcomes the limitations associated with using a limited number of standards for quantification. Importantly, our method is independent of the internal standard, instrumental setup, and collision energy. Furthermore, we integrated this method into a user-friendly KNIME workflow. The validation results illustrate the effectiveness of our approach in accurately quantifying ceramide subclasses from various biological matrices. This breakthrough opens up new avenues for exploring sphingolipid metabolism and gaining insights into its implications.

Sortase A-Cleavable CD1d Identifies Sphingomyelins as Major Class of CD1d-Associated Lipids

CD1d is an atypical MHC class I molecule which binds endogenous and exogenous lipids and can activate natural killer T (NKT) cells through the presentation of lipid antigens. CD1d surveys different cellular compartments including the secretory and the endolysosomal pathway and broadly binds lipids through its two hydrophobic pockets. Purification of the transmembrane protein CD1d for the analysis of bound lipids is technically challenging as the use of detergents releases CD1d-bound lipids. To address these challenges, we have developed a novel approach based on Sortase A-dependent enzymatic release of CD1d at the cell surface of live mammalian cells, which allows for single step release and affinity tagging of CD1d for shotgun lipidomics. Using this system, we demonstrate that CD1d carrying the Sortase A recognition motif shows unimpaired subcellular trafficking through the secretory and endolysosomal pathway and is able to load lipids in these compartments and present them to NKT cells. Comprehensive shotgun lipidomics demonstrated that the spectrum and abundance of CD1d-associated lipids is not representative of the total cellular lipidome but rather characterized by preferential binding to long chain sphingolipids and glycerophospholipids. As such, sphingomyelin species recently identified as critical negative regulators of NKT cell activation, represented the vast majority of endogenous CD1d-associated lipids. Moreover, we observed that inhibition of endolysosomal trafficking of CD1d surprisingly did not affect the spectrum of CD1d-bound lipids, suggesting that the majority of endogenous CD1d-associated lipids load onto CD1d in the secretory rather than the endolysosomal pathway. In conclusion, we present a novel system for the analysis of CD1d-bound lipids in mammalian cells and provide new insight into the spectrum of CD1d-associated lipids, with important functional implications for NKT cell activation.

Quantitative determination of sn-positional phospholipid isomers in MSn using silver cationization

Glycerophospholipids are one of the fundamental building blocks for life. The acyl chain connectivity to the glycerol backbone constitutes different sn-positional isomers, which have great diversity and importance for biological function. However, to fully realize their impact on function, analytical techniques that can identify and quantify sn-positional isomers in chemically complex biological samples are needed. Here, we utilize silver ion cationization in combination with tandem mass spectrometry (MSⁿ) to identify sn-positional isomers of phosphatidylcholine (PC) species. In particular, a labile carbocation is generated through a neutral loss (NL) of AgH, the dissociation of which provides diagnostic product ions that correspond to acyl chains at the sn-1 or sn-2 position. The method is comparable to currently available methods, has a sensitivity in the nM–µM range, and is compatible with quantitative imaging using mass spectrometry in MS⁴. The results reveal a large difference in isomer concentrations and the ion images show that the sn-positional isomers PC 18:1_18:0 are homogeneously distributed, whereas PC 18:1_16:0 and PC 20:1_16:0 show distinct localizations to sub-hippocampal structures.

Hepatic Hedgehog Signaling Participates in the Crosstalk between Liver and Adipose Tissue in Mice by Regulating FGF21

The Hedgehog signaling pathway regulates many processes during embryogenesis and the homeostasis of adult organs. Recent data suggest that central metabolic processes and signaling cascades in the liver are controlled by the Hedgehog pathway and that changes in hepatic Hedgehog activity also affect peripheral tissues, such as the reproductive organs in females. Here, we show that hepatocyte-specific deletion of the Hedgehog pathway is associated with the dramatic expansion of adipose tissue in mice, the overall phenotype of which does not correspond to the classical outcome of insulin resistance-associated diabetes type 2 obesity. Rather, we show that alterations in the Hedgehog signaling pathway in the liver lead to a metabolic phenotype that is resembling metabolically healthy obesity. Mechanistically, we identified an indirect influence on the hepatic secretion of the fibroblast growth factor 21, which is regulated by a series of signaling cascades that are directly transcriptionally linked to the activity of the Hedgehog transcription factor GLI1. The results of this study impressively show that the metabolic balance of the entire organism is maintained via the activity of morphogenic signaling pathways, such as the Hedgehog cascade. Obviously, several pathways are orchestrated to facilitate liver metabolic status to peripheral organs, such as adipose tissue.

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.

Tricky Isomers—The Evolution of Analytical Strategies to Characterize Plasmalogens and Plasmanyl Ether Lipids

Typically, glycerophospholipids are represented with two esterified fatty acids. However, by up to 20%, a significant proportion of this lipid class carries an ether-linked fatty alcohol side chain at the sn-1 position, generally referred to as ether lipids, which shape their specific physicochemical properties. Among those, plasmalogens represent a distinct subgroup characterized by an sn-1 vinyl-ether double bond. The total loss of ether lipids in severe peroxisomal defects such as rhizomelic chondrodysplasia punctata indicates their crucial contribution to diverse cellular functions. An aberrant ether lipid metabolism has also been reported in multifactorial conditions including Alzheimer’s disease. Understanding the underlying pathological implications is hampered by the still unclear exact functional spectrum of ether lipids, especially in regard to the differentiation between the individual contributions of plasmalogens (plasmenyl lipids) and their non-vinyl-ether lipid (plasmanyl) counterparts. A primary reason for this is that exact identification and quantification of plasmalogens and other ether lipids poses a challenging and usually labor-intensive task. Diverse analytical methods for the detection of plasmalogens have been developed. Liquid chromatography–tandem mass spectrometry is increasingly used to resolve complex lipid mixtures, and with optimized parameters and specialized fragmentation strategies, discrimination between ethers and plasmalogens is feasible. In this review, we recapitulate historic and current methodologies for the recognition and quantification of these important lipids and will discuss developments in this field that can contribute to the characterization of plasmalogens in high structural detail.

Achieving Absolute Molar Lipid Concentrations: A Phospholipidomics Cross-Validation Study

Standardization is essential in lipidomics and part of a huge community effort. However, with the still ongoing lack of reference materials, benchmarking quantification is hampered. Here, we propose traceable lipid class quantification as an important layer for the validation of quantitative lipidomics workflows. 31P nuclear magnetic resonance (NMR) and inductively coupled plasma (ICP)-mass spectrometry (MS) can use certified species-unspecific standards to validate shotgun or liquid chromatography (LC)-MS-based lipidomics approaches. We further introduce a novel lipid class quantification strategy based on lipid class separation and mass spectrometry using an all ion fragmentation (AIF) approach. Class-specific fragments, measured over a mass range typical for the lipid classes, are integrated to assess the lipid class concentration. The concept proved particularly interesting as low absolute limits of detection in the fmol range were achieved and LC-MS platforms are widely used in the field of lipidomics, while the accessibility of NMR and ICP-MS is limited. Using completely independent calibration strategies, the introduced validation scheme comprised the quantitative assessment of the complete phospholipid sub-ome, next to the individual lipid classes. Komagataella phaffii served as a prime example, showcasing mass balances and supporting the value of benchmarks for quantification at the lipid species level.

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.

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.

An advanced method for propargylcholine phospholipid detection by direct-infusion MS

Phospholipids with a choline head group are an abundant component of cellular membranes and are involved in many important biological functions. For studies on the cell biology and metabolism of these lipids, traceable analogues where propargylcholine replaces the choline head group have proven useful. We present a novel method to analyze propargylcholine phospholipids by MS. The routine employs 1-radyl-2-lyso-sn-glycero-3-phosphopropargylcholines as labeled lysophosphatidylcholine precursors, which upon cellular conversion direct the traceable tag with superb specificity and efficiency to the primary target lipid class. Using azidopalmitate as a click-chemistry reporter, we introduce a highly specific, sensitive, and robust MS detection procedure for the propargylcholine phospholipids. In a first study, we apply the new technique to investigate choline phospholipid metabolism in brain endothelial cells. These experiments reveal differences in the metabolism of phosphatidylcholine and its pendant, ether phosphatidylcholine. The novel method described here opens a new, quantitative, and detailed view on propargylcholine phospholipid metabolism and will greatly facilitate future studies on choline phospholipid metabolism.

LipidCreator workbench to probe the lipidomic landscape

Mass spectrometry (MS)-based targeted lipidomics enables the robust quantification of selected lipids under various biological conditions but comprehensive software tools to support such analyses are lacking. Here we present LipidCreator, a software that fully supports targeted lipidomics assay development. LipidCreator offers a comprehensive framework to compute MS/MS fragment masses for over 60 lipid classes. LipidCreator provides all functionalities needed to define fragments, manage stable isotope labeling, optimize collision energy and generate in silico spectral libraries. We validate LipidCreator assays computationally and analytically and prove that it is capable to generate large targeted experiments to analyze blood and to dissect lipid-signaling pathways such as in human platelets.

Software tools, databases and resources in metabolomics: updates from 2018 to 2019

Metabolomics has evolved as a discipline from a discovery and functional genomics tool, and is now a cornerstone in the era of big data-driven precision medicine. Sample preparation strategies and analytical technologies have seen enormous growth, and keeping pace with data analytics is challenging, to say the least. This review introduces and briefly presents around 100 metabolomics software resources, tools, databases, and other utilities that have surfaced or have improved in 2019. Table 1 provides the computational dependencies of the tools, categorizes the resources based on utility and ease of use, and provides hyperlinks to webpages where the tools can be downloaded or used. This review intends to keep the community of metabolomics researchers up to date with all the software tools, resources, and databases developed in 2019, in one place.