Guiding the choice of informatics software and tools for lipidomics research applications.

Progress in mass spectrometry lipidomics has led to a rapid proliferation of studies across biology and biomedicine. These generate extremely large raw datasets requiring sophisticated solutions to support automated data processing. To address this, numerous software tools have been developed and tailored for specific tasks. However, for researchers, deciding which approach best suits their application relies on ad hoc testing, which is inefficient and time consuming. Here we first review the data processing pipeline, summarizing the scope of available tools. Next, to support researchers, LIPID MAPS provides an interactive online portal listing open-access tools with a graphical user interface. This guides users towards appropriate solutions within major areas in data processing, including (1) lipid-oriented databases, (2) mass spectrometry data repositories, (3) analysis of targeted lipidomics datasets, (4) lipid identification and (5) quantification from untargeted lipidomics datasets, (6) statistical analysis and visualization, and (7) data integration solutions. Detailed descriptions of functions and requirements are provided to guide customized data analysis workflows.

Targeting Sphingosine-1-Phosphate Signaling to Prevent the Progression of Aortic Valve Disease.

BACKGROUND: Aortic valve disease (AVD) is associated with high mortality and morbidity. To date, there is no pharmacological therapy available to prevent AVD progression. Because valve calcification is the hallmark of AVD and S1P (sphingosine-1-phosphate) plays an important role in osteogenic signaling, we examined the role of S1P signaling in aortic stenosis disease. METHODS: AVD progression and its consequences for cardiac function were examined in a murine wire injury-induced AVD model with and without pharmacological and genetic modulation of S1P production, degradation, and receptor signaling. S1P was measured by LC-MS. Calcification of valvular interstitial cells and their response to biomechanical stress were analyzed in the context of S1P signaling. Human explanted aortic valves from patients undergoing aortic valve replacement and cardiovascular magnetic resonance imaging were analyzed for S1P by LC-MS. RESULTS: Raising S1P concentrations in mice with injury-induced AVD by pharmacological inhibition of its sole degrading enzyme S1P lyase vastly enhanced AVD progression and impaired cardiac function resembling human disease. In contrast, low S1P levels caused by SphK1 (sphingosine kinase 1) deficiency potently attenuated AVD progression. We found S1P/S1PR2 (S1P receptor 2) signaling to be responsible for the adverse S1P effect because S1PR2-deficient mice were protected against AVD progression and its deterioration by high S1P. It is important to note that pharmacological S1PR2 inhibition administered after wire injury successfully prevented AVD development. Mechanistically, biomechanical stretch stimulated S1P production by SphK1 in human valvular interstitial cells as measured by C17-S1P generation, whereas S1P/S1PR2 signaling induced their osteoblastic differentiation and calcification through osteogenic RUNX2/OPG signaling and the GSK3ß-Wnt-ß-catenin pathway. In patients with AVD, stenotic valves exposed to high wall shear stress had higher S1P content and increased SphK1 expression. CONCLUSIONS: Increased systemic or local S1P levels lead to increased valvular calcification. S1PR2 antagonists and SphK1 inhibitors may offer feasible pharmacological approaches to human AVD in prophylactic, disease-modifying or relapse-preventing manners.

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.

Lipidome Unsaturation Affects the Morphology and Proteome of the Drosophila Eye.

Organisms respond to dietary and environmental challenges by altering the molecular composition of their glycerolipids and glycerophospholipids (GPLs), which may favorably adjust the physicochemical properties of lipid membranes. However, how lipidome changes affect the membrane proteome and, eventually, the physiology of specific organs is an open question. We addressed this issue in Drosophila melanogaster, which is not able to synthesize sterols and polyunsaturated fatty acids but can acquire them from food. We developed a series of semisynthetic foods to manipulate the length and unsaturation of fatty acid moieties in GPLs and singled out proteins whose abundance is specifically affected by membrane lipid unsaturation in the Drosophila eye. Unexpectedly, we identified a group of proteins that have muscle-related functions and increased their abundances under unsaturated eye lipidome conditions. In contrast, the abundance of two stress response proteins, Turandot A and Smg5, is decreased by lipid unsaturation. Our findings could guide the genetic dissection of homeostatic mechanisms that maintain visual function when the eye is exposed to environmental and dietary challenges.

A Targeted, Bioinert LC-MS/MS Method for Sensitive, Comprehensive Analysis of Signaling Lipids.

Signaling lipids are key players in cellular processes. Despite their importance, no method currently allows their comprehensive monitoring in one analytical run. Challenges include a wide dynamic range, isomeric and isobaric species, and unwanted interaction along the separation path. Herein, we present a sensitive and robust targeted liquid chromatography-mass spectrometry (LC-MS/MS) approach to overcome these challenges, covering a broad panel of 17 different signaling lipid classes. It involves a simple one-phase sample extraction and lipid analysis using bioinert reversed-phase liquid chromatography coupled to targeted mass spectrometry. The workflow shows excellent sensitivity and repeatability in different biological matrices, enabling the sensitive and robust monitoring of 388 lipids in a single run of only 20 min. To benchmark our workflow, we characterized the human plasma signaling lipidome, quantifying 307 endogenous molecular lipid species. Furthermore, we investigated the signaling lipidome during platelet activation, identifying numerous regulations along important lipid signaling pathways. This highlights the potential of the presented method to investigate signaling lipids in complex biological systems, enabling unprecedentedly comprehensive analysis and direct insight into signaling pathways.

Eye proteome of Drosophila melanogaster.

Drosophila melanogaster is a popular model organism to elucidate the molecular mechanisms that underlie the structure and function of the eye as well as the causes of retinopathies, aging, light-induced damage, or dietary deficiencies. Large-scale screens have isolated genes whose mutation causes morphological and functional ocular defects, which led to the discovery of key components of the phototransduction cascade. However, the proteome of the Drosophila eye is poorly characterized. Here, we used GeLC-MS/MS to quantify 3516 proteins, including the absolute (molar) quantities of 43 proteins in the eye of adult male Drosophila reared on standard laboratory food. This work provides a generic and expandable resource for further genetic, pharmacological, and dietary studies.

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.

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.

Flexible Microtube Plasma for the Consecutive-Ionization of Cholesterol in Nano-Electrospray Mass Spectrometry.

Electrospray ionization mass spectrometry (ESI-MS) is an established method for the identification of biomarkers. By nano-ESI (nESI), the polar molecular fraction of complex biological samples can be successfully ionized. In contrast, the less-polar free cholesterol, which serves as an important biomarker for several human diseases, is barely accessible by nESI. Although, complex scan functions of modern high-resolution MS devices are able to increase the signal-to-noise ratio, they are limited by the ionization efficiency of the nESI. One possible method to increase the ionization efficiency is the derivatization with acetyl chloride, however interferences with cholesteryl esters must be considered, so chromatographic separation or complex scan functions may be required. A novel approach to increase the yield of cholesterol ions of the nESI could be the application of a second consecutive-ionization process. This publication presents the flexible microtube plasma (FµTP) as a consecutive-ionization source, which allows the determination of cholesterol in nESI-MS analysis. Focusing on the analytical performance, the nESI-FµTP approach increases the cholesterol signal yield in a complex liver extract by a factor of 49. The repeatability and long-term stability could be successfully evaluated. A linear dynamic range of 1.7 orders of magnitude, a minimum detectability of 5.46 mg/L, and a high accuracy (deviation, -8.1%) demonstrates the nESI-FµTP-MS as an excellent approach for a derivatization-free determination of cholesterol.

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).

ANXA7 Regulates Platelet Lipid Metabolism and Ca2+ Release in Arterial Thrombosis.

[Figure: see text].

Targeting early stages of cardiotoxicity from anti-PD1 immune checkpoint inhibitor therapy.

AIMS: Cardiac immune-related adverse events (irAEs) from immune checkpoint inhibition (ICI) targeting programmed death 1 (PD1) are of growing concern. Once cardiac irAEs become clinically manifest, fatality rates are high. Cardio-oncology aims to prevent detrimental effects before manifestation of severe complications by targeting early pathological changes. We therefore aimed to investigate early consequences of PD1 inhibition for cardiac integrity to prevent the development of overt cardiac disease. METHODS AND RESULTS: We investigated cardiac-specific consequences from anti-PD1 therapy in a combined biochemical and in vivo phenotyping approach. Mouse hearts showed broad expression of the ligand PDL1 on cardiac endothelial cells as a main mediator of immune-crosstalk. Using a novel melanoma mouse model, we assessed that anti-PD1 therapy promoted myocardial infiltration with CD4+ and CD8+ T cells, the latter being markedly activated. Left ventricular (LV) function was impaired during pharmacological stress, as shown by pressure-volume catheterization. This was associated with a dysregulated myocardial metabolism, including the proteome and the lipidome. Analogous to the experimental approach, in patients with metastatic melanoma (n = 7) receiving anti-PD1 therapy, LV function in response to stress was impaired under therapy. Finally, we identified that blockade of tumour necrosis factor alpha (TNFα) preserved LV function without attenuating the anti-cancer efficacy of anti-PD1 therapy. CONCLUSIONS: Anti-PD1 therapy induces a disruption of cardiac immune homeostasis leading to early impairment of myocardial functional integrity, with potential prognostic effects on the growing number of treated patients. Blockade of TNFα may serve as an approach to prevent the manifestation of ICI-related cardiotoxicity.

Analytical comparison of absolute quantification strategies to investigate the insulin signaling pathway in fat cells.

So far, mass spectrometry-based targeted proteomics is the most sensitive approach to answer and address specific biological questions in an accurate and quantitative fashion. However, the data analysis design used for such quantification varies in the field leading to discrepancies in the reported values. In this study, different quantification strategies based on calibration curves were evaluated and compared. The best accuracy and coefficient of variation was achieved by ratio to ratio calibration curves. We applied the ratio to ratio quantification approach to analyze very low abundant insulin signaling proteins such as PIK3RA (0.10-0.93 fmol/µg), AKT1 (0.1-0.39 fmol/µg), and the insulin receptor (0.22-2.62 fmol/µg) in a fat cell model and demonstrated the adaptation of this pathway at different states of insulin sensitivity.

Goslin 2.0 Implements the Recent Lipid Shorthand Nomenclature for MS-Derived Lipid Structures.

Goslin is the first grammar-based computational library for the recognition/parsing and normalization of lipid names following the hierarchical lipid shorthand nomenclature. The new version Goslin 2.0 implements the latest nomenclature and adds an additional grammar to recognize systematic IUPAC-IUB fatty acyl names as stored, e.g., in the LIPID MAPS database and is perfectly suited to update lipid names in LIPID MAPS or HMDB databases to the latest nomenclature. Goslin 2.0 is available as a standalone web application with a REST API as well as C++, C#, Java, Python 3, and R libraries. Importantly, it can be easily included in lipidomics tools and scripts providing direct access to translation functions. All implementations are open source.

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.

Targeted Phosphoinositides Analysis Using High-Performance Ion Chromatography-Coupled Selected Reaction Monitoring Mass Spectrometry.

Phosphoinositides are minor components of cell membranes, but play crucial roles in numerous signal transduction pathways. To obtain quantitative measures of phosphoinositides, sensitive, accurate, and comprehensive methods are needed. Here, we present a quantitative targeted ion chromatography-mass spectrometry-based workflow that separates phosphoinositide isomers and increases the quantitative accuracy of measured phosphoinositides. Besides testing different analytical characteristics such as extraction and separation efficiency, the reproducibility of the developed workflow was also investigated. The workflow was verified in resting and stimulated human platelets, fat cells, and rat hippocampal brain tissue, where the LOD and LOQ for phosphoinositides were at 312.5 and 625 fmol, respectively. The robustness of the workflow is shown with different applications that confirms its suitability to analyze multiple less-abundant phosphoinositides.

ArhGEF37 assists dynamin 2 during clathrin-mediated endocytosis.

Clathrin-mediated endocytosis (CME) engages over 30 proteins to secure efficient cargo and membrane uptake. While the function of most core CME components is well established, auxiliary mechanisms crucial for fine-tuning and adaptation remain largely elusive. In this study, we identify ArhGEF37, a currently uncharacterized protein, as a constituent of CME. Structure prediction together with quantitative cellular and biochemical studies present a unique BAR domain and PI(4,5)P2-dependent protein-membrane interactions. Functional characterization yields accumulation of ArhGEF37 at dynamin 2-rich late endocytic sites and increased endocytosis rates in the presence of ArhGEF37. Together, these results introduce ArhGEF37 as a regulatory protein involved in endocytosis.

Developing a Robust Assay to Monitor and Quantify Key Players of Metabolic Pathways during Adipogenesis by Targeted Proteomics.

Targeted data acquisition using nano liquid chromatrography (nano-LC) coupled mass spectrometry is an emerging approach when there is a need to quantify proteins with high accuracy, sensitivity, and reproducibility. Nevertheless, creating assays meeting all those criteria still remains a laborious task, especially when investigating low abundant proteins and small concentration changes. In this work a targeted data acquisition workflow is developed reducing time and effort to target and investigate key players of metabolic pathways during the process of adipocyte differentiation. This leads to accurate and sensitive quantification of proteins involved in the synthesis of fatty acids, glycerolipids, glycerophospholipids, sphingolipids, the production of energy and reduction equivalents. Additionally low abundant signaling molecules part of the peroxisome proliferator-activated receptor gamma (PPARγ) and insulin signaling pathway with ≈400 for the insulin receptor substrate and 1100 copies per cell for PPARγ are determined.

Goslin: A Grammar of Succinct Lipid Nomenclature.

We introduce Goslin, a polyglot grammar for common lipid shorthand nomenclatures based on the LIPID MAPS nomenclature and the shorthand nomenclature established by Liebisch and coauthors and used by LipidHome and SwissLipids. Goslin was designed to address the following pressing issues in the lipidomics field: (1) to simplify the implementation of lipid name handling for developers of mass spectrometry-based lipidomics tools, (2) to offer a tool that unifies and normalizes the main existing lipid name dialects enabling a lipidomics analysis in a high-throughput fashion, and (3) to provide a consistent mapping from lipid shorthand names to lipid building blocks and structural properties. We provide implementations of Goslin in four major programming languages, namely, C++, Java, Python 3, and R to kick-start adoption and integration. Further, we set up a web service for users to work with Goslin directly. All implementations are available free of charge under a permissive open source license.