Software and Computational Tools for LC-MS-Based Epilipidomics: Challenges and Solutions

Non-targeted mass spectrometry and feature-based molecular networking for determination of branched fatty acid esters of hydroxy fatty acids in milk

Branched fatty acid esters of hydroxy fatty acids (FAHFAs) represent trace lipids with significant natural biological functions. While exogenous FAHFAs have been extensively studied, research on FAHFAs in milk remains limited, constraining our grasp of their nutritional roles. This study introduces a non-targeted mass spectrometry approach combined with chemical networking of spectral fragmentation patterns to uncover FAHFAs. Through meticulous sample handling and comparisons of various data acquisition and processing modes, we validate the method's superiority, identifying twice as many FAHFAs compared to alternative techniques. This validated method was then applied to different milk samples, revealing 45 chemical signals associated with known and potential FAHFAs, alongside findings of 66 ceramide/hexosylceramide (Cer/HexCer), 48 phosphatidyl ethanolamine/lyso phosphatidyl ethanolamine (PE/LPE), 21 phosphatidylcholine/lysophosphatidylcholine (PC/LPC), 16 phosphatidylinositol (PI), 7 phosphatidylserine (PS), and 11 sphingomyelin (SM) compounds. This study expands our understanding of the FAHFA family in milk and provides a fast and convenient method for identifying FAHFAs.

Integrative deep learning framework predicts lipidomics-based investigation of preservatives on meat nutritional biomarkers and metabolic pathways

Preservatives are added as antimicrobial agents to extend the shelf life of meat. Adding preservatives to meat products can affect their flavor and nutrition. This review clarifies the effects of preservatives on metabolic pathways and network molecular transformations in meat products based on lipidomics, metabolomics and proteomics analyses. Preservatives change the nutrient content of meat products via altering ionic strength and pH to influence enzyme activity. Ionic strength in salt triggers muscle triglyceride hydrolysis by causing phosphorylation and lipid droplet splitting in adipose tissue hormone-sensitive lipase and triglyceride lipase. DisoLipPred exploiting deep recurrent networks and transfer learning can predict the lipid binding trend of each amino acid in the disordered region of input protein sequences, which could provide omics analyses of biomarkers metabolic pathways in meat products. While conventional meat quality assessment tools are unable to elucidate the intrinsic mechanisms and pathways of variables in the influences of preservatives on the quality of meat products, the promising application of omics techniques in food analysis and discovery through multimodal learning prediction algorithms of neural networks (e.g., deep neural network, convolutional neural network, artificial neural network) will drive the meat industry to develop new strategies for food spoilage prevention and control.

Lipid Quality Control and Ferroptosis: From Concept to Mechanism

Cellular quality control systems sense and mediate homeostatic responses to prevent the buildup of aberrant macromolecules, which arise from errors during biosynthesis, damage by environmental insults, or imbalances in enzymatic and metabolic activity. Lipids are structurally diverse macromolecules that have many important cellular functions, ranging from structural roles in membranes to functions as signaling and energy-storage molecules. As with other macromolecules, lipids can be damaged (e.g., oxidized), and cells require quality control systems to ensure that nonfunctional and potentially toxic lipids do not accumulate. Ferroptosis is a form of cell death that results from the failure of lipid quality control and the consequent accumulation of oxidatively damaged phospholipids. In this review, we describe a framework for lipid quality control, using ferroptosis as an illustrative example to highlight concepts related to lipid damage, membrane remodeling, and suppression or detoxification of lipid damage via preemptive and damage-repair lipid quality control pathways. Expected final online publication date for the Annual Review of Biochemistry , Volume 93 is June 2024. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

An overview of food lipids toward food lipidomics

Increasing evidence regarding lipids' beneficial effects on human health has changed the common perception of consumers and dietary officials about the role(s) of food lipids in a healthy diet. However, lipids are a wide group of molecules with specific nutritional and bioactive properties. To understand their true nutritional and functional value, robust methods are needed for accurate identification and quantification. Specific analytical strategies are crucial to target specific classes, especially the ones present in trace amounts. Finding a unique and comprehensive methodology to cover the full lipidome of each foodstuff is still a challenge. This review presents an overview of the lipids nutritionally relevant in foods and new trends in food lipid analysis for each type/class of lipids. Food lipid classes are described following the LipidMaps classification, fatty acids, endocannabinoids, waxes, C8 compounds, glycerophospholipids, glycerolipids (i.e., glycolipids, betaine lipids, and triglycerides), sphingolipids, sterols, sercosterols (vitamin D), isoprenoids (i.e., carotenoids and retinoids (vitamin A)), quinones (i.e., coenzyme Q, vitamin K, and vitamin E), terpenes, oxidized lipids, and oxylipin are highlighted. The uniqueness of each food group: oil-, protein-, and starch-rich, as well as marine foods, fruits, and vegetables (water-rich) regarding its lipid composition, is included. The effect of cooking, food processing, and storage, in addition to the importance of lipidomics in food quality and authenticity, are also discussed. A critical review of challenges and future trends of the analytical approaches and computational methods in global food lipidomics as the basis to increase consumer awareness of the significant role of lipids in food quality and food security worldwide is presented.

LORA, Lipid Over-Representation Analysis Based on Structural Information

With the increasing number of lipidomic studies, there is a need for an efficient and automated analysis of lipidomic data. One of the challenges faced by most existing approaches to lipidomic data analysis is lipid nomenclature. The systematic nomenclature of lipids contains all available information about the molecule, including its hierarchical representation, which can be used for statistical evaluation. The Lipid Over-Representation Analysis (LORA) web application (https://lora.metabolomics.fgu.cas.cz) analyzes this information using the Java-based Goslin framework, which translates lipid names into a standardized nomenclature. Goslin provides the level of lipid hierarchy, including information on headgroups, acyl chains, and their modifications, up to the "complete structure" level. LORA allows the user to upload the experimental query and reference data sets, select a grammar for lipid name normalization, and then process the data. The user can then interactively explore the results and perform lipid over-representation analysis based on selected criteria. The results are graphically visualized according to the lipidome hierarchy. The lipids present in the most over-represented terms (lipids with the highest number of enriched shared structural features) are defined as Very Important Lipids (VILs). For example, the main result of a demo data set is the information that the query is significantly enriched with "glycerophospholipids" containing "acyl 20:4" at the "sn-2 position". These terms define a set of VILs (e.g., PC 18:2/20:4;O and PE 16:0/20:4(5,8,10,14);OH). All results, graphs, and visualizations are summarized in a report. LORA is a tool focused on the smart mining of epilipidomics data sets to facilitate their interpretation at the molecular level.

Analytical Toolbox to Unlock the Diversity of Oxidized Lipids

ConspectusLipids are diverse class of small biomolecules represented by a large variety of chemical structures. In addition to the classical biosynthetic routes, lipids can undergo numerous modifications via introduction of small chemical moieties forming hydroxyl, phospho, and nitro derivatives, among others. Such modifications change the physicochemical properties of a parent lipid and usually result in new functionalities either by mediating signaling events or by changing the biophysical properties of lipid membranes. Over the last decades, a large body of evidence indicated the involvement of lipid modifications in a variety of physiological and pathological events. For instance, lipid (per)oxidation for a long time was considered as a hallmark of oxidative stress and related proinflammatory signaling. Recently, however, with the burst in the development of the redox biology field, oxidative modifications of lipids are also recognized as a part of regulatory and adaptive events that are highly specific for particular cell types, tissues, and conditions.The initial diversity of lipid species and the variety of possible lipid modifications result in an extremely large chemical space of the epilipidome, the subset of the natural lipidome formed by enzymatic and non-enzymatic lipid modifications occurring in biological systems. Together with their low natural abundance, structural annotation of modified lipids represents a major analytical challenge limiting the discovery of their natural variety and functions. Furthermore, the number of available chemically characterized standards representing various modified lipid species remains limited, making analytical and functional studies very challenging. Over the past decade we have developed and implemented numerous analytical methods to study lipid modifications and applied them in the context of different biological conditions. In this Account, we outline the development and evolution of modern mass-spectrometry-based techniques for the structural elucidation of modified/oxidized lipids and corresponding applications. Research of our group is mostly focused on redox biology, and thus, our primary interest was always the analysis of lipid modifications introduced by redox disbalance, including lipid peroxidation (LPO), oxygenation, nitration, and glycation. To this end, we developed an array of analytical solutions to measure carbonyls derived from LPO, oxidized and nitrated fatty acid derivatives, and oxidized and glycated complex lipids. We will briefly describe the main analytical challenges along with corresponding solutions developed by our group toward deciphering the complexity of natural epilipdomes, starting from in vitro-oxidized lipid mixtures, artificial membranes, and lipid droplets, to illustrate the diversity of lipid modifications in the context of metabolic diseases and ferroptotic cell death.

Decoding Metabolic Reprogramming in Plants under Pathogen Attacks, a Comprehensive Review of Emerging Metabolomics Technologies to Maximize Their Applications

In their environment, plants interact with a multitude of living organisms and have to cope with a large variety of aggressions of biotic or abiotic origin. What has been known for several decades is that the extraordinary variety of chemical compounds the plants are capable of synthesizing may be estimated in the range of hundreds of thousands, but only a fraction has been fully characterized to be implicated in defense responses. Despite the vast importance of these metabolites for plants and also for human health, our knowledge about their biosynthetic pathways and functions is still fragmentary. Recent progress has been made particularly for the phenylpropanoids and oxylipids metabolism, which is more emphasized in this review. With an increasing interest in monitoring plant metabolic reprogramming, the development of advanced analysis methods should now follow. This review capitalizes on the advanced technologies used in metabolome mapping in planta, including different metabolomics approaches, imaging, flux analysis, and interpretation using bioinformatics tools. Advantages and limitations with regards to the application of each technique towards monitoring which metabolite class or type are highlighted, with special emphasis on the necessary future developments to better mirror such intricate metabolic interactions in planta.