Lipidomics: Techniques, Applications, and Outcomes Related to Biomedical Sciences

Caenorhabditis elegans deep lipidome profiling by using integrative mass spectrometry acquisitions reveals significantly altered lipid networks

Lipidomics coverage improvement is essential for functional lipid and pathway construction. A powerful approach to discovering organism lipidome is to combine various data acquisitions, such as full scan mass spectrometry (full MS), data-dependent acquisition (DDA), and data-independent acquisition (DIA). Caenorhabditis elegans (C. elegans) is a useful model for discovering toxic-induced metabolism, high-throughput drug screening, and a variety of human disease pathways. To determine the lipidome of C. elegans and investigate lipid disruption from the molecular level to the system biology level, we used integrative data acquisition. The methyl-tert-butyl ether method was used to extract L4 stage C. elegans after exposure to triclosan (TCS), perfluorooctanoic acid, and nanopolystyrene (nPS). Full MS, DDA, and DIA integrations were performed to comprehensively profile the C. elegans lipidome by Q-Exactive Plus MS. All annotated lipids were then analyzed using lipid ontology and pathway analysis. We annotated up to 940 lipids from 20 lipid classes involved in various functions and pathways. The biological investigations revealed that when C. elegans were exposed to nPS, lipid droplets were disrupted, whereas plasma membrane-functionalized lipids were likely to be changed in the TCS treatment group. The nPS treatment caused a significant disruption in lipid storage. Triacylglycerol, glycerophospholipid, and ether class lipids were those primarily hindered by toxicants. Finally, toxicant exposure frequently involved numerous lipid-related pathways, including the phosphoinositide 3-kinase/protein kinase B pathway. In conclusion, an integrative data acquisition strategy was used to characterize the C. elegans lipidome, providing valuable biological insights into hypothesis generation and validation.

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Multiple data acquisitions were used to profile the lipidome of C. elegans.

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940 detected lipids of 20 main classes involved in various pathways.

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Relevant hypotheses were generated using high-coverable lipidomics and pathways analysis.

The emerging role of lipidomics in prediction of diseases

A recent paper published in PLoS Biology reported the application of lipidomics in predicting the incidence of diabetes and cardiovascular diseases in a population cohort. The study is clearly remarkable in demonstrating the role of lipidomics in prediction of diseases and translational research. We believe it comes to an era with quantitative lipidomics.

Tracing Lipid Metabolism by Alkyne Lipids and Mass Spectrometry: The State of the Art

Lipid tracing studies are a key method to gain a better understanding of the complex metabolic network lipids are involved in. In recent years, alkyne lipid tracers and mass spectrometry have been developed as powerful tools for such studies. This study aims to review the present standing of the underlying technique, highlight major findings the strategy allowed for, summarize its advantages, and discuss some limitations. In addition, an outlook on future developments is given.

Deep-lipidotyping by mass spectrometry: recent technical advances and applications

In-depth structural characterization of lipids is an essential component of lipidomics. There has been a rapid expansion of mass spectrometry methods that are capable of resolving lipid isomers at various structural levels over the past decade. These developments finally make deep-lipidotyping possible, which provides new means to study lipid metabolism and discover new lipid biomarkers. In this review, we discuss recent advancements in tandem mass spectrometry (MS/MS) methods for identification of complex lipids beyond the species (known headgroup information) and molecular species (known chain composition) levels. These include identification at the levels of carbon-carbon double bond (C=C) location and sn-position as well as characterization of acyl chain modifications. We also discuss the integration of isomer-resolving MS/MS methods with different lipid analysis workflows and their applications in lipidomics. The results showcase the distinct capabilities of deep-lipidotyping in untangling the metabolism of individual isomers and sensitive phenotyping by using relative fractional quantitation of the isomers.

Lipidomic Profiling in Synovial Tissue

The analysis of synovial tissue offers the potential for the comprehensive characterization of cell types involved in arthritis pathogenesis. The studies performed to date in synovial tissue have made it possible to define synovial pathotypes, which relate to disease severity and response to treatment. Lipidomics is the branch of metabolomics that allows the quantification and identification of lipids in different biological samples. Studies in animal models of arthritis and in serum/plasma from patients with arthritis suggest the involvement of different types of lipids (glycerophospholipids, glycerolipids, sphingolipids, oxylipins, fatty acids) in the pathogenesis of arthritis. We reviewed studies that quantified lipids in different types of tissues and their relationship with inflammation. We propose that combining lipidomics with currently used “omics” techniques can improve the information obtained from the analysis of synovial tissue, for a better understanding of pathogenesis and the development of new therapeutic strategies.

The Role of Sphingolipids in Allergic Disorders

Allergy is defined as a complex chronic inflammatory condition in which genetic and environmental factors are implicated. Sphingolipids are involved in multiple biological functions, from cell membrane components to critical signaling molecules. To date, sphingolipids have been studied in different human pathologies such as neurological disorders, cancer, autoimmunity, and infections. Sphingolipid metabolites, in particular, ceramide and sphingosine-1-phosphate (S1P), regulate a diverse range of cellular processes that are important in immunity and inflammation. Moreover, variations in the sphingolipid concentrations have been strongly associated with allergic diseases. This review will focus on the role of sphingolipids in the development of allergic sensitization and allergic inflammation through the activation of immune cells resident in tissues, as well as their role in barrier remodeling and anaphylaxis. The knowledge gained in this emerging field will help to develop new therapeutic options for allergic disorders.

Effects of Non-Polar Dietary and Endogenous Lipids on Gut Microbiota Alterations: The Role of Lipidomics

Advances in sequencing technologies over the past 15 years have led to a substantially greater appreciation of the importance of the gut microbiome to the health of the host. Recent outcomes indicate that aspects of nutrition, especially lipids (exogenous or endogenous), can influence the gut microbiota composition and consequently, play an important role in the metabolic health of the host. Thus, there is an increasing interest in applying holistic analytical approaches, such as lipidomics, metabolomics, (meta)transcriptomics, (meta)genomics, and (meta)proteomics, to thoroughly study the gut microbiota and any possible interplay with nutritional or endogenous components. This review firstly summarizes the general background regarding the interactions between important non-polar dietary (i.e., sterols, fat-soluble vitamins, and carotenoids) or amphoteric endogenous (i.e., eicosanoids, endocannabinoids-eCBs, and specialized pro-resolving mediators-SPMs) lipids and gut microbiota. In the second stage, through the evaluation of a vast number of dietary clinical interventions, a comprehensive effort is made to highlight the role of the above lipid categories on gut microbiota and vice versa. In addition, the present status of lipidomics in current clinical interventions as well as their strengths and limitations are also presented. Indisputably, dietary lipids and most phytochemicals, such as sterols and carotenoids, can play an important role on the development of medical foods or nutraceuticals, as they exert prebiotic-like effects. On the other hand, endogenous lipids can be considered either prognostic indicators of symbiosis or dysbiosis or even play a role as specialized mediators through dietary interventions, which seem to be regulated by gut microbiota.

Lipidomics in Understanding Pathophysiology and Pharmacologic Effects in Inflammatory Diseases: Considerations for Drug Development

The lipidome has a broad range of biological and signaling functions, including serving as a structural scaffold for membranes and initiating and resolving inflammation. To investigate the biological activity of phospholipids and their bioactive metabolites, precise analytical techniques are necessary to identify specific lipids and quantify their levels. Simultaneous quantification of a set of lipids can be achieved using high sensitivity mass spectrometry (MS) techniques, whose technological advancements have significantly improved over the last decade. This has unlocked the power of metabolomics/lipidomics allowing the dynamic characterization of metabolic systems. Lipidomics is a subset of metabolomics for multianalyte identification and quantification of endogenous lipids and their metabolites. Lipidomics-based technology has the potential to drive novel biomarker discovery and therapeutic development programs; however, appropriate standards have not been established for the field. Standardization would improve lipidomic analyses and accelerate the development of innovative therapies. This review aims to summarize considerations for lipidomic study designs including instrumentation, sample stabilization, data validation, and data analysis. In addition, this review highlights how lipidomics can be applied to biomarker discovery and drug mechanism dissection in various inflammatory diseases including cardiovascular disease, neurodegeneration, lung disease, and autoimmune disease.

Serum untargeted lipidomics by UHPLC-ESI-HRMS aids the biomarker discovery of colorectal adenoma

BACKGROUND

Colorectal adenoma (CA) is an important precancerous lesion and early screening target of colorectal cancer (CRC). Lipids with numerous physiological functions are proved to be involved in the development of CRC. However, there is no lipidomic study with large-scale serum samples on diagnostic biomarkers for CA.

METHODS

The serum lipidomics of CA patients (n = 50) and normal control (NR) (n = 50) was performed by ultra high performance liquid chromatography-high resolution mass spectrometry with electrospray ionization (UHPLC-ESI-HRMS). Univariate and multivariate statistical analyses were utilized to screen the differential lipids between groups, and combining the constituent ratio analysis and diagnostic efficiency evaluation by receiver operating characteristic (ROC) curve disclosed the potential mechanism and biomarkers for CA.

RESULTS

There were obvious differences in serum lipid profiles between CA and NR groups. Totally, 79 differential lipids were selected by criterion of P < 0.05 and fold change > 1.5 or < 0.67. Triacylglycerols (TAGs) and phosphatidylcholines (PCs) were the major differential lipids with ratio > 60%, indicating these two lipid metabolic pathways showed evident disequilibrium, which could contribute to CA formation. Of them, 12 differential lipids had good diagnostic ability as candidate biomarkers for CA (AUC ≥ 0.900) by ROC analysis.

CONCLUSIONS

To our knowledge, this is the first attempt to profile serum lipidomics and explore lipid biomarkers of CA to help early screening of CRC. 12 differential lipids are obtained to act as potential diagnostic markers of CA. PCs and fatty acids were the main dysregulated biomarkers for CA in serum.

Probing Herbicide Toxicity to Algae (Selenastrum capricornutum) by Lipid Profiling with Machine Learning and Microchip/MALDI-TOF Mass Spectrometry

Matrix-assisted laser desorption ionization mass spectrometry (MALDI-MS)-based lipid profiling is a powerful method to study the cytotoxicity of chemical exposure to microorganisms at the single cell level. We report here a combined approach of machine learning (ML) and microchip-based MALDI-time of flight (TOF) mass spectrometry to investigate the cytotoxic effect of herbicides on algae through single cell lipid profiling. Algal species Selenastrum capricornutum was chosen as the target system, and its exposure to different doses of common chemical herbicides and the resulting cytotoxic behaviors under various stress conditions were characterized. A lipid library for S. capricornutum has been established with 63 identified lipids that include glycosyldiacylglycerols and triacylglycerols. We demonstrated that major alternations occurred for lipids with functional groups of digalactosyldiacylglycerol (DGDG), triacylglycerol (TAG), and monogalactosyldiacylglycerol (MGDG). DGDG was shown to decrease upon exposure to herbicides of norflurazon and atrazine, while some MGDG and TAG lipids would increase for norflurazon. Compared to other algae, S. capricornutum was more strongly impacted by norflurazon than atrazine while the latter was observed to have a greater effect on C. reinhardtii. Machine learning algorithms have been applied to improve the classification of herbicide impact and help identify lipid species affected by the chemical exposure. A total of 69 machine learning models were trained and tested for the identification of ideal algorithms in the classification process, in which flexible discriminant analysis and support vector machine model were found to be the most accurate and consistent. The ML algorithms accurately differentiated herbicide impact and have identified cytotoxic differences that were previously hidden. The results suggest that herbicides express toxicity among different algae likely on the basis of metabolic differences. The ML-assisted method proves to be highly effective and can provide an advanced technological platform for probing cytotoxicity for bacterial species and in metabolic pathway analysis.

Helminth lipidomics: Technical aspects and future prospects

Lipidomics is a relatively recent molecular research field, and explores lipids (fats) and their biology using advanced mass spectrometry technologies. Although this field has expanded significantly in biomedical and biotechnological disciplines, it is still in its infancy in molecular parasitology. Our goal here is to review and discuss technical aspects of MS-based lipidomics and its recent applications to parasitic worms, as well as challenges and future directions for worm lipid research. In a multi-omic paradigm, we expect that the exploration of lipidomic data for parasitic worms will yield important insights into lipid-associated biological pathways and processes, including the regulation of essential signalling pathways, parasite invasion, establishment, adaptation and development.

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Lipids are involved in critical biological functions in parasitic worms.

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Lipidomics is an emerging research field in molecular helminthology.

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This article covers technological advances and applications to parasitic worms.

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It also discusses challenges and future directions for lipidomic research.

Stimulating the Hematopoietic Effect of Simulated Digestive Product of Fucoidan from Sargassum fusiforme on Cyclophosphamide-Induced Hematopoietic Damage in Mice and Its Protective Mechanisms Based on Serum Lipidomics

Hematopoietic damage is a serious side effect of cytotoxic drugs, and agents promoting hematopoiesis are quite important for decreasing the death rate in cancer patients. In our previous work, we prepared the simulated digestive product of fucoidan from Sargassum fusiforme, DSFF, and found that DSFF could activate macrophages. However, more investigations are needed to further evaluate whether DSFF could promote hematopoiesis in the chemotherapy process. In this study, the protective effect of DSFF (1.8-7.2 mg/kg, i.p.) on cyclophosphamide-induced hematopoietic damage in mice and the underlying mechanisms were investigated. Our results show that DSFF could restore the numbers of white blood cells, neutrophils, and platelets in the peripheral blood, and could also retard bone marrow cell decrease in mice with cyclophosphamide-induced hematopoietic damage. UPLC/Q-Extraction Orbitrap/MS/MS-based lipidomics results reveal 16 potential lipid biomarkers in a serum that responded to hematopoietic damage in mice. Among them, PC (20:1/14:0) and SM (18:0/22:0) were the key lipid molecules through which DSFF exerted protective actions. In a validation experiment, DSFF (6.25-100 μg/mL) could also promote K562 cell proliferation and differentiation in vitro. The current findings indicated that DSFF could affect the blood cells and bone marrow cells in vivo and thus showed good potential and application value in alleviating the hematopoietic damage caused by cyclophosphamide.

Lipid Profiles of Human Serum Fractions Enhanced with CD9 Antibody-Immobilized Magnetic Beads

Blood samples are minimally invasive and can be collected repeatedly, but they are far from the site of disease and the target molecules are diluted by the large amount of blood. Therefore, we performed lipidomics using immunoprecipitation as a method to enrich specific fractions of serum. In this study, a CD9 antibody was immobilized on magnetic beads to enrich CD9-containing components in the serum for lipidomics. The percentages of phospholipids recovered from serum by methanol and isopropanol extractions were not significantly different, but triglycerides were barely recovered from serum by methanol extraction, requiring the use of isopropanol. However, once the serum was enriched with CD9 magnetic beads, triglycerides, and phospholipids were recovered at similar levels in both methanol and isopropanol extractions. Therefore, it is possible that the triglyceride fraction of the whole serum and the triglyceride fraction were enriched in CD9 magnetic beads differ in localization and properties. In addition, the variation per disease was small in general serum lipidomics; however, the difference per disease appeared larger when CD9 magnetic bead enrichment was employed.

LipidOne: user-friendly lipidomic data analysis tool for a deeper interpretation in a systems biology scenario

SUMMARY

LC/MS-based analysis techniques combined with specialized lipid tool allow for the qualitative and quantitative determination of thousands of lipid molecules. Some recent bioinformatics tools have been developed to study changes in the lipid profile in case-control experiments and correlate these changes to different enzyme activity or gene expression. However, the existing tools have the limitation to treat only the assembled lipid molecules. In reality, each individual molecule can be considered as an assembly of smaller parts, often called building blocks. These are the result of a myriad of biochemical synthesis and transformation processes that, from a systems biology perspective, should not be ignored. Here, we present LipidOne, a new lipidomic tool which highlights all qualitative and quantitative changes in lipid building blocks both among all detected lipid classes and among experimental groups. Thanks to LipidOne, even differences in lipid building blocks can now be linked to the activity of specific classes of enzymes, transcripts and genes.

AVAILABILITY AND IMPLEMENTATION

LipidOne software is freely available at www.dcbb.unipg.it/LipidOne and https://github.com/matteogiulietti/LipidOne.

CONTACT

roberto.pellegrino@unipg.it.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Obesity-Related Insulin Resistance: The Central Role of Adipose Tissue Dysfunction

Obesity is a key player in the onset and progression of insulin resistance (IR), a state by which insulin-sensitive cells fail to adequately respond to insulin action. IR is a reversible condition, but if untreated leads to type 2 diabetes alongside increasing cardiovascular risk. The link between obesity and IR has been widely investigated; however, some aspects are still not fully characterized.In this chapter, we introduce key aspects of the pathophysiology of IR and its intimate connection with obesity. Specifically, we focus on the role of adipose tissue dysfunction (quantity, quality, and distribution) as a driver of whole-body IR. Furthermore, we discuss the obesity-related lipidomic remodeling occurring in adipose tissue, liver, and skeletal muscle. Key mechanisms linking lipotoxicity to IR in different tissues and metabolic alterations (i.e., fatty liver and diabetes) and the effect of weight loss on IR are also reported while highlighting knowledge gaps.

Effects of exercise on high-fat diet-induced non-alcoholic fatty liver disease and lipid metabolism in ApoE knockout mice

Background

Non-alcoholic fatty liver disease (NAFLD), which is growing more common in the Western world, has become the main cause of chronic liver disease and is strongly associated with metabolism syndromes. NAFLD can indicate a wide spectrum of hepatic pathologies, ranging from simple hepatic steatosis and inflammatory non-alcoholic steatohepatitis to more severe stages of fibrosis and cirrhosis. Moreover, evidence has demonstrated that physical inactivity and westernized dietary habits may facilitate the development of NAFLD. Lipid modulation and metabolism could be important factors in the development of steatosis. Lipid species, characterized using a lipidomic approach with untargeted analysis, could provide potential biomarkers for the pathogenesis of NAFLD or therapeutic applications. Thus, in this study, the effects of exercise on the improvement of NAFLD were further investigated from a lipidomic perspective through the aspects of lipid regulation and metabolism.

Methods

Wild type (WT) C57BL/6 J and C57BL/6-ApoE^em1Narl/Narl mice were assigned to one of four groups: WT mice fed a normal chow diet (CD), apolipoprotein E (ApoE) knockout mice fed a normal CD, ApoE knockout mice fed a high-fat diet (HFD), and ApoE knockout mice fed a HFD and provided with swimming exercise. The treatments (e.g., normal diet, HFD, and exercise) were provided for 12 consecutive weeks before the growth curves, biochemistry, fat composition, pathological syndromes, and lipid profiles were determined.

Results

Exercise significantly reduced the HFD-induced obesity (weight and fat composition), adipocyte hypertrophy, liver lipid accumulation, and pathological steatosis. In addition, exercise ameliorated HFD-induced steatosis in the process of NAFLD. The lipidomic analysis revealed that the changes in plasma triglyceride (14:0/16:0/22:2), phosphatidic acid (18:0/17:2), and phosphatidylglycerol (16:0/20:2) induced by the administration of the HFD could be reversed significantly by exercise.

Conclusions

The 12-week regular exercise intervention significantly alleviated HFD-induced NAFLD through modulation of specific lipid species in plasma. This finding could elucidate the lipids effects behind the hepatic pathogenesis with exercise.

LC-MS-Based Lipidomic Analysis of Serum Samples from Patients with Type 2 Diabetes Mellitus (T2DM)

Background

With the development of social economy, type 2 diabetes mellitus (T2DM) is becoming a severe health problem globally.

Methods

To systematically understand the lipid metabolism in T2DM, we applied untargeted lipidomics to the serum of T2DM patients and control group using ultrahigh-performance liquid chromatography (UHPLC) coupled with high-resolution mass spectrometry (MS).

Results

Over two thousand molecular features were detected by our approach, of which 222 lipid species in positive ion mode and 145 species in negative were reliably identified based on precise molecular weights and MS/MS patterns. Multivariate analysis was adopted to differentiate T2DM patients and the control group using principal component analysis (PCA) and orthogonal partial least squares discrimination analysis (OPLS-DA). The dysregulated lipid species were found and their significance in pathophysiology was discussed. Correlation analysis of selected lipids and important clinical variables was performed and addressed.

Conclusions

This study unveils several new lipids and pathways considerably involved in T2DM and provides novel insights into understanding the pathogenesis underlying T2DM.

The foundations and development of lipidomics

For over a century, the importance of lipid metabolism in biology was recognized but difficult to mechanistically understand due to the lack of sensitive and robust technologies for identification and quantification of lipid molecular species. The enabling technological breakthroughs emerged in the 1980s with the development of soft ionization methods (Electrospray Ionization and Matrix Assisted Laser Desorption/Ionization) that could identify and quantify intact individual lipid molecular species. These soft ionization technologies laid the foundations for what was to be later named the field of lipidomics. Further innovative advances in multistage fragmentation, dramatic improvements in resolution and mass accuracy, and multiplexed sample analysis fueled the early growth of lipidomics through the early 1990s. The field exponentially grew through the use of a variety of strategic approaches, which included direct infusion, chromatographic separation, and charge-switch derivatization, which facilitated access to the low abundance species of the lipidome. In this Thematic Review, we provide a broad perspective of the foundations, enabling advances, and predicted future directions of growth of the lipidomics field.

Metabolic Phenotyping in Prostate Cancer Using Multi-Omics Approaches

Prostate cancer (PCa), one of the most frequently diagnosed cancers among men worldwide, is characterized by a diverse biological heterogeneity. It is well known that PCa cells rewire their cellular metabolism to meet the higher demands required for survival, proliferation, and invasion. In this context, a deeper understanding of metabolic reprogramming, an emerging hallmark of cancer, could provide novel opportunities for cancer diagnosis, prognosis, and treatment. In this setting, multi-omics data integration approaches, including genomics, epigenomics, transcriptomics, proteomics, lipidomics, and metabolomics, could offer unprecedented opportunities for uncovering the molecular changes underlying metabolic rewiring in complex diseases, such as PCa. Recent studies, focused on the integrated analysis of multi-omics data derived from PCa patients, have in fact revealed new insights into specific metabolic reprogramming events and vulnerabilities that have the potential to better guide therapy and improve outcomes for patients. This review aims to provide an up-to-date summary of multi-omics studies focused on the characterization of the metabolomic phenotype of PCa, as well as an in-depth analysis of the correlation between changes identified in the multi-omics studies and the metabolic profile of PCa tumors.

Lipidomic analysis of single and combined effects of polyethylene microplastics and polychlorinated biphenyls on human hepatoma cells

Microplastics are an emerging environmental issue as a result of their ubiquity, persistence, and intrinsic toxic potential. In addition, their ability to sorb and transport a wide variety of environmental pollutants (i.e. "Trojan Horse" effect) exerts significant adverse impacts upon ecosystems. The toxicological evaluation of the single and combined effects produced by polyethylene microplastics and two polychlorinated biphenyl congeners was performed on the human hepatoma cell line HepG2 by cell viability assessment and an untargeted lipidomic study. The cell lethality evaluation evinced that MPs did not induce relevant cell lethality at any of the concentration range tested, while both PCBs presented a hormetic behavior. The lipidomic analysis suggested that both single PCB exposures induced significant lipidomic changes, especially for glycerophospholipids and glycerolipids. In contrast, for MPs single exposure, the most remarkable change was the substantial enhancement of triglyceride content. Regarding combined exposures, results showed that MPs could induce even more harmful effects than those produced intrinsically as a result of desorbing previously sorbed toxic pollutants. To the best of our knowledge, this is the first study assessing the toxicity of microplastics and their possible "Trojan Horse" effect by applying an untargeted lipidomic methodology.

Analyses of Pseudoexfoliation aqueous humor lipidome

Pseudoexfoliation syndrome (PEX) is a systemic disorder that manifests as fluffy, proteinaceous fibrillar material throughout the body. In the eye such deposits result in glaucoma (PEXG), due to impeding aqueous...

Lipid profiling in malignant mesothelioma reveals promising signatures for diagnosis and prognosis: A plasma-based LC-MS lipidomics study

BACKGROUND AND AIM

Malignant mesothelioma (MM), being a rare and aggressive carcinoma, can barely be cured. Incidence of this cancer will keep climbing up in the next few decades since its major carcinogen, asbestos, is still in use in many countries. Unfortunately, prognosis of MM is unsatisfactory principally due to poor early diagnosis as a result of its long latency period and ambiguous symptoms. Lipids are known to contribute to cellular structure, signaling, and energy storage, and are widely reported to be related with tumorigenesis. Therefore, we aim to discover novel lipid biomarkers by plasma-based lipidomics that may improve MM diagnosis.

METHODS

Plasma samples from 25 MM patients and 32 healthy controls (HCs) were collected and analysed using a high-throughput liquid chromatography-mass spectrometry (LC-MS). Univariate and multivariate analyses were subsequently performed to visualize the separation trend between two groups and to screen for differential feature ions. Ions were annotated using LipidSearch 4.2 and their enriched pathways were detected on LIPEA. Receiver operating characteristic (ROC) curves were used for analysing each annotated lipid's diagnostic value. Survival analyses were performed to investigate each lipid's prognostic value.

RESULTS

In supervised partial least squares discriminant analysis (PLS-DA), clear separation between MM and HC groups was observed. A total of 34 differential lipids were annotated, among which 5 upregulated and 29 downregulated. Levels of plasma triacylglycerols (TGs) were higher in smoking versus non-smoking patients, and lower in female versus male patients. The top six lipids possessing highest diagnostic value included two phosphatidylethanolamines (PEs), two phosphatidylcholines (PCs) and two ceramides. Moreover, elevated circulating TG levels were associated with poorer survival, whereas increased monohexosylceramide (Hex1Cer) might be beneficial.

CONCLUSIONS

Our study revealed differentially expressed lipid patterns in MM compared to HC. PC, PE, and ceramides showed outstanding diagnostic performance, while TG and Hex1Cer exhibited significant prognostic values. Nevertheless, more studies should verify these trends as well as further investigating on underlying mechanisms.

RECOGNITION AND AVOIDANCE OF ION SOURCE-GENERATED ARTIFACTS IN LIPIDOMICS ANALYSIS

Lipid research is attracting more and more attention as various key roles and novel biological functions of lipids have been demonstrated and discovered in the organism. Mass spectrometry (MS)-based lipidomics approaches are the most powerful and effective tools for analysis of cellular lipidomes with very high sensitivity and specificity. However, the artifacts generated from in-source fragmentation are always present in all kinds of ion sources, even soft ionization techniques (i.e., electrospray ionization and matrix-assisted laser desorption/ionization [MALDI]). These artifacts can cause many problems for lipidomics, especially when the fragment ions correspond to/are isomeric species of other endogenous lipid species in complex biological samples. These commonly observed artifacts could lead to misannotation, false identification, and consequently, incorrect attribution of phenotypes, and will have negative impact on any MS-based lipidomics research including but not limited to biomarker discovery, drug development, etc. Liquid chromatography-MS, shotgun lipidomics, and MALDI-MS imaging are three representative lipidomics approaches in which ion source-generated artifacts are all manifested and are comprehensively summarized in this article. The strategies on how to avoid/reduce the artifacts of in-source fragmentation on lipidomics analysis are also discussed in detail. We believe that with the recognition and avoidance of ion source-generated artifacts, MS-based lipidomics approaches will provide better accuracy on comprehensive analysis of biological samples and will make greater contribution to the research on metabolism and translational/precision medicine (collectively termed functional lipidomics). © 2020 John Wiley & Sons Ltd. Mass Spec Rev.

Comparison of one-phase and two-phase extraction methods for porcine tissue lipidomics applying a fast and reliable tentative annotation workflow

Lipidomics has great potential for the discovery of biomarkers, elucidation of metabolic processes and identifying dysregulations in complex biological systems. Concerning biofluids like plasma or cerebrospinal fluid, several studies for the comparison of lipid extraction solvents have already been conducted. With respect to tissues, which can differ significantly in terms of dry matter content and composition, only few studies are available. The proper selection of an extraction method that covers the complexity and individuality of different tissues is challenging. The goal of this work was to provide a systematic overview on the potential of different extraction methods for a broad applicability. This study covers six different extraction procedures and four different reconstitution solvents applied to ten different porcine tissues. To get an overview of the individual lipid profiles, a workflow was developed for a fast and reliable tentative lipid annotation. Therefore, several machine learning tools were utilized, like the prediction of collision cross sections to support the tentative lipid identification in case of untargeted lipidomics. In terms of data evaluation, unsupervised (e.g. principal component analysis) and supervised (e.g. partial least square - discriminant analysis) methods were applied to visualize and subsequently interpret all generated information. Furthermore, the influence of the tissue composition on the extraction performance was investigated. It could be shown that the ten porcine tissues can be distinguished based on their lipid profile with the applied workflow and that the methyl-tert-butyl ether (MTBE) based extraction method (two-phase) showed the best overall performance for the 16 examined lipid species. With this method the highest number of features (428 in lung tissue) could be annotated. Upcoming one-phase extractions also showed a high potential concerning total number of extracted lipids. Methanol/MTBE/chloroform (MMC) extracted slightly less lipids (393 in lung and liver) than MTBE but turned out to be the best one-phase extraction method. Additionally, the numbers of extracted lipids obtained by isopropanol/water 90:10 (IPA90) (399 in stomach) and by isopropanol/methanol/chloroform (IMC) (395 in stomach) were similar to those of the modified Folch method (402 in stomach). One-phase extractions can therefore clearly be seen as preferable when a high throughput is needed.

Cross-Laboratory Standardization of Preclinical Lipidomics Using Differential Mobility Spectrometry and Multiple Reaction Monitoring

Modern biomarker and translational research as well as personalized health care studies rely heavily on powerful omics' technologies, including metabolomics and lipidomics. However, to translate metabolomics and lipidomics discoveries into a high-throughput clinical setting, standardization is of utmost importance. Here, we compared and benchmarked a quantitative lipidomics platform. The employed Lipidyzer platform is based on lipid class separation by means of differential mobility spectrometry with subsequent multiple reaction monitoring. Quantitation is achieved by the use of 54 deuterated internal standards and an automated informatics approach. We investigated the platform performance across nine laboratories using NIST SRM 1950-Metabolites in Frozen Human Plasma, and three NIST Candidate Reference Materials 8231-Frozen Human Plasma Suite for Metabolomics (high triglyceride, diabetic, and African-American plasma). In addition, we comparatively analyzed 59 plasma samples from individuals with familial hypercholesterolemia from a clinical cohort study. We provide evidence that the more practical methyl-tert-butyl ether extraction outperforms the classic Bligh and Dyer approach and compare our results with two previously published ring trials. In summary, we present standardized lipidomics protocols, allowing for the highly reproducible analysis of several hundred human plasma lipids, and present detailed molecular information for potentially disease relevant and ethnicity-related materials.

Lipidomics Reveals Serum Specific Lipid Alterations in Diabetic Nephropathy

In diabetes mellitus (DM), disorders of glucose and lipid metabolism are significant causes of the onset and progression of diabetic nephropathy (DN). However, the exact roles of specific lipid molecules in the pathogenesis of DN remain unclear. This study recruited 577 participants, including healthy controls (HCs), type-2 DM (2-DM) patients, and DN patients, from the clinic. Serum samples were collected under fasting conditions. Liquid chromatography-mass spectrometry-based lipidomics methods were used to explore the lipid changes in the serum and identify potential lipid biomarkers for the diagnosis of DN. Lipidomics revealed that the combination of lysophosphatidylethanolamine (LPE) (16:0) and triacylglycerol (TAG) 54:2-FA18:1 was a biomarker panel for predicting DN. The receiver operating characteristic analysis showed that the panel had a sensitivity of 89.1% and 73.4% with a specificity of 88.1% and 76.7% for discriminating patients with DN from HCs and 2-DM patients. Then, we divided the DN patients in the validation cohort into microalbuminuria (diabetic nephropathy at an early stage, DNE) and macroalbuminuria (diabetic nephropathy at an advanced stage, DNA) groups and found that LPE(16:0), phosphatidylethanolamine (PE) (16:0/20:2), and TAG54:2-FA18:1 were tightly associated with the stages of DN. The sensitivity of the biomarker panel to distinguish between patients with DNE and 2-DM, DNA, and DNE patients was 65.6% and 85.9%, and the specificity was 76.7% and 75.0%, respectively. Our experiment showed that the combination of LPE(16:0), PE(16:0/20:2), and TAG54:2-FA18:1 exhibits excellent performance in the diagnosis of DN.

Advances in Analyzing the Breast Cancer Lipidome and Its Relevance to Disease Progression and Treatment

Abnormal lipid metabolism is common in breast cancer with the three main subtypes, hormone receptor (HR) positive, human epidermal growth factor 2 (HER2) positive, and triple negative, showing common and distinct lipid dependencies. A growing body of studies identify altered lipid metabolism as impacting breast cancer cell growth and survival, plasticity, drug resistance, and metastasis. Lipids are a class of nonpolar or polar (amphipathic) biomolecules that can be produced in cells via de novo synthesis or acquired from the microenvironment. The three main functions of cellular lipids are as essential components of membranes, signaling molecules, and nutrient storage. The use of mass spectrometry-based lipidomics to analyze the global cellular lipidome has become more prevalent in breast cancer research. In this review, we discuss current lipidomic methodologies, highlight recent breast cancer lipidomic studies and how these findings connect to disease progression and therapeutic development, and the potential use of lipidomics as a diagnostic tool in breast cancer. A better understanding of the breast cancer lipidome and how it changes during drug resistance and tumor progression will allow informed development of diagnostics and novel targeted therapies.

Fully Automatized Detection of Phosphocholine-Containing Lipids through an Isotopically Labeled Buffer Modification Workflow

High-resolution mass spectrometry is the foremost technique for qualitative and quantitative lipidomics analyses. Glycerophospholipids and sphingolipids, collectively termed polar lipids, are commonly investigated by hyphenated liquid chromatography-mass spectrometry (LC-MS) techniques that reduce aggregation effects and provide a greater dynamic range of detection sensitivity compared to shotgun lipidomics. However, automatic polar lipid identification is hindered by several isobaric and isomer mass overlaps, which cause software programs to often fail to correctly annotate the lipid species. In the present paper, a buffer modification workflow based on the use of labeled and unlabeled acetate ions in the chromatographic buffers was optimized by Box-Behnken design of the experiments and applied to the characterization of phosphocholine-containing lipids in human plasma samples. The contemporary generation of [M + CH₃COO]^-, [M + CD₃COO]^-, and [M - CH₃]^- coupled with a dedicated data processing workflow, which was specifically set up on Compound Discoverer software, allowed us to correctly determine adduct composition, molecular formulas, and grouping, as well as granting a lower false-positive rate and streamlining the manual validation step compared to commonly employed lipidomics platforms. The proposed workflow represents a robust yet easier alternative to the existing approaches for improving lipid annotation, as it does not require extensive sample pretreatment or prior isotopic enrichment or derivatization.

The Application Value of Lipoprotein Particle Numbers in the Diagnosis of HBV-Related Hepatocellular Carcinoma with BCLC Stage 0-A

Early diagnosis is essential for improving the prognosis and survival of patients with hepatocellular carcinoma (HCC). This study aims to explore the clinical value of lipoprotein subfractions in the diagnosis of hepatitis B virus (HBV)-related HCC. Lipoprotein subfractions were detected by ¹H-NMR spectroscopy, and the pattern-recognition method and binary logistic regression were performed to classify distinct serum profiles and construct prediction models for HCC diagnosis. Differentially expressed proteins associated with lipid metabolism were detected by LC-MS/MS, and the potential prognostic significance of the mRNA expression was evaluated by Kaplan–Meier survival analysis. The diagnostic panel constructed from the serum particle number of very-low-density lipoprotein (VLDL), intermediate-density lipoprotein (IDL), and low-density lipoprotein (LDL-1~LDL-6) achieved higher accuracy for the diagnosis of HBV-related HCC and HBV-related benign liver disease (LD) than that constructed from serum alpha-fetoprotein (AFP) alone in the training set (AUC: 0.850 vs. AUC: 0.831) and validation set (AUC: 0.926 vs. AUC: 0.833). Furthermore, the panel achieved good diagnostic performance in distinguishing AFP-negative HCC from AFP-negative LD (AUC: 0.773). We also found that lipoprotein lipase (LPL) transcript levels showed a significant increase in cancerous tissue and that high expression was significantly positively correlated with the poor prognosis of patients. Our research provides new insight for the development of diagnostic biomarkers for HCC, and abnormal lipid metabolism and LPL-mediated abnormal serum lipoprotein metabolism may be important factors in promoting HCC development.

Unraveling the metabolic pathway of choline-TMA-TMAO: Effects of gypenosides and implications for the therapy of TMAO related diseases

Trimethylamine-N-oxide (TMAO) has emerged as a promising new therapeutic target for the treatment of central nervous system diseases, atherosclerosis and other diseases. However, its origin in the brain is unclear. Gynostemma pentaphyllum (Thunb.) Makino can reduce the increase of TMAO level caused by a high fat diet. But its effective chemical composition and specific mechanism have not been reported. The study confirmed that TMA was more easily to penetrate blood brain barrier than TMAO, the MAO enzyme was partly involved in the transformation of the TMA in brain, which further supplemented the choline-TMA-TMAO pathway. Based on the above metabolic pathway, using multi-omics approaches, such as microbiodiversity, metagenomics and lipidomics, it was demonstrated that the reduction of plasma TMAO levels by gypenosides did not act on FMO3 and MAO in the pathway, but remodeled the microbiota and affected the trimethylamine lyase needed in the conversion of choline to TMA in intestinal flora. At the same time, gypenosides interfered with enzymes associated with TCA and lipid metabolism, thus affecting TMAO and lipid metabolism. Considering the bidirectional transformation of phosphatidycholine and choline, lipid metabolism and TMAO metabolism could affected each other to some extent. In conclusion, our study revealed the intrinsic correlation between long-term application of gypenosides to lipid reduction and nervous system protection, and explained why gypenosides were used to treat brain diseases, even though they had a poor ability to enter the brain. Besides, it provided a theoretical basis for clinical application of gypenosides and the development of new drugs.

Anti-NAFLD Effect of Djulis Hull and Its Major Compound, Rutin, in Mice with High-Fat Diet (HFD)-Induced Obesity

Nonalcoholic fatty liver disease (NAFLD) has become the main cause of chronic liver disease worldwide, and the increasing trend of NAFLD has burdened the healthcare system. NAFLD encompasses a wide range of liver pathologies, from simple benign hepatocyte steatosis to more severe inflammatory nonalcoholic steatohepatitis. Djulis (Chenopodium formosanum Koidz.) is traditionally used as a native cereal and a food supplement that promotes human health through its antioxidant, hepatoprotection, skin protection, hypolipidemic, hypoglycemic, and antitumor effects. Djulis hull, regarded as agricultural waste, is usually removed during food processing and contains high rutin content. The present study evaluated the anti-NAFLD effect of Djulis hull and its major compound, rutin, in mice with high-fat diet (HFD)-induced obesity. Male C57BL/6J mice were randomly divided into one of five diet groups (n = 6 per group) and fed the following for 16 weeks: (1) normal diet group (ND), (2) HFD group (HFD), (3) HFD and oral gavage of low dose (50 mg/kg) of Djulis hull crude extract group (HFD/LCE), (4) HFD and oral gavage of high dose (250 mg/kg) of Djulis hull crude extract group (HFD/HCE), or (5) HFD and oral gavage (50 mg/kg) of rutin (HFD/R) group. We found that Djulis hull crude extract markedly reduced HFD-induced elevation in body weight and fat around the kidney weights, hepatic injury indicators (AST and ALT), and steatosis and hypertrophy. Furthermore, Djulis hull crude extract administration significantly affected DG(20:4/18:1), PA(22:0/17:1), PC(10:0/17:0), and PA(18:4/20:5) in HFD-induced obese mice. In addition, treating HFD-induced obese rats with Djulis hull crude extract significantly increased fatty acid oxidation by increasing the protein expression of phosphorylated AMP-activated protein kinase, peroxisome proliferator-activated receptor-α, and hepatic carnitine palmitoyltransferase-1 in the liver. Moreover, the administration of Djulis hull crude extract significantly decreased the inflammatory response (PPARγ, IL-6, and TNF-α) to modulate oxidative damage. Therefore, Djulis hull crude extract attenuated the progression of NAFLD by reducing inflammation mediated by PPARγ and enhancing the expression levels of genes involved in fatty acid oxidation mediated by AMPK signaling.

A Lipidomics Atlas of Selected Sphingolipids in Multiple Mouse Nervous System Regions

Many lipids, including sphingolipids, are essential components of the nervous system. Sphingolipids play critical roles in maintaining the membrane structure and integrity and in cell signaling. We used a multi-dimensional mass spectrometry-based shotgun lipidomics platform to selectively analyze the lipid species profiles of ceramide, sphingomyelin, cerebroside, and sulfatide; these four classes of sphingolipids are found in the central nervous system (CNS) (the cerebrum, brain stem, and spinal cord) and peripheral nervous system (PNS) (the sciatic nerve) tissues of young adult wild-type mice. Our results revealed that the lipid species profiles of the four sphingolipid classes in the different nervous tissues were highly distinct. In addition, the mRNA expression of sphingolipid metabolism genes-including the ceramidase synthases that specifically acylate the N-acyl chain of ceramide species and sphingomyelinases that cleave sphingomyelins generating ceramides-were analyzed in the mouse cerebrum and spinal cord tissue in order to better understand the sphingolipid profile differences observed between these nervous tissues. We found that the distinct profiles of the determined sphingolipids were consistent with the high selectivity of ceramide synthases and provided a potential mechanism to explain region-specific CNS ceramide and sphingomyelin levels. In conclusion, we portray for the first time a lipidomics atlas of select sphingolipids in multiple nervous system regions and believe that this type of knowledge could be very useful for better understanding the role of this lipid category in the nervous system.

Simple and Reproducible Derivatization with Benzoyl Chloride: Improvement of Sensitivity for Multiple Lipid Classes in RP-UHPLC/MS

The chemical derivatization of multiple lipid classes was developed using benzoyl chloride as a nonhazardous derivatization agent at ambient conditions. The derivatization procedure was optimized with standards for 4 nonpolar and 8 polar lipid classes and measured by reversed-phase ultrahigh-performance liquid chromatography-tandem mass spectrometry. The derivatization and nonderivatization approaches were compared on the basis of the calibration curves of 22 internal standards from 12 lipid classes. The new method decreased the limit of detection 9-fold for monoacylglycerols (0.9-1.0 nmol/mL), 6.5-fold for sphingoid base (0.2 nmol/mL), and 3-fold for diacylglycerols (0.9 nmol/mL). The sensitivity expressed by the ratio of calibration slopes was increased 2- to 10-fold for almost all investigated lipid classes and even more than 100-fold for monoacylglycerols. Moreover, the benzoylation reaction produces a more stable derivative of cholesterol in comparison to the easily in-source fragmented nonderivatized form and enabled the detection of fatty acids in a positive ion mode, which does not require polarity switching as for the nonderivatized form. The intralaboratory comparison with an additional operator without previous derivatization experiences shows the simplicity, robustness, and reproducibility. The stability of the derivatives was determined by periodical measurements during a one month period and five freeze/thaw cycles. The fully optimized derivatization method was applied to human plasma, which allows the detection of 169 lipid species from 11 lipid classes using the high confidence level of identification in reversed-phase (RP)-ultra high performance liquid chromatography (UHPLC)/mass spectrometry (MS). Generally, we detected more lipid species for monoacylglycerols, diacylglycerols, and sphingoid bases in comparison with previously reported papers without the derivatization.

Astaxanthin from Haematococcus pluvialis alleviates obesity by modulating lipid metabolism and gut microbiota in mice fed a high-fat diet

Obesity is a global chronic disease epidemic that is attributed to the abnormal accumulation of lipids in adipose tissue. Astaxanthin (AST) from Haematococcus pluvialis, a natural carotenoid, exhibits antioxidant, anti-lipogenic, anti-diabetic and other potent effects. Herein, we evaluated the effect of AST to illuminate its efficacy and mechanisms in high-fat diet-fed mice. AST supplementation not only significantly decreased body weight and lipid droplet accumulation in the liver but also modulated liver function and serum lipid levels. Lipidomic analysis revealed that 13 lipids might be potential biomarkers responsible for the effects of AST in lipid reduction, such as total free fatty acids (FFAs), triacylglycerols (TGs) and cholesterol esters (CEs). The gut microbiota sequencing results indicated that AST alleviated HFD-induced gut microbiota dysbiosis by optimizing the ratio of Firmicutes to Bacteroides and inhibiting the abundance of obesity-related pathogenic microbiota while promoting the abundance of probiotics related to glucose and lipid metabolism. In addition, qRT-PCR demonstrated that AST could regulate the gene expressions of the AMPK/SREBP1c pathway by downregulating lipogenesis correlated-genes and upregulating the lipid oxidant related-gene. The present study revealed the new function of AST in regulating lipid metabolism, which provided a theoretical basis for the development of high-quality AST functional food and the application of diet active substances in obesity, as demonstrated in mice.

Plasma lipidomic profiles of kidney, breast and prostate cancer patients differ from healthy controls

Early detection of cancer is one of the unmet needs in clinical medicine. Peripheral blood analysis is a preferred method for efficient population screening, because blood collection is well embedded in clinical practice and minimally invasive for patients. Lipids are important biomolecules, and variations in lipid concentrations can reflect pathological disorders. Lipidomic profiling of human plasma by the coupling of ultrahigh-performance supercritical fluid chromatography and mass spectrometry is investigated with the aim to distinguish patients with breast, kidney, and prostate cancers from healthy controls. The mean sensitivity, specificity, and accuracy of the lipid profiling approach were 85%, 95%, and 92% for kidney cancer; 91%, 97%, and 94% for breast cancer; and 87%, 95%, and 92% for prostate cancer. No association of statistical models with tumor stage is observed. The statistically most significant lipid species for the differentiation of cancer types studied are CE 16:0, Cer 42:1, LPC 18:2, PC 36:2, PC 36:3, SM 32:1, and SM 41:1 These seven lipids represent a potential biomarker panel for kidney, breast, and prostate cancer screening, but a further verification step in a prospective study has to be performed to verify clinical utility.

Lipid Profiling in Cancer Diagnosis with Hand-Held Ambient Mass Spectrometry Probes: Addressing the Late-Stage Performance Concerns

Untargeted lipid fingerprinting with hand-held ambient mass spectrometry (MS) probes without chromatographic separation has shown promise in the rapid characterization of cancers. As human cancers present significant molecular heterogeneities, careful molecular modeling and data validation strategies are required to minimize late-stage performance variations of these models across a large population. This review utilizes parallels from the pitfalls of conventional protein biomarkers in reaching bedside utility and provides recommendations for robust modeling as well as validation strategies that could enable the next logical steps in large scale assessment of the utility of ambient MS profiling for cancer diagnosis. Six recommendations are provided that range from careful initial determination of clinical added value to moving beyond just statistical associations to validate lipid involvements in disease processes mechanistically. Further guidelines for careful selection of suitable samples to capture expected and unexpected intragroup variance are provided and discussed in the context of demographic heterogeneities in the lipidome, further influenced by lifestyle factors, diet, and potential intersect with cancer lipid pathways probed in ambient mass spectrometry profiling studies.

Multi-Omic Approaches to Breast Cancer Metabolic Phenotyping: Applications in Diagnosis, Prognosis, and the Development of Novel Treatments

Breast cancer (BC) is characterized by high disease heterogeneity and represents the most frequently diagnosed cancer among women worldwide. Complex and subtype-specific gene expression alterations participate in disease development and progression, with BC cells known to rewire their cellular metabolism to survive, proliferate, and invade. Hence, as an emerging cancer hallmark, metabolic reprogramming holds great promise for cancer diagnosis, prognosis, and treatment. Multi-omics approaches (the combined analysis of various types of omics data) offer opportunities to advance our understanding of the molecular changes underlying metabolic rewiring in complex diseases such as BC. Recent studies focusing on the combined analysis of genomics, epigenomics, transcriptomics, proteomics, and/or metabolomics in different BC subtypes have provided novel insights into the specificities of metabolic rewiring and the vulnerabilities that may guide therapeutic development and improve patient outcomes. This review summarizes the findings of multi-omics studies focused on the characterization of the specific metabolic phenotypes of BC and discusses how they may improve clinical BC diagnosis, subtyping, and treatment.

LINT-Web: A Web-Based Lipidomic Data Mining Tool Using Intra-Omic Integrative Correlation Strategy

Lipidomics is a younger member of the "omics" family. It aims to profile lipidome alterations occurring in biological systems. Similar to the other "omics", lipidomic data is highly dimensional and contains a massive amount of information awaiting deciphering and data mining. Currently, the available bioinformatic tools targeting lipidomic data processing and lipid pathway analysis are limited. A few tools designed for lipidomic analysis perform only basic statistical analyses, and lipid pathway analyses rely heavily on public databases (KEGG, Reactome, and HMDB). Due to the inadequate understanding of lipid signaling and metabolism, the use of public databases for lipid pathway analysis can be biased and misleading. Instead of using public databases to interpret lipidomic ontology, the authors introduce an intra-omic integrative correlation strategy for lipidomic data mining. Such an intra-omic strategy allows researchers to unscramble and predict lipid biological functions from correlated genomic ontological results using statistical approaches. To simplify and improve the lipidomic data processing experience, they designed an interactive web-based tool: LINT-web (http://www.lintwebomics.info/) to perform the intra-omic analysis strategy, and validated the functions of LINT-web using two biological systems. Users without sophisticated statistical experience can easily process lipidomic datasets and predict the potential lipid biological functions using LINT-web.

The Plasma Membrane at the Cornerstone Between Flexibility and Adaptability: Implications for Saccharomyces cerevisiae as a Cell Factory

In the last decade, microbial-based biotechnological processes are paving the way toward sustainability as they implemented the use of renewable feedstocks. Nonetheless, the viability and competitiveness of these processes are often limited due to harsh conditions such as: the presence of feedstock-derived inhibitors including weak acids, non-uniform nature of the substrates, osmotic pressure, high temperature, extreme pH. These factors are detrimental for microbial cell factories as a whole, but more specifically the impact on the cell’s membrane is often overlooked. The plasma membrane is a complex system involved in major biological processes, including establishing and maintaining transmembrane gradients, controlling uptake and secretion, intercellular and intracellular communication, cell to cell recognition and cell’s physical protection. Therefore, when designing strategies for the development of versatile, robust and efficient cell factories ready to tackle the harshness of industrial processes while delivering high values of yield, titer and productivity, the plasma membrane has to be considered. Plasma membrane composition comprises diverse macromolecules and it is not constant, as cells adapt it according to the surrounding environment. Remarkably, membrane-specific traits are emerging properties of the system and therefore it is not trivial to predict which membrane composition is advantageous under certain conditions. This review includes an overview of membrane engineering strategies applied to Saccharomyces cerevisiae to enhance its fitness under industrially relevant conditions as well as strategies to increase microbial production of the metabolites of interest.

Overview of Lipidomic Analysis of Triglyceride Molecular Species in Biological Lipid Extracts

Triglyceride (TG) is a class of neutral lipids, which functions as an energy storage depot and is important for cellular growth, metabolism, and function. The composition and content of TG molecular species are crucial factors for nutritional aspects in food chemistry and are directly associated with several diseases, including atherosclerosis, diabetes, obesity, stroke, etc. As a result of the complexities of aliphatic moieties and their different connections/locations to the glycerol backbone in TG molecules, accurate identification of individual TG molecular species and quantitative assessment of TG composition and content are particularly challenging, even at the current stage of lipidomics development. Herein, methods developed for analysis of TG species, such as liquid chromatography-mass spectrometry with a variety of columns and different mass spectrometric techniques, shotgun lipidomics approaches, and ion-mobility-based analysis, are reviewed. Moreover, the potential limitations of the methods are discussed. It is our sincere hope that the overviews and discussions can provide some insights for researchers to select an appropriate approach for TG analysis and can serve as the basis for those who would like to establish a methodology for TG analysis or develop a new method when novel tools become available. Biologically accurate analysis of TG species with an enabling method should lead us toward improving the nutritional quality, revealing the effects of TG on diseases, and uncovering the underlying biochemical mechanisms related to these diseases.

The Importance of Lipidomic Approach for Mapping and Exploring the Molecular Networks Underlying Physical Exercise: A Systematic Review

Maintaining appropriate levels of physical exercise is an optimal way for keeping a good state of health. At the same time, optimal exercise performance necessitates an integrated organ system response. In this respect, physical exercise has numerous repercussions on metabolism and function of different organs and tissues by enhancing whole-body metabolic homeostasis in response to different exercise-related adaptations. Specifically, both prolonged and intensive physical exercise produce vast changes in multiple and different lipid-related metabolites. Lipidomic technologies allow these changes and adaptations to be clarified, by using a biological system approach they provide scientific understanding of the effect of physical exercise on lipid trajectories. Therefore, this systematic review aims to indicate and clarify the identifying biology of the individual response to different exercise workloads, as well as provide direction for future studies focused on the body’s metabolome exercise-related adaptations. It was performed using five databases (Medline (PubMed), Google Scholar, Embase, Web of Science, and Cochrane Library). Two author teams reviewed 105 abstracts for inclusion and at the end of the screening process 50 full texts were analyzed. Lastly, 14 research articles specifically focusing on metabolic responses to exercise in healthy subjects were included. The Oxford quality scoring system scale was used as a quality measure of the reviews. Information was extracted using the participants, intervention, comparison, outcomes (PICOS) format. Despite that fact that it is well-known that lipids are involved in different sport-related changes, it is unclear what types of lipids are involved. Therefore, we analyzed the characteristic lipid species in blood and skeletal muscle, as well as their alterations in response to chronic and acute exercise. Lipidomics analyses of the studies examined revealed medium- and long-chain fatty acids, fatty acid oxidation products, and phospholipids qualitative changes. The main cumulative evidence indicates that both chronic and acute bouts of exercise determine significant changes in lipidomic profiles, but they manifested in very different ways depending on the type of tissue examined. Therefore, this systematic review may offer the possibility to fully understand the individual lipidomics exercise-related response and could be especially important to improve athletic performance and human health.

Lipidomic Profiling of Algae with Microarray MALDI-MS toward Ecotoxicological Monitoring of Herbicide Exposure

Misuse of agrochemicals has a long-lasting negative impact on aquatic systems. Mismanagement of herbicides in agri-food sectors is often linked to a simultaneous decline in the health of downstream waterways. However, monitoring the herbicide levels in these areas is a laborious task, and modern analytical approaches, such as solid-phase extraction-liquid chromatography-mass spectrometry (SPE-LC-MS) and enzyme-linked immunosorbent assay, are low-throughput and require significant sample preparation. We report here the use of microchip technology in combination with matrix-assisted laser desorption ionization mass spectrometry (MALDI-MS) for the assessment of the ecotoxicological effect of agrochemicals on aquatic species at the single-cell level. This approach quantifies the fluctuations in lipid content in sentinel organisms and targets the microalga, Chlamydomonas reinhardtii (C. reinhardtii), as the model system. Specifically, we investigated the cytotoxicity of three herbicides (atrazine, clomazone, and norflurazon) on C. reinhardtii by analyzing the lipid component variation upon assorted herbicide exposure. Lipidomic profiling reveals a significantly altered lipid content at >EC₅₀ in atrazine-exposed cells. The response for norflurazon showed similar trends but diminished in magnitude, while the result for clomazone was near muted. At lower herbicide concentrations, digalactosyldiacylglycerols showed a rapid decrease in abundance, while several other lipids displayed a moderate increase. The microchip-based MALDI technique demonstrates the ability to achieve lipidomic profiling of aquatic species exposed to different stressors, proving effective for high-throughput screening and single-cell analysis in ecotoxicity studies.

PI3Kα inhibitor CYH33 triggers antitumor immunity in murine breast cancer by activating CD8+T cells and promoting fatty acid metabolism

BACKGROUND

The phosphatidylinositol 3-kinase (PI3K) is frequently hyperactivated in cancer and plays important roles in both malignant and immune cells. The effect of PI3Kα inhibitors on the tumor microenvironment (TME) remains largely unknown. Here, we investigated the modulation of the TME by a clinical PI3Kα-specific inhibitor CYH33.

METHODS

The activity of CYH33 against a panel of murine tumors in the immune-competent context or athymic mice was detected. Single-cell RNA sequencing and multi-parameter flow cytometry were performed to determine the immune profiling of TME. The effect of CYH33 on immune cells was conducted with primary murine cells.

RESULTS

CYH33 exhibited more potent antitumor activity in immune-competent context. CYH33 enhanced the infiltration and activation of CD8+T and CD4+T cells, while attenuating M2-like macrophages and regulatory CD4+T cells. Increase in memory T cells was confirmed by the induction of long-term immune memory on CYH33 treatment. Mechanistically, CYH33 relieved the suppressed expansion of CD8+T cells via preferential polarization of the macrophages to the M1 phenotype. CYH33 promoted fatty acid (FA) metabolism in the TME, while FA enhanced the activity of CD8+T cells in vitro. The combination of CYH33 with the FA synthase (FASN) inhibitor C75 synergistically inhibited tumor growth with enhanced host immunity.

CONCLUSIONS

CYH33 induces immune activation and synergizes with FASN inhibitor to further promote the antitumor immunity, which gains novel insights into how PI3K inhibitors exert their activity by modulating TME and provides a rationale for the concurrent targeting of PI3K and FASN in breast cancer treatment.

Phospholipids: Identification and Implication in Muscle Pathophysiology

Phospholipids (PLs) are amphiphilic molecules that were essential for life to become cellular. PLs have not only a key role in compartmentation as they are the main components of membrane, but they are also involved in cell signaling, cell metabolism, and even cell pathophysiology. Considered for a long time to simply be structural elements of membranes, phospholipids are increasingly being viewed as sensors of their environment and regulators of many metabolic processes. After presenting their main characteristics, we expose the increasing methods of PL detection and identification that help to understand their key role in life processes. Interest and importance of PL homeostasis is growing as pathogenic variants in genes involved in PL biosynthesis and/or remodeling are linked to human diseases. We here review diseases that involve deregulation of PL homeostasis and present a predominantly muscular phenotype.

LipidSig: a web-based tool for lipidomic data analysis

With the continuing rise of lipidomic studies, there is an urgent need for a useful and comprehensive tool to facilitate lipidomic data analysis. The most important features making lipids different from general metabolites are their various characteristics, including their lipid classes, double bonds, chain lengths, etc. Based on these characteristics, lipid species can be classified into different categories and, more interestingly, exert specific biological functions in a group. In an effort to simplify lipidomic analysis workflows and enhance the exploration of lipid characteristics, we have developed a highly flexible and user-friendly web server called LipidSig. It consists of five sections, namely, Profiling, Differential Expression, Correlation, Network and Machine Learning, and evaluates lipid effects on cellular or disease phenotypes. One of the specialties of LipidSig is the conversion between lipid species and characteristics according to a user-defined characteristics table. This function allows for efficient data mining for both individual lipids and subgroups of characteristics. To expand the server's practical utility, we also provide analyses focusing on fatty acid properties and multiple characteristics. In summary, LipidSig is expected to help users identify significant lipid-related features and to advance the field of lipid biology. The LipidSig webserver is freely available at http://chenglab.cmu.edu.tw/lipidsig