A lipidome atlas in MS-DIAL 4

Bacterial extracellular vesicles and their interplay with the immune system

The mammalian intestinal tract harbors trillions of microorganisms confined within this space by mucosal barriers. Despite these barriers, bacterial components may still be found elsewhere in the body, even in healthy subjects. Bacteria can release small lipid-bound particles, also named bacterial extracellular vesicles (bEV). While bacteria themselves cannot normally penetrate the mucosal defense, bEVs may infiltrate the barrier and disseminate throughout the body. The extremely diverse cargo that bEVs can carry, depending on their parent species, strain, and growth conditions, grant them an equally broad potential to interact with host cells and influence immune functions. Herein, we review the current knowledge of processes underlying the uptake of bEVs by mammalian cells, and their effect on the immune system. Furthermore, we discuss how bEVs could be targeted and manipulated for diverse therapeutic purposes.

PPARγ As a Potential Target for Adipogenesis Induced by Fine Particulate Matter in 3T3-L1 Preadipocytes

Mounting evidence has shown that ambient PM_2.5 exposure is closely associated with the development of obesity, and adipose tissue represents an important endocrine target for PM_2.5. In this study, the 3T3-L1 preadipocyte differentiation model was employed to comprehensively explore the adipogenic potential of PM_2.5. After 8 days of PM_2.5 exposure, adipocyte fatty acid uptake and lipid accumulation were significantly increased, and adipogenic differentiation of 3T3-L1 cells was promoted in a concentration-dependent manner. Transcriptome and lipidome analyses revealed the systematic disruption of transcriptional and lipid profiling at 10 μg/mL PM_2.5. Functional enrichment and visualized network analyses showed that the peroxisome proliferator-activated receptor (PPAR) pathway and the metabolism of glycerophospholipids, glycerolipids, and sphingolipids were most significantly affected during adipocyte differentiation. Reporter gene assays indicated that PPARγ was activated by PM_2.5, demonstrating that PM_2.5 promoted adipogenesis by activating PPARγ. The increased transcriptional and protein expressions of PPARγ and downstream adipogenesis-associated markers (e.g., Fabp4 and CD36) were further cross-validated using qRT-PCR and western blot. PM_2.5-induced adipogenesis, PPARγ pathway activation, and lipid remodeling were significantly attenuated by the supplementation of a PPARγ antagonist (T0070907). Overall, this study yielded mechanistic insights into PM_2.5-induced adipogenesis in vitro by identifying the potential biomolecular targets for the prevention of PM_2.5-induced obesity and related metabolic diseases.

Ultraviolet exposure regulates skin metabolome based on the microbiome

Skin metabolites (< 1500 Da) play a critical role in barrier function, hydration, immune response, microbial invasion, and allergen penetration. We aimed to understand the global metabolic profile changes of the skin in relation to the microbiome and UV exposure and exposed germ-free (devoid of microbiome), disinfected mice (partially devoid of skin microbiome) and control mice with intact microbiome to immunosuppressive doses of UVB radiation. Targeted and untargeted lipidome and metabolome profiling was performed with skin tissue by high-resolution mass spectrometry. UV differentially regulated various metabolites such as alanine, choline, glycine, glutamine, and histidine in germ-free mice compared to control mice. Membrane lipid species such as phosphatidylcholine, phosphatidylethanolamine, and sphingomyelin were also affected by UV in a microbiome-dependent manner. These results shed light on the dynamics and interactions between the skin metabolome, microbiome, and UV exposure and open new avenues for the development of metabolite- or lipid-based applications to maintain skin health.

Information theory and machine learning illuminate large-scale metabolomic responses of Brachypodium distachyon to environmental change

Plant responses to environmental change are mediated via changes in cellular metabolomes. However, <5% of signals obtained from liquid chromatography tandem mass spectrometry (LC-MS/MS) can be identified, limiting our understanding of how metabolomes change under biotic/abiotic stress. To address this challenge, we performed untargeted LC-MS/MS of leaves, roots, and other organs of Brachypodium distachyon (Poaceae) under 17 organ-condition combinations, including copper deficiency, heat stress, low phosphate, and arbuscular mycorrhizal symbiosis. We found that both leaf and root metabolomes were significantly affected by the growth medium. Leaf metabolomes were more diverse than root metabolomes, but the latter were more specialized and more responsive to environmental change. We found that 1 week of copper deficiency shielded the root, but not the leaf metabolome, from perturbation due to heat stress. Machine learning (ML)-based analysis annotated approximately 81% of the fragmented peaks versus approximately 6% using spectral matches alone. We performed one of the most extensive validations of ML-based peak annotations in plants using thousands of authentic standards, and analyzed approximately 37% of the annotated peaks based on these assessments. Analyzing responsiveness of each predicted metabolite class to environmental change revealed significant perturbations of glycerophospholipids, sphingolipids, and flavonoids. Co-accumulation analysis further identified condition-specific biomarkers. To make these results accessible, we developed a visualization platform on the Bio-Analytic Resource for Plant Biology website (https://bar.utoronto.ca/efp_brachypodium_metabolites/cgi-bin/efpWeb.cgi), where perturbed metabolite classes can be readily visualized. Overall, our study illustrates how emerging chemoinformatic methods can be applied to reveal novel insights into the dynamic plant metabolome and stress adaptation.

Human metabolome variation along the upper intestinal tract

Most processing of the human diet occurs in the small intestine. Metabolites in the small intestine originate from host secretions, plus the ingested exposome1 and microbial transformations. Here we probe the spatiotemporal variation of upper intestinal luminal contents during routine daily digestion in 15 healthy male and female participants. For this, we use a non-invasive, ingestible sampling device to collect and analyse 274 intestinal samples and 60 corresponding stool homogenates by combining five mass spectrometry assays2,3 and 16S rRNA sequencing. We identify 1,909 metabolites, including sulfonolipids and fatty acid esters of hydroxy fatty acids (FAHFA) lipids. We observe that stool and intestinal metabolomes differ dramatically. Food metabolites display trends in dietary biomarkers, unexpected increases in dicarboxylic acids along the intestinal tract and a positive association between luminal keto acids and fruit intake. Diet-derived and microbially linked metabolites account for the largest inter-individual differences. Notably, two individuals who had taken antibiotics within 6 months before sampling show large variation in levels of bioactive FAHFAs and sulfonolipids and other microbially related metabolites. From inter-individual variation, we identify Blautia species as a candidate to be involved in FAHFA metabolism. In conclusion, non-invasive, in vivo sampling of the human small intestine and ascending colon under physiological conditions reveals links between diet, host and microbial metabolism.

A comparison of feature extraction capabilities of advanced UHPLC-HRMS data analysis tools in plant metabolomics

Data analysis of ultrahigh performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS) is an essential and time-consuming step in plant metabolomics and feature extraction is the fundamental step for current tools. Various methods lead to different feature extraction results in practical applications, which may puzzle users for selecting adequate data analysis tools to deal with collected data. In this work, we provide a comprehensive method evaluation for some advanced UHPLC-HRMS data analysis tools in plant metabolomics, including MS-DIAL, XCMS, MZmine, AntDAS, Progenesis QI, and Compound Discoverer. Both mixtures of standards and various complex plant matrices were specifically designed for evaluating the performances of the involved method in analyzing both targeted and untargeted metabolomics. Results indicated that AntDAS provide the most acceptable feature extraction, compound identification, and quantification results in targeted compound analysis. Concerning the complex plant dataset, both MS-DIAL and AntDAS can provide more reliable results than the others. The method comparison is maybe useful for the selection of suitable data analysis tools for users.

PeakDecoder enables machine learning-based metabolite annotation and accurate profiling in multidimensional mass spectrometry measurements

Multidimensional measurements using state-of-the-art separations and mass spectrometry provide advantages in untargeted metabolomics analyses for studying biological and environmental bio-chemical processes. However, the lack of rapid analytical methods and robust algorithms for these heterogeneous data has limited its application. Here, we develop and evaluate a sensitive and high-throughput analytical and computational workflow to enable accurate metabolite profiling. Our workflow combines liquid chromatography, ion mobility spectrometry and data-independent acquisition mass spectrometry with PeakDecoder, a machine learning-based algorithm that learns to distinguish true co-elution and co-mobility from raw data and calculates metabolite identification error rates. We apply PeakDecoder for metabolite profiling of various engineered strains of Aspergillus pseudoterreus, Aspergillus niger, Pseudomonas putida and Rhodosporidium toruloides. Results, validated manually and against selected reaction monitoring and gas-chromatography platforms, show that 2683 features could be confidently annotated and quantified across 116 microbial sample runs using a library built from 64 standards.

Short-Term Stability of Serum and Liver Extracts for Untargeted Metabolomics and Lipidomics

Thermal reactions can significantly alter the metabolomic and lipidomic content of biofluids and tissues during storage. In this study, we investigated the stability of polar metabolites and complex lipids in dry human serum and mouse liver extracts over a three-day period under various temperature conditions. Specifically, we tested temperatures of -80 °C (freezer), -24 °C (freezer), -0.5 °C (polystyrene box with gel-based ice packs), +5 °C (refrigerator), +23 °C (laboratory, room temperature), and +30 °C (thermostat) to simulate the time between sample extraction and analysis, shipping dry extracts to different labs as an alternative to dry ice, and document the impact of higher temperatures on sample integrity. The extracts were analyzed using five fast liquid chromatography-mass spectrometry (LC-MS) methods to screen polar metabolites and complex lipids, and over 600 metabolites were annotated in serum and liver extracts. We found that storing dry extracts at -24 °C and partially at -0.5 °C provided comparable results to -80 °C (reference condition). However, increasing the storage temperatures led to significant changes in oxidized triacylglycerols, phospholipids, and fatty acids within three days. Polar metabolites were mainly affected at storage temperatures of +23 °C and +30 °C.

InSpectra - A platform for identifying emerging chemical threats

Non-target analysis (NTA) employing high-resolution mass spectrometry (HRMS) coupled with liquid chromatography is increasingly being used to identify chemicals of biological relevance. HRMS datasets are large and complex making the identification of potentially relevant chemicals extremely challenging. As they are recorded in vendor-specific formats, interpreting them is often reliant on vendor-specific software that may not accommodate advancements in data processing. Here we present InSpectra, a vendor independent automated platform for the systematic detection of newly identified emerging chemical threats. InSpectra is web-based, open-source/access and modular providing highly flexible and extensible NTA and suspect screening workflows. As a cloud-based platform, InSpectra exploits parallel computing and big data archiving capabilities with a focus for sharing and community curation of HRMS data. InSpectra offers a reproducible and transparent approach for the identification, tracking and prioritisation of emerging chemical threats.

Metabolomic Analysis of Extracellular Vesicles from the Cereal Fungal Pathogen Fusarium graminearum

Fusarium graminearum (F. graminearum) is a filamentous fungus that infects cereals such as corn, wheat, and barley, with serious impact on yield as well as quality when the grain is contaminated with mycotoxins. Despite the huge impact of F. graminearum on food security and mammalian health, the mechanisms used by F. graminearum to export virulence factors during infection are not fully understood and may involve non-classical secretory pathways. Extracellular vesicles (EVs) are lipid-bound compartments produced by cells of all kingdoms that transport several classes of macromolecules and are implicated in cell-cell communication. EVs produced by human fungal pathogens carry cargo that facilitate infection, leading us to ask whether plant fungal pathogens also deliver molecules that increase virulence via EVs. We examined the metabolome of the EVs produced by F. graminearum to determine whether they carry small molecules that could modulate plant-pathogen interactions. We discovered that EVs from F. graminearum were produced in liquid medium-containing inducers of trichothecene production, but in lower quantities compared to other media. Nanoparticle tracking analysis and cryo-electron microscopy revealed that the EVs were morphologically similar to EVs from other organisms; hence, the EVs were metabolically profiled using LC-ESI-MS/MS. This analysis revealed that EVs carry 2,4-dihydroxybenzophenone (BP-1) and metabolites that have been suggested by others to have a role in host-pathogen interactions. BP-1 reduced the growth of F. graminearum in an in vitro assay, suggesting that F. graminearum might use EVs to limit metabolite self-toxicity.

Untargeted metabolomic analysis to explore the impact of soil amendments in a non-conventional wastewater treatment

As non-conventional wastewater treatment, vegetation filters make the most of the natural attenuation processes that occur in soil to remove contaminants, while providing several environmental benefits. However, this practice may introduce contaminants of emerging concern (CECs) and their transformation products (TPs) into the environment. A potential improvement to the system was tested using column experiments containing soil (S) and soil amended with woodchips (SW) or biochar (SB) irrigated with synthetic wastewater that included 11 selected CECs. This study evaluated: i) known CECs attenuation and ii) unknown metabolites formation. Known CECs attenuation was assessed by total mass balance by considering both water and soil media. An untargeted metabolomic strategy was developed to assess the formation of unknown metabolites and to identify them in water samples. The results indicated that SB enhanced CECs attenuation and led to the formation of fewer metabolites. Sorption and biodegradation processes were favored by the bigger surface area of particles in SB column, especially for compounds with negative charges. Incorporating woodchips into soil shortened retention times in the column, which reduced attenuation phenomena and resulted in the formation of significantly more metabolites. Incomplete biodegradation reactions, fostered by shorter retention times in SW column could mainly explain these results.

Evaluating Software Tools for Lipid Identification from Ion Mobility Spectrometry-Mass Spectrometry Lipidomics Data

The unambiguous identification of lipids is a critical component of lipidomics studies and greatly impacts the interpretation and significance of analyses as well as the ultimate biological understandings derived from measurements. The level of structural detail that is available for lipid identifications is largely determined by the analytical platform being used. Mass spectrometry (MS) coupled with liquid chromatography (LC) is the predominant combination of analytical techniques used for lipidomics studies, and these methods can provide fairly detailed lipid identification. More recently, ion mobility spectrometry (IMS) has begun to see greater adoption in lipidomics studies thanks to the additional dimension of separation that it provides and the added structural information that can support lipid identification. At present, relatively few software tools are available for IMS-MS lipidomics data analysis, which reflects the still limited adoption of IMS as well as the limited software support. This fact is even more pronounced for isomer identifications, such as the determination of double bond positions or integration with MS-based imaging. In this review, we survey the landscape of software tools that are available for the analysis of IMS-MS-based lipidomics data and we evaluate lipid identifications produced by these tools using open-access data sourced from the peer-reviewed lipidomics literature.

Multimodal plasma metabolomics and lipidomics in elucidating metabolic perturbations in tuberculosis patients with concurrent type 2 diabetes

Type 2 diabetes mellitus (DM) poses a major burden for the treatment and control of tuberculosis (TB). Characterization of the underlying metabolic perturbations in DM patients with TB infection would yield insights into the pathophysiology of TB-DM, thus potentially leading to improvements in TB treatment. In this study, a multimodal metabolomics and lipidomics workflow was applied to investigate plasma metabolic profiles of patients with TB and TB-DM. Significantly different biological processes and biomarkers in TB-DM vs. TB were identified using a data-driven, knowledge-based framework. Changes in metabolic and signaling pathways related to carbohydrate and amino acid metabolism were mainly captured by amide HILIC column metabolomics analysis, while perturbations in lipid metabolism were identified by the C18 metabolomics and lipidomics analysis. Compared to TB, TB-DM exhibited elevated levels of bile acids and molecules related to carbohydrate metabolism, as well as the depletion of glutamine, retinol, lysophosphatidylcholine, and phosphatidylcholine. Moreover, arachidonic acid metabolism was determined as a potential important factor in the interaction between TB and DM pathophysiology. In a correlation network of the significantly altered molecules, among the central nodes, chenodeoxycholic acid was robustly associated with TB and DM. Fatty acid (22:4) was a component of all significant modules. In conclusion, the integration of multimodal metabolomics and lipidomics provides a thorough picture of the metabolic changes associated with TB-DM. The results obtained from this comprehensive profiling of TB patients with DM advance the current understanding of DM comorbidity in TB infection and contribute to the development of more effective treatment.

Differences and Similarities in Lipid Composition, Nutritional Value, and Bioactive Potential of Four Edible Chlorella vulgaris Strains

The microalga Chlorella vulgaris is a popular food ingredient widely used in the industry, with an increasing market size and value. Currently, several edible strains of C. vulgaris with different organoleptic characteristics are commercialized to meet consumer needs. This study aimed to compare the fatty acid (FA) and lipid profile of four commercialized strains of C. vulgaris (C-Auto, C-Hetero, C-Honey, and C-White) using gas- and liquid-chromatography coupled to mass-spectrometry approaches, and to evaluate their antioxidant and anti-inflammatory properties. Results showed that C-Auto had a higher lipid content compared to the other strains and higher levels of omega-3 polyunsaturated FAs (PUFAs). However, the C-Hetero, C-Honey, and C-White strains had higher levels of omega-6 PUFAs. The lipidome signature was also different between strains, as C-Auto had a higher content of polar lipids esterified to omega-3 PUFAs, while C-White had a higher content of phospholipids with omega-6 PUFAs. C-Hetero and C-Honey showed a higher content of triacylglycerols. All extracts showed antioxidant and anti-inflammatory activity, highlighting C-Auto with greater potential. Overall, the four strains of C. vulgaris can be selectively chosen as a source of added-value lipids to be used as ingredients in food and nutraceutical applications for different market needs and nutritional requirements.

Essential lipid autacoids rewire mitochondrial energy efficiency in metabolic dysfunction-associated fatty liver disease

BACKGROUND AND AIM

Injury to hepatocyte mitochondria is common in metabolic dysfunction-associated fatty liver disease. Here, we investigated whether changes in the content of essential fatty acid-derived lipid autacoids affect hepatocyte mitochondrial bioenergetics and metabolic efficiency.

APPROACH AND RESULTS

The study was performed in transgenic mice for the fat-1 gene, which allows the endogenous replacement of the membrane omega-6-polyunsaturated fatty acid (PUFA) composition by omega-3-PUFA. Transmission electron microscopy revealed that hepatocyte mitochondria of fat-1 mice had more abundant intact cristae and higher mitochondrial aspect ratio. Fat-1 mice had increased expression of oxidative phosphorylation complexes I and II and translocases of both inner (translocase of inner mitochondrial membrane 44) and outer (translocase of the outer membrane 20) mitochondrial membranes. Fat-1 mice also showed increased mitofusin-2 and reduced dynamin-like protein 1 phosphorylation, which mediate mitochondrial fusion and fission, respectively. Mitochondria of fat-1 mice exhibited enhanced oxygen consumption rate, fatty acid β-oxidation, and energy substrate utilization as determined by high-resolution respirometry, [1- 14 C]-oleate oxidation and nicotinamide adenine dinucleotide hydride/dihydroflavine-adenine dinucleotide production, respectively. Untargeted lipidomics identified a rich hepatic omega-3-PUFA composition and a specific docosahexaenoic acid (DHA)-enriched lipid fingerprint in fat-1 mice. Targeted lipidomics uncovered a higher content of DHA-derived lipid autacoids, namely resolvin D1 and maresin 1, which rescued hepatocytes from TNFα-induced mitochondrial dysfunction, and unblocked the tricarboxylic acid cycle flux and metabolic utilization of long-chain acyl-carnitines, amino acids, and carbohydrates. Importantly, fat-1 mice were protected against mitochondrial injury induced by obesogenic and fibrogenic insults.

CONCLUSION

Our data uncover the importance of a lipid membrane composition rich in DHA and its lipid autacoid derivatives to have optimal hepatic mitochondrial and metabolic efficiency.

A mass spectrum-oriented computational method for ion mobility-resolved untargeted metabolomics

Ion mobility (IM) adds a new dimension to liquid chromatography-mass spectrometry-based untargeted metabolomics which significantly enhances coverage, sensitivity, and resolving power for analyzing the metabolome, particularly metabolite isomers. However, the high dimensionality of IM-resolved metabolomics data presents a great challenge to data processing, restricting its widespread applications. Here, we develop a mass spectrum-oriented bottom-up assembly algorithm for IM-resolved metabolomics that utilizes mass spectra to assemble four-dimensional peaks in a reverse order of multidimensional separation. We further develop the end-to-end computational framework Met4DX for peak detection, quantification and identification of metabolites in IM-resolved metabolomics. Benchmarking and validation of Met4DX demonstrates superior performance compared to existing tools with regard to coverage, sensitivity, peak fidelity and quantification precision. Importantly, Met4DX successfully detects and differentiates co-eluted metabolite isomers with small differences in the chromatographic and IM dimensions. Together, Met4DX advances metabolite discovery in biological organisms by deciphering the complex 4D metabolomics data.

Cellular transformation promotes the incorporation of docosahexaenoic acid into the endolysosome-specific lipid bis(monoacylglycerol)phosphate in breast cancer

Bis(monoacylglycero)phosphates (BMPs), a class of lipids highly enriched within endolysosomal organelles, are key components of the lysosomal intraluminal vesicles responsible for activating sphingolipid catabolic enzymes. While BMPs are understudied relative to other phospholipids, recent reports associate BMP dysregulation with a variety of pathological states including neurodegenerative diseases and lysosomal storage disorders. Since the dramatic lysosomal remodeling characteristic of cellular transformation could impact BMP abundance and function, we employed untargeted lipidomics approaches to identify and quantify BMP species in several in vitro and in vivo models of breast cancer and comparative non-transformed cells and tissues. We observed lower BMP levels within transformed cells relative to normal cells, and consistent enrichment of docosahexaenoic acid (22:6) fatty acyl chain-containing BMP species in both human- and mouse-derived mammary tumorigenesis models. Our functional analysis points to a working model whereby 22:6 BMPs serve as reactive oxygen species scavengers in tumor cells, protecting lysosomes from oxidant-induced lysosomal membrane permeabilization. Our findings suggest that breast tumor cells might divert polyunsaturated fatty acids into BMP lipids as part of an adaptive response to protect their lysosomes from elevated reactive oxygen species levels, and raise the possibility that BMP-mediated lysosomal protection is a tumor-specific vulnerability that may be exploited therapeutically.

Identification of three potential novel biomarkers for early diagnosis of acute ischemic stroke via plasma lipidomics

INTRODUCTION

Acute ischemic stroke (AIS) accounts for the majority of all stroke, globally the second leading cause of death. Due to its rapid development after onset, its early diagnosis is crucial.

OBJECTIVES

We aim to identify potential highly reliable blood-based biomarkers for early diagnosis of AIS using quantitative plasma lipid profiling via a machine learning approach.

METHODS

Lipidomics was used for quantitative plasma lipid profiling, based on ultra-performance liquid chromatography tandem mass spectrometry. Our samples were divided into a discovery and a validation set, each containing 30 AIS patients and 30 health controls (HC). Differentially expressed lipid metabolites were screened based on the criteria VIP > 1, p < 0.05, and fold change > 1.5 or < 0.67. The least absolute shrinkage and selection operator (LASSO) and random forest algorithms in machine learning were used to select differential lipid metabolites as potential biomarkers.

RESULTS

Three key differential lipid metabolites, CarnitineC10:1, CarnitineC10:1-OH and Cer(d18:0/16:0), were identified as potential biomarkers for early diagnosis of AIS. The former two, associated with thermogenesis, were down-regulated, whereas the latter, associated with necroptosis and sphingolipd metabolism, was upregulated. Univariate and multivariate logistic regressions showed that these three lipid metabolites and the resulting diagnostic model exhibited a strong ability in discriminating between AIS patients and HCs in both the discovery and validation sets, with an area under the curve above 0.9.

CONCLUSIONS

Our work provides valuable information on the pathophysiology of AIS and constitutes an important step toward clinical application of blood-based biomarkers for diagnosing AIS.

To metabolomics and beyond: a technological portfolio to investigate cancer metabolism

Tumour cells have exquisite flexibility in reprogramming their metabolism in order to support tumour initiation, progression, metastasis and resistance to therapies. These reprogrammed activities include a complete rewiring of the bioenergetic, biosynthetic and redox status to sustain the increased energetic demand of the cells. Over the last decades, the cancer metabolism field has seen an explosion of new biochemical technologies giving more tools than ever before to navigate this complexity. Within a cell or a tissue, the metabolites constitute the direct signature of the molecular phenotype and thus their profiling has concrete clinical applications in oncology. Metabolomics and fluxomics, are key technological approaches that mainly revolutionized the field enabling researchers to have both a qualitative and mechanistic model of the biochemical activities in cancer. Furthermore, the upgrade from bulk to single-cell analysis technologies provided unprecedented opportunity to investigate cancer biology at cellular resolution allowing an in depth quantitative analysis of complex and heterogenous diseases. More recently, the advent of functional genomic screening allowed the identification of molecular pathways, cellular processes, biomarkers and novel therapeutic targets that in concert with other technologies allow patient stratification and identification of new treatment regimens. This review is intended to be a guide for researchers to cancer metabolism, highlighting current and emerging technologies, emphasizing advantages, disadvantages and applications with the potential of leading the development of innovative anti-cancer therapies.

Synthesis vs. salvage of ester- and ether-linked phosphatidylethanolamine in the intracellular protozoan pathogen Toxoplasma gondii

Toxoplasma gondii is a prevalent zoonotic pathogen infecting livestock as well as humans. The exceptional ability of this parasite to reproduce in several types of nucleated host cells necessitates a coordinated usage of endogenous and host-derived nutritional resources for membrane biogenesis. Phosphatidylethanolamine is the second most common glycerophospholipid in T. gondii, but how its requirement in the acutely-infectious fast-dividing tachyzoite stage is satisfied remains enigmatic. This work reveals that the parasite deploys de novo synthesis and salvage pathways to meet its demand for ester- and ether-linked PtdEtn. Auxin-mediated depletion of the phosphoethanolamine cytidylyltransferase (ECT) caused a lethal phenotype in tachyzoites due to impaired invasion and cell division, disclosing a vital role of the CDP-ethanolamine pathway during the lytic cycle. In accord, the inner membrane complex appeared disrupted concurrent with a decline in its length, parasite width and major phospholipids. Integrated lipidomics and isotope analyses of the TgECT mutant unveiled the endogenous synthesis of ester-PtdEtn, and salvage of ether-linked lipids from host cells. In brief, this study demonstrates how T. gondii operates various means to produce distinct forms of PtdEtn while featuring the therapeutic relevance of its de novo synthesis.

Metabolite fingerprinting of the ripening process in Pixian douban using a feature-based molecular network and metabolomics analysis

The unique flavor of Pixian douban (PXDB) is widely acknowledged to be associated with its maturation process. However, there is limited knowledge about the non-volatile metabolites that contribute to this flavor. To bridge this gap, this study employed a metabolomics approach and a feature-based molecular network (FBMN) analysis to investigate the non-volatile metabolite fingerprints of PXDB during its two-year maturation process. Specifically, the FBMN tool was utilized to annotate the flavonoid, amide derivatives, and lipid components of PXDB for the first time. Subsequently, the MolNetEnhancer tool was employed to complement the FBMN annotation and identify eight substructural components. Finally, metabolomics analysis was carried out to identify 45 key metabolites involved in flavor formation across 10 major metabolic pathways (p < 0.05). Overall, the findings of this study have significantly expanded our understanding of the non-volatile metabolite fingerprinting and flavor formation mechanisms.

Oral Administration of Chaetoceros gracilis—A Marine Microalga—Alleviates Hepatic Lipid Accumulation in Rats Fed a High-Sucrose and Cholesterol-Containing Diet

Microalgae are attracting attention as a next-generation alternative source of protein and essential fatty acids that do not consume large amounts of water or land. Chaetoceros gracilis (C. gracilis)—a marine microalga—is rich in proteins, fucoxanthin, and eicosapentaenoic acid (EPA). Growing evidence indicates that dietary fucoxanthin and EPA have beneficial effects in humans. However, none of these studies have shown that dietary C. gracilis has beneficial effects in mammals. In this study, we investigated the effects of dietary C. gracilis on lipid abnormalities in Sprague-Dawley rats fed a high-sucrose cholesterol-containing diet. Dried C. gracilis was added to the control diet at a final dose of 2 or 5% (w/w). After four weeks, the soleus muscle weights were found to be dose-responsive to C. gracilis and showed a tendency to increase. The hepatic triglyceride and total cholesterol levels were significantly reduced by C. gracilis feeding compared to those in the control group. The activities of FAS and G6PDH, which are related to fatty acid de novo synthesis, were found to be dose-responsive to C. gracilis and tended to decrease. The hepatic glycerol content was also significantly decreased by C. gracilis feeding, and the serum HDL cholesterol levels were significantly increased, whereas the serum levels of cholesterol absorption markers (i.e., campesterol and β-sitosterol) and the hepatic mRNA levels of Scarb1 were significantly decreased. Water-soluble metabolite analysis showed that the muscular contents of several amino acids, including leucine, were significantly increased by C. gracilis feeding. The tendency toward an increase in the weight of the soleus muscle as a result of C. gracilis feeding may be due to the enhancement of muscle protein synthesis centered on leucine. Collectively, these results show that the oral administration of C. gracilis alleviates hepatic lipid accumulation in rats fed a high-sucrose and cholesterol-containing diet, indicating the potential use of C. gracilis as a food resource.

Lipidomic Profiling Reveals Concerted Temporal Patterns of Functionally Related Lipids in Aedes aegypti Females Following Blood Feeding

We conducted a lipidomic analysis of the whole body of female Aedes aegypti mosquitoes at different time points over the course of feeding and reproduction. There were temporal biphasic increases of more than 80% of lipids identified at the time of feeding and from 16 h to 30 h post blood meal (PBM). During these two increases, the abundance of many lipids dropped while body weight remained stable, probably reflecting blood lipid digestion and the synthesis of vitellogenin in this period. A concerted temporal pattern was particularly strong at the second peak for membrane and signalling lipids such as phosphatidylethanolamine (PE), phosphatidylinositol (PI), cardiolipin (CL), hexosylceramide (HexCer) and lyso-phosphatidic acid (LPA). Lyso-glycerophospholipids showed three distinct change patterns that are functionally related: Lyso-PE and Lyso-phosphatidylcholine (LPC), which are membrane lipids, showed little change; LPA, a signalling lipid, showed a significant increase from 16 to 30 h PBM; Lyso-PI, a bioactive lipid, and both lyso-phosphatidylglycerol (LPG) and lyso-phosphatidylserine (LPS), which are bacterial membrane lipids, showed one significant increase from the time of feeding to 16 h post blood meal. The result of our study on the anautogenous insect Ae. aegypti point to specific lipids likely to be important in the reproductive process with a role in the formation and growth of ovarian follicles.

Don't let go: co-fractionation mass spectrometry for untargeted mapping of protein-metabolite interactomes

The chemical complexity of metabolomes goes hand in hand with their functional diversity. Small molecules have many essential roles, many of which are executed by binding and modulating the function of a protein partner. The complex and dynamic protein-metabolite interaction (PMI) network underlies most if not all biological processes, but remains under-characterized. Herein, we highlight how co-fractionation mass spectrometry (CF-MS), a well-established approach to map protein assemblies, can be used for proteome and metabolome identification of the PMIs. We will review recent CF-MS studies, discuss the main advantages and limitations, summarize the available CF-MS guidelines, and outline future challenges and opportunities.

The functional implications of high-amylose wholegrain wheat flours: An in vitro digestion and fermentation approach combined with metabolomics

Wheat flour is one of the most prevalent foodstuffs for human consumption, and novel strategies are underway to enhance its nutritional properties. This work evaluated wholegrain flours from bread wheat lines with different amylose/amylopectin ratios through in vitro starch digestion and large intestine fermentation. High-amylose flours presented a higher resistant starch content and lower starch hydrolysis index. Moreover, UHPLC-HRMS metabolomics was carried out to determine the profile of the resulting in vitro fermentates. The multivariate analysis highlighted distinctive profiles between the flours derived from the different lines compared to the wild type. Peptides, glycerophospholipids, polyphenols, and terpenoids were identified as the main markers of the discrimination. The high-amylose flour fermentates showed the richest bioactive profile, containing stilbenes, carotenoids, and saponins. Present findings pave the way toward applying high-amylose flours to design novel functional foods.

Essential protein P116 extracts cholesterol and other indispensable lipids for Mycoplasmas

Mycoplasma pneumoniae, responsible for approximately 30% of community-acquired human pneumonia, needs to extract lipids from the host environment for survival and proliferation. Here, we report a comprehensive structural and functional analysis of the previously uncharacterized protein P116 (MPN_213). Single-particle cryo-electron microscopy of P116 reveals a homodimer presenting a previously unseen fold, forming a huge hydrophobic cavity, which is fully accessible to solvent. Lipidomics analysis shows that P116 specifically extracts lipids such as phosphatidylcholine, sphingomyelin and cholesterol. Structures of different conformational states reveal the mechanism by which lipids are extracted. This finding immediately suggests a way to control Mycoplasma infection by interfering with lipid uptake.

Metabolic signature of HepaRG cells exposed to ethanol and tumor necrosis factor alpha to study alcoholic steatohepatitis by LC-MS-based untargeted metabolomics

Despite the high prevalence of alcoholic liver disease, its identification and characterization remain poor, especially in early stages such as alcoholic fatty liver disease and alcoholic steatohepatitis. This latter implies diagnostic difficulties, few therapeutic options and unclear mechanisms of action. To elucidate the metabolic alterations and pinpoint affected biochemical pathways, alcoholic steatohepatitis was simulated in vitro by exposing HepaRG cells to ethanol (IC₁₀, 368 mM) and tumor necrosis factor alpha (TNF-α, 50 ng/mL) for 24 h. This combined exposure was compared to solely ethanol-exposed as well as -nonexposed cells. Four different metabolomics platforms were used combining liquid chromatography, high-resolution mass spectrometry and drift tube ion mobility to elucidate both intracellular and extracellular metabolic alterations. Some of the key findings include the influence of TNF-α in the upregulation of hepatic triglycerides and the downregulation of hepatic phosphatidylethanolamines and phosphatidylcholines. S-Adenosylmethionine showed to play a central role in the progression of alcoholic steatohepatitis. In addition, fatty acyl esters of hydroxy fatty acid (FAHFA)-containing triglycerides were detected for the first time in human hepatocytes and their alterations showed a potentially important role during the progression of alcoholic steatohepatitis. Ethoxylated phosphorylcholine was identified as a potential new biomarker of ethanol exposure.

Four-dimensional trapped ion mobility spectrometry lipidomics for high throughput clinical profiling of human blood samples

Lipidomics encompassing automated lipid extraction, a four-dimensional (4D) feature selection strategy for confident lipid annotation as well as reproducible and cross-validated quantification can expedite clinical profiling. Here, we determine 4D descriptors (mass to charge, retention time, collision cross section, and fragmentation spectra) of 200 lipid standards and 493 lipids from reference plasma via trapped ion mobility mass spectrometry to enable the implementation of stringent criteria for lipid annotation. We use 4D lipidomics to confidently annotate 370 lipids in reference plasma samples and 364 lipids in serum samples, and reproducibly quantify 359 lipids using level-3 internal standards. We show the utility of our 4D lipidomics workflow for high-throughput applications by reliable profiling of intra-individual lipidome phenotypes in plasma, serum, whole blood, venous and finger-prick dried blood spots.

Prediction of a Large-Scale Database of Collision Cross-Section and Retention Time Using Machine Learning to Reduce False Positive Annotations in Untargeted Metabolomics

Metabolite identification in untargeted metabolomics is complex, with the risk of false positive annotations. This work aims to use machine learning to successively predict the retention time (Rt) and the collision cross-section (CCS) of an open-access database to accelerate the interpretation of metabolomic results. Standards of metabolites were tested using liquid chromatography coupled with high-resolution mass spectrometry. In CCSBase and QSRR predictor machine learning models, experimental results were used to generate predicted CCS and Rt of the Human Metabolome Database. From 542 standards, 266 and 301 compounds were detected in positive and negative electrospray ionization mode, respectively, corresponding to 380 different metabolites. CCS and Rt were then predicted using machine learning tools for almost 114,000 metabolites. R² score of the linear regression between predicted and measured data achieved 0.938 and 0.898 for CCS and Rt, respectively, demonstrating the models' reliability. A CCS and Rt index filter of mean error ± 2 standard deviations could remove most misidentifications. Its application to data generated from a toxicology study on tobacco cigarettes reduced hits by 76%. Regarding the volume of data produced by metabolomics, the practical workflow provided allows for the implementation of valuable large-scale databases to improve the biological interpretation of metabolomics data.

The unknown lipids project: harmonized methods improve compound identification and data reproducibility in an inter-laboratory untargeted lipidomics study

Untargeted lipidomics allows analysis of a broader range of lipids than targeted methods and permits discovery of unknown compounds. Previous ring trials have evaluated the reproducibility of targeted lipidomics methods, but inter-laboratory comparison of compound identification and unknown feature detection in untargeted lipidomics has not been attempted. To address this gap, five laboratories analyzed a set of mammalian tissue and biofluid reference samples using both their own untargeted lipidomics procedures and a common chromatographic and data analysis method. While both methods yielded informative data, the common method improved chromatographic reproducibility and resulted in detection of more shared features between labs. Spectral search against the LipidBlast in silico library enabled identification of over 2,000 unique lipids. Further examination of LC-MS/MS and ion mobility data, aided by hybrid search and spectral networking analysis, revealed spectral and chromatographic patterns useful for classification of unknown features, a subset of which were highly reproducible between labs. Overall, our method offers enhanced compound identification performance compared to targeted lipidomics, demonstrates the potential of harmonized methods to improve inter-site reproducibility for quantitation and feature alignment, and can serve as a reference to aid future annotation of untargeted lipidomics data.

Lipidomics analysis in drug discovery and development

Despite being a relatively new addition to the Omics' landscape, lipidomics is increasingly being recognized as an important tool for the identification of druggable targets and biochemical markers. In this review we present recent advances of lipid analysis in drug discovery and development. We cover current state of the art technologies which are constantly evolving to meet demands in terms of sensitivity and selectivity. A careful selection of important examples is then provided, illustrating the versatility of lipidomics analysis in the drug discovery and development process. Integration of lipidomics with other omics', stem-cell technologies, and metabolic flux analysis will open new avenues for deciphering pathophysiological mechanisms and the discovery of novel targets and biomarkers.

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.

Comprehensive lipid profiles investigation reveals host metabolic and immune alterations during anti-tuberculosis treatment: Implications for therapeutic monitoring

In this study, we investigated the lipidome of tuberculosis patients during standard chemotherapy to discover biosignatures that could aid therapeutic monitoring. UPLC-QToF MS was used to analyze 82 baseline and treatment plasma samples of patients with pulmonary tuberculosis. Subsequently, a data-driven and knowledge-based workflow, including robust annotation, statistical analysis, and functional analysis, was applied to assess lipid profiles during treatment. Overall, the lipids species from 17 lipid subclasses were significantly altered by anti-tuberculosis chemotherapy. Cholesterol ester (CE), monoacylglycerols, and phosphatidylcholine (PC) were upregulated, whereas triacylglycerols, sphingomyelin, and ether-linked phosphatidylethanolamines (PE O-) were downregulated. Notably, PCs demonstrated a clear upward expression pattern during tuberculosis treatment. Several lipid species were identified as potential biomarkers for therapeutic monitoring, such as PC(42:6), PE(O-40:5), CE(24:6), and dihexosylceramide Hex2Cer(34:2;2 O). Functional and lipid gene enrichment analysis revealed alterations in pathways related to lipid metabolism and host immune responses. In conclusion, this study provides a foundation for the use of lipids as biomarkers for clinical management of tuberculosis.

Normal plasmalogen levels are maintained in tissues from mice with hepatocyte-specific deletion in peroxin 5

On the basis of findings that cultured rat hepatocytes secrete lipoprotein with a high plasmalogen content and the occurrence of this lipid in human serum, it has been suggested that hepatocytes play a role in the supply of plasmalogens to tissues. We tested this hypothesis in a mouse with a hepatocyte-specific defect in peroxisomes, an organelle essentially required for plasmalogen biosynthesis. We analyzed plasmalogens in lipid extracts of forebrain, liver and five further tissues and in plasma by reaction with dansylhydrazine in hydrochloric acid, which cleaves the vinyl ether of plasmalogens and forms a fluorescent dansylhydrazone, which we quantified by reversed phase high performance liquid chromatography. Reaction with dansylhydrazine in acetic acid was used to quantify free aldehydes as a control. Our results show normal levels of plasmalogens in plasma and in all tissues examined, including forebrain and the liver, irrespective of the inactivation of hepatic peroxisomes. None of the selected ether lipids analyzed by mass spectrometry in plasma and liver was decreased in the mice deficient in liver peroxisomes. In contrast, we found three plasmenylcholine species which were even significantly increased in the livers of these animals. Quantification of mRNA expression of plasmalogen biosynthetic enzymes revealed particularly low expression of fatty acyl-CoA reductase, the key regulatory enzyme of plasmalogen biosynthesis, in liver, with and without hepatic peroxisome deficiency. Our results do not support the suggested role of hepatocytes in supplying plasmalogens to tissues.

Loss of Hepatic Leucine-Rich Repeat-Containing G-Protein Coupled Receptors 4 and 5 Promotes Nonalcoholic Fatty Liver Disease

The roof plate-specific spondin-leucine-rich repeat-containing G-protein coupled receptor 4/5 (LGR4/5)-zinc and ring finger 3 (ZNRF3)/ring finger protein 43 (RNF43) module is a master regulator of hepatic Wnt/β-catenin signaling and metabolic zonation. However, its impact on nonalcoholic fatty liver disease (NAFLD) remains unclear. The current study investigated whether hepatic epithelial cell-specific loss of the Wnt/β-catenin modulator Lgr4/5 promoted NAFLD. The 3- and 6-month-old mice with hepatic epithelial cell-specific deletion of both receptors Lgr4/5 (Lgr4/5dLKO) were compared with control mice fed with normal diet (ND) or high-fat diet (HFD). Six-month-old HFD-fed Lgr4/5dLKO mice developed hepatic steatosis and fibrosis but the control mice did not. Serum cholesterol-high-density lipoprotein and total cholesterol levels in 3- and 6-month-old HFD-fed Lgr4/5dLKO mice were decreased compared with those in control mice. An ex vivo primary hepatocyte culture assay and a comprehensive bile acid (BA) characterization in liver, plasma, bile, and feces demonstrated that ND-fed Lgr4/5dLKO mice had impaired BA secretion, predisposing them to develop cholestatic characteristics. Lipidome and RNA-sequencing analyses demonstrated severe alterations in several lipid species and pathways controlling lipid metabolism in the livers of Lgr4/5dLKO mice. In conclusion, loss of hepatic Wnt/β-catenin activity by Lgr4/5 deletion led to loss of BA secretion, cholestatic features, altered lipid homeostasis, and deregulation of lipoprotein pathways. Both BA and intrinsic lipid alterations contributed to the onset of NAFLD.

Lipidome variation of industrial Saccharomyces cerevisiae strains analyzed by LC-QTOF/MS-based untargeted lipidomics

Although various yeast strains used in the food industry have been characterized by multilayer analysis, knowledge of the variation of lipid profiles involved in fermentation characteristics and stress tolerance remains in its infancy. In this study, untargeted lipidomics was applied to 10 yeast strains, including laboratory, baker's, wine, and sake yeasts, which exhibit distinct fermentation phenotypes, to obtain a comprehensive overview of the yeast lipidome. The relative standard deviation (RSD) in the abundance of the 352 identified lipid molecular species was investigated to reveal the specific and common lipids. Lipids containing very long-chain fatty acids and hydroxy long-chain fatty acids showed relatively large RSD, whereas lipids containing acyl chains, which are commonly found in yeast, such as C16-C18, showed less RSD among the 10 strains. Furthermore, principal component analysis of lipid profiles showed similar trends among industrial yeast strains. As lipids are involved in yeast phenotypes, including stress tolerance and fermentation characteristics, correlation analysis was performed with lipid abundance and phenotypes. The results revealed that molecular species with a high RSD in abundance among the 10 strains were correlated with specific stress tolerance and fermentation phenotypes.

A liquid chromatography-mass spectrometry-based metabolomics strategy to explore plant metabolic diversity

Plants are expert chemists producing millions of metabolites, only a fraction of which are known to date. Plant metabolomics explores the rationale for highly diverse metabolites evolved and synthesized by plants. Over two-thirds of modern medicines are somehow inspired and/or derived from plants, making the identification of phytochemicals a means of discovering new medicines to challenge existing and emerging diseases. This chapter introduces our established liquid chromatography-tandem mass spectrometry-based untargeted metabolomics approach centered around discovering specialized metabolites (so-called secondary metabolites) across broad lineages of nonmodel plant species. Detecting hundreds to thousands of metabolite peaks, including assigning chemical identity, makes metabolomics data generation and analysis a very complex process. Various mass spectrometry techniques are currently being developed to approach the comprehensive metabolome. Among them, untargeted metabolomics can provide new biological insights by simultaneously and unbiasedly measuring and analyzing all detected metabolites. We have provided a hands-on modular account for untargeted plant metabolomics, from preparing plant biological samples to data analysis and processing using ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry. The methods described here offer a foundation and expert opinion on plant metabolome analysis.

Intermittent fasting induces rapid hepatocyte proliferation to restore the hepatostat in the mouse liver

Nutrient availability fluctuates in most natural populations, forcing organisms to undergo periods of fasting and re-feeding. It is unknown how dietary changes influence liver homeostasis. Here, we show that a switch from ad libitum feeding to intermittent fasting (IF) promotes rapid hepatocyte proliferation. Mechanistically, IF-induced hepatocyte proliferation is driven by the combined action of systemic FGF15 and localized WNT signaling. Hepatocyte proliferation during periods of fasting and re-feeding re-establishes a constant liver-to-body mass ratio, thus maintaining the hepatostat. This study provides the first example of dietary influence on adult hepatocyte proliferation and challenges the widely held view that liver tissue is mostly quiescent unless chemically or mechanically injured.

Comparison between Sickle Cell Disease Patients and Healthy Donors: Untargeted Lipidomic Study of Erythrocytes

Sickle cell disease (SCD) is one of the most common severe monogenic disorders in the world caused by a mutation on HBB gene and characterized by hemoglobin polymerization, erythrocyte rigidity, vaso-occlusion, chronic anemia, hemolysis, and vasculopathy. Recently, the scientific community has focused on the multiple genetic and clinical profiles of SCD. However, the lipid composition of sickle cells has received little attention in the literature. According to recent studies, changes in the lipid profile are strongly linked to several disorders. Therefore, the aim of this study is to dig deeper into lipidomic analysis of erythrocytes in order to highlight any variations between healthy and patient subjects. 241 lipid molecular species divided into 17 classes have been annotated and quantified. Lipidomic profiling of SCD patients showed that over 24% of total lipids were altered most of which are phospholipids. In-depth study of significant changes in lipid metabolism can give an indication of the enzymes and genes involved. In a systems biology scenario, these variations can be useful to improve the understanding of the biochemical basis of SCD and to try to make a score system that could be predictive for the severity of clinical manifestations.

Torularhodin-Loaded Bilosomes Ameliorate Lipid Accumulation and Amino Acid Metabolism in Hypercholesterolemic Mice

SCOPE

Hypercholesterolemia is a cause of cardiovascular disease. Torularhodin is a carotenoid, and its entrapment in bilosomes helps to improve its bioavailability.

METHODS AND RESULTS

The effects of torularhodin-loaded bilosomes on lipid accumulation, inflammatory response, and serum metabolic profiles in hypercholesterolemic ApoE-/- C57BL/6J mice were investigated by feeding a high-fat, high-cholesterol diet (HFHCD) for 20 weeks. At the same time, mice were gavaged with torularhodin-loaded bilosomes for 10 weeks. The results showed that torularhodin successfully alleviated weight gain and insulin resistance in mice and could also lower blood lipids. Meanwhile, torularhodin improved liver lipid accumulation in mice and modulated inflammatory factors in the "blood-liver-ileum." Nontargeted metabolomics revealed that torularhodin significantly increased the concentrations of l-tryptophan, glyceraldehyde, hypotaurine, pyrophosphate, and niacinamide in serum (p < 0.01). In addition, targeted amino acid metabolomics verification found that torularhodin promoted the metabolism of serum amino acids in mice, particularly for branched-chain amino acids, thereby helping to improve hypercholesterolemia in mice. Finally, interaction network bioinformatics was used to demonstrate that amino acid metabolism represented an important mechanism by which torularhodin improves lipid accumulation and inflammatory response in mice.

CONCLUSIONS

Torularhodin can improve hypercholesterolemia in HFHCD-fed mice, thereby supporting the feasibility of its usage in food applications for cardiovascular disease prevention.

Accurate Analysis of Lipid Building Blocks Using the Tool LipidOne

LC/MS-based analysis techniques combined with specialized lipid platforms allow the qualitative and quantitative determination of thousands of lipid molecules. Each individual molecule can be considered as an assembly of smaller parts, often called building blocks that are the result of a myriad of biochemical synthesis and transformation processes. LipidOne is a new lipidomic tool that automatically highlights all qualitative and quantitative changes in lipid building blocks both among all detected lipid classes and between experimental groups. Thanks to LipidOne, the discovered differences among lipid building blocks can be easily linked to the activity of specific enzymes.

Optimization of Mobile Phase Modifiers for Fast LC-MS-Based Untargeted Metabolomics and Lipidomics

Liquid chromatography-mass spectrometry (LC-MS) is the method of choice for the untargeted profiling of biological samples. A multiplatform LC-MS-based approach is needed to screen polar metabolites and lipids comprehensively. Different mobile phase modifiers were tested to improve the electrospray ionization process during metabolomic and lipidomic profiling. For polar metabolites, hydrophilic interaction LC using a mobile phase with 10 mM ammonium formate/0.125% formic acid provided the best performance for amino acids, biogenic amines, sugars, nucleotides, acylcarnitines, and sugar phosphate, while reversed-phase LC (RPLC) with 0.1% formic acid outperformed for organic acids. For lipids, RPLC using a mobile phase with 10 mM ammonium formate or 10 mM ammonium formate with 0.1% formic acid permitted the high signal intensity of various lipid classes ionized in ESI(+) and robust retention times. For ESI(-), the mobile phase with 10 mM ammonium acetate with 0.1% acetic acid represented a reasonable compromise regarding the signal intensity of the detected lipids and the stability of retention times compared to 10 mM ammonium acetate alone or 0.02% acetic acid. Collectively, we show that untargeted methods should be evaluated not only on the total number of features but also based on common metabolites detected by a specific platform along with the long-term stability of retention times.

Multi-omics profiling of PC-3 cells reveals bufadienolides-induced lipid metabolic remodeling by regulating long-chain lipids synthesis and hydrolysis

INTRODUCTION

Lipid metabolism participates in various biological processes such as proliferation, apoptosis, migration, invasion, and maintenance of membrane homeostasis of prostate tumor cells. Bufadienolides, the active ingredients of Chansu, show a robust anti-proliferative effect against prostate cancer cells in vitro, but whether bufadienolides could regulate the lipid metabolism in prostate cancer has not been evaluated.

OBJECTIVES

Our study explored the regulatory effects of bufadienolides on lipid metabolism in human prostate carcinoma cells (PC-3).

METHODS

Untargeted lipidomics and transcriptomics were combined to study the effect of different bufadienolides interventions on lipid and gene changes of PC-3 cells. The key genes related to lipid metabolism and prostate cancer development were verified by qPCR and western blotting.

RESULTS

Lipidomic analysis showed that the active bufadienolides significantly downregulated the content of long-chain lipids of PC-3 cells. Based on transcriptomic and qPCR analyses, many genes related to lipid metabolism were significantly regulated by active bufadienolides, such as ELOVL6, CYP2E1, GAL3ST1, CERS1, PLA2G10, PLD1, SPTLC3, and GPX2. Bioinformatics analysis of the Cancer Genome Atlas database and literature retrieval showed that elongation of very long-chain fatty acids protein 6 (ELOVL6) and phospholipase D1 (PLD1) might be important regulatory genes. Western blot analysis revealed that active bufadienolides could downregulate PLD1 protein levels which might promote anti-prostate cancer effect.

CONCLUSIONS

All these findings support that bufadienolides might induce lipid metabolic remodeling by regulating long-chain lipids synthesis and phospholipid hydrolysis to achieve an anti-prostate cancer effect, and PLD1 would probably be the key protein.

Lipid Biogeochemistry and Modern Lipidomic Techniques

Lipids are structurally diverse biomolecules that serve multiple roles in cells. As such, they are used as biomarkers in the modern ocean and as paleoproxies to explore the geological past. Here, I review lipid geochemistry, biosynthesis, and compartmentalization; the varied uses of lipids as biomarkers; and the evolution of analytical techniques used to measure and characterize lipids. Advancements in high-resolution accurate-mass mass spectrometry have revolutionized the lipidomic and metabolomic fields, both of which are quickly being integrated into marine meta-omic studies. Lipidomics allows us to analyze tens of thousands of features, providing an open analytical window and the ability to quantify unknown compounds that can be structurally elucidated later. However, lipidome annotation is not a trivial matter and represents one of the biggest challenges for oceanographers, owing in part to the lack of marine lipids in current in silico databases and data repositories. A case study reveals the gaps in our knowledge and open opportunities to answer fundamental questions about molecular-level control of chemical reactions and global-scale patterns in the lipidscape.

Lipidomics-Paving the Road towards Better Insight and Precision Medicine in Rare Metabolic Diseases

Even though the application of Next-Generation Sequencing (NGS) has significantly facilitated the identification of disease-associated mutations, the diagnostic rate of rare diseases is still below 50%. This causes a diagnostic odyssey and prevents specific treatment, as well as genetic counseling for further family planning. Increasing the diagnostic rate and reducing the time to diagnosis in children with unclear disease are crucial for a better patient outcome and improvement of quality of life. In many cases, NGS reveals variants of unknown significance (VUS) that need further investigations. The delineation of novel (lipid) biomarkers is not only crucial to prove the pathogenicity of VUS, but provides surrogate parameters for the monitoring of disease progression and therapeutic interventions. Lipids are essential organic compounds in living organisms, serving as building blocks for cellular membranes, energy storage and signaling molecules. Among other disorders, an imbalance in lipid homeostasis can lead to chronic inflammation, vascular dysfunction and neurodegenerative diseases. Therefore, analyzing lipids in biological samples provides great insight into the underlying functional role of lipids in healthy and disease statuses. The method of choice for lipid analysis and/or huge assemblies of lipids (=lipidome) is mass spectrometry due to its high sensitivity and specificity. Due to the inherent chemical complexity of the lipidome and the consequent challenges associated with analyzing it, progress in the field of lipidomics has lagged behind other omics disciplines. However, compared to the previous decade, the output of publications on lipidomics has increased more than 17-fold within the last decade and has, therefore, become one of the fastest-growing research fields. Combining multiple omics approaches will provide a unique and efficient tool for determining pathogenicity of VUS at the functional level, and thereby identifying rare, as well as novel, genetic disorders by molecular techniques and biochemical analyses.

Heterogeneous Distribution of Phospholipid Molecular Species in the Surface Culture of Flammulina velutipes: New Facts about Lipids Containing α-Linolenic Fatty Acid

Mycelial fungi grow as colonies consisting of polar growing hyphae, developing radially from spore or inoculum. Over time, the colony develops, hyphae are subject to various exogenous or endogenous stimuli, and mycelium becomes heterogeneous in growth, gene expression, biosynthesis, and secretion of proteins and metabolites. Although the biochemical and molecular mechanisms of mycelium heterogeneity have been the subject of many studies, the role of lipids in colony development and zonality is still not understood. This work was undertaken to extend our knowledge of mycelium heterogeneity and to answer the question of how different lipid molecular species are distributed in the surface colony of the basidial fungus Flammulina velutipes and how this distribution correlates with its morphology. The heterogeneity in the lipid metabolism and lipid composition of the fungal mycelium was demonstrated. According to the real-time PCR and LC-MS/MS results, the expression of genes of PC metabolism, accumulation of phospholipid classes, and degree of unsaturation of PC and PE increased in the direction from the center to the periphery of the colony. The peripheral zone of the colony was characterized by a higher value of the PC/PE ratio and a higher level of phospholipids esterified by linolenic acid. Considering that the synthesis of phospholipids in fungi occurs in different ways, we also conducted experiments with deuterium-labeled phospholipid precursors and found out that the Kennedy pathway is the predominant route for PC biosynthesis in F. velutipes. The zonal differences in gene expression and lipid composition can be explained by the participation of membrane lipids in polar growth maintenance and regulation.

Changes in Lipidomics, Metabolomics, and the Gut Microbiota in CDAA-Induced NAFLD Mice after Polyene Phosphatidylcholine Treatment

Non-alcoholic fatty liver disease (NAFLD) is the most common chronic liver disease in most parts of the world. Although there is no first-line drug approved for the treatment of NAFLD, polyene phosphatidylcholine (PPC) is used by clinicians to treat NAFLD patients. This study aimed to evaluate the efficacy of PPC on a mice model of NAFLD, and to study the PPC's mechanism of action. The mice were fed a choline-deficient, L-amino acid-defined (CDAA) diet to induce NAFLD and were subsequently treated with PPC. The treatment effects were evaluated by the liver index, histopathological examination, and routine blood chemistry analyses. Lipidomics and metabolomics analyses of 54 samples were carried out using ultraperformance liquid chromatography (UPLC) coupled to a mass spectrometer to select for changes in metabolites associated with CDAA diet-induced NAFLD and the effects of PPC treatment. The intestinal flora of mice were extracted for gene sequencing to find differences before and after the induction of NAFLD and PPC treatment. PPC significantly improved the CDAA diet-induced NAFLD condition in mice. A total of 19 metabolites including 5 polar metabolites and 14 lipids showed marked changes. In addition, significant differences in the abundance of Lactobacillus were associated with NAFLD. We inferred that the protective therapeutic effect of PPC on the liver was related to the supplement of phosphatidylcholine, lysophosphatidylcholine, and sphingomyelin (PC, LPC, and SM, resectively) and acylcarnitine metabolism. This study developed a methodology for exploring the pathogenesis of NAFLD and can be extended to other therapeutic agents for treating NAFLD.

Dysregulated ceramide metabolism in mouse progressive dermatitis resulting from constitutive activation of Jak1

Coordinated lipid metabolism contributes to maintaining skin homeostasis by regulating skin barrier formation, immune reactions, thermogenesis, and perception. Several reports have documented the changes in lipid composition in dermatitis, including in atopic dermatitis (AD); however, the specific mechanism by which these lipid profiles are altered during AD pathogenesis remains unknown. Here, we performed untargeted and targeted lipidomic analyses of an AD-like dermatitis model resulting from constitutive activation of Janus kinase 1 (Spade mice) to capture the comprehensive lipidome profile during dermatitis onset and progression. We successfully annotated over 700 skin lipids, including glycerophospholipids, ceramides, neutral lipids, and fatty acids, many of which were found to be present at significantly changed levels after dermatitis onset, as determined by the pruritus and erythema. Among them, we found the levels of ceramides composed of nonhydroxy fatty acid and dihydrosphingosine containing very long-chain (C22 or more) fatty acids were significantly downregulated before AD onset. Furthermore, in vitro enzyme assays using the skin of Spade mice demonstrated the enhancement of ceramide desaturation. Finally, we revealed topical application of ceramides composed of nonhydroxy fatty acid and dihydrosphingosine before AD onset effectively ameliorated the progression of AD symptoms in Spade mice. Our results suggest that the disruption in epidermal ceramide composition is caused by boosting ceramide desaturation in the initiation phase of AD, which regulates AD pathogenesis.