Impact of extraction method on the lipids of Himalayan marmot oil with ultrahigh-performance liquid chromatography Q-Exactive Orbitrap mass spectrometry analysis.

RATIONALE: Himalayan marmot oil (SPO) has been used for pharmaceutical purposes for centuries, but its composition is still unclear. The bioactivity of SPO highly depends on the techniques used for its processing. This study focused on the comprehensive lipidomics of SPO, especially on the ones derived from dry rendering, wet rendering, cold pressing, and ultrasound-assisted solvent extraction. METHODS: We performed lipid profiling of SPO acquired by different extraction methods using ultrahigh-performance liquid chromatography Q-Exactive Orbitrap mass spectrometry, and 17 classes of lipids (2 BMPs, 12 LysoPCs, 9 LysoPEs, 41 PCs, 24 PEs, 23 Plasmenyl-PCs, 10 Plasmenyl-PEs, 10 MGs, 63 DGs, 187 TGs, 2 MGDGs, 3 Cer[NDS]s, 22 Cer[NS]s, 2 GlcCer[NS]s, 14 SMs, 14 CEs, and 6 AcylCarnitines) were characterized. RESULTS: Fifty-five lipids were differentially altered (VIP > 1.5, p < 0.05) between the extraction techniques, which can be used as potential biomarkers to differentiate SPO extracted by various methods. Additionally, the contents of oleic acid and arachidic acid were abundant in all samples that may suggest their medicinal values and are conducive to in-depth research. CONCLUSIONS: These findings reveal the alterations of lipid profile and free fatty acid composition in SPO obtained with different extraction methods, providing a theoretical foundation for investigating its important components as functional factors in medicines and cosmetics.

High-throughput lipidomic profiles sampled with electroporation-based biopsy differentiate healthy skin, cutaneous squamous cell carcinoma, and basal cell carcinoma.

BACKGROUND: The incidence rates of cutaneous squamous cell carcinoma (cSCC) and basal cell carcinoma (BCC) skin cancers are rising, while the current diagnostic process is time-consuming. We describe the development of a novel approach to high-throughput sampling of tissue lipids using electroporation-based biopsy, termed e-biopsy. We report on the ability of the e-biopsy technique to harvest large amounts of lipids from human skin samples. MATERIALS AND METHODS: Here, 168 lipids were reliably identified from 12 patients providing a total of 13 samples. The extracted lipids were profiled with ultra-performance liquid chromatography and tandem mass spectrometry (UPLC-MS-MS) providing cSCC, BCC, and healthy skin lipidomic profiles. RESULTS: Comparative analysis identified 27 differentially expressed lipids (p < 0.05). The general profile trend is low diglycerides in both cSCC and BCC, high phospholipids in BCC, and high lyso-phospholipids in cSCC compared to healthy skin tissue samples. CONCLUSION: The results contribute to the growing body of knowledge that can potentially lead to novel insights into these skin cancers and demonstrate the potential of the e-biopsy technique for the analysis of lipidomic profiles of human skin tissues.

Lipidomics random forest algorithm of seminal plasma is a promising method for enhancing the diagnosis of necrozoospermia.

BACKGROUND: Despite the clear clinical diagnostic criteria for necrozoospermia in andrology, the fundamental mechanisms underlying it remain elusive. This study aims to profile the lipid composition in seminal plasma systematically and to ascertain the potential of lipid biomarkers in the accurate diagnosis of necrozoospermia. It also evaluates the efficacy of a lipidomics-based random forest algorithm model in identifying necrozoospermia. METHODS: Seminal plasma samples were collected from patients diagnosed with necrozoospermia (n = 28) and normozoospermia (n = 28). Liquid chromatography-mass spectrometry (LC-MS) was used to perform lipidomic analysis and identify the underlying biomarkers. A lipid functional enrichment analysis was conducted using the LION lipid ontology database. The top 100 differentially significant lipids were subjected to lipid biomarker examination through random forest machine learning model. RESULTS: Lipidomic analysis identified 46 lipid classes comprising 1267 lipid metabolites in seminal plasma. The top five enriched lipid functions as follows: fatty acid (FA) with ≤ 18 carbons, FA with 16-18 carbons, monounsaturated FA, FA with 18 carbons, and FA with 16 carbons. The top 100 differentially significant lipids were subjected to machine learning analysis and identified 20 feature lipids. The random forest model identified lipids with an area under the curve > 0.8, including LPE(20:4) and TG(4:0_14:1_16:0). CONCLUSIONS: LPE(20:4) and TG(4:0_14:1_16:0), were identified as differential lipids for necrozoospermia. Seminal plasma lipidomic analysis could provide valuable biochemical information for the diagnosis of necrozoospermia, and its combination with conventional sperm analysis may improve the accuracy and reliability of the diagnosis.

A cell-free nutrient-supplemented perfusate allows four-day ex vivo metabolic preservation of human kidneys.

The growing disparity between the demand for transplants and the available donor supply, coupled with an aging donor population and increasing prevalence of chronic diseases, highlights the urgent need for the development of platforms enabling reconditioning, repair, and regeneration of deceased donor organs. This necessitates the ability to preserve metabolically active kidneys ex vivo for days. However, current kidney normothermic machine perfusion (NMP) approaches allow metabolic preservation only for hours. Here we show that human kidneys discarded for transplantation can be preserved in a metabolically active state up to 4 days when perfused with a cell-free perfusate supplemented with TCA cycle intermediates at subnormothermia (25 °C). Using spatially resolved isotope tracing we demonstrate preserved metabolic fluxes in the kidney microenvironment up to Day 4 of perfusion. Beyond Day 4, significant changes were observed in renal cell populations through spatial lipidomics, and increases in injury markers such as LDH, NGAL and oxidized lipids. Finally, we demonstrate that perfused kidneys maintain functional parameters up to Day 4. Collectively, these findings provide evidence that this approach enables metabolic and functional preservation of human kidneys over multiple days, establishing a solid foundation for future clinical investigations.

MobiLipid: A Tool for Enhancing CCS Quality Control of Ion Mobility-Mass Spectrometry Lipidomics by Internal Standardization.

Ion mobility-mass spectrometry (IM-MS) offers benefits for lipidomics by obtaining IM-derived collision cross sections (CCS), a conditional property of an ion that can enhance lipid identification. While drift tube (DT) IM-MS retains a direct link to the primary experimental method to derive CCS values, other IM technologies rely solely on external CCS calibration, posing challenges due to dissimilar chemical properties between lipids and calibrants. To address this, we introduce MobiLipid, a novel tool facilitating the CCS quality control of IM-MS lipidomics workflows by internal standardization. MobiLipid utilizes a newly established DTCCSN2 library for uniformly (U)13C-labeled lipids, derived from a U13C-labeled yeast extract, containing 377 DTCCSN2 values. This automated open-source R Markdown tool enables internal monitoring and straightforward compensation for CCSN2 biases. It supports lipid class- and adduct-specific CCS corrections, requiring only three U13C-labeled lipids per lipid class-adduct combination across 10 lipid classes without requiring additional external measurements. The applicability of MobiLipid is demonstrated for trapped IM (TIM)-MS measurements of an unlabeled yeast extract spiked with U13C-labeled lipids. Monitoring the CCSN2 biases of TIMCCSN2 values compared to DTCCSN2 library entries utilizing MobiLipid resulted in mean absolute biases of 0.78% and 0.33% in positive and negative ionization mode, respectively. By applying the CCS correction integrated into the tool for the exemplary data set, the mean absolute CCSN2 biases of 10 lipid classes could be reduced to approximately 0%.

De novo transcriptome and lipidome analysis of Desmodesmus abundans under model flue gas reveals adaptive changes after ten years of acclimation to high CO2.

Microalgae's ability to mitigate flue gas is an attractive technology that can valorize gas components through biomass conversion. However, tolerance and growth must be ideal; therefore, acclimation strategies are suggested. Here, we compared the transcriptome and lipidome of Desmodesmus abundans strains acclimated to high CO2 (HCA) and low CO2 (LCA) under continuous supply of model flue gas (MFG) and incomplete culture medium (BG11-N-S). Initial growth and nitrogen consumption from MFG were superior in strain HCA, reaching maximum productivity a day before strain LCA. However, similar productivities were attained at the end of the run, probably because maximum photobioreactor capacity was reached. RNA-seq analysis during exponential growth resulted in 16,435 up-regulated and 4,219 down-regulated contigs in strain HCA compared to LCA. Most differentially expressed genes (DEGs) were related to nucleotides, amino acids, C fixation, central carbon metabolism, and proton pumps. In all pathways, a higher number of up-regulated contigs with a greater magnitude of change were observed in strain HCA. Also, cellular component GO terms of chloroplast and photosystems, N transporters, and secondary metabolic pathways of interest, such as starch and triacylglycerols (TG), exhibited this pattern. RT-qPCR confirmed N transporters expression. Lipidome analysis showed increased glycerophospholipids in strain HCA, while LCA exhibited glycerolipids. Cell structure and biomass composition also revealed strains differences. HCA possessed a thicker cell wall and presented a higher content of pigments, while LCA accumulated starch and lipids, validating transcriptome and lipidome data. Overall, results showed significant differences between strains, where characteristic features of adaptation and tolerance to high CO2 might be related to the capacity to maintain a higher flux of internal C, regulate intracellular acidification, active N transporters, and synthesis of essential macromolecules for photosynthetic growth.

Untargeted lipidomics analysis in women with morbid obesity and type 2 diabetes mellitus: A comprehensive study.

There is a phenotype of obese individuals termed metabolically healthy obese that present a reduced cardiometabolic risk. This phenotype offers a valuable model for investigating the mechanisms connecting obesity and metabolic alterations such as Type 2 Diabetes Mellitus (T2DM). Previously, in an untargeted metabolomics analysis in a cohort of morbidly obese women, we observed a different lipid metabolite pattern between metabolically healthy morbid obese individuals and those with associated T2DM. To validate these findings, we have performed a complementary study of lipidomics. In this study, we assessed a liquid chromatography coupled to a mass spectrometer untargeted lipidomic analysis on serum samples from 209 women, 73 normal-weight women (control group) and 136 morbid obese women. From those, 65 metabolically healthy morbid obese and 71 with associated T2DM. In this work, we find elevated levels of ceramides, sphingomyelins, diacyl and triacylglycerols, fatty acids, and phosphoethanolamines in morbid obese vs normal weight. Conversely, decreased levels of acylcarnitines, bile acids, lyso-phosphatidylcholines, phosphatidylcholines (PC), phosphatidylinositols, and phosphoethanolamine PE (O-38:4) were noted. Furthermore, comparing morbid obese women with T2DM vs metabolically healthy MO, a distinct lipid profile emerged, featuring increased levels of metabolites: deoxycholic acid, diacylglycerol DG (36:2), triacylglycerols, phosphatidylcholines, phosphoethanolamines, phosphatidylinositols, and lyso-phosphatidylinositol LPI (16:0). To conclude, analysing both comparatives, we observed decreased levels of deoxycholic acid, PC (34:3), and PE (O-38:4) in morbid obese women vs normal-weight. Conversely, we found elevated levels of these lipids in morbid obese women with T2DM vs metabolically healthy MO. These profiles of metabolites could be explored for the research as potential markers of metabolic risk of T2DM in morbid obese women.

Meibum Lipidomic Analysis in Evaporative Dry Eye Subjects.

Meibomian Glands (MG) are sebaceous glands responsible for the production of meibum, the main component of the Tear Film Lipid Layer (TFLL). The TFLL facilitates the spread of the tear film over the ocular surface, provides stability and reduces tear evaporation. Alterations in meibum composition lead to different ocular alterations like Meibomian Gland Dysfunction (MGD) and subsequent Evaporative Dry Eye (EDE). The aim of the present study was to investigate the composition and abundance of meibum lipids and their relationship with eyelid margin abnormalities, lipid layer patterns and MG status. The study utilizes a lipidomic approach to identify and quantify lipids in meibum samples using an Elute UHPLC system. This system considered all four dimensions (mass/charge, retention time, ion mobility and intensity) to provide the accurate identification of lipid species. Samples were categorized as healthy or low/no signs of alteration (group 1) or severe signs of alteration or EDE/MGD (group 2). The current investigation found differences in Variable Importance in Projection lipid abundance between both groups for the MGD signs studied. Changes in meibum composition occur and are related to higher scores in eyelid margin hyperaemia, eyelid margin irregularity, MG orifice plugging, MG loss and lipid layer pattern.

Exploration of the Lipid Profile of Edible Oleaginous Microgreens by Mass Spectrometry-Based Lipidomics.

The spreading awareness of the health benefits associated with the consumption of plant-based foods is fueling the market of innovative vegetable products, including microgreens, recognized as a promising source of bioactive compounds. To evaluate the potential of oleaginous plant microgreens as a source of bioactive fatty acids, gas chromatography-mass spectrometry was exploited to characterize the total fatty acid content of five microgreens, namely, chia, flax, soy, sunflower, and rapeseed (canola). Chia and flax microgreens appeared as interesting sources of α-linolenic acid (ALA), with total concentrations of 2.6 and 2.9 g/100 g of dried weight (DW), respectively. Based on these amounts, approximately 15% of the ALA daily intake recommended by the European Food Safety Authority can be provided by 100 g of the corresponding fresh products. Flow injection analysis with high-resolution Fourier transform single and tandem mass spectrometry enabled a semi-quantitative profiling of triacylglycerols (TGs) and sterol esters (SEs) in the examined microgreen crops, confirming their role as additional sources of fatty acids like ALA and linoleic acid (LA), along with glycerophospholipids. The highest amounts of TGs and SEs were observed in rapeseed and sunflower microgreens (ca. 50 and 4-5 µmol/g of DW, respectively), followed by flax (ca. 20 and 3 µmol/g DW). TG 54:9, 54:8, and 54:7 prevailed in the case of flax and chia, whereas TG 54:3, 54:4, and 54:5 were the most abundant TGs in the case of rapeseed. ß-Sitosteryl linoleate and linolenate were generally prevailing in the SE profiles, although campesteryl oleate, linoleate, and linolenate exhibited a comparable amount in the case of rapeseed microgreens.

Data-dependent and -independent acquisition lipidomics analysis reveals the tissue-dependent effect of metformin on lipid metabolism.

INTRODUCTION: Despite the well-recognized health benefits, the mechanisms and site of action of metformin remains elusive. Metformin-induced global lipidomic changes in plasma of animal models and human subjects have been reported. However, there is a lack of systemic evaluation of metformin-induced lipidomic changes in different tissues. Metformin uptake requires active transporters such as organic cation transporters (OCTs), and hence, it is anticipated that metformin actions are tissue-dependent. In this study, we aim to characterize metformin effects in non-diabetic male mice with a special focus on lipidomics analysis. The findings from this study will help us to better understand the cell-autonomous (direct actions in target cells) or non-cell-autonomous (indirect actions in target cells) mechanisms of metformin and provide insights into the development of more potent yet safe drugs targeting a particular organ instead of systemic metabolism for metabolic regulations without major side effects. OBJECTIVES: To characterize metformin-induced lipidomic alterations in different tissues of non-diabetic male mice and further identify lipids affected by metformin through cell-autonomous or systemic mechanisms based on the correlation between lipid alterations in tissues and the corresponding in-tissue metformin concentrations. METHODS: A dual extraction method involving 80% methanol followed by MTBE (methyl tert-butyl ether) extraction enables the analysis of free fatty acids, polar metabolites, and lipids. Extracts from tissues and plasma of male mice treated with or without metformin in drinking water for 12 days were analyzed using HILIC chromatography coupled to Q Exactive Plus mass spectrometer or reversed-phase liquid chromatography coupled to MS/MS scan workflow (hybrid mode) on LC-Orbitrap Exploris 480 mass spectrometer using biologically relevant lipids-containing inclusion list for data-independent acquisition (DIA), named as BRI-DIA workflow followed by data-dependent acquisition (DDA), to maximum the coverage of lipids and minimize the negative effect of stochasticity of precursor selection on experimental consistency and reproducibility. RESULTS: Lipidomics analysis of 6 mouse tissues and plasma allowed a systemic evaluation of lipidomic changes induced by metformin in different tissues. We observed that (1) the degrees of lipidomic changes induced by metformin treatment overly correlated with tissue concentrations of metformin; (2) the impact on lysophosphatidylcholine (lysoPC) and cardiolipins was positively correlated with tissue concentrations of metformin, while neutral lipids such as triglycerides did not correlate with the corresponding tissue metformin concentrations; (3) increase of intestinal tricarboxylic acid (TCA) cycle intermediates after metformin treatment. CONCLUSION: The data collected in this study from non-diabetic mice with 12-day metformin treatment suggest that the overall metabolic effect of metformin is positively correlated with tissue concentrations and the effect on individual lipid subclass is via both cell-autonomous mechanisms (cardiolipins and lysoPC) and non-cell-autonomous mechanisms (triglycerides).

Integration of clinical phenoms and metabolomics facilitates precision medicine for lung cancer.

Lung cancer is a common malignancy that is frequently associated with systemic metabolic disorders. Early detection is pivotal to survival improvement. Although blood biomarkers have been used in its early diagnosis, missed diagnosis and misdiagnosis still exist due to the heterogeneity of lung cancer. Integration of multiple biomarkers or trans-omics results can improve the accuracy and reliability for lung cancer diagnosis. As metabolic reprogramming is a hallmark of lung cancer, metabolites, specifically lipids might be useful for lung cancer detection, yet systematic characterizations of metabolites in lung cancer are still incipient. The present study profiled the polar metabolome and lipidome in the plasma of lung cancer patients to construct an inclusive metabolomic atlas of lung cancer. A comprehensive analysis of lung cancer was also conducted combining metabolomics with clinical phenotypes. Furthermore, the differences in plasma lipid metabolites were compared and analyzed among different lung cancer subtypes. Alcohols, amides, and peptide metabolites were significantly increased in lung cancer, while carboxylic acids, hydrocarbons, and fatty acids were remarkably decreased. Lipid profiling revealed a significant increase in plasma levels of CER, PE, SM, and TAG in individuals with lung cancer as compared to those in healthy controls. Correlation analysis confirmed the association between a panel of metabolites and TAGs. Clinical trans-omics studies elucidated the complex correlations between lipidomic data and clinical phenotypes. The present study emphasized the clinical importance of lipidomics in lung cancer, which involves the correlation between metabolites and the expressions of other omics, ultimately influencing clinical phenotypes. This novel trans-omics network approach would facilitate the development of precision therapy for lung cancer.

Plasma-based lipidomics reveals potential diagnostic biomarkers for esophageal squamous cell carcinoma: a retrospective study.

Background: Esophageal squamous cell carcinoma (ESCC) is highly prevalent and has a high mortality rate. Traditional diagnostic methods, such as imaging examinations and blood tumor marker tests, are not effective in accurately diagnosing ESCC due to their low sensitivity and specificity. Esophageal endoscopic biopsy, which is considered as the gold standard, is not suitable for screening due to its invasiveness and high cost. Therefore, this study aimed to develop a convenient and low-cost diagnostic method for ESCC using plasma-based lipidomics analysis combined with machine learning (ML) algorithms. Methods: Plasma samples from a total of 40 ESCC patients and 31 healthy controls were used for lipidomics study. Untargeted lipidomics analysis was conducted through liquid chromatography-mass spectrometry (LC-MS) analysis. Differentially expressed lipid features were filtered based on multivariate and univariate analysis, and lipid annotation was performed using MS-DIAL software. Results: A total of 99 differential lipids were identified, with 15 up-regulated lipids and 84 down-regulated lipids, suggesting their potential as diagnostic targets for ESCC. In the single-lipid plasma-based diagnostic model, nine specific lipids (FA 15:4, FA 27:1, FA 28:7, FA 28:0, FA 36:0, FA 39:0, FA 42:0, FA 44:0, and DG 37:7) exhibited excellent diagnostic performance, with an area under the curve (AUC) exceeding 0.99. Furthermore, multiple lipid-based ML models also demonstrated comparable diagnostic ability for ESCC. These findings indicate plasma lipids as a promising diagnostic approach for ESCC.

Melatonin Mitigates Lead-Induced Oxidative Stress and Modifies Phospholipid Profile in Tobacco BY-2 Suspension Cells.

Many studies have shown that melatonin (an indoleamine) is an important molecule in plant physiology. It is known that this indoleamine is crucial during plant stress responses, especially by counteracting secondary oxidative stress (efficient direct and indirect antioxidant) and switching on different defense plant strategies. In this report, we present exogenous melatonin's potential to protect lipid profile modification and membrane integrity in Nicotiana tabacum L. line Bright Yellow 2 (BY-2) cell culture exposed to lead. There are some reports of the positive effect of melatonin on animal cell membranes; ours is the first to report changes in the lipid profile in plant cells. The experiments were performed in the following variants: LS: cells cultured on unmodified LS medium-control; (ii) MEL: BY-2 cells cultured on LS medium with melatonin added from the beginning of culture; (iii) Pb: BY-2 cells cultured on LS medium with Pb2+ added on the 4th day of culture; (iv) MEL+Pb: BY-2 cells cultured on LS medium with melatonin added from the start of culture and stressed with Pb2+ added on the 4th day of culture. Lipidomic analysis of BY-2 cells revealed the presence of 40 different phospholipids. Exposing cells to lead led to the overproduction of ROS, altered fatty acid composition and increased PLD activity and subsequently elevated the level of phosphatidic acid at the cost of dropping the phosphatidylcholine. In the presence of lead, double-bond index elevation, mainly by higher quantities of linoleic (C18:2) and linolenic (C18:3) acids in the log phase of growth, was observed. In contrast, cells exposed to heavy metal but primed with melatonin showed more similarities with the control. Surprisingly, the overproduction of ROS caused of lipid peroxidation only in the stationary phase of growth, although considerable changes in lipid profiles were observed in the log phase of growth-just 4 h after lead administration. Our results indicate that the pretreatment of BY-2 with exogenous melatonin protected tobacco cells against membrane dysfunctions caused by oxidative stress (lipid oxidation), but also findings on a molecular level suggest the possible role of this indoleamine in the safeguarding of the membrane lipid composition that limited lead-provoked cell death. The presented research indicates a new mechanism of the defense strategy of plant cells generated by melatonin.

Relationship between Plasma Lipid Profile and Cognitive Status in Early Alzheimer Disease.

Alzheimer disease (AD) is a heterogeneous and complex disease in which different pathophysiological mechanisms are involved. This heterogenicity can be reflected in different atrophy patterns or clinical manifestations. Regarding biochemical pathways involved in early AD, lipid metabolism plays an important role; therefore, lipid levels have been evaluated as potential AD diagnosis biomarkers, and their levels could be related to different AD clinical manifestations. Therefore, the aim of this work is to study AD lipid profiles from early AD patients and evaluate their clinical significance. For this purpose, untargeted plasma lipidomic analysis was carried out in early AD patients (n = 31) diagnosed with cerebrospinal fluid (CSF) biomarkers. Cluster analysis was carried out to define early AD subgroups according to the lipid levels. Then, the clinical significance of each lipid profile subgroup was studied, analyzing differences for other variables (cognitive status, CSF biomarkers, medication, comorbidities, age, and gender). The cluster analysis revealed two different groups of AD patients. Cluster 1 showed higher levels of plasma lipids and better cognitive status than Cluster 2. However, no differences were found for the other variables (age, gender, medication, comorbidities, cholesterol, and triglycerides levels) between both groups. Plasma lipid levels could differentiate two early AD subgroups, which showed different cognitive statuses. However, further research with a large cohort and longitudinal study evaluating the clinical evolution of these patients is required. In general, it would involve a relevant advance in the knowledge of AD pathological mechanisms, potential treatments, and precision medicine.

Prognostic potential of lipid profiling in cancer patients: a systematic review of mass spectrometry-based studies.

Cancer prognosis remains a critical clinical challenge. Lipidomic analysis via mass spectrometry (MS) offers the potential for objective prognostic prediction, leveraging the distinct lipid profiles of cancer patient-derived specimens. This review aims to systematically summarize the application of MS-based lipidomic analysis in prognostic prediction for cancer patients. Our systematic review summarized 38 studies from the past decade that attempted prognostic prediction of cancer patients through lipidomics. Commonly analyzed cancers included colorectal, prostate, and breast cancers. Liquid (serum and urine) and tissue samples were equally used, with liquid chromatography-tandem MS being the most common analytical platform. The most frequently evaluated prognostic outcomes were overall survival, stage, and recurrence. Thirty-eight lipid markers (including phosphatidylcholine, ceramide, triglyceride, lysophosphatidylcholine, sphingomyelin, phosphatidylethanolamine, diacylglycerol, phosphatidic acid, phosphatidylserine, lysophosphatidylethanolamine, lysophosphatidic acid, dihydroceramide, prostaglandin, sphingosine-1-phosphate, phosphatidylinosito, fatty acid, glucosylceramide and lactosylceramide) were identified as prognostic factors, demonstrating potential for clinical application. In conclusion, the potential for developing lipidomics in cancer prognostic prediction was demonstrated. However, the field is still nascent, necessitating future studies for validating and establishing lipid markers as reliable prognostic tools in clinical practice.

Pseudotargeted lipidomics analysis of scoparone on glycerophospholipid metabolism in non-alcoholic steatohepatitis mice by LC-MRM-MS.

As the inflammatory subtype of nonalcoholic fatty liver disease (NAFLD), the progression of nonalcoholic steatohepatitis (NASH) is associated with disorders of glycerophospholipid metabolism. Scoparone is the major bioactive component in Artemisia capillaris which has been widely used to treat NASH in traditional Chinese medicine. However, the underlying mechanisms of scoparone against NASH are not yet fully understood, which hinders the development of effective therapeutic agents for NASH. Given the crucial role of glycerophospholipid metabolism in NASH progression, this study aimed to characterize the differential expression of glycerophospholipids that is responsible for scoparone's pharmacological effects and assess its efficacy against NASH. Liquid chromatography-multiple reaction monitoring-mass spectrometry (LC-MRM-MS) was performed to get the concentrations of glycerophospholipids, clarify mechanisms of disease, and highlight insights into drug discovery. Additionally, pathologic findings also presented consistent changes in high-fat diet-induced NASH model, and after scoparone treatment, both the levels of glycerophospholipids and histopathology were similar to normal levels, indicating a beneficial effect during the observation time. Altogether, these results refined the insights on the mechanisms of scoparone against NASH and suggested a route to relieve NASH with glycerophospholipid metabolism. In addition, the current work demonstrated that a pseudotargeted lipidomic platform provided a novel insight into the potential mechanism of scoparone action.

Lipidome is a valuable tool for the severity prediction of coronavirus disease 2019.

Objective: To describe the lipid metabolic profile of different patients with coronavirus disease 2019 (COVID-19) and contribute new evidence on the progression and severity prediction of COVID-19. Methods: This case-control study was conducted in Peking University Third Hospital, China. The laboratory-confirmed COVID-19 patients aged ≥18 years old and diagnosed as pneumonia from December 2022 to January 2023 were included. Serum lipids were detected. The discrimination ability was calculated with the area under the curve (AUC). A random forest (RF) model was conducted to determine the significance of different lipids. Results: Totally, 44 COVID-19 patients were enrolled with 16 mild and 28 severe patients. The top 5 super classes were triacylglycerols (TAG, 55.9%), phosphatidylethanolamines (PE, 10.9%), phosphatidylcholines (PC, 6.8%), diacylglycerols (DAG, 5.9%) and free fatty acids (FFA, 3.6%) among the 778 detected lipids from the serum of COVID-19 patients. Certain lipids, especially lysophosphatidylcholines (LPCs), turned to have significant correlations with certain immune/cytokine indexes. Reduced level of LPC 20:0 was observed in severe patients particularly in acute stage. The AUC of LPC 20:0 reached 0.940 in discriminating mild and severe patients and 0.807 in discriminating acute and recovery stages in the severe patients. The results of RF models also suggested the significance of LPCs in predicting the severity and progression of COVID-19. Conclusion: Lipids probably have the potential to differentiate and forecast the severity, progression, and clinical outcomes of COVID-19 patients, with implications for immune/inflammatory responses. LPC 20:0 might be a potential target in predicting the progression and outcome and the treatment of COVID-19.

UHPLC-HRMS-based Multiomics to Explore the Potential Mechanisms and Biomarkers for Colorectal Cancer.

BACKGROUND: Understanding the metabolic changes in colorectal cancer (CRC) and exploring potential diagnostic biomarkers is crucial for elucidating its pathogenesis and reducing mortality. Cancer cells are typically derived from cancer tissues and can be easily obtained and cultured. Systematic studies on CRC cells at different stages are still lacking. Additionally, there is a need to validate our previous findings from human serum. METHODS: Ultrahigh-performance liquid chromatography tandem high-resolution mass spectrometry (UHPLC-HRMS)-based metabolomics and lipidomics were employed to comprehensively measure metabolites and lipids in CRC cells at four different stages and serum samples from normal control (NR) and CRC subjects. Univariate and multivariate statistical analyses were applied to select the differential metabolites and lipids between groups. Biomarkers with good diagnostic efficacy for CRC that existed in both cells and serum were screened by the receiver operating characteristic curve (ROC) analysis. Furthermore, potential biomarkers were validated using metabolite standards. RESULTS: Metabolite and lipid profiles differed significantly among CRC cells at stages A, B, C, and D. Dysregulation of glycerophospholipid (GPL), fatty acid (FA), and amino acid (AA) metabolism played a crucial role in the CRC progression, particularly GPL metabolism dominated by phosphatidylcholine (PC). A total of 46 differential metabolites and 29 differential lipids common to the four stages of CRC cells were discovered. Eight metabolites showed the same trends in CRC cells and serum from CRC patients compared to the control groups. Among them, palmitoylcarnitine and sphingosine could serve as potential biomarkers with the values of area under the curve (AUC) more than 0.80 in the serum and cells. Their panel exhibited excellent performance in discriminating CRC cells at different stages from normal cells (AUC = 1.00). CONCLUSIONS: To our knowledge, this is the first research to attempt to validate the results of metabolism studies of serum from CRC patients using cell models. The metabolic disorders of PC, FA, and AA were closely related to the tumorigenesis of CRC, with PC being the more critical factor. The panel composed of palmitoylcarnitine and sphingosine may act as a potential biomarker for the diagnosis of CRC, aiding in its prevention.

Investigation of the Effects of Labware Contamination on Mass Spectrometry-Based Human Serum Lipidome Analysis.

Polypropylene microcentrifuge tubes (MCTs) are increasingly used in lipidome sample preparation. In the absence of a comprehensive study evaluating ramifications of plasticware utilization in mass spectrometry-based lipidomic analyses, we conducted a systematic analysis to elucidate potential negative effects ascribable to labware contamination in serum lipidomics. During serum lipid extractions, tested glassware introduced 24 labware contaminants. In contrast, Eppendorf polypropylene MCTs contributed 485 contaminant features, many of which could be erroneously putatively identified as lipids via their m/z values. Eppendorf MCTs contamination engendered severe ion-suppression of 40 low abundance serum lipids, while generating mild to modest lipid ion-suppression across a multitude of higher abundance coeluting lipids. Less compatible polypropylene MCTs from an alternative manufacturer introduced a staggering 2,949 contaminant m/z values, severely affecting 75 coeluting serum lipids and causing more frequent and pronounced ion-suppression instances. Furthermore, by performing serum extractions with varied initial volumes, it was ascertained that labware-induced lipid ion-suppression is a dynamic phenomenon, contingent on both lipid and labware contaminant concentrations where low-abundance lipids are disproportionately impacted by coelutes of suppressive contaminants. In addition to lipid ion-suppression, the identification and quantification of 7 fatty acid endogenous serum lipids were compromised by the leaching of structurally identical surfactants from MCTs. MCTs artificially introduced 10 additional primary amides extraneous to serum samples. Utmost caution is imperative in interpreting data concerning primary amides and fatty acids when employing plastic labware. Through this investigation, we aspire to elevate awareness regarding the pernicious impact of labware contamination on lipidome analysis.

Lipidomic analysis of human TANGO2-deficient cells suggests a lipid imbalance as a cause of TANGO2 deficiency disease.

TANGO2 deficiency disease (TDD) is a multisystem disease caused by variants in the TANGO2 gene. Symptoms include neurodevelopmental delays, seizures and potentially lethal metabolic crises and cardiac arrhythmias. While the function of TANGO2 remains elusive, vitamin B5/pantothenic acid supplementation has been shown to alleviate symptoms in a fruit fly model and has also been used with success to treat individuals suffering from TDD. Since vitamin B5 is the precursor to the lipid activator coenzyme A (CoA), we hypothesized that TANGO2-deficient cells would display changes in the lipid profile compared to control and that these changes would be rescued by vitamin B5 supplementation. In addition, the specific changes seen might point to a pathway in which TANGO2 functions. Indeed, we found profound changes in the lipid profile of human TANGO2-deficient cells as well as an increased pool of free fatty acids in both human cells devoid of TANGO2 and Drosophila harboring a previously described TANGO2 loss of function allele. All these changes were reversed upon vitamin B5 supplementation. Pathway analysis showed significant increases in triglyceride as well as in lysophospholipid levels as the top enriched pathways in the absence of TANGO2. Consistent with a defect in triglyceride metabolism, we found changes in lipid droplet numbers and sizes in the absence of TANGO2 compared to control. Our data will allow for comparison between other model systems of TDD and the homing in on critical lipid imbalances that lead to the disease state.