Saturated fatty acid concentrations are predictive of insulin sensitivity and beta cell compensation in dogs.

Chronic feeding of a high fat diet (HFD) in preclinical species induces broad metabolic dysfunction characterized by body weight gain, hyperinsulinemia, dyslipidemia and impaired insulin sensitivity. The plasma lipidome is not well characterized in dogs with HFD-induced metabolic dysfunction. We therefore aimed to describe the alterations that occur in the plasma lipid composition of dogs that are fed a HFD and examine the association of these changes with the clinical signs of metabolic dysfunction. Dogs were fed a normal diet (ND) or HFD for 12 weeks. Insulin sensitivity (SI) and beta cell compensation (AIRG) were assessed through an intravenous glucose tolerance test (IVGTT) and serum biochemistry was analyzed before the introduction of HFD and again after 12 weeks of continued ND or HFD feeding. Plasma lipidomics were conducted prior to the introduction of HFD and again at week 8 in both ND and HFD-fed dogs. 12 weeks of HFD feeding resulted in impaired insulin sensitivity and increased beta cell compensation measured by SI (ND mean: 11.5 [mU/l]-1 min-1, HFD mean: 4.7 [mU/l]-1 min-1) and AIRG (ND mean: 167.0 [mU/l]min, HFD mean: 260.2 [mU/l]min), respectively, compared to dogs fed ND over the same duration. Chronic HFD feeding increased concentrations of plasma lipid species and deleterious fatty acids compared to dogs fed a ND. Saturated fatty acid (SFA) concentrations were significantly associated with fasting insulin (R2 = 0.29), SI (R2 = 0.49) and AIRG (R2 = 0.37) in all dogs after 12 weeks, irrespective of diet. Our results demonstrate that chronic HFD feeding leads to significant changes in plasma lipid composition and fatty acid concentrations associated with metabolic dysfunction. High SFA concentrations may be predictive of deteriorated insulin sensitivity in dogs.

Mitochondrial lipidomes are tissue specific - low cholesterol contents relate to UCP1 activity.

Lipid composition is conserved within sub-cellular compartments to maintain cell function. Lipidomic analyses of liver, muscle, white and brown adipose tissue (BAT) mitochondria revealed substantial differences in their glycerophospholipid (GPL) and free cholesterol (FC) contents. The GPL to FC ratio was 50-fold higher in brown than white adipose tissue mitochondria. Their purity was verified by comparison of proteomes with ER and mitochondria-associated membranes. A lipid signature containing PC and FC, calculated from the lipidomic profiles, allowed differentiation of mitochondria from BAT of mice housed at different temperatures. Elevating FC in BAT mitochondria prevented uncoupling protein (UCP) 1 function, whereas increasing GPL boosted it. Similarly, STARD3 overexpression facilitating mitochondrial FC import inhibited UCP1 function in primary brown adipocytes, whereas a knockdown promoted it. We conclude that the mitochondrial GPL/FC ratio is key for BAT function and propose that targeting it might be a promising strategy to promote UCP1 activity.

Identification and validation of a blood- based diagnostic lipidomic signature of pediatric inflammatory bowel disease.

Improved biomarkers are needed for pediatric inflammatory bowel disease. Here we identify a diagnostic lipidomic signature for pediatric inflammatory bowel disease by analyzing blood samples from a discovery cohort of incident treatment-naïve pediatric patients and validating findings in an independent inception cohort. The lipidomic signature comprising of only lactosyl ceramide (d18:1/16:0) and phosphatidylcholine (18:0p/22:6) improves the diagnostic prediction compared with high-sensitivity C-reactive protein. Adding high-sensitivity C-reactive protein to the signature does not improve its performance. In patients providing a stool sample, the diagnostic performance of the lipidomic signature and fecal calprotectin, a marker of gastrointestinal inflammation, does not substantially differ. Upon investigation in a third pediatric cohort, the findings of increased lactosyl ceramide (d18:1/16:0) and decreased phosphatidylcholine (18:0p/22:6) absolute concentrations are confirmed. Translation of the lipidomic signature into a scalable diagnostic blood test for pediatric inflammatory bowel disease has the potential to support clinical decision making.

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.

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.

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.

Roles of glutamic pyruvate transaminase 2 in reprogramming of airway epithelial lipidomic and metabolomic profiles after smoking.

Metabolic abnormalities represent one of the pathological features of chronic obstructive pulmonary disease (COPD). Glutamic pyruvate transaminase 2 (GPT2) is involved in glutamate metabolism and lipid synthesis pathways, whilst the exact roles of GPT2 in the occurrence and development of COPD remains uncertain. This study aims at investigating how GPT2 and the associated genes modulate smoking-induced airway epithelial metabolism and damage by reprogramming lipid synthesis. The circulating or human airway epithelial metabolomic and lipidomic profiles of COPD patients or cell-lines explored with smoking were assessed to elucidate the pivotal roles of GPT2 in reprogramming processes. We found that GPT2 regulate the reprogramming of lipid metabolisms caused by smoking, especially phosphatidylcholine (PC) and triacylglycerol (TAG), along with changes in the expression of lipid metabolism-associated genes. GPT2 modulated cell sensitivities and survival in response to smoking by enhancing mitochondrial functions and maintaining lipid and energy homeostasis. Our findings provide evidence for the involvement of GPT2 in the reprogramming of airway epithelial lipids following smoking, as well as the molecular mechanisms underlying GPT2-mediated regulation, which may offer an alternative of therapeutic strategies for chronic lung diseases.

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.

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.

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.

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.

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.

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.

Integrated omics of Saccharomyces cerevisiae CENPK2-1C reveals pleiotropic drug resistance and lipidomic adaptations to cannabidiol.

Yeast metabolism can be engineered to produce xenobiotic compounds, such as cannabinoids, the principal isoprenoids of the plant Cannabis sativa, through heterologous metabolic pathways. However, yeast cell factories continue to have low cannabinoid production. This study employed an integrated omics approach to investigate the physiological effects of cannabidiol on S. cerevisiae CENPK2-1C yeast cultures. We treated the experimental group with 0.5 mM CBD and monitored CENPK2-1C cultures. We observed a latent-stationary phase post-diauxic shift in the experimental group and harvested samples in the inflection point of this growth phase for transcriptomic and metabolomic analysis. We compared the transcriptomes of the CBD-treated yeast and the positive control, identifying eight significantly overexpressed genes with a log fold change of at least 1.5 and a significant adjusted p-value. Three notable genes were PDR5 (an ABC-steroid and cation transporter), CIS1, and YGR035C. These genes are all regulated by pleiotropic drug resistance linked promoters. Knockout and rescue of PDR5 showed that it is a causal factor in the post-diauxic shift phenotype. Metabolomic analysis revealed 48 significant spectra associated with CBD-fed cell pellets, 20 of which were identifiable as non-CBD compounds, including fatty acids, glycerophospholipids, and phosphate-salvage indicators. Our results suggest that mitochondrial regulation and lipidomic remodeling play a role in yeast's response to CBD, which are employed in tandem with pleiotropic drug resistance (PDR). We conclude that bioengineers should account for off-target product C-flux, energy use from ABC-transport, and post-stationary phase cell growth when developing cannabinoid-biosynthetic yeast strains.

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.

Paired plasma lipidomics and proteomics analysis in the conversion from mild cognitive impairment to Alzheimer's disease.

BACKGROUND: Alzheimer's disease (AD) is a neurodegenerative condition for which there is currently no available medication that can stop its progression. Previous studies suggest that mild cognitive impairment (MCI) is a phase that precedes the disease. Therefore, a better understanding of the molecular mechanisms behind MCI conversion to AD is needed. METHOD: Here, we propose a machine learning-based approach to detect the key metabolites and proteins involved in MCI progression to AD using data from the European Medical Information Framework for Alzheimer's Disease Multimodal Biomarker Discovery Study. Proteins and metabolites were evaluated separately in multiclass models (controls, MCI and AD) and together in MCI conversion models (MCI stable vs converter). Only features selected as relevant by 3/4 algorithms proposed were kept for downstream analysis. RESULTS: Multiclass models of metabolites highlighted nine features further validated in an independent cohort (0.726 mean balanced accuracy). Among these features, one metabolite, oleamide, was selected by all the algorithms. Further in-vitro experiments in rodents showed that disease-associated microglia excreted oleamide in vesicles. Multiclass models of proteins stood out with nine features, validated in an independent cohort (0.720 mean balanced accuracy). However, none of the proteins was selected by all the algorithms. Besides, to distinguish between MCI stable and converters, 14 key features were selected (0.872 AUC), including tTau, alpha-synuclein (SNCA), junctophilin-3 (JPH3), properdin (CFP) and peptidase inhibitor 15 (PI15) among others. CONCLUSIONS: This omics integration approach highlighted a set of molecules associated with MCI conversion important in neuronal and glia inflammation pathways.