Metabolic profiling reveals the nutraceutical effect of Gongolaria abies-marina and Rosmarinus officinalis extracts in a type 1 diabetes animal model.

Nutraceuticals have gained increasing interest, prompting the need to investigate plant extracts for their beneficial properties and potential side effects. This study aimed to assess the nutraceutical effects of environmentally clean extracts from Rosmarinus officinalis and Gongolaria abies-marina (formerly Cystoseira abies-marina (Phaeophyceae)) on the metabolic profile of streptozotocin-induced diabetic rats. We conducted untargeted LC-QTOF-MS metabolic profiling on six groups of rats: three diabetic groups receiving either a placebo, R. officinalis, or G. abies-marina extracts, and three corresponding control groups. The metabolic analysis revealed significant alterations in the levels of various glycerophospholipids, sterol lipids, and fatty acyls. Both extracts influenced the metabolic profile, partially mitigating diabetes-induced changes. Notably, G. abies-marina extract had a more pronounced impact on the animals' metabolic profiles compared to R. officinalis. In conclusion, our findings suggest that environmentally clean extracts from R. officinalis and G. abies-marina possess nutraceutical potential, as they were able to modulate the metabolic profile in streptozotocin-induced diabetic rats. G. abies-marina extract exhibited a more substantial effect on metabolic alterations induced by diabetes compared to R. officinalis. These results warrant further exploration of these plant extracts for their potential in managing diabetes-related metabolic disturbances.

First insight about the ability of specific glycerophospholipids to discriminate non-small cell lung cancer subtypes.

Introduction: Discrimination between adenocarcinoma (ADC) and squamous cell carcinoma (SCC) subtypes in non-small cell lung cancer (NSCLC) patients is a significant challenge in oncology. Lipidomics analysis provides a promising approach for this differentiation. Methods: In an accompanying paper, we explored oxPCs levels in a cohort of 200 NSCLC patients. In this research, we utilized liquid chromatography coupled with mass spectrometry (LC-MS) to analyze the lipidomics profile of matching tissue and plasma samples from 25 NSCLC patients, comprising 11 ADC and 14 SCC cases. This study builds upon our previous findings, which highlighted the elevation of oxidised phosphatidylcholines (oxPCs) in NSCLC patients. Results: We identified eight lipid biomarkers that effectively differentiate between ADC and SCC subtypes using an untargeted approach. Notably, we observed a significant increase in plasma LPA 20:4, LPA 18:1, and LPA 18:2 levels in the ADC group compared to the SCC group. Conversely, tumour PC 16:0/18:2, PC 16:0/4:0; CHO, and plasma PC 16:0/18:2; OH, PC 18:0/20:4; OH, PC 16:0/20:4; OOH levels were significantly higher in the ADC group. Discussion: Our study is the first to report that plasma LPA levels can distinguish between ADC and SCC patients in NSCLC, suggesting a potential role for LPAs in NSCLC subtyping. This finding warrants further investigation into the mechanisms underlying these differences and their clinical implications.

imputomics: web server and R package for missing values imputation in metabolomics data.

MOTIVATION: Missing values are commonly observed in metabolomics data from mass spectrometry. Imputing them is crucial because it assures data completeness, increases the statistical power of analyses, prevents inaccurate results, and improves the quality of exploratory analysis, statistical modeling, and machine learning. Numerous Missing Value Imputation Algorithms (MVIAs) employ heuristics or statistical models to replace missing information with estimates. In the context of metabolomics data, we identified 52 MVIAs implemented across 70 R functions. Nevertheless, the usage of those 52 established methods poses challenges due to package dependency issues, lack of documentation, and their instability. RESULTS: Our R package, 'imputomics', provides a convenient wrapper around 41 (plus random imputation as a baseline model) out of 52 MVIAs in the form of a command-line tool and a web application. In addition, we propose a novel functionality for selecting MVIAs recommended for metabolomics data with the best performance or execution time. AVAILABILITY AND IMPLEMENTATION: 'imputomics' is freely available as an R package (github.com/BioGenies/imputomics) and a Shiny web application (biogenies.info/imputomics-ws). The documentation is available at biogenies.info/imputomics.

Extracellular matrix hyaluronan modulates fat cell differentiation and primary cilia dynamics.

Hyaluronan is an important extracellular matrix component, with poorly documented physiological role in the context of lipid-rich adipose tissue. We have investigated the global impact of hyaluronan removal from adipose tissue environment by in vitro exposure to exogenous hyaluronidase (or heat inactivated enzyme). Gene set expression analysis from RNA sequencing revealed downregulated adipogenesis as a main response to hyaluronan removal from human adipose tissue samples, which was confirmed by hyaluronidase-mediated inhibition of adipocyte differentiation in the 3T3L1 adipose cell line. Hyaluronidase exposure starting from the time of induction with the differentiation cocktail reduced lipid accumulation in mature adipocytes, limited the expression of terminal differentiation marker genes, and impaired the early induction of co-regulated Cebpa and Pparg mRNA. Reduction of Cebpa and Pparg expression by exogenous hyaluronidase was also observed in cultured primary preadipocytes from subcutaneous, visceral or brown adipose tissue of mice. Mechanistically, inhibition of adipogenesis by hyaluronan removal was not caused by changes in osmotic pressure or cell inflammatory status, could not be mimicked by exposure to threose, a metabolite generated by hyaluronan degradation, and was not linked to alteration in endogenous Wnt ligands expression. Rather, we observed that hyaluronan removal associated with disrupted primary cilia dynamics, with elongated cilium and higher proportions of preadipocytes that remained ciliated in hyaluronidase-treated conditions. Thus, our study points to a new link between ciliogenesis and hyaluronan impacting adipose tissue development.

A single extraction 96-well method for LC-MS/MS quantification of urinary eicosanoids, steroids and drugs.

Urinary eicosanoid concentrations reflect inflammatory processes in multiple diseases and have been used as biomarkers of disease as well as suggested for patient stratification in precision medicine. However, implementation of urinary eicosanoid profiling in large-scale analyses is restricted due to sample preparation limits. Here we demonstrate a single solid-phase extraction of 300 µL urine in 96-well-format for prostaglandins, thromboxanes, isoprostanes, cysteinyl-leukotriene E4 and the linoleic acid-derived dihydroxy-octadecenoic acids (9,10- and 12,13-DiHOME). A simultaneous screening protocol was also developed for cortisol/cortisone and 7 exogenous steroids as well as 3 cyclooxygenase inhibitors. Satisfactory performance for quantification of eicosanoids with an appropriate internal standard was demonstrated for intra-plate analyses (CV = 8.5-15.1%) as well as for inter-plate (n = 35) from multiple studies (CV = 22.1-34.9%). Storage stability was evaluated at - 20 °C, and polar tetranors evidenced a 50% decrease after 5 months, while the remaining eicosanoids evidenced no significant degradation. All eicosanoids were stable over 3.5-years in urine stored at - 80 °C. This method will facilitate the implementation of urinary eicosanoid quantification in large-scale screening.

Metabolomic profile of acute myeloid leukaemia parallels of prognosis and response to therapy.

The heterogeneity of acute myeloid leukemia (AML), a complex hematological malignancy, is caused by mutations in myeloid cells affecting their differentiation and proliferation. Thus, various cytogenetic alterations in AML cells may be characterized by a unique metabolome and require different treatment approaches. In this study, we performed untargeted metabolomics to assess metabolomics differences between AML patients and healthy controls, AML patients with different treatment outcomes, AML patients in different risk groups based on the 2017 European LeukemiaNet (ELN) recommendations for the diagnosis and management of AML, AML patients with and without FLT3-ITD mutation, and a comparison between patients with FLT3-ITD, CBF-AML (Core binding factor acute myelogenous leukemia), and MLL AML (mixed-lineage leukemia gene) in comparison to control subjects. Analyses were performed in serum samples using liquid chromatography coupled with mass spectrometry (LC-MS). The obtained metabolomics profiles exhibited many alterations in glycerophospholipid and sphingolipid metabolism and allowed us to propose biomarkers based on each of the above assessments as an aid for diagnosis and eventual classification, allowing physicians to choose the best-suited treatment approach. These results highlight the application of LC-MS-based metabolomics of serum samples as an aid in diagnostics and a potential minimally invasive prognostic tool for identifying various cytogenetic and treatment outcomes of AML.

Serum metabolomics identified specific lipid compounds which may serve as markers of disease progression in patients with Alström and Bardet-Biedl syndromes.

Objectives: Alström syndrome (ALMS) and Bardet-Biedl syndrome (BBS) are among the so-called ciliopathies and are associated with the development of multiple systemic abnormalities, including early childhood obesity and progressive neurodegeneration. Given the progressive deterioration of patients' quality of life, in the absence of defined causal treatment, it seems reasonable to identify the metabolic background of these diseases and search for their progression markers. The aim of this study was to find metabolites characteristic to ALMS and BBS, correlating with clinical course parameters, and related to the diseases progression. Methods: Untargeted metabolomics of serum samples obtained from ALMS and BBS patients (study group; n = 21) and obese/healthy participants (control group; each of 35 participants; n = 70) was performed using LC-QTOF-MS method at the study onset and after 4 years of follow-up. Results: Significant differences in such metabolites as valine, acylcarnitines, sphingomyelins, phosphatidylethanolamines, phosphatidylcholines, as well as lysophosphatidylethanolamines and lysophosphatidylcholines were observed when the study group was compared to both control groups. After a follow-up of the study group, mainly changes in the levels of lysophospholipids and phospholipids (including oxidized phospholipids) were noted. In addition, in case of ALMS/BBS patients, correlations were observed between selected phospholipids and glucose metabolism parameters. We also found correlations of several LPEs with patients' age (p < 0.05), but the level of only one of them (hexacosanoic acid) correlated negatively with age in the ALMS/BBS group, but positively in the other groups. Conclusion: Patients with ALMS/BBS have altered lipid metabolism compared to controls or obese subjects. As the disease progresses, they show elevated levels of lipid oxidation products, which may suggest increased oxidative stress. Selected lipid metabolites may be considered as potential markers of progression of ALMS and BBS syndromes.

Glioma and post-translational modifications: A complex relationship.

Post-translational modifications (PTMs) are common covalent processes in biochemical pathways that alter protein function and activity. These modifications occur through proteolytic cleavage or attachment of modifying groups, such as phosphoryl, methyl, glycosyl, or acetyl groups, with one or more amino acid residues of a single protein. Some PTMs also present crosstalk abilities that affect both protein functionality and structure, creating new proteoforms. Any alteration in organism homeostasis may be a cancer hallmark. Cataloging PTMs and consequently, emerging proteoforms, present new therapeutic targets, approaches, and opportunities to discover additional discriminatory biomarkers in disease diagnostics. In this review, we focus on experimentally confirmed PTMs and their potential crosstalk in glioma research to introduce new opportunities for this tumor type, which emerge within the PTMomics area.

Adaptation of the AbsoluteIDQ p180 kit to the analysis of metabolites in the human aqueous humor.

The aim of this study was to use the commercial kit AbsoluteIDQ p180 (Biocrates) for the quantification of metabolites in aqueous humor (AH), as well as to determine the optimal volume of AH that is necessary to obtain reliable and reproducible results. Different volumes of AH (10 µl, 20 µl, and 30 µl) were tested. Of the 188 metabolites measurable with the Biocrates kit, 69 were detected in AH. Depending on the volume used, 41, 51, and 63 metabolites were measured using 10 µl, 20 µl, and 30 µl of AH, respectively. The repeatability of the measurements improved with increasing AH volume. Considering only those metabolites that were obtained with a CV < 15%, 34 metabolites at 10 µl, 41 at 20 µl, and 44 at 30 µl AH were received. On this basis, it can be concluded that the tested method can be successfully applied to analyze metabolites in the human AH. To achieve the most comprehensive detection range and highest repeatability of measurements, it is recommended to use 30 µl AH.

Searching for Effective Methods of Diagnosing Nervous System Lesions in Patients with Alström and Bardet-Biedl Syndromes.

Bardet-Biedl syndrome (BBS) and Alström syndrome (ALMS) are rare multisystem diseases with an autosomal recessive mode of inheritance and genetic heterogeneity, characterized by visual impairment, hearing impairment, cardiomyopathy, childhood obesity, and insulin resistance. The purpose of our study was to evaluate the indicators of nervous system changes occurring in patients with ALMS and BBS using optical coherence tomography (OCT) and magnetic resonance spectroscopy (MRS) methods compared to a group of healthy subjects. The OCT results showed significantly lower macular thickness in the patient group compared to the control group (p = 0.002). The MRS study observed differences in metabolite levels between the study and control groups in brain areas such as the cerebellum, thalamus, and white matter. After summing the concentrations from all areas, statistically significant results were obtained for N-acetylaspartate, total N-acetylaspartate, and total creatine. Concentrations of these metabolites were reduced in ALMS/BBS patients by 38% (p = 0.0004), 35% (p = 0.0008), and 28% (p = 0.0005), respectively. Our results may help to understand the pathophysiology of these rare diseases and identify strategies for new therapies.

Simultaneous Comparison of Aqueous Humor and Serum Metabolic Profiles of Diabetic and Nondiabetic Patients Undergoing Cataract Surgery-A Targeted and Quantitative Metabolomics Study.

The aim of this study was to compare the aqueous humor (AH) and serum concentrations of metabolites in diabetic (n = 36) and nondiabetic (n = 36) senior adults undergoing cataract surgery. Blood samples were collected before surgery and AH during surgery. Liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS)-based targeted metabolomic and lipidomic analyses of samples were performed using the AbsoluteIDQ® p180 kit. Out of 188 metabolites targeted by the kit, 41 and 133 were detected in >80% of AH and serum samples, respectively. Statistical analysis performed to indicate metabolites differentiating diabetic and nondiabetic patients showed 8 and 20 significant metabolites in AH and serum, respectively. Pathway analysis performed for significant metabolites revealed that galactose metabolism is mostly affected in the AH, while arginine biosynthesis is mostly affected in the serum. Among metabolites that differentiate diabetic and nondiabetic patients, arginine was the only metabolite common to both serum and AH samples, as well as the only one with a decreased concentration in both body fluids of diabetic patients. Concentrations of the rest were elevated in AH and lowered in serum. This may suggest different mechanisms of diabetes-related dysregulation of the local metabolism in the eye in comparison to systemic changes observed in the blood.

Changes in plasma endocannabinoids concentrations correlate with 18F-FDG PET/MR uptake in brown adipocytes in humans.

Introduction: Recent data suggest a possible role of endocannabinoids in the regulation of brown adipose tissue (BAT) activity. Those findings indicate potential treatment options for obesity. The aim of this study was to evaluate the relationship between plasma endocannabinoids concentrations and the presence of BAT in humans. Methods: The study group consisted of 25 subjects divided into two groups: BAT positive BAT(+), (n = 17, median age = 25 years) and BAT negative BAT(-), (n = 8, median age = 28 years). BAT was estimated using 18F-FDG PET/MR after 2 h of cold exposure. The level of plasma endocannabinoids was assessed at baseline, 60 min and 120 min of cold exposure. Results: In both groups, BAT(+) and BAT(-), during the cooling, we observed a decrease of the same endocannabinoids: arachidonoylethanolamide (AEA), eicosapentaenoyl ethanolamide (EPEA) and oleoyl ethanolamide (OEA) with a much more profound decline in BAT(+) subjects. Statistically significant fall of PEA (palmitoylethanolamide) and SEA (stearoylethanolamide) concentrations after 60 min (FC = 0.7, p = 0.007 and FC = 0.8, p = 0.03, respectively) and 120 min (FC = 0.81, p = 0.004, and FC = 0.9, p = 0.01, respectively) of cooling was observed only in individuals with BAT. Conclusion: We noticed the profound decline of endocannabinoids concentrations in subjects with increased 18F-FDG PET/MR uptake in BAT. Identification of a new molecules related to BAT activity may create a new target for obesity treatment.

Applied Molecular-Based Quality Control of Biobanked Samples for Multi-Omics Approach.

Biobanks are vital for high-throughput translational research, but the rapid development of novel molecular techniques, especially in omics assays, poses challenges to traditional practices and recommendations. In our study, we used biospecimens from oncological patients in Polish clinics and collaborated with the Indivumed Group. For serum/plasma samples, we monitored hemolysis, controlled RNA extraction, assessed cDNA library quality and quantity, and verified NGS raw data. Tissue samples underwent pathologic evaluation to confirm histology and determine tumor content. Molecular quality control measures included evaluating the RNA integrity number, assessing cDNA library quality and quantity, and analyzing NGS raw data. Our study yielded the creation of distinct workflows for conducting preanalytical quality control of serum/plasma and fresh-frozen tissue samples. These workflows offer customization options to suit the capabilities of different biobanking entities. In order to ensure the appropriateness of biospecimens for advanced research applications, we introduced molecular-based quality control methods that align with the demands of high-throughput assays. The novelty of proposed workflows, rooted in innovative molecular techniques, lies in the integration of these QC methods into a comprehensive schema specifically designed for high-throughput research applications.

A comparison of different machine-learning techniques for the selection of a panel of metabolites allowing early detection of brain tumors.

Metabolomics combined with machine learning methods (MLMs), is a powerful tool for searching novel diagnostic panels. This study was intended to use targeted plasma metabolomics and advanced MLMs to develop strategies for diagnosing brain tumors. Measurement of 188 metabolites was performed on plasma samples collected from 95 patients with gliomas (grade I-IV), 70 with meningioma, and 71 healthy individuals as a control group. Four predictive models to diagnose glioma were prepared using 10 MLMs and a conventional approach. Based on the cross-validation results of the created models, the F1-scores were calculated, then obtained values were compared. Subsequently, the best algorithm was applied to perform five comparisons involving gliomas, meningiomas, and controls. The best results were obtained using the newly developed hybrid evolutionary heterogeneous decision tree (EvoHDTree) algorithm, which was validated using Leave-One-Out Cross-Validation, resulting in an F1-score for all comparisons in the range of 0.476-0.948 and the area under the ROC curves ranging from 0.660 to 0.873. Brain tumor diagnostic panels were constructed with unique metabolites, which reduces the likelihood of misdiagnosis. This study proposes a novel interdisciplinary method for brain tumor diagnosis based on metabolomics and EvoHDTree, exhibiting significant predictive coefficients.

Extent of interocular (a)symmetry based on the metabolomic profile of human aqueous humor.

Aims: Interocular comparison of the metabolomic signature of aqueous humor (AH) was performed. The aim of the study was to quantitatively evaluate the symmetry in concentrations of various metabolites belonging to different categories. Methods: The study included AH samples from 23 patients, 74.17 ± 11.52 years old, undergoing simultaneous bilateral cataract surgery at the Ophthalmology Department of the Medical University of Bialystok, Poland. Liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS)-based targeted metabolomics and lipidomics analyses of AH samples were performed using the AbsoluteIDQ® p180 kit. Out of 188 metabolites available in the kit, 67 were measured in the majority (>70%) of the samples: 21/21 amino acids, 10/22 biogenic amines, 9/40 acylcarnitines, 0/14 lysophosphatidylcholines, 21/76 phosphatidylcholines, 5/15 sphingolipids, and 1/1sum of hexoses. Results: The comparison of both eyes revealed that the concentrations of metabolites did not differ significantly (p < 0.05) except for taurine (p = 0.037). There was moderate-to-strong positive interocular correlation (r > 0.5) between most metabolites regarding concentration. This was confirmed by the high intraclass correlation coefficient (ICC) values of different levels, which varied for the different metabolites. However, there were exceptions. Correlations were not significant for 2 acylcarnitines (tiglylcarnitine and decadienylcarnitine) and 3 glycerophospholipids (PC aa C32:3, PC aa C40:2, and PC aa C40:5). Conclusion: With a few exceptions, a single eye was found to be representative of the fellow eye in terms of the concentration of most of the analyzed metabolites. The degree of intraindividual variability in the AH of fellow eyes differs for particular metabolites/metabolite categories.

Metabolomics Analysis of Aqueous Humor Based on Liquid Chromatography-Mass Spectrometry.

Aqueous humor (AH) is a transparent fluid that fills the anterior segment of the eye. The composition and level of metabolites in AH are important for understanding its physiology and changes caused by the occurrence of eye disease. A simple method for the preparation and analysis of AH samples was developed using the liquid chromatography-quadrupole time-of-flight mass spectrometry (LC-QTOF-MS) technique. The analyses were performed using two types of chromatography: reversed-phase liquid chromatography-mass spectrometry (LC-RP-MS) and hydrophilic interaction liquid chromatography-mass spectrometry (LC-HILIC-MS), in the sample prepared by one protocol.

Exploration of oxidized phosphocholine profile in non-small-cell lung cancer.

Introduction: Lung cancer is one of the most frequently studied types of cancer and represents the most common and lethal neoplasm. Our previous research on non-small cell lung cancer (NSCLC) has revealed deep lipid profile reprogramming and redox status disruption in cancer patients. Lung cell membranes are rich in phospholipids that are susceptible to oxidation, leading to the formation of bioactive oxidized phosphatidylcholines (oxPCs). Persistent and elevated levels of oxPCs have been shown to induce chronic inflammation, leading to detrimental effects. However, recent reports suggest that certain oxPCs possess anti-inflammatory, pro-survival, and endothelial barrier-protective properties. Thus, we aimed to measure the levels of oxPCs in NSCLC patients and investigate their potential role in lung cancer. Methods: To explore the oxPCs profiles in lung cancer, we performed in-depth, multi-level metabolomic analyses of nearly 350 plasma and lung tissue samples from 200 patients with NSCLC, including adenocarcinoma (ADC) and squamous cell carcinoma (SCC), the two most prevalent NSCLC subtypes and COPD patients as a control group. First, we performed oxPC profiling of plasma samples. Second, we analyzed tumor and non-cancerous lung tissues collected during the surgical removal of NSCLC tumors. Because of tumor tissue heterogeneity, subsequent analyses covered the surrounding healthy tissue and peripheral and central tumors. To assess whether the observed phenotypic changes in the patients were associated with measured oxPC levels, metabolomics data were augmented with data from medical records. Results: We observed a predominance of long-chain oxPCs in plasma samples and of short-chain oxPCs in tissue samples from patients with NSCLC. The highest concentration of oxPCs was observed in the central tumor region. ADC patients showed higher levels of oxPCs compared to the control group, than patients with SCC. Conclusion: The detrimental effects associated with the accumulation of short-chain oxPCs suggest that these molecules may have greater therapeutic utility than diagnostic value, especially given that elevated oxPC levels are a hallmark of multiple types of cancer.

Optimization of a GC-MS method for the profiling of microbiota-dependent metabolites in blood samples: An application to type 2 diabetes and prediabetes.

Changes in serum or plasma metabolome may reflect gut microbiota dysbiosis, which is also known to occur in patients with prediabetes and type 2 diabetes (T2DM). Thus, developing a robust method for the analysis of microbiota-dependent metabolites (MDMs) is an important issue. Gas chromatography with mass spectrometry (GC-MS) is a powerful approach enabling detection of a wide range of MDMs in biofluid samples with good repeatability and reproducibility, but requires selection of a suitable solvents and conditions. For this reason, we conducted for the first time the study in which, we demonstrated an optimisation of samples preparation steps for the measurement of 75 MDMs in two matrices. Different solvents or mixtures of solvents for MDMs extraction, various concentrations and volumes of derivatizing reagents as well as temperature programs at methoxymation and silylation step, were tested. The stability, repeatability and reproducibility of the 75 MDMs measurement were assessed by determining the relative standard deviation (RSD). Finally, we used the developed method to analyse serum samples from 18 prediabetic (PreDiab group) and 24 T2DM patients (T2DM group) from our 1000PLUS cohort. The study groups were homogeneous and did not differ in age and body mass index. To select statistically significant metabolites, T2DM vs. PreDiab comparison was performed using multivariate statistics. Our experiment revealed changes in 18 MDMs belonging to different classes of compounds, and seven of them, based on the SVM classification model, were selected as a panel of potential biomarkers, able to distinguish between patients with T2DM and prediabetes.

The Beneficial Effect of Cinnamon and Red Capsicum Intake on Postprandial Changes in Plasma Metabolites Evoked by a High-Carbohydrate Meal in Men with Overweight/Obesity.

The relationship of high-carbohydrate (HC) meal intake to metabolic syndrome is still not fully explained. Metabolomics has the potential to indicate metabolic pathways altered by HC meals, which may improve our knowledge regarding the mechanisms by which HC meals may contribute to metabolic syndrome development. The fasting and postprandial metabolic response to HC or normo-carbohydrate (NC) meals with/without cinnamon + capsicum intake was evaluated using untargeted metabolomics and compared between normal-weight (NW) and overweight/obese (OW/OB) healthy men. Healthy male participants (age-matched) were divided into two groups (12 subjects per group). One was composed of men with normal weight (NW) and the other of men with overweight/obesity (OW/OB). On separate visits (with 2-3 week intervals), the participants received standardized HC or NC meals (89% or 45% carbohydrates, respectively). Fasting (0 min) and postprandial (30, 60, 120, 180 min) blood were collected for untargeted plasma metabolomics. Based on each metabolic feature's intensity change in time, the area under the curve (AUC) was calculated. Obtained AUCs were analyzed using multivariate statistics. Several metabolic pathways were found dysregulated after an HC meal in people from the OW/OB group but not the NW group. The consumption of HC meals by people with overweight/obesity led to a substantial increase in AUC, mainly for metabolites belonging to phospholipids and fatty acid amides. The opposite was observed for selected sphingolipids. The intake of cinnamon and capsicum normalized the concentration of selected altered metabolites induced by the intake of HC meals. A HC meal may induce an unfavourable postprandial metabolic response in individuals with overweight/obesity, and such persons should avoid HC meals.

Optimization of capillary electrophoresis coupled to negative mode electrospray ionization-mass spectrometry using polyvinyl alcohol coated capillaries. Application to a study on non-small cell lung cancer.

Despite recent developments in separation techniques, the analysis of relatively small highly polar negatively charged analytes (e.g. small organic acids, phosphorylated sugars, and underivatized amino acids) remains challenging. Capillary electrophoresis coupled to mass spectrometry (CE-MS) has been included in the untargeted metabolomics toolbox, although mostly in positive polarity. The aim of this study was to assess the use of CE-MS to analyze highly polar and negatively charged metabolites at physiological levels without the need for derivatization. After a preliminary selection, conditions regarding CE (buffers, applied potential, injection time and applied pressure), electrospray parameters (sheath liquid flow, temperature and drying gas flow, nebulizer, and capillary voltage), and fragmentor voltage were optimized using a capillary coated with polyvinyl alcohol (PVA) for the metabolic profiling of anionic compounds compared to fused silica as the reference capillary. In addition, a database of 240 metabolites with two relative migration times (RMT) obtained against methionine sulfone and 2-morpholinoethanesulfonic acid (MES) as internal standards (IS) has been compiled. Finally, the optimized method has been used to characterize the metabolic profile of blood plasma in patients with non-small cell lung cancer (NSCLC). The identified compounds are mostly amino acids and their derivatives, carboxylic acids and organic compounds from the TCA cycle, and sugars and their phosphoderivates. In addition, we performed a comparative study to find significant differences between non-small cell lung cancer (NSCLC) vs non-cancer individuals, and squamous cell carcinoma (SCC) and adenocarcinoma (ADC) vs non-cancer individuals, respectively, searching for differences between the various types of NSCLC.