Metabolites最新文献

Our recent findings revealed that human adipose tissues (AT)-derived extracellular vesicles (adiposomes) vary in cargo among obese and lean individuals. The main objective of this study was to investigate the adiposomal lipid profiles and their correlation with cardiometabolic risk factors. AT samples were collected from obese subjects and lean controls and analyzed for their characteristics and lipid content. In addition, we measured the correlation between adiposomal lipid profiles and body composition, glucose and lipid metabolic profiles, brachial artery vasoreactivity, AT arteriolar flow-induced dilation, and circulating markers such as IL-6, C-reactive protein, and nitric oxide (NO). Compared to lean controls, adiposomes isolated from obese subjects were higher in number after normalization to AT volume. The two major lipid classes differentially expressed were lysophosphatidylcholine/phosphatidylcholine (LPC/PC) and ceramides (Cer). All lipids in the LPC/PC class were several-fold lower in adiposomes from obese subjects compared to lean controls, on top of which were PC 18:2, PC 18:1, and PC 36:3. Most ceramides were markedly upregulated in the obese group, especially Cer d37:0, Cer d18:0, and Cer d39:0. Regression analyses revealed associations between adiposomal lipid profiles and several cardiometabolic risk factors such as body mass index (BMI), fat percentage, insulin resistance, arteriolar and brachial artery vasoreactivity, NO bioavailability, and high-density lipoproteins (HDL-C). We conclude that the ability of adiposomes from obese subjects to disrupt cardiometabolic function could be partly attributed to the dysregulated lipid cargo.

Currently, the clinical cure rate for primary liver cancer remains low. Effective screening and early diagnosis of hepatocellular carcinoma (HCC) remain clinical challenges. Exosomes are intimately associated with tumor development and their contents have the potential to serve as highly sensitive tumor-specific markers. A comprehensive untargeted metabolomics study was conducted using exosome samples extracted from the serum of 48 subjects (36 HCC patients and 12 healthy controls) via a commercial kit. An ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) strategy was used to identify the metabolic compounds. A total of 18 differential metabolites were identified using the non-targeted metabolomics approach of UPLC-QTOF-MS/MS. Pathway analysis revealed significant alterations in the arachidonic acid metabolism, linoleic acid metabolism, and unsaturated fatty acid metabolism pathways. ROC analysis indicated that three metabolites with AUC values exceeding 0.900 were selected as potential biomarkers: caprylic acid and linoleic acid were upregulated in the HCC group, whereas pentadecanoic acid was downregulated. Linoleic acid, caprylic acid, and pentadecanoic acid are potential biomarkers for diagnosing HCC. The significant alterations in these three metabolic pathways offer new insights into the mechanisms underlying HCC formation and progression.

Metabolomics has been used extensively to capture the exposome. We investigated whether prospectively measured metabolites provided predictive power beyond well-established risk factors among 758 women with adjudicated cancers [n = 577 breast (BC) and n = 181 colorectal (CRC)] and n = 758 controls with available specimens (collected mean 7.2 years prior to diagnosis) in the Women's Health Initiative Bone Mineral Density subcohort. Fasting samples were analyzed by LC-MS/MS and lipidomics in serum, plus GC-MS and NMR in 24 h urine. For feature selection, we applied LASSO regression and Super Learner algorithms. Prediction models were subsequently derived using logistic regression and Super Learner procedures, with performance assessed using cross-validation (CV). For BC, metabolites did not increase predictive performance over established risk factors (CV-AUCs~0.57). For CRC, prediction increased with the addition of metabolites (median CV-AUC across platforms increased from ~0.54 to ~0.60). Metabolites related to energy metabolism: adenosine, 2-hydroxyglutarate, N-acetyl-glycine, taurine, threonine, LPC (FA20:3), acetate, and glycerate; protein metabolism: histidine, leucic acid, isoleucine, N-acetyl-glutamate, allantoin, N-acetyl-neuraminate, hydroxyproline, and uracil; and dietary/microbial metabolites: myo-inositol, trimethylamine-N-oxide, and 7-methylguanine, consistently contributed to CRC prediction. Energy metabolism may play a key role in the development of CRC and may be evident prior to disease development.

Identification of features with high levels of confidence in liquid chromatography-mass spectrometry (LC-MS) lipidomics research is an essential part of biomarker discovery, but existing software platforms can give inconsistent results, even from identical spectral data. This poses a clear challenge for reproducibility in biomarker identification. In this work, we illustrate the reproducibility gap for two open-access lipidomics platforms, MS DIAL and Lipostar, finding just 14.0% identification agreement when analyzing identical LC-MS spectra using default settings. Whilst the software platforms performed more consistently using fragmentation data, agreement was still only 36.1% for MS² spectra. This highlights the critical importance of validation across positive and negative LC-MS modes, as well as the manual curation of spectra and lipidomics software outputs, in order to reduce identification errors caused by closely related lipids and co-elution issues. This curation process can be supplemented by data-driven outlier detection in assessing spectral outputs, which is demonstrated here using a novel machine learning approach based on support vector machine regression combined with leave-one-out cross-validation. These steps are essential to reduce the frequency of false positive identifications and close the reproducibility gap, including between software platforms, which, for downstream users such as bioinformaticians and clinicians, can be an underappreciated source of biomarker identification errors.

An increase in dietary protein intake (DPI) carries a risk with respect to increased sodium intake, which further leads to the development of cardiovascular morbidity in peritoneal dialysis (PD) patients. Dialytic (DSR) and urinary sodium removal (USR) are potential indicators of sodium intake. In this single-center cross-sectional study with 60 prevalent PD patients, we analyze the correlation of DPI with sodium intake and the association between residual renal function (RRF) and comorbidity grade, expressed as the Davies score with sodium removal and protein metabolism indices such as normalized protein catabolic rate (nPCR) and lean body mass (LBM). The value of RRF < 2 mL/min/1.73 m² is significantly associated with lower USR (p = 0.000) and lower %LBM (p < 0.001). The greatest USR is detected in patients with low Davies comorbidity grade (p = 0.018). Compared to patients with DPI < 0.8 g/kg/day, patients with DPI > 0.8 g/kg/day have a greater sodium intake (3.69 ± 0.71 vs. 2.94 ± 0.86; p < 0.018) and a greater nPCR (p < 0.001). Protein intake is significantly correlated with sodium intake (p = 0.041), but not with total sodium removal (TSR). A strong correlation is observed between sodium intake and TSR (p = 0.000), although single TSR values are not the same as the corresponding sodium intake values. An increasing protein intake implies the necessity to determine both sodium intake and sodium removal. Preservation of RRF has a beneficial role not just in sodium removal, but also in the increase of LBM.

Ophiocordyceps sinensis, a medicinal fungus utilized in traditional Chinese medicine, exhibits a range of biological activities and pharmacological functions. In this study, we determined the amino acid composition of 94 amino acids in Ophiocordyceps sinensis using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Fresh samples of Ophiocordyceps sinensis were analyzed under three different drying methods: vacuum freeze drying (DG), oven drying (HG), and air drying (YG). This investigation aims to assess the effects of these drying methods on the content and quality of amino acid metabolites in Ophiocordyceps sinensis. Principal component analysis (PCA) and hierarchical cluster analysis (HCA) were employed for sample classification and the identification of differentially accumulated metabolites (DAMs). The results revealed the detection of 79 amino acid metabolites, which included elevated levels of oxidized L-glutamic acid, L-glutamic acid, and glutathione. Differential amino acid metabolites that met the criteria of fold change (|FC|) ≥ 2, p-value (p) ≤ 0.5, and variable importance in projection (VIP) ≥ 1 were analyzed. Significant differences in 48 amino acid metabolites between the groups were primarily related to protein synthesis. According to the KEGG analysis, all three comparison samples exhibited significant enrichment in several pathways. These pathways included the interaction of neuroactive ligands with receptors, the metabolism of cysteine and methionine, and the biosynthesis of plant hormones. The variations in amino acid metabolite levels observed across the three drying methods may be attributed to the degradation of proteins or amino acid metabolites, influenced by several factors, including temperature, enzyme activity, and moisture content. Additionally, Maillard and oxidative reactions involving substances such as amino acids, sugars, and oxygen may also play a significant role. This study demonstrates that various drying methods significantly influence the amino acid metabolite content of Ophiocordyceps sinensis. Therefore, the selection of drying methods should be tailored to meet specific requirements. This research provides important insights into the metabolite composition of Ophiocordyceps sinensis under different drying techniques, thereby contributing to a more comprehensive understanding of its nutritional and therapeutic properties.

Adenosine triphosphate (ATP) has a high intracellular millimolar concentration (ca. 2.4 mM) throughout the phylogenetic spectrum of eukaryotes, archaea, and prokaryotes. In addition, the function of ATP as a hydrotrope in the prevention of protein aggregation and maintenance of protein solubilization is essential to cellular, tissue, and organ homeostasis. The ³¹P spectral modulus (PSM) is a measure of the health status of cell, tissue, and organ systems, as well as of ATP, and it is based on in vivo ³¹P nuclear magnetic resonance (³¹P NMR) spectra. The PSM is calculated by dividing the area of the ³¹P NMR integral curve representing the high-energy phosphates by that of the low-energy phosphates. Unlike the difficulties encountered in measuring organophosphates such as ATP or any other phosphorylated metabolites in a conventional ³¹P NMR spectrum or in processed tissue samples, in vivo PSM measurements are possible with NMR surface-coil technology. The PSM does not rely on the resolution of individual metabolite signals but uses the total area derived from each of the NMR integral curves of the above-described spectral regions. Calculation is based on a simple ratio of the high- and low-energy phosphate bands, which are conveniently arranged in the high- and low-field portions of the ³¹P NMR spectrum. In practice, there is essentially no signal overlap between these two regions, with the dividing point being ca. -3 δ. ATP is the principal contributor to the maintenance of an elevated PSM that is typically observed in healthy systems. The purpose of this study is to demonstrate that (1) in general, the higher the metabolic activity, the higher the ³¹P spectral modulus, and (2) the modulus calculation does not require highly resolved ³¹P spectral signals and thus can even be used with reduced signal-to-noise spectra such as those detected as a result of in vivo analyses or those that may be obtained during a clinical MRI examination. With increasing metabolic stress or maturation of metabolic disease in cells, tissues, or organ systems, the PSM index declines; alternatively, with decreasing stress or resolution of disease states, the PSM increases. The PSM can serve to monitor normal homeostasis as a diagnostic tool and may be used to monitor disease processes with and without interventional treatment.

The prevalence of non-obese individuals with insulin resistance (IR) and type 2 diabetes (T2D) is increasing worldwide. This study investigates the metabolic signature of phospholipid-associated metabolites in non-obese individuals with IR and T2D, aiming to identify potential biomarkers for these metabolic disorders. The study cohort included non-obese individuals from the Qatar Biobank categorized into three groups: insulin sensitive, insulin resistant, and patients with T2D. Each group comprised 236 participants, totaling 708 individuals. Metabolomic profiling was conducted using high-resolution mass spectrometry, and statistical analyses were performed to identify metabolites associated with the progression from IS to IR and T2D. The study observed significant alterations in specific phospholipid metabolites across the IS, IR, and T2D groups. Choline phosphate, glycerophosphoethanolamine, choline, glycerophosphorylcholine (GPC), and trimethylamine N-oxide showed significant changes correlated with disease progression. A distinct metabolic signature in non-obese individuals with IR and T2D was characterized by shifts in choline metabolism, including decreased levels of choline and trimethylamine N-oxide and increased levels of phosphatidylcholines, phosphatidylethanolamines, and their degradation products. These findings suggest that alterations in choline metabolism may play a critical role in the development of glucose intolerance and insulin resistance. Targeting choline metabolism could offer potential therapeutic strategies for treating T2D. Further research is needed to validate these biomarkers and understand their functional significance in the pathogenesis of IR and T2D in non-obese populations.

Hemorheological factors may show arterio-venous differences. Alterations in acid-base and metabolic parameters may also influence these factors. However, little is known about changes in micro-rheological parameters during abdominal surgery, influencing splanchnic circulation. In anesthetized pigs, the external jugular vein, femoral artery and vein were cannulated unilaterally, and paramedian laparotomy was performed. In the anastomosis group, after resecting a bowel segment, end-to-end jejuno-jejunostomy was completed. Blood samples (from cannulas and by puncturing the portal vein) were taken before and after the intervention. Hematological, acid-base and blood gas parameters, metabolites, red blood cell (RBC) deformability and aggregation were determined. The highest hematocrit was found in portal blood, increasing further by the end of operation. A significant pH decrease was seen, and portal blood showed the highest lactate and creatinine concentration. The highest RBC aggregation values were found in arterial, the lowest in renal venous blood. The RBC aggregation increased with higher lactate concentration and lower pH. Osmotic gradient deformability declined, with the lowest values in portal and renal venous samples. In conclusion, micro-rheological parameters showed arterio-venous and porto-renal venous differences, influenced by oxygenation level, pH and lactate concentration. The intestinal anastomosis operation caused an immediate micro-rheological deterioration with portal venous dominancy in this experiment.

In recent years, afforestation has been conducted in China's hot and dry valleys. However, there is still a paucity of knowledge regarding the performance of tree species in these semi-arid regions, particularly with regard to interspecies differences. The present study compares the growth and metabolome characteristics of two widely used cypress species, namely Cupressus chengiana and Platycladus orientalis, grown at two sites with distinct climate conditions in the hot and dry Minjiang Valley in southwestern China. The findings indicate that C. chengiana trees exhibit superior growth rates compared to P. orientalis trees at both study sites. In comparison to P. orientalis trees, C. chengiana trees demonstrated a greater tendency to close their stomata in order to prevent water loss at the hotter and drier site, Llianghekou (LHK). Additionally, C. chengiana trees exhibited significantly lower hydrogen peroxide levels than P. orientalis trees, either due to lower production and/or higher scavenging of reactive oxygen species. C. chengiana trees accumulated soluble sugars as well as sugar derivatives, particularly those involved in sucrose and galactose metabolisms under stressful conditions. The species-specific differences were also reflected in metabolites involved in the tricarboxylic acid cycle, nitrogen, and secondary metabolisms. The metabolome profiles of the two species appeared to be influenced by the prevailing climatic conditions. It appeared that the trees at the drier and hotter site, LHK, were capable of efficient nitrogen uptake from the soil despite the low soil nitrogen concentration. This study is the first to compare the growth performance and metabolic profiles of two widely used tree species with high resistance to adverse conditions. In addition to the species-specific differences and adaptations to different sites, the present study also provides insights into potential management strategies to alleviate abiotic stress, particularly with regard to nitrogen nutrients, in the context of climate change.