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Hypertension is one component of metabolic syndrome (MetS). Here, the study evaluated hypertension‐associated metabolites in relation to other MetS components. Fasting plasma samples were collected from 22 hypertensive and 63 normotensive subjects for non‐targeted metabolomics. Compared with normotensive subjects, hypertensive patients were more diabetic (6.3% vs. 36.4%) and had dyslipidemia (27.0% vs. 63.6%) (both p < .05). By non‐targeted metabolomics, 758 metabolites in 22 classes were identified and 56 were differentially regulated between hypertensive and normotensive groups. Amongst these 56 metabolites, receiver operating characteristic analysis showed that 14 had an area under the curve above 0.6. Multivariate‐adjusted logistic regression analysis demonstrated that per one‐fold increase of L‐glutmatic acid, L‐cystine, (9S,10E,12Z,15Z)‐9‐Hydroxy‐10,12,15‐octadecatrienoic acid, deoxyribose 5‐phosphate, and falcarinolone, the odds ratios were 3.64, 4.61, 0.26, 0.26, and 0.37 for having the risk of hypertension, respectively. Of five metabolites, by Spearman's correlation analysis, only L‐glutmatic acid and L‐cystine levels were positively associated with systolic and diastolic blood pressure (all p < .05). Spearman's correlation analysis further revealed that L‐glutmatic acid levels were positively correlated with to body mass index (BMI), fasting blood glucose, and serum triglyceride but negatively associated with HDL‐c (all p < .05) whereas L‐cystine levels were not related to any of these components (p ≥ .13). Multivariate‐adjusted linear regression analysis confirmed the positive correlation between L‐cystine levels and systolic or diastolic blood pressure (β = 2.66 for SBP; β = 2.50 for DBP; both p < .05). In conclusion, L‐cystine could be a potent metabolite for increased risk of hypertension.

Background: Clonorchiasis is an important foodborne parasitic disease. However, eggs of Clonorchis sinensis (C. sinensis) cannot be detected in feces during biliary obstruction. Moreover, many diseases can cause biliary obstruction, such as gallstones, adenocarcinoma, cholangiocarcinoma and Ascaris lumbricoides infection. Therefore, it is of great significance to distinguish between patients of biliary obstruction and biliary obstruction with C. sinensis infection.Methods: A total of 48 biliary obstruction patients were enrolled, including 23 infected with C. sinensis (C. sinensis) (OB+C.s) and 25 non-infected subjects (OB). The bile samples were collected by endoscopic retrograde cholangiopancreatography and analyzed using ultra-high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC-QTOF MS). Additionally, multivariate statistical analysis methods were employed to identify differential metabolites. Next, bile amino acid levels were determined by targeted metabolomics analysis.Result: A total of 146 and 132 significant metabolites were identified in electrospray ionization (ESI)+ and ESI− modes, respectively. The levels of amino acids (asparagine, glutamate, ornithine) and polyamines (spermidine and spermine) were significantly changed. Targeted analysis showed that the levels of amino acids (such as L-arginine, L-glutamine, L-lysine, L-propionic, and L-tyrosine) were lower in OB+C.s patients compared to those in OB patients. Marked metabolic pathways were involved in “Glutathione metabolism”, “Caffeine metabolism”, “Alanine, aspartate and glutamate metabolism”, “Arginine and proline metabolism”, “Purine metabolism”, “Beta-Alanine metabolism”, and “D-glutamine and D-glutamate metabolism”.Conclusion: These results show that there were significant differences between OB+C.s and OB patients, especially in amino acids. The metabolic signature and perturbations in metabolic pathways may help to better distinguish OB+C.s and OB patients.

Trichosanthis Radix (TR) is one of the most severely sulfur-fumigated herbs in the market, whose transformation mechanism of chemical compositions and sulfur-fumigation markers of TR have not been clarified. To excavate characteristic sulfur-fumigation markers of TR samples, this study brings up a practical protocol using both ultra-performance liquid chromatography/quadrupole time-of-flight-mass spectrum (UPLC-ESI-QTOF-MS/MS)-based non-targeted metabolomics and ultra-performance liquid chromatography/electrospray ionization/quadrupole multiple-stage linear ion-trap mass spectrum (UPLC-ESI-QTRAP-MS/MS)-based widely targeted metabolomics. The results of study demonstrated that five characteristic markers are sulfur-containing components, which were identified as -Hydroxybenzyl hydrogen sulfite, cucurbitacin D sulfite I, cucurbitacin D sulfite II, cucurbitacin B sulfite I, and cucurbitacin B sulfite II, respectively. Additionally, cucurbitacin B and D were also filtered and identified as the characteristic sulfur-fumigation markers. Meanwhile, the different sulfur-fumigation extent of TR samples was tested by chemical transformations analysis and sulfur dioxide residues test. Further, 58.16% (139 of 239) of the differential metabolites content significantly reduced in sulfur-fumigated TR samples. Besides, 20 kinds of non-sulfur marker metabolites were tested to evaluate the quality of TR samples before and after sulfur fumigation, predominantly including phenolic acids, amino acids, lipids and nucleotides. Taking TR as an example, this work provides a comprehensive practical protocol for the quality supervision of sulfur-fumigation herbs.

In this study, the non‐targeted large‐scale plant metabolomics (UPLC‐Q‐Orbitrap‐MS) was performed for the comparison of chemical profiling of the leaves, barks, flowers, peels, pulps, and seeds of Clausena lansium (Lour.) Skeels (called “wampee”). A total of 364 metabolites were identified, and 62 potential biomarkers were selected by the multivariate statistical analysis. Hierarchical cluster analysis suggested that the selected biomarkers were significant differential metabolites among various parts of wampee. Metabolic pathway analysis showed a significant enrichment of the “Flavone and flavonol synthesis” and “Isoquinoline alkaloid biosynthesis” pathway. This study provides important information for the isolation and identification of functional components from different tissues of wampee and the metabolic biosynthesis pathway elucidation in detail. The comparison of chemical profiling of the leaves, barks, flowers, peels, pulps, and seeds of wampee was investigated. This study provides important information for the isolation and identification of functional components from different tissues of wampee and the metabolic biosynthesis pathway elucidation in detail.

In targeted metabolomic analysis using liquid chromatography–multiple reaction monitoring–mass spectrometry (LC-MRM-MS), hundreds of MRMs are performed in a single run, yielding a large dataset containing thousands of chromatographic peaks. Automation tools for processing large MRM datasets have been reported, but a visual review of chromatograms is still critical, as real samples with biological matrices often cause complex chromatographic patterns owing to non-specific, insufficiently separated, isomeric, and isotopic components. Herein, we report the development of new software, TRACES, a lightweight chromatogram browser for MRM-based targeted LC-MS analysis. TRACES provides rapid access to all MRM chromatograms in a dataset, allowing users to start ad hoc data browsing without preparations such as loading compound libraries. As a special function of the software, we implemented a chromatogram-level deisotoping function that facilitates the identification of regions potentially affected by isotopic signals. Using MRM libraries containing precursor and product formulae, the algorithm reveals all possible isotopic interferences in the dataset and generates deisotoped chromatograms. To validate the deisotoping function in real applications, we analyzed mouse tissue phospholipids in which isotopic interference by molecules with different fatty-acyl unsaturation levels is known. TRACES successfully removed isotopic signals within the MRM chromatograms, helping users avoid inappropriate regions for integration.

Chemotherapy combined with checkpoint blockade antibodies targeting programmed cell death protein (PD‐1) has achieved remarkable success in non‐small cell lung cancer. However, few patients benefit from long‐term treatment. Therefore, biomarkers capable of guiding the optimal therapeutic selection and reducing unnecessary toxicity are of pressing importance. In our research, we gathered serial blood samples from two groups of non‐small cell lung cancer patients: 49 patients received a combination of therapies, and 34 patients went under chemotherapy alone. Utilizing non‐targeted metabolomic analysis, we examined different metabolites’ disparity. Among the lot, L‐phenylalanine emerged as a significant prognostic marker in the combination treatment of non‐small cell lung cancer patients, interestingly absent in patients under sole chemotherapy. The reduced ratio of L‐phenylalanine concentration (two‐cycle treatment vs. pre‐treatment) was associated with improved progression‐free survival (hazard ratio = 1.8000, 95% confidence interval: 0.8566‒3.7820, p < 0.0001) and overall survival (hazard ratio = 1.583, 95% confidence interval: 0.7416‒3.3800, p < 0.005). We further recruited two validation cohorts (cohort 1: 40 patients and cohort 2: 30 patients) to validate the sensitivity and specificity of L‐phenylalanine prediction. Our results demonstrate that a model based on L‐phenylalanine variations could serve as an early risk‐assessment tool for non‐small cell lung cancer patients undergoing treatment, potentially facilitating strategic clinical decision‐making. Liu et al. studied serum from patients with non‐small cell lung cancer before, during, and after treatment with anti‐programmed cell death protein‐1 plus chemotherapy, and revealed the metabolic heterogeneity of responders and non‐responders. The combination of clinical data profiling and change of L‐phenylalanine concentration collected pre‐ and post‐treatment presented a strong predictor for response to immunotherapy in a minimally invasive manner.

Non-targeted analysis by high-resolution mass spectrometry (HRMS) is an essential discovery tool in metabolomics. To date, standardization and validation remain a challenge. Community-wide accepted cost-effective benchmark materials are lacking. In this work, we propose yeast (Pichia pastoris) extracts derived from fully controlled fermentations for this purpose. We established an open-source metabolite library of >200 identified metabolites based on compound identification by accurate mass, matching retention times, and MS/MS, as well as a comprehensive literature search. The library includes metabolites from the classes of (1) organic acids and derivatives (2) nucleosides, nucleotides, and analogs, (3) lipids and lipid-like molecules, (4) organic oxygen compounds, (5) organoheterocyclic compounds, (6) organic nitrogen compounds, and (7) benzoids at expected concentrations ranges of sub-nM to µM. As yeast is a eukaryotic organism, key regulatory elements are highly conserved between yeast and all annotated metabolites were also reported in the human metabolome database (HMDB). Orthogonal state-of-the-art reversed-phase (RP-) and hydrophilic interaction chromatography mass spectrometry (HILIC-MS) non-targeted analysis and authentic standards revealed that 104 out of the 206 confirmed metabolites were reproducibly recovered and stable over the course of three years when stored at −80 °C. Overall, 67 out of these 104 metabolites were identified with comparably stable areas over all three yeast fermentation and are the ideal starting point for benchmarking experiments. The provided yeast benchmark material enabled not only to test for the chemical space and coverage upon method implementation and developments but also allowed in-house routines for instrumental performance tests. Transferring the quality control strategy of proteomics workflows based on the number of protein identification in HeLa extracts, metabolite IDs in the yeast benchmarking material can be used as metabolomics quality control. Finally, the benchmark material opens new avenues for batch-to-batch corrections in large-scale non-targeted metabolomics studies.

Metabolites in human biofluids document the physiological status of individuals. We conducted comprehensive, non‐targeted, non‐invasive metabolomic analysis of urine from 27 healthy human subjects, comprising 13 young adults (30 ± 3 years) and 14 seniors (76 ± 4 years). Quantitative analysis of 99 metabolites revealed 55 that displayed significant differences in abundance between the two groups. Forty‐four did not show a statistically significant relationship with age. These include 13 standard amino acids, 5 methylated, 4 acetylated, and 9 other amino acids, 6 nucleosides, nucleobases, and derivatives, 4 sugar derivatives, 5 sugar phosphates, 4 carnitines, 2 hydroxybutyrates, 1 choline, and 1 ethanolamine derivative, and glutathione disulfide. Abundances of 53 compounds decreased, while 2 (glutathione disulfide, myo‐inositol) increased in elderly people. The great majority of age‐linked markers were highly correlated with creatinine. In contrast, 44 other urinary metabolites, including urate, carnitine, hippurate, and betaine, were not age‐linked, neither declining nor increasing in elderly subjects. As metabolite profiles of urine and blood are quite different, age‐related information in urine offers additional valuable insights into aging mechanisms of endocrine system. Correlation analysis of urinary metabolites revealed distinctly inter‐related groups of compounds.

Human induced pluripotent stem cells (hiPSCs) possess immense potential as a valuable source for the generation of a wide variety of human cells, yet monitoring the early cell differentiation towards a specific lineage remains challenging. In this study, we employed a non-targeted metabolomic analysis technique to analyze the extracellular metabolites present in samples as small as one microliter. The hiPSCs were subjected to differentiation by initiating culture under the basal medium E6 in combination with chemical inhibitors that have been previously reported to direct differentiation towards the ectodermal lineage such as Wnt/β-catenin and TGF-β kinase/activin receptor, alone or in combination with bFGF, and the inhibition of glycogen kinase 3 (GSK-3), which is commonly used for the diversion of hiPSCs towards mesodermal lineage. At 0 h and 48 h, 117 metabolites were identified, including biologically relevant metabolites such as lactic acid, pyruvic acid, and amino acids. By determining the expression of the pluripotency marker OCT3/4, we were able to correlate the differentiation status of cells with the shifted metabolites. The group of cells undergoing ectodermal differentiation showed a greater reduction in OCT3/4 expression. Moreover, metabolites such as pyruvic acid and kynurenine showed dramatic change under ectodermal differentiation conditions where pyruvic acid consumption increased 1–2-fold, while kynurenine secretion decreased 2-fold. Further metabolite analysis uncovered a group of metabolites specifically associated with ectodermal lineage, highlighting the potential of our findings to determine the characteristics of hiPSCs during cell differentiation, particularly under ectodermal lineage conditions.

Metabolomics is the comprehensive study of small-molecule metabolites. Obtaining a wide coverage of the metabolome is challenging because of the broad range of physicochemical properties of the small molecules. To study the compounds of interest spectroscopic (NMR), spectrometric (MS) and separation techniques (LC, GC, supercritical fluid chromatography, CE) are used. The choice for a given technique is influenced by the sample matrix, the concentration and properties of the metabolites, and the amount of sample. This review discusses the most commonly used analytical techniques for metabolomic studies, including their advantages, drawbacks and some applications.