New insight into primary hyperparathyroidism using untargeted metabolomics.

Primary Hyperparathyroidism (PHPT) is characterized by excessive parathormone (PTH) secretion and disrupted calcium homeostasis. Untargeted metabolomics offers a valuable approach to understanding the complex metabolic alterations associated with different diseases, including PHPT. Plasma untargeted metabolomics was applied to investigate the metabolic profiles of PHPT patients compared to a control group. Two complementary liquid-phase separation techniques were employed to comprehensively explore the metabolic landscape in this retrospective, single-center study. The study comprised 28 female patients diagnosed following the current guidelines of PHPT diagnosis and a group of 30 healthy females as a control group. To evaluate their association with PHPT, we identified changes in plasma metabolic profiles in patients with PHPT compared to the control group. The primary outcome measure included detecting plasma metabolites and discriminating PHPT patients from controls. The study unveiled specific metabolic imbalances that may link L-amino acids with peptic ulcer disease, gamma-glutamyls with oxidative stress, and asymmetric dimethylarginine (ADMA) with cardiovascular complications. Several metabolites, such as gamma-glutamyls, caffeine, sex hormones, carnitine, sphingosine-1-phosphate (S-1-P), and steroids, were connected with reduced bone mineral density (BMD). Metabolic profiling identified distinct metabolic patterns between patients with PHPT and healthy controls. These findings provided valuable insights into the pathophysiology of PHPT.

Matcha alleviates obesity by modulating gut microbiota and its metabolites.

Matcha shows promise for diabetes, obesity, and gut microbiota disorders. Studies suggest a significant link between gut microbiota, metabolites, and obesity. Thus, matcha may have a positive impact on obesity by modulating gut microbiota and metabolites. This study used 16S rDNA sequencing and untargeted metabolomics to examine the cecal contents in mice. By correlation analysis, we explored the potential mechanisms responsible for the positive effects of matcha on obesity. The results indicated that matcha had a mitigating effect on the detrimental impacts of a high-fat diet (HFD) on multiple physiological indicators in mice, including body weight, adipose tissue weight, serum total cholesterol (TC), and low-density lipoprotein (LDL) levels, as well as glucose tolerance. Moreover, it was observed that matcha had an impact on the structural composition of gut microbiota and gut metabolites. Specifically, matcha was able to reverse the alterations in the abundance of certain obesity-improving bacteria, such as Alloprevotella, Ileibacterium, and Rikenella, as well as the abundance of obesity-promoting bacteria Romboutsia, induced by a HFD. Furthermore, matcha can influence the levels of metabolites, including formononetin, glutamic acid, pyroglutamic acid, and taurochenodeoxycholate, within the gastrointestinal tract. Additionally, matcha enhances caffeine metabolism and the HIF-1 signaling pathway in the KEGG pathway. The results of the correlation analysis suggest that formononetin, theobromine, 1,3,7-trimethyluric acid, and Vitamin C displayed negative correlation with both the obesity phenotype and microbiota known to exacerbate obesity, while demonstrating positive correlations with microbiota that alleviated obesity. However, glutamic acid, pyroglutamic acid, and taurochenodeoxycholate had the opposite effect. In conclusion, the impact of matcha on gut metabolites may be attributed to its modulation of the abundance of Alloprevotella, Ileibacterium, Rikenella, and Romboutsia within the gastrointestinal tract, thereby potentially contributing to the amelioration of obesity.

The prognosis and metabolite changes of NSCLC patients receiving first-line immunotherapy combined chemotherapy in different M1c categories according to 9th edition of TNM classification.

BACKGROUND: The 9th edition of the TNM Classification for lung cancer delineates M1c into two subcategories: M1c1 (Multiple extrathoracic lesions within a single organ system) and M1c2 (Multiple extrathoracic lesions involving multiple organ systems). Existing research indicates that patients with lung cancer in stage M1c1 exhibit superior overall survival compared to those in stage M1c2. The primary frontline therapy for patients with advanced non-small cell lung cancer (NSCLC), lacking driver gene mutations, involves the use of immune checkpoint inhibitors (ICIs) combined with chemotherapy. Nevertheless, a dearth of evidence exists regarding potential survival disparities between NSCLC patients with M1c1 and M1c2 undergoing first-line immune-chemotherapy, and reliable biomarkers for predicting treatment outcomes are elusive. Serum metabolic profiles may elucidate distinct prognostic mechanisms, necessitating the identification of divergent metabolites in M1c1 and M1c2 undergoing combination therapy. This study seeks to scrutinize survival discrepancies between various metastatic patterns (M1c1 and M1c2) and pinpoint metabolites associated with treatment outcomes in NSCLC patients undergoing first-line ICIs combined with chemotherapy. METHOD: In this study, 33 NSCLC patients lacking driver gene mutations diagnosed with M1c1, and 22 similarly diagnosed with M1c2 according to the 9th edition of TNM Classification, were enrolled. These patients received first-line PD-1 inhibitor plus chemotherapy. The relationship between metastatic patterns and progression-free survival (PFS) in patients undergoing combination therapy was analyzed using univariate and multivariate Cox regression models. Serum samples were obtained from all patients before treatment initiation for untargeted metabolomics analysis, aiming to identify differential metabolites. RESULTS: In the univariate analysis of PFS, NSCLC patients in M1c1 receiving first-line PD-1 inhibitor plus chemotherapy exhibited an extended PFS (HR = 0.49, 95% CI, 0.27-0.88, p = 0.017). In multivariate PFS analyses, these M1c1 patients receiving first-line PD-1 inhibitor plus chemotherapy also demonstrated prolonged PFS (HR = 0.45, 95% CI, 0.22-0.92, p = 0.028). The serum metabolic profiles of M1c1 and M1c2 undergoing first-line PD-1 inhibitors plus chemotherapy displayed notable distinctions. In comparison to M1c1 patients, M1c2 patients exhibited alterations in various pathways pretreatment, including platelet activation, linoleic acid metabolism, and the VEGF signaling pathway. Diminished levels of lipid-associated metabolites (diacylglycerol, sphingomyelin) were correlated with adverse outcomes. CONCLUSION: NSCLC patients in M1c1, devoid of driver gene mutations, receiving first-line PD-1 inhibitors combined with chemotherapy, experienced superior outcomes compared to M1c2 patients. Moreover, metabolomic profiles strongly correlated with the prognosis of these patients, and M1c2 patients with unfavorable outcomes manifested distinct changes in metabolic pathways before treatment. These changes predominantly involved alterations in lipid metabolism, such as decreased diacylglycerol and sphingomyelin, which may impact tumor migration and invasion.

Anti-bacterial effects, and metabolites derived from bifidobacterial fermentation of an exopolysaccharide of Cs-HK1 medicinal fungus.

This study was to investigate the antibacterial effects and metabolites derived from bifidobacterial fermentation of an exopolysaccharide EPS-LM produced by a medicinal fungus Cordyceps sinensis, Cs-HK1. EPS-LM was a partially purified polysaccharide fraction which was mainly composed of Man, Glc and Gal at 7.31:12.95:1.00 mol ratio with a maximum molecular weight of 360 kDa. After fermentation of EPS-LM in two bifidobacterial cultures, B. breve and B. longum, the culture digesta showed significant antibacterial activities, inhibiting the proliferation and biofilm formation of Escherichia coli. Based on untargeted metabolomic profiling of the digesta, the levels of short chain fatty acids, carboxylic acids, benzenoids and their derivatives were all increased significantly (p < 0.01), which probably contributed to the enhanced antibacterial activity by EPS-LM. Since EPS-LM was only slightly consumed for the bifidobacterial growth, it mainly stimulated the biosynthesis of bioactive metabolites in the bifidobacterial cells. The results also suggested that EPS-LM polysaccharide may have a regulatory function on the bifidobacterial metabolism leading to production of antibacterial metabolites, which may be of significance for further exploration.

Seasonal variations and sensory profiles of oolong tea: Insights from metabolic analysis of Tieguanyin cultivar.

The impact of seasonal variations on the quality of oolong tea products remains a subject of ongoing exploration. This study delves into the intricate relationships between seasonality, metabolites, and sensory characteristics in finished oolong tea products. Metabolomic data from 266 Tieguanyin oolong tea products harvested in both spring and autumn, along with corresponding sensory evaluations, were acquired. Using OPLS-DA and PLS-DA models with UPLC-QToF/MS data, our findings showed that seasonal effects were notably more pronounced in light-scented Tieguanyin products (lightly-roasted) compared to strong-scented products (moderately-roasted). Furthermore, over half of the identified key seasonal discriminant metabolites happened to be crucial for determining the sensory grade. The study marks the first-time recognition of triterpene saponins as critical factors in determining both the harvest season and the sensory grade of oolong tea. These insights deepen our understanding of the interplays between seasonal variations, metabolites, and sensory attributes in oolong tea products.

Combined metabolomics and bioactivity assays kernelby-productsof two native Chinese cherry species: The sources of bioactive nutraceutical compounds.

Cherry kernels are a by-product of cherries that are usually discarded, leading to waste and pollution. In this study, the chemical composition of 21 batches of cherry kernels from two different cherry species was analyzed using untargeted metabolomics. The in vitro antioxidant activity, cellular antioxidant activity, and antiproliferative activity of these kernel extracts were also determined, and a correlation analysis was conducted between differential compounds and biological activity. A total of 49 differential compounds were screened. The kernels of Prunus tomentosa were found to have significantly higher total phenol, total flavonoid content, and biological activity than those of Prunus pseudocerasus (P < 0.05). Correlation analysis showed that flavonoids had the greatest contribution to biological activity. The study suggests that both species of cherry kernel, particularly Prunus tomentosa, could be a potential source of bioactive compounds that could be used in the pharmaceutical, cosmetic, and food industries.

Insights into the effects of anilofos on direct-seeded rice production system through untargeted metabolomics.

Weed infestation is the major biological threat in direct-seeded rice production and can cause significant yield losses. The effective use of herbicides is particularly important in direct-seeded rice production. Anilofos, a pre-emergence herbicide, has been shown to be effective against the weed barnyardgrass. However, its impacts on crop yield and the direct-seeded rice production ecosystem remain underexplored. In this study, we conducted field trials and used untargeted metabolomics to investigate systemic effects of two different treatments (40 g/acre and 60 g/acre) on rice shoot and root as well as the rhizosphere soil during the critical tillering stage. Here, a total of 400 metabolites were determined in the crop and soil, with differential metabolites primarily comprising lipids and lipid-like molecules as well as phenylpropanoids and polyketides. Spearman correlation network analysis and a Zi-Pi plot revealed 7 key differential metabolites with significant topological roles, including succinic acid semialdehyde and riboflavin. KEGG pathway analysis showed that anilofos downregulated the amino acid metabolism while mainly promoted carbohydrate metabolism and secondary metabolites biosynthesis of the crop, which made minimal disruption on soil metabolism. Notably, we found 40 g/acre anilofos application could significantly improve the rice yield, potentially linked to the improved activity of flavonoid biosynthesis and starch and sucrose metabolism. This research provides a comprehensive evaluation of anilofos effects in the direct-seeded rice production system, offering new insights into optimizing herbicide use to improve agricultural sustainability and productivity.

Children of Nature: Thoughts on Targeted and Untargeted Analytical Approaches to Decipher Polyphenol Reactivity in Food Processing and Metabolism.

Following 25 years of polyphenol research in our laboratory, the astonishing chemical and metabolic reactivity of polyphenols resulting in considerable chemical diversity has emerged as the most remarkable attribute of this class of natural products. To illustrate this concept, we will present selected data from black tea and coffee chemistry. In black tea chemistry, enzymatic fermentation converts six catechin derivatives into an estimated 30 000 different polyphenolic compounds via a process we have termed the oxidative cascade process. In coffee roasting, around 45 chlorogenic acids are converted into an estimated 250 novel derivatives following a series of diverse chemical transformations. Following ingestion by humans, these dietary polyphenols, whether genuine secondary metabolites or food processing products, encounter the microorganisms of the gut microbiota, converting them into a myriad of novel structures. In the case of coffee, only two out of 250 chlorogenic acids are absorbed intact, with most others being subject to gut microbial metabolism. Modern mass spectrometry (MS) has been key in unravelling the true complexity of polyphenols subjected to food processing and metabolism. We will accompany this assay with a short overview on analytical strategies developed, including ultrahigh-resolution MS, tandem MS, multivariate statistics, and molecular networking that allow an insight into the fascinating chemical processes surrounding dietary polyphenols. Finally, experimental results studying biological activity of polyphenols will be presented and discussed, highlighting a general promiscuity of this class of compounds associated with nonselective protein binding leading to loss of enzymatic function, another noteworthy general property of many dietary polyphenols frequently overlooked.

Elucidating of the metabolic impact of risperidone on brain microvascular endothelial cells using untargeted metabolomics-based LC-MS.

Risperidone is useful for the treatment of schizophrenia symptoms; however, it also has side effects, and an overdose can be harmful. The metabolic effects of risperidone at high therapeutic doses and its metabolites have not been elucidated. Endogenous cellular metabolites may be comprehensively analyzed using untargeted metabolomics-based liquid chromatography-mass spectrometry (LC-MS), which can reveal changes in cell regulation and metabolic pathways. By identifying the metabolites and pathway changes using a nontargeted metabolomics-based LC-MS approach, we aimed to shed light on the potential toxicological effects of high-dose risperidone on brain microvascular endothelial cells (MVECs) associated with the human blood brain barrier. A total of 42 metabolites were selected as significant putative metabolites of the toxicological response of high-dose risperidone in MVECs. Six highly correlated pathways were identified, including those involving diacylglycerol, fatty acid, ceramide, glycerophospholipid, amino acid, and tricarboxylic acid metabolism. We demonstrated that methods focused on metabolomics are useful for identifying metabolites that may be used to clarify the mechanism of drug-induced toxicity.

Chloroplastic ascorbate modifies plant metabolism and may act as a metabolite signal regardless of oxidative stress.

Ascorbate is a major plant metabolite that plays crucial roles in various processes, from reactive oxygen scavenging to epigenetic regulation. However, to what extent and how ascorbate modulates metabolism is largely unknown. We investigated the consequences of chloroplastic and total cellular ascorbate-deficiencies by studying chloroplastic ascorbate-transporter mutant lines lacking PHOSPHATE TRANSPORTER 4; 4 (PHT4; 4) , and the ascorbate-deficient vtc2-4 mutant of Arabidopsis (Arabidopsis thaliana). Under regular growth conditions, both ascorbate deficiencies caused minor alterations in photosynthesis, with no apparent signs of oxidative damage. In contrast, metabolomics analysis revealed global and largely overlapping alterations in the metabolome profiles of both ascorbate-deficiency mutants, suggesting that chloroplastic ascorbate modulates plant metabolism. We observed significant alterations in amino acid metabolism, particularly in arginine metabolism, activation of nucleotide salvage pathways, and changes in secondary metabolism. In addition, proteome-wide analysis of thermostability revealed that ascorbate may interact with enzymes involved in arginine metabolism, the Calvin-Benson cycle, and several photosynthetic electron transport components. Overall, our results suggest that, independently of oxidative stress, chloroplastic ascorbate modulates the activity of diverse metabolic pathways in vascular plants and may act as an internal metabolic signal.

Exploring gut microbiota and metabolite alterations in patients with thyroid-associated ophthalmopathy using high-throughput sequencing and untargeted metabolomics.

Introduction: Thyroid-associated ophthalmopathy (TAO) is an autoimmune-driven orbital inflammatory disease. Despite research efforts, its exact pathogenesis remains unclear. This study aimed to characterize the intestinal flora and metabolic changes in patients with TAO to identify the flora and metabolites associated with disease development. Methods: Thirty patients with TAO and 29 healthy controls were included in the study. The intestinal flora and metabolites were analyzed using high-throughput sequencing of the 16S rRNA gene and non-targeted metabolomics technology, respectively. Fresh fecal samples were collected from both populations for analysis. Results: Reduced gut richness and diversity were observed in patients with TAO. Compared to healthy controls, significant differences in relative abundance were observed in patients with TAO at the order level Clostridiales, family level Staphylococcaceae, genus level Staphylococcus, Fournierella, Eubacterium siraeum, CAG-56, Ruminococcus gnavus, Intestinibacter, Actinomyces, and Erysipelotrichaceae UCG-003 (logFC>1 and P<0.05). Veillonella and Megamonas were closely associated with clinical symptoms in patients with TAO. Among the 184 significantly different metabolites, 63 were upregulated, and 121 were downregulated in patients with TAO compared to healthy controls. The biosynthesis of unsaturated fatty acids was the significantly enriched metabolic pathway. Correlation analysis revealed Actinomyces was positively correlated with NAGlySer 15:0/16:0, FAHFA 3:0/20:0, and Lignoceric Acid, while Ruminococcus gnavu was positively correlated with Cer 18:0;2O/16:0; (3OH) and ST 24:1;O4/18:2. Conclusion: Specific intestinal flora and metabolites are closely associated with TAO development. Further investigation into the functional associations between these flora and metabolites will enhance our understanding of TAO pathogenesis.

Propionic Acidemia, Methylmalonic Acidemia, and Cobalamin C Deficiency: Comparison of Untargeted Metabolomic Profiles.

Methylmalonic acidemia (MMA), propionic acidemia (PA), and cobalamin C deficiency (cblC) share a defect in propionic acid metabolism. In addition, cblC is also involved in the process of homocysteine remethylation. These three diseases produce various phenotypes and complex downstream metabolic effects. In this study, we used an untargeted metabolomics approach to investigate the biochemical differences and the possible connections among the pathophysiology of each disease. The significantly changed metabolites in the untargeted urine metabolomic profiles of 21 patients (seven MMA, seven PA, seven cblC) were identified through statistical analysis (p < 0.05; log2FC > |1|) and then used for annotation. Annotated features were associated with different metabolic pathways potentially involved in the disease's development. Comparative statistics showed markedly different metabolomic profiles between MMA, PA, and cblC, highlighting the characteristic species for each disease. The most affected pathways were related to the metabolism of organic acids (all diseases), amino acids (all diseases), and glycine and its conjugates (in PA); the transsulfuration pathway; oxidative processes; and neurosteroid hormones (in cblC). The untargeted metabolomics study highlighted the presence of significant differences between the three diseases, pointing to the most relevant contrast in the cblC profile compared to MMA and PA. Some new biomarkers were proposed for PA, while novel data regarding the alterations of steroid hormone profiles and biomarkers of oxidative stress were obtained for cblC disease. The elevation of neurosteroids in cblC may indicate a potential connection with the development of ocular and neuronal deterioration.

Validation of two LCHRMS methods for large-scale untargeted metabolomics of serum samples: Strategy to establish method fitness-for-purpose.

Untargeted metabolomics by LCHRMS is a powerful tool to enhance our knowledge of pathophysiological processes. Whereas validation of a bioanalytical method is customary in most analytical chemistry fields, it is rarely performed for untargeted metabolomics. This study aimed to establish and validate an analytical platform for a long-term, clinical metabolomics study. Sample preparation was performed with an automated liquid handler and four analytical methods were developed and evaluated. The validation study spanned three batches with twelve runs using individual serum samples and various quality control samples. Data was acquired with untargeted acquisition and only metabolites identified at level 1 were evaluated. Validation parameters were set to evaluate key performance metrics relevant for the intended application: reproducibility, repeatability, stability, and identification selectivity, emphasizing dataset intrinsic variance. Concordance of semi-quantitative results between methods was evaluated to identify potential bias. Spearman rank correlation coefficients (rs) were calculated from individual serum samples. Of the four methods tested, two were selected for validation. A total of 47 and 55 metabolites (RPLC-ESI+- and HILIC-ESI--HRMS, respectively) met specified validation criteria. Quality assurance involved system suitability testing, sample release, run release, and batch release. The median repeatability and within-run reproducibility as coefficient of variation% for metabolites that passed validation on RPLC-ESI+- and HILIC-ESI--HRMS were 4.5 and 4.6, and 1.5 and 3.8, respectively. Metabolites that passed validation on RPLC-ESI+-HRMS had a median D-ratio of 1.91, and 89 % showed good signal intensity after ten-fold dilution. The corresponding numbers for metabolites with the HILIC-ESI--HRMS method was 1.45 and 45 %, respectively. The rs median ({range}) for metabolites that passed validation on RPLC-ESI+- was 0.93 (N = 9 {0.69-0.98}) and on HILIC-ESI--HRMS was 0.93 (N = 22 {0.55-1.00}). The validated methods proved fit-for-purpose and the laboratory thus demonstrated its capability to produce reliable results for a large-scale, untargeted metabolomics study. This validation not only bolsters the reliability of the assays but also significantly enhances the impact and credibility of the hypotheses generated from the studies. Therefore, this validation study serves as a benchmark in the documentation of untargeted metabolomics, potentially guiding future endeavors in the field.

Integrating serum pharmacochemistry, network pharmacology and untargeted metabolomics strategies to reveal the material basis and mechanism of action of Feining keli in the treatment of chronic bronchitis.

ETHNOPHARMACOLOGICAL RELEVANCE: Feining keli (FNKL) is herbal preparation mainly made from Senecio cannabifolius Less., In recent years, more and more studies have found that FNKL has excellent therapeutic effects on chronic bronchitis (CB). Nevertheless, its pharmacodynamic material basis and mechanism of action are still unknown. AIM OF THE STUDY: This study aimed to explore the pharmacodynamic material basis and mechanism of action of FNKL in treating CB. MATERIALS AND METHODS: The CB rat model was induced using nasal drops of lipopolysaccharide (LPS) in combination with smoking. Various assessments including behavioral and body mass examination, lung index measurement, enzyme linked immunosorbent assay (ELISA), as well as histological analyses using hematoxylin and eosin (H&E) and Masson staining were conducted to validate the reliability of the CB model. The serum components of FNKL in CB rats were identified using ultra-high-performance liquid chromatography Orbitrap Exploris mass spectrometer (UHPLC-OE-MS). Network pharmacology was used to predict the network of action of the active ingredients in FNKL based on these serum components. Signaling pathways were enriched and analyzed, and molecular docking was conducted for key targets. Molecular dynamics simulations were performed using GROMACS software. The mechanism was confirmed through a series of experiments including Western blot (WB), immunofluorescence (IF), and reverse transcription (RT)-PCR. Additionally, untargeted metabolomics was employed to identify biomarkers and relevant metabolic pathways associated with the treatment of CB with FNKL. RESULTS: In CB rats, FNKL improved body mass, lung index, and pathological damage of lung tissues. It also decreased interleukin (IL)-6, tumor necrosis factor-alpha (TNF-α), malonaldehyde (MDA) levels, and percentage of lung collagen fiber area. Furthermore, FNKL increased IL-10 and superoxide dismutase (SOD) levels, which helped alleviate bronchial inflammation in the lungs. A total of 70 FNKL chemical components were identified in CB rat serum. Through network pharmacology analysis, 5 targets, such as PI3K, AKT, NF-κB, HIF-1α, and MYD88, were identified as key targets of FNKL in the treatment of CB. Additionally, the key signaling pathways identified were PI3K/AKT pathway、NF-κB/MyD88 pathway、HIF-1α pathway. WB, IF, and RT-PCR experiments were conducted to confirm the findings. Molecular docking studies demonstrated successful docking of 16 potential active components with 5 key targets. Additionally, molecular dynamics simulations indicated the stability of quercetin-3-galactoside and HIF-1α. Metabolomics analysis revealed that FNKL primarily regulated pathways related to alpha-linolenic acid metabolism, primary bile acid biosynthesis, bile secretion, arachidonic acid metabolism, neuroactive ligand-receptor interaction, and folate biosynthesis. Furthermore, the expression levels of traumatic acid, traumatin, alpha linolenic acid, cholic acid, 2-arachidonoylglycerol, deoxycholic acid, 7,8-dihydroneopterin, and other metabolites were found to be regulated. CONCLUSION: FNKL exhibits positive therapeutic effects on CB, with quercetin-3-galactoside identified as a key active component. The mechanism of FNKL's therapeutic action on CB involves reducing inflammatory response, oxidative stress, and regulating metabolism, and its molecular mechanism was better elucidated in a holistic manner. This study serves as a reference for understanding the pharmacodynamic material basis and mechanism of action of FNKL in treating CB, and provides avenues for exploring the effects of compounded herbal medicines on CB.

Identification of Blood Biomarkers in Ischemic Stroke by Integrated Analysis of Metabolomics and Proteomics.

We aimed to uncover the pathological mechanism of ischemic stroke (IS) using a combined analysis of untargeted metabolomics and proteomics. The serum samples from a discovery set of 44 IS patients and 44 matched controls were analyzed using a specific detection method. The same method was then used to validate metabolites and proteins in the two validation sets: one with 30 IS patients and 30 matched controls, and the other with 50 IS patients and 50 matched controls. A total of 105 and 221 differentially expressed metabolites or proteins were identified, and the association between the two omics was determined in the discovery set. Enrichment analysis of the top 25 metabolites and 25 proteins in the two-way orthogonal partial least-squares with discriminant analysis, which was employed to identify highly correlated biomarkers, highlighted 15 pathways relevant to the pathological process. One metabolite and seven proteins exhibited differences between groups in the validation set. The binary logistic regression model, which included metabolite 2-hydroxyhippuric acid and proteins APOM_O95445, MASP2_O00187, and PRTN3_D6CHE9, achieved an area under the curve of 0.985 (95% CI: 0.966-1) in the discovery set. This study elucidated alterations and potential coregulatory influences of metabolites and proteins in the blood of IS patients.

Konjac supplementation can alleviate obesity induced by high-fat diet in mice by modulating gut microbiota and its metabolites.

As a multi-factorial disease, obesity has become one of the major health problems in the world, and it is still increasing rapidly. Konjac supplementation, as a convenient dietary therapy, has been shown to be able to regulate gut microbiota and improve obesity. However, the specific mechanism by which konjac improves obesity through gut microbiota remains to be studied. In this study, a high-fat diet (HFD) was used to induce a mouse obesity model, and 16S rDNA sequencing and an untargeted metabolomics were used to investigate the impact of konjac on gut microbiota and gut metabolites in HFD-induced obese mice. The results show that konjac can reduce the body weight, adipose tissue weight, and lipid level of high-fat diet induced obese mice by changing the gut microbiota structure and gut metabolic profile. Association analysis revealed that konjac supplementation induced changes in gut microbiota, resulting in the up-regulation of 7-dehydrocholesterol and trehalose 6-phosphate, as well as the down-regulation of glycocholic acid and ursocholic acid within the Secondary bile acid biosynthesis pathway, ultimately leading to improvements in obesity. Among them, g_Acinetobacter (Greengene ID: 911888) can promote the synthesis of 7-dehydrocholesterol by synthesizing ERG3. g_Allobaculum (Greengene ID: 271516) and g_Allobaculum (Greengene ID: 259370) can promote the breakdown of trehalose 6-phosphate by synthesizing glvA. Additionally, the down-regulation of glycocholic acid and ursocholic acid may be influenced by the up-regulation of Lachnospiraceae_NK4A136_group. In conclusion, konjac exerts an influence on gut metabolites through the regulation of gut microbiota, thereby playing a pivotal role in alleviating obesity induced by a high-fat diet.

Identification of Chagas disease biomarkers using untargeted metabolomics.

Untargeted metabolomic analysis is a powerful tool used for the discovery of novel biomarkers. Chagas disease (CD), caused by Trypanosoma cruzi, is a neglected tropical disease that affects 6-7 million people with approximately 30% developing cardiac manifestations. The most significant clinical challenge lies in its long latency period after acute infection, and the lack of surrogate markers to predict disease progression or cure. In this cross-sectional study, we analyzed sera from 120 individuals divided into four groups: 31 indeterminate CD, 41 chronic chagasic cardiomyopathy (CCC), 18 Latin Americans with other cardiomyopathies and 30 healthy volunteers. Using a high-throughput panel of 986 metabolites, we identified three distinct profiles among individuals with cardiomyopathy, indeterminate CD and healthy volunteers. After a more stringent analysis, we identified some potential biomarkers. Among peptides, phenylacetylglutamine and fibrinopeptide B (1-13) exhibited an increasing trend from controls to ICD and CCC. Conversely, reduced levels of bilirubin and biliverdin alongside elevated urobilin correlated with disease progression. Finally, elevated levels of cystathionine, phenol glucuronide and vanillactate among amino acids distinguished CCC individuals from ICD and controls. Our novel exploratory study using metabolomics identified potential biomarker candidates, either alone or in combination that if confirmed, can be translated into clinical practice.

Metabolite profiling of different Iranian traditional yogurts using an untargeted metabolomics approach.

We used gas chromatography-mass spectrometry (GC-MS) with an untargeted metabolomics approach to look at the metabolite profiles of traditional Iranian yogurts made from cow, goat, buffalo, and sheep milk. Results showed that different animal milks significantly influenced physicochemical properties and fatty acid (FA) composition, resulting in diverse metabolites. Over 80 % of all the fatty acids in the yogurt samples were saturated. The main fatty acids found were myristic acid (C14:0), palmitic acid (C16:0), and oleic acid + petroselenic acid (cis-9 C18:1 + cis-6 C18:1). In total, 36 metabolites, including esters, aldehydes, alcohols, and acids, were detected. Some important metabolites that changed yogurt profiles were 2-heptanone, methyl acetate, 2-propanone, butyl formate, and 4-methyl benzal. Associations between metabolite profiles and milk compositional traits were also observed, with statistical models showing a strong correlation between metabolite profiles and FA content. This study is the first to explore the impact of different animal sources and regions in Iran on the metabolome profiles of traditional yogurts. These results give us useful information about how metabolites differ between species and can be used to make new dairy products based on milk compositions and metabolites, which will help with future formulations of autochthonous starters.

Immunomodulatory effect of tibetan medicine compound extracts against ORFV in vitro by metabolomics.

Ovine contagious pustular dermatitis (ORF) is one of the main diseases of sheep and is a zoonotic disease caused by Ovine contagious pustular dermatitis virus (ORFV) infection, posing a significant constraint on sheep breeding industry and human health. The Tibetan medical formulation composed of Polygonum leucoides, Polygonum xanthoxylum and Acanthophora rotunda significantly regulated lymphocyte immune function following ORFV stimulation, although the mechanism remains unclear. In order to study the immunomodulatory effects and mechanism of three Tibetan medicinal extracts (Polygonum leucoides, Polygonum xanthoxylum, and Acanthophora rotunda) against ORFV in vitro, sheep peripheral blood lymphocytes were isolated in vitro and treated with different concentrations of Tibetan medicine compound extract solution after ORFV infection. The cytokine expression levels in lymphocytes were measured at 4 h, 8 h and 12 h. Additionally endogenous metabolites in lymphocytes at 0 h, 4 h, 8 h and 12 h were quantified by untargeted metabolomics method. The results showed that, the extracts could regulate the lymphocyte immune factors altered by ORFV, and regulate the lymphocyte immune function through cysteine and methionine metabolic pathways as well as the pyrimidine metabolic pathways, potentially alleviating the immune evasion induced by ORFV.

High-coverage characterization and discovery of molecular markers for quality control of natural fragrant plant extracts using UPLC-HRMS-based untargeted metabolomics.

The chemical components of natural fragrant plant extracts are of high complexity, and the strategies for quality control (QC) and further discovery of fragrance mechanisms still need to be further investigated. This study integrated the strategies and methods of untargeted metabolomics and chemometrics and statistical modeling to attain the goal. The techniques of reversed-phase and HILIC analysis of ultra-performance liquid chromatography-high-resolution mass spectrometry (UPLC-HRMS) were simultaneously used to collect data in both positive and negative ion modes. The pattern analysis of fingerprints and discovery of characteristic molecular markers for QC analysis were comprehensively employed to reach in-depth analysis of the quality variation and discovery of differential molecules among natural fragrant plant extracts. The former uses fingerprint technique to analyze their overall similarities and differences, and the latter comprehensively discovers molecular substances characterizing the chemical characteristics of fragrant extracts with the help of metabolomics and univariate and multivariate methods. The findings are expected to be used as the molecular markers in product manufacturing, sales, and consumption to achieve accurate quality control and recognition of targeted molecules for potential quality monitoring using spectroscopy techniques. In this work, 27 natural fragrant extracts were applied as examples, and their chemical components were comprehensively analyzed with discovery of markers for quality control. After data integration, 1178 molecules were annotated, and 267 differential metabolite molecules with the values of variable importance in the projection (VIP) larger than 1.0 were found. The results show that the method proposed in this work is of great significance for high-coverage analysis, QC marker discovery, and aroma mechanism elucidation, which has potential applications in the areas of food, cosmetics, pharmaceuticals, tobacco, and others.