Dynamic changes in pigment metabolites during the green-to-orange transition of hawthorn peel revealed by targeted metabolomics

Idiopathic intracranial hypertension, a disease classically occurring in women with obesity, is characterized by raised intracranial pressure. Weight loss leads to the reduction in intracranial pressure. Additionally, pharmacological glucagon-like peptide-1 agonism reduces cerebrospinal fluid secretion and intracranial pressure. The potential mechanisms by which weight loss reduces intracranial pressure are unknown and were the focus of this study. Meal stimulation tests (fasted plasma sample, then samples at 15, 30, 60, 90 and 120 min following a standardized meal) were conducted pre- and post-bariatric surgery [early (2 weeks) and late (12 months)] in patients with active idiopathic intracranial hypertension. Dynamic changes in gut neuropeptides (glucagon-like peptide-1, gastric inhibitory polypeptide and ghrelin) and metabolites (untargeted ultra-high performance liquid chromatography-mass spectrometry) were evaluated. We determined the relationship between gut neuropeptides, metabolites and intracranial pressure. Eighteen idiopathic intracranial hypertension patients were included [Roux-en-Y gastric bypass (RYGB) n = 7, gastric banding n = 6 or sleeve gastrectomy n = 5]. At 2 weeks post-bariatric surgery, despite similar weight loss, RYGB had a 2-fold (50%) greater reduction in intracranial pressure compared to sleeve. Increased meal-stimulated glucagon-like peptide-1 secretion was observed after RYGB (+600%) compared to sleeve (+319%). There was no change in gastric inhibitory polypeptide and ghrelin. Dynamic changes in meal-stimulated metabolites after bariatric surgery consistently identified changes in lipid metabolites, predominantly ceramides, glycerophospholipids and lysoglycerophospholipids, which correlated with intracranial pressure. A greater number of differential lipid metabolites were observed in the RYGB cohort at 2 weeks, and these also correlated with intracranial pressure. In idiopathic intracranial hypertension, we identified novel changes in lipid metabolites and meal-stimulated glucagon-like peptide-1 levels following bariatric surgery which were associated with changes in intracranial pressure. RYGB was most effective at reducing intracranial pressure despite analogous weight loss to gastric sleeve at 2 weeks post-surgery and was associated with more pronounced changes in these metabolite pathways. We suggest that these novel perturbations in lipid metabolism and glucagon-like peptide-1 secretion are mechanistically important in driving a reduction in intracranial pressure following weight loss in patients with idiopathic intracranial hypertension. Therapeutic targeting of these pathways, for example with glucagon-like peptide-1 agonist infusion, could represent a therapeutic strategy.

Metabolic profiling of tobacco leaves at different growth stages or different stalk positions by gas chromatography–mass spectrometry

Functional MRI (fMRI) has provided much insight into the changes in the neuronal activity on the basis of blood oxygen level dependent (BOLD) phenomenon. The dynamic changes in the metabolites can be detected using functional proton magnetic resonance spectroscopy (H-fMRS). The strategy of combining fMRI and H-fMRS would facilitate the understanding of the neurochemical interpretation of the BOLD signal. The dorsolateral prefrontal region is critically involved in the processing of working memory (WM), as demonstrated by the studies involving the neuroimaging, neuropsychological, and electrophysiological experiments. In this study, we tested the association between BOLD signal and changes in brain metabolites in the left dorsolateral prefrontal region using N-back verbal WM task. We used single-voxel task-based H-MRS acquired in the left dorsolateral prefrontal region and fMRI during the performance of N-back verbal WM task to investigate the association between changes in metabolites and BOLD response in 10 healthy participants. The correlation between changes in metabolites and percent signal change was examined by the Pearson correlation. The Pearson correlation analysis revealed a significant positive correlation between the BOLD signal and glutamate/glutamine in the left dorsolateral prefrontal region during the verbal WM. Our finding suggests that glutamate/glutamine cycle plays a critical role in the neuronal activation as reflected by the changes in the BOLD response.

Large-scale metabolome analysis reveals dynamic changes of metabolites during foxtail millet grain filling

Dynamic changes in metabolites may affect liver disease progression, and provide new methods for predicting liver damage. We used ultra-performance liquid chromatography-mass spectroscopy to assess serum metabolites in healthy controls (HC), and patients with acute hepatitis E (AHE) or hepatitis E virus acute liver failure (HEV-ALF). The principal component analysis, partial least squares discriminant analysis, and discriminant analysis of orthogonal projections to latent structures models illustrated significant differences in the metabolite components between AHE patients and HCs, or between HEV-ALF and AHE patients. In pathway enrichment analysis, we further identified two altered pathways, including linoleic acid metabolism and phenylalanine, tyrosine, and tryptophan biosynthesis, when comparing AHE patients with HCs. Linoleic acid metabolism and porphyrin and chlorophyll metabolism pathways were significantly different in HEV-ALF when compared with AHE patients. The discriminative performances of differential metabolites showed that taurocholic acid, glycocholic acid, glycochenodeoxycholate-3-sulfate, and docosahexaenoic acid could be used to distinguish HEV-ALF from AHE patients. The serum levels of glycocholic acid, taurocholic acid, deoxycholic acid glycine conjugate, and docosahexaenoic acid were associated with the prognosis of HEV-ALF patients. Dynamic changes in serum metabolites were associated with AHE infection and severity. The identified metabolites can be used to diagnose and predict the prognosis of HEV-ALF.

BACKGROUNDFibrosis is the single most important predictor of significant morbidity and mortality in patients with chronic liver disease. Established non-invasive tests for monitoring fibrosis are lacking, and new biomarkers of liver fibrosis and function are needed.AIMTo depict the process of liver fibrosis and look for novel biomarkers for diagnosis and monitoring fibrosis progression.METHODSCCl4 was used to establish the rat liver fibrosis model. Liver fibrosis process was measured by liver chemical tests, liver histopathology, and Masson’s trichrome staining. The expression levels of two fibrotic markers including α-smooth muscle actin and transforming growth factor β1 were assessed using immunohistochemistry and real-time polymerase chain reaction. Dynamic changes in metabolic profiles and biomarker concentrations in rat serum during liver fibrosis progression were investigated using ultra-performance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry. The discriminatory capability of potential biomarkers was evaluated by receiver operating characteristic (ROC) curve analysis.RESULTSTo investigate the dynamic changes of metabolites during the process of liver fibrosis, sera from control and fibrosis model rats based on pathological results were analyzed at five different time points. We investigated the association of liver fibrosis with 21 metabolites including hydroxyethyl glycine, L-threonine, indoleacrylic acid, β-muricholic acid (β-MCA), cervonoyl ethanolamide (CEA), phosphatidylcholines, and lysophosphatidylcholines. Two metabolites, CEA and β-MCA, differed significantly in the fibrosis model rats compared to controls (P < 0.05) and showed prognostic value for fibrosis. ROC curve analyses performed to calculate the area under the curve (AUC) revealed that CEA and β-MCA differed significantly in the fibrosis group compared to controls with AUC values exceeding 0.8, and can clearly differentiate early stage from late stage fibrosis or cirrhosis.CONCLUSIONThis study identified two novel biomarkers of fibrosis, CEA and β-MCA, which were effective for diagnosing fibrosis in an animal model.

Revealing the mechanism of post-harvest processing on rose quality based on dynamic changes in water content, enzyme activity, volatile and non-volatile metabolites

The long-term effect of botulinum neurotoxin A (BoNT-A) on children with cerebral palsy (CP) is unclear, and how the dynamic changes of metabolites impact the duration of effect remains unknown. To tackle this, we collected 120 plasma samples from 91 children with spastic CP for analysis, with 30 samples in each time point: prior to injection and 1, 3, and 6 months after injection. A total of 354 metabolites were identified across all the time points, 39 of which exhibited significant changes (with tentative IDs) (p values <0.05, VIP > 1). Principal component analysis and partial least-squares discriminant analysis disclosed a clear separation between different groups (p values <0.05). Network analysis revealed the coordinated changes of functional metabolites. Pathway analysis highlighted the metabolic pathways associated with energy consumption and glycine, serine, and threonine metabolism and cysteine and methionine metabolism. Collectively, our results identified the significant dynamic changes of plasma metabolite after BoNT-A injections on children with CP. Metabolic pathways associated with energy expenditure might provide a new perspective for the effect of BoNT-A in children with CP. Glycine, serine, and threonine metabolism and cysteine and methionine metabolism might be related to the duration of effect of BoNT-A.

Identification of dynamic changes in volatile compounds and metabolites during the smoking process of Zhenba bacon by GC-IMS combined metabolomics

Unravelling dynamic changes in non-volatile and volatile metabolites of pulses during soaking: An integrated metabolomics approach.

Gut derived (S)-Equol mitigates influenza viral pneumonia by modulating macrophage polarization via Nrf2 mediated AKT/ERK/NF-κb signaling pathways.

Longitudinal changes of brain metabolites during a functional stimulation are unknown in amnestic mild cognitive impairment (aMCI) and Alzheimer's disease (AD) subjects. This study was to evaluate the longitudinal changes of brain metabolites using proton magnetic resonance spectroscopy (1H MRS) in response to treatment during a memory task in the subjects of cognitive normal (CN), aMCI, and AD. We acquired functional magnetic resonance spectroscopy (fMRS) data from 28 CN elderly, 16 aMCI and 12 AD subjects during a face-name association task. We measured fMRS metabolite ratios over 24 months in the 8-month apart, determined the temporal changes of the metabolites, and evaluated the differences among the three groups under the three different conditions (base, novel, repeat). The results of comparisons for the three subject groups and the three-time points showed that tNAA/tCho and tCr/tCho were statistically significant among the three subject groups in any of the three conditions. The dynamic temporal change measurements for the metabolites for each condition showed that Glx/tCho and Glu/tCho levels at the third visit increased significantly compared with in the first visit in the novel condition in the AD group. We found declines in tNAA/tCho and tCr/tCho in the aMCI and AD subjects with increasing disease severity, being highest in CN and lowest in AD. The Glx/tCho level increased temporally in the AD subjects after they took an acetylcholine esterase inhibitor. Therefore, Glx may be suitable to demonstrate functional recovery after treatment.

Black waxy rice wine fermentation metabolites are closely related to the product's final quality. However, little is known about dynamic metabolite changes during fermentation. Here, we used gas chromatography time‐of‐flight mass spectrometry (GC‐TOF‐MS) metabolomics and multivariate statistical analysis to explore the relationship between metabolites and fermentation time. A total of 159 metabolites were identified during the entire fermentation process. The PCA analysis revealed a clear separation between the samples after 4 days and 2 days, and the samples after 4–24 days clustered together. This indicated that BGRW fermentation progresses rapidly in the first 48 hr of fermentation. A total of 40 metabolites were identified as differential during fermentation (VIP > 1 and p < .05), including 12 organic acids, four amino acids, one fatty acid, 17 sugars and sugar alcohols, one alcohol, and five other metabolites. Pathway analysis showed that the differential metabolites were involved in 28 metabolic pathways, and the most commonly influenced pathways (impact value > 0.1 and p < .05) were galactose metabolism, pyruvate metabolism; starch and sucrose metabolism; alanine, aspartic acid, and glutamate metabolism; the tricarboxylic acid cycle, glyoxylic acid, and dicarboxylic acid metabolism; and amino sugar and nucleotide sugar metabolism. Moreover, the integrated metabolic pathway was generated to understand the transformation and accumulation of differential metabolites. Overall, these results provide a comprehensive overview of metabolite changes during black waxy rice wine fermentation.

Metabolomics is an emerging discipline subsequent to genomics, transcriptomics and proteomics, aiming for systematically studying the regularity of changes in metabolite to revealing organism's nature of movement and metabolism. It is especially important in modern pharmacological studies. Metabolic fingerprinting analysis is a method for metabolic analysis on high throughput of all metabolites, studying changes in drugs, organisms and endogenic metabolites caused by drugs and finding out related biomarkers to reflect dynamic changes inside organisms more directly and explain the mechanism of drugs and their effects on diseases. This essay summarizes some new metabolic fingerprint analytical methods and data processing methods used for metabolic fingerprint, elaborates their advantages and disadvantages and looks ahead to their combination with studies on traditional Chinese medicines, providing room for the development of new methods and new approaches for studies on complexity theory system of traditional Chinese medicines.

In forensic practice, determining the postmortem submersion interval (PMSI) and cause-of-death of cadavers in aquatic ecosystems has always been challenging task. Traditional approaches are not yet able to address these issues effectively and adequately. Our previous study proposed novel models to predict the PMSI and cause-of-death based on metabolites of blood from rats immersed in freshwater. However, with the advance of putrefaction, it is hardly to obtain blood samples beyond 3 days postmortem. To further assess the feasibility of PMSI estimation and drowning diagnosis in the later postmortem phase, gastrocnemius, the more degradation-resistant tissue, was collected from drowned rats and postmortem submersion model in freshwater immediately after death, and at 1day, 3 days, 5 days, 7 days, and 10 days postmortem respectively. Then the samples were analyzed with liquid chromatography-tandem mass spectrometry (LC-MS/MS) to investigate the dynamic changes of the metabolites. A total of 924 metabolites were identified. Similar chronological changes of gastrocnemius metabolites were observed in the drowning and postmortem submersion groups. The difference in metabolic profiles between drowning and postmortem submersion groups was only evident in the initial 1day postmortem, which was faded as the PMSI extension. Nineteen metabolites representing temporally-dynamic patterns were selected as biomarkers for PMSI estimation. A regression model was built based on these biomarkers with random forest algorithm, which yielded a mean absolute error (± SE) of 5.856 (± 1.296) h on validation samples from an independent experiment. These findings added to our knowledge of chronological changes in muscle metabolites from submerged vertebrate remains during decomposition, which provided a new perspective for PMSI estimation.