Transcriptomics combined with metabolisms reveals the effect of light-exclusive films on the quality and polyphenols of 'Cabernet Sauvignon' grapes.

The grape quality might be affected if the solar intensity (SI) was too strong. In this study, the influence of light-exclusive films on the transcriptomic properties and metabolic substances of grapes were evaluated. The results showed that films, especially polycarbonate (PC), could significantly decrease the SI. The sugar content was obviously decreased, while the acid content was increased. The anthocyanin content was decreased, in contrast to the total polyphenols, flavonoids and tannins. The corresponding derivatives owned the same trend. Lots of differentially expressed genes (DEGs) were detected, especially under PC. The expression pattern and GO function enrichment of DEGs from PC significantly differed from other groups. DEGs enrichment also proved that films, especially PC, could significantly improve the contents of tannins, flavonoids and other polyphenols. VvUFGT, VvF3'5'H, VvLDOX, VvLAR1 and VvANR were confirmed to be the key genes in the biosynthetic pathway of polyphenols under different films.

Reconstruction and analysis of correlation networks based on GC-MS metabolomics data for hypercholesterolemia.

BACKGROUND AND AIMS: Hypercholesterolemia is characterized by the elevation of plasma total cholesterol level, especially low-density lipoprotein (LDL) cholesterol. This disease is usually caused by a mutation in genes such as LDL receptor, apolipoprotein B, or proprotein convertase subtilisin/kexin type 9. However, a considerable number of patients with hypercholesterolemia do not have any mutation in these candidate genes. In this study, we examined the difference in the metabolic level between patients with hypercholesterolemia and healthy subjects, and screened the potential biomarkers for this disease. METHODS: Analysis of plasma metabolomics in hypercholesterolemia patients and healthy controls was performed by gas chromatography-mass spectrometry and metabolic correlation networks were constructed using Gephi-0.9.2. RESULTS: First, metabolic profile analysis confirmed the distinct metabolic footprints between the patients and the healthy ones. The potential biomarkers screened by orthogonal partial least-squares discrimination analysis included l-lactic acid, cholesterol, phosphoric acid, d-glucose, urea, and d-allose (Variable importance in the projection > 1). Second, arginine and methionine metabolism were significantly perturbed in hypercholesterolemia patients. Finally, we identified that l-lactic acid, l-lysine, l-glutamine, and l-cysteine had high scores of centrality parameters in the metabolic correlation network. CONCLUSION: Plasma l-lactic acid could be used as a sensitive biomarker for hypercholesterolemia. In addition, arginine biosynthesis and cysteine and methionine metabolism were profoundly altered in patients with hypercholesterolemia.

Revealing metabolic pathways relevant to prediabetes based on metabolomics profiling analysis.

AIMS: Dahl salt-sensitive (SS) rats develop similar prediabetes lesion characteristics, such as impaired glucose tolerance (IGT), when compared with the salt resistant rat. In this study, we evaluate the risk of high glucose intake during prediabetes and reveal the metabolic pathways relevant to the pathophysiology of prediabetes to diabetes using the SS rat model and compared this with the salt-resistant consomic SS.13BN rat model. METHODS: SS rats were fed with normal chow ±10% glucose solution ad libitum for five weeks. The same experimental treatment was performed on the SS.13BN rats. Metabolites derived from the serum and liver tissue were measured through biochemical and metabolomics analyses. Multivariate, pathway enrichment, and metabolic correlation network analyses were performed based on the metabolomics data. RESULTS: Biochemical analysis revealed that serum triglyceride (TG) significantly increased with a significant decrease in serum total cholesterol (TC) after high glucose intake in the SS rat. Metabolic pathway analysis revealed that high glucose intake interfered with galactose, glyoxylate, and dicarboxylate metabolism, most evidently in the SS rat. Hepatic l-lactic acid content increased in the SS rat after high glucose intake, whereas the opposite was observed in SS.13BN rats. Metabolic correlation network analysis based on serum metabolites revealed that urea and l-valine had higher metabolic centrality in the SS rat. CONCLUSION: Our findings revealed that high glucose intake can significantly stimulate hypertriglyceridemia and reduce serum TC level. The profoundly altered metabolic pathway included galactose, glyoxylate, and dicarboxylate metabolism. l-lactic acid was screened as a biomarker in liver, whereas l-valine and urea were screened as hub metabolites in serum.