Protein Metabolism Research Articles

Integrated metabolomics and metagenomics reveal plant-microbe interactions driving aroma differentiation in flue-cured tobacco leaves

Current research on tobacco aroma predominantly focuses on single-omics approaches. In this study, we conducted a comprehensive investigation of the relationships between tobacco metabolite profiles, microbial communities, and aroma characteristics. Untargeted metabolomics and metagenomic analyses were performed on flue-cured upper tobacco leaves to compare light aromatic tobacco (LAT) and strong aromatic tobacco (SAT). The results showed that sugar metabolite levels in LAT were significantly higher than those in SAT, whereas levels of specific acids and amino acid metabolites in SAT exceeded those in LAT. Redundancy analysis (RDA) and metabolomic correlation analyses indicated that the genera Methylorubrum and Pseudomonas may promote sugar metabolite accumulation, while Pseudokineococcus potentially regulates both sugar and acid metabolites. In contrast, Methylobacterium and Sphingomonas were associated with acid and amino acid metabolism, with Methylobacterium additionally exhibiting inhibitory effects on sugar metabolism. Metagenomic analysis revealed that Methylorubrum, Pseudomonas, and Pseudokineococcus were abundant in LAT, whereas Methylobacterium and Sphingomonas dominated in SAT. Notably, the bidirectional regulation of aromatic metabolites by microbial genera such as Pseudokineococcus highlights the universality of plant-microbe interactions in shaping metabolic networks—a mechanism potentially applicable to other crop systems. These findings reveal conserved microbial functional traits (e.g., metabolic pathway modulation) that may drive plant phenotypic differentiation beyond tobacco, offering insights into microbiome-mediated crop quality improvement. The results provide theoretical guidance for tobacco aging and aroma regulation and underscore the broader significance of microbial community engineering in agriculture for manipulating plant metabolic outputs.

Reprogramming of lipids and amino acids metabolism is an early event in myocardium of type 1 diabetic rhesus monkeys.

Reprogramming of lipids and amino acids metabolism is an early event in myocardium of type 1 diabetic rhesus monkeys.

The role of TNF in metabolic disorders and liver diseases.

The role of TNF in metabolic disorders and liver diseases.

Neonatal amino acid metabolism in gestational diabetes mellitus mothers treated with different treatment strategies.

The changes in amino acid (AA) levels have been observed in pregnant women with gestational diabetes mellitus (GDM). However, it remains unclear whether the AA levels in offspring of GDM mothers are affected by GDM. This study aimed to investigate the changes in AA metabolism in offspring of pregnant women with GDM undergoing different glycemic control treatment regimens. 272 pregnant women treated at our hospital were selected and divided into the GDM and the non-GDM groups. The GDM group was further subdivided into three treatment groups: exercise-diet therapy, metformin therapy, and insulin therapy. The levels of 11 AAs of their offsprings were detected using tandem mass spectrometry and the differences in neonatal AA metabolism between the three treatment groups and the non-GDM group were compared. There were significant differences in the levels of Arg, Cit, Met, Orn, and Pro of their offsprings between different treatment groups and the non-GDM group (P < 0.05). After controlling for relevant confounding factors, the differences in Arg and Orn remained statistically significant in the three treatment groups compared to the non-GDM group (P < 0.05); Cit remained statistically significant in the exercise-diet group (P < 0.05); and Met and Pro remained statistically significant in the exercise-diet group and insulin group (P < 0.05). Regardless of the glycemic control treatment regimens used for GDM, AA metabolism related to the arginine family is influenced.

The protocatechuic acid catabolism regulator PcaV inhibits lincomycin biosynthesis either directly or indirectly through the control of the expression of other regulatory or metabolic genes.

The protocatechuic acid catabolism regulator PcaV inhibits lincomycin biosynthesis either directly or indirectly through the control of the expression of other regulatory or metabolic genes.

Transcriptomic and metabolomic analyses provide insights into the energy metabolism and signaling regulation of byssus secretion in winged pearl oyster Pteria penguin.

Transcriptomic and metabolomic analyses provide insights into the energy metabolism and signaling regulation of byssus secretion in winged pearl oyster Pteria penguin.

Comparison of in vitro fermentation characteristics of carob gum and guar gum.

Comparison of in vitro fermentation characteristics of carob gum and guar gum.

Study on the mechanism of acteoside in treating purinomycin aminonucleoside-induced chronic glomerulonephritis in childhood rats based on Cxcr4-PI3K-Akt-eNOS axis.

Study on the mechanism of acteoside in treating purinomycin aminonucleoside-induced chronic glomerulonephritis in childhood rats based on Cxcr4-PI3K-Akt-eNOS axis.

Effects of co-fermentation with different erythritol producing abilities Yarrowia lipolytica on the flavor, functionality, and sensory characteristics of Huangjiu.

Effects of co-fermentation with different erythritol producing abilities Yarrowia lipolytica on the flavor, functionality, and sensory characteristics of Huangjiu.

Exploring the fate of 6PPD in zebrafish (Danio rerio): Understanding toxicokinetics, biotransformation mechanisms, and metabolomic profiling at environmentally relevant levels.

Exploring the fate of 6PPD in zebrafish (Danio rerio): Understanding toxicokinetics, biotransformation mechanisms, and metabolomic profiling at environmentally relevant levels.

Can oxidative potential be a plant risk indicator for heavy metals contaminated soil? Analysis of ryegrass (Lolium perenne L.) metabolome based on machine learning.

Evaluating the plant risk of soil pollution by plant physiological indices usually requires a long cycle and has significant uncertainty. In this study, oxidative potential (OP) of the in situ heavy metal contaminated soils was measured by the dithiothreitol method. The oxidative stress response of the model plant ryegrass (Lolium perenne L.) induced by heavy metal contaminated soil was evaluated by the biomarkers, including superoxide dismutase and total antioxidant capacity. The comprehensive biomarker response index has a significant exponential correlation with the OP of soil (r​=​0.923, p​<​0.01) in ryegrass. Metabolomics analysis also showed a significant relationship of the metabolic effect level index of amino acids and sugars with OP. Random forest was selected from four machine learning models to screen the metabolites most relevant to OP, and Shapley additive explanations analysis was used to explain the contribution and the influence direction of the features on the model. Based on the selected 20 metabolites, the metabolic pathways most related to OP in plants, including alkaloid synthesis and amino acids metabolism, were identified. Compared to the plant physiological indices, OP is a more stable and faster indicator for the plant risk assessment of heavy metals contaminated soil.

Machine learning–based identification of a metabolic gene prognostic signature (MALMPS) model to investigate the clinical and molecular heterogeneity of stage II/III colorectal cancer.

e15548 Background: Colorectal cancer (CRC) is a frequently lethal disease with heterogeneous outcomes, and stage II/III CRC accounts for nearly 70%. Metabolic reprogramming was associated with cancer progression. Methods: We utilized nine datasets and a machine learning framework with 83 algorithm combinations to develop a robust prognostic signature. The in-house SDPH dataset were used for transcriptomic, metabolomics and spatial metabolomics analyses. Results: The combination of the random survival forest and generalized boosted regression modeling machine learning algorithms yielded the MAchine Learning-based Metabolic gene Prognostic Signature (MALMPS) model, comprising 21 metabolic gene as independent variables. The MALMPS model outperformed traditional clinical traits and molecular features in prognostic prediction, achieving an average C-index of 0.862 ( 95%CI : 0.841-0.882) in the training dataset and 0.687 ( 95%CI : 0.677-0.707) in the validation datasets. We stratified the CRC patients into the high- and low-risk groups based on the median cutoff of the MALMPS. Notably, the high-risk subgroup exhibited poor prognosis, inflammation activation, and enriched carbohydrate, glycosaminoglycan, and lipid metabolism. In contrast, the low-risk group displayed a higher mutation frequency in TGF-β pathway, and enrichment in nucleotides, cofactors, and amino acids metabolism. Metabolites profiling in the SDPH dataset further validated the distinct metabolic alterations between the high- and low-risk groups. COX7B, identified as playing a vital role in the MALMPS, was demonstrated to promote the malignant behavior of CRC by multi-omics analysis and in vitro assays. Drug sensitivity analysis revealed the potential of targeting the IGF-1R and Wnt/β-catenin for treating high-risk samples. Finally, the nomogram constructed incorporating MALMPS and molecular features shows strong performance in the validation datasets. Conclusions: The findings indicate that MALMPS might be a valuable instrument for predicting the recurrence risk of stage II/III colorectal cancer, particularly for identifying individuals at high risk.

Transcriptional signatures associated with the survival of Escherichia coli biofilm during treatment with plasma-activated water.

Transcriptional signatures associated with the survival of Escherichia coli biofilm during treatment with plasma-activated water.

Prodigiosin inhibits proliferation and induces apoptosis through influencing amino acid metabolism in multiple myeloma.

Prodigiosin inhibits proliferation and induces apoptosis through influencing amino acid metabolism in multiple myeloma.

Uncovering the crucial metabolic pathways in the invasive plant Hydrocotyle verticillata for defence against copper exposure by integrative transcriptome and metabolome analysis.

Uncovering the crucial metabolic pathways in the invasive plant Hydrocotyle verticillata for defence against copper exposure by integrative transcriptome and metabolome analysis.

Time- and concentration-dependent metabolic responses reveal adaptation failure in cadmium-exposed Haliotis diversicolor.

Time- and concentration-dependent metabolic responses reveal adaptation failure in cadmium-exposed Haliotis diversicolor.

Metabolic disruptions induced by low concentrations of DMSO in RTgill-W1 fish cells: The importance of solvent controls in in vitro studies.

Metabolic disruptions induced by low concentrations of DMSO in RTgill-W1 fish cells: The importance of solvent controls in in vitro studies.

A metabolomics and proteomics-based study on the metabolic effects of arecoline on the liver.

A metabolomics and proteomics-based study on the metabolic effects of arecoline on the liver.

The bridging role of soil organic carbon in regulating bacterial community by microplastic pollution: Evidence from different microplastic additions.

The bridging role of soil organic carbon in regulating bacterial community by microplastic pollution: Evidence from different microplastic additions.

The imidazoline I2 receptor agonist 2-BFI enhances cytotoxic activity of hydroxychloroquine by modulating oxidative stress, energy-related metabolism and autophagic influx in human colorectal adenocarcinoma cell lines.

The imidazoline I2 receptor agonist 2-BFI enhances cytotoxic activity of hydroxychloroquine by modulating oxidative stress, energy-related metabolism and autophagic influx in human colorectal adenocarcinoma cell lines.