Medicinal fungi Phellinus igniarius exhibited hypoglycemic effects; however, the protective mechanisms of P. igniarius on type 2 diabetes are not yet fully understood. Herein, the anti-diabetic effect of P. igniarius was investigated via gas chromatography-mass spectrometry (GC/MS)-based metabolome analysis. The rats were divided into normal group; model group; positive group; and groups treated with low, medium, and high dose of P. igniarius. After the treatments, a significant decrease in blood glucose concentration was observed. The levels of total cholesterol and triglyceride were dramatically decreased, whereas the level of insulin was increased. Multivariate statistical analysis revealed 31 differential endogenous metabolites between model group and normal group. A total of 14, 28, and 31 biomarkers were identified for low, medium, and high dose of P. igniarius treated groups, respectively. Twenty-one of the biomarkers were validated by using standard substances. The linear correlation coefficients ranged from 0.9990 to 1.0000. The methodology exhibited good repeatability, recoveries, and stability. The major intervened metabolic pathways covered glyoxylate and dicarboxylic acid metabolism; alanine, aspartate, and glutamate metabolism; and glycine, serine, and threonine metabolism. Our metabolome analysis has provided insights into the underlying mechanism of P. igniarius on type 2 diabetes.

Immunometabolism has been an emerging hotspot in the fields of tumors, obesity, and atherosclerosis in recent decades, yet few studies have investigated its connection with rheumatoid arthritis (RA). In principle, intracellular metabolic pathways upstream regulated by nutrients and growth factors control the effector functions of immune cells. Dynamic communication and hypermetabolic lesions of immune cells within the inflammatory synovial microenvironment contributes to the development and progression of RA. Hence, targeting metabolic pathways within immune subpopulations and pathological cells may represent novel therapeutic strategies for RA. Natural products constitute a great potential treasury for the research and development of novel drugs targeting RA. Here, we aimed to delineate an atlas of glycolysis, lipid metabolism, amino acid biosynthesis, and nucleotide metabolism in the synovial microenvironment of RA that affect the pathological processes of synovial cells. Meanwhile, therapeutic potentials and pharmacological mechanisms of natural products that are demonstrated to inhibit related key enzymes in the metabolic pathways or reverse the metabolic microenvironment and communication signals were discussed and highlighted.

BACKGROUND: Although it is traditionally believed that ATP binding cassette subfamily C member 2 (ABCC2) is a multidrug resistance-associated protein correlated with a worse prognosis, our previous and several other studies demonstrated the contrary to be true in gastric cancer (GC). We aim to explore the underlying mechanism of this discovery.
METHODS: Our study utilized whole-exome sequencing (WES), RNA sequencing, and droplet digital PCR (ddPCR) analysis of 80 gastric cancer samples, along with comprehensive immunohistochemical (IHC) analysis of 1044 human GC tissue samples.By utilizing CRISPRCas9 to genetically modify cell lines with the ABCC2-24C > T (rs717620) point mutation and conducting dual-luciferase reporter assays, we identified that transcription factors SOX9 and ETS1 serve as negative regulators of ABCC2 expression. Seahorse assay and mass spectrometry were used to discover altered metabolic patterns. Gain and loss-of-function experiments in GC cell lines and preclinical models were carried out to validate ABCC2 biological function.
RESULTS: ABCC2 high expression correlated with better prognosis, and rs717620 can influence ABCC2 expression by disrupting the binding of ETS1 and SOX9. Gain and loss-of-function experiments in GC cell lines demonstrated amino acid deprivation reduces proliferation, migration, and drug resistance in ABCC2-high GC cells. ABCC2 leads to reduced intracellular amino acid pools and disruption of cellular energy metabolism. This phenomenon depended on ABCC2-mediated GSH extrusion, resulting in alterations in redox status, thereby increasing the cell\'s susceptibility to ferroptosis. Furthermore, patient-derived organoids and patient-derived tumor-like cell clusters were used to observe impact of ABCC2 on therapeutic effect. In the xenograft model with high ABCC2 expression, we observed that constricting amino acid intake in conjunction with GPX4 inactivation resulted in notable tumor regression.
CONCLUSIONS: Our findings demonstrate a significant role of ABCC2 in amino acid metabolism and ferroptosis by mediating GSH efflux in GC. This discovery underlines the potential of combining multiple ferroptosis targets as a promising therapeutic strategy for GC with high ABCC2 expression.
CONCLUSIONS: ABCC2 plays a crucial role in inducing metabolic vulnerability and ferroptosis in gastric cancer through enhanced glutathione efflux. The ABCC2 24C > T polymorphism is a key factor influencing its expression. These results highlight the potential of ABCC2 as a predictive biomarker and therapeutic target in gastric cancer.

The human endometrial decidualization is a transformative event in the pregnant uterus that involves the differentiation of stromal cells into decidual cells. While crucial to the establishment of a successful pregnancy, the metabolic characteristics of decidual cells in vivo remain largely unexplored. Here, we integrated the single-cell RNA sequencing (scRNA-seq) datasets on the endometrium of the menstrual cycle and the maternal-fetal interface in the first trimester to comprehensively decrypt the metabolic characteristics of stromal fibroblast cells. Our results revealed that the differentiation of stromal cells into decidual cells is accompanied by increased amino acid and sphingolipid metabolism. Furthermore, metabolic heterogeneity exists in decidual cells with differentiation maturity disparities. Decidual cells with high metabolism exhibit higher cellular activity and show a strong propensity for signaling. In addition, significant metabolic reprogramming in amino acids and lipids also occurs during the transition from non-pregnancy to pregnancy in the uteri of pigs, cattle, and mice. Our analysis provides comprehensive insights into the dynamic landscape of stromal fibroblast cell metabolism, contributing to our understanding of the metabolism at the molecular dynamics underlying the decidualization process in the human endometrium.

Current kidney perfusion protocols are not optimized for addressing the ex vivo physiological and metabolic needs of the kidney. Ex vivo normothermic perfusion may be utilized to distinguish high-risk kidneys to determine suitability for transplantation. Here, we assessed the association of tissue metabolic changes with changes in a kidney injury biomarker and functional parameters in eight deceased donor kidneys deemed unsuitable for transplantation during a 12-hour ex vivo normothermic perfusion. The kidneys were grouped into good and poor performers based on blood flow and urine output. The mean age of the deceased kidney donors was 43 years with an average cold ischemia time of 37 hours. Urine output and creatinine clearance progressively increased and peaked at six hours post-perfusion among good performers. Poor performers had 71 ng/ml greater (95% confidence interval 1.5, 140) urinary neutrophil gelatinase-associated lipocalin at six hours compared to good performers corresponding to peak functional differences. Organ performance was distinguished by tissue metabolic differences in branched chain amino acid metabolism and that their tissue levels negatively correlated with urine output among all kidneys at six hours. Tissue lipid profiling showed poor performers were highlighted by the accumulation of membrane structure components including glycerolipids and sphingolipids at early perfusion time points. Thus, we showed that six hours is needed for kidney function recovery during ex vivo normothermic perfusion and that branched chain amino acid metabolism may be a major determinant of organ function and resilience.

Rhizobium leguminosarum aspartate aminotransferase (AatA) mutants show drastically reduced symbiotic nitrogen fixation in legume nodules. Whilst AatA reversibly transaminates the two major amino-donor compounds aspartate and glutamate, the reason for the lack of N2 fixation in the mutant has remained unclear. During our investigations into the role of AatA, we found that it catalyses an additional transamination reaction between aspartate and pyruvate, forming alanine. This secondary reaction runs at around 60 % of the canonical aspartate transaminase reaction rate and connects alanine biosynthesis to glutamate via aspartate. This may explain the lack of any glutamate-pyruvate transaminase activity in R. leguminosarum, which is common in eukaryotic and many prokaryotic genomes. However, the aspartate-to-pyruvate transaminase reaction is not needed for N2 fixation in legume nodules. Consequently, we show that aspartate degradation is required for N2 fixation, rather than biosynthetic transamination to form an amino acid. Hence, the enzyme aspartase, which catalyses the breakdown of aspartate to fumarate and ammonia, suppressed an AatA mutant and restored N2 fixation in pea nodules.

Amino acid metabolism plays a pivotal role in tumor microenvironment, influencing various aspects of cancer progression. The metabolic reprogramming of amino acids in tumor cells is intricately linked to protein synthesis, nucleotide synthesis, modulation of signaling pathways, regulation of tumor cell metabolism, maintenance of oxidative stress homeostasis, and epigenetic modifications. Furthermore, the dysregulation of amino acid metabolism also impacts tumor microenvironment and tumor immunity. Amino acids can act as signaling molecules that modulate immune cell function and immune tolerance within the tumor microenvironment, reshaping the anti-tumor immune response and promoting immune evasion by cancer cells. Moreover, amino acid metabolism can influence the behavior of stromal cells, such as cancer-associated fibroblasts, regulate ECM remodeling and promote angiogenesis, thereby facilitating tumor growth and metastasis. Understanding the intricate interplay between amino acid metabolism and the tumor microenvironment is of crucial significance. Expanding our knowledge of the multifaceted roles of amino acid metabolism in tumor microenvironment holds significant promise for the development of more effective cancer therapies aimed at disrupting the metabolic dependencies of cancer cells and modulating the tumor microenvironment to enhance anti-tumor immune responses and inhibit tumor progression.

The Brazilian Atlantic Forest, renowned for its exceptional species richness and high endemism, acts as a vital reservoir of terrestrial biodiversity, often referred to as a biodiversity hotspot. Consequently, there is an urgent need to restore this forest to safeguard certain species and to unravel the ecophysiological adaptations of others. This study aims to integrate some physiological parameters, including gas exchange and chlorophyll a fluorescence, with anatomical and metabolic techniques to elucidate how five different native species (Paubrasilia echinata, Chorisia glaziovii, Clusia nemorosa, Licania tomentosa, and Schinus terebinthifolius), each occupying distinct ecological niches, respond to seasonal variations in rainfall and their consequences. Our investigation has revealed that C. nemorosa and P. echinata exhibit robust mechanisms to mitigate the adverse effects of drought. In contrast, others demonstrate greater adaptability (e.g., S. terebinthifolia and C. glaziovii). In this context, exploring metabolic pathways has proven invaluable in comprehending the physiological strategies and their significance in species acclimatization. This study provides a comprehensive overview of the impact of water restrictions and their consequential effects on various species, defining the strategies each species uses to mitigate water privation during the dry season.

Spinal echinococcosis is one of the most overlooked zoonotic parasitic diseases worldwide. There is currently no safe and effective treatment to eradicate it, and research based on the physiological-metabolic signature of the disease is lacking. Herein, we repurposed agrimol B as a potent anti-hydatid compound and validated its pharmacological mechanism based on arginine uptake as a target through multi-omics sequencing. This herbal component suppressed energy metabolism and activated ROS aggregation by inducing mitochondrial membrane potential depolarization, which subsequently triggered autophagy-dependent apoptosis leading to parasite death. Moreover, we discovered that arginine deprivation induced metabolic changes led to a shift from ornithine to nitrogen oxide synthesis, thus boosting the iNOS enzyme-regulated dominant metabolic pathway. The excess NO targeted the mitochondrial respiratory chain complex IV to disrupt energy metabolic homeostasis and induced a downstream pathological waterfall effect to kill the hydatid. A novel metabolic regulatory mechanism targeting mitochondrial damage for arginine starvation therapy was discovered. Finally, arginine depletion was found to be superior to the anti-spinal echinococcosis effect of albendazole and accompanied by the potential for disc protection. This study unveils the role of arginine in the physiological metabolism of Echinococcus granulosus and reveals the value of targeting arginine metabolism as a potential therapy. In addition, agrimol B is proposed as a promising therapeutic strategy for spinal echinococcosis to block arginine uptake and break this parasite\'s metabolic balance.

Accurate assessment of future liver remnant growth after partial hepatectomy (PH) in patients with different liver backgrounds is a pressing clinical issue. Amino acid (AA) metabolism plays a crucial role in liver regeneration. In this study, we combined metabolomics and machine learning (ML) to develop a generalized future liver remnant assessment model for multiple liver backgrounds. The liver index was calculated at 0, 6, 24, 48, 72 and 168 h after 70 % PH in healthy mice and mice with nonalcoholic steatohepatitis or liver fibrosis. The serum levels of 39 amino acids (AAs) were measured using UPLC-MS/MS. The dataset was randomly divided into training and testing sets at a 2:1 ratio, and orthogonal partial least squares regression (OPLS) and minimally biased variable selection in R (MUVR) were used to select a metabolite signature of AAs. To assess liver remnant growth, nine ML models were built, and evaluated using the coefficient of determination (R2), mean absolute error (MAE), and root mean square error (RMSE). The post-Pareto technique for order preference by similarity to the ideal solution (TOPSIS) was employed for ranking the ML algorithms, and a stacking technique was utilized to establish consensus among the superior algorithms. Compared with those of OPLS, the signature AAs set identified by MUVR (Thr, Arg, EtN, Phe, Asa, 3MHis, Abu, Asp, Tyr, Leu, Ser, and bAib) are more concise. Post-Pareto TOPSIS ranking demonstrated that the majority of ML algorithm in combinations with MUVR outperformed those with OPLS. The established SVM-KNN consensus model performed best, with an R2 of 0.79, an MAE of 0.0029, and an RMSE of 0.0035 for the testing set. This study identified a metabolite signature of 12 AAs and constructed an SVM-KNN consensus model to assess future liver remnant growth after PH in mice with different liver backgrounds. Our preclinical study is anticipated to establish an alternative and generalized assessment method for liver regeneration.