Energy Metabolism
What Is Energy Metabolism Targeted Metabolomics?
Why Choose MetwareBio for Energy Metabolism Profiling?
Energy Metabolism Coverage: 80 Metabolites Across Central Carbon Pathways
| Coverage Area | Representative Metabolites | Research Value |
|---|---|---|
| Glycolysis and Pyruvate Metabolism | Glucose, glucose-6-phosphate, fructose-6-phosphate, fructose-1,6-bisphosphate, glyceraldehyde-3-phosphate, 3-phosphoglycerate, phosphoenolpyruvic acid, pyruvic acid, lactate | Evaluate glycolytic activity, anaerobic glycolysis, pyruvate utilization, and metabolic reprogramming |
| TCA Cycle and Mitochondrial Organic Acids | Citric acid, isocitric acid, cis-aconitic acid, α-ketoglutaric acid, succinic acid, fumaric acid, malic acid, oxaloacetate, acetyl-CoA, succinyl-CoA | Assess TCA cycle activity, mitochondrial metabolism, anaplerosis, and central carbon flux-related remodeling |
| Pentose Phosphate Pathway and Sugar Phosphates | 6-phosphogluconic acid, erythrose-4-phosphate, ribose-5-phosphate, ribulose-5-phosphate, xylulose-5-phosphate, sedoheptulose-7-phosphate, NADPH | Interpret PPP regulation, redox balance, NADPH production, nucleotide precursor supply, and biosynthetic metabolism |
| Energy-Related Nucleotides and Redox Cofactors | ATP, ADP, AMP, adenine, inosine, guanosine, cAMP, GDP, GTP, IMP, UMP, NAD, NADPH, flavin mononucleotide | Support evaluation of cellular energy status, purine and pyrimidine metabolism, oxidative phosphorylation-related changes, and redox regulation |
| Amino Acid-Linked Energy Metabolism | Serine, glutamic acid, glutamine, alanine, aspartate, threonine, lysine, tyrosine, arginine, ornithine, leucine, citrulline, cystine | Connect amino acid utilization with central carbon metabolism, nitrogen balance, anaplerotic input, and stress-related metabolic adaptation |
| Energy-Associated Organic Acids and Carbohydrate Metabolites | 3-phenyllactic acid, itaconic acid, 2-hydroxyglutaric acid, glycolic acid, glyceric acid, gluconate, glucuronic acid, ureidopropionate, cysteic acid | Capture broader energy-linked metabolic changes related to organic acid turnover, carbohydrate metabolism, immune-metabolic regulation, and pathway crosstalk |
Project Workflow of Energy Metabolism Profiling
Energy Metabolism Data Analysis and Deliverables
MetwareBio provides complete deliverables for energy metabolism targeted metabolomics, including absolute concentration tables, assay calibration information, quality control summaries, differential metabolite analysis, pathway annotation, and a structured project report. These outputs support energy metabolism biomarker discovery, pathway validation, mitochondrial function studies, and quantitative comparison across experimental groups. Visualization results may include PCA plots, volcano plots, heatmaps, correlation analysis, bar charts, KEGG pathway annotation, and KEGG enrichment analysis, depending on the number of quantified metabolites, project design, and statistical outcomes. Contact Us for Demo
Project Experience in Energy Metabolism Profiling
Applications of Energy Metabolism Analysis
Energy metabolism targeted metabolomics is widely used to investigate glycolytic reprogramming, TCA cycle remodeling, oxidative stress, and altered nutrient utilization in cancer. Quantitative profiling of central carbon metabolites helps reveal tumor metabolic vulnerabilities and evaluate treatment-induced metabolic responses.
Altered energy metabolism is closely associated with mitochondrial dysfunction, obesity, diabetes, fatty liver disease, metabolic syndrome, and other disorders involving impaired energy homeostasis. Targeted quantification of glycolysis-, TCA cycle-, PPP-, nucleotide-, and amino acid-linked metabolites supports studies of mitochondrial metabolism, substrate utilization, insulin resistance, and systemic metabolic dysregulation.
Immune cell activation and inflammatory responses are tightly linked to glycolysis, mitochondrial metabolism, PPP activity, and redox regulation. Energy metabolism targeted metabolomics helps connect immune phenotypes with central carbon pathway activity and inflammation-associated metabolic remodeling.
Targeted energy metabolism profiling can evaluate how drugs, candidate compounds, dietary interventions, environmental factors, or disease models affect cellular and systemic energy pathways. This assay supports preclinical pharmacology, toxicology, nutritional studies, mechanism-of-action research, and intervention response evaluation.
Energy metabolism is central to plant growth, stress adaptation, carbon allocation, and cellular respiration. Targeted quantification of glycolysis, TCA cycle, PPP, nucleotide-related, and amino acid-linked energy metabolites supports studies of plant stress responses, crop physiology, nutrient utilization, and agricultural trait regulation.
Energy Metabolism Targeted Metabolomics Case Study
Case Study | Targeted Energy Metabolism Profiling Reveals Gut Microbiota–Energy Metabolism Regulation in Major Depressive Disorder
In a Gut Microbes study titled Gut microbiota reshapes host energy metabolism to modulate depressive behaviors, researchers integrated targeted metabolomics and shotgun metagenomics using samples from 100 major depressive disorder patients and 68 healthy controls to investigate how gut microbiota reshape host energy metabolism. The study found significant disturbances in central energy pathways, including glycolysis, the TCA cycle, and the ornithine cycle, which were associated with depressive symptoms and cognitive impairment. Targeted energy metabolism profiling identified altered metabolites such as lactate, L-glutamic acid, isocitric acid, L-citrulline, cyclic AMP, adenine, ornithine, and AMP, supporting the proposed "gut microbiota–energy metabolites–depressive phenotype" axis. Further validation in a chronic social defeat stress mouse model showed that fecal microbiota transplantation helped reverse stress-induced shifts toward anaerobic glycolysis and restore mitochondrial morphology in brain regions, demonstrating the value of targeted energy metabolism metabolomics for studying microbiota–host metabolic regulation, mitochondrial dysfunction, and neuropsychiatric disease mechanisms.
Sample Requirements for Energy Metabolism Analysis
| Sample Class | Sample Type | Recommended Sample Size | Minimum Sample Size |
| Liquid I | Plasma, serum, hemolymph, whole blood, milk, egg white | 100 μL | 20 μL |
| Liquid II | Cerebrospinal fluid (CSF), interstitial fluid (TIF), uterine fluid, pancreatic juice, bile, pleural effusion, follicular fluid, fallopian tube fluid, postmortem fluid, tissue fluid, culture medium (liquid), culture supernatant, fermentation broth, tears, aqueous humor, digestive juices, bone marrow (liquid) | 100 μL | 50 μL |
| Liquid III | Seminal plasma, amniotic fluid, prostatic fluid, rumen fluid, respiratory condensate, gastric lavage fluid, bronchoalveolar lavage fluid (BALF), urine, sweat, saliva, sputum | 500 μL | 50 μL |
| Tissue I | Small animal tissues, placenta, blood clot, mycelium, nematode, zebrafish whole fish, bone marrow solid sample, nail | 100 mg | 50 mg |
| Tissue II | Large animal tissues, whole insect body, insect wings, pupa, eggs, large fungi, large amount of fungal mycelium or mycelial balls, cartilage, bone solid sample | 500 mg | 50 mg |
| Tissue III | Zebrafish organs, insect organs, whole microinsect body such as Drosophila | 20 units | / |
| Tissue IV | Plant Tissue (Root, Stem, Leaf, Fruit, Flower, Bud, Node, Callus, Seed) | 300 mg | 200 mg |
| Solid I | Feces, intestinal contents, lyophilized fecal powder | 200 mg | 50 mg |
| Solid II | Milk powder, microbial fermentation product solid sample, culture medium solid sample, earwax, lyophilized tissue powder, feed, egg yolk powder, lyophilized plant powder, lyophilized egg powder | 100 g | 50 mg |
| Solid III | Honey, nasal mucus, sputum, fresh egg yolk | 2 g | 500 mg |
| Solid IV | Sludge, soil | 600 mg | 300 mg |
| Cell I | Adherent cells, animal cell lines | 1 × 10⁶ cells | 5 × 10⁵ cells |
| Cell II | E. coli, yeast cells | 1 × 10¹⁰ cells | 5 × 10⁸ cells |
| Cell III | Small amount of fungal mycelial balls or mycelium, cyanobacteria, large amount of bacteria pellet, slime mold, microbial sludge, dried microbial powder | 100 mg | / |
| Organelle I | Lysosomes, mitochondria, endoplasmic reticulum | 4 × 10⁷ cells or 0.2 g tissue |
1 × 10⁷ cells or 0.1 g tissue |
| Organelle II | Exosomes, extracellular vesicles | 2 × 10⁹ particles or 40 μg protein (BCA) |
1 × 10⁹ particles or 20 μg protein (BCA) |
| Special Sample I | Skin tape or patch | 2 pieces | 1 piece |
| Special Sample II | Test strips | 2 pieces | 1 piece |
| Special Sample III | Swab | 1 piece | 1 piece |
- A minimum of 3 biological replicates per group is required. For better statistical power, ≥30 biological replicates per group are recommended for human cohort studies, and 8–10 biological replicates per group are recommended for animal studies.
- Energy metabolites are sensitive to enzymatic activity and metabolic turnover. Fast quenching, consistent sampling time, rapid freezing, and standardized storage are important for reliable targeted metabolomics results.
FAQ on Energy Metabolism Targeted Metabolomics
Energy metabolism is the biological process by which cells convert nutrients such as glucose, fatty acids, and amino acids into ATP and metabolic intermediates required for cellular function. It involves interconnected pathways such as glycolysis, the TCA cycle, the pentose phosphate pathway (PPP), nucleotide metabolism, and mitochondrial energy metabolism. Changes in energy metabolism can reflect altered nutrient utilization, mitochondrial dysfunction, redox imbalance, stress responses, disease progression, or treatment effects.
MetwareBio’s energy metabolism targeted metabolomics assay uses LC-MS/MS in MRM mode to support sensitive detection of predefined energy-related metabolites. The workflow is designed for ng-level detection sensitivity, although the actual detection limit may vary depending on the metabolite, sample matrix, and sample amount. This sensitivity supports quantitative profiling of low-abundance central carbon metabolites in complex biological samples.
Accurate quantification is supported by compound-specific calibration, internal standard correction, and standardized LC-MS/MS data processing. Calibration curves are used to convert metabolite signals into concentration values, while internal standards help correct variation from sample preparation, injection, and instrument response. Quality control samples are included to monitor analytical stability, reproducibility, and batch consistency.
LC-MS/MS MRM improves specificity by monitoring optimized precursor-to-product ion transitions for predefined target metabolites. Combined with chromatographic retention time, standard-based method optimization, and ion transition matching, MRM detection helps reduce background interference and distinguish target metabolites from matrix-derived signals. This targeted approach is especially useful for reliable quantification of structurally related and low-abundance energy metabolites.
Energy metabolites are often labile and can change rapidly after sample collection due to ongoing enzymatic activity, temperature changes, ischemia, or delayed processing. Samples should be collected quickly, quenched or frozen as soon as possible, stored at −80°C, and shipped on dry ice. Consistent collection time, standardized handling, avoidance of repeated freeze-thaw cycles, and minimizing room-temperature exposure are critical for reliable energy metabolism targeted metabolomics results.
Reference
Lei, P., Qi, Z., Ma, Q., Zhao, B., Wen, B., Jiang, W., Xi, W., Liu, Y., Zhang, S., Wang, Y., Guo, Y., Wang, W., Ma, X., Jia, M., & Fan, Y. (2026). Gut microbiota reshapes host energy metabolism to modulate depressive behaviors. Gut Microbes, 18(1), 2662556. https://doi.org/10.1080/19490976.2026.2662556
