Targeted Metabolic Pathways Analysis Service
Targeted metabolomics, as implemented by Creative Proteomics, focuses on specific metabolites and their pathways. Coupling this approach with metabolic flux analysis techniques, such as stable isotope labeling and tracing, enables high-sensitivity, high-precision quantitative analyses of metabolic pathways. This capability offers a robust tool for researchers engaged in mechanistic studies.
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- Background
- Service Offering
- Bioinformatics
- Advantage
- Platforms
- Sample Requirements
- Application
- Case Study
Exploring the Significance of Metabolic Pathway Analysis
Metabolic pathways constitute the fundamental networks for the transformation of substances and energy within organisms, and their dynamic alterations directly reflect the physiological status and pathological responses of cells, tissues, or whole organisms. Precise analysis of changes in the activity of these pathways can illuminate pivotal scientific questions regarding disease mechanisms, drug targets, and responses to environmental stresses. While traditional untargeted metabolomics can provide broad coverage of metabolites, it often lacks the sensitivity and quantitative accuracy necessary for in-depth characterization of the dynamic features of specific pathways. Through precise analysis of key metabolic nodes, the following can be elucidated:
Disease Mechanisms:
Insights into the Warburg effect in tumors, mitochondrial dysfunction in neurodegenerative diseases, and insulin resistance pathways in metabolic syndrome.
Drug Development:
Involves target selection and monitoring of toxic metabolite accumulation.
Environmental Responses:
Regulation of secondary metabolites in plants under stress conditions.
Comparison of Technical Advantages
| Analysis Type | Targeted Metabolomics | Untargeted Metabolomics |
|---|---|---|
| Sensitivity | Achieves fmol level (10-100 fold increase) | Typically μmol-mmol level |
| Quantitative Precision | Coefficient of Variation (CV) < 5% (isotope internal standard correction) | CV > 15% |
| Throughput | Accurate analysis of 300+ pathway-related metabolites | Detection of 1000+ unknown metabolites |
| Application Scenarios | Mechanistic studies, biomarker validation | Exploratory research |
This comparison highlights the specific strengths of targeted metabolomics in providing high sensitivity and precision, ideal for mechanistic studies and biomarker verification, whereas untargeted metabolomics is better suited for exploratory research by enabling broad detection of metabolites.
Service Offerings
Targeted Metabolic Pathway Analysis
Analytical Coverage:
Perform both qualitative and quantitative analyses of key metabolites within targeted metabolic pathways, including but no limited amino acids, organic acids, carbohydrates, and lipid intermediates.
| Category | Pathways |
|---|---|
| Common Pathways Covered | Energy Metabolism: Glycolysis Pathway, Tricarboxylic Acid (TCA) Cycle, Oxidative Phosphorylation, Central Carbon Metabolism, Pentose Phosphate Pathway |
| Amino Acid Metabolism: Glutamine Metabolism , Arginine Metabolism, Tryptophan Metabolism | |
| Lipid Metabolism: Fatty Acid β-Oxidation, Ketogenesis, Mevalonate Pathway | |
| One-carbon Metabolism: Methionine Cycle, Folate Cycle | |
| Nucleotide Metabolism: Purine/Pyrimidine Synthesis, Urea cycle Metabolism | |
| Isoprenoid Biosynthesis, Carnitine Biosynthesis | |
| Secondary Metabolism: Polyamines, Flavonoids, Plant Hormone Pathways | |
| Specialized Pathways | Tumor Microenvironment: Lactate Shuttle, Nucleotide Salvage Synthesis |
| Neuroscience: Neurotransmitter Metabolism (Dopamine/Serotonin/GABA) | |
| Plant Physiology: Jasmonic Acid/Salicylic Acid Signaling Pathways, Flavonoid Synthesis |
Metabolic Flux Analysis
- Use of stable isotope labeling (e.g., ¹³C, ¹⁵N) to trace the dynamic flow of metabolites, allowing for real-time pathway activity elucidation.
Bioinformatics Platform Advanced Analysis
Core Features:
- Pathway Enrichment Analysis:
- Utilize KEGG/MetaCyc databases with Fisher's exact test (p<0.01) to identify significant pathways.
- Visualization Tools: Sunburst plots display hierarchical pathway structures, with color gradients mapping log(p-value).
- Interactive Pathway Maps:
- Dynamic display of metabolite-enzyme-cofactor interaction networks.
- Support for clickable views to examine metabolite concentrations, isotope labeling rates, and other parameters.
- Disease Association Analysis:
- Sankey diagrams reveal the strength of associations between metabolic pathways and diseases (e.g., tumor metabolic reprogramming and chemotherapy resistance).
- Database Integration: Annotation of disease-related pathways utilizing OMIM, DisGeNET.
Data Integration and Visualization
- Provision of metabolic pathway maps, heatmaps, and metabolic flux network diagrams to support the understanding of pathway regulation.
Software Tools:
- Quantitative Analysis: Skyline, MultiQuant
- Metabolic Flux Modeling: INCA, OpenFLUX
- Databases: HMDB, KEGG, MassBank
The workflow of the pathway-based metabolomics data analysis. (Sijia Huang et al., 2016)
Enhanced Service Advantages
- In-depth Analysis: Leverage metabolic flux analysis to illuminate the dynamic activity of metabolic pathways.
- Customized Services: Tailor metabolite panels and labeling experiment schemes according to research objectives.
- Professional Team: Technical support provided by a team of metabolomics Ph.Ds and mass spectrometry engineers.
- Precision Quantification:
Employ isotope dilution methods to achieve pg-level detection sensitivity.
Dynamic range spanning four orders of magnitude (1 nM - 10 μM). - Cross-species Compatibility:
Human/Animal: Specialized panels for the tumor microenvironment and neurodegenerative diseases.
Plant: Pathways relevant to stress physiology and secondary metabolite synthesis.
Microbial: Analysis of electron transport chains and quorum sensing-related metabolism.
Analytical Platforms
Instrument Platforms:
- High-resolution mass spectrometers (e.g., Thermo Scientific Q Exactive HF-X, Sciex TripleTOF 6600)
- Ultrahigh-Performance Liquid Chromatography (UHPLC; Waters ACQUITY UPLC), Gas Chromatography (GC; Agilent 7890B)
Sample Requirements
| Sample Type | Minimum Sample Size | Sample Preparation Requirements | Recommended Storage Conditions |
|---|---|---|---|
| Cultured Cells | (1 \times 10^6) cells | After collection, wash cells with phosphate-buffered saline (PBS) and lyse to release metabolites. | Long-term storage at -80°C |
| Primary Mouse Cells (Cultured/Uncultured) | (1 \times 10^6) cells | Follow the same procedure as cultured cells: collect, wash with PBS, and lyse. | Long-term storage at -80°C |
| Tissue (e.g., liver, heart, brain) | 50-100 mg | Homogenize tissue using an appropriate buffer, followed by metabolite extraction. | Long-term storage at -80°C |
| Serum/Plasma | 200 µL | Centrifuge at 3000 RPM for 10 minutes to separate serum/plasma, avoiding the use of anticoagulants. | Long-term storage at -80°C |
| Biological Fluids (e.g., urine, bile) | 500 µL | After collection, centrifuge to remove particulates. | Long-term storage at -80°C |
| Thioglycollate-Induced Macrophages | (1 \times 10^6) cells | Collect cells post-thioglycollate injection; follow cultured cell procedure (PBS wash and lysis). | Long-term storage at -80°C |
Metabolic Pathway Metabolomics Service: Applications Across Diverse Fields
Metabolomics analysis of metabolic pathways has extensive applicability across multiple domains. By integrating various technological platforms and databases, it facilitates the elucidation of dynamic changes within biological systems at the metabolic network level.
Disease Research
Disease Biomarker Discovery
Metabolomics enables the identification of disease-specific metabolic biomarkers through the analysis of metabolite profiles in biofluids such as blood and urine. Notable examples include:
- In the early diagnosis of liver cancer, glycocholic acid and phenylacetylglutamine have been validated as potential biomarkers.
- In cardiovascular disease research, the gut microbiota-derived metabolite PAGln influences thrombosis via modulation of adrenergic receptors and serves as a therapeutic target.
Disease Subtype Classification and Prognostic Assessment
Metabolic pathway enrichment analysis can differentiate disease subtypes (e.g., different stages of cancer) and predict patients' responses to treatment. For instance, the KEGG pathway analysis, in conjunction with pathway impact topology weights, facilitates the identification of critical pathways, thereby supporting clinical decision-making.
Guidance for Personalized Medicine
Metabolomics data can inform individualized medication strategies, such as optimizing drug dosages through metabolic enzyme activity analysis or adjusting treatment regimens based on metabolite feedback.
Agriculture and Plant Science
Analysis of Stress Resistance Metabolic Pathways
The integration of multi-omics technologies (genomics + metabolomics) reveals the metabolic regulatory networks plants utilize to cope with environmental stresses (e.g., drought, salinity). The synthesis pathway analysis of secondary metabolites like phenolics and alkaloids aids in developing stress-resistant crops.
Crop Quality Improvement
Metabolic pathway analysis can identify key metabolites influencing agronomic traits (e.g., sugar and vitamin content), guiding gene editing or breeding optimization. For example, metabolites related to the tricarboxylic acid (TCA) cycle are closely associated with crop yield.
Drug Development and Mechanistic Studies
Drug Target Discovery
Metabolomics, combined with functional validations (e.g., gene knockout, enzyme inhibitor treatment), can pinpoint critical regulatory nodes. For instance, the arachidonic acid pathway catalyzed by the CYP450 enzymes has been identified as a novel drug target for colon cancer treatment.
Efficacy and Toxicity Evaluation
By analyzing the dynamic changes in metabolic pathways following drug intervention, researchers can assess therapeutic efficacy and side effects. Metabolic flux analysis, for instance, is employed to track a drug's impact on lipid metabolism.
Environmental Monitoring and Ecological Research
Pollutant Metabolic Impact Assessment
Metabolomics can detect the toxic effects of environmental pollutants (e.g., heavy metals, organic pollutants) on organisms, revealing disrupted metabolic pathways such as oxidative stress and energy metabolism disorders.
Dynamic Analysis of Ecosystem Metabolism
Metabolomics analysis of soil or water samples aids in assessing ecosystem health status and the functionality of microbial communities.
Fundamental Research and Multi-Omics Integration
Construction and Functional Analysis of Metabolic Networks
Utilizing databases like KEGG to map metabolic pathways, combined with topological analysis (e.g., degree centrality), helps pinpoint core metabolites and elucidates their regulatory roles within biological systems.
Integrated Omics Analysis
The integration of metabolomics with genomic and transcriptomic data allows for a systematic analysis of complex metabolic regulatory mechanisms. For example, the correlation analysis between gene expression and metabolite accumulation in plant natural product synthesis pathways validates the functional roles of key enzymes.
Case Study
Metabolic remodelling during early mouse embryo development. Zhang et al. (2021).
Nature Metabolism
DOI: 10.1038/s42255-021-00464-x
- Research Background
- Methods and Techniques
- Key Findings
- Biological Significance
Early embryonic development in mammals entails a complex interplay among cell division, epigenetic reprogramming, and metabolic regulation. The study of these processes is often hindered by the limited sample size available for early embryonic stages, typically consisting of only a few hundred cells. Conventional metabolomics techniques falter in detecting low-abundance metabolites due to this constraint. The research team led by Hu Zeping at Tsinghua University has overcome this limitation by developing an ultrasensitive targeted metabolomics technology. This innovation has enabled a systematic delineation of dynamic metabolic pathways within mouse embryos for the first time.
- Targeted Metabolomics:
- Sample Size: A mere 100 mouse embryos are required, as opposed to the millions of cells necessitated by traditional methodologies.
- Technology Platform: The combination of Liquid Chromatography-Mass Spectrometry/Mass Spectrometry (LC-MS/MS) with novel derivatization strategies enhances detection sensitivity by an order of magnitude (10x).
- Pathway Coverage: Includes the tricarboxylic acid (TCA) cycle, amino acid metabolism (e.g., methionine, spermidine/spermine), and nucleotide metabolism.
Metabolic Pathway Variations:
- Two-cell Stage Embryos: There is heightened activity in methionine metabolism and the niacinamide pathway.
- Blastocyst Stage: Upregulation of the TCA cycle and purine synthesis pathways is observed, along with an elevated level of α-ketoglutarate.
Regulatory Role of L-2-Hydroxyglutarate (L-2-HG):
- L-2-HG reaches millimolar concentrations in oocytes and diminishes progressively during embryonic development.
- Exogenous L-2-HG impedes embryonic development by hindering histone H3K4me3 demethylation, likely through inhibition of α-ketoglutarate (α-KG)-dependent epigenetic enzymes.
This study elucidates the molecular mechanisms by which metabolites can influence embryonic development through epigenetic regulation. Additionally, it provides theoretical support for the optimization of nutritional conditions in assisted reproductive technologies, including in vitro fertilization.
