- Untargeted Metabolomics
- Lipidomics
- Targeted Metabolomics
- Functional Metabolomics
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Proteomics
- Nanoparticle proteomics
- iTRAQ/TMT-based Proteomics Analysis
- Label free Quantitative Proteomics
- Protein Identification
- DIA proteomics
- Peptidomics
- Parallel Reaction Monitoring (PRM) Targeted Proteome
- Metpro -Ⅱ Protein-Metabolite Interactions
- Phosphoproteomics
- Acetylation Analysis
- Protein Ubiquitination Analysis
Non target isotope tracing analysis
Classical metabolomics can reflect changes in the body's metabolites and potentially activated pathways. However, a limitation arises when the same metabolite participates in multiple pathways without a change in abundance. Metabolic networks are complex and dynamically changing, and classical metabolomics can only provide static information on metabolite abundance. To overcome this limitation, metabolic pathway analysis technology proves valuable. In our pursuit to gain a deeper understanding of cellular metabolism, we employ various omics tools, including genomics, metagenomics, transcriptomics, proteomics, and metabolomics.
However, existing omics technologies fall short in fully capturing post-transcriptional regulation, enzyme activity, and cellular processes. To address this, the concept of fluxomics, which comprehensively studies the flow rates of all metabolites, has been proposed. This allows for a detailed description of cellular metabolic activity during physiological processes.
Technical Advantages:
- High resolution: Can distinguish between isotopically labeled and unlabeled metabolites.
- Non-targeted pathway analysis, unlike targeted metabolic pathway, is not limited to specific metabolic pathways, allowing for directional analysis of labeled metabolites.
Application Directions:
- Non-targeted metabolic pathway analysis finds extensive applications in life sciences and pharmaceutical research. These include cellular metabolism regulation, discovery of new metabolic pathways, understanding disease metabolism mechanisms, identification and validation of new drug targets, drug efficacy and toxicity evaluation, disease diagnosis or prognosis biomarkers, drug metabolism, and precision medicine.
- Genetic engineering: Enhancing the production of target metabolites in genetically engineered bacteria and understanding changes in metabolic function before and after genetic modification.
- Disease mechanisms: Revealing personalized treatment mechanisms for tumor metabolism inhibitors and identifying early diagnostic markers for disease development processes.
- Metabolic reprogramming: Studying the mechanisms of immune metabolic reprogramming in inflammatory macrophages and chloroplast metabolic reprogramming in plants.
Collaborative Cases:
- "Exogenous fatty acid renders improved salt tolerance in Zygosaccharomyces rouxii by altering lipid metabolism" (2023) LWT - Food Science and Technology. (IF=6.056) [Customer's Publication]
- "Metabolites and metabolic pathways associated with allelochemical effects of linoleic acid on Karenia mikimotoi" (2023) Journal of Hazardous Materials. (IF=13.224) [Customer's Publication]
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