Metabolomics v-innovate Technologies

v-innovate Technologies Metabolomics

Acetyl-CoA Analysis Service

Acetyl-CoA Analysis Service

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v-innovate Technologies' targeted metabolomics services target specific metabolites and pathways of interest, which can accurately monitor dynamic metabolic processes, reveal related metabolic mechanisms and verify potential metabolic biomarkers, to guide your research with reliable and accurate measurement results.

About Acetyl-CoA

Acetyl-CoA is an important intermediate metabolite in the metabolism of energy substances, and it is a pivotal substance in the metabolism of energy substances in the body.

The three major nutrients of sugar, fat, and protein converge into a common metabolic pathway through acetyl-CoA-the tricarboxylic acid cycle and oxidative phosphorylation. Through this pathway, they are completely oxidized to produce carbon dioxide and water, releasing energy for the synthesis of ATP.

Acetyl-CoA is a precursor material for the synthesis of energy substances such as fatty acids and ketone bodies, and a precursor material for the synthesis of physiologically active substances such as cholesterol and its derivatives.

Its chemical formula is C23H38N7O17P3S, and CAS number is 72-89-9.

MS-based technical means can realize the qualitative and quantitative analysis of acetyl-CoA.

Molecular structure of acetyl-CoAMolecular structure of acetyl-CoA

Technical Route of Targeted Metabolomics of Acetyl-CoA

Technical Route of Targeted Metabolomics of Acetyl-CoA

Sample Requirements

Sample type
Plants, yeasts, microorganisms, etc.
     Serum, plasma, urine, bile, bile acid, etc.
     Cells, liver, brain tissue and other animal tissues and feces, etc.
     There is no restriction on plant varieties. For varieties with special requirements or rare varieties, please contact our staff for more information.
Sample demand
Plant root / stem / leaf / fruit / seed > 200 mg fresh weight, freeze-dried sample > 0.5 g
     Cells / microorganisms / cell supernatant / culture medium supernatant: the number of cells or bacteria > 107, supernatant > 2 ml
     Serum / plasma / urine / ruminal fluid / cerebrospinal fluid / amniotic fluid and other homogeneous liquid samples > 200 µl.
     (Hemolysis should be avoided. Cerebrospinal fluid can be as low as 100 µl.)
     Animal tissue / feces related samples > 200 mg / sample
     For other sample types, please consult technical support or sales.
Sample mixed and repeat
In order to ensure the accuracy of the samples and reduce systematic errors during sampling, it is necessary to select more than 3 materials with the same condition for each sample.
     ※ The same condition refers to the same period, basically the same phenotype, and the same part.
     It is recommended that prepare more than 6 biological replicates.
Storage and transportation
Quick-frozen preservation with liquid nitrogen can minimize the leakage time of plant samples at room temperature, and store it at -80°C.
     Dry ice transportation (about 3~4 kg dry ice is consumed every day, please use sufficient dry ice for transportation).

Feedback to Customers

v-innovate Technologies will provide you with detailed technical reports, including

  • Experimental steps
  • Related mass spectrometry parameters
  • Part of the mass spectrum picture
  • Raw data
  • Metabolic molecular identification results

v-innovate Technologies offers several approaches to metabolomics studies, delivers precise and detailed data and analysis report. We can also customize the methods or establish new methods together with our collaborators, so they are fit-for-purpose and meet your specific needs. If you have any questions or specific requirements, please feel free to contact us.

References

  1. Riera-Borrull M, Rodríguez-Gallego E, Hernández-Aguilera A, et al. Exploring the process of energy generation in pathophysiology by targeted metabolomics: performance of a simple and quantitative method. Journal of the American Society for Mass Spectrometry, 2015, 27(1): 168-177.
  2. Kim M J, Lee M Y, Shon J C, et al. Untargeted and targeted metabolomics analyses of blackberries – Understanding postharvest red drupelet disorder. Food Chemistry, 2019, 300:125169.
  3. Wang X, Zhao X, Zhao J, et al. Serum metabolite signatures of epithelial ovarian cancer based on targeted metabolomics. Clinica Chimica Acta, 2021, 518: 59-69.
For Research Use Only. Not for use in diagnostic procedures.

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