Untargeted metabolomics, namely discovery metabolomics, involves the comparison of the metabolome between the control and test groups, to identify differences between their metabolite profiles which may be relevant to specific biological conditions.
Untargeted Metabolomics Workflow
There are usually three steps in the experimental workflow:
- Profiling in order to seek the metabolites with statistically significant variations in abundance within a set of experimental and control samples;
- Determination of metabolite ID, including the chemical structure;
- Comprehensions as the last step which makes connections between the identified metabolites and the biological processes.
In the workflow of discovery metabolomics, analytical reproducibility is critical for expression profiling work; annotation is a tentative identification based on an accurate mass match to a database or a spectral match to a library; the collected data can be interpreted for biomarker discovery, biological signature/fingerprint selection and pathway mapping. Above are the most important parts in untargeted metabolomic research. The tech panel in Creative Proteomics is experienced in sample preparation, data interpretations. It also can provide you reliable metabolite identification.
What Untargeted Metabolomics services we provide?
With integrated a set of separation, characterization, identification and quantification systems featured with excellent robustness & reproducibility, high and ultra-sensitivity, Creative Proteomics provides reliable, rapid and cost-effective Untargeted Metabolomics as below.
- Serum Untargeted Metabolomics
- Urine Untargeted Metabolomics
- Cerebrospinal Fluid Untargeted Metabolomics
- Plant Untargeted Metabolomics
- Exosome Untargeted Metabolomics
- GC–MS Untargeted Metabolomic Analysis
- LC-MS/MS Untargeted Metabolomics Services
- Gut Flora Metabolomics Research Solution
Advantages
- Based on advanced liquid phase tandem mass spectrometry technology, it can detect up to thousands of pg-level compounds, and can be competent for the detection of thermally unstable, non-volatile, and non-volatile substances.
- Lower cost
Analysis Content
- Data pre-processing
- Univariate analysis
- PCA analysis, PLS-DA analysis
- Difference m/z value screening and identification
- Cluster analysis
- Differential metabolite metabolic pathway annotation analysis
Sample Requirement
- Cells, tissues, urine, whole blood, serum, plasma, etc.
- Plasma or serum > 300 μL, urine > 5 mL, tissue > 100 mg, and cells > 107.
FAQ
Q1: What databases for metabolite identification?
A: Public databases such as KEGG, METLIN, etc., have an accuracy of less than 10ppm, and identification can be more accurate if the corresponding secondary spectra are available inside the database. If you want to verify, you can buy standard products. We also supply high quality standard products.
Q2: Is there a requirement for the number of samples of untargeted metabolomes?
A: For untargeted metabolomes whose goal is to find differential metabolites, the number of clinical samples is recommended to be no less than 30 per group. For model organisms and plant and animal samples, no less than 10 are recommended.
Q3: What is the difference between untargeted metabolomic analysis and lipid metabolomic analysis?
A: untargeted metabolome analysis is a research method to quantitatively analyze all metabolites in the organism and find the relative relationship between metabolites and physiological and pathological changes. The research object is small molecular substances with a relative molecular mass less than 1000Da, such as lipids , ketones, organic acids, etc. As we all know, genomics and proteomics explore life activities at the gene and protein levels respectively, but in fact many life activities in cells occur at the metabolite level, such as cell signal release, energy transfer and intercellular communication, etc. are all affected by metabolites regulation. Untargeted metabolome analysis is to discover differentially expressed metabolite information through univariate and multivariate analysis, thereby reflecting the environment in which cells are located and the interaction between them and external factors.
Lipidomics is a discipline that studies the lipid composition, lipid metabolism and lipid interactions of organisms, and is the most important branch of metabolomics. Lipids have a variety of important biological functions, such as material transport, energy metabolism, information transmission, and metabolic regulation. Abnormal lipid metabolism can cause many human diseases, including Alzheimer's disease, diabetes, obesity, and atherosclerosis. hardening, etc.
