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Targeted and untargeted metabolomic analysis techniques

Metabolomics is the assembly of biochemical reactions in organisms, the material basis for life to maintain life, and an important basis for studying life activities. Metabolomics is based on high-throughput analysis and bioinformatics technology to study the endogenous metabolic activities of life under the influence of the internal and external environment, including the detection and analysis of the types, quantities and changes of metabolites, so as to study collective life. The nature of the occurrence and development of activities.

metabolomic analysis

Metabolites are the end products of biological processes, and their state changes can accurately reflect changes in cellular functions. Studies have shown that a variety of diseases, including cancer, such as liver disease, kidney disease, cardiovascular and neurological diseases, are associated with physiological disorders or loss of cellular function caused by changes in intracellular metabolic status. Metabolomics has become a research tool for functional genomics in the post-genomics era, an important means for large-scale screening of new biomarkers for early prediction, diagnosis and typing of diseases, and one of the important technical means for precision medicine.

Metabolomics Advantage

Changes in the type and quantity of metabolites are easy to detect;
Compared with genomics and proteomics, the technical means are simpler;
Compared with genomics and proteomics, the number of metabolites is small and easy to detect, validate and analyze;
Changes in metabolic levels can reveal the physiological and pathological states of the body in real time.

metabolomic classification

Metabolomics can be further divided into non-targeted and targeted metabolomics according to different research purposes.

Untargeted metabolomics refers to the use of LC-MS, GC-MS, NMR technology to unbiased detection of all small molecule metabolites (mainly before and after stimulation or perturbation in cells, tissues, organs or organisms). The dynamic changes of endogenous small molecule compounds with relative molecular weight less than 1000 Da) were screened by bioinformatics analysis, and the pathway analysis of differential metabolites was carried out to reveal the physiological mechanism of their changes.

Targeted Metabolomics is the research and analysis of a specific class of metabolites. Both have their own advantages and disadvantages, and are often used in combination for the discovery and quantification of differential metabolites, and for in-depth research and analysis of subsequent metabolic molecular markers, which are used in food identification, disease research, animal model validation, and biomarker discovery. It plays an important role in disease diagnosis, drug development, drug screening, drug evaluation, clinical research, plant metabolism research, and microbial metabolism research.
Metabolomics application direction

1. Detection of complex metabolites in biological samples.
2. Find biomarkers of disease.
3. Marker validation and absolute quantitative research.
4. Study the mechanism of metabolic pathway.

Difference Between Targeted Metabolomics and Untargeted Metabolomics

Targeting: focus on target metabolites, generally based on pathways
Non-targeting: discovering differential metabolites and finding biomarkers

Qualitative and quantitative
Targeting: qualitative and quantitative simultaneous, can detect concentration
Non-targeted: can be qualitative, relatively quantitative

Targeting: It is necessary to purchase standard products first, carry out methodological verification and then test, and the cost is high
Non-targeted: direct injection can be analyzed, and the cost is relatively low

Metabolome Platform Comparison

Non-targeted metabolomics commonly used LC/MS, GC/MS, NMR three detection methods, the advantages and disadvantages are as follows:

1. NMR (Nuclear Magnetic Resonance)
The advantage is that it is non-destructive to the sample and has no bias in the measurement, that is, it is suitable for liquid samples such as blood and urine, but also for solid samples such as tissues and organs, and the measurement speed is fast, which can realize the dynamic monitoring of the sample metabolome. Disadvantages Mainly the lower resolution.

2. GC-MS (Gas Chromatography)
GC-MS is a metabolomics research technology, which has the characteristics of mature and stable technology and high resolution. At the same time, due to the relatively complete database, the quality is also better. The disadvantages are mainly in the complex sample processing and the difficulty in derivatization. It is difficult to characterize and quantify the substances, which affects the use of this technology in a wider range.

3. LC-MS (Liquid Chromatography)
The advantages are mainly manifested in simple sample preparation and pretreatment, good experimental repeatability, high resolution, and wide separation and analysis range.

Untargeted metabolomic analysis technology

Metabolomics often requires the use of multiple analytical techniques to meet different experimental needs. Common metabolomic analysis techniques include nuclear magnetic resonance (NMR), liquid chromatography-mass spectrometry (LC-MS), gas chromatography-mass spectrometry (GC-MS), capillary electrophoresis-mass spectrometry (CD-MS) , HILIC–MS and so on. High-resolution mass spectrometry techniques mainly include TOF-MS, FTICR-MS, Orbitrap-MS, Sector-MS and so on.

1. GC-MS (Gas Chromatography) is a classic technology in metabolomics research. It has the characteristics of mature and stable technology and high resolution. At the same time, due to the relatively complete database, the quality is more accurate. The disadvantage is mainly in the sample. The processing is complicated, and it is difficult to characterize and quantify substances that are not easily derivatized, which affects the application of this technology in a wider range.

2. The advantages of LC-MS (liquid chromatography) are mainly manifested in simple sample preparation and pretreatment, good experimental repeatability, high resolution, and a wide range of separation and analysis.

Data analysis

Data preprocessing: Use tools such as XCMS, MZmine and MarkerView for raw data processing.
Identification of differential metabolites: Common analysis methods include principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), and orthogonal partial least squares discriminant analysis (OPLS-DA). Data analysis results also need to screen for differential metabolites by t-test and variable importance in projection (VIP) value. It is generally considered that the variables satisfying both P<0.05 and VIP>1.0 are differential metabolites.
Metabolic pathway analysis: Common metabolomic pathway databases include HMDB, KEGG, Reactome, BioCyc, MetaCyc and other databases, which can be used for metabolic pathway and interaction network analysis.
Multi-omics analysis: Multi-omics analysis is already the trend of omics discovery. Available databases and tools include IMPaLA website, iPEAP software, MetaboAnalyst website, SAMNetWeb website, pwOMICS, MetaMapR, MetScape, Grinn, WGCNA, MixOmic, DiffCorr, qpgraph, huge, etc.

About samples

1. Microbial and cellular samples: rapidly inactivates metabolic activity (quenching) while keeping cells from lysing
2. Animal body fluids (such as urine, blood, tissues, organs, saliva): Pre-treatment should be performed quickly after sampling, such as adding anticoagulants and preservatives, and immediately freezing (-80°C)
3. Plant samples: quickly freeze (liquid nitrogen) after collection, and then transfer to -80℃ for storage, 200mg/case
4. Serum sample: 500ul/case (not less than 200ul/case), must avoid repeated freezing and thawing. (The blood was collected in a centrifuge tube and allowed to stand for 30 minutes for coagulation. Then centrifuge to get the supernatant and load it into a clean centrifuge tube, and then centrifuge for 5 minutes at 8000 rpm. -80°C frozen for delivery.)
5. Urine sample: 1ml/case, in principle, you can take a little more (urine directly into centrifuge tubes, 1ml per tube, add a drop (about 10ul) of 1/100 (w/v) stack Sodium nitride, frozen at -80°C)
6. Rumen juice: 1ml/case, in principle, a little more can be taken. Collection steps: rumen fluid was centrifuged at 6000×g for 15min, the supernatant was taken, aliquoted, frozen at -80°C, and sent on dry ice. In order to keep the sample longer, a drop (about 10µl) of 1/100 mass-volume (w/v) sodium azide solution can be added after sampling.

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