Metabolism is the general term for all biochemical reactions in an organism. Metabolic activity is the material basis for organisms to maintain life. The analysis of metabolites is an important aspect of studying the molecular basis of life activities. Metabolomics was originally proposed by Professor Jeremy Nicholson of Imperial College London. He believes that metabolomics is to use the physiological and pathological processes of the human body as a dynamic system to study the types and quantities of endogenous metabolites in an organism after being disturbed by internal and external environmental factors. and the science of its changing laws.
Its core tasks include detection, analysis and exploration of the overall change law of metabolites, and through this change law to study the nature of the occurrence and development of the body’s life activities. Based on the rapid development of analytical technology and information technology, metabolomics has developed rapidly, and together with genomics, transcriptomics, proteomics, etc., constitutes “system biology”, and plays an important role in systems biology research.
Compared with other omics, metabolomics has obvious advantages: 1) changes occurring at the metabolite level are easier to detect; 2) compared with genomics and proteomics, it requires whole-genome sequencing and establishment of a large number of expression tags 3) Compared with the number of genes and proteins, the number of metabolites is small, which is easy to confirm and carry out subsequent analysis; 4) The changes of metabolites and metabolic pathways of biological samples can systematically reveal the body Physiological state.
Targeted metabolomics is a method to analyze and study only a limited number or types of metabolites related to biological events according to the principles and ideas of metabolomics. Typically, after differential metabolites are discovered by untargeted metabolomics, targeted metabolomics is used for further systematic confirmation. The newly developed glycoomics and lipidomics in recent years also belong to the category of targeted metabolomics. Compared with non-targeted metabolomics, targeted metabolomics is more targeted in analysis, complementing the advantages of non-targeted metabolomics, and is an important part of metabolomics.
1.1 Sample collection, preprocessing and analysis
Targeted metabolomics and untargeted metabolomics use similar sample types. However, in terms of sample pretreatment, because targeted metabolomics is more targeted, the selection of extraction methods based on target metabolites or metabolomes may be different from non-targeted metabolomics. For example, the purpose of lipidomics research is to extract more lipids, so the selected solvents have better dissolving ability for lipids, which are quite different from those used in general metabolomics research. There are also many differences. Targeted metabolomics and untargeted metabolomics use basically the same analytical instruments.
1.2 Data processing
Targeted metabolomics only focuses on a few or a few types of metabolites known to have biological effects, so its data processing is simpler and more convenient than non-targeted metabolomics. The data processing methods and databases used are similar to those of non-targeted metabolomics, but for certain types of metabolites, such as carbohydrates and lipidomes, there are usually specific databases such as LipidMaps and LipidBank.
1. Marien et al performed lipidomic profiling targeting phospholipids in normal and hepatic squamous cell tumor tissue samples. It was found that the content of long-chain acylphospholipids in cancer tissues was significantly higher than that in normal tissues. Further research found that the increase in the content of long-chain acylphospholipids in cancer tissues was related to acyl chain elongases (ELOVLs).
After screening, it was found that ELOVL6 was most closely related to the elongation of phosphatidyl chains in cancer tissues. Inhibition of ELOVL6 can significantly reduce the colony-forming ability of squamous cell tumor cells; at the same time, animal experiments show that inhibition of ELOVL6 can significantly slow down the growth of subcutaneous xenografts. This indicates that ELOVL6 can affect the occurrence and development of squamous cell tumors by regulating the content of long-chain acyl phospholipids, so it can be used as a potential target for squamous cell tumor treatment and drug development.
2. Nomura et al. studied the proteomics of melanoma, ovarian cancer, breast cancer and other tumor cells, and found that the expression of a lipolytic enzyme monoacylglycerol lipase (MAGL) was abnormally increased compared with normal tissues and cells. High, the biological function of this enzyme is mainly to break down fat to release free fatty acids, and to supply energy through fatty acid oxidation and other pathways.
The researchers further conducted lipidomic studies on tumor cell lines and cancerous tissues, and found that a variety of free fatty acids were abnormally elevated, and key signaling molecules for tumor invasion and metastasis, such as lysobisphosphatidic acids (LPA) and prostaglandin E2 ( The expression of prostaglandin E2, PGE2) was also abnormally increased.
On the one hand, inhibiting the activity of MAGL reduces free fatty acids in cancerous tissues and cells, and at the same time affects the metastasis and invasion ability of cancer cells; It increases the malignancy and aggressiveness of the tumor. Thus, increased MAGL activity may promote cancer cells to more efficiently break down free fatty acids from neutral lipids for energy supply. Through the study of proteomics and targeted metabolomics, it was found that MAGL can be used as an effective target to inhibit the energy metabolism of cancer cells.