Recently, urine metabolomics has emerged as a prominent field for non-invasive biomarkers discovery that can detect subtle metabolic changes brought by a specific disease or therapeutic intervention.
Urine is a sterile, transparent amber-colored fluid generated by the kidneys. The kidneys extract excess water, sugars, and a variety of other soluble wastes from the bloodstream. Urine generally is composed of metabolic breakdown products from a large number of foods, drugs, drinks, endogenous waste metabolites, environmental contaminants and bacterial by-products. For example, urobilin, is hemoglobin breakdown product which gives urine its characteristic color. Urine also contains high concentrations of creatinine, ammonia, organic acids, various water-soluble toxins and urea from amino acid metabolism. Urination is the most important route for the elimination of water-soluble waste products. Many of these compounds are poorly identified and poorly understood. To improve our understanding of this biofluid, with the help of computer-aided literature mining and comprehensive, quantitative technologies, a comprehensive, quantitative, metabolome-wide characterization of human urine is of great interest. Up till now, there are about 3100 detectable metabolites in Human Urine Metabolome Database. The number is still increasing as other lower abundance metabolites are identified with the development of technology.
Among metabolomics researchers, urine has long been a preferred diagnostic biofluid for more than 100 years. It is sterile, easy-to-get, available in large volumes, largely free from intervention of proteins or lipids and chemically complex. The analysis of urine for medical diagnostics where examining the color, cloudiness, smell and even the taste of urine for identification of a variety of diseases dates back to ancient Egypt. In the Byzantine era and the Middle Ages, urine color wheels, a diagram that associated the color of urine with a particular disease, were commonly applied by physicians for diagnostic purpose. For example, absence of color indicates diabetes, foamy urine indicates proteinuria, a brownish color would be indicative of jaundice and a red hue might be indicative of certain urinary tract cancers. In modern medical practice, urine continues to be an important diagnostic fluid. Actually, it was the first biofluid used for the clinical diagnosis of alkaptonuria, a human genetic disease. Up till now, routine analysis for glucose, bilirubin, ketone bodies, nitrates, leukocyte esterase, specific gravity, hemoglobin, urobilinogen and protein are used for the estimation of a variety of renal conditions and many medical disorders in other system.
Various methods are used for analysis of urine and up to 294different metabolites are identified by these methods in human urine. However, quantification of metabolites is not so easy and the largest number of quantified metabolites ever reported in human urine is less than 100. GC-MS has long been used for comprehensive characterization of the chemical content of human urine. However, metabolite coverage by GC-MS tends to be relatively incomplete. NMR may currently be the most comprehensive technology since nearly all detectable peaks are identifiable. Among all analytical techniques, LC-MS is widely used in urine metabolomics because of the best selectivity, sensitivity, and identification capabilities for the identification and quantification of early all metabolites in the urine. However, for the compound classes such as thiols and isoflavones, neither NMR, GC-MS, or LC-MS the necessary sensitivity, the appropriate instrumental configuration to identify and quantify. Instead, HPLC are the most appropriate method for detecting thiols and isoflavones because of its sensitivity, precision and being easily coupled with sensitive detection technologies like fluorescence and ultraviolet detection.
For metabolomic analysis, the collected urine samples must be frozen immediately to quench any biogenic and non-biogenic chemical reactions. Due to the lack stability of urine metabolites, repetitive freeze-thaw cycles and higher storage temperatures (such as 4°C) should be avoided.
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