Robust and Comprehensive Targeted Metabolomics Method for Quantification of 50 Different Primary, Secondary, and Sulfated Bile Acids in Multiple Biological Species (Human, Monkey, Rabbit, Dog, and Rat) and Matrices (Plasma and Urine) Using Liquid Chromatography High Resolution Mass Spectrometry (LC-HRMS) Analysis
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Abstract
Bile acids (BAs) are biomolecules synthesized in the liver from cholesterol and are constituents of bile. The in-vivo BA pool includes more than 50 known diverse BAs which are unconjugated, amino acid conjugated, sulfated, and glucuronidated metabolites. Hemostasis of bile acids is known to be highly regulated and an interplay between liver metabolism, gut microbiome function, intestinal absorption, and enterohepatic recirculation. Interruption of BA homeostasis has been attributed to several metabolic diseases and drug induced liver injury (DILI), and their use as potential biomarkers is increasingly becoming important. Speciated quantitative and comprehensive profiling of BAs in various biomatrices from humans and preclinical animal species are important to understand their significance and biological function. Consequently, a versatile one single bioanalytical method for BAs is required to accommodate quantitation in a broad range of biomatrices from human and preclinical animal species. Here we report a versatile, comprehensive, and high throughput liquid chromatography-high resolution mass spectrometry (LC-HRMS) targeted metabolomics method for quantitative analysis of 50 different BAs in multiple matrices including human serum, plasma, and urine and plasma and urine of preclinical animal species (rat, rabbit, dog, and monkey). The method has been sufficiently qualified for accuracy, precision, robustness, and ruggedness and addresses the issue of nonspecific binding of bile acids to plastic for urine samples. Application of this method includes comparison for BA analysis between matched plasma and serum samples, human and animal species differences in BA pools, data analysis, and visualization of complex BA data using BA indices or ratios to understand BA biology, metabolism, and transport.
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