Simultaneous Quantitation of Structurally Analogous Bile Acid Isomers via Charge-State-Engineered UPLC-MS

Abstract

Ursodeoxycholic, hyodeoxycholic, chenodeoxycholic, and deoxycholic acid are endogenous, dihydroxylated bile acid isomers that share a molecular mass but fulfill specific biological roles. However, their isomeric structures complicate analytical separation, while low physiological concentrations demand high detection sensitivity. Consequently, despite the utility of liquid chromatography-tandem mass spectrometry for simultaneous analysis, current methodologies are often hampered by inadequate sensitivity and lengthy analysis durations. To address this analytical bottleneck, we developed an ultra-high performance liquid chromatography-mass spectrometry (UPLC-MS) method for the quantitative analysis of four bile acid isomers. This method employs a novel charge-state homogenization strategy, guided by computational prediction of ionization behavior (pH/ionic forms), to optimize chromatographic and mass spectrometric conditions. By inducing complete deprotonation and generating uniform carboxylate anions for all analytes, this approach synergistically enhances detection sensitivity, chromatographic resolution, and analysis speed. The rigorously validated method demonstrates exceptional performance: sub-ng/mL sensitivity (LODs 0.10–0.22 ng/mL), rapid analysis (<8 min), excellent linearity (R² > 0.998 over 4 orders of magnitude), high reproducibility (intra/inter-day RSD 1.2–9.1%), and satisfactory accuracy (86.1–107.1% recovery). Its broad applicability was confirmed across diverse matrices (poultry/porcine blood, bile, concentrates), handling trace to high bile acid levels. This rapid, sensitive and highly-resolutive analytical approach addresses key challenges in bile acid isomers quantitation, offering significant advantages for pharmacokinetic research, and quality control in animal health and pharmaceutical applications. Furthermore, the underlying charge-state homogenization principle provides a rational framework for optimizing chromatographic parameters (organic modifiers, stationary phases, gradients) in complex analyses.