Development of chemical isotope labeling LC-MS for tissue metabolomics and its application for brain and liver metabolome profiling in Alzheimer's disease mouse model

Abstract

Tissue metabolomics can play an important role in biological studies and biomarker discovery. However, high-coverage metabolome analysis of tissue samples remains a challenge. In this work, we report an analytical method for in-depth tissue metabolome profiling with highly accurate metabolite quantification. This method is based on tissue homogenization with an extraction solvent mixture of methanol, dichloromethane and water, high-performance differential chemical isotope labeling (CIL) of metabolite extracts, followed by high-resolution liquid chromatography mass spectrometry (LC-MS) detection of labeled metabolites. The method development was initially carried out using chicken liver tissue. To demonstrate the analytical performance and potential applications of this approach in real world tissue metabolomics, we examined changes in the amine/phenol submetabolome of liver and brain tissues from an Alzheimer's disease (AD) mouse model. A total of 2319 and 1769 peak pairs or amine-/phenol-containing metabolites were commonly detected in 80% of the liver samples (n = 22) and 80% of the brain samples (n = 22), respectively. In liver samples, 89 metabolites were positively identified using labeled standard library and 1063 peak pairs were putatively matched to metabolome databases, while 78 were positively identified and 753 were putatively matched in brain samples. Using multivariate and univariate analyses to study these metabolites, we observed significant metabolome differences between AD transgenic mice and wild-type mice in both liver and brain tissues, with several metabolite biomarker candidates having good discriminative power. We envisage that the CIL LC-MS method reported herein can be used in various application areas requiring in-depth analysis of tissue metabolomes.