Metabolic study of aristolochic acid I-exposed mice liver by atmospheric pressure matrix-assisted laser desorption/ionization mass spectrometry imaging and machine learning.

Abstract

Aristolochic acid I (AAI) as one of the major aristolochic acids (AAs) can cause progressive aristolochic acid nephropathy (AAN), which has been widely investigated since the early 1990s. Besides renal diseases, it has been recently revealed that AAI can induce liver damage. In this study, we report the molecular mapping of liver tissue sections from AAI-exposed mice using atmospheric pressure matrix-assisted laser desorption/ionization mass spectrometry (AP-MALDI MS) and show the distinct metabolic alterations when compared to the control group. We first used renal tissue sections to evaluate the performance of AP-MALDI MSI in spatial discrimination of different morphological regions. Then, the hepatic tissues from the AAI-induced and the control mice were analyzed, displaying rich metabolic profiles from both groups. Orthogonal partial least squares-discriminant analysis (OPLS-DA) is used to show complete separation of the two groups. A machine learning algorithm--least absolute shrinkage and selection operator (lasso) is used for statistical analysis of a total of 11,726 pixels of imaging data extracted from 3 normal liver and 3 AAI-exposed liver tissue sections, generating a classifier with high accuracy (99.81%). In total, 16m/z values, including small metabolites and lipid species, are selected to discriminate AAI-exposed liver tissues. Finally, we explore the potentially impacted pathways using metabolomics pathway analysis (MetPA), indicating multiple metabolic pathway alterations including taurine and hypotaurine metabolism, glycerophospholipid metabolism, d-Glutamine and d-glutamate metabolism, and arachidonic acid metabolism, which provides new insights in AAI-induced hepatotoxicity.