ABSTRACT
Acetaminophen (APAP) is a mild analgesic and antipyretic used commonly worldwide. Although considered a safe and effective over-the-counter medication, it is also the leading cause of drug-induced acute liver failure. Its hepatotoxicity has been linked to the covalent binding of its reactive metabolite, N-acetyl p-benzoquinone imine (NAPQI), to proteins. The aim of this study was to identify APAP-protein targets in both rat and mouse liver, and to compare the results from both species, using bottom-up proteomics with data-dependent high resolution mass spectrometry and targeted multiple reaction monitoring (MRM) experiments. Livers from rats and mice, treated with APAP, were homogenized and digested by trypsin. Digests were then fractionated by mixed-mode solid-phase extraction prior to liquid chromatography-tandem mass spectrometry (LC-MS/MS). Targeted LC-MRM assays were optimized based on high-resolution MS/MS data from information-dependent acquisition (IDA) using control liver homogenates treated with a custom alkylating reagent yielding an isomeric modification to APAP on cysteine residues, to build a modified peptide database. A list of putative in vivo targets of APAP were screened from data-dependent high-resolution MS/MS analyses of liver digests, previous in vitro studies, as well as selected proteins from the target protein database (TPDB), an online resource compiling previous reports of APAP targets. Multiple protein targets in each species were found, while confirming modification sites. Several proteins were modified in both species, including ATP-citrate synthase, betaine-homocysteine S-methyltransferase 1, cytochrome P450 2C6/29, mitochondrial glutamine amidotransferase-like protein/ES1 protein homolog, glutamine synthetase, microsomal glutathione S-transferase 1, mitochondrial-processing peptidase, methanethiol oxidase, protein/nucleic acid deglycase DJ-1, triosephosphate isomerase and thioredoxin. The targeted method afforded better reproducibility for analysing these low-abundant modified peptides in highly complex samples compared to traditional data-dependent experiments.
