Mass spectrometry imaging of diclofenac and its metabolites in tissues using nanospray desorption electrospray ionization

Glucuronidation is a common phase II metabolic process for drugs and xenobiotics which increases their solubility for excretion. Acyl glucuronides (glucuronides of carboxylic acids) present concerns as they have been implicated in gastrointestinal toxicity and hepatic failure. Despite the substantial success in the bulk analysis of these species, previous attempts using traditional mass spectrometry imaging (MSI) techniques have completely or partially failed and therefore little is known about their localization in tissues. Herein, we use nanospray desorption electrospray ionization mass spectrometry imaging (nano-DESI MSI), an ambient liquid extraction-based ionization technique, as a viable alternative to other MSI techniques to examine the localization of diclofenac, a widely used nonsteroidal anti-inflammatory drug, and its metabolites in mouse kidney and liver tissues. MSI data acquired over a broad m/z range showed low signals of the drug and its metabolites resulting from the low ionization efficiency and substantial signal suppression on the tissue. Significant improvements in the signal-to-noise were obtained using selected ion monitoring (SIM) with m/z windows centered around the low-abundance ions of interest. Using nano-DESI MSI in SIM mode, we observed that diclofenac acyl glucuronide and hydroxydiclofenac are localized to the inner medulla and cortex of the kidney, respectively, which is consistent with the previously reported localization of enzymes that process diclofenac into its respective metabolites. In contrast, a uniform distribution of diclofenac and its metabolites was observed in the liver tissue. Concentration ratios of diclofenac and hydroxydiclofenac calculated from nano-DESI MSI data are generally in agreement to those obtained using liquid chromatography tandem mass spectrometry (LC-MS/MS) analysis. Collectively, our results demonstrate that nano-DESI MSI can be successfully used to image diclofenac and its primary metabolites and derive relative quantitative data from different tissue regions. Our approach will enable a better understanding of metabolic processes associated with diclofenac and other drugs that are difficult to analyze using commercially available MSI platforms.