Issue 7, 2017

Molecular imaging of small molecule drugs in animal tissues using laser desorption postionization mass spectrometry

Abstract

Localization and quantification of the target drug in tissues is a key indicator of efficacy in drug discovery. In contrast to established methods that require matrices and complex sample pretreatment steps, matrix-free and low cost in situ analysis of small molecule drugs by mass spectrometry (MS) remains challenging. Here, we present a novel approach, laser desorption postionization (LDPI), which is coupled to a linear time-of-flight (TOF) MS and used to image the distribution of acriflavine (ACF) directly from a histological section of mouse kidney without any matrix or sample pretreatment. The identification of the mass peaks assigned to ACF was further confirmed by DESI-MS/MS. Moreover, the matrix effect from the tissue section was explored, showing minimal desorption and ionization suppression in the LDPI-MS process. LDPI-MS imaging (LDPI-MSI) was performed on 30 μm kidney sections from mice 15 min postdose that were dosed with 30 mg kg−1 of ACF by monitoring the fragment ion at m/z 209. The LDPI-MS image revealed a global view of the distribution of ACF in the kidney compartments (pelvis, medulla, and cortex). Estimated concentrations of ACF residue in mouse kidney were obtained by LDPI-MSI and LC-MS/MS and a 12.1% difference in measured tissue concentration was found. These results suggest that the use of LDPI-MS in small molecule drug localization and quantification directly from biological tissue at the same time is favorable.

Graphical abstract: Molecular imaging of small molecule drugs in animal tissues using laser desorption postionization mass spectrometry

Supplementary files

Article information

Article type
Paper
Submitted
24 Dec 2016
Accepted
02 Mar 2017
First published
02 Mar 2017

Analyst, 2017,142, 1119-1124

Molecular imaging of small molecule drugs in animal tissues using laser desorption postionization mass spectrometry

J. Chen, Y. Hu, Q. Lu, P. Wang and H. Zhan, Analyst, 2017, 142, 1119 DOI: 10.1039/C6AN02721K

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