Issue 29, 2016

Validation and quantification of genomic 5-carboxylcytosine (5caC) in mouse brain tissue by liquid chromatography-tandem mass spectrometry

Abstract

5-Carboxylcytosine (5caC) is one of the most important oxidation products of 5-methylcytosine, an epigenetic biomarker generated from cytosine (Cyt). Although several methods have been developed to detect 5caC, they still can not accurately quantify trace amounts of 5caC. To conquer this challenge, we developed and validated a simple, robust method for the quantification of 5caC levels in mammalian tissue by LC-MS/MS. Tissue DNA was isolated using a commercial kit, hydrolyzed using 88% formic acid at 140 °C, separated using a bridged ethylene hybrid HILIC column, and analyzed by tandem MS. The linearity was evaluated in the concentration range of 40 to 4000 ng mL−1 for Cyt and 1 to 100 ng mL−1 for 5caC, and both the correlation coefficients were higher than 0.99. The limits of detection were 0.05 ng mL−1 for Cyt and 0.1 ng mL−1 for 5caC, and the limits of quantification were 0.1 ng mL−1 for Cyt and 1 ng mL−1 for 5caC. All the relative standard deviation (RSD) values of intra-day precision were lower than 6%. The recovery of the method ranged from 93.42% to 96.54% with RSD lower than 0.6%. Using this method, we illustrated that 5caC was distributed in mouse brain tissue, and the content of 5caC in the cerebrum was higher than that in the cerebellum and brainstem. Our studies indicated that the LC-MS/MS method was adequate for analyzing 5caC levels in biological samples.

Graphical abstract: Validation and quantification of genomic 5-carboxylcytosine (5caC) in mouse brain tissue by liquid chromatography-tandem mass spectrometry

Article information

Article type
Paper
Submitted
20 May 2016
Accepted
18 Jun 2016
First published
21 Jun 2016

Anal. Methods, 2016,8, 5812-5817

Author version available

Validation and quantification of genomic 5-carboxylcytosine (5caC) in mouse brain tissue by liquid chromatography-tandem mass spectrometry

L. Zhang, Z. Li, G. Chen, Q. Huang, J. Zhang, J. Wen, X. Ye and C. Cai, Anal. Methods, 2016, 8, 5812 DOI: 10.1039/C6AY01445C

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