Citation: YIN Zhi-Hong,  CHEN Zhao-Ming,  CHEN Xing,  YANG Zi-Feng,  LI Zheng-Tu,  YE Feng,  ZHANG Zhi-Juan,  FANG Ming-Liang,  LI Xue. Quantitative Analysis of Typical Aldehydes and Ketones in Headspace Air of Cell[J]. Chinese Journal of Analytical Chemistry, ;2021, 49(8): 1375-1383. doi: 10.19756/j.issn.0253-3820.211072 shu

Quantitative Analysis of Typical Aldehydes and Ketones in Headspace Air of Cell

  • Corresponding author: LI Xue, tamylee@jnu.edu.cn
  • Received Date: 26 January 2021
    Revised Date: 1 April 2021

    Fund Project: Supported by the "Guangdong Special Support Plan" Local Innovation and Entrepreneurship Team Project (No.2019BT02Z546), the Open Project of the State Key Laboratory of Respiratory Diseases (No.SKLRD-OP-201913), the Pre-research Project of Core Key Technologies in the Field of Earth Sciences, Chinese Academy of Sciences (No.282021000003).

  • Aldehydes and ketones in breath can reflect the oxidative stress response of the cells in the body. A better understanding of the aldehydes and ketones emitted from the cells is the key to revealing the mechanism of breath test for the diagnosis of oxidative stress-related diseases. In this study, a quantitative method was developed for 22 typical aldehyde and ketone metabolites. Standard compounds were transformed into stable DNPH-carbonyl adducts by using 2,4-dinitrophenylhydrazine (DNPH) impregnated cartridge. These adducts were further eluted and analyzed by ultra high performance liquid chromatography coupled with high resolution mass spectrometry. The standard curves of 22 DNPH-carbonyl adducts showed linearity at high (40-1000 μg/L), medium (8-400 μg/L) and low (0.08-8 μg/L) levels, respectively. The coefficient of correlation (R2) was >0.998 and the detection limits were 0.003-0.09 μg/L. The method demonstrated good precision, e.g. intra-day RSD <3.92% and inter-day RSD <5.3%, as well as satisfactory recoveries of 95.1%-109.6% (RSD<5.9%). The method was further applied to the analysis of aldehydes and ketones in the headspace of A549 cells and influenza A (H1N1) infected A549 cells. The experimental data were analyzed by using orthogonal partial least squares discriminant analysis, and a total of 19 aldehydes and ketones were quantified and 11 potential biomarkers were screened for the diagnosis of IAV infection.
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