Metabolomic analysis of amino acids and organic acids in aging mouse eyes using gas chromatography–tandem mass spectrometry. (10th January 2022)

• Record Type: Journal Article
• Authors: Seo, Chan; Park, Sehoon; Kim, Youngbae; Ji, Moongi; Lee, Hyeon‐Seong; Hwang, Yun‐Ho; Choi, Subin; Min, Jeuk; Oh, Song‐Jin; Yee, Sung‐Tae; Lee, Wonjae; Paik, Man‐Jeong
• Is Part Of: Biomedical chromatography. Volume 36:Number 3(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-01-10
• Subjects: aging -- amino acids -- eye -- gas chromatography–tandem mass spectrometry -- metabolomics -- organic acids; Chromatographic analysis -- Periodicals; Biology -- Periodicals; Medicine -- Periodicals; Biology -- Periodicals; Chromatography -- methods -- Periodicals; Medicine -- Periodicals; 543.089
• DOI: 10.1002/bmc.5298
• Languages: English
• ISSNs: 0269-3879

Abstract

Abstract: This is a metabolomics study for monitoring altered amino acid (AA) and organic acid (OA) metabolism of in eyes from aging an mouse model at 8 and 18 weeks and 18 months. Simultaneous metabolic profiling analysis of OAs and AAs was performed as ethoxycarbonyl/methoxime/ tert ‐butyldimethylsilyl derivatives by gas chromatography–tandem mass spectrometry. A total of 42 metabolites—24 AAs and 18 OAs—were determined and their composition values were normalized to the corresponding mean values of 8‐week‐old mice as the control group. Then their normalized values were plotted as star graphs, which were distorted and readily distinguishable for each age‐related group. Among the 42 metabolites, 18 AAs and 11 OAs were age dependent and significantly different ( p < 0.05). Principal component analysis and partial least squares discriminant analysis showed unclear separation between 8‐ and 18‐week‐old mice but clear separation between these and 18‐month‐old mice. In particular, the variable importance in projection scores of 4‐hydroxyproline, cis ‐aconitic acid, glycine, isocitric acid, leucine, pipecolic acid and lysine from partial least‐squares–discriminant analysis were higher than 1.3. A heatmap for the classification and visualization of 42 metabolites showed differences in metabolite changes with aging. Altered AA and OA profiles were monitored, which may explain the metabolic disturbance of AA and OA. These findings are related to mitochondrial dysfunctions related to energy metabolism and the impaired antioxidant system in the aging eye. Therefore, the present metabolomics results of the association between physiological states and altered metabolism of AA and OA will be useful for understanding the aging eye and related diseases.