Metabolomic analysis of amino acids and organic acids in aging mouse eyes using gas chromatography-tandem mass spectrometry.

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.

Metabolomic study on bleomycin and polyhexamethylene guanidine phosphate-induced pulmonary fibrosis mice models.

INTRODUCTION: Polyhexamethylene guanidine phosphate (PHMG) has been used as a disinfectant and biocide, and was known to be harmless and non-toxic. However, in 2011, PHMG used as a humidifier disinfectant was reported to be associated with lung diseases, such as, fibrosis in the toxicant studies on pulmonary fibrosis by PHMG. However, no metabolomics study has been performed in PHMG-induced mouse models of pulmonary fibrosis. OBJECTIVES: We performed a metabolomic study to understand the biochemical events that occur in bleomycin (BLM)- and PHMG-induced mouse models of pulmonary fibrosis using gas chromatography-mass spectrometry (GC-MS), LC-tandem MS, and GC-tandem MS. RESULTS: The levels of 61 metabolites of 30 amino acids, 13 organic acids, 12 fatty acids, 5 polyamines, and oxidized glutathione were determined in the pulmonary tissues of mice with BLM- and PHMG-induced pulmonary fibrosis and in normal controls. Principal component analysis and partial least squares discriminant analysis used to compare level of these 61 metabolites in pulmonary tissues. Levels of metabolites were significantly different in the BLM and PHMG groups as compared with the control group. In particular, the BLM- and PHMG-induced pulmonary fibrosis models showed elevated collagen synthesis and oxidative stress and metabolic disturbance of TCA related organic acids including fumaric acid by NADPH oxidase. In addition, polyamine metabolism showed severe alteration in the PHMG group than that of the BLM group. CONCLUSION: This result suggests PHMG will be able to induce pulmonary fibrosis by arginine metabolism and NADPH oxidase signaling.

Metabolomic approaches to polyamines including acetylated derivatives in lung tissue of mice with asthma.

INTRODUCTION: Recently, the relationship between polyamine (PA) metabolism and asthma has been studied in severe asthmatic therapy, but systematic PA metabolism including their acetylated derivatives was not fully understood. OBJECTIVES: Profiling analysis of polyamines (PAs) was performed to understand the biochemical events and monitor altered PA metabolism in lung tissue of mice with asthma. METHODS: Polyamine profiling of lung tissue of mice with asthma was performed without derivatization by liquid chromatography-tandem mass spectrometry (LC-MS/MS) combined with star pattern recognition analysis. The PA levels between control and asthma groups were evaluated by multivariate analysis. RESULTS: In mouse lung tissue, seven PAs were determined by LC-MS/MS in multiple reaction monitoring (MRM) mode. Their levels were normalized to the corresponding mean levels of the control group for star pattern analysis, which showed distorted heptagonal shapes with characteristic and readily distinguishable patterns for each group. Levels of putrescine (p < 0.0034), N1-acetylputrescine (p < 0.0652), and N8-acetylspermidine (p < 0.0827) were significantly increased in asthmatic lung tissue. The separation of the two groups was evaluated using multivariate analysis. In unsupervised learning, acetylated PAs including N1-acetylspermine were the main metabolites for discrimination. In supervised learning, putrescine and N1-acetylputrescine were evaluated as important metabolites. CONCLUSIONS: The present results provide basic data for understanding polyamine metabolism in asthma and may help to improve the therapy for severe asthma patients.

Analysis of the free fatty acid metabolome in the plasma of patients with systemic lupus erythematosus and fever.

INTRODUCTION: Systemic lupus erythematosus (SLE) is a multifactorial autoimmune disease with heterogeneous clinical manifestations mediated by immune dysregulation. OBJECTIVES: We aimed to analyze the metabolomic differences in free fatty acids (FFAs) between patients with SLE and healthy controls (HCs). METHODS: In this study, the levels of 24 FFAs, as their tert-butyldimethylsilyl derivatives, in the plasma of 41 patients with SLE and 41 HCs, were investigated using gas chromatography with mass spectrometry in selected-ion monitoring mode. RESULTS: The results showed that patients with SLE and HCs had significantly different levels of 13 of the 24 FFAs. The levels of myristic, palmitoleic, oleic, and eicosenoic acids were significantly higher, whereas the levels of caproic, caprylic, linoleic, stearic, arachidonic, eicosanoic, behenic, lignoceric, and hexacosanoic acids were significantly lower in patients with SLE, than in the HCs. In the partial-correlation analysis of the FFA profiles and markers of disease activity of SLE, several metabolic markers correlated with SLE disease activity. CONCLUSIONS: Our results provide a comprehensive understanding of the relationship between FFAs and markers of SLE disease activity. Thus, this approach has promising potential for the discovery of metabolic biomarkers of SLE.