Hyeon-Seong Lee1, Chan Seo1, Yun-Ho Hwang1, Tae Hwan Shin2, Hyung-Jin Park2, Youngbae Kim1, Moongi Ji1, Jeuk Min1, Subin Choi1, Hangun Kim1, Ae Kyung Park1, Sung-Tae Yee1, Gwang Lee2, Man-Jeong Paik3,4. 1. College of Pharmacy and Research Institute of Life and Pharmaceutical Sciences, Sunchon National University, Suncheon, Republic of Korea. 2. Department of Physiology, Department of Biomedical Sciences, Ajou University School of Medicine, Suwon, Republic of Korea. 3. College of Pharmacy and Research Institute of Life and Pharmaceutical Sciences, Sunchon National University, Suncheon, Republic of Korea. paik815@sunchon.ac.kr. 4. College of Pharmacy, Sunchon National University, 540-950, Suncheon, Republic of Korea. paik815@sunchon.ac.kr.
Abstract
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.
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 asthmapatients.
Entities:
Keywords:
Acetylated polyamines; Asthma; Liquid chromatography–tandem mass spectrometry; Lung tissue; Metabolomics; Polyamine profiling analysis; Star pattern recognition analysis
Authors: Michelle L North; Hartmut Grasemann; Nivedita Khanna; Mark D Inman; Gail M Gauvreau; Jeremy A Scott Journal: Am J Respir Cell Mol Biol Date: 2013-06 Impact factor: 6.914
Authors: Man Jeong Paik; Wen Yu Li; Young Hwan Ahn; Phil Hyu Lee; Sangdun Choi; Kyoung Rae Kim; Yong Man Kim; Oh Young Bang; Gwang Lee Journal: Clin Chim Acta Date: 2008-12-25 Impact factor: 3.786