Kazunori Sasaki

Metabolomic anatomy of an animal model revealing homeostatic imbalances in dyslipidaemia

Metabolomics is an emerging technology that reveals homeostatic imbalances in biological systems. Global determination of metabolite concentrations in body fluid and tissues provides novel anatomical aspects of pathological conditions that cannot be obtained from target-specific measurements. Here, we characterised metabolic imbalance in Watanabe heritable hyperlipidaemic rabbits as a model of hypercholesterolaemia. Using a mass spectrometry-based system, we measured a total of 335 metabolites in plasma and tissues (liver, aorta, cardiac muscle, and brain) from WHHL and healthy control rabbits. From the comparison between two metabolomic profiles, pathophysiological features including glutathione and phosphatidylcholine metabolism indicated the occurrence of oxidative stress in several tissues. Especially for the liver, imbalanced purine catabolism shed light on the transcriptional activation of xanthine oxidase, which is thought to act in absorbing or possibly triggering oxidative stress. We also applied this system to assess the therapeutic effects of simvastatin administration. After the treatment, a portion of the metabolomic features in pathological conditions showed alterations suggesting restoration of metabolism to the healthy condition. These changes were considered to be due to the pleiotropic action of statin, including antioxidant effects, rather than its main inhibitory action on cholesterol biosynthesis.

Metabolomics-based approach for ranking the candidate structures of unidentified peaks in capillary electrophoresis time-of-flight mass spectrometry: CE and CEC

One of the technical challenges encountered during metabolomics research is determining the chemical structures of unidentified peaks. We have developed a metabolomics‐based chemoinformatics approach for ranking the candidate structures of unidentified peaks. Our approach uses information about the known metabolites detected in samples containing unidentified peaks and involves three discrete steps. The first step involves identifying “precursor/product metabolites” as potential reactants or products derived from the unidentified peaks. In the second step, candidate structures for the unidentified peak are searched against the PubChem database using a molecular formula. These structures are then ranked by structural similarity against precursor/product metabolites and candidate structures. In the third step, the migration time is predicted to refine the candidate structures. Two simulation studies were conducted to highlight the efficacy of our approach, including the use of 20 proteinogenic amino acids as pseudo‐unidentified peaks, and leave‐one‐out experiments for all of the annotated metabolites with and without filtering against the Human Metabolome Database. We also applied our approach to two unidentified peaks in a urine sample, which were identified as glycocyamidine and N‐acetylglycine. These results suggest that our approach could be used to identify unidentified peaks during metabolomics analysis.

Plasma metabolome analysis of patients with major depressive disorder: Phosphoethanolamine and depression

This study sought to characterize the plasma metabolite profiling of patients with major depressive disorder (MDD).

Metabolome analysis reveals the association between the kynurenine pathway and human herpesvirus 6 encephalopathy in immunocompetent children

IntroductionHuman herpesvirus 6 (HHV-6) is the second most common causative pathogen of acute encephalopathy in immunocompetent children in Japan. Identification of biomarkers associated the pathophysiology is desirable to monitor disease severity, progression, and prognosis.ObjectivesTo investigate potential biomarkers for HHV-6 encephalopathy, serum metabolome profiling was analyzed and candidate metabolites were investigated the function in the diseases.MethodsPediatric patients with HHV-6 encephalopathy (n = 8), febrile seizure (n = 20), and febrile infection without febrile seizure (n = 7) were enrolled in this study, and serum metabolites were identified and quantified. For further analysis, serum samples of HHV-6 infected patients were analyzed by absolute quantification assay for kynurenine (KYN) and quinolinic acid (QUIN) in a total of 38 patients with or without encephalopathy. An in vitro blood–brain barrier (BBB) model was used to evaluate the effect of KYN and QUIN on BBB integrity because BBB damage induces brain edema.ResultsMetabolome profiling identified 159 metabolites in serum samples. The levels of KYN and QUIN, which belong to the tryptophan-KYN pathway, were significantly higher in the HHV-6 encephalopathy group than the other two groups. When quantified in the larger patient group, remarkably high levels of KYN and QUIN were observed exclusively in the encephalopathy group. Trans-endothelial electrical resistance of the BBB model was significantly decreased after QUIN treatment in culture.ConclusionMetabolome analysis revealed that KYN and QUIN may be associated with the pathophysiology of HHV-6 encephalopathy. In particular, QUIN may damage BBB integrity.