Yong-Kook Kwon

Characterizing the effect of heavy metal contamination on marine mussels using metabolomics.

Marine mussels (Mytilus) are widely used as bioindicators to measure pollution in marine environments. In this study, (1)H NMR spectroscopy and multivariate statistical analyses were used to differentiate mussel groups from a heavy metal-polluted area (Onsan Bay) and a clean area (Dokdo area). Principal component analysis and orthogonal projection to latent structure-discriminant analysis revealed significant separation between extracts of mussels from Onsan Bay and from the Dokdo area. Organic osmolytes (betaine and taurine) and free amino acids (alanine, arginine, glutamine, phenylalanine, and threonine) were more highly accumulated in Onsan Bay mussels compared with Dokdo mussels. These results demonstrate that NMR-based metabolomics can be used as an efficient method for characterizing heavy metal contamination derived from polluted area compared to clean area and to identify metabolites related to environments that are contaminated with heavy metals.

An integrated analysis for determining the geographical origin of medicinal herbs using ICP-AES/ICP-MS and 1H NMR analysis

ICP-MS and (1)H NMR are commonly used to determine the geographical origin of food and crops. In this study, data from multielemental analysis performed by ICP-AES/ICP-MS and metabolomic data obtained from (1)H NMR were integrated to improve the reliability of determining the geographical origin of medicinal herbs. Astragalus membranaceus and Paeonia albiflora with different origins in Korea and China were analysed by (1)H NMR and ICP-AES/ICP-MS, and an integrated multivariate analysis was performed to characterise the differences between their origins. Four classification methods were applied: linear discriminant analysis (LDA), k-nearest neighbour classification (KNN), support vector machines (SVM), and partial least squares-discriminant analysis (PLS-DA). Results were compared using leave-one-out cross-validation and external validation. The integration of multielemental and metabolomic data was more suitable for determining geographical origin than the use of each individual data set alone. The integration of the two analytical techniques allowed diverse environmental factors such as climate and geology, to be considered. Our study suggests that an appropriate integration of different types of analytical data is useful for determining the geographical origin of food and crops with a high degree of reliability.

1H NMR-Based Metabolite Profiling of Plasma in a Rat Model of Chronic Kidney Disease

Chronic kidney disease (CKD) is characterized by the gradual loss of the kidney function to excrete wastes and fluids from the blood. 1H NMR-based metabolomics was exploited to investigate the altered metabolic pattern in rats with CKD induced by surgical reduction of the renal mass (i.e., 5/6 nephrectomy (5/6 Nx)), particularly for identifying specific metabolic biomarkers associated with early of CKD. Plasma metabolite profiling was performed in CKD rats (at 4- or 8-weeks after 5/6 Nx) compared to sham-operated rats. Principle components analysis (PCA), partial least squares-discriminant analysis (PLS-DA) and orthogonal partial least squares-discriminant analysis (OPLS-DA) score plots showed a significant separation between the groups. The resulting metabolic profiles demonstrated significantly increased plasma levels of organic anions, including citrate, β-hydroxybutyrate, lactate, acetate, acetoacetate, and formate in CKD. Moreover, levels of alanine, glutamine, and glutamate were significantly higher. These changes were likely to be associated with complicated metabolic acidosis in CKD for counteracting systemic metabolic acidosis or increased protein catabolism from muscle. In contrast, levels of VLDL/LDL (CH2)n and N-acetylglycoproteins were decreased. Taken together, the observed changes of plasma metabolite profiles in CKD rats provide insights into the disturbed metabolism in early phase of CKD, in particular for the altered metabolism of acid-base and/or amino acids.

Patterns of gene and metabolite define the effects of extracellular osmolality on kidney collecting duct.

To investigate the effects of changes in extracellular osmolality on the function of kidney collecting duct cells, particularly on water and sodium reabsorption in the conditions of diuresis and antidiuresis, we generated transcriptome and metabolome profiles of primary cultured inner medullary collecting duct (IMCD) cells. They were grown in hyperosmolar culture medium (640 mOsm) for 4 days and then exposed to either reduced (300 mOsm) or same osmolality for 1 or 2 days more. Integrated analysis of the transcriptome and metabolome revealed that decreased extracellular osmolality was associated with decreased levels of organic osmolytes, glucose, intermediates of citric acid cycle, and branched-chain amino acids (BCAA) in IMCD cells, along with significantly decreased gene expression and protein abundance of P-type transporters (ATP1B1), ABC transporters (ABCC5 and ABCG1), and insulin signaling pathways (IRS2). Quantitative real-time RT-PCR and semiquantitative immunoblotting confirmed the changes of transcript levels of differentially expressed genes and protein levels. Taken together, integrated analysis of omics data demonstrated that water and sodium reabsorption could be reduced by decreased extracellular osmolality per se, through decreased levels of ABC transporters and IRS2, which play a potential role in the transport of organic osmolytes, BCAA, glucose, and trafficking of epithelial sodium channel.

Dose-dependent metabolic alterations in human cells exposed to gamma irradiation.

Radiation exposure is a threat to public health because it causes many diseases, such as cancers and birth defects, due to genetic modification of cells. Compared with the past, a greater number of people are more frequently exposed to higher levels of radioactivity today, not least due to the increased use of diagnostic and therapeutic radiation-emitting devices. In this study, ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS)-based metabolic profiling was used to investigate radiation- induced metabolic changes in human fibroblasts. After exposure to 1 and 5 Gy of γ-radiation, the irradiated fibroblasts were harvested at 24, 48, and 72 h and subjected to global metabolite profiling analysis. Mass spectral peaks of cell extracts were analyzed by pattern recognition using principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA). The results showed that the cells irradiated with 1 Gy returned to control levels at 72 h post radiation, whereas cells irradiated with 5 Gy were quite unlike the controls; therefore, cells irradiated with 1 Gy had recovered, whereas those irradiated with 5 Gy had not. Lipid and amino acid levels increased after the higher-level radiation, indicating degradation of membranes and proteins. These results suggest that MS-based metabolite profiling of γ-radiation-exposed human cells provides insight into the global metabolic alterations in these cells.

Changes in serum metabolites with the stage of chronic kidney disease: Comparison of diabetes and non-diabetes.

BACKGROUND The renal dysfunction of chronic kidney disease (CKD) alters serum metabolite levels, but it is not clear how diabetes mellitus (DM) affects the metabolic changes in CKD. METHODS Serum metabolites from pre-dialysis CKD patients (n=291) with or without DM and from healthy controls (n=56) was measured using nuclear magnetic resonance. RESULTS Initial principal components analysis and partial least squares-discriminant analysis score plots segregated the CKD patients according to CKD stage and separated DM from non-DM patients. In the CKD patients, associations were seen with clinical characteristics, hyperglycemia, altered amino acid metabolism, accumulated uremic toxins, and dyslipidemia. Of interest, diabetes more strongly affected the metabolic signature during early stage CKD. Furthermore, serum metabolite profiles were successfully applied to the PLS regression model to predict the estimated glomerular filtration rate. The R(2) values from the PLS models for CKD patients with DM were higher than those for CKD without DM. CONCLUSIONS Metabolomics is useful clinically for providing a metabolic signature that is associated with the CKD phenotype and diabetes more seriously affects patients with early stage CKD compared to those with advanced CKD.

Integrated profiling of global metabolomic and transcriptomic responses to viral hemorrhagic septicemia virus infection in olive flounder

Abstract Viral hemorrhagic septicemia virus (VHSV) is one of the most serious viral pathogen that infects farmed fish. In this study, we measured the replication of VHSV increased steadily at 9, 24, 72, and 120 h after infection and progression of necrosis was observed at 72 hpi. We performed transcriptomic and metabolomics profiling of kidney tissues collected at each infection time using Illumina HiSeq2000 and ultra‐performance liquid chromatography/quadrupole time‐of‐flight mass spectroscopy to investigate the mechanisms of VHSV infection in the kidneys of olive flounder. A total of 13,862 mRNA molecules and 72 metabolites were selected to identify the mechanisms of infection and they were integrated using KEGG pathway database. Six KEGG metabolic pathways, including carbohydrate metabolism, amino acid metabolism, lipid metabolism, transport and catabolism, metabolism of cofactors and vitamins, and energy metabolism, were significantly suppressed, whereas the immune system was activated by VHSV infection. A decrease in levels of amino acids such as valine, leucine, and isoleucine, as well as in their derivative carnitines, was observed after VHSV infection. In addition, an increase in arachidonic acid level was noted. Integrated analysis of transcriptome and metabolome using KEGG pathway database revealed four types of responses in the kidneys of olive flounder to VHSV infection. Among these, the mechanisms related to the immune system and protein synthesis were activated, whereas ATP synthesis and the antioxidant system activity were suppressed. This is the first study describing the mechanisms of metabolic responses to VHSV infection in olive flounder. The results suggest that the suppression of ATP synthesis and antioxidant systems, such as glutathione and peroxisome signaling, could be the cause of necrosis, whereas the activation of the immune system could result in the inflammation of kidney tissue in VHSV‐infected olive flounder. HighlightsMetabolic responses to VHSV infection in olive flounder kidney was investigated.The integration of transcriptome and metabolome profiling was applied.Immune system via inflammation and protein synthesis were activated by VHSV infection.ATP synthesis and ROS antioxidant system were suppressed by VHSV infection.

Discrimination of Polygonatum species and identification of novel markers using (1) H NMR- and UPLC/Q-TOF MS-based metabolite profiling.

BACKGROUND Rhizomes of Polygonatum species are commonly used as herbal supplements in Asia. They have different medicinal effects by species but have been misused and mixed owing to their similar taste and smell. Therefore accurate and reliable analytical methods to discriminate between Polygonatum species are required. RESULTS In this study, global and targeted metabolite profiling using (1) H nuclear magnetic resonance ((1) H NMR) spectroscopy and ultra-performance liquid chromatography/quadrupole time-of-flight mass spectrometry (UPLC/Q-TOF MS) was applied to discriminate between different Polygonatum species. Partial least squares discriminant analysis (PLS-DA) models were used to classify and predict species of Polygonatum. Cross-validation derived from PLS-DA revealed good predictive accuracy. Polygonatum species were classified into unique patterns based on K-means clustering analysis. 4-Hydrobenzoic acid and trigonelline were identified as novel marker compounds and quantified accurately. CONCLUSION The results demonstrate that metabolite profiling approaches coupled with chemometric analysis can be used to classify and discriminate between different species of various herbal medicines.