• Journal of Microbiology and Biotechnology
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• v.28 no.8
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• pp.1247-1259
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• 2018

Raspberries are polyphenol-rich fruits with the potential to reduce the severity of the clinical signs associated with obesity, a phenomenon that may be related to changes in the gut microbiota. The aim of this study was to investigate the effect of raspberry supplementation on the fecal microbiota using an in vivo model of obesity. Obese diabetic db/db mice were used in this study and assigned to two experimental groups (with and without raspberry supplementation). Fecal samples were collected at the end of the supplementation period (8 weeks) and used for bacterial 16S rRNA gene profiling using a MiSeq instrument (Illumina). QIIME 1.8 was used to analyze the 16S data. Raspberry supplementation was associated with an increased abundance of Lachnospiraceae (p = 0.009), a very important group for gut health, and decreased abundances of Lactobacillus, Odoribacter, and the fiber degrader S24-7 family as well as unknown groups of Bacteroidales and Enterobacteriaceae (p < 0.05). These changes were enough to clearly differentiate bacterial communities accordingly to treatment, based on the analysis of UniFrac distance metrics. However, a predictive approach of functional profiles showed no difference between the treatment groups. Fecal metabolomic analysis provided critical information regarding the raspberry-supplemented group, whose relatively higher phytosterol concentrations may be relevant for the host health, considering the proven health benefits of these phytochemicals. Further studies are needed to investigate whether the observed differences in microbial communities (e.g., Lachnospiraceae) or metabolites relate to clinically significant differences that can prompt the use of raspberry extracts to help patients with obesity.

• Journal of Plant Biotechnology
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• v.33 no.3
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• pp.209-222
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• 2006

The whole genome sequence was completed in arabidopsis and rice. Large amounts of EST data have been available from many other plants. Also, vast quantities of diverse biological data have been generated by various '-omics' technologies such as transcriptomics, proteomics, and metabolomics. Bioinformatics plays an essential role in extracting useful information from these tremendous amounts of biological data. In this review we introduced experimental methods to generate massive data, applications to plant science such as plant disease resistance and molecular breeding and bioinformatics tools and web sites available in plant biotechnology R&D. We concluded that new experimental methods and bioinfomation analysis techniques have made major contributions to the development of plant biotechnology and that bioinformatics has become a critical factor in plant biotechnology R&D.

• Genomics & Informatics
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• v.7 no.1
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• pp.38-40
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• 2009

The EST Knowledge Integrated System, EKIS (http://ekis.kribb.re.kr), was established as a part of Korea's Ministry of Education, Science and Technology initiative for genome sequencing and application research of the biological model organisms (GEAR) project. The goals of the EKIS are to collect EST information from GEAR projects and make an integrated database to provide transcriptomic and metabolomic information for biological scientists. The EKIS constitutes five independent categories and several retrieval systems in each category for incorporating massive EST data from high-throughput sequencing of 65 different species. Through the EKIS database, scientists can freely access information including BLAST functional annotation as well as Genechip and pathway information for KEGG. By integrating complex data into a framework of existing EST knowledge information, the EKIS provides new insights into specialized metabolic pathway information for an applied industrial material.

• BMB Reports
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• v.51 no.1
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• pp.14-20
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• 2018

Biomedical research involving nanoparticles has produced useful products with medical applications. However, the potential toxicity of nanoparticles in biofluids, cells, tissues, and organisms is a major challenge. The '-omics' analyses provide molecular profiles of multifactorial biological systems instead of focusing on a single molecule. The 'omics' approaches are necessary to evaluate nanotoxicity because classical methods for the detection of nanotoxicity have limited ability in detecting miniscule variations within a cell and do not accurately reflect the actual levels of nanotoxicity. In addition, the 'omics' approaches allow analyses of in-depth changes and compensate for the differences associated with high-throughput technologies between actual nanotoxicity and results from traditional cytotoxic evaluations. However, compared with a single omics approach, integrated omics provides precise and sensitive information by integrating complex biological conditions. Thus, these technologies contribute to extended safety evaluations of nanotoxicity and allow the accurate diagnoses of diseases far earlier than was once possible in the nanotechnology era. Here, we review a novel approach for evaluating nanotoxicity by integrating metabolomics with metabolomic profiling and transcriptomics, which is termed "metabotranscriptomics."

• Bulletin of the Korean Chemical Society
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• v.33 no.7
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• pp.2156-2162
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• 2012

Many literatures focus on the biological relevance and the identification of biomarkers for disease activity assessment while less attention has been paid to the development of standard procedures for sample preparation and storage based on liquid chromatography technique. The influencing factors including protein precipitation, storage temperature, storage time, and reconstitution by ultra pure water were analyzed employing HPLC-DAD. The effects were investigated from five participants over three months by principal components analysis (PCA) and the values of percent changes (PC). The samples with protein precipitation might slow the rate of bacterial enzymatic conversion. After protein precipitation, the average PC of urine samples ($0.136{\pm}0.013$, n = 5) is relatively less than that of the serum samples ($0.173{\pm}0.026$, n = 5) for three months. Minimal effects on metabolic profiles of serum and urine (PC < 0.15) are reasonable for metabolomic studies after protein precipitation and storage at $-20^{\circ}C$ for two months.

• Journal of the Korean Magnetic Resonance Society
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• v.22 no.4
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• pp.149-157
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• 2018

Diabetes is known to be one of common causes for several types of peripheral nerve damage. Diabetic neuropathy (DN) is a significant complication lowering the quality of life that can be frequently found in diabetes patients. In this study, the metabolomic characteristic of DN and Diabetes was investigated with NMR spectroscopy. The sera samples were collected from DN patients, Diabetes patients, and healthy volunteers. Based on the pair-wise comparison, three metabolites were found to be noticeable: glucose, obviously, was upregulated both in DN patients (DNP) and Diabetes. Citrate is also increased in both diseases. However, the dietary nutrient and biosynthesized metabolite from glucose, ascorbate, was elevated only in DNP, compared to healthy control. The multivariate model of OPLS-DA clearly showed the group separation between healthy control-DNP and healthy control-Diabetes. The most significant metabolites that contributed the group separation included glucose, citrate, ascorbate, and lactate. Lactate did not show the statistical significance of change in t-test while it tends to down-regulated both in DNP and Diabetes. We also conducted the ROC curve analysis to make a multivariate model for discrimination of healthy control and diseases with the identified three metabolites. As a result, the discrimination model between healthy control and DNP (or Diabetes) was successful while the model between DNP and Diabetes was not satisfactory for discrimination. In addition, multiple combinations of lactate and citrate in the OPLS-DA model of healthy control and diabetes group (DNP + Diabetes patients) gave good ROC value of 0.952, which imply these two metabolites could be used for diagnosis of Diabetes without glucose information.

• Journal of Ginseng Research
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• v.43 no.4
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• pp.654-665
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• 2019

Background: Panax ginseng Meyer has widely been used as a traditional herbal medicine because of its diverse health benefits. Amounts of ginseng compounds, mainly ginsenosides, vary according to seasons, varieties, geographical regions, and age of ginseng plants. However, no study has comprehensively determined perturbations of various metabolites in ginseng plants including roots and leaves as they grow. Methods: Nuclear magnetic resonance ($^1H$ NMR)-based metabolomics was applied to better understand the metabolic physiology of ginseng plants and their association with climate through global profiling of ginseng metabolites in roots and leaves during whole growing periods. Results: The results revealed that all metabolites including carbohydrates, amino acids, organic acids, and ginsenosides in ginseng roots and leaves were clearly dependent on growing seasons from March to October. In particular, ginsenosides, arginine, sterols, fatty acids, and uracil diphosphate glucose-sugars were markedly synthesized from March until May, together with accelerated sucrose catabolism, possibly associated with climatic changes such as sun exposure time and rainfall. Conclusion: This study highlights the intrinsic metabolic characteristics of ginseng plants and their associations with climate changes during their growth. It provides important information not only for better understanding of the metabolic phenotype of ginseng but also for quality improvement of ginseng through modification of cultivation.

• Laboraroty Animal Research
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• v.34 no.4
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• pp.232-238
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• 2018

Animal models have been used to elucidate the pathophysiology of varying diseases and to provide insight into potential targets for therapeutic intervention. Although alternatives to animal testing have been proposed to help overcome potential drawbacks related to animal experiments and avoid ethical issues, their use remains vital for the testing of new drug candidates and to identify the most effective strategies for therapeutic intervention. Particularly, the study of metabolic diseases requires the use of animal models to monitor whole-body physiology. In line with this, the National Institute of Food and Drug Safety Evaluation (NIFDS) in Korea has established their own animal strains to help evaluate both efficacy and safety during new drug development. The objective of this study was to characterize the response of C57BL/6NKorl mice from the NIFDS compared with that of other mice originating from the USA and Japan in a chemical-induced diabetic condition. Multiple low-dose treatments with streptozotocin were used to generate a type-1 diabetic animal model which is closely linked to the known clinical pathology of this disease. There were no significantly different responses observed between the varying streptozotocin-induced type-1 diabetic models tested in this study. When comparing control and diabetic mice, increases in liver weight and disturbances in serum amino acids levels of diabetic mice were most remarkable. Although the relationship between type-1 diabetes and BCAA has not been elucidated in this study, the results, which reveal a characteristic increase in diabetic mice of all origins are considered worthy of further study.

• Animal Bioscience
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• v.34 no.12
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• pp.1930-1939
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• 2021

Objective: The aim of the study was to conduct metabolic profiling of dairy cattle serum and urine using proton nuclear magnetic resonance (¹H-NMR) spectroscopy and to compare the results obtained with those of other dairy cattle herds worldwide so as to provide a basic dataset to facilitate research on metabolites in serum and urine. Methods: Six dairy cattle were used in this study; all animals were fed the same diet, which was composed of total mixed ration; the fed amounts were based on voluntary intake. Blood from the jugular neck vein of each steer was collected at the same time using a separate serum tube. Urine samples were collected by hand sweeping the perineum. The metabolites were determined by ¹H-NMR spectroscopy, and the obtained data were statistically analyzed by performing principal component analysis, partial least squares-discriminant analysis, variable importance in projection scores, and metabolic pathway data using Metaboanalyst 4.0. Results: The total number of metabolites in the serum and urine was measured to be 115 and 193, respectively, of which 47 and 81, respectively were quantified. Lactate (classified as an organic acid) and urea (classified as an aliphatic acylic compound) exhibited the highest concentrations in serum and urine, respectively. Some metabolites that have been associated with diseases such as ketosis, bovine respiratory disease, and metritis, and metabolites associated with heat stress were also found in the serum and urine samples. Conclusion: The metabolites measured in the serum and urine could potentially be used to detect diseases and heat stress in dairy cattle. The results could also be useful for metabolomic research on the serum and urine of ruminants in Korea.

• Animal Bioscience
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• v.34 no.2
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• pp.213-222
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• 2021

Objective: The metabolites that constitute the rumen fluid and milk in dairy cattle were analyzed using proton nuclear magnetic resonance (1H-NMR) spectroscopy and compared with the results obtain for other dairy cattle herds worldwide. The aim was to provide basic dataset for facilitating research on metabolites in rumen fluid and milk. Methods: Six dairy cattle were used in this study. Rumen fluid was collected using a stomach tube, and milk was collected using a pipeline milking system. The metabolites were determined by 1H-NMR spectroscopy, and the obtained data were statistically analyzed by principal component analysis, partial least squares discriminant analysis, variable importance in projection scores, and metabolic pathway data using Metaboanalyst 4.0. Results: The total numbers of metabolites in rumen fluid and milk were measured to be 186 and 184, and quantified as 72 and 109, respectively. Organic acid and carbohydrate metabolites exhibited the highest concentrations in rumen fluid and milk, respectively. Some metabolites that have been associated with metabolic diseases (acidosis and ketosis) in cows were identified in rumen fluid, and metabolites associated with ketosis, somatic cell production, and coagulation properties were identified in milk. Conclusion: The metabolites measured in rumen fluid and milk could potentially be used to detect metabolic diseases and evaluate milk quality. The results could also be useful for metabolomic research on the biofluids of ruminants in Korea, while facilitating their metabolic research.