• Journal of Plant Biotechnology
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• v.33 no.3
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• pp.161-169
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• 2006

Plant metabolomics is a plant biology field for identifying all of the metabolites found in a certain plant cell, tissue, organ, or whole plant in a given time and conditions and for studying changes in metabolic profiling as time goes or conditions change. Metabolomics is one of the most recently developed omics for holistic approach to biology and is a kind of systems biology. For holistic approach, metabolomics frequently uses chemometrics or multivariate statistical analysis of metabolic profillings. In plant biology, metabolomics is useful to determine functions of genes often in combination with DHA microarrays by analyzing tagged mutants of the model plants Arabidopsis and rice. This review paper attempted to introduce basic concepts of metabolomics and practical uses of multivariate statistical analysis of metabolic profiling obtained by $^1$H HMR and Fourier transform infrared spectrometry.

• Journal of the Korean Magnetic Resonance Society
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• v.22 no.2
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• pp.26-33
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• 2018

Xanthium sibiricum is used as a traditional folk medicine for the treatment of cancer, fever, headache, nasal sinusitis, and skin pruritus. This study aimed to identify components from Xanthium sibiricum extracts using an SPE-800MHz NMR-MS hyphenated system. The simultaneous acquisition of MS and NMR spectra from the same chromatographic peaks significantly increases the depth of information acquired for the compound and allows the elucidation of structures that would not be possible using MS or NMR data alone. LC -NMR analysis was conducted using a HPLC separation system coupled to 800 MHz spectrometer equipped with a cryoprobe, and a SPE unit was used to automatically trap chromatographic peaks using a HPLC pump. LC-MS analysis was conducted with a Q-TOF MS instrument using ESI ionization in the negative ion mode. Using the hyphenated analysis, several secondary metabolites were identified, such as 3',5'-O-dicaffeoylquinic acid, 1',5'-O-dicaffeoyl- quinic acid, and ethyl caffeate. These results demonstrate that the SPE-800MHz NMR-MS hyphenated system can be used to identify metabolites within natural products that have complex mixtures.

• Journal of the Korean Magnetic Resonance Society
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• v.16 no.1
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• pp.46-66
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• 2012

Metabolomic studies using human urine have shown that human metabolism is altered by a variety of environmental, cultural, and physiological factors. Comprehensive information about normal human metabolite profiles is necessary for accurate clinical diagnosis of disease and for disease prevention and treatment. In this study, metabolite correlation analyses, using $^1H$ nuclear magnetic resonance (NMR) spectroscopy coupled with multivariate statistics, were performed on human urine to compare metabolic differences based on gender and/or obesity in healthy human subjects. First, we applied partial least squares discriminant analysis to the NMR spectral data set to verify the data's ability to discriminate by gender and obesity. Then, the differences in metabolite-metabolite correlation between male and female, and between normal and high body mass index (obese) subjects were investigated through pairwise correlations. Creatine and several metabolites, including isoleucine, trans-aconitate, and trimethylamine N-oxide (TMAO), exhibited different quantitative relationships depending on gender. Dimethylamine had a different correlation with glycine and TMAO, based on gender. The correlation of TMAO with amino acids was considerably lower in obese, compared to normal, subjects. We expect that the results will shed light on the metabolic pathways of healthy humans and will assist in the accurate diagnosis of human disease.

• Mass Spectrometry Letters
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• v.11 no.1
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• pp.1-5
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• 2020

In this study, some of the recently reported data processing strategies were evaluated and modified based on their capabilities and a brief workflow for data mining was redefined for Q-TOF LC-MS based untargeted metabolomics. Commercial pooled human plasma samples were used for this purpose. An ultrafiltration procedure was applied on sample preparation. Sample set was analyzed through Q-TOF LC/MS. A C18 column (Agilent Zorbax 1.8 µM, 50 × 2.1 mm) was used for chromatographic separation. Raw chromatograms were processed using XCMS - R programming language edition and Isotopologue Parameter Optimization (IPO) was used to optimize XCMS parameters. The raw XCMS table was processed using MS Excel to find reliable and reproducible peaks. Totally 1650 reliable and reproducible potential metabolite peaks were found based on the data processing procedures given in this paper. The redefined dataset was upload into MetaboAnalyst platform and the identified metabolites were matched with 86 metabolic pathways. Thus, two list were obtained and presented in this study as supplement files. The first list is to present the retention times and m/z values of detected metabolite peaks. The second list is the metabolic pathways related with the identified metabolites. The briefly described data processing strategies and dataset presented in this study could be beneficial for the researchers working on untargeted metabolomics for processing their data and validating their results.

• Microbiology and Biotechnology Letters
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• v.34 no.4
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• pp.306-310
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• 2006

For screening of the compounds exhibiting antimicrobial activities against the D-alanyl-D-alanine of Gram positive bacteria, approximately 2,500 actinomycetes isolated from soil were examined far antimicrobial activity. In consequence, we recently isolated the Streptomyces sp. G91353 strain produced an active compound, A91353, that inhibits the growth of Gram positive bacteria. A91353 was identified as N-acetyl-phenylalanine by various spectroscopic methods. The minimum inhibitory concentration (MIC) values of N-acetyl-phenylalanine on Gram positive bacteria such as Streptococcus pyogenes 308A, Streptococcus pyogenes 77A were determined as $50{\mu}g/ml$, respectively, but did not effect on Gram negative strains. These results indicate that N-acetyl-phenylalanine have an antimicrobial activity, which may be caused by the disturbance of D-alanyl-D-alanine synthesis.

• Journal of Microbiology and Biotechnology
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• v.18 no.7
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• pp.1203-1206
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• 2008

A Gram-positive strain designated as MSL-$14^T$ isolated from a soil sample collected from Bigeum Island, Korea, was subjected to polyphasic taxonomy. The isolate was strictly aerobic. Cells were short rods and motile. Optimum growth temperature and pH was 28$^{\circ}C$ and 7.0, respectively. It was characterized chemotaxonomically as having a cell-wall peptidoglycan type based on LL-2,6-diaminopimelic acid and MK-$8(H_4)$ as the predominant menaquinone. The major fatty acids were iso-$C_{16:0}$, $C_{17:1}$ omega8c, and $C_{18:1}$ omega9c. The G+C content was 67.6 mol%. Phylogenetic analysis based on the 16S rRNA gene sequence revealed that strain MSL-$14^T$ is affiliated to the genus Nocardioides and formed a distinct lineage within the genus. MSL-$14^T$ showed highest sequence similarity to Nocardioides aestuarii JCM $12125^T$, having a similarity of 96.5%. Based on the 16S rRNA gene sequence divergence and phenotypic characteristics, it is proposed that strain MSL-$14^T$ should be classified as representing a novel member of the genus Nocardioides, for which we propose the name Nocardioides tritolerans sp. novo The type strain is strain MSL-$14^T$ (=KCTC $19289^T$=DSM $19320^T$).

• Journal of the Korean Magnetic Resonance Society
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• v.16 no.2
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• pp.91-102
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• 2012

Metabolomics is the systematic identification and quantification of all metabolites in an organism or biological sample. NMR has been used as a major application tool in plant metabolomics such as quality control, chemotaxonomy, and analysis of genetically modified plants. Herbal medicines are the important therapeutics and are used to manage common diseases such as cold, inflammation, pain, heart diseases, liver cirrhosis, diabetes and central nerve system diseases. Herb plants include various kinds of species such as geranium, mint, and thyme and so on and contain different kinds of metabolites. We performed NMR-based metabolomics study on the seven different species of herb plants using $^1H$ NMR experiments and OPLS-DA to understand the correlation between the classification of herb plants and their metabolite contents. This study showed clear metabolic discrimination among various herb plants. This metabolmics study found several diagnostic NMR signals which are able to be used as bio-markers for identification of the specific herb plants among various species. Clear metabolic discrimination of herb plants suggests three chemotaxonomic groups of herb species.

• Animal Bioscience
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• v.37 no.5
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• pp.918-928
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• 2024

Objective: The adulteration of raw beef (BMr) with dog meat (DMr) and pork (PMr) becomes a serious problem because it is associated with halal status, quality, and safety of meats. This research aimed to develop an effective authentication method to detect non-halal meats (dog meat and pork) in beef using metabolomics approach. Methods: Liquid chromatography-high resolution mass spectrometry (LC-HRMS) using untargeted approach combined with chemometrics was applied for analysis non-halal meats in BMr. Results: The untargeted metabolomics approach successfully identified various metabolites in BMr DMr, PMr, and their mixtures. The discrimination and classification between authentic BMr and those adulterated with DMr and PMr were successfully determined using partial least square-discriminant analysis (PLS-DA) with high accuracy. All BMr samples containing non-halal meats could be differentiated from authentic BMr. A number of discriminating metabolites with potential as biomarkers to discriminate BMr in the mixtures with DMr and PMr could be identified from the analysis of variable importance for projection value. Partial least square (PLS) and orthogonal PLS (OPLS) regression using discriminating metabolites showed high accuracy (R² >0.990) and high precision (both RMSEC and RMSEE <5%) in predicting the concentration of DMr and PMr present in beef indicating that the discriminating metabolites were good predictors. The developed untargeted LC-HRMS metabolomics and chemometrics successfully identified non-halal meats adulteration (DMr and PMr) in beef with high sensitivity up to 0.1% (w/w). Conclusion: A combination of LC-HRMS untargeted metabolomic and chemometrics promises to be an effective analytical technique for halal authenticity testing of meats. This method could be further standardized and proposed as a method for halal authentication of meats.

• Genomics & Informatics
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• v.19 no.2
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• pp.13.1-13.8
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• 2021

Ranked in the topmost position among the deadliest diseases in the world, cardiovascular diseases (CVDs) are a global burden with alterations in heart and blood vessels. Early diagnostics and prognostics could be the best possible solution in CVD management. OMICS (genomics, proteomics, transcriptomics, and metabolomics) approaches could be able to tackle the challenges against CVDs. Genome-wide association studies along with next-generation sequencing with various computational biology tools could lead a new sight in early detection and possible therapeutics of CVDs. Human cardiac proteins are also characterized by mass spectrophotometry which could open the scope of proteomics approaches in CVD. Besides this, regulation of gene expression by transcriptomics approaches exhibits a new insight while metabolomics is the endpoint on the downstream of multi-omics approaches to confront CVDs from the early onset. Although a lot of challenges needed to overcome in CVD management, OMICS approaches are certainly a new prospect.

• The Korean Journal of Pesticide Science
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• v.12 no.1
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• pp.97-101
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• 2008

For the isolation of Actinomycetes showing nematocidal activity against Pine wood nematode, Bursaphelenchus xylophilus, about 2000 culture broth of Actinomycetes were tested and their activity were compared with that of Streptomyces avermitilis resulting a selected strain AW050027. The cultural, morphological and physiological analysis was performed for the identification of a selected strain. Phylogenetic analyses based on 165 rDNA gene sequences showed that the selected strain AW050027 belonged to the genus Micromonospora and M. corioriae $NAR01^T$ was the closest neighbors, sharing 98.9% 165 rDNA gene sequence similarity.