• Korean Journal of Agricultural Science
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• v.45 no.3
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• pp.447-454
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• 2018

Zearalenone (ZEN), a mycotoxin produced by Fusarium in food and feed, causes serious damage to the health of humans and livestock. Therefore, we compared the metabolomic profiles in the liver, serum, and urine of piglets fed a ZEN-contaminated diet using proton nuclear magnetic resonance ($^1H-NMR$) spectroscopy. The spectra from the three different samples, treated with ZEN concentrations of 0.8 mg/kg for 4 weeks, were aligned and identified using MATLAB. The aligned data were subjected to discriminating analysis using multivariate statistical analysis and a web server for metabolite set enrichment analysis. The ZEN-exposed groups were almost separated in the three different samples. Metabolic analysis showed that 28, 29, and 20 metabolites were profiled in the liver, serum, and urine, respectively. The discriminating analysis showed that the alanine, arginine, choline, and glucose concentrations were increased in the liver. Phenylalanine and tyrosine metabolites showed high concentrations in serum, whereas valine showed a low concentration. In addition, the formate levels were increased in the ZEN-treated urine. For the integrated analysis, glucose, lactate, taurine, glycine, alanine, glutamate, glutamine, and creatine from orthogonal partial least squares discriminant analysis (OPLS-DA) were potential compounds for the discriminating analysis. In conclusion, our findings suggest that potential biomarker compounds can provide a better understanding on how ZEN contaminated feed in swine affects the liver, serum, and urine.

• Biomolecules & Therapeutics
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• v.21 no.6
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• pp.470-475
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• 2013

Ultraviolet (UV) radiation is a major environmental factor that leads to acute and chronic reactions in the human skin. UV exposure induces wrinkle formation, DNA damage, and generation of reactive oxygen species (ROS). Most mechanistic studies of skin physiology and pharmacology related with UV-irradiated skin have focused on proteins and their related gene expression or single-targeted small molecules. The present study identified and analyzed the alteration of skin metabolites following UVB irradiation and topical retinyl palmitate (RP, 5%) treatment in hairless mice using direct analysis in real time (DART) time-of-flight mass spectrometry (TOF-MS) with multivariate analysis. Under the negative ion mode, the DART ion source successfully ionized various fatty acids including palmitoleic and linolenic acid. From DART-TOF-MS fingerprints measured in positive mode, the prominent dehydrated ion peak (m/z: 369, M+H-$H_2O$) of cholesterol was characterized in all three groups. In positive mode, the discrimination among three groups was much clearer than that in negative mode by using multivariate analysis of orthogonal partial-least squares-discriminant analysis (OPLS-DA). DART-TOF-MS can ionize various small organic molecules in living tissues and is an efficient alternative analytical tool for acquiring full chemical fingerprints from living tissues without requiring sample preparation. DART-MS measurement of skin tissue with multivariate analysis proved to be a powerful method to discriminate between experimental groups and to find biomarkers for various experiment models in skin dermatological research.

• Journal of Ginseng Research
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• v.38 no.1
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• pp.52-58
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• 2014

To determine whether Fourier transform (FT)-IR spectral analysis combined with multivariate analysis of whole-cell extracts from ginseng leaves can be applied as a high-throughput discrimination system of cultivation ages and cultivars, a total of total 480 leaf samples belonging to 12 categories corresponding to four different cultivars (Yunpung, Kumpung, Chunpung, and an open-pollinated variety) and three different cultivation ages (1 yr, 2 yr, and 3 yr) were subjected to FT-IR. The spectral data were analyzed by principal component analysis and partial least squares-discriminant analysis. A dendrogram based on hierarchical clustering analysis of the FT-IR spectral data on ginseng leaves showed that leaf samples were initially segregated into three groups in a cultivation age-dependent manner. Then, within the same cultivation age group, leaf samples were clustered into four subgroups in a cultivar-dependent manner. The overall prediction accuracy for discrimination of cultivars and cultivation ages was 94.8% in a cross-validation test. These results clearly show that the FT-IR spectra combined with multivariate analysis from ginseng leaves can be applied as an alternative tool for discriminating of ginseng cultivars and cultivation ages. Therefore, we suggest that this result could be used as a rapid and reliable F1 hybrid seed-screening tool for accelerating the conventional breeding of ginseng.

• Korean Journal of Agricultural Science
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• v.48 no.4
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• pp.875-890
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• 2021

In order to confirm the safety of a genetically modified organism (GMO), we assess its potential toxicity on non-target insects and spiders. In this study, the effects of GM soybean, a type of vitamin-A-enhanced transgenic soybean with tolerance to the herbicide glufosinate, were assessed under a field condition. The study compared this vitamin-A-enhanced transgenic soybean and a non-GM soybean (Gwangan) in a living modified organism (LMO) isolated field of Kyungpook National University (Gunwi) and the National Institute Agricultural Sciences (Jeonju) in the Republic of Korea in 2019 - 2020. In total, 207,760 individual insects and arachnids, representing 81 families and 13 orders, were collected during the study. From the two types of soybean fields, corresponding totals of 105,765 and 101,995 individuals from the vitamin-A-enhanced transgenic soybean and Gwangan samples areas were collected. An analysis of variance indicated no significant differences (p < 0.05). A multivariate analysis showed that the dominance and richness outcomes of plant-dwelling insects were similar. The data on insect species population densities were subjected to a principal component analysis (PCA) and an orthogonal partial least squares-discriminant analysis (OPLS-DA), which did not distinguish between the two varieties, i.e., the vitamin-A-enhanced transgenic soybean and the non-GM soybean in any cultivated field. However, the results of the PCA analysis could be divided overall into four groups based on the yearly survey areas. Therefore, there was no evidence for the different impact of vitamin A-enhanced transgenic soybean on the above-ground insects and spiders compared to non-GM soybean.

• Mass Spectrometry Letters
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• v.4 no.4
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• pp.59-66
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• 2013

A metabolomics study was conducted to identify urinary biomarkers for breast cancer, using gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS), analyzed by principal components analysis (PCA) as well as a partial least squares-discriminant analysis (PLS-DA) for a metabolic pattern analysis. To find potential biomarkers, urine samples were collected from before- and after-mastectomy of breast cancer patients and healthy controls. Androgens, corticoids, estrogens, nucleosides, and polyols were quantitatively measured and urinary metabolic profiles were constructed through PCA and PLS-DA. The possible biomarkers were discriminated from quantified targeted metabolites with a metabolic pattern analysis and subsequent screening. We identified two biomarkers for breast cancer in urine, ${\beta}$-cortol and 5-methyl-2-deoxycytidine, which were categorized at significant levels in a student t-test (p-value < 0.05). The concentrations of these metabolites in breast cancer patients significantly increased relative to those of controls and patients after mastectomy. Biomarkers identified in this study were highly related to metabolites causing oxidative DNA damage in the endogenous metabolism. These biomarkers are not only useful for diagnostics and patient stratification but can be mapped on a biochemical chart to identify the corresponding enzyme for target identification via metabolomics.

• Asian-Australasian Journal of Animal Sciences
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• v.33 no.1
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• pp.79-90
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• 2020

Objective: In the present study, an liquid chromatography/mass spectrometry (LC/MS) metabolomics approach was performed to investigate potential biomarkers of milk production in high- and low-milk-yield dairy cows and to establish correlations among rumen fluid metabolites. Methods: Sixteen lactating dairy cows with similar parity and days in milk were divided into high-yield (HY) and low-yield (LY) groups based on milk yield. On day 21, rumen fluid metabolites were quantified applying LC/MS. Results: The principal component analysis and orthogonal correction partial least squares discriminant analysis showed significantly separated clusters of the ruminal metabolite profiles of HY and LY groups. Compared with HY group, a total of 24 ruminal metabolites were significantly greater in LY group, such as 3-hydroxyanthranilic acid, carboxylic acids, carboxylic acid derivatives (L-isoleucine, L-valine, L-tyrosine, etc.), diazines (uracil, thymine, cytosine), and palmitic acid, while the concentrations of 30 metabolites were dramatically decreased in LY group compared to HY group, included gentisic acid, caprylic acid, and myristic acid. The metabolite enrichment analysis indicated that protein digestion and absorption, ABC transporters and unsaturated fatty acid biosynthesis were significantly different between the two groups. Correlation analysis between the ruminal microbiome and metabolites revealed that certain typical metabolites were exceedingly associated with definite ruminal bacteria; Firmicutes, Actinobacteria, and Synergistetes phyla were highly correlated with most metabolites. Conclusion: These findings revealed that the ruminal metabolite profiles were significantly different between HY and LY groups, and these results may provide novel insights to evaluate biomarkers for a better feed digestion and may reveal the potential mechanism underlying the difference in milk yield in dairy cows.

• Environmental Analysis Health and Toxicology
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• v.25 no.4
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• pp.295-306
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• 2010

Objectives : This study was undertaken to examine the metabolomic changes due to gender and diurnal variation at sampling time and to identify an appropriate time point for urine sampling in epidemiologic studies using metabolomic profiles. Methods : Urine samples were collected twice a day (morning and afternoon) from 20 healthy Korean adults after fasting for 8 hours. The metabolomic assay was investigated using $^1H$ NMR spectroscopy coupled with the principal components analysis (PCA) and partial least squares discriminant analysis (PLS-DA). The metabolites responsible for differentiation between groups were identified through the loading plot of PLS-DA and quantified using Chenomx NMR Suite with a 600 MHz library. Results : Metabolites responsible for differentiation in gender and sampling time were creatinine, trimethyl anine oxide (TMAO), hippurate, mannitol, citrate and acetoacetate. Dimethylamine showed difference only as a factor of diurnal time. The level of creatinine was higher in men compared to women, and the levels of citrate, TMAO, hippurate, mannitol, and acetoacetate were higher in women compared to men. The levels of creatinine, TMAO, hippurate, dimethylamine and mannitol were higher in the morning rather than the afternoon while those of citrate and acetoacetate were higher in the afternoon rather than the morning. Conclusions : Since urinary metabolomic profiles varied by gender and diurnal cycle, urine sampling should be performed at the same time point for all participants in epidemiologic studies using metabolomic profiles.

• Journal of Ginseng Research
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• v.46 no.2
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• pp.290-295
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• 2022

Background: Dried and red ginseng are well-known types of processed ginseng and are widely used as healthy food. The dried and red ginseng quality may vary with the storage period of raw ginseng. Therefore, herein, the effect of the storage period of fresh ginseng on processed ginseng quality was evaluated through multicomponent quantification with statistical analysis. Methods: A method based on ultrahigh performance liquid chromatography coupled to triple quadrupole mass spectrometry in multiple-reaction monitoring mode (UPLC-MRM-MS) was developed for quantitation of ginsenosides and oligosaccharides in dried and red ginseng. Principal component analysis and partial least squares discriminant analysis were conducted to evaluate the dynamic distributions of ginsenosides and oligosaccharides after different storage periods. Results: Eighteen PPD, PPT and OLE ginsenosides and nine reducing and nonreducing oligosaccharides were identified and quantified. With storage period extension, the ginsenoside content in the processed ginseng increased slightly in the first 2 weeks and decreased gradually in the following 9 weeks. The content of reducing oligosaccharides decreased continuously as storage time extending, while that of the nonreducing oligosaccharides increased. Chemical conversions occurred during storage, based on which potential chemical markers for the storage period evaluation of fresh ginseng were screened. Conclusion: According to ginsenoside and oligosaccharide distributions, it was found that the optimal storage period was 2 weeks and that the storage period of fresh ginseng should not exceed 4 weeks at 0 ℃. This study provides deep insights into the quality control of processed ginseng and comprehensive factors for storage of raw ginseng.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1245-1245
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• 2001

Food adulteration is a serious consumer fraud and a matter of concern to food processors and regulatory agencies. A range of analytical methods have been investigated to facilitate the detection of adulterated or mis-labelled foods & food ingredients but most of these require sophisticated equipment, highly-qualified staff and are time-consuming. Regulatory authorities and the food industry require a screening technique which will facilitate fast and relatively inexpensive monitoring of food products with a high level of accuracy. Near infrared spectroscopy has been investigated for its potential in a number of authenticity issues including meat speciation (McElhinney, Downey & Fearn (1999) JNIRS, 7(3), 145-154; Downey, McElhinney & Fearn (2000). Appl. Spectrosc. 54(6), 894-899). This report describes further analysis of these spectral sets using a hierarchical approach and binary decisions solved using logistic regression. The sample set comprised 230 homogenized meat samples i. e. chicken (55), turkey (54), pork (55), beef (32) and lamb (34) purchased locally as whole cuts of meat over a 10-12 week period. NIR reflectance spectra were recorded over the wavelength range 400-2498nm at 2nm intervals on a NIR Systems 6500 scanning monochromator. The problem was defined as a series of binary decisions i. e. is the meat red or white\ulcorner is the red meat beef or lamb\ulcorner, is the white meat pork or poultry\ulcorner etc. Each of these decisions was made using an individual binary logistic model based on scores derived from principal component or partial least squares (PLS1 and PLS2) analysis. The results obtained were equal to or better than previous reports using factorial discriminant analysis, K-nearest neighbours and PLS2 regression. This new approach using a combination of exploratory and logistic analyses also appears to have advantages of transparency and the use of inherent structure in the spectral data. Additionally, it allows for the use of different data transforms and multivariate regression techniques at each decision step.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1152-1152
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• 2001

Food adulteration is a serious consumer fraud and a matter of concern to food processors and regulatory agencies. A range of analytical methods have been investigated to facilitate the detection of adulterated or mis-labelled foods & food ingredients but most of these require sophisticated equipment, highly-qualified staff and are time-consuming. Regulatory authorities and the food industry require a screening technique which will facilitate fast and relatively inexpensive monitoring of food products with a high level of accuracy. Near infrared spectroscopy has been investigated for its potential in a number of authenticity issues including meat speciation (McElhinney, Downey & Fearn (1999) JNIRS, 7(3), 145 154; Downey, McElhinney & Fearn (2000). Appl. Spectrosc. 54(6), 894-899). This report describes further analysis of these spectral sets using a hierarchical approach and binary decisions solved using logistic regression. The sample set comprised 230 homogenized meat samples i. e. chicken (55), turkey (54), pork (55), beef (32) and lamb (34) purchased locally as whole cuts of meat over a 10-12 week period. NIR reflectance spectra were recorded over the wavelength range 400-2498nm at 2nm intervals on a NIR Systems 6500 scanning monochromator. The problem was defined as a series of binary decisions i. e. is the meat red or white\ulcorner is the red meat beef or lamb\ulcorner, is the white meat pork or poultry\ulcorner etc. Each of these decisions was made using an individual binary logistic model based on scores derived from principal component or partial least squares (PLS1 and PLS2) analysis. The results obtained were equal to or better than previous reports using factorial discriminant analysis, K-nearest neighbours and PLS2 regression. This new approach using a combination of exploratory and logistic analyses also appears to have advantages of transparency and the use of inherent structure in the spectral data. Additionally, it allows for the use of different data transforms and multivariate regression techniques at each decision step.