• Title/Summary/Keyword: partial least squares discriminant analysis

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LC/MS-based metabolomics approach for selection of chemical markers by domestic production region of Schisandra chinensis (오미자(Schisandra chinensis)의 국내 산지별 화학적마커 선정을 위한 LC/MS 기반의 대사체학 접근법)

  • In Seon Kim;Seon Min Oh;Ha Eun Song;Doo-Young Kim;Dahye Yoon;Dae Young Lee;Hyung Won Ryu
    • Journal of Applied Biological Chemistry
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    • v.66
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    • pp.467-476
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    • 2023
  • Schisandra chinensis (S. chinensis) is a deciduous broad-leaved cave plant belonging to the Schisandraceae family and is widely distributed in East Asia including Korea, Japan, China, and Taiwan. It has been reported that the main components contained in S. chinensis include lignan compounds and triterpenoid compounds. To distinguish the characteristics of S. chinensis by production region of Korea, a discriminant was established by performing metabolite profiling and principal component analysis, a multivariate statistical analysis technique. As a result, 16 types of triterpenoids, 9 types of lignan, and 1 type each of flavonoid, phenylpropanoid, and fatty acid were identified. In addition, through multivariate statistical analysis, it was confirmed that the four groups in Danyang, Moongyeong, Geochang, and Pyeongchang were divided, by applying the s-plot model of orthogonal partial least squares discriminant analysis. Biomarkers were identified: lanostane, cycloartane, schiartane triterpenoid, and dibenzocyclo-octadiene lignan were identified as chemical markers, respectively.

Metabolite Profiling and Bioactivity of Rice Koji Fermented by Aspergillus Strains

  • Kim, Ah-Jin;Choi, Jung-Nam;Kim, Ji-Young;Kim, Hyang-Yeon;Park, Sait-Byul;Yeo, Soo-Hwan;Choi, Ji-Ho;Liu, Kwang-Hyeon;Lee, Choong-Hwan
    • Journal of Microbiology and Biotechnology
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    • v.22 no.1
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    • pp.100-106
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    • 2012
  • In this study, the metabolite profiles of three Aspergillus strains during rice koji fermentation were compared. In the partial least squares discriminant analysis-based gas chromatography-mass spectrometry data sets, the metabolite patterns of A. oryzae (KCCM 60345) were clearly distinguished from A. kawachii (KCCM 60552) and only marginal differences were observed for A. oryzae (KCCM 60551) fermentation. In the 2 days fermentation samples, the overall metabolite levels of A. oryzae (KCCM 60345) were similar to the A. oryzae (KCCM 60551) levels and lower than the A. kawachii (KCCM 60552) levels. In addition, we identified discriminators that were mainly contributing tyrosinase inhibition (kojic acid) and antioxidant activities (pyranonigrin A) in A. oryzae (KCCM 60345) and A. kawachii (KCCM 60552) inoculated rice koji, respectively. In this study, we demonstrated that the optimal inoculant Aspergillus strains and fermentation time for functional rice koji could be determined through a metabolomics approach with bioactivity correlations.

Germination Prediction of Cucumber (cucumis sativus) Seed using Raman Spectroscopy (라만분광을 이용한 오이 종자의 발아예측)

  • Mo, Changyeun;Kang, Sukwon;Lee, Kangjin;Kim, Giyoung;Cho, Byoung-Kwan;Lim, Jong-Guk;Lee, Ho-Sun;Park, Jongryul
    • Journal of Biosystems Engineering
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    • v.37 no.6
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    • pp.404-410
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    • 2012
  • Purpose: The objective of this research was to select high quality cucumber (cucumis sativus) seed by classifying into viable or non-viable one using Raman spectroscopy. Method: Both transmission and back-scattering Raman spectra of viable and non-viable seeds in the range from $150cm^{-1}$ to $1890cm^{-1}$ were collected with a laser illumination. Results: The Raman spectra of cucumber seed showed Raman peaks with features of polyunsaturated fatty acids. The partial least squares-discriminant analysis (PLS-DA) to predict viable seeds was developed with measured transmission and backscattering spectra with Raman spectroscopy and germination test results. Various types of spectra pretreatment were investigated to develop the classification models. The results of developed PLS-DA models using the transmission spectra with mean normalization or range normalization, and back-scattering spectra with mean normalization treatment or baseline correction showed 100% discrimination accuracy. Conclusions: These results showed that Raman spectroscopy technologies can be used to select the high quality cucumber seeds.

Variation of γ-Oryzanol by Incorporation of Green Manure Crops in Korean Rice Cultivars

  • Kim, Heon-Woong;Lee, Sung-Hyeon;Lee, Young-Min;Jang, Hwan-Hee;Hwang, Kyung-A;Cho, Hyun-Suk;Lee, Jeong-Tae;Jeon, Weon-Tai;Kim, Jung-Bong
    • Korean Journal of Soil Science and Fertilizer
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    • v.47 no.4
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    • pp.275-283
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    • 2014
  • The ${\gamma}$-oryzanol, ferulic acid esters, which are well-known for their function on cholesterol lowering and prevention of inflammation, diabetes and cancer, are found in the seeds of cereal crops such as rice, corn, wheat and rye. Among them, rice has been reported to contain the highest ferulic acid esters. Since rice cultivation with green manure as a N source is an environmental friendly agricultural practice, it is necessary to identify and quantify as well as evaluate the variations in these compounds in rice samples as affected by different green manure conditions. A total of ten components of ${\gamma}$-oryzanol were isolated and cycloartenyl ferulate, 24-methylenecycloartanyl ferulate, campesteryl ferulate and sitosteryl ferulate were identified as the major components in Korean rice cultivars, 'Unkwang' and 'Hopum'. Comparing the ${\gamma}$-oryzanol contents of these varieties, 'Unkwang' showed clearly similar pattern with conventional type. With the PLS-DA (partial least squares of discriminant analysis) using SIMCA 11.0 ver., the specific pattern and cluster of ${\gamma}$-oryzanol scores with green manure conditions were confirmed, and thus distinguishing green manure effects were possible.

Intraspecies Volatile Interactions Affect Growth Rates and Exometabolomes in Aspergillus oryzae KCCM 60345

  • Singh, Digar;Lee, Choong Hwan
    • Journal of Microbiology and Biotechnology
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    • v.28 no.2
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    • pp.199-209
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    • 2018
  • Volatile organic compounds (VOCs) are increasingly been recognized as the chemical mediators of mold interactions, shaping their community dynamics, growth, and metabolism. Herein, we selectively examined the time-correlated (0 D-11 D, where D = incubation days) effects of intraspecies VOC-mediated interactions (VMI) on Aspergillus oryzae KCCM 60345 (S1), following co-cultivation with partner strain A. oryzae KACC 44967 (S2), in a specially designed twin plate assembly. The comparative evaluation of $S1_{VMI}$ (S1 subjected to VMI with S2) and its control ($S1_{Con}$) showed a notable disparity in their radial growth ($S1_{VMI}$ < $S1_{Con}$) at 5 D, protease activity ($S1_{VMI}$ > $S1_{Con}$) at 3-5 D, amylase activity ($S1_{VMI}$ < $S1_{Con}$) at 3-5 D, and antioxidant levels ($S1_{VMI}$ > $S1_{Con}$) at 3 D. Furthermore, we observed a distinct clustering pattern for gas chromatography-time of flight-mass spectrometry datasets from 5 D extracts of $S1_{VMI}$ and $S1_{Con}$ in principle component analysis (PC1: 30.85%; PC2: 10.31%) and partial least squares discriminant analysis (PLS-DA) (PLS1: 30.77; PLS2: 10.15%). Overall, 43 significantly discriminant metabolites were determined for engendering the metabolic variance based on the PLS-DA model (VIP > 0.7, p < 0.05). In general, a marked disparity in the relative abundance of amino acids ($S1_{VMI}$ > $S1_{Con}$) at 5 D, organic acids ($S1_{VMI}$ > $S1_{Con}$) at 5 D, and kojic acid ($S1_{VMI}$ < $S1_{Con}$) at 5-7 D were observed. Examining the headspace VOCs shared between S1 and S2 in the twin plate for 5 D incubated samples, we observed the relatively higher abundance of C-8 VOCs (1-octen-3-ol, (5Z)-octa-1,5-dien-3-ol, 3-octanone, 1-octen-3-ol acetate) having known semiochemical functions. The present study potentially illuminates the effects of VMI on commercially important A. oryzae's growth and biochemical phenotypes with subtle details of altered metabolomes.

Discrimination of African Yams Containing High Functional Compounds Using FT-IR Fingerprinting Combined by Multivariate Analysis and Quantitative Prediction of Functional Compounds by PLS Regression Modeling (FT-IR 스펙트럼 데이터의 다변량 통계분석을 이용한 고기능성 아프리칸 얌 식별 및 기능성 성분 함량 예측 모델링)

  • Song, Seung Yeob;Jie, Eun Yee;Ahn, Myung Suk;Kim, Dong Jin;Kim, In Jung;Kim, Suk Weon
    • Horticultural Science & Technology
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    • v.32 no.1
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    • pp.105-114
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    • 2014
  • We established a high throughput screening system of African yam tuber lines which contain high contents of total carotenoids, flavonoids, and phenolic compounds using ultraviolet-visible (UV-VIS) spectroscopy and Fourier transform infrared (FT-IR) spectroscopy in combination with multivariate analysis. The total carotenoids contents from 62 African yam tubers varied from 0.01 to $0.91{\mu}g{\cdot}g^{-1}$ dry weight (wt). The total flavonoids and phenolic compounds also varied from 12.9 to $229{\mu}g{\cdot}g^{-1}$ and from 0.29 to $5.2mg{\cdot}g^{-1}$dry wt. FT-IR spectra confirmed typical spectral differences between the frequency regions of 1,700-1,500, 1,500-1,300 and $1,100-950cm^{-1}$, respectively. These spectral regions were reflecting the quantitative and qualitative variations of amide I, II from amino acids and proteins ($1,700-1,500cm^{-1}$), phosphodiester groups from nucleic acid and phospholipid ($1,500-1,300cm^{-1}$) and carbohydrate compounds ($1,100-950cm^{-1}$). Principal component analysis (PCA) and subsequent partial least square-discriminant analysis (PLS-DA) were able to discriminate the 62 African yam tuber lines into three separate clusters corresponding to their taxonomic relationship. The quantitative prediction modeling of total carotenoids, flavonoids, and phenolic compounds from African yam tuber lines were established using partial least square regression algorithm from FT-IR spectra. The regression coefficients ($R^2$) between predicted values and estimated values of total carotenoids, flavonoids and phenolic compounds were 0.83, 0.86, and 0.72, respectively. These results showed that quantitative predictions of total carotenoids, flavonoids, and phenolic compounds were possible from FT-IR spectra of African yam tuber lines with higher accuracy. Therefore we suggested that quantitative prediction system established in this study could be applied as a rapid selection tool for high yielding African yam lines.

Simultaneous determination and difference evaluation of 14 ginsenosides in Panax ginseng roots cultivated in different areas and ages by high-performance liquid chromatography coupled with triple quadrupole mass spectrometer in the multiple reaction-monitoring mode combined with multivariate statistical analysis

  • Xiu, Yang;Li, Xue;Sun, Xiuli;Xiao, Dan;Miao, Rui;Zhao, Huanxi;Liu, Shuying
    • Journal of Ginseng Research
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    • v.43 no.4
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    • pp.508-516
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    • 2019
  • Background: Ginsenosides are not only the principal bioactive components but also the important indexes to the quality assessment of Panax ginseng Meyer. Their contents in cultivated ginseng vary with the growth environment and age. The present study aimed at evaluating the significant difference between 36 cultivated ginseng of different cultivation areas and ages based on the simultaneously determined contents of 14 ginsenosides. Methods: A high-performance liquid chromatography (HPLC) coupled with triple quadrupole mass spectrometer (MS) method was developed and used in the multiple reaction-monitoring (MRM) mode (HPLC-MRM/MS) for the quantitative analysis of ginsenosides. Multivariate statistical analysis, such as principal component analysis and partial least squares-discriminant analysis, was applied to discriminate ginseng samples of various cultivation areas and ages and to discover the differentially accumulated ginsenoside markers. Results: The developed HPLC-MRM/MS method was validated to be precise, accurate, stable, sensitive, and repeatable for the simultaneous determination of 14 ginsenosides. It was found that the 3- and 5-yr-old ginseng samples were differentiated distinctly by all means of multivariate statistical analysis, whereas the 4-yr-old samples exhibited similarity to either 3- or 5-yr-old samples in the contents of ginsenosides. Among the 14 detected ginsenosides, Rg1, Rb1, Rb2, Rc, 20(S)-Rf, 20(S)-Rh1, and Rb3 were identified as potential markers for the differentiation of cultivation ages. In addition, the 5-yr-old samples were able to be classified in cultivation area based on the contents of ginsenosides, whereas the 3- and 4-yr-old samples showed little differences in cultivation area. Conclusion: This study demonstrated that the HPLC-MRM/MS method combined with multivariate statistical analysis provides deep insight into the accumulation characteristics of ginsenosides and could be used to differentiate ginseng that are cultivated in different areas and ages.

Metabolomic analysis of healthy human urine following administration of glimepiride using a liquid chromatography-tandem mass spectrometry

  • Do, Eun Young;Gwon, Mi-Ri;Kim, Bo Kyung;Ohk, Boram;Lee, Hae Won;Kang, Woo Youl;Seong, Sook Jin;Kim, Hyun-Ju;Yoon, Young-Ran
    • Translational and Clinical Pharmacology
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    • v.25 no.2
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    • pp.67-73
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    • 2017
  • Glimepiride, a third generation sulfonylurea, is an antihyperglycemic agent widely used to treat type 2 diabetes mellitus. In this study, an untargeted urinary metabolomic analysis was performed to identify endogenous metabolites affected by glimepiride administration. Urine samples of twelve healthy male volunteers were collected before and after administration of 2 mg glimepiride. These samples were analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS), and then subjected to multivariate data analysis including principal component analysis and orthogonal partial least squares discriminant analysis. Through this metabolomic profiling, we identified several endogenous metabolites such as adenosine 3', 5'-cyclic monophosphate (cAMP), quercetin, tyramine, and urocanic acid, which exhibit significant metabolomic changes between pre- and posturine samples. Among these, cAMP, which is known to be related to insulin secretion, was the most significantly altered metabolite following glimepiride administration. In addition, the pathway analysis showed that purine, tyrosine, and histidine metabolism was affected by pharmacological responses to glimepiride. Together, the results suggest that the pharmacometabolomic approach, based on LC-MS/MS, is useful in understanding the alterations in biochemical pathways associated with glimepiride action.

Discrimination of the drinking water taste by potentiometric electronic tongue and multivariate analysis (전자혀 및 다변량 분석법을 활용한 먹는물의 구별 방법)

  • Eunju Kim;Tae-Mun Hwang;Jae-Wuk Koo;Jaeyong Song;Hongkyeong Park;Sookhyun Nam
    • Journal of Korean Society of Water and Wastewater
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    • v.37 no.6
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    • pp.425-435
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    • 2023
  • Organoleptic parameters such as color, odor, and flavor influence consumer perception of drinking water quality. This study aims to evaluate the taste of the selected bottled and tap water samples using an electronic tongue (E-tongue) instead of a sensory test. Bottled and tap water's mineral components are related to the overall preference for water taste. Contrary to the sensory test, the potentiometric E-tongue method presented in this study distinguishes taste by measuring the mineral components in water, and the data obtained can be statistically analyzed. Eleven bottled water products from various brands and one tap water from I city in Korea were evaluated. The E-tongue data were statistically analyzed using multivariate statistical tools such as hierarchical clustering analysis (HCA), principal component analysis (PCA), and partial least squares discriminant analysis (PLS-DA). The results show that the E-tongue method can clearly distinguish taste discrimination in drinking water differing in water quality based on the ion-related water quality parameters. The water quality parameters that affect taste discrimination were found to be total dissolved solids (TDS), sodium (Na+), calcium (Ca2+), magnesium (Mg2+), sulfate (SO42-), chloride (Cl-), potassium (K+) and pH. The distance calculation of HCA was used to quantify the differences between 12 different types of drinking water. The proposed E-tongue method is a practical tool to quantitatively evaluate the differences between samples in water quality items related to the ionic components. It can be helpful in quality control of drinking water.

Mass-Based Metabolomic Analysis of Lactobacillus sakei and Its Growth Media at Different Growth Phases

  • Lee, Sang Bong;Rhee, Young Kyoung;Gu, Eun-Ji;Kim, Dong-Wook;Jang, Gwang-Ju;Song, Seong-Hwa;Lee, Jae-In;Kim, Bo-Min;Lee, Hyeon-Jeong;Hong, Hee-Do;Cho, Chang-Won;Kim, Hyun-Jin
    • Journal of Microbiology and Biotechnology
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    • v.27 no.5
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    • pp.925-932
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    • 2017
  • Changes in the metabolite profiles of Lactobacillus sakei and its growth media, based on different culture times (0, 6, 12, and 24 h), were investigated using gas chromatography-mass spectrometry (MS) and liquid chromatography-MS with partial least squares discriminant analysis, in order to understand the growth characteristics of this organism. Cell and media samples of L. sakei were significantly separated on PLS-DA score plots. Cell and media metabolites, including sugars, amino acids, and organic acids, were identified as major metabolites contributing to the difference among samples. The alteration of cell and media metabolites during cell growth was strongly associated with energy production. Glucose, fructose, carnitine, tryptophan, and malic acid in the growth media were used as primary energy sources during the initial growth stage, but after the exhaustion of these energy sources, L. sakei could utilize other sources such as trehalose, citric acid, and lysine in the cell. The change in the levels of these energy sources was inversely similar to the energy production, especially ATP. Based on these identified metabolites, the metabolomic pathway associated with energy production through lactic acid fermentation was proposed. Although further studies are required, these results suggest that MS-based metabolomic analysis might be a useful tool for understanding the growth characteristics of L. sakei, the most important bacterium associated with meat and vegetable fermentation, during growth.