Selection of high ginsenoside producing ginseng hairy root lines using targeted metabolic analysis

Woo, Sung-Sick; Song, Ji-Sook; Lee, Ju‐Yeon; In, Dong Su; Chung, Hwa-Jee; Liu, Jang Ryol; Choi, Dong-Woog

doi:10.1016/j.phytochem.2004.08.039

Cited by 54 publications

(31 citation statements)

References 28 publications

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“…PCA uses an N-dimensional vector approach to separate samples on the basis of the cumulative correlation of all metabolite data and then identifies the vector (eigenvector) that yields the greatest separation among samples without requiring prior knowledge of the data sets [36]. Mean-centered and par-scaled (scaled to square root of SD) mathematical methods were performed to pretreat the data sets resulting from the above samples.…”

Section: Pcamentioning

confidence: 99%

Ultra‐performance LC/TOF MS analysis of medicinal Panax herbs for metabolomic research

Xie

Plumb

et al. 2008

J of Separation Science

159

108

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Original Paper Ultra-performance LC/TOF MS analysis of medicinal Panax herbs for metabolomic researchIn this study, metabolite profiling of five medicinal Panax herbs including Panax ginseng (Chinese ginseng), Panax notoginseng (Sanchi), Panax japonicus (Rhizoma Panacis Majoris), Panax quinquefolium L. (American ginseng), and P. ginseng (Korean ginseng) were performed using ultra-performance LC-quadrupole TOF MS (UPLC-QTOFMS) and multivariate statistical analysis technique. Principal component analysis (PCA) of the analytical data showed that the five Panax herbs could be separated into five different groups of phytochemicals. The chemical markers such as ginsenoside Rf, 20(S)-pseudoginsenoside F11, malonyl gisenoside Rb1, and gisenoside Rb2 accountable for such variations were identified through the loadings plot of PCA, and were identified tentatively by the accurate mass of TOFMS and partially verified by the available reference standards. Results from this study indicate that the proposed method is reliable for the rapid analysis of a group of metabolites present in herbal medicines and other natural products and applicable in the differentiation of complex samples that share similar chemical ingredients. IntroductionMetabolomics aims to identify and quantify the full complement of low-molecular-weight, soluble metabolites in actively metabolizing tissues [1 -4], which has aroused extensive awareness and interests, especially in the botanical studies such as quality control of plants [5 -9], plant engineering [10, 11] using a number of techniques including NMR or different combinations of LC, GC, and MS. Also, based on the multivariate analysis of complex biological profiles, metabolomics has been successfully applied to plant genotype discrimination and differentiation [1, 12 -14]. Plants are rich in chemically diverse metabolites, which cannot be completely detected by a single analytical method currently available in phytochemical laboratories. Over the past 20 years, HPLC/MS (LC/MS) has become one of the main analytical techniques used in controlling the quality and consistency of both the chemical markers and active substances of traditional Chinese medicines (TCMs). Despite early claims that MS, and particularly MS/MS, is able to remove the need for good chromatographic separation in the analysis of low abundance samples, a poor LC run prior to MS analysis will lead to issues of ion suppression and isobaric interferences that cannot be overcome by a spectrometer alone. More recently, the desire for significantly reduced analysis time with increased sample throughput, resolution, and sensitivity has resulted in the development of ultrafast separation and identification using LC-MS techniques [15,16]. Among the various LC platforms, ultra-performance LC (UPLC) is considered suitable for metabolite profiling and metabolomics [17 -28], especially, for large-scale untargeted metabolic profiling due to its enhanced reproducibility in retention time [24]. The ability to generate high peak capacities in short...

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Section: Pcamentioning

confidence: 99%

Ultra‐performance LC/TOF MS analysis of medicinal Panax herbs for metabolomic research

Xie

Plumb

et al. 2008

J of Separation Science

159

108

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“…1 cm, 50 mg FW), the amount of pHBAGE reached a steady level, around 40 mol/g fresh weight, which represented around 1.3 % of tissue fresh weight and 14 % of tissue dry weight. This exceeds the best yield previously achieved elsewhere: 7.3 % of dry weight in leaves of transgenic sugarcane harboring the same HCHL gene, cultivated for 35 weeks (McQualter et al, 2005); and it compares very well with the yields of other useful plant secondary products achieved in other in vitro culture systems, notably anthocyanin, 15 % DW (Rajendran et al, 1992) ; berberine, 13.2 % DW (Sato and Yamada, 1984);and shikonin, 12.4 % DW (Fujita et al, 1981); ginsenoside, 1.7 % DW (Woo et al, 2004). Considering these results, 14 % DW in plant tissues seems to be near the maximum possible level for the accumulation of secondary metabolites, although the level of the primary metabolite, sucrose, can reach around 20 % in sugar beet (Gurel et al, 2008).…”

Section: Discussionmentioning

confidence: 85%

HCHL expression in hairy roots of Beta vulgaris yields a high accumulation of p-hydroxybenzoic acid (pHBA) glucose ester, and linkage of pHBA into cell walls

Rahman

Kouno

Hashiguchi

et al. 2009

Bioresource Technology

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As part of a study to explore the potential for new or modified bio-product formation, Beta vulgaris (sugar beet) has been genetically modified to express in root-organ culture a bacterial gene of phenylpropanoid catabolism. The HCHL gene, encoding p-hydroxycinnamoyl-CoA hydratase/lyase , was introduced into Beta vulgaris under the control of a CaMV 35S promoter, using Agrobacterium rhizogenes LBA 9402. Hairy root clones expressing the HCHL gene, together with non-expressing clones, were analyzed and revealed that one expression-positive clone accumulated the glucose ester of p-hydroxybenzoic acid (pHBA) at about 14 % on a dry weight basis. This is the best yield achieved in plant systems so far. Determination of cell-wall components liberated by alkaline hydrolysis confirmed that the ratio of pHBA to ferulic acid was considerably higher in the HCHL-expressing clones, whereas only ferulic acid was detected in a non-expressing clone. The change in cell-wall components also resulted in a decrease in tensile strength in the HCHL-expressing clones.

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“…Therefore, such classical methods using single-dimensional data might produce incorrect information. PCA is an unsupervised pattern recognition tool which uses an n-dimensional vector approach to separate samples on the basis of the cumulative correlation of all component data and then identifi es the vector that yields the greatest separation between samples [19]. The multivariate data for PCA can be obtained from a variety of spectroscopic experiments such as MS, NMR, HPLC, GC, LC/MS, GC/MS, and IR.…”

Section: Resultsmentioning

confidence: 99%

Discrimination of Panax ginseng Roots Cultivated in Different Areas in Korea Using HPLC-ELSD and Principal Component Analysis

Lee¹,

Cho²,

Lee³

et al. 2011

Journal of Ginseng Research

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Selection of high ginsenoside producing ginseng hairy root lines using targeted metabolic analysis

Cited by 54 publications

References 28 publications

Ultra‐performance LC/TOF MS analysis of medicinal Panax herbs for metabolomic research

Ultra‐performance LC/TOF MS analysis of medicinal Panax herbs for metabolomic research

HCHL expression in hairy roots of Beta vulgaris yields a high accumulation of p-hydroxybenzoic acid (pHBA) glucose ester, and linkage of pHBA into cell walls

Discrimination of Panax ginseng Roots Cultivated in Different Areas in Korea Using HPLC-ELSD and Principal Component Analysis

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