Unintended polar metabolite profiling of carotenoid-biofortified transgenic rice reveals substantial equivalence to its non-transgenic counterpart

Kim, Jae Kwang; Park, Soo-Yun; Lee, Si Myung; Lim, Sung-Hun; Kim, Hyo Jin; Oh, Sung‐Dug; Yeo, Yunsoo; Cho, Hyun Suk; Ha, Sun-Hwa

doi:10.1007/s11816-012-0231-6

Cited by 39 publications

(28 citation statements)

References 25 publications

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“…Polar metabolite extraction was performed as described previously [24]. A total of 10 mg of ground sample was extracted with 1 ml of a mixed solvent of methanol/water/chloroform (2.5∶1:1 by vol.).…”

Section: Methodsmentioning

confidence: 99%

“…The primary metabolite profile is closely related to the phenotype of the organism and includes important nutritional characteristics [22], [23]. In addition, metabolite profiling combined with chemometrics has proved to be useful in functional genomics research [24]. Metabolomics allows for classification of samples with diverse biological status, origin, or quality by using chemometric techniques such as hierarchical clustering analysis (HCA), and partial least squares discriminant analysis (PLS-DA).…”

Section: Introductionmentioning

confidence: 99%

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Metabolomics Analysis and Biosynthesis of Rosmarinic Acid in Agastache rugosa Kuntze Treated with Methyl Jasmonate

Kim

Uddin

et al. 2013

PLoS ONE

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This study investigated the effect of methyl jasmonate (MeJA) on metabolic profiles and rosmarinic acid (RA) biosynthesis in cell cultures of Agastache rugosa Kuntze. Transcript levels of phenylpropanoid biosynthetic genes, i.e., ArPAL, Ar4CL, and ArC4H, maximally increased 4.5-fold, 3.4-fold, and 3.5-fold, respectively, compared with the untreated controls, and the culture contained relatively high amounts of RA after exposure of cells to 50 µM MeJA. RA levels were 2.1-, 4.7-, and 3.9-fold higher after exposure to 10, 50, and 100 µM MeJA, respectively, than those in untreated controls. In addition, the transcript levels of genes attained maximum levels at different time points after the initial exposure. The transcript levels of ArC4H and Ar4CL were transiently induced by MeJA, and reached a maximum of up to 8-fold at 3 hr and 6 hr, respectively. The relationships between primary metabolites and phenolic acids in cell cultures of A. rugosa treated with MeJA were analyzed by gas chromatography coupled with time-of-flight mass spectrometry. In total, 45 metabolites, including 41 primary metabolites and 4 phenolic acids, were identified from A. rugosa. Metabolite profiles were subjected to partial least square-discriminate analysis to evaluate the effects of MeJA. The results indicate that both phenolic acids and precursors for the phenylpropanoid biosynthetic pathway, such as aromatic amino acids and shikimate, were induced as a response to MeJA treatment. Therefore, MeJA appears to have an important impact on RA accumulation, and the increased RA accumulation in the treated cells might be due to activation of the phenylpropanoid genes ArPAL, ArC4H, and Ar4CL.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Metabolomics Analysis and Biosynthesis of Rosmarinic Acid in Agastache rugosa Kuntze Treated with Methyl Jasmonate

Kim

Uddin

et al. 2013

PLoS ONE

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“…The great advantage of these techniques is that they are simpler and more rapid due to the simplicity of sample preparation and analysis compared to chromatographic techniques. These spectroscopic techniques are applied in various plant research fields, including rapid discrimination among plant species (Kim et al 2004); metabolic evaluation of GM plants (Roessner et al 2001;Kim et al 2013), commercial food stocks (Pongsuwan et al 2008) and medicinal herbs (Lee et al 2009); improvement of breeding programmes (Das and Parida 2014); understanding various physiological and stress responses (Lopez-Sanchez et al 2010); and determination of gene functions (Okazaki and Saito 2012).…”

Section: Introductionmentioning

confidence: 99%

Monthly metabolic changes and PLS prediction of carotenoid content of citrus fruit by combined Fourier transform infrared spectroscopy and quantitative HPLC analysis

Kim

Ahn

Kwon

et al. 2015

Plant Biotechnol Rep

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This work examined the potential of Fourier transform infrared spectroscopy (FT-IR) spectroscopy and high-performance liquid chromatography (HPLC) analysis in evaluating metabolic changes during ripening of citrus fruit. Further, the feasibility of prediction modeling of carotenoid content by multivariate statistical analysis combined with FT-IR spectral and HPLC data was examined without additional HPLC analysis. FT-IR spectra of citrus (Citrus unshiu Marc. cv. Miyagawa) fruit peels and flesh were measured at monthly intervals of fruit development. Quantification of carotenoids from the fruit was confirmed by quantitative HPLC analysis. The most remarkable evolution of FT-IR spectral decrease during ripening of fruit was found in the amide region (1500-1700 cm -1 ), whereas there was an increase in the carbohydrate region (1000-1200 cm -1 ). The evolution of different FT-IR spectral bands was related to fruit constituents, including organic acids, carbohydrates, carotenoids, and phenolic compounds. Significant qualitative changes in the carotenoid pattern included an increase in bcryptoxanthin and decrease in lutein content during citrus fruit development. The content of antheraxanthin (R 2 = 0.9117), b-carotene (R 2 = 0.8816), b-cryptoxanthin (R 2 = 0.8856), and violaxanthin (R 2 = 0.7305) from peels of citrus fruit could be predicted from FT-IR spectral data using partial least square (PLS) regression modeling. Considering the results of PLS-discriminant analysis (PLS-DA) of FT-IR spectral data and PLS regression modeling of carotenoid content, FT-IR in combination with multivariate analysis enables not only discrimination of metabolic variation during fruit development, but also prediction of carotenoid content from citrus fruit.

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“…In addition, the levels of sucrose, mannitol and glutamic were increased in GM rice. In another study, carotenoid biofortified GM rice and five conventional rice cultivars were analyzed by GC-TOF MS [82]. PCA carried out with the 52 identified metabolites could separate the pigmented and non-pigmented rice samples (Fig.…”

Section: Ms-based Technologiesmentioning

confidence: 99%

Profiling of Genetically Modified Organisms Using Omics Technologies

Valdés

Simó

Ibáñez

et al. 2014

Comprehensive Analytical Chemistry

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Strict regulations including risk assessment, labeling, traceability and marketing have been established due to the controversial safety aspects of genetically modified organisms (GMOs).One of the main polemic issues associated with GMOs safety are the possible unintended effects, defined as effects that go beyond the primary expected effects of the genetic modification. In order to effectively investigate the potential adverse effects on the human health, including the existence or not of unintended effects, new analytical tools are needed to facilitate comprehensive compositional studies of GMOs. In this context, profiling technologies have the potential to provide valuable information regarding GMOs composition that can be useful for characterization, traceability and even GMO detection. In this chapter, the application of the main -omics technologies (transcriptomics, proteomics, and metabolomics) in combination with bioinformatics and chemometrics tools to GMO profiling are discussed.

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Unintended polar metabolite profiling of carotenoid-biofortified transgenic rice reveals substantial equivalence to its non-transgenic counterpart

Cited by 39 publications

References 25 publications

Metabolomics Analysis and Biosynthesis of Rosmarinic Acid in Agastache rugosa Kuntze Treated with Methyl Jasmonate

Metabolomics Analysis and Biosynthesis of Rosmarinic Acid in Agastache rugosa Kuntze Treated with Methyl Jasmonate

Monthly metabolic changes and PLS prediction of carotenoid content of citrus fruit by combined Fourier transform infrared spectroscopy and quantitative HPLC analysis

Profiling of Genetically Modified Organisms Using Omics Technologies

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