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Chinese Journal of Applied Ecology 2015-Dec

[Metabolic profiling of the short-term responses of Nicotiana tabacum leaves cultivated under different LED lights].

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Lin Meng
Meng Liang
Cheng-dong Wang
Xiao-bing Liu
Wen-jing Song
Jiao Shi
Yi-min Xu

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The physiologically mature tobacco (Nicotiana tabacum) leaves was exposed to different light-emitting diode (LED) lights, i.e. ultraviolet A (UV-A), blue, green, yellow, red, white, to investigate their short-term response. Results showed that: 1) 68 GC/MS-stable metabolites were detected by non-targeted method. In the PLS-DA score plot, tobacco leaf samples showed clear grouping in each light cultivating condition. 61 metabolites were identified in mass spectra library. Besides, 45 metabolites, mainly including organic acids, carbohydrates, TCA cycle intermediate metabolites and amino acids, showed significant differences among the six light treatments. Hierarchical cluster analysis (HCA) and heat map showed that differential metabolites could be divided into five groups, and there were significant differences among the six treatments, especially under red and blue lights. Except for the metabolites of group B, almost all other metabolites contents in tobacco leaves treated with red light were higher than those under blue light. 2) Contents of solanesol, 3 alkaloids and 5 polyphenols were measured with targeted method. 4 alkaloids, including nicotine detected by non-targeted method, showed similar variation among all treatments, of which red and yellow light increased alkaloid accumulation significantly. The kaempferol-3-O-rutinoside and rutin showed similar variation among the six treatments, with the lowest content under blue light and the highest content under yellow light, nevertheless, 3 other polyphenols were differently affected by light qualities. The aolanesol accumulation was significantly repressed by yellow light, but showed highest content under blue light. In conclusion, light quality affected many metabolic pathways significantly in tobacco, such as fatty acid metabolism, glycometabolism, alkaloid metabolism, amino acid metabolism, tricarboxylic acid cycle and shikimate pathway.

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