转基因抗虫棉棉籽组分的代谢组学研究

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中国生物工程杂志 ›› 2012, Vol. 32 ›› Issue (11) : 35-41.

研究报告

转基因抗虫棉棉籽组分的代谢组学研究

孙彩霞¹, 汪莹¹, 吴晓菲¹, 陈利军², 武志杰²

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Metabonomic Study on the Composition of Insect-resistant Transgenic Cottonseeds

SUN Cai-xia¹, WANG Ying¹, WU Xiao-fei¹, CHEN Li-jun², WU Zhi-jie²

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文章历史 +

摘要

采用核磁共振氢谱(¹H NMR)获取不同转基因抗虫棉棉籽及其非转基因对照棉籽的代谢物谱,并结合多维统计分析探查植物基因工程操作是否引发棉籽中代谢产物种类和数量的非预期改变。结果表明,不同棉籽的¹H NMR谱图轮廓基本特征相似,均可分为氨基酸区、碳水化合物区及芳香区;当谱图按分区扩展后,多处峰信号在转基因与非转基因对照间有明显的不同。采用偏最小二乘法-判别分析(PLS-DA)可实现转基因抗虫棉棉籽与非转基因对照的代谢轮廓判别且分类的效果优于主成分分析(PCA)方法。转基因抗虫棉籽与其非转基因对照间的主要差异代谢物与初级氮代谢、三羧酸循环及脂肪酸代谢有关。

Abstract

The term of metabolome has been used to describe the responses of plant to external perturbations recently. The study of metabolite profiling of different insect-resistant cottonseeds and their non-transgenic counterparts using ¹H NMR and multivariate analysis technique was performed to investigate the unintended metabolic variations associated with genetic modifications. The results obtained showed that the overall appearance of the spectrum was quite similar among different cottonseeds. However, there were many different peak signals in the animo acids region (3～0.5 ppm) of the expansion spectra of transgenic cottonseeds when compared with their controls. Although score plots generated using principal component analysis showed the potential to distinguish transgenic cottonseeds from non-transgenic controls, a better classification between them was obtained by partial least square-discriminant analysis. The major compounds contributing to the discrimination were those metabolites that involved the metabolic pathway of fatty acid, the primary nitrogen metabolism and the tricarboxylic acid cycle.

导出引用

孙彩霞, 汪莹, 吴晓菲, 陈利军, 武志杰. 转基因抗虫棉棉籽组分的代谢组学研究[J]. 中国生物工程杂志, 2012, 32(11): 35-41

SUN Cai-xia, WANG Ying, WU Xiao-fei, CHEN Li-jun, WU Zhi-jie. Metabonomic Study on the Composition of Insect-resistant Transgenic Cottonseeds[J]. China Biotechnology, 2012, 32(11): 35-41

中图分类号： O657.3

参考文献

[1] 许国旺, 杨军. 代谢组学及其研究进展. 色谱, 2003, 21(4): 316-320. Xu G W, Yang J. Recent advances in metabonomics. Chinese Journal of Chromatography, 2003, 21(4): 316-320.
[2] Stitt M, Sulpice R, Keurentjes J. Metabolic Networks: How to identify key components in the regulation of metabolism and growth. Plant Physiology, 2010, 152(2): 428-444.
[3] Stitt M. Nitrate regulation of metabolism and growth. Current Opinion in Plant Biology, 1999, 2(3): 178-186.
[4] 滕中秋, 付卉青, 贾少华, 等. 植物应答非生物胁迫的代谢组学研究进展. 植物生态学报, 2011, 35 (1): 110-118. Teng Z Q, Fu H Q, Jia S H, et al. Review of current progress in the metabolomics for plant response to abiotic stress. Chinese Journal of Plant Ecology, 2011, 35 (1): 110-118.
[5] Cellini F, Chesson A, Colquhoun I, et al. Unintended effects and their detection in genetically modified crops. Food and Chemical Toxicology, 2004, 42(7): 1089-1125.
[6] Karl-Heinz O, Nelly A, Singh B, et al. Metabonomics classifies pathways affected by bioactive compounds. Phytochemistry, 2003, 62(6): 971-985.
[7] Noteborn H P J M, Lommen A, van der Jagt R C, et al. Chemical fingerprinting for the evaluation of unintended secondary metabolic changes in transgenic food crops. Journal of Biotechnology, 2000, 77(1): 103-114.
[8] Roessner U, Luedemann A, Brust D, et al. Metabolic profiling allows comprehensive phenotyping of genetically or environmentally modified plant systems. Plant Cell, 2001, 13(1):11-29.
[9] Charlton A J, Farrington W H H, Brereton P J. Application of ¹H NMR and multivariate statistics for screening complex mixtures: quality control and authenticity of instant coffee. Journal of Agricultural Food Chemistry, 2002, 50(11): 3098-3103.
[10] Manetti C, Bianchetti C, Casciani L, et al. A metabonomic study of transgenic maize (Zea mays) seeds revealed variations in osmolytes and branched Amino Acids. Journal of Experimental Botany, 2006, 57, (11): 2613-2625.
[11] Elangovan A V, Tyagi PK, Shrivastav A K, et al. GMO ( Bt-Cry1Ac gene) cottonseed meal is cimilar to non-GMO low free gossypol cottonseed meal for growth performance of broiler chickens. Animal Feed Science Technology, 2006, 129(3-4): 252-263.
[12] Gall Le G, Metzdorff S B, Pedersen J, et al. Metabolite profiling of Arabidopsis thaliana (L.) plants transformed with an antisense chalcone synthase gene. Metabolomics, 2005, 1(2): 181-198.
[13] Ren Y, Wang T, Peng Y, et al. Distinguish transgenic from non-transgenic Arabidopsis plants by ¹H NMR-based metabolic fingerprinting. Journal of Genetic and Genomics, 2009, 36(10):621-628.
[14] Choi H K, Choi Y H, Verberne M, et al. Metabolic fingerprinting of wild type and transgenic tobacco plants by ¹H NMR and multivariate analysis technique. Phytochemistry, 2004, 65(7): 857-864.
[15] Trygg J, Holmes E, Lundstedt T J. Chemometrics in metabonomics. Journal of Proteome Research, 2007, 6(2): 469-479.
[16] Savorani F, Tomasi G, Engelsen S B. icoshift: A versatile tool for the rapid alignment of ¹D NMR spectra. Journal of Magnetic Resonance, 2010, 202(2): 190-202.
[17] 贾伟. 医学代谢组学. 上海:上海科学技术出版社, 2011. 193-218. Jia W. Medical Metabonomics. Shanghai: Shanghai Science and Technology Press, 2011. 193-218.
[18] Wold S, Sjstrm M, Eriksson L. PLS-regression: a basic tool of chemometrics. Chemometrics and Intelligent Laboratory Systems, 2001, 58(2): 109-130.
[19] Wiklund S, Johansson E, Sjostrom L, et al. Visualization of GC/TOF-MS-based metabolomics data for identification of biochemically interesting compounds using OPLS class models. Analytical Chemistry, 2008, 80(1): 115-122.
[20] Castro C, Manetti C. A multiway approach to analyze metabonomic data: a study of maize seeds development. Analytical Biochemistry, 2007, 371(2):194-200.
[21] Beneduci A, Chidichimo G, Dardo G, et al. Highly routinely reproducible alignment of ¹H NMR spectral peaks of metabolites in huge sets of urines. Analytica Chimica Acta, 2011, 685(2):186-195.
[22] Sieciechowicz K A, Joy K W, Ireland R J. The metabolism of asparagine in plants. Phytochemistry, 1988, 27(3): 663-671.
[23] 孙彩霞, 张玉兰, 孙玉全, 等. 三种不同光谱学方法测定转基因抗虫棉组织营养元素含量. 光谱学与光谱分析, 2009, 29(11): 3038-3041. Sun C X, Zhang Y L, Sun Y Q, et al. Determination of nutrient elements in transgenic insect-resistant cotton tissues by three different spectroscopical methods. Spectroscopy and Spectral Analysis, 2009, 29(11): 3038-3041.
[24] Conner A J, Jacobs J M E. Genetic engineering of crops as potential source of genetic hazard in the human diet. Mutation Research, Genetic Toxicology and Environmental Mutagenesis, 1999, 443(1-2): 223-234.
[25] Bouché N, Fromm H. GABA in plants: just a metabolite? Trends in Plant Science, 2004, 9(3): 110-115.
[26] Schultz J C. Biochemical ecology: how plants fight dirty. Nature, 2002, 416(6878): 267-271.
[27] Poerschmann J, Rauschen S, Langer U, et al. Fatty acid patterns of genetically modified Cry3Bb1 expressing Bt-maize MON88017 and its near-isogenic line. Journal of Agricultural Food Chemistry, 2009, 57(1): 127-132.
[28] Defernez M, Gunning Y M, Parr A J, et al. NMR and HPLC-UV profiling of potatoes with genetic modifications to metabolic pathways. Journal of Agricultural and Food Chemistry, 2004, 52(20): 6075-6085.