Metabolite profiles of rice cultivars containing bacterial blight-resistant genes are distinctive from susceptible rice

Acta Biochimica et Biophysica Sinica

Volumn 44, Issue 8, 2012, Pages 650-659

  Wu, Jiao ^a,b   Yu, Haichuan ^b   Dai, Haofu ^a   Mei, Wenli ^a   Huang, Xin ^c   Zhu, Shuifang ^c   Peng, Ming ^a  

^a Institute of Tropical Bioscience and Biotechnology   (China)

^b XINXIANG MEDICAL UNIVERSITY   (China)

^c CHINESE ACADEMY OF INSPECTION AND QUARANTINE   (China)

Author keywords

gas chromatography mass spectrometry; genetically modified; metabolomics; rice

Indexed keywords

ALANINE; COUMARIC ACID; FERULIC ACID; GLYCEROL; LINOLEIC ACID; MALIC ACID; MALIC ACID DERIVATIVE; SUCCINIC ACID; TYROSINE; VEGETABLE PROTEIN;

ARTICLE; BIOLOGICAL MODEL; BIOTECHNOLOGY; CHEMISTRY; GENETICS; MASS FRAGMENTOGRAPHY; METABOLISM; METABOLOMICS; METHODOLOGY; MICROBIOLOGY; PLANT DISEASE; PRINCIPAL COMPONENT ANALYSIS; REGRESSION ANALYSIS; RICE; TRANSGENE; TRANSGENIC PLANT;

ALANINE; BIOTECHNOLOGY; COUMARIC ACIDS; GAS CHROMATOGRAPHY-MASS SPECTROMETRY; GLYCEROL; LEAST-SQUARES ANALYSIS; LINOLEIC ACID; MALATES; METABOLOMICS; MODELS, GENETIC; ORYZA SATIVA; PLANT DISEASES; PLANT PROTEINS; PLANTS, GENETICALLY MODIFIED; PRINCIPAL COMPONENT ANALYSIS; SUCCINIC ACID; TRANSGENES; TYROSINE;

AGROBACTERIUM; BACTERIA (MICROORGANISMS);

EID: 84864461377     PISSN: 16729145     EISSN: 17457270     Source Type: Journal    
DOI: 10.1093/abbs/gms043     Document Type: Article

References (43)

1. Mew TW. Current status and future prospects of research on bacterial blight of rice. Ann Rev Phytopathol 1987, 25: 359-382.
2. Zhang Q. Highlights in identification and application of resistance genes to bacterial blight. Chin J Rice Sci 2005, 19: 453-459.
3. Chen S, Lin XH, Xu CG and Zhang Q. Improvement of bacterial blight resistance of 'Minghui 63', an elite restorer line of hybrid rice, by molecular marker-assisted selection. Crop Sci 2000, 40: 239-244. (Pubitemid 30124599)
4. Song WY, Wang GL, Chen LL, Kim HS, Pi LY, Holsten T and Gardner J, et al. A receptor kinase-like protein encoded by the rice disease resistance gene, Xa21. Science 1995, 270: 1804-1806. (Pubitemid 26007223)
5. Khush GS, Bacalangco E and Ogawa T. A new gene for resistance to bacterial blight from O. longistaminate. Rice Genet Newslett 1990, 7: 121-122.
6. Zhang Q, Wang CL, Zhao KJ, Yang WC, Qiao F, Zhou YL and Liu GC. Development of near-isogenic line CBB23 with a new resistance gene to bacterial blight in rice and its application. Chin J Rice Sci 2002, 16: 206-210.
7. Yang ZY, Zhang ZX, Wei YL, Zhao YC and Gao Y. Breeding and characteristics of japonica type wide compatibility line C418. Hybrid Rice 1998, 13: 31-32.
8. Sana TR, Fischer S, Wohlgemuth G, Katrekar A, Jung KH, Ronald PC and Fiehn O. Metabolomic and transcriptomic analysis of the rice response to the bacterial blight pathogen Xanthomonas oryzae pv. oryzae. Metabolomics 2010, 6: 451-465.
9. Zhai W, Chen C, Zhu X, Chen X, Zhang D, Li X and Zhu L. Analysis of T-DNA- Xa21 loci and bacterial blight resistance effects of the transgene Xa21 in transgenic rice. Theor Appl Genet 2004, 109: 534-542. (Pubitemid 39138783)
10. Bai H, Li LY and Liu GZ. Advances of rice bacterial blight disease resistance gene Xa21. Yi Chuan 2006, 28: 745-753.
11. Zheng JT, Tu SH, Zhang JF, Zhao KJ, Zhang SJ and Xie HA. Breeding of restorer lines of hybrid rice with bacterial blight resistance gene Xa23 by using marker-assisted selection. Chin J Rice Sci 2009, 23: 437-439.
12. Xia Z, Zhao X, Fan H, Jin L, Gao L, Luo Y and Zhai W. Improving of bacterial blight resistance of hybrid rice parents through marker assisted selection of the Xa23 gene. Mol Plant Breeding 2010, 8: 652-656.
13. Li XB, Yi CD, Zhai WX, Yang ZY and Zhu LH. A genetically modified japonica restorer line, C418-Xa21, and its hybrid rice with bacterial blight resistance. Sheng Wu Gong Cheng Xue Bao 2001, 17: 380-384.
14. Kok EJ and Kuiper HA. Comparative safety assessment for biotech crops. Trends Biotechnol 2003, 21: 439-444. (Pubitemid 38366065)
15. Fernie AR and Schauer N. Metabolomics-assisted breeding: a viable option for crop improvement? Trends Genet 2009, 25: 39-48.
16. Taylor J, King RD, Altmann T and Fiehn O. Application of metabolomics to plant genotype discrimination using statistics and machine learning. Bioinformatics 2002, 18(Suppl. 2): S241-248.
17. Fiehn O. Metabolomics-the link between genotypes and phenotypes. Plant Mol Biol 2002, 48: 155-171.
18. Yi LZ, He J, Liang YZ, Yuan DL and Chau FT. Plasma fatty acid metabolic profiling and biomarkers of type 2 diabetes mellitus based on GC/MS and PLS-LDA. FEBS Lett 2006, 580: 6837-6845. (Pubitemid 44909124)
19. Bino RJ, Hall RD, Fiehn O, Kopka J, Saito K, Draper J and Nikolau BJ, et al. Potential of metabolomics as a functional genomics tool. Trends Plant Sci 2004, 9: 418-425. (Pubitemid 39160937)
20. Fernie AR, Trethewey RN, Krotzky AJ and Willmitzer L. Metabolite profiling: from diagnostics to systems biology. Nat Rev Mol Cell Biol 2004, 5: 763-769. (Pubitemid 39208185)
21. Schauer N, Steinhauser D, Strelkov S, Schomburg D, Allison G, Moritz T and Lundgren K, et al. GC-MS libraries for the rapid identification of metabolites in complex biological samples. FEBS Lett 2005, 579: 1332-1337. (Pubitemid 40289176)
22. Fiehn O, Kopka J, Dormann P, Altmann T, Trethewey RN and Willmitzer L. Metabolite profiling for plant functional genomics. Nat Biotechnol 2000, 18: 1157-1161.
23. Roessner-Tunali U, Hegemann B, Lytovchenko A, Carrari F, Bruedigam C, Granot D and Fernie AR. Metabolic profiling of transgenic tomato plants overexpressing hexokinase reveals that the influence of hexose phos-phorylation diminishes during fruit development. Plant Physiol 2003, 133: 84-99. (Pubitemid 37144084)
24. Strelkov S, von Elstermann M and Schomburg D. Comprehensive analysis of metabolites in Corynebacterium glutamicum by gas chromatography/mass spectrometry. Biol Chem 2004, 385: 853-861. (Pubitemid 39335308)
25. Lee SH, Woo HM, Jung BH, Lee J, Kwon OS, Pyo HS and Choi MH, et al. Metabolomic approach to evaluate the toxicological effects of nonyl-phenol with rat urine. Anal Chem 2007, 79: 6102-6110. (Pubitemid 47282319)
26. Skogerson K, Harrigan GG, Reynolds TL, Halls SC, Ruebelt M, Iandolino A and Pandravada A, et al. Impact of genetics and environment on the metabolite composition of maize grain. J Agric Food Chem 2010, 58: 3600-3610.
27. Jiao Z, Si XX, Li GK, Zhang ZM and Xu XP. Unintended compositional changes in transgenic rice seeds (Oryza sativa L.) studied by spectral and chromatographic analysis coupled with chemometrics methods. J Agric Food Chem 2010, 58: 1746-1754.
28. Zhou J, Ma C, Xu H, Yuan K, Lu X, Zhu Z and Wu Y, et al. Metabolic profiling of transgenic rice with cryIAc and sck genes: an evaluation of unintended effects at metabolic level by using GC-FID and GC-MS. J Chromatogr B Analyt Technol Biomed Life Sci 2009, 877: 725-732.
29. Lisec J, Schauer N, Kopka J, Willmitzer L and Fernie AR. Gas chroma-tography mass spectrometry-based metabolite profiling in plants. Nat Protoc 2006, 1: 387-396.
30. Jonsson P, Johansson AI, Gullberg J, Trygg J, Jiye A, Grung B and Marklund S, et al. High-throughput data analysis for detecting and identifying differences between samples in GC/MS-based metabolomic analyses. Anal Chem 2005, 77: 5635-5642. (Pubitemid 41268639)
31. Steinhauser D, Usadel B, Luedemann A, Thimm O and Kopka J. CSB.DB: a comprehensive systems-biology database. Bioinformatics 2004, 20: 3647-3651. (Pubitemid 40136804)
32. Kopka J, Schauer N, Krueger S, Birkemeyer C, Usadel B, Bergmuller E and Dormann P, et al. GMD@CSB.DB: the Golm Metabolome Database. Bioinformatics 2005, 21: 1635-1638. (Pubitemid 40542722)
33. Hirai MY, Yano M, Goodenowe DB, Kanaya S, Kimura T, Awazuhara M and Arita M, et al. Integration of transcriptomics and metabolomics for understanding of global responses to nutritional stresses in Arabidopsis thaliana. Proc Natl Acad Sci U S A 2004, 101: 10205-10210. (Pubitemid 38891220)
34. Lee do Y and Fiehn O. High quality metabolomic data for Chlamydomonas reinhardtii. Plant Methods 2008, 4: 7.
35. Ge G, Zheng X, Wu J, Ye Z and Shi C. Analysis of the conditional correlations from different genetic systems between the protein content and the appearance quality traits of Indica rice. J Genet Genomics 2007, 34: 129-137. (Pubitemid 46498856)
36. Fitzgerald MA, McCouch SR and Hall RD. Not just a grain of rice: the quest for quality. Trends Plant Sci 2009, 14: 133-139.
37. Fiehn O, Wohlgemuth G, Scholz M, Kind T, Lee do Y, Lu Y and Moon S, et al. Quality control for plant metabolomics: reporting MSI-compliant studies. Plant J 2008, 53: 691-704. (Pubitemid 351224695)
38. Kameshita I, Tokushige M, Izui K and Katsuki H. Phosphoenolpyruvate carboxylase of Escherichia coli. Affinity labeling with bromopyruvate. J Biochem 1979, 86: 1251-1257. (Pubitemid 10217032)
39. Masumoto C, Miyazawa S, Ohkawa H, Fukuda T, Taniguchi Y, Murayama S and Kusano M, et al. Phosphoenolpyruvate carboxylase intrinsically located in the chloroplast of rice plays a crucial role in ammonium assimilation. Proc Natl Acad Sci USA 2010, 107: 5226-5231.
40. Chen LQ, Hou BH, Lalonde S, Takanaga H, Hartung ML, Qu XQ and Guo WJ, et al. Sugar transporters for intercellular exchange and nutrition of pathogens. Nature 2010, 468: 527-532.
41. Guo W, Zou LF, Li YR, Cui YP, Ji ZY, Cai LL and Zou HS, et al. Fructose-bisphophate aldolase exhibits functional roles between carbon metabolism and the hrp system in rice pathogen Xanthomonas oryzae pv. oryzicola. PLoS One 2012, 7: e31855.
42. Reynolds TL, Nemeth MA, Glenn KC, Ridley WP and Astwood JD. Natural variability of metabolites in maize grain: differences due to genetic background. J Agric Food Chem 2005, 53: 10061-10067. (Pubitemid 43081216)
43. Catchpole GS, Beckmann M, Enot DP, Mondhe M, Zywicki B, Taylor J and Hardy N, et al. Hierarchical metabolomics demonstrates substantial compositional similarity between genetically modified and conventional potato crops. Proc Natl Acad Sci USA 2005, 102: 14458-14462. (Pubitemid 41429719)