Dissection of flag leaf metabolic shifts and their relationship with those occurring simultaneously in developing seed by application of non-targeted metabolomics


Autoři: Chaoyang Hu aff001;  Jun Rao aff003;  Yue Song aff004;  Shen-An Chan aff004;  Takayuki Tohge aff005;  Bo Cui aff002;  Hong Lin aff002;  Alisdair R. Fernie aff005;  Dabing Zhang aff002;  Jianxin Shi aff002
Působiště autorů: Key Laboratory of Marine Biotechnology of Zhejiang Province, Key Laboratory of Applied Marine Biotechnology of Ministry of Education, School of Marine Sciences, Ningbo University, Ningbo, China aff001;  Joint International Research Laboratory of Metabolic & Developmental Sciences, SJTU-University of Adelaide Joint Centre for Agriculture and Health, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China aff002;  Jiangxi Cancer Hospital, Nanchang, China aff003;  Agilent Technologies Incorporated Company, Shanghai, China aff004;  Central Metabolism Group, Max Planck Institute of Molecular Plant Physiology, Potsdam, Golm, Germany aff005
Vyšlo v časopise: PLoS ONE 15(1)
Kategorie: Research Article
doi: 10.1371/journal.pone.0227577

Souhrn

Rice flag leaves are major source organs providing more than half of the nutrition needed for rice seed development. The dynamic metabolic changes in rice flag leaves and the detailed metabolic relationship between source and sink organs in rice, however, remain largely unknown. In this study, the metabolic changes of flag leaves in two japonica and two indica rice cultivars were investigated using non-targeted metabolomics approach. Principal component analysis (PCA) revealed that flag leaf metabolomes varied significantly depending on both species and developmental stage. Only a few of the metabolites in flag leaves displayed the same change pattern across the four tested cultivars along the process of seed development. Further association analysis found that levels of 45 metabolites in seeds that are associated with human nutrition and health correlated significantly with their levels in flag leaves. Comparison of metabolomics of flag leaves and seeds revealed that some flavonoids were specific or much higher in flag leaves while some lipid metabolites such as phospholipids were much higher in seeds. This reflected not only the function of the tissue specific metabolism but also the different physiological properties and metabolic adaptive features of these two tissues.

Klíčová slova:

Amino acid metabolism – Carbohydrate metabolism – Carbohydrates – Leaves – Lipid metabolism – Metabolites – Rice – Seeds


Zdroje

1. Zhang H. & Flottmann S. Source-sink manipulations indicate seed yield in canola is limited by source availability. Eur. J. Agron. 2018, 96, 70–76.

2. Xing Y. & Zhang Q. Genetic and Molecular Bases of Rice Yield. Annu. Rev. Plant Biol. 2010, 61, 421–442. doi: 10.1146/annurev-arplant-042809-112209 20192739

3. Watanabe M. et al. Comprehensive dissection of spatiotemporal metabolic shifts in primary, secondary, and lipid metabolism during developmental senescence in Arabidopsis. Plant Physiol. 2013, 162, 1290–1310. doi: 10.1104/pp.113.217380 23696093

4. Schiltz S., Munier-Jolain N., Jeudy C., Burstin J. & Salon C. Dynamics of exogenous nitrogen partitioning and nitrogen remobilization from vegetative organs in pea revealed by 15N in vivo labeling throughout seed filling. Plant Physiol. 2005, 137, 1463–1473. doi: 10.1104/pp.104.056713 15793068

5. Buchananwollaston V. et al. The molecular analysis of leaf senescence-a genomics approach. Plant Biotechnol. J. 2010, 1, 3–22.

6. Gepstein S. Leaf senescence—not just a ‘wear and tear’ phenomenon. Genome Biol. 2004, 5, 212–212. doi: 10.1186/gb-2004-5-3-212 15003110

7. Tao H., Xu S., Cao W. & Zhu K. Research progress of leaf senescence associated genes in rice. Mol. Plant Breeding, 2017, 6, 87–92.

8. Lee R. H., Lin M. C. & Chen S. C. A novel alkaline α-galactosidase gene is involved in rice leaf senescence. Plant Mol. Biol. 2004, 55, 281–295. doi: 10.1007/s11103-004-0641-0 15604681

9. Fukao T., Yeung E. & Baileyserres J. The submergence tolerance gene SUB1A delays leaf senescence under prolonged darkness through hormonal regulation in rice. Plant Physiol. 2012, 160, 1795–1807. doi: 10.1104/pp.112.207738 23073696

10. Zhang A. H. et al. Comparative proteomic analysis provides new insights into the regulation of carbon metabolism during leaf senescence of rice grown under field conditions. J. Plant Physiol. 2010, 167, 1380–1389. doi: 10.1016/j.jplph.2010.05.011 20663584

11. Vergara B. S. Rice plant growth and development, In: Luh B.S. (eds) Rice. Springer, Boston, MA, 1991, 13–22.

12. Deng Z. Y., Gong C. Y. & Wang T. Use of proteomics to understand seed development in rice. Proteomics 2013, 13, 1784–1800. doi: 10.1002/pmic.201200389 23483697

13. Ali M. A. et al. Source-sink relationship between photosynthetic organs and grain yield attributes during grain filling stage in spring wheat (Triticum aestivum). Int. J. Agric. Biol. 2010, 12, 509–515.

14. Wang P., Zhou G., Yu H. & Yu S. Fine mapping a major QTL for flag leaf size and yield-related traits in rice. Theor. Appl. Genet. 2011, 123, 1319–1330. doi: 10.1007/s00122-011-1669-6 21830109

15. Yue B., Xue W. Y., Luo L. J. & Xing Y. Z. QTL analysis for flag leaf characteristics and their relationships with yield and yield traits in rice. Acta Genet. Sin. 2006, 33, 824–832. doi: 10.1016/S0379-4172(06)60116-9 16980129

16. Fukumorita T. & Chino M. Sugar, amino acid and inorganic contents in rice phloem sap. Plant Cell Physiol. 1982, 23, 273–283.

17. Zhang Z., Cui B. & Zhang Y. Electrical penetration graphs indicate that tricin is a key secondary metabolite of rice, inhibiting phloem feeding of brown planthopper, Nilaparvata lugens. Entomol. Exp. Appl. 2015, 156, 14–27.

18. Stevenson P. C., Kimmins F. M., Grayer R. J. & Raveendranath S. Schaftosides from rice phloem as feeding inhibitors and resistance factors to brown planthoppers, Nilaparvata lugens. Entomol. Exp. Appl. 1996, 80, 246–249.

19. Deng Z. Y., Gong C. Y. & Wang T. Use of proteomics to understand seed development in rice. Proteomics 2013, 13, 1784–1800. doi: 10.1002/pmic.201200389 23483697

20. Hu C. et al. Identification of conserved and diverse metabolic shifts during rice grain development. Sci. Rep. 2016, 6, 20942. doi: 10.1038/srep20942 26860358

21. Lisec J., Schauer N., Kopka J., Willmitzer L. & Fernie A. R. Gas chromatography mass spectrometry-based metabolite profiling in plants. Nat. Protoc. 2006, 1, 387–396. doi: 10.1038/nprot.2006.59 17406261

22. Luedemann A., Strassburg K., Erban A. & Kopka J. TagFinder for the quantitative analysis of gas chromatography-mass spectrometry (GC-MS)-based metabolite profiling experiments. Bioinform. 2008, 24, 732–737.

23. Gong L. et al. Genetic analysis of the metabolome exemplified using a rice population. Proc. Natl. Acad. Sci. 2013, 110, 20320–20325. doi: 10.1073/pnas.1319681110 24259710

24. Yang Z. et al. Toward better annotation in plant metabolomics: isolation and structure elucidation of 36 specialized metabolites from Oryza sativa (rice) by using MS/MS and NMR analyses. Metabolomics 2014, 10, 543–555. doi: 10.1007/s11306-013-0619-5 25057267

25. Horai H. et al. MassBank: a public repository for sharing mass spectral data for life sciences. J. mass spectrom. 2010, 45, 703–714. doi: 10.1002/jms.1777 20623627

26. Guijas C. et al. METLIN: A technology platform for identifying knowns and unknowns. Anal. Chem. 2018, 90, 3156–3164. doi: 10.1021/acs.analchem.7b04424 29381867

27. Xia J. & Wishart D. S. Using metaboAnalyst 3.0 for comprehensive metabolomics data analysis. Curr. Protoc. Bioinform. 2016, 55, 14.10.11–14.10.91.

28. Howe E. et al. MeV: MultiExperiment Viewer, In: Ochs M., Casagrande J., Davuluri R. (eds) Biomedical Informatics for Cancer Research, Springer, Boston, MA, 2010.

29. Chen W. et al. Genome-wide association analyses provide genetic and biochemical insights into natural variation in rice metabolism. Nat. Genet. 2014, 46, 714–721. doi: 10.1038/ng.3007 24908251

30. Smilde A. K. et al. ANOVA-simultaneous component analysis (ASCA): A new tool for analyzing designed metabolomics data. Bioinform. 2005, 21, 3043–3048.

31. Nueda M. J. et al. Discovering gene expression patterns in time course microarray experiments by ANOVA-SCA. Bioinform. 2007, 23, 1792–1800.

32. Dong X. et al. Comprehensive profiling and natural variation of flavonoids in rice. J. Integr. Plant Biol. 2014, 56, 876–886. doi: 10.1111/jipb.12204 24730595

33. Taiz L. & Zeiger E. Plant Physiology, 5th edition, Sinauer Associates, Inc., Sunderland, 2010.

34. Bylka W., Matlawska I. & Pilewski N. A. Natural flavonoids as antimicrobial agents. J. Am. Nutraceut. Assoc. 2004, 7, 1–30.

35. Ling B., Dong H., Zhang M., Xu D. & Wang J. Potential resistance of tricin in rice against brown planthopper Nilaparvata lugens (Stål). Acta Ecol. Sin. 2007, 27, 1300–1306.

36. Zhou J. M. & Ibrahim R. K. Tricin-a potential multifunctional nutraceutical. Phytochem. Rev. 2010, 9, 413–424.

37. Návarová H., Bernsdorff F., Döring A. C. & Zeier J. Pipecolic acid, an endogenous mediator of defense amplification and priming, is a critical regulator of inducible plant immunity. Plant Cell 2012, 24, 5123–5141. doi: 10.1105/tpc.112.103564 23221596

38. Raviv B., Godwin J., Granot G. & Grafi G. The dead can nurture: Novel insights into the function of dead organs enclosing embryos. Int. J. Mol. Sci. 2018, 19, 2455.

39. Sreenivasulu N. & Wobus U. Seed-development programs: A systems biology-based comparison between dicots and monocots, Annu. Rev. Plant Biol. 2013, 64, 189–217. doi: 10.1146/annurev-arplant-050312-120215 23451786

40. Hong J., Yang L., Zhang D. & Shi J. Plant metabolomics: an indispensable system biology tool for plant science. Int. J. Mol. Sci. 2016, 7, 767.

41. Araújo W. L., Nunes-Nesi A. & Fernie A. R. Fumarate: Multiple functions of a simple metabolite. Phytochem. 2011, 72, 838–843.

42. Dong X. et al. Spatiotemporal distribution of phenolamides and the genetics of natural variation of hydroxycinnamoyl spermidine in rice. Mol. Plant 2015, 8, 111–12. doi: 10.1016/j.molp.2014.11.003 25578276

43. Agati G. et al. Functional roles of flavonoids in photoprotection: new evidence, lessons from the past. Plant Physiol. Bioch. 2013, 72, 35–45.

44. Peanparkdee M., Yamauchi R. & Iwamoto S. Characterization of antioxidants extracted from Thai riceberry bran using ultrasonic-assisted and conventional solvent extraction methods. Food Bioprocess Tech. 2018, 11, 713–722.

45. Treutter D. Significance of flavonoids in plant resistance and enhancement of their biosynthesis. Plant Biol. 2005, 7, 581–591. doi: 10.1055/s-2005-873009 16388461

46. Buer C. S., Imin N. & Djordjevic M. A. Flavonoids: New roles for old molecules. J. Integr. Plant Biol. 2010, 52, 98–111. doi: 10.1111/j.1744-7909.2010.00905.x 20074144

47. Lee S. C. et al. Effect of far-infrared radiation on the antioxidant activity of rice hulls. J. Agr. Food Chem. 2003, 51, 4400–4403.

48. Zhang X, Rerksiri W, Liu A, Zhou X, Xiong H, Xiang J, et al. Transcriptome profile reveals heat response mechanism at molecular and metabolic levels in rice flag leaf. Gene. 2013, 530, 185–92. doi: 10.1016/j.gene.2013.08.048 23994682

49. Voelker T. & Kinney A. J. Variations in the biosynthesis of seed-storage lipids. Annu Rev. Plant Physiol. Plant Mol. Biol. 2001, 52, 335–361. doi: 10.1146/annurev.arplant.52.1.335 11337402

50. Travieso M. D. C., Pino O., Sánchez Y., Rojas M. & Peteira B. In vitro evaluation of phospholipids effect on germination of tomato seeds (Lycopersicon esculentum Mill). Cultivos Tropicales 2015, 36, 148–152.

51. Pukacka S. & Kuiper P. J. C. Phospholipid composition and fatty acid peroxidation during ageing of Acer platanoides seeds. Physiol. Plantarum 2010, 72, 89–93.

52. Macoy D. M., Kim W. Y., Sang Y. L. & Min G. K. Biotic stress related functions of hydroxycinnamic acid amide in plants. J. Plant Biol. 2015, 58, 156–163.

53. Tanabe K., Hojo Y., Shinya T. & Galis I. Molecular evidence for biochemical diversification of phenolamide biosynthesis in rice plants. J. Integr. Plant Biol. 2016, 58, 903–913. doi: 10.1111/jipb.12480 27015846

54. Bonneau L., Carré M. & Martin-Tanguy J. Polyamines and related enzymes in rice seeds differing in germination potential. Plant Growth Regul. 1994, 15, 75–82.

55. Cornelius S., Witz S., Rolletschek H. & Möhlmann T. Pyrimidine degradation influences germination seedling growth and production of Arabidopsis seeds. J. Exp. Bot. 2011, 62, 5623–5632. doi: 10.1093/jxb/err251 21865177

56. Geigenberger P. et al. Inhibition of de novo pyrimidine synthesis in growing potato tubers leads to a compensatory stimulation of the pyrimidine salvage pathway and a subsequent increase in biosynthetic performance. Plant Cell 2005, 17, 2077–2088. doi: 10.1105/tpc.105.033548 15951490

57. Chen M., Thelen J. J. Plastid uridine salvage activity is required for photoassimilate allocation and partitioning in Arabidopsis. Plant Cell 2011, 23, 2991–3006. doi: 10.1105/tpc.111.085829 21828290

58. Howarth J. R. et al. Co-ordinated expression of amino acid metabolism in response to N and S deficiency during wheat grain filling. J. Exp. Bot. 2008, 59, 3675–3689. doi: 10.1093/jxb/ern218 18791197

59. Slewinski T. L. Non-structural carbohydrate partitioning in grass stems: a target to increase yield stability, stress tolerance, and biofuel production. J. Exp. Bot. 2012, 63, 4647–4670. doi: 10.1093/jxb/ers124 22732107

60. Zhu T., Budworth P., Chen W., Provart N., Chang H.S., Guimil S., et al. Transcriptional control of nutrient partitioning during rice grain filling. Plant Biotechnol. J. 2003, 1, 59–70. doi: 10.1046/j.1467-7652.2003.00006.x 17147681

61. Trethewey, J. A. K., Rolston, M. P., Mcgill, C. R. & Rowarth, J. S. Is the flag leaf important in perennial ryegrass seed production?, Seed symposium: seeds for futures. proceedings of a joint symposium between the agronomy society of New Zealand and the New Zealand Grassland Association held at Massey University, Palmerston North, New Zealand, 2010, 26–27 November 2008.

62. Borrell A. K., Incoll L. D., Simpson R. J. & Dalling M. J. Partitioning of Dry Matter and the Deposition and Use of Stem Reserves in a Semi-dwarf Wheat Crop. Ann. Bot. 1989, 63, 527–539.

63. Zhang A, Lu Q, Yin Y, Ding S, Wen X, Lu C. Comparative proteomic analysis provides new insights into the regulation of carbon metabolism during leaf senescence of rice grown under field conditions. J. Plant Physiol. 2010, 167(16): 1380–1389. doi: 10.1016/j.jplph.2010.05.011 20663584

64. Schwender J., Ohlrogge J. B. & Shachar-Hill Y. A flux model of glycolysis and the oxidative pentosephosphate pathway in developing Brassica napus embryos. J. Biol. Chem. 2003, 278, 29442. doi: 10.1074/jbc.M303432200 12759349

65. Wang C. et al. Pipecolic acid confers systemic immunity by regulating free radicals. Science Advances 2018, 4, eaar4509. doi: 10.1126/sciadv.aar4509 29854946

66. Chen Y. C. et al. N-hydroxy-pipecolic acid is a mobile metabolite that induces systemic disease resistance in Arabidopsis. Proc. Natl. Acad. Sci. 2018, 115, e4920–e4929. doi: 10.1073/pnas.1805291115 29735713

67. Shan L. & He P. Pipped at the post: pipecolic acid derivative identified as SAR regulator. Cell 2018, 173, 286–287. doi: 10.1016/j.cell.2018.03.045 29625046

68. Ding P. et al. Characterization of a pipecolic acid biosynthesis pathway required for systemic acquired resistance. Plant Cell 2016, 28, 2603. doi: 10.1105/tpc.16.00486 27758894

69. Hu C. et al. Proteomics and metabolomics analyses reveal the cucurbit sieve tube system as a complex metabolic space. Plant J. 2016, 87, 442–454. doi: 10.1111/tpj.13209 27155400

70. Tegeder M. & Rentsch D. Uptake and partitioning of amino acids and peptides. Mol. Plant 2010, 3, 997–1011. doi: 10.1093/mp/ssq047 21081651

71. Galili G., Amir R. & Fernie A. R. The Regulation of essential amino acid synthesis and accumulation in plants. Plant Biol. 2016, 67, 153–178.

72. Okumoto S. & Pilot G. Amino acid export in plants: a missing link in nitrogen cycling. Mol. Plant 2011, 4, 453–463. doi: 10.1093/mp/ssr003 21324969

73. Sperotto R.A., Ricachenevsky F.K., Duarte G.L., Boff T., Lopes K.L., Sperb ER., et al. Identification of up-regulated genes in flag leaves during rice grain filling and characterization of OsNAC5, a new ABA-dependent transcription factor. Planta 2009, 230, 985–1002. doi: 10.1007/s00425-009-1000-9 19697058

74. Yazaki K. Transporters of secondary metabolites. Curr. Opin. Plant Biol. 2005, 8, 301–307. doi: 10.1016/j.pbi.2005.03.011 15860427

75. Andersen T. G. et al. Integration of biosynthesis and long-distance transport establish organ-specific glucosinolate profiles in vegetative arabidopsis. Plant Cell 2013, 25, 3133–3145. doi: 10.1105/tpc.113.110890 23995084

76. Shitan N. Secondary metabolites in plants: transport and self-tolerance mechanisms. Biosci. Biotech. Bioch. 2016, 80, 1283–1293.


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