Advertisement

Metabolomics

, 12:61 | Cite as

Differential metabolomic responses of PAMP-triggered immunity and effector-triggered immunity in Arabidopsis suspension cells

  • Biswapriya B. Misra
  • Evaldo de Armas
  • Sixue ChenEmail author
Original Article

Abstract

Introduction

The rhizobacterial tomato pathogen Pseudomonas syringae pv. tomato str. DC3000 (PstDC3000), like many plant pathogenic bacteria, can elicit hypersensitive response in non-host plant cells. PstDC3000 uses a type III protein secretion system (T3SS) to deliver effector proteins.

Objectives

We compared metabolomic responses of Arabidopsis suspension cells to a wild-type PstDC3000, a T3SS deletion mutant PstDC3000D28E, and a pathogen associated molecular pattern (PAMP) flagellin’s N-terminal domain’s 22-aa peptide (flg22) to obtain metabolomics insights into the plant cell PAMP-triggered immunity (PTI) and effector-triggered immunity (ETI).

Methods

Using targeted HPLC-MRM-MS and untargeted GC-MS approaches, we monitored qualitative and quantitative changes of 312 metabolites in central and specialized metabolic pathways in a time-course study.

Results

The overall metabolomic changes induced by the three treatments included phenylpropanoid, flavonoid, and phytohormone biosynthetic pathways, as well as primary metabolism in amino acid and sugar biosynthesis. In addition to shared metabolites, flg22, PstDC3000D28E and PstDC3000 each caused unique metabolite changes in the course of the development of PTI and ETI.

Conclusion

PstDC3000D28E triggered PTI responses were different from those of flg22. This study has not only revealed the discernible metabolomics features associated with the flg22, PstDC3000D28E and PstDC3000 treatments, but also laid a foundation toward further understanding of metabolic regulation and responses underlying plant PTI and ETI.

Keywords

Pseudomonas flg22 Metabolic responses Arabidopsis cells Targeted metabolomics 

Notes

Acknowledgments

This work was supported by the U.S. National Science Foundation grant NSF-MCB-1158000 to SC.

Compliance with ethical standards

Conflict of Interest

The authors declare that they have no potential conflicts of interest.

Human and animal rights

This article does not contain any studies with human participants or animals performed by any of the authors.

Supplementary material

11306_2016_984_MOESM1_ESM.docx (3.2 mb)
Supplementary material 1 (DOCX 3277 kb)
11306_2016_984_MOESM2_ESM.xlsx (843 kb)
Supplementary material 2 (XLSX 843 kb)

References

  1. Afroz, A., Zahur, M., Zeeshan, N., & Komatsu S. (2013). Plant-bacterium interactions analyzed by proteomics. Frontiers in Plant Science, 4, 21. doi: 10.3389/fpls.2013.00021.CrossRefPubMedPubMedCentralGoogle Scholar
  2. Aliferis, K. A., Faubert, D., & Jabaji, S. (2014). A metabolic profiling strategy for the dissection of plant defense against fungal pathogens. PLoS ONE, 9, e111930.CrossRefPubMedPubMedCentralGoogle Scholar
  3. Allwood, J. W., Clarke, A., Goodacre, R., & Mur, L. A. (2010). Dual metabolomics: A novel approach to understanding plant-pathogen interactions. Phytochemistry, 71, 590–597.CrossRefPubMedGoogle Scholar
  4. Allwood, J. W., Heald, J., Lloyd, A. J., Goodacre, R., & Mur, L. A. (2012). Separating the inseparable: The metabolomic analysis of plant-pathogen interactions. In: N. W. Hardy & R. D. Hall (Eds.), Plant metabolomics (pp. 31–49). Humana Press.Google Scholar
  5. Bauer, Z., Gómez-Gómez, L., Boller, T., & Felix, G. (2001). Sensitivity of different ecotypes and mutants of Arabidopsis thaliana toward the bacterial elicitor flagellin correlates with the presence of receptor-binding sites. Journal of Biological Chemistry, 276, 45669–45676.CrossRefPubMedGoogle Scholar
  6. Bednarek, P., Piślewska-Bednarek, M., Svatoš, A., Schneider, B., Doubský, J., Mansurova, M., et al. (2009). A glucosinolate metabolism pathway in living plant cells mediates broad-spectrum antifungal defense. Science, 323, 101–106.CrossRefPubMedGoogle Scholar
  7. Benjamini, Y., & Hochberg, Y. (1995). Controlling the false discovery rate—A practical and powerful approach to multiple testing. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 57, 289–300.Google Scholar
  8. Block, A., Li, G., Fu, Z. Q., & Alfano, J. R. (2008). Phytopathogen type III effector weaponry and their plant targets. Current Opinion in Plant Biology, 11, 396–403.CrossRefPubMedPubMedCentralGoogle Scholar
  9. Blocker, A., Komoriya, K., & Aizawa, S. I. (2003). Type III secretion systems and bacterial flagella: Insights into their function from structural similarities. Proceedings of the National Academy of Sciences of the United States of America, 100, 3027–3030.CrossRefPubMedPubMedCentralGoogle Scholar
  10. Buell, C. R., Joardar, V., Lindeberg, M., Selengut, J., Paulsen, I. T., Gwinn, M. L., et al. (2003). The complete genome sequence of the Arabidopsis and tomato pathogen Pseudomonas syringae pv. tomato DC3000. Proceedings of the National Academy of Sciences of the United States of America, 100, 10181–10186.CrossRefPubMedPubMedCentralGoogle Scholar
  11. Caraux, G., & Pinloche, S. (2005). PermutMatrix: A graphical environment to arrange gene expression profiles in optimal linear order. Bioinformatics, 21, 1280–1281.CrossRefPubMedGoogle Scholar
  12. Carviel, J. L., Wilson, D. C., Isaacs, M., Carella, P., Catana, V., Golding, B., et al. (2014). Investigation of intercellular salicylic acid accumulation during compatible and incompatible Arabidopsis-Pseudomonas syringae interactions using a fast neutron-generated mutant allele of EDS5 identified by genetic mapping and whole-genome sequencing. PLoS ONE, 9, e88608.CrossRefPubMedPubMedCentralGoogle Scholar
  13. Ceoldo, S., Toffali, K., Mantovani, S., Baldan, G., Levi, M., & Guzzo, F. (2009). Metabolomics of Daucus carota cultured cell line under stressing conditions reveals interactions between phenolic compounds. Plant Science, 176, 553–565.CrossRefPubMedGoogle Scholar
  14. Chen, W., Gong, L., Guo, Z., Wang, W., Zhang, H., Liu, X., et al. (2013). A novel integrated method for largescale detection, identification, and quantification of widely targeted metabolites: Application in the study of rice metabolomics. Molecular Plant, 6, 1769–1780.CrossRefPubMedGoogle Scholar
  15. Clay, N. K., Adio, A. M., Denoux, C., Jander, G., & Ausubel, F. M. (2009). Glucosinolate metabolites required for an Arabidopsis innate immune response. Science, 323, 95–101.CrossRefPubMedPubMedCentralGoogle Scholar
  16. Cornelis, G. R. (2010). The type III secretion injectisome, a complex nanomachine for intracellular ‘toxin’ delivery. Biological Chemistry, 391, 745–751.CrossRefPubMedGoogle Scholar
  17. Cunnac, S., Chakravarthy, S., Kvitko, B. H., Russell, A. B., Martin, G. B., & Collmer, A. (2011). Genetic disassembly and combinatorial reassembly identify a minimal functional repertoire of type III effectors in Pseudomonas syringae. Proceedings of the National Academy of Sciences of the United States of America, 108, 2975–2980.CrossRefPubMedPubMedCentralGoogle Scholar
  18. ditFrey, N. F., Garcia, A. V., Bigeard, J., Zaag, R., Bueso, E., Garmier, M., et al. (2014). Functional analysis of Arabidopsis immune-related MAPKs uncovers a role for MPK3 as negative regulator of inducible defenses. Genome Biology, 15, R87.CrossRefGoogle Scholar
  19. Duan, G., Christian, N., Schwachtje, J., Walther, D., & Ebenhöh, O. (2013). The metabolic interplay between plants and phytopathogens. Metabolites, 3, 1–23.CrossRefPubMedPubMedCentralGoogle Scholar
  20. Dutta, B., Kanani, H., Quackenbush, J., & Klapa, M. I. (2009). Time-series integrated “omic” analyses to elucidate short-term stress-induced responses in plant liquid cultures. Biotechnology and Bioengineering, 102, 264–279.CrossRefPubMedPubMedCentralGoogle Scholar
  21. Feng, F., & Zhou, J. M. (2012). Plant-bacterial pathogen interactions mediated by type III effectors. Current Opinion in Plant Biology, 15, 469–476.CrossRefPubMedGoogle Scholar
  22. Fiehn, O., Wohlgemuth, G., Scholz, M., Kind, T., Lee, D. Y., Lu, Y., et al. (2008). Quality control for plant metabolomics: Reporting MSI-compliant studies. Plant Journal, 53, 691–704.CrossRefPubMedGoogle Scholar
  23. Gachon, C. M., Langlois-Meurinne, M., Henry, Y., & Saindrenan, P. (2005). Transcriptional co-regulation of secondary metabolism enzymes in Arabidopsis: Functional and evolutionary implications. Plant Molecular Biology, 58, 229–245.CrossRefPubMedGoogle Scholar
  24. Galán, J. E., & Collmer, A. (1999). Type III secretion machines: Bacterial devices for protein delivery into host cells. Science, 284, 1322–1328.CrossRefPubMedGoogle Scholar
  25. Galán, J. E., & Wolf-Watz, H. (2006). Protein delivery into eukaryotic cells by type III secretion machines. Nature, 444, 567–573.CrossRefPubMedGoogle Scholar
  26. García-Alcalde, F., García-López, F., Dopazo, J., & Conesa, A. (2011). Paintomics: A web based tool for the joint visualization of transcriptomics and metabolomics data. Bioinformatics, 27, 137–139.CrossRefPubMedPubMedCentralGoogle Scholar
  27. Gholami, M., Boughton, B. A., Fakhari, A. R., Ghanati, F., Mirzaei, H. H., Borojeni, L. Y., et al. (2014). Metabolomic study reveals a selective accumulation of l-arginine in the d-ornithine treated tobacco cell suspension culture. Process Biochemistry, 49, 140–147.CrossRefGoogle Scholar
  28. Grapov, D., & Newman, J. W. (2012). imDEV: A graphical user interface to R multivariate analysis tools in Microsoft Excel. Bioinformatics, 28, 2288–2290.CrossRefPubMedPubMedCentralGoogle Scholar
  29. Guan, X., Buchholz, G., & Nick, P. (2013). The cytoskeleton is disrupted by the bacterial effector HrpZ, but not by the bacterial PAMP flg22, in tobacco BY-2 cells. Journal of Experimental Botany, 64, 1805–1816.CrossRefPubMedPubMedCentralGoogle Scholar
  30. Hann, D. R., Domínguez-Ferreras, A., Motyka, V., Dobrev, P. I., Schornack, S., & Jehle, A. (2014). The Pseudomonas type III effector HopQ1 activates cytokinin signaling and interferes with plant innate immunity. New Phytologist, 201, 585–598.CrossRefPubMedGoogle Scholar
  31. Jones, J. D., & Dangl, J. L. (2006). The plant immune system. Nature, 444, 323–329.CrossRefPubMedGoogle Scholar
  32. Ketchum, R. E. B., Rithner, C. D., Qiu, D., Kim, Y. S., Williams, R. M., & Croteau, R. B. (2003). Taxus metabolomics: Methyl jasmonate preferentially induces production of taxoids oxygenated at C-13 in Taxus x media cell cultures. Phytochemistry, 62, 901–909.CrossRefPubMedGoogle Scholar
  33. Kim, J. K., Bamba, T., Harada, K., Fukusaki, E., & Kobayashi, A. (2007). Time-course metabolic profiling in Arabidopsis thaliana cell cultures after salt stress treatment. Journal of Experimental Botany, 58, 415–424.CrossRefPubMedGoogle Scholar
  34. Kim, JI., Dolan, W. L., Anderson, N. A., & Chapple, C., (2015). Indole glucosinolate biosynthesis limits phenylpropanoid accumulation in Arabidopsis thaliana. Plant Cell, 27, 1529–1546.CrossRefPubMedGoogle Scholar
  35. Kopka, J., Schauer, N., Krueger, S., Birkemeyer, C., Usadel, B., Bergmüller, E., et al. (2005). GMD@ CSB. DB: The Golm metabolome database. Bioinformatics, 21, 1635–1638.CrossRefPubMedGoogle Scholar
  36. Kruse, C., Jost, R., Lipschis, M., Kopp, B., Hartmann, M., & Hell, R. (2007). Sulfur-enhanced defence: Effects of sulfur metabolism, nitrogen supply, and pathogen lifestyle. Plant Biology, 9, 608–619.CrossRefPubMedGoogle Scholar
  37. Kuehn, H., Liberzon, A., Reich, M., Mesirov, J. P. (2008). Using GenePattern for gene expression analysis. Current protocols in bioinformatics. doi: 10.1002/0471250953.bi0712s22.PubMedCentralGoogle Scholar
  38. Less, H., Angelovici, R., Tzin, V., & Galili, G. (2011). Coordinated gene networks regulating Arabidopsis plant metabolism in response to various stresses and nutritional cues. Plant Cell, 23, 1264–1271.CrossRefPubMedPubMedCentralGoogle Scholar
  39. Lindeberg, M., Cunnac, S., & Collmer, A. (2012). Pseudomonas syringae type III effector repertoires: Last words in endless arguments. Trends in Microbiology, 20, 199–208.CrossRefPubMedGoogle Scholar
  40. Lisec, J., Schauer, N., Kopka, J., Willmitzer, L., & Fernie, A. R. (2006). Gas chromatography mass spectrometry-based metabolite profiling in plants. Nature Protocols, 1, 387–396.CrossRefPubMedGoogle Scholar
  41. Liu, D., Ford, K. L., Roessner, U., Natera, S., Cassin, A. M., Patterson, J. H., et al. (2013a). Rice suspension cultured cells are evaluated as a model system to study salt responsive networks in plants using a combined proteomic and metabolomic profiling approach. Proteomics, 13, 2046–2062.CrossRefPubMedGoogle Scholar
  42. Liu, G., Ji, Y., Bhuiyan, N. H., Pilot, G., Selvaraj, G., Zou, J., et al. (2010). Amino acid homeostasis modulates salicylic acid-associated redox status and defense responses in Arabidopsis. Plant Cell, 22, 3845–3863.CrossRefPubMedPubMedCentralGoogle Scholar
  43. Liu, Y., Wang, L., Cai, G., Jiang, S., Sun, L., & Li, D. (2013b). Response of tobacco to the Pseudomonas syringae pv. tomato DC3000 is mainly dependent on salicylic acid signaling pathway. FEMS Microbiology Letters, 344, 77–85.CrossRefPubMedGoogle Scholar
  44. Liu, P., Zhang, H., Yu, B., Xiong, L., & Xia, Y. (2015). Proteomic identification of early salicylate-and flg22-responsive redox-sensitive proteins in Arabidopsis. Scientific Reports, 5, 8625. doi: 10.1038/srep08625.CrossRefPubMedPubMedCentralGoogle Scholar
  45. Mine, A., Sato, M., & Tsuda, K. (2014). Toward a systems understanding of plant-microbe interactions. Front Plant Science5, 423. doi: 10.3389/fpls.2014.00423.CrossRefGoogle Scholar
  46. Misra, B. B., Assmann, S. M., & Chen, S. (2014). Plant single-cell and single-cell-type metabolomics. Trends Plant Science, 19, 637–646.CrossRefGoogle Scholar
  47. Misra, B. B., de Armas, E., Tong, Z., & Chen, S. (2015). Metabolomic responses of guard cells and mesophyll cells to bicarbonate. PLOS One, 10, e0144206.CrossRefPubMedPubMedCentralGoogle Scholar
  48. Murashige, T., & Skoog, F. (1962). A revised medium for rapid growth and bio assays with tobacco tissue cultures. Physiologia Plantarum, 15, 473–497.CrossRefGoogle Scholar
  49. Naseem, M., Kaltdorf, M., Hussain, A., & Dandekar, T. (2013). The impact of cytokinin on jasmonate-salicylate antagonism in Arabidopsis immunity against infection with PstDC3000. Plant Signaling & Behavior, 8, e26791.CrossRefGoogle Scholar
  50. Návarová, H., Bernsdorff, F., Döring, A. C., & Zeier, J. (2012). Pipecolic acid, an endogenous mediator of defense amplification and priming, is a critical regulator of inducible plant immunity. Plant Cell, 24, 5123–5141.CrossRefPubMedPubMedCentralGoogle Scholar
  51. Noutoshi, Y., Jikumaru, Y., Kamiya, Y., & Shirasu, K. (2012). ImprimatinC1, a novel plant immune-priming compound, functions as a partial agonist of salicylic acid. Scientific Reports, 2, 705. doi: 10.1038/srep00705.CrossRefPubMedPubMedCentralGoogle Scholar
  52. Oh, C. S., & Martin, G. B. (2011). Effector-triggered immunity mediated by the pto kinase. Trends in Plant Science, 16, 132–140.CrossRefPubMedGoogle Scholar
  53. Peck, S. C., Nühse, T. S., Hess, D., Iglesias, A., Meins, F., & Boller, T. (2001). Directed proteomics identifies a plant-specific protein rapidly phosphorylated in response to bacterial and fungal elicitors. Plant Cell, 13, 1467–1475.CrossRefPubMedPubMedCentralGoogle Scholar
  54. Pombo, M. A., Zheng, Y., Fernandez-Pozo, N., Dunham, D. M., Fei, Z., & Martin, G. B. (2014). Transcriptomic analysis reveals tomato genes whose expression is induced specifically during effector-triggered immunity and identifies the Epk1 protein kinase which is required for the host response to three bacterial effector proteins. Genome Biology, 15, 492.CrossRefPubMedPubMedCentralGoogle Scholar
  55. Rausch, T., & Wachter, A. (2005). Sulfur metabolism: A versatile platform for launching defence operations. Trends Plant Science, 10, 503–509.CrossRefGoogle Scholar
  56. R Development Core Team (2008). R: A language and environment for statistical computing.. Vienna, Austria: R Foundation for Statistical Computing. http://www.R-project.org.
  57. Reich, M., Liefeld, T., Gould, J., Lerner, J., Tamayo, P., & Mesirov, J. P. (2006). GenePattern 2.0. Nature Genetics, 38, 500–501.CrossRefPubMedGoogle Scholar
  58. Rico, A., Bennett, M. H., Forcat, S., Huang, W. E., & Preston, G. M. (2010). Agroinfiltration reduces ABA levels and suppresses Pseudomonas syringae-elicited salicylic acid production in Nicotiana tabacum. PLoS ONE, 5, e8977.CrossRefPubMedPubMedCentralGoogle Scholar
  59. Roberts, M. R. (2007). Does GABA act as a signal in plants? Hints from molecular studies. Plant Signaling & Behavior, 2, 408–409.CrossRefGoogle Scholar
  60. Robert-Seilaniantz, A., MacLean, D., Jikumaru, Y., Hill, L., Yamaguchi, S., Kamiya, Y., & Jones, J. D. (2011). The microRNA miR393 re-directs secondary metabolite biosynthesis away from camalexin and towards glucosinolates. Plant Journal, 67, 218–231.CrossRefPubMedGoogle Scholar
  61. Rojas, C. M., Senthil-Kumar, M., Tzin, V., & Mysore, K. S. (2014). Regulation of primary plant metabolism during plant-pathogen interactions and its contribution to plant defense. Frontiers in Plant Science, 5, 17. doi: 10.3389/fpls.2014.00017.CrossRefPubMedPubMedCentralGoogle Scholar
  62. Rosli, H. G., Zheng, Y., Pombo, M. A., Zhong, S., Bombarely, A., Fei, Z., et al. (2013). Transcriptomics-based screen for genes induced by flagellin and repressed by pathogen effectors identifies a cell wall-associated kinase involved in plant immunity. Genome Biology, 14, R139.CrossRefPubMedPubMedCentralGoogle Scholar
  63. Scalschi, L., Camañes, G., Llorens, E., Fernández-Crespo, E., López, M. M., García-Agustín, P., et al. (2014). Resistance inducers modulate Pseudomonas syringae pv. tomato strain DC3000 response in tomato plants. PLoS ONE, 9, e106429.CrossRefPubMedPubMedCentralGoogle Scholar
  64. Schenk, S. T., Hernández-Reyes, C., Samans, B., Stein, E., Neumann, C., Schikora, M., et al. (2014). N-acyl-homoserine lactone primes plants for cell wall reinforcement and induces resistance to bacterial pathogens via the salicylic acid/oxylipin pathway. Plant Cell, 26, 2708–2723.CrossRefPubMedPubMedCentralGoogle Scholar
  65. Schenke, D., Boettcher, C., & Scheel, D. (2011). Crosstalk between abiotic ultraviolet-B stress and biotic (flg22) stress signalling in Arabidopsis prevents flavonol accumulation in favor of pathogen defence compound production. Plant, Cell and Environment, 34, 1849–1864.CrossRefPubMedGoogle Scholar
  66. Sokal, R. R., & Rohlf, F. J. (1995). Biometry: The principles and practice of statistics in biological research (p. 337). New York: W.H. Freeman and Company.Google Scholar
  67. Soscia, C., Hachani, A., Bernadac, A., Filloux, A., & Bleves, S. (2007). Cross talk between type III secretion and flagellar assembly systems in Pseudomonas aeruginosa. Journal of Bacteriology, 189, 3124–3132.CrossRefPubMedPubMedCentralGoogle Scholar
  68. Stein, S. E. (1999). An integrated method for spectrum extraction and compound identification from gas chromatography/mass spectrometry data. Journal of the American Society for Mass Spectrometry, 10, 770–781.CrossRefGoogle Scholar
  69. Sumner, L. W., Lei, Z., Nikolau, B. J., & Saito, K. (2014). Modern plant metabolomics: Advanced natural product gene discoveries, improved technologies, and future prospects. Natural Product Reports, 32, 212–229.CrossRefGoogle Scholar
  70. Thilmony, R., Underwood, W., & He, S. Y. (2006). Genome-wide transcriptional analysis of the Arabidopsis thaliana interaction with the plant pathogen Pseudomonas syringae pv. tomato DC3000 and the human pathogen Escherichia coli O157: H7. Plant Journal, 46, 34–53.CrossRefPubMedGoogle Scholar
  71. Trdá, L., Fernandez, O., Boutrot, F., Héloir, M. C., Kelloniemi, J., Daire, X., et al. (2014). The grapevine flagellin receptor VvFLS2 differentially recognizes flagellin-derived epitopes from the endophytic growth-promoting bacterium Burkholderia phytofirmans and plant pathogenic bacteria. New Phytologist, 201, 1371–1384.CrossRefPubMedGoogle Scholar
  72. Tsuda, K., Mine, A., Bethke, G., Igarashi, D., Botanga, C. J., Tsuda, Y., et al. (2013). Dual regulation of gene expression mediated by extended MAPK activation and salicylic acid contributes to robust innate immunity in Arabidopsis thaliana. PLoS Genetics, 9, e1004015.CrossRefPubMedPubMedCentralGoogle Scholar
  73. Tsutsui, T., Nakano, A., & Ueda, T. (2015). The plant-specific RAB5 GTPase ARA6 is required for starch and sugar homeostasis in Arabidopsis thaliana. Plant and Cell Physiology, 56, 1073–1083.CrossRefPubMedGoogle Scholar
  74. Vargas, P., Farias, G. A., Nogales, J., Prada, H., Carvajal, V., Barón, M., et al. (2013). Plant flavonoids target Pseudomonas syringae pv. tomato DC3000 flagella and type III secretion system. Environmental Microbiology Reports, 5, 841–850.CrossRefPubMedGoogle Scholar
  75. Villela-Dias, C., Camillo, L. R., de Oliveira, G. A., Sena, J. A., Santiago, A. S., de Sousa, S. T., et al. (2014). Nep1-like protein from Moniliophthora perniciosa induces a rapid proteome and metabolome reprogramming in cells of Nicotiana benthamiana. Physiologia Plantarum, 150, 1–17.CrossRefPubMedGoogle Scholar
  76. Walley, J. W., Kliebenstein, D. J., Bostock, R. M., & Dehesh, K. (2013). Fatty acids and early detection of pathogens. Current Opinion in Plant Biology, 16, 520–526.CrossRefPubMedGoogle Scholar
  77. Xia, J. G., Psychogios, N., Young, N., & Wishart, D. S. (2009). MetaboAnalyst: A web server for metabolomic data analysis and interpretation. Nucleic Acids Research, 37, W652–W660.CrossRefPubMedPubMedCentralGoogle Scholar
  78. Zeier, J. (2013). New insights into the regulation of plant immunity by amino acid metabolic pathways. Plant, Cell and Environment, 36, 2085–2103.CrossRefPubMedGoogle Scholar
  79. Zhou, J. M., & Chai, J. (2008). Plant pathogenic bacterial type III effectors subdue host responses. Current Opinion in Microbiology, 11, 179–185.CrossRefPubMedGoogle Scholar
  80. Zipfel, C., & Robatzek, S. (2010). Pathogen-associated molecular pattern-triggered immunity: veni, vidi…? Plant Physiology, 154, 551–554.CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Biswapriya B. Misra
    • 1
  • Evaldo de Armas
    • 2
  • Sixue Chen
    • 1
    • 3
    Email author
  1. 1.Department of Biology, Genetics Institute, Plant Molecular and Cellular Biology ProgramUniversity of FloridaGainesvilleUSA
  2. 2.Training InstituteThermo Fisher ScientificWest Palm BeachUSA
  3. 3.Interdisciplinary Center for Biotechnology Research, Cancer & Genetics Research Complex, Room 438University of FloridaGainesvilleUSA

Personalised recommendations