Ntakadzeni Edwin Madala Supervisor: Prof IA Dubery Co-supervisor: Dr LA Piater

1. Isonitrosoacetophenone induces metabolic perturbations inNicotianatabacum, Sorghum bicolor, and Arabidopsis thaliana. A holistic UPLC-ESI-HD-MS based metabolomics analysis. Ntakadzeni Edwin Madala Supervisor: Prof IA Dubery Co-supervisor: Dr LA Piater Dr PA Steenkamp

2. Background Information: Plants have developed biochemical and molecular responses to defend themselves under different stress environments.

3. Plant defenses can be triggered by various stimuli Pathogens Synthetic or naturally occurring molecules, especially those derived from pathogens More recently, chemicals have also been employed to trigger SAR, the most widely used being benzothiadiazole (BTH) with trade name BION Different promoters of genes with direct activity towards plant defense responses (such as the one of PR1a) have been shown to respond to different types of chemical inducers. Other chemicals include : β-aminobutyric acid (BABA) Methyl-2,6-dichloroisonicotinic acid (INA) Riboflavin (Gorlachet al., 1996; Gatz, 1997 Gatz and Lenk, 1998; Oostendorpet al., 2001; Dao et al., 2009)

4. Duberyet al. 1999, reported the accumulation of an oxime-containing stress metabolite/phytoalexin, (4-(3-methyl-2-butenoxy)-isonitrosoacetophenone or citaldoxime) in citrus peel undergoing oxidative stress due to gamma radiation treatment. • Oxime functional groups are rare in natural products. • In plants, oximes are intermediates of a range of metabolic pathways subject to controls that result in variation in both the type and amount of end product formed. • Aldoximes are intermediates during the biosynthesis of glucosinolates and cyanogenic glycosides (Mahandevan, 1973; Møller, 2010)

5. Differences between INAP and Phenylacetaldehydeoxime Unknown Function ? Cyanogenic glycoside precursor Isonitrosoacetophenone (INAP) Phenylacetaldehydeoxime

6. Differences between non-cyanogenic and cyanogenic plants.

7. Metabolomics. “Identification and quantification of all metabolites in a specific issue/cell at given physiological status.”

8. Techniques and data analyses. Techniques (NMR, GC-MS, LC-MS, IR). High dimensional data. In metabolomics, scientists spend most of the time analyzing data. Chemometric/multivariate data analysis. PCA OPLS-DA (SUS) PLS-DA HCA Metabolic trees

9. Materials and Methods

10. Materials and Methods

11. INAP Induced metabolic changes in sorghum and tobacco cells. Results and Discussion • Overlaid UPLC-PDA chromatogram (Tobacco).

12. Comparison of UPLC-MS data generated using different ionization polarity. UPLC-MS (ESI-) UPLC-MS (ESI+)

13. Overview ofQuadrupole Time Of Flight (Q-TOF) MS

14. Changes in the collision energy affects the metabolomics data output.

15. PCA score plots for both Tobacco (A) and Sorghum(B). Tobacco Sorghum

16. Hierarchical Cluster Analysis (HCA) dendrograms Tobacco Sorghum

17. Metabolic trees visualization (For the first time the metabolic trees are used to decipher the time trend) Sorghum Tobacco

18. Summary of results up so far: • INAP induces metabolic changes in both sorghum and tobacco cells. • MS settings affects metabolic data output. • Different data visualization models are required for comprehensive understanding of the biological meaning underlying the exhibited response. • Metabolic trees and HCA offers an alternative to PCA score plots as they contains more statistically sounding results. • Question: Oxime response/metabolism: • Cyanogenic plants: known from literature • Non-cyanogenic plants: ????

19. Effect of INAP on tobacco cell suspensions. (Identification of responsive metabolites) Comparison of representative chromatograms [30 min, positive ionization UPLC-MS base peak intensity (BPI)] of extracts from tobacco cell suspension samples treated with INAP for different time intervals 24 h 18 h 12 h 6 h Con

20. Representative OPLS-DA score plot, based on the UPLC-MS chromatograms, showing clustering of control vs. 6 h treatment of tobacco cell suspensions with INAP.

21. Loading S-plot showing bio-markers which are responsible for the different clustering observed in the OPLS-DA score plots, with those most significant contributing to the treatment response highlighted by red box.

22. Structures of Biomarkers of which the levels were found to increase after INAP treatment. Gallic Acid 3 1 2 Sinapic acid 5 6 4 Biotransformed INAP Vanillic acid Chlorogenic acid

23. INAP was found to undergo biotransformation in tobacco cells As seen from other INAP induced metabolites, they were also methoxylated and glycosylated, which justify the biotransformation steps proposed above. Madalaet al., 2012. Biotechnology Letters. DOI: 10.1007/s10529-012-0909-4

24. Conclusion The induced metabolites have known antioxidant activities which in turn explain the initial accumulation of INAP in citrus peel undergoing oxidative stress. INAP induced metabolic perturbations in tobacco cell suspensions. (i) It was metabolised through a series of hydroxylation and methoxylation steps and (ii) triggered the synthesis of benzoic acid derivatives that could create an enhanced defensive capacity The use UPLC-MS based metabolomics and multivariate data analysis suffice the understanding of metabolic perturbations induced by chemical inducers.

25. Ackwoledgements • Prof IA Dubery • Dr LA Piater • Dr PA Steenkamp • Mr MJ George • F Tugizimana • T Finnegan • The Plant Research Group. • Dr William Allwood and Andrew Vaughan. • NRF and University of Johnnesburg Thanks to All!