Transcript HEADING FOR PRESENTATION HERE

Isonitrosoacetophenone induces metabolic
perturbations in Nicotiana tabacum, Sorghum
bicolor, and Arabidopsis thaliana. A holistic UPLCESI-HD-MS based metabolomics analysis.
Background Information:
• Plants have developed biochemical and molecular
responses to defend themselves under different stress
environments.
• 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)
• Dubery et al. 1999, reported the accumulation of an oximecontaining stress metabolite/phytoalexin, (4-(3-methyl-2butenoxy)-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)
Differences between INAP and Phenylacetaldehyde
oxime
Unknown Function ?
Isonitrosoacetophenone (INAP)
Cyanogenic glycoside
precursor
Phenylacetaldehyde oxime
Differences between non-cyanogenic and cyanogenic
plants.
Metabolomics.
“Identification and quantification of all metabolites in a specific
issue/cell at given physiological status.”
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
Materials and Methods
Cells and
treatments
• Tobacco and sorghum cell suspensions were treated with INAP to final concentration of 1 mM
at different time intervals (6 h, 12 h, 18 h and 24 h). Control cells were not treated.
• Wet cells (2 g) were homogenised in 100% methanol. Extracts were dried completely with the
a speed vac at 42ºC. The dried pellet was suspended in 500 µL of 50% methanol. The extracts
were filtered through 0.22 µm nylon filter membranes fitted on 1 mL syringe to remove any
Extraction and
sample preparation
residual debris and transferred to UPLC vials fitted with 0.5 mL inserts and pre-slitted lids
UPLC-MS
• Five (5) µL was injected on the Waters Acquity UPLC-MS instrument equipped with the BEH C18
column (100 mm × 2.1 mm with a particle size of 1.7 µm). The composition of mobile phase A
consisted of 0.1% formic acid in deionized water and mobile phase B consisted of 0.1% formic
acid in methanol. Data was acquired by both PDA and MS detectors, the MS detector was
operated at both negative and positive ionization modes.
Materials and Methods
• Chromatograms were initially visually, compared to each other. MS raw data was further
TM
analyzed by MarkerLynx
Data Analysis
Multivariate
Data Analyses
• MarkerLynx results containing peak information [Area under the peak, retention time (RT) and
Mass (m/z)] were exported to SIMCA-P software for multivariate statistics analyses. Both PCA
and OPLS-DA models were constructed from the exported data.
• Metabolites of which the levels were affected by INAP were identified from the PCA loadings
plot and OPLS-DA loading S-plot. The mass of these biomarkers were used to predict the
elemental compositions. These elemental compositions were used to search for chemical
identity of these biomarkers from the dictionary of natural products (DNP) and ChemSpider
Biomarker
Identification databases.
Results and Discussion
INAP Induced metabolic changes in sorghum and
tobacco cells.
• Overlaid
UPLC-PDA
chromatogram
(Tobacco).
Comparison of UPLC-MS data generated using
different ionization polarity.
UPLC-MS (ESI-)
UPLC-MS (ESI+)
Overview of Quadrupole Time Of Flight (Q-TOF) MS
Changes in the collision energy affects the
metabolomics data output.
PCA score plots for both Tobacco (A) and Sorghum(B).
Tobacco
Sorghum
Hierarchical Cluster Analysis (HCA) dendrograms
Tobacco
Sorghum
Metabolic trees visualization
(For the first time the metabolic trees are used to
decipher the time trend)
Tobacco
Sorghum
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: ????
Effect of INAP on tobacco cell suspensions.
(Identification of responsive metabolites)
Comparison
of
representative
chromatograms [30 min,
positive ionization UPLCMS base peak intensity
(BPI)] of extracts from
tobacco cell suspension
samples treated with
INAP for different time
intervals
24 h
18 h
12 h
6h
Con
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.
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.
Structures of Biomarkers of which the levels were
found to increase after INAP treatment.
Gallic Acid
1
3
2
Sinapic acid
4
Chlorogenic acid
5
Vanillic acid
6
Biotransformed
INAP
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.
Madala et al., 2012. Biotechnology Letters. DOI: 10.1007/s10529-012-0909-4
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.
Ackwoledgements
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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!