Metabolome Analysis
In order to determine if, how much and where the expression of the RUBY reporter impacts the metabolome of Nicotiana benthamiana, a gas chromatography coupled with mass spectroscopy (GC/MS) analysis was performed. This is of interest, as the biosynthesis that is used to produce visible red betalains uses tyrosine as a precursor [1]. However, tyrosine is also a precursor of several important products involved in defense, pollinator attraction, electron transport and structural support [8]. In addition, tyrosine shares precursors with other aromatic amino acids [8]. The increased use of these substances could cause downstream effects. Therefore, the goal is to determine whether other pathways are disturbed by changes in tyrosine levels, as this would need to be taken into account, when using RUBY as a reporter.
Sampling
Different samples were used for the analysis of the metabolome:
1. The part of the leaf, that was infiltrated with agrobacteria containing RUBY (“R”)
2. The same leaf, but at a site that was not infiltrated (“G”)
3. Another leaf of the same plant (“K”)
The G-samples serve as a comparison for the R-samples. As changes that affect some part of the leaf could also affect the whole leaf, other leaves that were not infiltrated were also taken into account. In theory, changes could even affect the entire plant. However, sampling additional plants that were not infiltrated at all would have made it difficult to distinguish, whether changes are caused by RUBY expression, or due to differences in development, light conditions or further influences.
Samples were taken from five plants, each with three similar old leaves infiltrated. Patches from each plant were combined to form a replicate. The R-sample of a plant therefore consists of the red leaf tissue of all three infiltrated leaves. The G-sample consists of the green tissue samples of these leaves and the K-samples of tissue samples from 2 other leaves. The advantage of combining several leaves is that variance due to differences in development between leaves that differ in age, should be averaged out.
Betalains
First, the presence of betanin was analyzed for the samples, as without its presence, we would not expect any changes. Betanin is one of the major components produced by RUBY
[4]. Its abundance was detected using liquid chromatography combined with mass spectroscopy (LC/MS). In figure 10 it can be seen that for all five R-samples there is a clear detection peak for betanin, while it is not visible for the G-samples. That confirms that betanin was synthesized in the infiltrated tissue, but not in the rest of the leaf. This also verifies that betanin does not spread inside the leaf, which could otherwise impact the control samples.
Figure 10: Plot of betanin peak intensity measured by GC/MS for all G (green) and R (blue) samples.
Tyrosine
Further metabolites were analyzed using GC/MS, as this allows a more complete overview of the metabolome than LC. As a first step, the tyrosine levels were analyzed, as most of the changes will be connected to changes in tyrosine levels. To assure a correct identification, a tandem mass spectroscopy measurement was performed. As expected, tyrosine levels change significantly with a significance level of 0.01 (figure 11).
Figure 11: Mean values of normalizednormalized abundances of tyrosine in G and R samples measured by GC coupled with MS/MS. Error bars represent 99% confidence intervals. The change is significant to a significance value of 0.01.
In total, 94 metabolites could be identified in the samples. Peak areas were normalized with an internal standard as well as the initial weight of the sample. A principal component analysis (PCA) was performed, to check whether the Ruby infiltration is the major cause of variance between samples. The plot of the first two principal components (PC) is shown in figure 12.
Figure 12: Plot of first two principal components of PCA of metabolome data of all three sample conditions. The explained variance is 58.3%.
As it can be seen, differently treated samples separated in clusters along the first PC. This is especially true for the R-samples that clearly separate from all other samples. This indicates that the infiltration indeed is the major cause of variance between samples. The G- and R-samples lie closer together than the K- and R-samples, which supports the hypothesis that changes caused by RUBY affect the entire leaf and not only the infiltrated patch. In the second PC, the variance inside the treatment groups becomes more important than the difference between groups. There is one outlier (sample K1) which is similar to one of the G-samples. A possibility is to exclude this sample from further analyses. This was not done because it is not clear what the reason for this outlier might be. The first PC explains 39% of the variance, the second PC another 19%. This suggests having a look at the third PC, which adds another 9%. The resulting three dimensional plot is shown in figure 13. However, this only shows some additional variance inside of treatment groups and therefore is not relevant for assessment of changes due to infiltration.
Figure 13: Plot of first three principal components of PCA of metabolome data of all three sample conditions. The explained variance is 67.7%.
As a next step, statistical analysis of the detection for each metabolite was performed. Results are shown as volcano-plots. For the comparison between R- and G-samples (figure 14), it can be seen that indeed several metabolites changed significantly (significance level of 0.01 (red dots)). Except for Glycerol-3-P, all significantly changed metabolites increased due to RUBY expression. This increase was even higher than change in tyrosine levels, for which a decrease in abundance was detected. When the biosynthesis of tyrosine is further examined, it stands out that several precursors are changed, starting from glycolysis (Figure 15) with glucose-6-phosphate, fructose-6-phosphate and pyruvate. The glycolysis is connected to tyrosine and further aromatic amino acids through the shikimate-pathway of which shikimate has increased (Figure 16). This supports the hypothesis that the reactions leading to tyrosine are upregulated. The decrease of tyrosine is likely due to conversion into betalains. As we could still detect , it is likely that the increase of precursors allows most of the additional required tyrosine to be reproduced. Another amino acid of the same biosynthesis pathway that is affected by the changes is tryptophan. Its abundance is increased but also with smaller significance than the precursors. This may be a side effect of their upregulation.
However, there are other influenced metabolites such as sucrose and cellobiose. This can be another side-effect of an increased sugar metabolism. Further explanations can be the need of sugars to form betalain from betanidin or repair of damage to cell walls or membranes due to infiltration.
Comparison of G to K leads to no significant changes. That means that the effect of RUBY expression does not affect the rest of the leaf as much as the infiltrated spot.
In conclusion, we could show that the RUBY expression influences the metabolome, which can be traced back to be connected with the higher demand of the betalain precursor tyrosine. Tyrosine itself can be reproduced fast enough so that the cell does not run out of it. It should be taken into account when using RUBY as a reporter, the metabolome is influenced and therefore can influence the results.
Figure 14: Volcano plot of statistical analysis of metabolome data. The log2 of the fold change is drawn on the x-axis, the negative log10 of the p value corrected for multiple hypothesis testing according to Benjamini-Hochberg (q-value) on the y-axis. Metabolites that increased in abundance in RUBY-infiltrated tissue have negative x-values. Metabolites which are significantly changed to a significance value of 0.01 are drawn as red dots. Metabolites that would been changed to a significance value of 0.02 are labeled
Figure 15: Depiction of pathway from glycolysis to biosynthesis of tyrosine and other aromatic amino acids obtained from KEGG
[9]. Significant changes (glycolysis, shikimate) are highlighted with red rectangles, other relevant changes (tryptophane, tyrosine) are highlighted with orange rectangles.
Figure 16: Depiction of glycolysis obtained from KEGG. Significant changes (glucose-6P, fructose-6P, pyruvate) are highlighted with red rectangles.
