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. 2021 Feb 27;11(3):143.
doi: 10.3390/metabo11030143.

Solanum lycopersicum Seedlings. Metabolic Responses Induced by the Alkamide Affinin

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Solanum lycopersicum Seedlings. Metabolic Responses Induced by the Alkamide Affinin

Tonatiu Campos-García et al. Metabolites. .

Abstract

Alkamides have been observed to interact in different ways in several superior organisms and have been used in traditional medicine in many countries e.g., to relieve pain. Previous studies showed that affinin when applied to other plant species induces prominent changes in the root architecture and induces transcriptional adjustments; however, little is known about the metabolic pathways recruited by plants in response to alkamides. Previous published work with Arabidopsis seedlings treated in vitro with affinin at 50 µM significantly reduced primary root length. In tomato seedlings, that concentration did not reduce root growth but increase the number and length of lateral roots. Non-targeted metabolomic analysis by Gas Chromatography couplet to Mass Spectrometry (GC/EIMS) showed that, in tomato seedlings, affinin increased the accumulation of several metabolites leading to an enrichment of several metabolic pathways. Affinin at 100 µM alters the accumulation of metabolites such as organic acids, amino acids, sugars, and fatty acids. Finally, our results showed a response possibly associated with nitrogen, GABA shunt and serine pathways, in addition to a possible alteration in the mitochondrial electron transport chain (ETC), interesting topics to understand the molecular and metabolic mechanisms in response to alkamide in plants.

Keywords: Solanum lycopersicum; affinin; alkamides; gas chromatography couplet to mass spectrometry (GC/EIMS); metabolite profiling; plant immunity; tomato.

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Conflict of interest statement

The authors have no conflict of interest to declare. All co-authors have seen and agree with the contents of the manuscript and there is no financial interest to report. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the result.

Figures

Figure 1
Figure 1
Changes in tomato seedlings root growth and morphology, induced by affinin treatment. Tomato seedlings were grown in a medium with or without the indicated affinin concentrations. After ten days, seedlings showed changes in: (a) primary root length (PRL), number of emerged lateral roots (eLRs), lateral roots length (LRL); (b) biomass expressed as fresh weight (FW) of five pooled shoots or roots with three biological repeats. Data were analyzed with one-way ANOVA and a Tukey test. Different letters (A–C) were used to indicate means that differ significantly (p ≤ 0.05) (n = 3).
Figure 2
Figure 2
Enrichment pathway analysis. Metabolite pathways enrichment analysis of highly accumulated metabolites in (a) shoots and (b) roots from plants treated with affinin at 100 µM (n = 3).
Figure 3
Figure 3
Heatmaps of changes in the average metabolite abundance in tomato (a) shoots and (b) roots in response to affinin treatments. Mean metabolite abundance for each sample type is shown: red, higher abundance; green lower abundance (n = 3).
Figure 4
Figure 4
Score scatter plots of the two-component PLS-DA model based on the relative level of identified metabolites among samples from: (a) shoots R2 = 0.99, Q2 = 0.63; and roots (b) R2 = 0.96, Q2 = 0.79. The discrimination between affinin treatments for most important metabolites (VIP scores) responsible for the separation of clusters in PLS-DA, with the mini-heatmap on the right of each graph indicating their variation in concentration within different treatments for: shoots (c) and roots (d) (n = 3).
Figure 5
Figure 5
Two-way ANOVA visualization to identify interesting patterns between shoots and roots: (a) 3D scores scatter plot of PCA for the top three principal components, and the two experimental factors are indicated using different colors for treatments and different shapes for tissue (n = 3); (b) Venn diagram that summarizes the number of significant metabolites associated with each tissue, as well as their interactions; (c) two-way heatmap visualization of metabolite abundance. Distance was measured using the Pearson algorithm and the clustering algorithm using average distance.
Figure 6
Figure 6
Core metabolism overview of metabolic changes in shoots and roots induced by affinin treatments. Pathways were constructed mapping each metabolite and function in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database for Solanum lycopersicum-annotated pathways. Mean metabolite abundance for each sample type is showed in red for higher abundance or green for lower abundance while empty boxes indicate metabolites not detected.

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