The Lipopolysaccharide-Induced Metabolome Signature in Arabidopsis thaliana Reveals Dynamic Reprogramming of Phytoalexin and Phytoanticipin Pathways

Abstract

Lipopolysaccharides (LPSs), as MAMP molecules, trigger the activation of signal transduction pathways involved in defence. Currently, plant metabolomics is providing new dimensions into understanding the intracellular adaptive responses to external stimuli. The effect of LPS on the metabolomes of Arabidopsis thaliana cells and leaf tissue was investigated over a 24 h period. Cellular metabolites and those secreted into the medium were extracted with methanol and liquid chromatography coupled to mass spectrometry was used for quantitative and qualitative analyses. Multivariate statistical data analyses were used to extract interpretable information from the generated multidimensional LC-MS data. The results show that LPS perception triggered differential changes in the metabolomes of cells and leaves, leading to variation in the biosynthesis of specialised secondary metabolites. Time-dependent changes in metabolite profiles were observed and biomarkers associated with the LPS-induced response were tentatively identified. These include the phytohormones salicylic acid and jasmonic acid, and also the associated methyl esters and sugar conjugates. The induced defensive state resulted in increases in indole-and other glucosinolates, indole derivatives, camalexin as well as cinnamic acid derivatives and other phenylpropanoids. These annotated metabolites indicate dynamic reprogramming of metabolic pathways that are functionally related towards creating an enhanced defensive capacity. The results reveal new insights into the mode of action of LPS as an activator of plant innate immunity, broadens knowledge about the defence metabolite pathways involved in Arabidopsis responses to LPS, and identifies specialised metabolites of functional importance that can be employed to enhance immunity against pathogen infection.

Fig 1

UHPLC-HDMS (ESI⁺) BPI chromatograms of LPS-elicited Arabidopsis cell—(A) and growth medium (B) extracts. Cell suspensions were treated with LPS at a concentration of 80 μg/mL and incubated for different time periods (8, 12 and 24 h) before extraction with methanol. The bottom chromatograms represents the control which was non-treated and incubated for 24 h. The respective Y axes (expressed in %) were linked using the MarkerLynx^TM tool for visual comparison.

Fig 2

PCA score plots of metabolite content of extracts from (A) cell, (B) medium and (C) leaf tissue. Models are based on the UHPLC-qTOF-MS (positive mode) time study of Arabidopsis cell suspensions comparing control versus 8, 12 and 24 h treatments with LPS. Leaf tissue extracts were prepared 24 h post-treatment with LPS and a MgSO₄ treatment control. The plots show intra- and inter group clustering/separation at different time points. Equivalent plots for the data obtained in negative mode are presented in Fig D in S2 File.

Fig 3. OPLS-DA-based identification of discriminating biomarkers responsible for sample clustering seen in the PCA score plots.

Models are based on the UHPLC-qTOF-MS (positive mode) data sets of Arabidopsis cell–and medium extracts comparing control versus samples treated with LPS for 24 h. Numbers 1–3 indicate selected variables with m/z and Rt indicated. The equivalent plots for the data obtained in negative mode is presented in Fig E in S2 File.

Fig 4. Volcano plot for identification of discriminating biomarkers.

Analysis is based on the UHPLC-qTOF-MS (positive mode) time study of Arabidopsis cell extracts comparing control versus samples treated with LPS for 24 h. The dashed line shown on the plot indicates where the p-value = 0.001, with ions above the line being statistically significant (p<0.001). Ions present in the left quadrant of the volcano plot are associated with the NT control and ions in the right quadrant are positively correlated to the treatment. The pink spots represent ions that have a fold change of > 1.5. Ions situated towards the left and right top quadrants represent values of large magnitude fold changes as well as high statistical significance. The equivalent plot for the data obtained in negative mode is presented in Fig E in S2 File.

Fig 5

Graphic presentation of distribution of indole glucosinolates present in (A) cell -, (B) medium—and (C) leaf extracts from Arabidopsis elicited with LPS. The graphs show the relative concentration, expressed as intensity of integrated ion abundance, for glucobrassicin (blue), 4-hydroxyglucobrassicin (brown) and 4-methoxyglucobrasicin (green) from 8 h to 24 h-treated in comparison to 24 h non-treated controls. Error bars indicate the standard deviation.

Fig 6. The indolic metabolite footprint of LPS-triggered signalling in Arabidopsis.

In response to LPS perception, enhanced activity of CYP79B2/B3 (Beets et al. 2012) converts Trp and lead to the accumulation of indole-3-acetaldoxime (IAOx), the common precursor of indole glucosinolates (IGSs), indole phytoalexins (camalexin), indole-3-carboxaldehyde (I3CHO), indole-3-carboxylic acid (I3COOH) and indole acetic acid (IAA). Associated derivatives and conjugates are indicated in italics. The antimicrobial roles of the annotated metabolites (e.g. phytoalexins, phytoanticipins and priming agents) and the metabolic interrelationships are discussed in the main text.