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MetaboLights MTBLS1550 - GNPS Metabolomics analysis identifies metabolites associated with systemic acquired resistance in Arabidopsis

ABSTRACT:

BACKGROUND: Systemic acquired resistance (SAR) is a plant defense response that provides long-lasting, broad-spectrum pathogen resistance to uninfected distal leaves following an initial localized infection. However, little information is available on the molecular biological basis of SAR especially in uninfected distal leaves.

METHODS: Here, we used two SAR-inducing pathogen to induce SAR in Arabidopsis, and a metabolomics approach based on ultra-high-performance liquid chromatography (UPLC) and mass spectrometry (MS) technique was used to identify SAR-related metabolites in SAR-inducing pathogen infected local leaves and uninfected distal leaves.

RESULTS: Multiple statistical analyses were used to identify differentially expressed metabolites. The result showed that primary metabolism and secondary metabolism were significantly altered in local leaves and distal leaves, including phenolic compounds, amino acids, nucleotides, organic acids and many other metabolites.

CONCLUSIONS: The content of amino acids and phenolic compounds increased in distal leaves, suggesting their contribution to the establishment of SAR in distal leaves. In addition, 2’-hydroxy-4, 4’, 6’-trimethoxychalcone, phenylalanine and p-coumaric acid were identified as potential components which may play important roles both in basic resistance and SAR. This study provided a reference for understanding metabolic mechanism associated with SAR in Arabidopsis, which will be useful for further investigation of the molecular basis of SAR.

INSTRUMENT(S): Thermo Scientific instrument model|1000494

ORGANISM(S): Arabidopsis Thaliana|3702

SUBMITTER: Hang Gao

PROVIDER: MSV000085657 | GNPS | Tue Jun 30 20:49:00 BST 2020

REPOSITORIES: GNPS

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Project description:Changes in gene expression form a crucial part of the plant response to pathogen infection. Whole-leaf expression profiling has played a valuable role in identifying genes and processes that contribute to the interactions between the model plant Arabidopsis thaliana and a diverse range of pathogens. However, for highly localised infections, such as downy mildew caused by the biotrophic oomycete pathogen Hyaloperonospora arabidopsidis (Hpa), whole-leaf profiling may fail to capture the complete Arabidopsis response. Highly localised expression changes may be diluted by the comparative abundance of non-responding leaf cells or the Hpa oomycete evading detection by cells. Furthermore, local and systemic Hpa responses of a differing nature may become convoluted. To address this we applied the technique of Fluorescence Activated Cell Sorting (FACS), typically used for analyzing plant abiotic responses, to the study of plant-pathogen interactions. Using the promoter of Downy Mildew Resistant 6 (DMR6) linked to GFP as a fluorescent marker of pathogen-contacting cells, we isolated Hpa-proximal and Hpa-distal cells from infected leaf samples using FACS, and measured global gene expression. The whole experiment was carried out in triplicate, with two time points (5 and 7 days post-inoculation) and three cell types (pathogen-proximal, pathogen-distal and uninfected control), totalling 18 microarrays. Transgenic Arabidopsis thaliana Col-0 with the transgene pDMR6:GFP was used for all experiments. Seedling populations were inoculated with 30,000-60,000 spores/ml of Hyaloperonospora arabidopsis strain Noks1 at 7 days old, and overground tissue sampled at 5 and 7 days post-inoculation. Protoplasts were generated from these samples according to Grønlund et al. 2012 JOVE, and sorted by fluorescence activated cell sorting into a GFP-positive (pathogen-proximal) and GFP-negative (pathogen-distal) population. As a control, uninfected seedlings were also sampled at 12 and 14 days old (equivalent age of 5 and 7 days post-inoculation), protoplasts generated and sorted to yield a GFP-negative population of uninfected control cells. Gene expression was analysed using NimbleGen 12 x 135K microarrays, designed for the TAIR10 genome. Data was normalised using the Robust Multichip Averaging algorithm.

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MetaboLights MTBLS1550 - GNPS Metabolomics analysis identifies metabolites associated with systemic acquired resistance in Arabidopsis

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