Differential Metabolic Reprogramming in Paenibacillus alvei-Primed Sorghum bicolor Seedlings in Response to Fusarium pseudograminearum Infection.
René CarlsonFidele TugizimanaPaul A SteenkampIan A DuberyNico LabuschagnePublished in: Metabolites (2019)
Metabolic changes in sorghum seedlings in response to Paenibacillus alvei (NAS-6G6)-induced systemic resistance against Fusarium pseudograminearum crown rot were investigated by means of untargeted ultra-high performance liquid chromatography-high definition mass spectrometry (UHPLC-HDMS). Treatment of seedlings with the plant growth-promoting rhizobacterium P. alvei at a concentration of 1 × 108 colony forming units mL-1 prior to inoculation with F. pseudograminearum lowered crown rot disease severity significantly at the highest inoculum dose of 1 × 106 spores mL-1. Intracellular metabolites were subsequently methanol-extracted from treated and untreated sorghum roots, stems and leaves at 1, 4 and 7 days post inoculation (d.p.i.) with F. pseudograminearum. The extracts were analysed on an UHPLC-HDMS platform, and the data chemometrically processed to determine metabolic profiles and signatures related to priming and induced resistance. Significant treatment-related differences in primary and secondary metabolism post inoculation with F. pseudograminearum were observed between P. alvei-primed versus naïve S. bicolor seedlings. The differential metabolic reprogramming in primed plants comprised of a quicker and/or enhanced upregulation of amino acid-, phytohormone-, phenylpropanoid-, flavonoid- and lipid metabolites in response to inoculation with F. pseudograminearum.
Keyphrases
- ms ms
- ultra high performance liquid chromatography
- tandem mass spectrometry
- mass spectrometry
- high resolution mass spectrometry
- liquid chromatography
- plant growth
- simultaneous determination
- arabidopsis thaliana
- drug induced
- high glucose
- amino acid
- diabetic rats
- high performance liquid chromatography
- gas chromatography
- high resolution
- solid phase extraction
- genome wide
- gene expression
- deep learning
- poor prognosis
- endothelial cells
- dna methylation
- big data
- fatty acid
- artificial intelligence
- gas chromatography mass spectrometry
- smoking cessation