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解析感染后激发状态下应对感染时的代谢重编程

Unravelling the Metabolic Reconfiguration of the Post-Challenge Primed State in Responding to Infection.

作者信息

Tugizimana Fidele, Steenkamp Paul A, Piater Lizelle A, Labuschagne Nico, Dubery Ian A

机构信息

Research Centre for Plant Metabolomics, Department of Biochemistry, University of Johannesburg, Auckland Park, Johannesburg 2006, South Africa.

Department of Plant and Soil Science, University of Pretoria, Hatfield, Pretoria 0028, South Africa.

出版信息

Metabolites. 2019 Sep 20;9(10):194. doi: 10.3390/metabo9100194.

DOI:10.3390/metabo9100194
PMID:31547091
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6835684/
Abstract

Priming is a natural phenomenon that pre-conditions plants for enhanced defence against a wide range of pathogens. It represents a complementary strategy, or sustainable alternative that can provide protection against disease. However, a comprehensive functional and mechanistic understanding of the various layers of priming events is still limited. A non-targeted metabolomics approach was used to investigate metabolic changes in plant growth-promoting rhizobacteria (PGPR)-primed seedlings infected with the anthracnose-causing fungal pathogen, , with a focus on the post-challenge primed state phase. At the 4-leaf growth stage, the plants were treated with a strain of at 10 cfu mL. Following a 24 h PGPR application, the plants were inoculated with a spore suspension (10 spores mL), and the infection monitored over time: 1, 3, 5, 7 and 9 days post-inoculation. Non-infected plants served as negative controls. Intracellular metabolites from both inoculated and non-inoculated plants were extracted with 80% methanol-water. The extracts were chromatographically and spectrometrically analysed on an ultra-high performance liquid chromatography (UHPLC) system coupled to high-definition mass spectrometry. The acquired multidimensional data were processed to create data matrices for chemometric modelling. The computed models indicated time-related metabolic perturbations that reflect primed responses to the fungal infection. Evaluation of orthogonal projection to latent structure-discriminant analysis (OPLS-DA) loading shared and unique structures (SUS)-plots uncovered the differential stronger defence responses against the fungal infection observed in primed plants. These involved enhanced levels of amino acids (tyrosine, tryptophan), phytohormones (jasmonic acid and salicylic acid conjugates, and zeatin), and defence-related components of the lipidome. Furthermore, other defence responses in both naïve and primed plants were characterised by a complex mobilisation of phenolic compounds and biosynthesis of the flavones, apigenin and luteolin and the 3-deoxyanthocyanidin phytoalexins, apigeninidin and luteolinidin, as well as some related conjugates.

摘要

引发是一种自然现象,它使植物预先具备增强对多种病原体防御能力的条件。它代表了一种补充策略,或是一种可持续的替代方法,能够提供疾病防护。然而,对于引发事件各个层面的全面功能和机制理解仍然有限。采用非靶向代谢组学方法研究了经促进植物生长的根际细菌(PGPR)引发处理的幼苗在感染引起炭疽病的真菌病原体后的代谢变化,重点关注激发后引发状态阶段。在四叶生长阶段,用10 cfu/mL的一种菌株处理植株。在施用PGPR 24小时后,给植株接种孢子悬浮液(10个孢子/mL),并随时间监测感染情况:接种后1、3、5、7和9天。未感染的植株作为阴性对照。用80%甲醇水从接种和未接种的植株中提取细胞内代谢物。提取物在与高分辨率质谱联用的超高效液相色谱(UHPLC)系统上进行色谱和光谱分析。对获取的多维数据进行处理,以创建用于化学计量学建模的数据矩阵。计算模型表明了与时间相关的代谢扰动,反映了对真菌感染的引发反应。对正交投影到潜在结构判别分析(OPLS-DA)载荷共享和独特结构(SUS)图的评估揭示了在引发植株中观察到的对真菌感染更强的差异防御反应。这些反应包括氨基酸(酪氨酸、色氨酸)、植物激素(茉莉酸和水杨酸共轭物以及玉米素)以及脂质组中与防御相关成分的水平升高。此外,未引发和引发植株中的其他防御反应的特征是酚类化合物的复杂调动以及黄酮类化合物、芹菜素和木犀草素以及3-脱氧花青素植保素芹菜素idin和木犀草素idin及其一些相关共轭物的生物合成。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7a87/6835684/839654640860/metabolites-09-00194-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7a87/6835684/fca567439e3e/metabolites-09-00194-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7a87/6835684/ea8a5721aaa5/metabolites-09-00194-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7a87/6835684/ce9fc6e2ea2d/metabolites-09-00194-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7a87/6835684/8a1469071fe0/metabolites-09-00194-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7a87/6835684/d956a426178c/metabolites-09-00194-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7a87/6835684/839654640860/metabolites-09-00194-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7a87/6835684/fca567439e3e/metabolites-09-00194-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7a87/6835684/ea8a5721aaa5/metabolites-09-00194-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7a87/6835684/ce9fc6e2ea2d/metabolites-09-00194-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7a87/6835684/8a1469071fe0/metabolites-09-00194-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7a87/6835684/d956a426178c/metabolites-09-00194-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7a87/6835684/839654640860/metabolites-09-00194-g006.jpg

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