茶云纹叶枯病侵染叶片细胞壁多糖的拉曼化学成像机理及特性研究

项目名称： 茶云纹叶枯病侵染叶片细胞壁多糖的拉曼化学成像机理及特性研究

项目编号： No.61201073

项目类型： 青年科学基金项目

立项/批准年度： 2013

项目学科： 电子学与信息系统

项目作者： 李晓丽

作者单位： 浙江大学

项目金额： 27万元

中文摘要： 主要由多糖类物质组成的高等植物细胞壁，是细胞抵抗病原物侵染的首要屏障，所有植物病原物在入侵细胞时均与细胞壁多糖发生作用，因此监测此过程细胞壁多糖的动态变化对于探明植物的发病机制具有重要意义。本项目以被茶云纹叶枯病侵染的茶树叶片为试验对象，研究染病叶片细胞壁多糖的拉曼化学成像机理及特性。首先依据多糖标准品的拉曼光谱指认染病组织细胞壁多糖成分的拉曼特征谱带，并借助化学计量学方法筛选出波峰明显且专一性好的谱带，作为多糖成分的定量峰，建立多糖成分的定性鉴别和定量检测方法；再结合细胞壁的显微图像信息绘制出多糖成分在细胞壁上的空间分布图，实现细胞壁多糖成分的定位检测，从而建立细胞壁多糖的拉曼化学成像检测方法；然后借助该方法探索茶云纹叶枯病侵染过程中细胞壁多糖的变化规律。本项目的研究结果将为细胞壁中其它多聚体的原位快速检测奠定坚实基础，并对进一步探索植物-病原物的分子互作机理具有重要意义。

中文关键词： 茶云纹叶枯病；共焦显微拉曼技术；细胞壁成分；化学成像；化学计量学

英文摘要： The cell wall of higher plant which is mainly composed of polysaccharides, is the primary structural barrier of cell against pathogen infection. All plant pathogens interact with cell wall palysaccharides, so it is meaningful for detection of plant pathogenesis to monitor dynamic variation of cell wall palysaccharides during the plant pathogenic process. This project will investigate the Raman chemical imaging mechanism and characteristic of cell wall polysaccharides of tea leaf infected by tea leaf blight. Firstly, the Raman characteristic bands will be assigned to polysaccharides constitutes according to the Raman scattering rationale and the Raman spectroscopy of standard polysaccharides, and with the aid of chemometrics the obvious and specific Raman bands will be selected as quantitative analysis peaks. Then the approach will be developed for qualitative discrimination and quantitative determination of polysaccharides constitutes in cell wall. Furthermore, the topochemical distribution of polysaccharides constitutes in cell wall could be visualized by integrating microscopic image of cell wall with the Raman fingerprint bands which are contributed by polysaccharides constitutes. As a result the Raman chemical imaging approach will be developed for analysis of cell wall polysaccharides, and it will be used f

英文关键词： Tea brown blight；ConConfocal Raman microscopy；Cell wall components；Chemical imaging；Chemometrics