基于病菌侵染细胞壁SERS非标记成像的苹果树腐烂病早期诊断方法研究

The occurrence of apple vaisa canker disease has a serious impact on apple yield and quality, and the early diagnosis of rot disease is of great significance. There are two key scientific problems needed to be solved urgently: exploring the interaction mechanism between pathogens and host, establishing fast and stable model to detect the apple vaisa canker disease. In this project, the interaction process between pathogens and host cell wall was taken as the breakthrough of study point, apple tree stem cell wall was used as the research object, details of research were to: establish discriminative analysis model for exploring the interaction mechanism between pathogen and host based on surface enhanced Raman (SERS) technique, theoretical analysis and data mining methods; study the dynamic response of pathogen infection on cell wall and the change of polysaccharide content, establish a high-throughput and label-free imaging method to detect the disease at early stage; combine Raman spectra with characteristic fingerprint information, construct analysis methods covered multi source information to verify the accuracy of this early diagnosis model. This project aims to study the interaction process between pathogens and hosts in the molecular level, the results provide research ideas for further investigation of the pathogenic mechanism between pathogen and host, and offer theoretical basis and technical support for prevention and controlling apple vaisa canker disease and breeding for disease resistance.

苹果树腐烂病的发生对苹果产量和品质造成严重影响，腐烂病的早期诊断意义重大。探明腐烂病原菌与苹果树细胞互作机理，建立有效的苹果树腐烂病早期诊断模型已成为迫切需要解决的问题。本项目以苹果树腐烂病菌与寄主细胞壁的互作响应为切入点，以苹果树枝干细胞壁为研究对象，运用表面增强拉曼（SERS）技术，将理论分析与数据挖掘方法结合，构建腐烂病原菌侵染细胞壁的SERS响应特性模型，探明病原菌与寄主的互作响应机制；研究病原菌侵染细胞壁的动态响应和细胞壁多糖化合物含量的变化规律，建立高通量非标记成像方法，实现苹果树腐烂病的早期诊断；将寄主细胞壁拉曼光谱与特征指纹图谱结合，建立多源信息融合的苹果树腐烂病早期诊断方法，验证苹果树腐烂病早期诊断模型的准确性。本项目以期从分子水平探明腐烂病病原菌与苹果树细胞的互作响应特性，为揭示苹果树腐烂病菌致病机理提供研究思路，也为苹果树腐烂病的防控和抗病育种提供理论依据和技术支撑。

苹果树腐烂病的发生对苹果产量和品质造成严重影响，腐烂病的早期诊断意义重大。探明腐烂病原菌与苹果树细胞互作机理，建立有效的苹果树腐烂病早期诊断模型已成为迫切需要解决的问题。本项目以苹果树腐烂病菌与寄主细胞壁的互作响应为切入点，以苹果树枝干细胞壁为研究对象，运用表面增强拉曼（SERS）技术，将理论分析与数据挖掘方法，主要的研究内容有：1）基于构筑银溶胶纳米，并对其性能以及稳定性加以反复验证，得到原始的树皮 SERS 信号；基于密度泛函理论，在 B3LYP 水平上进行理论模拟，进行了苹果树皮主要成分，如木质素、纤维素和果胶多糖结构单体分子的拉曼光谱理论计算，完成拉曼特征峰振动模式的归属；2）在优化测试参数下，获取健康和染菌苹果树皮的 SERS 信号；研究 SERS 数据预处理，进行宇宙射线、基线漂移和荧光信号的去除；进行谱峰解析和归属，完成苹果树腐烂病菌侵染的早期检测方法和模型的建立，并分析苹果树皮组织与腐烂病互作过程中多糖成分的变化规律；3）建立苹果树皮在腐烂病原菌侵染下的多糖变化的非标记高通量化学成像方法，完成苹果树皮组织在腐烂病原菌侵染下的多糖变化可视化；同时结合机器学习建立基于时间序列的苹果树腐烂菌侵染下寄主细胞的反应并建立动态检测模型。