植物病原细菌的BIOLOG系统鉴定及其多元统计初析

利用Biolog细菌鉴定系统对我国水稻上几种条斑病菌及其相关菌株进行了快速鉴定研究。结果表明16株供试菌株中12株准确鉴定到种或致病变种,有4株鉴定到属。聚类分析显示李氏禾条斑病菌和“稻短条斑病菌”的Biolog代谢指纹相似性高,与小麦黑颖病菌（TAS）亲缘关系较近,而与水稻条斑病菌、稻白叶枯病菌具有明显差异。使用多元统计分析方法对供试菌株的Biolog代谢指纹进行比较研究,通过聚类分析和主成份分析不仅能够区分菌株间的显著差异,而且依据因子权重值可筛选出具有鉴别价值的碳源。

STATISTICAL ANALYSIS OF CATABOLIC PROFILES USING BIOLOG GN MICROPLATES FOR IDENTIFYING PATHOGENIC BACTERIA

The Biolog system (Biolog Inc.USA,BIS)with Microstation TM V3 5 software were used for rapid identification of several three bacterial pathogens causing rice leaf streak and related plant-pathogenic bacteria.The results show that 12 of the 16 strains tested are correctly identified to species (pathovars) level.and four strains identified to genus level.Cluster analysis using Mlclust program (Biolog) and Proc cluster (SAS release 6 04)process shows that the Biolog catabolic profiling between strains of leersiae bacterial leaf streak (BLS) and "rice short streak"(egR1008) is similar,having higher phenotypic similarity with wheat-derived isolates (eg TAS),but differed from rice bacterial blight and rice BLS pathogens.Multivariate statistices were first used to analysis the Biolog data.the result indicates that cluster analysis and principal component (PC) analysis are very useful in testing for significent differences between communties,and PC analysis is advantageous to find discriminating carbon-sourses according to weighted factor loadings.