烟叶表面微生物类群两种检测方法的比较研究

摘要 为研究克隆文库法和高通量测序两种方法对烟叶表面微生物类群的检测效果，确定检测烟叶表面微生物多样性的最优方法，检测了基于细菌16S rDNA和真菌ITS区域的烤烟表面微生物类群的多样性. 结果显示，高通量测序得到的序列数量比克隆文库法多，两种方法检测到细菌的OTU数目相近，但高通量检测的真菌OTU数目较多；稀疏曲线显示高通量测序的数据饱和度更高；预计的群落多样性(Chao1指数和Ace指数)克隆文库法均高于高通量测序法，实际的群落多样性(Simpson指数和Shannon指数)表明克隆文库法检测的细菌多样性略高，而高通量测序检测的真菌多样性略高；在检测到的细菌和真菌种类上，高通量测序略多于克隆文库法，两种方法检测的细菌优势类群基本一致，为假单胞菌属、不动杆菌属和鞘氨醇单胞菌属，但真菌类群相差较大，且高通量测序检测到大量新的真菌序列. 总体上，高通量测序方法具有通量大、产出数据多的优势，可更全面、更准确地反映烟叶表面微生物群落结构. 
Abstract：In order to compare the microbial communities on tobacco leaves between clone library method and highthroughput sequencing method, we analyzed the diversity of microbial communities based on bacterial 16S rDNA and fungal ITS on tobacco leaves collected from Fujian province in China. The results showed that more numbers of bacterial and fungal sequences were detected by highthroughput sequencing than clone library. The number of operational taxonomic units (OTUs) clustered from highthroughput sequencing method was almost the same as that from clone library method in bacterial communities, while that was higher from highthroughput sequencing in fungal communities. The rarefaction curves drawn from highthroughput sequencing method tended to approach the saturation plateau. The expected community diversity indices (Chao1 and Ace) were higher in clone library method, whereas the observed community diversity indices (Simpson and Shannon) suggested that higher bacterial diversities were detected through clone library method and higher fungal diversities were detected through highthroughput sequencing method. There were more kinds of bacteria and fungi genera identified through highthroughput sequencing method. The dominant genera of bacteria were similar detected from both of the methods, including Pseudomonas, Acinetobacter and Sphingonomonas. However, the fungal genera detected through these two methods were significantly different. Overall, novel highthroughput sequencing methods outperform clone library approaches in terms of resolution and magnitude. They enable identification and relative quantification of community members of tobacco leaves and offer new insights into environmental microbiology. 