准确定量分析环境微生物群落丰度及其组成的研究

基于分类标记rRNA基因进行PCR扩增和高通量测序是研究微生物群落丰度及组成的主要方法,也是微生物生态学研究的基础。然而传统分类基因在微生物物种间的拷贝数差异对准确定量微生物群落组成造成不可避免的误差，而降低其结构组成及微生物生态相关机理分析的可靠性。我们前期从事传统分类基因和单拷贝功能基因扩增子测序，阐明环境中物种多样性和功能多样性及相关机理。本课题基于分类基因（16S rRNA基因、ITS）测序成熟技术和单拷贝基因（gyrB、RPB1）测序的准确性，以前期实验分析平台为基础，拟使用人工合成微生物菌群为研究对象，结合传统分类基因和单拷贝基因测序及生物量定量的方法准确分析微生物群落丰度与组成，阐明rRNA拷贝数差异性对测序的影响；并将该方法应用于环境样品，准确阐述微生物群落在自然修复过程中的演替及机制。本项目的开展将为联合多种分类标记基因准确分析环境微生物群落丰度和组成提供理论参考。

Advances in high-throughput sequencing technology have led to the rapid development of microbial ecology. PCR-based phylogenetic analysis targeting marker genes, such as the ribosomal RNA (rRNA), is fundamental to ecology study, providing essential information for the understanding of microbial community composition and structure. A major issue with the use of molecular rRNA as a measure of microbial abundance is that many microbes have multiple copies of the genes in their genome. Thus, variation in rRNA gene abundance can be caused by variations in both the abundance of microbes and the genomic copy numbers. Such inevitable error hinders accurate measurements of community composition, structure, microbe-microbe and microbe-environmental factors interactions. In our preliminary study, we focused on phylogenetic marker gene and single copy functional gene sequencing to understand the phylogenetic diversity and functional diversity of microbial communities in different environments, and explore the underlying mechanisms. This proposal seeks to remedy that problem by adjusting the phylogenetic marker gene copy number (16S rRNA and ITS) using single copy genes (gyrB and RPB1) in the genome using our sequencing and data analysis platform. Upon parallel amplification and sequencing of these genes, the exact copy number of 16S rRNA and ITS genes will be estimated by comparing their abundance with those of gyrB and RPB1 genes. The effectiveness of the proposed approach will be verified using mock microbial community; and further used to estimate community dynamics along the restoration of an abandoned mine more accurately. The proposed approach will provide theoretical framework and scientific basis for the joint analysis of different phylogenetic marker genes for accurate measurement of microbial community diversity.