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[1]许 颖** 马德胜 宋文枫 魏小芳.16S rDNA高通量测序技术分析油藏微生物多样性?[J].应用与环境生物学报,2016,22(03):409-414.[doi:10.3724/SP.J.1145.2015.09003]
　XU Ying**,MA Desheng,SONG Wenfeng & WEI Xiaofang.16S rDNA-assisted high-throughput sequencing analysis of microbial diversity in oil reservoirs*[J].Chinese Journal of Applied & Environmental Biology,2016,22(03):409-414.[doi:10.3724/SP.J.1145.2015.09003]
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16S rDNA高通量测序技术分析油藏微生物多样性?()
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《应用与环境生物学报》[ISSN:1006-687X/CN:51-1482/Q]

卷:
22卷
期数:
2016年03期
页码:
409-414
栏目:
研究论文
出版日期:
2016-06-25

文章信息/Info

Title:
16S rDNA-assisted high-throughput sequencing analysis of microbial diversity in oil reservoirs*
作者:
许 颖** 马德胜 宋文枫 魏小芳
中国石油勘探开发研究院，提高石油采收率国家重点实验室 北京 100083
Author(s):
XU Ying**;  MA Desheng;  SONG Wenfeng & WEI Xiaofang
PetroChina Research Institute of Petroleum Exploration & Development, State Key Laboratory of Enhanced Oil Recovery, Beijing 100083, China
关键词:
油藏; 微生物多样性; 16S rDNA; 高通量测序; 石油微生物; 微生物采油
Keywords:
The indigenous microbial community in oil reservoirs has great influence on the application of microbial enhanced oil recovery technology (MEOR). This research aimed to investigate the microbial diversity in oil reservoirs by the combined methods of the r
分类号:
TE357.9
DOI:
10.3724/SP.J.1145.2015.09003
摘要:
以16S rDNA为分子标记，采用高通量测序技术分析吉林油田FY区块D1、D2和D3三口采油井中的微生物群落构成. 对3个DNA样本中细菌16S rDNA的PCR扩增产物进行高通量测序，得到123 360条优化序列，测序深度指数超过99.9%. 根据序列相似性进行聚类分析，得到139个OTU. 基于OTU的物种分类分析，发现3个样本中的细菌种类覆盖91个属29个纲20个门，其中包括多种采油有益菌. 分别对各个样本的菌种组成和相对丰度进行分析，发现不同采油井的主要菌种组成和优势类群呈现出差异性. D1中以γ-proteobacteria（52%）和ε-proteobacteria（39%）为主，优势属为Pseudomonas（51%）和Arcobacter（38%）；D2中以ε-proteobacteria（88%）为主，优势属为Arcobacter（88%）；D3中以α-proteobacteria（55%）、ε-proteobacteria（20%）和β-proteobacteria（19%）为主，优势属为Rhizobium（36%）和Arcobacter（20%）. 本研究结果可为油藏微生物资源的开发利用和微生物采油技术的开展提供精确全面的背景信息支持. （图6 表1 参27）
Abstract:
The indigenous microbial community in oil reservoirs has great influence on the application of microbial enhanced oil recovery technology (MEOR). This research aimed to investigate the microbial diversity in oil reservoirs by the combined methods of the recently developed next generation sequencing technology (NGS) and 16S rDNA molecular marker. Total DNA of three samples was extracted separately, followed by amplification of bacterial 16S rDNA fragment. PCR products were sequenced on the Illumina MiSeq platform. Sequencing dataset with high quality was collected for further analysis. Identification of bacteria at different taxonomic levels was performed based on the result of blast against annotated 16S rDNA database. Microbial diversity in each sample was analyzed separately and compared with each other. We obtained 123 360 16S rDNA sequences with high quality. The sequencing coverage was more than 99.9%. These sequences were clustered into 139 OTUs. Bacterial species detected in these samples covered 91 genera, 29 classes and 20 phyla, including many groups beneficial for MEOR. Bacteria (e.g. Arcobacter, Pseudomonas and Acinetobacter) that can utilize petroleum hydrocarbons as sole carbon sources were detected, even those with extremely low abundance. Moreover, the analysis of microbial community structure for each sample showed different patterns of composition characteristics and dominant groups. In D1, the main classes were γ-proteobacteria (52%) and ε-proteobacteria (39%), and the predominant genera were Pseudomonas (51%) and Arcobacter (38%). In D2, the main class was ε-proteobacteria (88%), and the predominant genus was Arcobacter (88%). In D3, the main classes were α-proteobacteria (55%), ε-proteobacteria (20%) and β-proteobacteria (19%), and the predominant genera were Rhizobium (36%) and Arcobacter (20%).The results indicated that analysis based on high-throughput sequencing data of 16S rDNA fragments is powerful in accurately reflecting microbial community structure and provides more information for MEOR than traditional methods.

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更新日期/Last Update: 2016-06-25