|Table of Contents|

16S rDNA-assisted high-throughput sequencing analysis of microbial diversity in oil reservoirs*(PDF)

Chinese Journal of Applied & Environmental Biology[ISSN:1006-687X/CN:51-1482/Q]

2016 03
Research Field:
Publishing date:


16S rDNA-assisted high-throughput sequencing analysis of microbial diversity in oil reservoirs*
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
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

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.


1 Magot M, Ollivier B, Patel BK. Microbiology of petroleum reservoirs [J]. Anton Leeuw S Microbial, 2000, 77 (2): 103-116 2 刘金峰, 牟伯中. 油藏极端环境中的微生物[J]. 微生物学杂志, 2004, 24 (4): 31-34 [Liu JF, Mu BZ. Extreme environment of oil reservoir and associated microorganisms [J]. J Microbiol, 2004, 24 (4): 31-34] 3 承磊, 仇天雷, 邓宇, 张辉. 油藏厌氧微生物研究进展[J]. 应用与环境生物学报, 2006, 12 (5): 740-744 [Cheng L, Qiu TL, Deng Yu, Zhang Hui. Recent advances in anaerobic microbiology of petroleum reservoirs [J]. Chin J Appl Environ Biol, 2006, 12 (5): 740-744] 4 Brown LR. Microbial enhanced oil recovery (MEOR) [J]. Curr Opin Microbiol, 2010, 13 (3): 316-20 5 Sen R. Biotechnology in petroleum recovery: the microbial EOR [J]. Prog Energ Combust, 2008, 34 (6): 714-724 6 Van Hamme JD, Singh A, Ward OP. Recent advances in petroleum microbiology [J]. Microbiol Mol Biol Rev, 2003, 67 (4): 503-549 7 Rappé MS, Giovannoni SJ. The uncultured microbial majority [J]. Annu Rev Microbiol, 2003, 57: 369-94 8 Pace NR, Stahl DA, Lane DJ, Olsen GJ. The analysis of natural microbiol population by ribsomal RNA sequence [J]. Adv Microb Ecol, 1986, 9 (1): 1-55 9 Woese CR, Fox GE. Phylogenetic structure of the prokaryotic domain: the primary kingdoms [J]. P Natl Acad Sci, 1977, 74 (11): 5088- 5090 10 Case RJ, Boucher Y, Dahll?f I, Holmstr?m C, Doolittle WF, Kjelleberg S. Use of 16S rRNA and rpoB genes as molecular markers for microbial ecology studies [J]. Appl Environ Microb, 2007, 73 (1): 278-88 11 李辉, 牟伯中. 油藏微生物多样性的分子生态学研究进展[J]. 微生物学通报, 2008, 35 (5): 803-808 [Li H, Mu BZ. Recent advances in molecular microbial ecology of petroleum reservoirs [J]. Microbiol China, 2008, 35 (5): 803-808] 12 Liu WT, Marsh TL, Cheng H, Characterization of microbial diversity by determining terminal restriction fragment length polymorphisms of genes encoding 16S rRNA [J]. Appl Environ Microb, 1997, 63 (11): 4516-4522 13 王凤兰, 王晓东. 分子微生物生态学技术在中国油田开发中的应用[J]. 应用与环境生物学报, 2007, 13 (4): 597-600 [Wang FL, Wang XD. Application of molecular ecological technique of microbes in oilfield exploitation in China [J]. Chin J Appl Environ Biol, 2007, 13 (4): 597-600] 14 夏围围, 贾仲君. 高通量测序和DGGE分析土壤微生物群落的技术评价[J]. 微生物学报, 2014, 54 (12): 1489-1499 [Xia WW, Jia ZJ. Comparative analysis of soil microbial communities by pyrosequencing and DGGE [J]. Acta Microbiol Sin, 2014, 54 (12): 1489-1499] 15 Grabowski A, Nercessian O, Fayolle F, Blanchet D, Jeanthon C. Microbial diversity in production waters of a low-temperature biodegraded oil reservoir [J]. FEMS Microbiol Ecol, 2005, 54 (3): 427-443 16 Orphan VJ, Taylor LT, Hafenbradl D, Delong EF. Culture-dependent and culture-independent characterization of microbial assemblages associated with high-temperature petroleum reservoirs [J]. Appl Environ Microb, 2000, 66 (2): 700-711 17 宋智勇, 郝滨, 赵凤敏, 高光军, 汪卫东. 胜利油田水驱油藏内源微生物群落结构及分布规律[J]. 西安石油大学学报(自然科学版), 2013, 28 (4): 44-50 [Song ZY, Hao B, Zhao FM, Gao GJ, Wang WD. Community structure and distribution characters of indigenous microorganism in water flooding reservoir of Shengli oilfield. J Xi’an Shiyou Univ Nat Sci Ed), 2013, 28 (4): 44-50] 18 王兴彪, 张晴, 刘洋, 汤岳琴, 吴钢, 吴晓磊. 脱水原油中的微生物及其原油降解活性[J]. 应用与环境生物学报, 2013, 19 (3): 515-518 [Wang XB, Zhang Q, Liu Y, Tang YQ, Wu G, Wu XL. Microorganisms and their oil-degrading activities in dehydrated crude oil [J]. Chin J Appl Environ Biol, 2013, 19 (3): 515-518] 19 Shendure J, Ji H. Next-generation DNA sequencing [J]. Nat Biotechnol, 2008, 26 (10): 1135-1145 20 van Dijk EL, Auger H, Jaszczyszyn Y, Thermes C. Ten years of next-generation sequencing technology [J]. Trends Genet, 2014, 30 (9): 418-426 21 She YH, Zhang XL, Zhang F, Wang LH, Zhao LP. Molecular analysis of the microbial communities of the Dagang Kongdian flooding bed oilfield [J]. J Microorganism, 2005, 45 (3): 329-34 22 任国领, 曲丽娜, 乐建君, 由春梅, 黄永红. 大庆萨南开发区高台子油层细菌群落结构[J]. 大庆石油学院学报, 2011, 35 (4): 71-82 [Ren GL, Qu LN, Le JJ, You CM, Huang YH. Bacterial community structure in Sanan Gaotaizi reservoir of Daqing oilfield [J]. J Daqing Petrol Inst, 2011, 35 (4): 71-82] 23 Etoumi A, Musrati I El, Gammoudi B El, Behlil M El. The reduction of wax precipitation in waxy crude oils by Pseudomonas species [J]. J Ind Microbiol Biot, 2008, 35 (11): 1241-1245 24 夏文杰, 董汉平, 俞理. 烃降解菌WJ-1及其生物表面活性剂特性研究[J]. 油田化学, 2009, 26 (4): 436-418 [Xia WJ, Dong HP, Yu L. Physiological and biochemical characteristics of hydrocarbon-degrading strain WJ-1 and its biosurfactants [J]. Oilfield Chem, 2009, 26 (4): 436-418] 25 刘芝芳, 易绍金. DNB-SRB-MEOR技术的研究与应用进展[J]. 长江大学学报(自然科学版), 2011, 8 (3): 67-69 [Liu ZF, Yi SJ. The recent advance and application of DNB-SRB-MEOR technology [J]. J Yangtze Univ Nat Sci Ed, 2011, 8 (3): 67-69] 26 Koma D, Hasumi F, Yamamoto E, OhtaT, Chung S, Kubo M. Biodegradation of long-chain n-paraffins from waste oil of car engine by Acinetobacter sp. [J]. J Biosci Bioeng, 2011, 91: 94-96 27 艾明强, 李慧, 刘晓波, 史荣久, 韩斯琴, 李娜娜, 张颖. 大庆油田油藏采出水的细菌群落结构[J]. 应用生态学报, 2010, 21 (4): 1014-1020 [Ai MQ, Li H, Liu XB, Shi RJ, Han SQ, Li NN, Zhang Y. Bacterial community structure in production water from oil reservoirs in Daqing Oilfield [J]. Chin J Appl Ecol, 2010, 21 (4): 1014-1020]


Last Update: 2016-06-25