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典型油田区油污土壤微生物群落区域性分布研究
引用本文:荆佳维,王卅,郭书海. 典型油田区油污土壤微生物群落区域性分布研究[J]. 环境科学学报, 2021, 41(11): 4660-4675
作者姓名:荆佳维  王卅  郭书海
作者单位:中国科学院沈阳应用生态研究所,沈阳110016;中国科学院大学,北京100049;污染土壤生物-物化协同修复技术国家地方联合工程实验室,沈阳110016;中国科学院沈阳应用生态研究所,沈阳110016;污染土壤生物-物化协同修复技术国家地方联合工程实验室,沈阳110016
基金项目:国家自然科学基金(No.21707150);国家重点研发计划项目(No.2018YFC1801900);辽宁省‘兴辽英才计划’项目(No.XLYC1802111)
摘    要:石油污染改变土壤微生态环境,驱动了土壤微生物群落结构的演替与进化.为了深入探究油田区油污土壤中微生物群落分布特征,揭示区域性的土壤微生物群落结构成因,采用Miseq平台的16S rDNA扩增子测序技术分析了辽河油田和大庆油田区6组共计18个土壤样品的微生物群落多样性及结构组成,并结合土壤环境因子指标剖析了群落结构成因,进而预测了具有石油代谢能力的功能菌属.结果表明,石油含量随着距井口距离增加而减少,石油的空间分布特征是影响微生物群落结构变化的关键因子,6组土壤样品的OTU分属于49门、131纲、169目、328科和564属,微生物种群多样性随着污油浓度的增加而减小;两油田共有5个相同优势菌门,2种优势菌属;辽河油田区独特优势菌门为Saccharibacteria门,优势菌属为微枝形杆菌属(Microvirga)、分支杆菌属(Mycobacterium)和Defluviicoccus属;大庆油田独特优势菌门为拟杆菌门(Bacteroidetes),独特优势菌属包括盐单胞菌属(Halomonas)、食烷菌属(Alcanivorax)和海杆菌属(Marinobacter)等.冗余分析(RDA)结果表明污油组成是微生物群落差异性分布的决定性因素,胶质的高含量与强毒性诱导辽河油田区微生物群落获得较强的胁迫抗性;同时区域生态环境背景差异也是影响微生物群落整体胁迫抗性的重要因子.结合PICRUSt分析预测,共发现2种辽河油田区和5种大庆油田区石油功能降解优势菌属,为石油降解功能菌剂的种质资源的高效开发提供目标菌株.

关 键 词:油田土壤  微生物群落  环境因子  污油组成  高通量测序
收稿时间:2021-01-07
修稿时间:2021-01-24

Regional distribution of crude oil-contaminated soil microbial communities in typical oilfields
JING Jiawei,WANG S,GUO Shuhai. Regional distribution of crude oil-contaminated soil microbial communities in typical oilfields[J]. Acta Scientiae Circumstantiae, 2021, 41(11): 4660-4675
Authors:JING Jiawei  WANG S  GUO Shuhai
Affiliation:1. Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016;2. University of Chinese Academy of Sciences, Beijing 100049;3. National-Local Joint Engineering Laboratory of Contaminated Soil Remediation by Bio-physicochemical Synergistic Process, Shenyang 110016;1. Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016;2. National-Local Joint Engineering Laboratory of Contaminated Soil Remediation by Bio-physicochemical Synergistic Process, Shenyang 110016
Abstract:Petroleum pollution changes the soil microecological environment and drives the succession and evolution of soil microbial community structure. To explore the distribution characteristics of microbial community in oilfield soil, and reveal the causes of the formation of regional soil microbial community structure, the microbial community diversity and structure of 18 soil samples from 6 groups in Liaohe oilfield and Daqing oilfield are analyzed by Miseq16S rDNA sequencing technique. Then combining with the index of soil environmental factors, the causes of community structure are analyzed, and the functional bacteria with the ability of petroleum metabolism are predicted. The results showed that the petroleum content decreases with the increase of the distance from the oil well, and the spatial distribution of petroleum is the key factor affecting the change of microbial community structure. The OTUs of the 6 soil sample groups belong to 49 phyla, 131 classes, 169 orders, 328 families and 564 genera. The diversity of microbial population decreases with the increase of petroleum pollution. There are 5 same dominant phyla and 2 dominant genera in the two oilfields. The unique dominant phylum in Liaohe oilfield is Saccharibacteria, and the dominant genera are Microvirga, Mycobacterium and Defluviicoccus. The unique dominant phylum in Daqing oilfield is Bacteroidetes, and the dominant genera are Halomonas, Alcanivora, Marinobacter, etc. The results of redundancy analysis (RDA) showed that the composition of oil was the decisive factor for the differential distribution of microbial community. The high content and strong toxicity of colloid induce the microbial community in Liaohe oilfield to acquire strong stress resistance. At the same time, the background difference of regional ecological environment is also an important factor affecting the overall stress resistance of microbial community. Combining with the PICRUSt analysis, predict 2 dominant genera of petroleum degradation in Liaohe oilfield and 5 in Daqing oilfield. It provids a target reference for the efficient development of petroleum degradation functional germplasm resources.
Keywords:oilfield soil  microbial community  environmental factors  petroleum composition  high-throughput sequencing
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