Universal Indicators for Oil and Gas Prospecting Based on Bacterial Communities Shaped by Light-Hydrocarbon Microseepage in China.
Light hydrocarbons accumulated in subsurface soil by long-term microseepage could favor the anomalous growth of indigenous hydrocarbon-oxidizing microorganisms, which could be crucial indicators of underlying petroleum reservoirs. Here, Illumina MiSeq sequencing of the 16S rRNA gene was conducted to determine the bacterial community structures in soil samples collected from three typical oil and gas fields at different locations in China. Incubation with n-butane at the laboratory scale was performed to confirm the presence of "universal microbes" in light-hydrocarbon microseepage ecosystems. The results indicated significantly higher bacterial diversity in next-to-well samples compared with background samples at two of the three sites, which were notably different to oil-contaminated environments. Variation partitioning analysis showed that the bacterial community structures above the oil and gas fields at the scale of the present study were shaped mainly by environmental parameters, and geographic location was able to explain only 7.05% of the variation independently. The linear discriminant analysis effect size method revealed that the oil and gas fields significantly favored the growth of Mycobacterium, Flavobacterium, and Pseudomonas, as well as other related bacteria. The relative abundance of Mycobacterium and Pseudomonas increased notably after n-butane cultivation, which highlighted their potential as biomarkers of underlying oil deposits. This work contributes to a broader perspective on the bacterial community structures shaped by long-term light-hydrocarbon microseepage and proposes relatively universal indicators, providing an additional resource for the improvement of microbial prospecting of oil and gas.
State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, Beijing 100193, P.R. China.
Chunping
C
Deng
State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, Beijing 100193, P.R. China.
Xuejian
X
Yu
State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, Beijing 100193, P.R. China.
Jinshui
J
Yang
State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, Beijing 100193, P.R. China.
Baozhen
B
Li
National Research Center for Geoanalysis, Beijing 100037, P.R. China.
Weilin
W
Sun
State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, Beijing 100193, P.R. China.
Hongli
H
Yuan
D001419:Bacteria / Q000145:classification*; D044822:Biodiversity; D002681:China; D016000:Cluster Analysis; D006838:Hydrocarbons; D008027:Light; D059206:Natural Gas; D061329:Oil and Gas Fields; D010578:Petroleum; D010802:Phylogeny; D012987:Soil / Q000737:chemistry; D012988:Soil Microbiology
D006838:Hydrocarbons; D059206:Natural Gas; D010578:Petroleum; D012987:Soil
Light-hydrocarbon microseepage; bacterial community structure; hydrocarbon-oxidizing bacteria; linear discriminant analysis effect size