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典型气田土壤铁还原活性与微生物群落关系研究
引用本文:孙博雅,程永毅,肖广全,王彦琴,王明霞,周志峰.典型气田土壤铁还原活性与微生物群落关系研究[J].环境科学学报,2021,41(10):4170-4178.
作者姓名:孙博雅  程永毅  肖广全  王彦琴  王明霞  周志峰
作者单位:西南大学资源环境学院, 重庆 400715
基金项目:国家自然科学基金项目(No.41771501)
摘    要:由微生物驱动的土壤铁还原过程在铁的生物地球化学循环中起到重要作用,该过程还可与土壤重金属的转化及石油烃类有机污染物的降解等过程相偶联.油气田土壤常具有潜在有机污染物风险,本研究以重庆涪陵页岩气田的土壤(潜在烃类有机物污染风险)为对象,测定土壤铁还原活性(Iron Reducing Potential,IRP),并利用Illumina Miseq测序解析其中的铁还原微生物类群,进而探讨IRP、土壤基本性质及微生物群落之间的关系.结果表明,该区域土壤铁还原菌群的优势菌门为厚壁菌门(Firmicutes)、变形菌门(Proteobacteria)和拟杆菌门(Bacteroidetes).与低IRP样品相比,高IRP样品中Pseudomonas、norank PeptococcaceaeLentimicrobium等菌属具有较高的相对丰度.基于各样品OTU (Operational Taxonomic Unit)组成的PCoA (Principal Co-ordinates Analysis)分析表明,高、中及低IRP样品中铁还原菌群落结构差异显著(R2=0.25,p<0.01),且一些分别属于Acetoanaerobium、Proteiniphilum、Petrimonas、TessaracoccusExiguobacterium菌属中的OTUs在高IRP样品中显著上调.结构方程模型表明,铁还原微生物的群落结构是直接决定土壤IRP的主要因子,土壤氨氮及有效磷均可通过影响微生物群落结构来间接影响IRP,且氨氮还可通过直接影响有效磷来间接影响土壤IRP.本研究揭示了影响典型页岩气田土壤铁还原活性的关键因子及微生物机制,为进一步深入研究铁还原条件下土壤有机污染物去除的微生物机制打下基础.

关 键 词:土壤  铁还原活性  铁还原菌群  群落结构  结构方程模型
收稿时间:2020/12/30 0:00:00
修稿时间:2021/1/22 0:00:00

Relationship between iron reducing potential of soil and microbial community structure in a typical shale gas field
SUN Boy,CHENG Yongyi,XIAO Guangquan,WANG Yanqin,WANG Mingxi,ZHOU Zhifeng.Relationship between iron reducing potential of soil and microbial community structure in a typical shale gas field[J].Acta Scientiae Circumstantiae,2021,41(10):4170-4178.
Authors:SUN Boy  CHENG Yongyi  XIAO Guangquan  WANG Yanqin  WANG Mingxi  ZHOU Zhifeng
Institution:College of Resources and Environment, Southwest University, Chongqing 400715
Abstract:The iron-reducing process driven by soil microbes plays a crucial role in the biochemical cycling of iron worldwide, which can be coupled with the transformation of heavy metals and the metabolism of organic pollutants that originate from petroleum hydrocarbons. Oil and gas fields usually exhibit a potential risk of organic pollutant contamination. In this study, to investigate the relationship between the iron-reducing potential (IRP) of soils and the iron-reducing microbial community, soil samples that can cause petroleum hydrocarbon pollution were collected from the Fuling shale gas field located in Chongqing, China. Subsequently, the IRP of each sample was determined, and the structure of the iron-reducing bacterial community enriched using each sample was explored via Illumina MiSeq sequencing. The results showed that Firmicutes, Proteobacteria, and Bacteroidetes were the dominant bacterial phyla in the iron-reducing bacterial consortia enriched using the soil samples derived from the shale gas field. Furthermore, higher relative abundances of some bacterial genera, such as Pseudomonas, norank Peptococcaceae, and Lentimicrobium were detected in the high IRP samples. The result of the principal coordinate analysis (PCoA) based on the OTU level indicated that there was a significant difference in the iron-reducing microbial community enriched using the low, medial, and high IRP samples (R2=0.25, p<0.01). Meanwhile, compared to the microbial consortia in the low IRP samples, some OTUs belonging to the bacterial genera Acetoanaerobium, Proteiniphilum, Petrimonas, Tessaracoccus, and Exiguobacterium were significantly upregulated in the high IRP consortiums. The structural equation model derived from the IRP, soil properties, and microbial community characteristics demonstrated that the iron-reducing bacterial community structure was the sole and key factor directly affecting soil IRP; however, soil ammonia and available phosphorus could indirectly affect soil IRP by their direct influence on the soil microbial community structure. Moreover, soil ammonia also showed an indirect effect on soil IRP by its step-by-step impact on available phosphorus, microbial community, and IRP. The results of this study reveal the key factors and microbial mechanisms that govern the soil IRP in this typical shale gas field, which should be significant for further investigation of the elimination mechanism of organic pollutants in soils under iron-reducing environments.
Keywords:soil  iron-reducing potential  iron-reducing bacteria  community structure  structural equation model
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