Bacterial Community Diversity of Oil-Contaminated Soils Assessed by High Throughput Sequencing of 16S rRNA Genes

Abstract

Soil bacteria play a major role in ecological and biodegradable function processes in oil-contaminated soils. Here, we assessed the bacterial diversity and changes therein in oil-contaminated soils exposed to different periods of oil pollution using 454 pyrosequencing of 16S rRNA genes. No less than 24,953 valid reads and 6246 operational taxonomic units (OTUs) were obtained from all five studied samples. OTU richness was relatively higher in contaminated soils than clean samples. Acidobacteria, Actinobacteria, Bacteroidetes, Chloroflexi, Planctomycetes and Proteobacteria were the dominant phyla among all the soil samples. The heatmap plot depicted the relative percentage of each bacterial family within each sample and clustered five samples into two groups. For the samples, bacteria in the soils varied at different periods of oil exposure. The oil pollution exerted strong selective pressure to propagate many potentially petroleum degrading bacteria. Redundancy analysis (RDA) indicated that organic matter was the highest determinant factor for explaining the variations in community compositions. This suggests that compared to clean soils, oil-polluted soils support more diverse bacterial communities and soil bacterial community shifts were mainly controlled by organic matter and exposure time. These results provide some useful information for bioremediation of petroleum contaminated soil in the future.

Spatial Pattern of Bacterial Community Diversity Formed in Different Groundwater Field Corresponding to Electron Donors and Acceptors Distributions at a Petroleum-Contaminated Site

“…The Shannon index has been reported to be more sensitive to changes in richness, while the Simpson index is more sensitive to the evenness [45]. Therefore, it can be said that, consistent with other studies [11,46], contamination can result in a decline of diversity and increase of abundances of dominant microorganisms. The RDA plots indicated that, of all the environmental factors, the toluene, xylene, and COD had the most effect on the bacterial communities.…”

“…Research on the diversity of bacterial communities has been carried out at petroleum-contaminated sites since the 1970s [7], and the amounts have grown rapidly as the 16S rRNA gene sequences mature and become universal; most were in soils and sediments [8][9][10][11][12]. A few researchers focusing on groundwater such as Anne Fahy and Zhaoxian Zheng, investigated the relationships between the bacterial community structures and the groundwater geochemistry respectively [13,14], and found that hydrocarbon metabolism would vary the diversity of the bacterial communities.…”

Spatial analysis of a hydrocarbon waste‐remediating landfarm demonstrates influence of management practices on bacterial and fungal community structure

“…Across the landfarm, common soil residents Actinomycetales were the most abundant order of bacteria (Table S2) and soils were highly enriched in taxonomic groups identified in other hydrocarbon‐contaminated soils and water (Peng et al ., ), consistent with the hypothesis that EVRAZ landfarm soils communities have been refined by years of bioremediation activity. These include (but are not limited to) bacterial taxonomic groups of Pseudomonadales (Leahy et al ., ; Seo et al ., ), Acidobacter (Seo et al ., ; Peng et al ., ), Gammaproteobacteria and Actinobacteria (Militon et al ., ; Peng et al ., ), Chloroflexi, Planctomycetes and Bacteroidetes (Peng et al ., ) (Table S2). Specific genera previously demonstrated to be associated with hydrocarbon‐impacted sites and high molecular weight polyaromatic hydrocarbons, such as bacterial OTUs identified as Anaerolineaceae, Caldilineaceae (Zhang et al ., ) and Lutibacter (McFarlin et al ., ) are shown to be elevated in abundance in samples from shallow and deep soils of A and B relative to section C (Fig.…”

Microbial community composition in alpine lake sediments from the Hengduan Mountains

“…The genomic DNA of 15 alpine lake sediments was extracted from 1 g of the sample using an E.A.N.A. Soil DNA Kit (OMEGA, Georgia, GA) as indicated in the instructions (Peng, Zi, & Wang, ). The V4 region of 16S rRNA gene was amplified by PCR using primers 515F (5′‐GTGCCAGCMGCCGCGGTAA‐3′) and 806R (5′‐GGACTACHVGGGTWTCTAAT‐ 3′) (Sun et al., , ).…”

“…All statistical analyses were carried out using the R language. The sequencing reads were classified into operational taxonomic units (OTUs; sequences with similarity ≥97% were defined as one OTU) (Peng et al., ). The OTU annotations were based on the Silva (Silva_119_release_aligned) database (Quast et al., ).…”