Dataset Information

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.

SUBMITTER: Peng M

PROVIDER: S-EPMC4626951 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Two consortia (Consortium A and Consortium B) that can use 1,4-dioxane (a groundwater contaminant of emerging concern) as the sole carbon source were enriched from Rice University (Houston, TX, USA) campus soil. Phylogenetic analysis by 16S rRNA sequencing revealed the dominant genus in both of the consortia is Mycobacterium (56% in Consortium A and 49% in Consortium B). The predominance of Mycobacterium spp, in these consortia support the notion that this is an important and commonly encountered genus of dioxane degraders. Among other genera present that make at least 2% of these consortia, only Afipia encompasses a strain (i.e., Afipia sp. D1) that was reported to degrade dioxane as sole carbon and energy source. A nested PCR analysis using two degenerate primers to target the hydroxylase alpha subunit of groups 3 to 6 SDIMOs was performed to gain insights into which enzymes were responsible for dioxane degradation by these consortia. The purified products obtained from the second PCR run were sequenced and compared to genes databases (NCBI) encompassing all of the currently reported SDIMOs. The dominant SDIMO genes in Consortium A corresponded to a group-6 putative propane monooxygenase-like SDIMO (98.8%); while in Consortium B, SDIMO genes from both groups 5 (47.3%) and 6 (51.9%) were observed. In both consortia, the relative abundance of thmA/dxmA gene was negligible (0.03%), which is consistent with the negative amplification of these genes as verified in qPCR. Overall, the high relative abundance of group-6 putative propane monooxygenases in our two consortia suggests the novel finding that group 6-SDIMOs could also play an important role in dioxane degradation. This underscores the need for further research on genes and enzymes involved in dioxane biodegradation to develop novel biomarkers that can be useful for forensic analysis and performance assessment of bioremediation and natural attenuation at dioxane-impacted sites. DNA was extracted from bacteria biomass harvested in exponential growth phase, when half or more of the added dioxane (100 mg/L) was consumed. Total DNA extractions were performed using the UltraClean® Microbial DNA Isolation Kit (MO BIO, Carlsbad, CA, USA) according to the manufacturer’s protocol. The V4 region of the 16S rRNA gene was amplified by PCR using the forward 515F and reverse 806R primers. Sequencing was performed at MR DNA (www.mrdnalab.com, Shallowater, TX, USA) by Illumina MiSeq paired-end sequencing (approximately 2×300 bp as the read length). Sequence data were processed using MR DNA analysis pipeline. Operational taxonomic units (OTUs) were defined by clustering at 3% divergence (97% similarity). Final OTUs were taxonomically classified using BLASTn against the RDPII (http://rdp.cme.msu.edu) and NCBI (www.ncbi.nlm.nih.gov) databases.Previously designed degenerate primers NVC57, NVC58, NVC65 and NVC66 to target conserved regions in the soluble di-iron monooxygenases (SDIMO) alpha subunit gene (groups 3 to 6) were used to examine the presence and diversity of SDIMO genes in these two consortia. A nested PCR strategy was used to increase the PCR product yield. In the first run, the PCR mixture contained 1 µL of NVC65 and NVC58 primer mixture (10 µM), 20 ng of the extracted genomic DNA, 12.5 µL of KAPA HiFi HotStart ReadyMix (2X) (KAPA Biosystems, Wilmington, MA, USA), and nuclease-free water to yield a total volume of 25 µL. PCR was performed in a Bio-Rad Thermal Cycler (Bio-Rad, Hercules, CA, USA) with the following temperature profile: initial denaturation (94°C, 5 min), then 29 amplification cycles (94°C for 30 s, 55°C for 30 s, 72°C for 1 min per kb) and a final extension (72°C for 5 min). The length of the PCR products in the first run was checked by 1% agarose gel and DNA bands of the correct size (1100 bp) were excised and purified. 20 ng of the purified PCR product was used as the DNA template in the second run, with the second set of primers (NVC57 and NVC66). The purified product (420 bp) from the second PCR was sent to MR DNA (www.mrdnalab.com, Shallowater, TX, USA) for Illumina MiSeq paired-end sequencing (approximately 2×300 bp as the read length). Sequence data were processed using MR DNA analysis pipeline. Operational taxonomic units (OTUs) were defined by clustering at 3% divergence (97% similarity). A database including all of the currently reported SDIMO genes on NCBI was created and used to taxonomically classify the final OTUs.

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

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