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

Peng M, Zi X, Wang Q - Int J Environ Res Public Health (2015)

Bottom Line: The heatmap plot depicted the relative percentage of each bacterial family within each sample and clustered five samples into two groups.Redundancy analysis (RDA) indicated that organic matter was the highest determinant factor for explaining the variations in community compositions.These results provide some useful information for bioremediation of petroleum contaminated soil in the future.

View Article: PubMed Central - PubMed

Affiliation: College of Life Science, Northeast Forestry University, No.26 Hexing Street, Xiangfang District, Harbin 150040, China. huangxiaoming321@sina.com.

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.

No MeSH data available.


Related in: MedlinePlus

Hierarchically clustered heatmap of bacterial distribution of different communities from the five samples at the genus level. Row represents the relative percentage of each bacterial genus, and column stands for different samples. The relative abundance for each bacterial genus were depicted by color intensity with the legend indicated at the under of the figure. The abbreviation of samples is shown in Table 1.
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ijerph-12-12002-f004: Hierarchically clustered heatmap of bacterial distribution of different communities from the five samples at the genus level. Row represents the relative percentage of each bacterial genus, and column stands for different samples. The relative abundance for each bacterial genus were depicted by color intensity with the legend indicated at the under of the figure. The abbreviation of samples is shown in Table 1.

Mentions: To get an overall view on the identified connections among the studied samples, a hierarchically clustered heatmap was performed. The heatmap plot depicted the relative percentage of each bacterial family (variables clustering on the Y-axis) within each sample (X-axis clustering) (Figure 4). As shown in Figure 4, JBT60 and JBT70 libraries grouped firstly together, and then they clustered with SYT. Finally, these two groups gathered by decreasing order of similarity. The relative abundance for each bacterial genus was depicted by color intensity with the legend indicated in the figure below. In this study, the majority of sequences belonged to Euzebya (4.66%–12.26%) and Nitriliruptor (39.45%–32.64%) were present in the two clean soils, whereas it was absent in long-term polluted soils. Sequence belonging to Chloracidobacterium, Arthrobacter, Nocardioides, Sphingomonas and Nocardioides were the most dominant bacterial genuses in the SYT sample but were rarely in the other soils. The bacterial genus Agromyces, Mycobacterium, Bryobacter, Anaerolineaceae, Phenylobacterium and Cellulomonas were only found in the JBT70 with relatively higher abundance but was rarely or not detected in the others. While in JBY60 sample, the dominant genera were distributed among Gemmatimonadaceae, Pirellula, Nitrospiraceae, Lamia, and Planctomycetaceae. The proteobacterial sequences belonged to different genera in the three oil-contaminated soils, with no common genera. The majority of Proteobacteria belonged to the genus Rhodospirillaceae, Sinobacteraceae in JBT60 but belonged to Hydrocarboniphaga and Pseudomonas, Rhodococcus in JBT70 and SYT, respectively. The remaining abundant genera Streptomyces, Bacillus, Marmoricola, llumatobacter were detected in all samples. From the distribution of color, blue was mainly found in two control samples, indicating that oil-contaminated samples were enriched and highly diverse when to compare with the control samples. The results of the PCA and heatmap analyses were in agreement. Both the analysis indicated that the oil-contaminated soils and control samples had different characteristic bacterial communities.


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

Peng M, Zi X, Wang Q - Int J Environ Res Public Health (2015)

Hierarchically clustered heatmap of bacterial distribution of different communities from the five samples at the genus level. Row represents the relative percentage of each bacterial genus, and column stands for different samples. The relative abundance for each bacterial genus were depicted by color intensity with the legend indicated at the under of the figure. The abbreviation of samples is shown in Table 1.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4626951&req=5

ijerph-12-12002-f004: Hierarchically clustered heatmap of bacterial distribution of different communities from the five samples at the genus level. Row represents the relative percentage of each bacterial genus, and column stands for different samples. The relative abundance for each bacterial genus were depicted by color intensity with the legend indicated at the under of the figure. The abbreviation of samples is shown in Table 1.
Mentions: To get an overall view on the identified connections among the studied samples, a hierarchically clustered heatmap was performed. The heatmap plot depicted the relative percentage of each bacterial family (variables clustering on the Y-axis) within each sample (X-axis clustering) (Figure 4). As shown in Figure 4, JBT60 and JBT70 libraries grouped firstly together, and then they clustered with SYT. Finally, these two groups gathered by decreasing order of similarity. The relative abundance for each bacterial genus was depicted by color intensity with the legend indicated in the figure below. In this study, the majority of sequences belonged to Euzebya (4.66%–12.26%) and Nitriliruptor (39.45%–32.64%) were present in the two clean soils, whereas it was absent in long-term polluted soils. Sequence belonging to Chloracidobacterium, Arthrobacter, Nocardioides, Sphingomonas and Nocardioides were the most dominant bacterial genuses in the SYT sample but were rarely in the other soils. The bacterial genus Agromyces, Mycobacterium, Bryobacter, Anaerolineaceae, Phenylobacterium and Cellulomonas were only found in the JBT70 with relatively higher abundance but was rarely or not detected in the others. While in JBY60 sample, the dominant genera were distributed among Gemmatimonadaceae, Pirellula, Nitrospiraceae, Lamia, and Planctomycetaceae. The proteobacterial sequences belonged to different genera in the three oil-contaminated soils, with no common genera. The majority of Proteobacteria belonged to the genus Rhodospirillaceae, Sinobacteraceae in JBT60 but belonged to Hydrocarboniphaga and Pseudomonas, Rhodococcus in JBT70 and SYT, respectively. The remaining abundant genera Streptomyces, Bacillus, Marmoricola, llumatobacter were detected in all samples. From the distribution of color, blue was mainly found in two control samples, indicating that oil-contaminated samples were enriched and highly diverse when to compare with the control samples. The results of the PCA and heatmap analyses were in agreement. Both the analysis indicated that the oil-contaminated soils and control samples had different characteristic bacterial communities.

Bottom Line: The heatmap plot depicted the relative percentage of each bacterial family within each sample and clustered five samples into two groups.Redundancy analysis (RDA) indicated that organic matter was the highest determinant factor for explaining the variations in community compositions.These results provide some useful information for bioremediation of petroleum contaminated soil in the future.

View Article: PubMed Central - PubMed

Affiliation: College of Life Science, Northeast Forestry University, No.26 Hexing Street, Xiangfang District, Harbin 150040, China. huangxiaoming321@sina.com.

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.

No MeSH data available.


Related in: MedlinePlus