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<p>Community structure of bacteria present in arsenic contaminated agricultural soil was studied with qPCR (quantitative PCR) and DGGE (Denaturing Gradient Gel Electrophoresis) as an indicator of extreme stresses. Copy number of six common bacterial taxa (<italic>Acidobacteria</italic>, <italic>Actinobacteria</italic>, <italic>α-, β-</italic> and <italic>γ-Proteobacteria</italic>, <italic>Firmicutes</italic>) was calculated using group specific primers of 16S rDNA. It revealed that soil contaminated with low concentration of arsenic was dominated by both <italic>Actinobacteria</italic> and <italic>Proteobacteria</italic> but a shift towards <italic>Proteo bacteria</italic> was observed with increasing arsenic concentration, and number of <italic>Actinobacteria</italic> eventually decreases. PCA (Principle Component Analysis) plot of bacterial community composition indicated a distinct resemblance among high arsenic content samples, while low arsenic content samples remained separated from others. Cluster analysis of soil parameters identifies three clusters, each of them was related to the arsenic content. Further, cluster analysis of 16S rDNA based DGGE fingerprint markedly distributed the soil bacterial populations into low (&lt; 10 ppm) and high (> 10 ppm) arsenic content subgroups. Following analysis of diversity indices shows significant variation in bacterial community structure. MDS (Multi Dimensional Scaling) plot revealed distinction in the distribution of each sample denoting variation in bacterial diversity. Phylogenetic sequence analysis of fragments excised from DGGE gel revealed the presence of <italic>γ-Proteobacteria</italic> group across the study sites. Collectively, our experiments indicated that gradient of arsenic contamination affected the shape of the soil bacterial population by significant structural shift.</p>
</abstract>

Community structure of bacteria present in arsenic contaminated agricultural soil was studied with qPCR (quantitative PCR) and DGGE (Denaturing Gradient Gel Electrophoresis) as an indicator of extreme stresses. Copy number of six common bacterial taxa (Acidobacteria, Actinobacteria, α-, β- and γ-Proteobacteria, Firmicutes) was calculated using group specific primers of 16S rDNA. It revealed that soil contaminated with low concentration of arsenic was dominated by both Actinobacteria and Proteobacteria but a shift towards Proteo bacteria was observed with increasing arsenic concentration, and number of Actinobacteria eventually decreases. PCA (Principle Component Analysis) plot of bacterial community composition indicated a distinct resemblance among high arsenic content samples, while low arsenic content samples remained separated from others. Cluster analysis of soil parameters identifies three clusters, each of them was related to the arsenic content. Further, cluster analysis of 16S rDNA based DGGE fingerprint markedly distributed the soil bacterial populations into low (< 10 ppm) and high (> 10 ppm) arsenic content subgroups. Following analysis of diversity indices shows significant variation in bacterial community structure. MDS (Multi Dimensional Scaling) plot revealed distinction in the distribution of each sample denoting variation in bacterial diversity. Phylogenetic sequence analysis of fragments excised from DGGE gel revealed the presence of γ-Proteobacteria group across the study sites. Collectively, our experiments indicated that gradient of arsenic contamination affected the shape of the soil bacterial population by significant structural shift.

Molecular Study of Indigenous Bacterial Community Composition on Exposure to Soil Arsenic Concentration Gradient

Polish Journal of Microbiology

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Community structure of bacteria present in arsenic contaminated agricultural soil was studied with qPCR (quantitative PCR) and DGGE (Denaturing Gradient Gel Electrophoresis) as an indicator of extreme stresses. Copy number of six common bacterial taxa (Acidobacteria, Actinobacteria, α-, β- and γ-Proteobacteria, Firmicutes) was calculated using group specific primers of 16S rDNA. It revealed that soil contaminated with low concentration of arsenic was dominated by both Actinobacteria and Proteobacteria but a shift towards Proteo bacteria was observed with increasing arsenic concentration, and number of Actinobacteria eventually decreases. PCA (Principle Component Analysis) plot of bacterial community composition indicated a distinct resemblance among high arsenic content samples, while low arsenic content samples remained separated from others. Cluster analysis of soil parameters identifies three clusters, each of them was related to the arsenic content. Further, cluster analysis of 16S rDNA based DGGE fingerprint markedly distributed the soil bacterial populations into low ( 10 ppm) arsenic content subgroups. Following analysis of diversity indices shows significant variation in bacterial community structure. MDS (Multi Dimensional Scaling) plot revealed distinction in the distribution of each sample denoting variation in bacterial diversity. Phylogenetic sequence analysis of fragments excised from DGGE gel revealed the presence of γ-Proteobacteria group across the study sites. Collectively, our experiments indicated that gradient of arsenic contamination affected the shape of the soil bacterial population by significant structural shift.

Community structure of bacteria present in arsenic contaminated agricultural soil was studied with qPCR (quantitative PCR) and DGGE (Denaturing Gradient Gel...

Molecular Study of Indigenous Bacterial Community Composition on Exposure to Soil Arsenic Concentration Gradient

Online veröffentlicht: 28. Juni 2017

Seitenbereich: 209 - 221

Eingereicht: 13. Apr. 2016

Akzeptiert: 30. Sept. 2016

DOI: https://doi.org/10.5604/pjm-2017-209

Schlüsselwörter
agricultural fields, arsenic (As), bacterial community, DGGE, copy number, qPCR

© 2017 SEMANTI BASU et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Molecular Study of Indigenous Bacterial Community Composition on Exposure to Soil Arsenic Concentration Gradient

Online veröffentlicht: 28. Juni 2017

Seitenbereich: 209 - 221

Eingereicht: 13. Apr. 2016

Akzeptiert: 30. Sept. 2016

DOI: https://doi.org/10.5604/pjm-2017-209

Schlüsselwörteragricultural fields, arsenic (As), bacterial community, DGGE, copy number, qPCR

© 2017 SEMANTI BASU et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Schlüsselwörter
agricultural fields, arsenic (As), bacterial community, DGGE, copy number, qPCR