Exploring the bacterial genetic diversity and community structure of crude oil contaminated soils using microbiomics

The impact of environmental pollution in air and water is reflected mainly in the soil ecosystem as it impairs soil functions. Also, since the soil is the habitat for billions of organisms, the biodiversity is in turn altered. Microbes are precise sensors of ecological contamination, and bacteria ha...

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Veröffentlicht in:Environmental research 2023-11, Vol.236 (Pt 2), p.116779-116779, Article 116779
Hauptverfasser: Veerasamy, Veeramani, Jagannathan, Uma Maheswari, Arakkala, Sherry Davis, Shafee, Wasim Akthar, Kaliannan, Thamaraiselvi
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container_end_page 116779
container_issue Pt 2
container_start_page 116779
container_title Environmental research
container_volume 236
creator Veerasamy, Veeramani
Jagannathan, Uma Maheswari
Arakkala, Sherry Davis
Shafee, Wasim Akthar
Kaliannan, Thamaraiselvi
description The impact of environmental pollution in air and water is reflected mainly in the soil ecosystem as it impairs soil functions. Also, since the soil is the habitat for billions of organisms, the biodiversity is in turn altered. Microbes are precise sensors of ecological contamination, and bacteria have a key and important function in terms of bioremediation of the contaminated soil. Hence in the current work, we aimed at assessing the unidentified bacterial population through Illumina MiSeq sequencing technology and their community structural changes in different levels of petroleum-contaminated soil and sludge samples (aged, sludge, and leakage soil) to identify unique bacteria for their potential application in remediation. The studies showed that major bacterial consortiums namely, Proteobacteria (57%), Alphaproteobacteria (31%), and Moraxellaceae (23%) were present in aged soil, whereas Proteobacteria (52%), Alphaproteobacteria (33%), and Rhodobacteraceae (28%) were dominantly found in sludge soil. In leakage soil, Proteobacteria (59%), Alphaproteobacteria (33%), and Rhodobacteraceae (29%) were abundantly present. The Venn diagrams are used to analyze the distribution of abundances in individual operational taxonomic units (OTUs) within three soil samples. After data filtering, they were grouped into OTU clusters and 329 OTUs were identified from the three soil samples. Among the 329, 160 OTUs were common in the three soil samples. The bacterial diversity is estimated using alpha diversity indices and Shanon index and was found to be 4.490, 4.073 and 4.631 in aged soil, sludge soil and leakage soil, respectively and similarly richness was found to be 618, 417 and 418. The heat map was generated by QIIME software and from the top 50 enriched genera few microbes such as Pseudomonas, Bacillus, Mycobacterium, Sphingomonas and Paracoccus, were shown across all the samples. In addition, we also analyzed various physicochemical properties of soil including pH, temperature, salinity, electrical conductivity, alkalinity, total carbon, total organic matter, nitrogen, phosphorus and potassium to calculate the soil quality index (SQI). The SQI of aged, sludge and leakage soil samples were 0.73, 0.64, and 0.89, respectively. These findings show the presence of unexplored bacterial species which could be applied for hydrocarbon remediation and further they can be exploited for the same. •Soil consists of a diverse group of microorganisms which maintain plant and soil
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In leakage soil, Proteobacteria (59%), Alphaproteobacteria (33%), and Rhodobacteraceae (29%) were abundantly present. The Venn diagrams are used to analyze the distribution of abundances in individual operational taxonomic units (OTUs) within three soil samples. After data filtering, they were grouped into OTU clusters and 329 OTUs were identified from the three soil samples. Among the 329, 160 OTUs were common in the three soil samples. The bacterial diversity is estimated using alpha diversity indices and Shanon index and was found to be 4.490, 4.073 and 4.631 in aged soil, sludge soil and leakage soil, respectively and similarly richness was found to be 618, 417 and 418. The heat map was generated by QIIME software and from the top 50 enriched genera few microbes such as Pseudomonas, Bacillus, Mycobacterium, Sphingomonas and Paracoccus, were shown across all the samples. In addition, we also analyzed various physicochemical properties of soil including pH, temperature, salinity, electrical conductivity, alkalinity, total carbon, total organic matter, nitrogen, phosphorus and potassium to calculate the soil quality index (SQI). The SQI of aged, sludge and leakage soil samples were 0.73, 0.64, and 0.89, respectively. 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In leakage soil, Proteobacteria (59%), Alphaproteobacteria (33%), and Rhodobacteraceae (29%) were abundantly present. The Venn diagrams are used to analyze the distribution of abundances in individual operational taxonomic units (OTUs) within three soil samples. After data filtering, they were grouped into OTU clusters and 329 OTUs were identified from the three soil samples. Among the 329, 160 OTUs were common in the three soil samples. The bacterial diversity is estimated using alpha diversity indices and Shanon index and was found to be 4.490, 4.073 and 4.631 in aged soil, sludge soil and leakage soil, respectively and similarly richness was found to be 618, 417 and 418. The heat map was generated by QIIME software and from the top 50 enriched genera few microbes such as Pseudomonas, Bacillus, Mycobacterium, Sphingomonas and Paracoccus, were shown across all the samples. 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subjects Bacterial consortium
Biodegradation
Metagenomics
Principle component analysis
Soil quality index
title Exploring the bacterial genetic diversity and community structure of crude oil contaminated soils using microbiomics
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