The molecular study of microbial and functional diversity of resistant microbes in heavy metal contaminated soil

Environmental Technology & Innovation(2020)

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摘要
The operations of biological systems are challenged by various environmental factors that interrupt biological processes. Accurate identification and predictive models can serve as useful tools for distinguishing microbes and understanding key organisms and their roles. This study was aimed at evaluating the microbial abundance/diversities (bacteria and fungi) present in contaminated soil using molecular approaches. The soil samples were artificially contaminated with heavy metal salts of nickel (25, 50, 75 mg/kg); chromium (50, 100, 150 mg/kg); lead (150, 300, 450 mg/kg) and cadmium (1.5, 3.0, 4.5 mg/kg). Pure culture of bacteria and fungi were identified using 16S rRNA gene sequence analysis for bacteria community and the Internal Transcribed Spacer (ITS) gene for fungi. The results show that the physicochemical properties of the soil reduced significantly at the end of the experiment (p<0.05). The microbial loads were low at the initial day 1 compared to the day 60 but only significant for Bacterial in Pb (300 and 450 mg/kg) and Cd (3 mg/kg) soils. Gene sequence analysis of the microbe revealed seven species of bacteria and four fungi species. Fungi had higher GC contents than bacteria in the contaminated soil suggesting their higher stability to pollution. Phylogenetic analysis revealed that the contaminated soil harboured a phylogenetically diverse bacterial population compared to fungi which were more clustered together. Predicted genes and protein show that the microbes have remarkable metabolic diversities. Some of the predicted protein sequences obtained in this study represent novel phylotypes indicating the possibility of discovery of bacteria and fungi with important new biomolecules. Metal-utilizing microbial sequences were predicted which imply a possible role for metal oxidation, reduction and remediation potential.
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关键词
Bacterial,Fungi,Diversity,Heavy metal,Phylogenetic analysis,Functional prediction
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