Monitoring and molecular characterization of bacterial species in heavy metals contaminated roadside soil of selected region along NH 8A, Gujarat

Heliyon

卷:7

R.Y. Hiranmai¹  Snigdha Singh² 

[1] School of Environment and Sustainable Development, Central University of Gujarat, Gandhinagar, Gujarat, 382030, India;

[2] Corresponding author.;

关键词: Microbial diversity;    Heavy metal pollution;    16S-rRNA sequencing;    Phylogenetic tree;   

DOI  :  

来源: DOAJ

【 摘 要 】

Heavy metal contamination is a universal concern due to health risks associated with metal pollution. Soil contamination by heavy metals is known to affect microbial activities at elevated concentrations adversely. However, indigenous soil bacterial populations' response to added heavy metal and metal combinations is poorly understood. Microbes prevailing in the soil are the driving factors. Their properties are recognized as sensitive indicators of soil quality and health. Moreover, these microscopic organisms are accountable for the fertility and aeration of the soil that forms fundamental aspects of soil function. The current study was performed to explore the diversity of bacterial species in heavy metal polluted roadside soil. The roadside soil samples were collected from diverse sites and processed for physicochemical properties, microbial characterization, and heavy metals distribution in the selected locations. Serial dilution and spread plate techniques were used for the isolation of bacterial species. The 16S-rRNA gene sequencing identified bacterial species in roadside soil as Bacillus drentensis (MK217088), Bacillus safensis (MK774729), Bacillus haynesii (MK192808), Bacillus subtilis (MK217089), and Bacillus cereus (MK801278). In addition, the 16S rRNA sequences of isolated bacterial strains were aligned to generate a phylogenetic tree. Thus, the current research study provides a platform for efficiently investigating roadside soils by microbial profiling that may discover novel microbes of scientific significance and improved potential.

【 授权许可】

Unknown