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16S rRNA gene analysis has emerged as one of the valuable tools that are being utilized in investigating the molecular phylogenetic structure of the particular environment. Here, we embarked upon understanding and delineating the molecular phylogeny structure of microbes in polluted soil samples from cancer prone belt of the Punjab, India, which is highly contaminated with herbicide, pesticide and heavy metals. To investigate the bacterial phylogeny structure, a high-molecular weight metagenomic DNA was extracted from the soil samples, followed by PCR amplification, cloning and analysis of the 16S rRNA genes. Study employing 16S rRNA profiling of the community DNA revealed the presence of two major phylums: the Proteobacteria (26.7 %), the Bacteroidetes (11.2 %), and several minor groups, i.e., Acidobacteria (4.2 %), Actinobacteria (4.2 %), Firmicutes (2.8 %), Verrucomicrobia (2.8 %), Gemmatimonadetes (1.4 %) and Chloroflexi (1.4 %). Among the Proteobacteria, we mainly observed the α-Proteobacteria (18.3 %). Nearly, 38 % of the recovered 16S rRNA gene sequences in this study do not share similarity with known culturable bacterial sequences reported in the genebank data base and hence considered to be novel. More interestingly, 16S rRNA gene sequences of archaeal origin (7.0 %) were also recovered that primarily indicate change in their evolution pattern. A phylogenetic tree constructed based on alignment-dependent method revealed the extent of similarity these clones shared with each other, followed by alignment-independent methods that statistically confirmed the sequence variation among the clones. Despite the high level of contamination in the study area, we observed remarkable microbial diversity that mainly includes the Gram-negative bacteria. The presence of more Gram-negative bacteria indicates that they have evolved a robust mechanism to resist and cope up with these pollutants compared to Gram-positive groups. Investigation of the polluted soil samples employing culture-independent approach revealed important bacterial groups which could be engineered for future bioremediation studies.

Delineating bacterial community structure of polluted soil samples collected from cancer prone belt of Punjab, India