Microbial Genes Involved in the Aromatic Compound Degradation Deciphered Through Metagenomics Analysis of Industrial Wastewater.

Abstract

Background: Understanding microbial and functional diversity from different stages of common effluent treatment plant (CETP) plays an important role to enhance the treatment performs of wastewater systems. However, unraveling microbial interactions as well as utilization of substrate involved in complex microbial communities is a challenging task. Hence, we demonstrate an integrated approach of shotgun metagenomics and whole genome sequencing to identify the microbial diversity and genes involved in degradation of benzoate, 1,2-dichloroethane and phenylalanine metabolism and degradation pathways from CETP microbiome.Results: The taxonomy profile was annotated using the Ribosomal Database Project (RDP) database in the MG-RAST server. The results showed that, bacteria accounted for 98.46% was the most abundant domain, followed by Eukaryota (0.10%) and Archea 0.02%. At Phylum level, Proteobacteria (28.8%) were dominant, followed by Bacteroidetes (16.1%), Firmicutes (11.7%) and Fusobacteria (6.9%). The most dominated species were Klebsiella pneumoniae, Wolinella succinogenes, Pseudomonas stutzeri, Desulfovibris vulgaris, Clostridium sticklandii, and Escherichia coli. The Clusters of Orthologous Groups (COGs) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, revealed the presence of the genes responsible for the metabolism and degradation of aromatic compounds. This information was validated with the whole genome analysis of the bacteria isolated from the CETP.Conclusion: The two type of integrated meta omics analyses revealed that the metabolic and degradation capability at both community wide and individual bacterial levels. In addition, we demonstrated that microbial diversity changes with the treatment process in which inlet of CETP effluent shows higher dominancy of Proteobacteria whereas in textile industry outlet the high abundance of Firmicutes was observed. We foresee this approach would contribute in designing the bioremediation strategies for the industrial treatment process.