AUTHOR=Kumar Dinesh , Patel Zarna , Pandit Priti , Pandit Ramesh , Patel Amrutlal , Joshi Madhvi , Joshi Chaitanya TITLE=Textile Industry Wastewaters From Jetpur, Gujarat, India, Are Dominated by Shewanellaceae, Bacteroidaceae, and Pseudomonadaceae Harboring Genes Encoding Catalytic Enzymes for Textile Dye Degradation JOURNAL=Frontiers in Environmental Science VOLUME=9 YEAR=2021 URL=https://www.frontiersin.org/journals/environmental-science/articles/10.3389/fenvs.2021.720707 DOI=10.3389/fenvs.2021.720707 ISSN=2296-665X ABSTRACT=

Textile industries play an important role in uplifting the national economies worldwide. Nevertheless, they generate a huge amount of intensive colored effluent, which is a serious threat to the environment. The microbial communities present in these highly polluted environmental sites help in remediating pollutants naturally. However, little is known about their genes and enzymes in the textile wastewater systems. In this study, we explored the microbial community structure and their functional capability in three different wastewater systems, i.e., industry sites, effluent treatment plant (ETP), and common effluent treatment plant (CETP). Our findings based on shotgun metagenomics highlight the varied bacterial diversity at the three industry sites. Overall, the major dominant phyla in the industry site and CETP samples were Proteobacteria and Bacteroidetes, while in the ETP site, Firmicutes, Cyanobacteria, and Proteobacteria were predominant. The final discharge sample site was having a higher proportion of the Proteobacteria and Bacteroidetes. Aeromonas caviae, Desulfovibrio desulfuricans, Klebsiella pneumoniae, Pseudomonas stutzeri, Shewanella decolorationis, Shewanella oneidensis, Shewanella putrefaciens, and Vibrio cholera were the abundant species across the three sites. Furthermore, this research study identified the key microbial genes encoding enzymes having a known role in textile dye and aromatic compound degradation. Functional annotation of the shotgun metagenome samples indicates the presence of reductase, azoreductase, nitrate/nitrite reductase, and oxidoreductase enzyme encoding genes. Our findings provide the shotgun metagenomics-based approach for mining the textile dye degrading genes and genomic insights into the bioremediation of textile industrial effluent.