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Decoding microbial community intelligence through metagenomics for efficient wastewater treatment

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Abstract

Activated sludge, a microbial ecosystem at industrial wastewater treatment plants, is an active collection of diverse gene pool that creates the intelligence required for coexistence at the cost of pollutants. This study has analyzed one such ecosystem from a site treating wastewater pooled from over 200 different industries. The metagenomics approach used could predict the degradative pathways of more than 30 dominating molecules commonly found in wastewater. Results were extended to design a bioremediation strategy using 4-methylphenol, 2-chlorobenzoate, and 4-chlorobenzoate as target compounds. Catabolic potential required to degrade four aromatic families, namely benzoate family, PAH family, phenol family, and PCB family, was mapped. Results demonstrated a network of diverse genera, where a few phylotypes were seen to contain diverse catabolic capacities and were seen to be present in multiple networks. The study highlights the importance of looking more closely at the microbial community of activated sludge to harness its latent potential. Conventionally treated as a black box, the activated biomass does not perform at its full potential. Metagenomics allows a clearer insight into the complex pathways operating at the site and the detailed documentation of genes allows the activated biomass to be used as a bioresource.

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Acknowledgements

The authors are grateful to the Council of Scientific and Industrial Research, India, CSIR-network project ESC-0108-MESER, for supporting this research. Niti B Jadeja is grateful to CSIR for the Senior Research Fellowship. The authors also acknowledge Ankleshwar CETP authorities for providing activated sludge and wastewater samples used in this study. The manuscript has been checked for plagiarism at an institute, reference no. KRC No.: KRC/2016/MAY/EGD/1.

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  1. Environmental Biotechnology and Genomics Division, National Environmental Engineering Research Institute, CSIR-NEERI, Nehru Marg, Nagpur, 440020, India

    Niti B. Jadeja, Hemant J. Purohit & Atya Kapley

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  1. Niti B. Jadeja
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  2. Hemant J. Purohit
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  3. Atya Kapley
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Correspondence to Atya Kapley.

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Jadeja, N.B., Purohit, H.J. & Kapley, A. Decoding microbial community intelligence through metagenomics for efficient wastewater treatment. Funct Integr Genomics 19, 839–851 (2019). https://doi.org/10.1007/s10142-019-00681-4

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