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Designing Knowledge-Based Bioremediation Strategies Using Metagenomics

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Metagenomic Data Analysis

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2649))

Abstract

Functional capacities for bioremediation are governed by metabolic mechanisms of inhabiting microbial communities at polluted niches. Process fluctuations lead to stress scenarios where microbes evolve continuously to adapt to sustain the harsh conditions. The biological wastewater treatment (WWT) process harbors the potential of these catabolic microbes for the degradation of organic molecules. In a typical biological WWT or soil bioremediation process, several microbial species coexist which code for enzymes that degrade complex compounds.

High throughput DNA sequencing techniques for microbiome analysis in bioremediation processes have led to a powerful paradigm revealing the significance of metabolic functions and microbial diversity. The present chapter describes techniques in taxonomy and functional gene analysis for understanding bioremediation potential and novel strategies built on in silico analysis for the improvisation of existing aerobic wastewater treatment methods. Methods explaining comparative metagenomics by Metagenome Analysis server (MG-RAST) are described with successful case studies by focusing on industrial wastewaters and soil bioremediation studies.

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Acknowledgments

The manuscript has been checked for plagiarism at an institute using iThenticate (Anti-Plagiarism Software) and granted the article reference number: CSIR-NEERI/KRC/2021/AUG/EBGD/2.

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Authors and Affiliations

  1. Ashoka Trust for Research in Ecology and the Environment, Royal Enclave, Bengaluru, India

    Niti B. Jadeja

  2. Environmental Biotechnology and Genomics Division, National Environmental Engineering Research Institute (CSIR-NEERI), Nagpur, India

    Atya Kapley

Authors
  1. Niti B. Jadeja
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  2. Atya Kapley
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Corresponding author

Correspondence to Atya Kapley .

Editor information

Editors and Affiliations

  1. Leeds Institute of Medical Research, University of Leeds, Leeds, UK

    Suparna Mitra

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© 2023 The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature

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Jadeja, N.B., Kapley, A. (2023). Designing Knowledge-Based Bioremediation Strategies Using Metagenomics. In: Mitra, S. (eds) Metagenomic Data Analysis. Methods in Molecular Biology, vol 2649. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-3072-3_9

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  • DOI: https://doi.org/10.1007/978-1-0716-3072-3_9

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-3071-6

  • Online ISBN: 978-1-0716-3072-3

  • eBook Packages: Springer Protocols

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