Paper Title
PREDICTION OF ENZYMES INVOLVED IN BIOREMEDIATION USING AQUATIC METAGENOMIC SEQUENCE FROM SEDIMENT SAMPLES OF RIVER GANGA

Abstract
Recent advancements in science and technology brings industrialization and along with it, pollution in several forms. Presence of pollutants has raised serious threats to human beings, animals, plant life, and also material resources, thereby reducing the quality of life in the environment (Ufarte´ et al., 2015). Land, air, water, soil, and so on have been contaminated and are rupturing the ecosystem. Most of these pollutants are formed by the persistent accumulation of harmful molecules (Kapley and Purohit, 2009). Although there are several proposed methods to tackle such pollutants in the environment, they have not been significantly successful (Hwang and Cutright, 2004; Brion and Pelletier, 2005).Conventional methods for remediation have their own limitations and shortcomings to deal with these environmental pollutants. Bio-based remediation techniques (Bioremediation) using microbes have gained momentum in the recent past, primarily ascribed to their eco-friendly approach. Bioremediation is considered to be one of the best ways to eliminate pollution from the environment. It is an eco-friendly method for pollutant management that utilizes the inherent potential of microorganisms such as bacteria, fungi, and algae to degrade the pollutants from the environment (Devarapalli and Kumavath, 2015). Microbial enzymes such as monooxygenases, dioxygenases, laccases, peroxidases, lipases, and so on are reported to be effective in removal of environmental pollutants. However, the need for novel enzymes with better efficiency is ever growing. Metagenomic approaches have thrown the doors wide open for large-scale screening of such pollutant degrading enzymes (PDEs). Over the traditional methods, where enzyme screening was carried out based on the cultivability of the bacteria, metagenomics provides an alternative to make the process highly robust and accurate. For the past few years, there has been an increasing interest in metagenomics-based mining of novel bioremediation enzymes. This study predicts the enzymes, involved in bioremediation using aquatic metagenomic sequence from sediment samples of river Ganga. Here, software tool like REMEDBis used to find out the bioremediating enzymes. These bioremediating enzymes can further multiplied and can be used for environmental cleanup.