Environmental pollution has emerged to be a major hazard in today's world. Pollutants from varied sources cause harmful effects to the ecosystem. The major pollutants across marine and terrestrial regions are hydrocarbons, plastics, and dyes. Conventional methods for remediation have their own limitations and shortcomings to deal with these environmental pollutants. Bio-based remediation techniques using microbes have gained momentum in the recent past, primarily ascribed to their eco-friendly approach. The role of microbial enzymes in remediating the pollutants are well reported, and further exploration of microbial resources could lead to discovery of novel pollutant degrading enzymes (PDEs). Recent advances in next-generation sequencing technologies and metagenomics have provided the impetus to explore environmental microbes for potentially novel bioremediation enzymes. In this study, a tool, RemeDB, was developed for identifying bioremediation enzymes sequences from metagenomes. RemeDB aims at identifying hydrocarbon, dye, and plastic degrading enzymes from various metagenomic libraries. A sequence database consisting of >30,000 sequences proven to degrade the major pollutants was curated from various literature sources and this constituted the PDEs' database. Programs such as HMMER and RAPSearch were incorporated to scan across large metagenomic sequences libraries to identify PDEs. The tool was tested with metagenome data sets from varied sources and the outputs were validated. RemeDB was efficient to classify and identify the signature patterns of PDEs in the input data sets.

中文翻译：

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RemeDB：从高通量宏基因组数据集快速预测生物修复中涉及的酶的工具。

环境污染已成为当今世界的主要危害。来自不同来源的污染物会对生态系统造成有害影响。海洋和陆地区域的主要污染物是碳氢化合物、塑料和染料。传统的修复方法在处理这些环境污染物时有其自身的局限性和不足。使用微生物的基于生物的修复技术在最近获得了动力，这主要归功于它们的环保方法。微生物酶在修复污染物中的作用已得到充分报道，进一步探索微生物资源可能会发现新的污染物降解酶（PDEs）。新一代测序技术和宏基因组学的最新进展为探索环境微生物以寻找潜在的新型生物修复酶提供了动力。在这项研究中，开发了一种工具 RemeDB，用于从宏基因组中识别生物修复酶序列。RemeDB 旨在从各种宏基因组库中识别碳氢化合物、染料和塑料降解酶。由超过 30,000 个被证明可以降解主要污染物的序列组成的序列数据库是从各种文献来源中挑选出来的，这构成了 PDE 的数据库。整合了诸如 HMMER 和 RAPSearch 之类的程序来扫描大型宏基因组序列库以识别 PDE。该工具使用来自不同来源的宏基因组数据集进行了测试，并验证了输出。