RemeDB

RemeDB identifies pollutant-degrading enzyme sequences from high-throughput metagenomic datasets to support discovery of enzymes for bioremediation of hydrocarbons, plastics, and dyes.

Key Features:

• Database Integration: Uses a curated sequence database of over 30,000 Pollutant Degrading Enzymes (PDEs) compiled from literature sources.
• Advanced Algorithms: Employs HMMER and RAPSearch to scan large metagenomic libraries for signature patterns associated with PDEs.
• Validation and Efficiency: Has been tested on diverse metagenome datasets to classify and identify PDEs accurately.

Scientific Applications:

• Bioremediation enzyme discovery: Identification and cataloging of enzymes capable of degrading hydrocarbons, plastics, and dyes from environmental microbial communities.
• Metagenomic mining with next-generation sequencing: Analysis of NGS-derived metagenomes to uncover novel PDE sequences from environmental samples.

Methodology:

Curate a database of known PDE sequences (>30,000) and scan high-throughput metagenomic datasets with HMMER and RAPSearch to identify candidate pollutant-degrading enzyme sequences.