BiG-MEx

BiG-MEx identifies and analyzes biosynthetic gene clusters (BGCs) and their protein domains in metagenomic datasets to profile diversity, novelty, and abundance of natural product BGC classes.

Key Features:

• Ultrafast processing: Performs ultrafast identification of BGC protein domains in metagenomic data.
• Domain and class composition: Detects a wide array of BGC protein domains and characterizes domain and class composition.
• Diversity and novelty assessment: Evaluates the diversity and novelty of BGC protein domains.
• Abundance prediction: Predicts abundance profiles of natural product BGC classes in metagenomic samples.
• Chemical class coverage: Targets natural product classes including aminoglycosides, lantibiotics, nonribosomal peptides, oligosaccharides, polyketides, and terpenes.
• Scalability: Demonstrated on large metagenomic datasets such as TARA Oceans and the Human Microbiome Project.

Scientific Applications:

• Distribution and ecology: Studying the distribution, diversity, and ecological roles of BGCs across metagenomic datasets.
• Natural product discovery: Exploring and identifying natural products with potential clinical and industrial applications.
• Microbial ecology and biotechnology: Advancing research in microbial ecology and biotechnology by profiling BGC diversity and abundance.

Methodology:

Identification of BGC protein domains, evaluation of domain diversity and novelty, prediction of abundance profiles of BGC classes, and analysis of domain and class composition in metagenomic datasets.