IMG-ABC

IMG-ABC catalogs predicted and experimentally validated biosynthetic gene clusters (BGCs) to enable systematic exploration and discovery of microbial secondary metabolites.

Key Features:

• Comprehensive Database: Integrates predicted and experimentally validated BGCs to provide an extensive repository of microbial biosynthetic data.
• Updated Prediction Pipeline: Incorporates antiSMASH v5 in the prediction pipeline to improve BGC detection accuracy and diversity.
• Environmental Metadata Integration: Links BGC entries with environmental metadata from GOLD to provide ecological context for microbial samples.

Scientific Applications:

• Secondary Metabolism Research: Supports investigation of microbial secondary metabolism through access to large-scale BGC data.
• Natural Product Discovery: Facilitates bioprospecting and discovery of novel natural products with potential applications in medicine, agriculture, and industry.
• Ecological Context Analysis: Enables study of how environmental factors correlate with presence and distribution of BGCs using GOLD metadata.

Methodology:

Uses high-throughput genome sequencing of isolated organisms and metagenomic samples, applies specialized computational workflows for BGC identification and characterization, and integrates antiSMASH v5 in the prediction pipeline.