BiG-MAP

BiG-MAP profiles the abundance and expression of biosynthetic gene clusters across metagenomic and metatranscriptomic datasets to evaluate microbial metabolic potential and functional roles in microbiomes.

Key Features:

• Profiling Gene Clusters: Quantifies abundance and expression levels of biosynthetic gene clusters across metagenomic and metatranscriptomic datasets.
• Differential Analysis: Performs differential abundance and differential expression analyses of gene clusters between sample groups or conditions.
• Hypothesis Generation: Identifies associations between gene cluster profiles and sample phenotypes to prioritize candidate clusters for follow-up.
• Cross-biome Application: Applicable to diverse microbiomes, including human, plant, animal, marine, and soil environments.

Scientific Applications:

• Human oral microbiome analysis: Identified 252 gene clusters with significant abundance differences between healthy and caries-associated samples, highlighted the muc operon and a putative reuterin biosynthetic gene cluster from a Streptococcus strain enriched in healthy samples, and linked findings to metabolomic evidence of (poly)acrolein, a compound known to inhibit Streptococcus mutans.
• Multi-omics comparative studies: Used to relate biosynthetic gene cluster profiles across metagenomes and metatranscriptomes to sample-associated phenotypes and metabolomic signals.

Methodology:

Integrates metagenomic and metatranscriptomic data to profile abundance and expression of biosynthetic gene clusters, performs differential abundance and expression analyses, and was validated using a mock community with support from metabolomic data in case studies.