DRAM

DRAM annotates metabolic functions in microbial and viral genomes to assign metabolic traits and identify auxiliary metabolic genes (AMGs) for ecological and functional analysis of microbiomes.

Key Features:

• Scalable Annotation Framework: Provides metabolically resolved, scalable annotation for large and complex microbiome genomic datasets.
• Microbial Trait Cataloging: Generates a comprehensive catalog of microbial traits from genomic sequences to facilitate analysis of roles in geochemical cycles.
• Automated Metabolic Partitioning: Automates partitioning of metabolic processes at substrate levels, exemplified by analysis of gut microbial carbohydrate metabolism.
• Applicability Across Diverse Genomes: Validated on an in silico soil community and previously published human gut metagenomes, demonstrating cross-environment robustness.
• Viral Mode (DRAM-v): Implements rules to identify virally-encoded auxiliary metabolic genes (AMGs) and metabolically categorize thousands of putative AMGs from soil and gut environments.

Scientific Applications:

• Microbial Contribution Analysis: Assigns microbial contributions to geochemical cycles based on genomic metabolic annotation.
• Metabolic Profiling: Deciphers metabolic pathways and enzyme activities to profile microbiome function in environmental and human health contexts.
• Viral Metabolism Insights: Identifies and categorizes AMGs to reveal viral influences on host metabolism and virus–host interactions.

Methodology:

DRAM integrates genomic data with known biochemical pathways and leverages computational algorithms to predict enzyme activities and metabolic roles; DRAM-v applies rule-based identification of virally-encoded AMGs.