metaGEM

metaGEM reconstructs genome-scale metabolic models (GEMs) from metagenomic short-read paired-end shotgun sequencing data and simulates community-level metabolic interactions to capture prokaryotic and intraspecies metabolic diversity.

Key Features:

• End-to-End Pipeline: Integrates bioinformatics tools using Snakemake to process raw metagenomic reads through metabolic model reconstruction.
• Metagenome Assembled Genomes (MAGs): Reconstructs MAGs from whole metagenome shotgun sequencing datasets to enable context-specific prokaryotic GEMs.
• Community-Level Simulations: Performs community metabolic interaction simulations, including flux balance analysis, to explore cross-feeding and metabolic exchanges.
• Diverse Applications: Applied to human gut microbiomes, plant-associated samples, soil, oceanic metagenomes, and laboratory cultures.
• Intraspecies Diversity Capture: Captures intraspecies metabolic variation by reconstructing GEMs directly from metagenomic data.
• Comprehensive Outputs: Produces abundance estimates, taxonomic assignments, growth rate estimations, pangenome analyses, and eukaryotic MAG identification.

Scientific Applications:

• Large-scale GEM Reconstruction: Enables reconstruction of over 14,000 prokaryotic GEMs from diverse metagenomic samples.
• Mechanistic Microbiome Hypotheses: Simulates community metabolic interactions to generate mechanistic hypotheses linking microbiome function to conditions such as type 2 diabetes.

Methodology:

Uses Snakemake workflows to process short-read paired-end data, reconstructs MAGs from metagenomic datasets, converts MAGs into GEMs for in silico simulations, and applies flux balance analysis to simulate community-level metabolic interactions.