Integrative Metagenomic Profiling
Resolving host-microbiome interactions in metabolic disease cohorts using shotgun metagenomics.
The Challenge
Gut microbiome analysis using traditional 16S rRNA sequencing lacks species-level and functional pathway resolution. Additionally, integrating high-dimensional microbiome taxonomic data with host RNA-seq transcriptomics is statistically challenging, often leading to false-positive correlations.
RASA's Technical Approach
RASA designed an integrative shotgun metagenomics workflow. We performed quality control with fastp, removed host reads using Hostile, and completed taxonomic profiling via MetaPhlAn4. Functional metabolic pathway profiling was handled using HUMAnN3. We assembled Metagenome-Assembled Genomes (MAGs) with MEGAHIT and binned them via MetaBAT2. Finally, we applied Canonical Correlation Analysis (CCA) and random forest classifiers to correlate microbial species abundance with host transcriptomic markers.
Results & Biological Insights
We successfully integrated 200+ shotgun metagenomic microbiome profiles with host mucosal transcriptomics. The study identified 14 novel metagenomic biomarkers and specific short-chain fatty acid (SCFA) producing bacterial strains directly correlated with insulin sensitivity pathways. These findings were published in a high-impact peer-reviewed journal and form the basis for a novel therapeutic metabolic program.