Human gut metagenomics study offers new insight for understanding the microbial communities residing in the gastrointestinal tract. Genome-Scale Metabolic Models (GEMs) are one of the potent tools for predicting the metabolic reactions among microbial communities. Developed from the traditional GEMs, enzyme constraints GEMs (ecGEMs) consider enzyme usage in the models as enzymes catalyze ability also plays important roles in metabolites reactions. Although the ecGEMs have alreadv been used in several studies for better dissecting the microbial metabolites pathways, still lack of the automatic pipeline to directly generate and analyse ecGEMs from the metagenomics raw data. In our previous project, we have developed the ENCORE, an end-to-end pipeline for reconstructing ecGEM from metagenomics sequencing data. In this project, we are going to apply the ENCORE pipeline to a liver cirrhosis cohort. We are going to compare the key metabolism alternations and key species across different stages of the liver cirrhosis. This would hopefully reveal the underlying disease mechanism and find out some potential biomarkers.