Oral and gut microbial carbohydrate-active enzymes landscape in health and disease

Inter-individual variability in the microbial gene complement encoding for carbohydrate-active enzymes (CAZymes) can profoundly regulate how the host interacts with diverse carbohydrate sources thereby influencing host health. CAZy-typing, characterizing the microbiota-associated CAZyme-coding genes within a host individual, can be a useful tool to predict carbohydrate pools that the host can metabolize, or identify which CAZyme families are underrepresented requiring supplementation via microbiota transplantation or probiotics. CAZy-typing, moreover, provides a novel framework to search for disease biomarkers. As a proof of concept, we used publicly available metagenomes (935) representing 310 type strain bacterial genomes to establish the link between disease status and CAZymes in the oral and gut microbial ecosystem. The abundance and distribution of 220 recovered CAZyme families in saliva and stool samples from patients with colorectal cancer, rheumatoid arthritis, and type 1 diabetes were compared with healthy subjects. Based on the multivariate discriminant analysis, the disease phenotype did not alter the CAZyme profile suggesting a functional conservation in carbohydrate metabolism in a disease state. When disease and healthy CAZyme profiles were contrasted in differential analysis, CAZyme markers that were underrepresented in type 1 diabetes (15), colorectal cancer (12), and rheumatoid arthritis (5) were identified. Of interest, are the glycosyltransferase which can catalyze the synthesis of glycoconjugates including lipopolysaccharides with the potential to trigger inflammation, a common feature in many diseases. Our analysis has also confirmed the expansive carbohydrate metabolism in the gut as evidenced by the overrepresentation of CAZyme families in the gut compared to the oral site. Nevertheless, each site exhibited specific CAZyme markers. Taken together, our analysis provides an insight into the CAZyme landscape in health and disease and has demonstrated the diversity in carbohydrate metabolism in host-microbiota which can be a sound basis for optimizing the selection of pre, pro, and syn-biotic candidate products