AbstractBowel microbiota is a “metaorgan” of metabolisms on which quantitative readouts must be performed before interventions can be introduced and evaluated. The study of the effects of probiotic Clostridium butyricum MIYAIRI 588 (CBM588) on intestine transplantees indicated an increased percentage of the “other glycan degradation” pathway in 16S-rRNA-inferred metagenomes. To verify the prediction, a scoring system of carbohydrate metabolisms derived from shotgun metagenomes was developed using hidden Markov models. A significant correlation (R = 0.9, p < 0.015) between both modalities was demonstrated. An independent validation revealed a strong complementarity (R = −0.97, p < 0.002) between the scores and the abundance of “glycogen degradation” in bacteria communities. On applying the system to bacteria genomes, CBM588 had only 1 match and ranked higher than the other 8 bacteria evaluated. The gram-stain properties were significantly correlated to the scores (p < 5 × 10−4). The distributions of the scored protein domains indicated that CBM588 had a considerably higher (p < 10−5) proportion of carbohydrate-binding modules than other bacteria, which suggested the superior ability of CBM588 to access carbohydrates as a metabolic driver to the bowel microbiome. These results demonstrated the use of integrated counts of protein domains as a feasible readout for metabolic potential within bacteria genomes and human metagenomes.
Human platelet-derived growth factor. Purification and resolution into two active protein fractions.