Fig. 1

Computational approach to identify colorectal cancer metabolic passengers. a As inputs we used (i) CRC metabolites that were identified from metabolomics literature, (ii) genome-scale metabolic models, and (iii) a basal gut-like environment [66]. b Important metabolites for biomass production were defined as the ones that reduced growth if that metabolite was removed. The MI score was defined by comparing the list of important metabolites with the CRC metabolites. c Specific growth advantage was evaluated by supplementing the basal environment with the 26 CRC metabolites, and comparing this with the growth advantage on 1000 sets of 26 random metabolites. The SGA score was defined as the proportion of random sets where the growth advantage was lower than with the CRC metabolites (depicted in the distribution mass to the left of the red vertical line that indicates growth on the CRC metabolites). In the illustrated examples, the yellow bacteria is predicted to be a CRC passenger