Statistical learning of bacterial growth in combinatorially constructed environments
By employing a full factorial design to map carbon source interactions across seven bacterial species, this study demonstrates that while individual nutrients can exhibit context-dependent negative effects due to global epistasis, bacterial growth in complex environments is predominantly driven by additive and pairwise effects, enabling accurate prediction and rational optimization of growth conditions through simple statistical models.