Providing new insights on the biphasic lifestyle of the predatory bacterium Bdellovibrio bacteriovorus through genome-scale metabolic modeling.

In this study we analyze the growth-phase dependent metabolic states of Bdellovibrio bacteriovorus by constructing a fully compartmented, mass and charge-balanced genome-scale metabolic model of this predatory bacterium (iCH457). Considering the differences between life cycle phases driving the growth of this predator, growth-phase condition-specific models have been generated allowing the systematic study of its metabolic capabilities. Using these computational tools, we have been able to analyze, from a system level, the dynamic metabolism of the predatory bacteria as the life cycle progresses. We provide computational evidences supporting potential axenic growth of B. bacteriovorus’s in a rich medium based on its encoded metabolic capabilities. Our systems-level analysis confirms the presence of “energy-saving” mechanisms in this predator as well as an abrupt metabolic shift between the attack and intraperiplasmic growth phases. Our results strongly suggest that predatory bacteria’s metabolic networks have low robustness, likely hampering their ability to tackle drastic environmental fluctuations, thus being confined to stable and predictable habitats. Overall, we present here a valuable computational testbed based on predatory bacteria activity for rational design of novel and controlled biocatalysts in biotechnological/clinical applications.