ArticlePLoS computational biology2020
Providing new insights on the biphasic lifestyle of the predatory bacterium Bdellovibrio bacteriovorus through genome-scale metabolic modeling.
Article in PLoS computational biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Comprehensive and comparative genomic analysis of a novel strain, Peredibacter starrii HCB2-198, to identify features of the genus.BMC microbiology · 2026Article
- Predatory potentials of novel3 Biotech · 2025Article
- Using AlphaFold-Multimer to study novel protein-protein interactions of predation essential hypothetical proteins inFrontiers in bioinformatics · 2025Article
- Bdellovibrio's prey-independent lifestyle is fueled by amino acids as a carbon source.Applied microbiology and biotechnology · 2024Article
- Controlling the expression of heterologous genes in Bdellovibrio bacteriovorus using synthetic biology strategies.Microbial biotechnology · 2024Article
- Identification and cultivation of anaerobic bacterial scavengers of dead cells.The ISME journal · 2023Article
- Two-state swimming: Strategy and survival of a model bacterial predator in response to environmental cues.Biophysical journal · 2023Article
- Underexplored bacteria as reservoirs of novel antimicrobial lipopeptides.Frontiers in chemistry · 2022Review
- Adaptive lifestyle of bacteria determines phage-bacteria interaction.Frontiers in microbiology · 2022Article
- Chromosome choreography during the non-binary cell cycle of a predatory bacterium.Current biology : CB · 2021Article
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Authors and funding
4 authors.
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Abstract
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.
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