A curated genome-scale metabolic model of Bordetella pertussis metabolism

Area of Science:

• Microbiology
• Systems Biology
• Metabolic Engineering

Background:

• Bordetella pertussis causes whooping cough, necessitating large-scale cultivation for vaccine production.
• Current B. pertussis cultivation is hampered by slow growth, low yields, and expensive media.
• Accurate metabolic models are crucial for optimizing bacterial growth and production.

Purpose of the Study:

• To develop and validate a curated metabolic model for B. pertussis.
• To improve the understanding of B. pertussis metabolism for enhanced cultivation.
• To provide a predictive tool for optimizing growth conditions and vaccine production.

Main Methods:

• Flux balance analysis (FBA) was employed to construct the metabolic model.
• The model was enhanced with an experimentally-determined biomass objective function and extensive manual curation.
• Genome-wide essential gene screening using transposon-directed insertional sequencing (TraDIS) was performed.
• Model predictions were validated against experimental growth data on various carbon sources.

Main Results:

• The curated metabolic model achieved 83% accuracy in predicting essential genes.
• The model successfully predicted growth improvements under specific nutrient conditions (glutamate:fumarate ratio).
• Experimental validation confirmed model predictions for gene essentiality and growth characteristics.

Conclusions:

• The developed FBA model provides a valuable tool for understanding and optimizing B. pertussis metabolism.
• This model can guide strategies for improving bacterial cultivation efficiency for vaccine production.
• The model and its predictions are provided in SBML format for broader research use.