Fyson Nick, King Jerry, Belcher Thomas, Preston Andrew, Colijn Caroline
Department of Mathematics, Imperial College, London, UK.
The Milner Centre for Evolution and Department of Biology and Biochemistry, University of Bath, Bath, UK.
PLoS Comput Biol. 2017 Jul 17;13(7):e1005639. doi: 10.1371/journal.pcbi.1005639. eCollection 2017 Jul.
The Gram-negative bacterium Bordetella pertussis is the causative agent of whooping cough, a serious respiratory infection causing hundreds of thousands of deaths annually worldwide. There are effective vaccines, but their production requires growing large quantities of B. pertussis. Unfortunately, B. pertussis has relatively slow growth in culture, with low biomass yields and variable growth characteristics. B. pertussis also requires a relatively expensive growth medium. We present a new, curated flux balance analysis-based model of B. pertussis metabolism. We enhance the model with an experimentally-determined biomass objective function, and we perform extensive manual curation. We test the model's predictions with a genome-wide screen for essential genes using a transposon-directed insertional sequencing (TraDIS) approach. We test its predictions of growth for different carbon sources in the medium. The model predicts essentiality with an accuracy of 83% and correctly predicts improvements in growth under increased glutamate:fumarate ratios. We provide the model in SBML format, along with gene essentiality predictions.
革兰氏阴性菌百日咳博德特氏菌是百日咳的病原体，百日咳是一种严重的呼吸道感染疾病，每年在全球导致数十万人死亡。虽然有有效的疫苗，但疫苗生产需要大量培养百日咳博德特氏菌。不幸的是，百日咳博德特氏菌在培养基中的生长相对缓慢，生物量产量低且生长特性多变。百日咳博德特氏菌还需要相对昂贵的生长培养基。我们提出了一种基于通量平衡分析的新型百日咳博德特氏菌代谢优化模型。我们通过实验确定的生物量目标函数对模型进行了优化，并进行了广泛的人工校正。我们使用转座子定向插入测序（TraDIS）方法通过全基因组必需基因筛选来测试模型的预测。我们测试了模型对培养基中不同碳源生长情况的预测。该模型预测必需性的准确率为83%，并正确预测了谷氨酸：富马酸比率增加时生长的改善情况。我们以SBML格式提供该模型以及基因必需性预测结果。
