对微生物联盟的基因组规模约束型建模工具进行结构化评估.
William T Scott1,2, Sara Benito-Vaquerizo1, Johannes Zimmermann3
1Laboratory of Systems and Synthetic Biology, Wageningen University & Research, Wageningen, the Netherlands.
PLoS computational biology
|August 14, 2023
概括
本研究评估了基于约束的重建和分析 (COBRA) 工具,用于模拟微生物群落. 它评估软件质量和预测能力,为未来开发基因组规模代谢模型 (GEM) 工具提供建议.
科学领域:
- 计算生物学 计算生物学
- 微生物生态学 微生物生态学
- 系统生物学 系统生物学
背景情况:
- 微生物联盟在医疗保健,生物技术和环境修复方面至关重要.
- 了解微生物相互作用是利用联盟潜力的关键.
- 使用基因组规模代谢模型 (GEMs) 的基于约束的重建和分析 (COBRA) 是模拟微生物群落的最先进技术.
研究的目的:
- 系统地评估现有的基于COBRA的工具来模拟微生物群落.
- 评估软件质量 (FAIR原则) 和这些工具的预测能力.
- 引导用户选择合适的工具,并告知开发人员未来的改进.
主要方法:
- 基于FAIR特征的24个COBRA工具的定性评估.
- 对来自三个案例研究的实验数据进行14种工具的定量测试 (合成气发酵,葡萄糖/氧化糖发酵,彼得里盘共同培养).
- 基于数学公式和模拟场景 (静态,动态,时空) 的工具性能分析.
主要成果:
- 在评估的COBRA工具中,性能存在显著差异.
- 工具性能上的差异与它们的数学公式和模拟方法有关.
- 质量评估显示,在各种工具中,对FAIR原则的遵守程度各不相同.
结论:
- 没有单一的COBRA工具在所有模拟类型中脱而出; 工具的选择取决于具体的应用.
- 需要改进的COBRA工具,增强预测能力,并遵守软件质量标准.
- 提供了改进未来GEM微生物建模工具的建议,以提高准确性和可用性.
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