空间转录基因引导的多尺度框架将P. aeruginosa的代谢状态与氧化应激生物膜微环境连接起来
Tracy J Kuper1, Mohammad Mazharul Islam2, Shayn M Peirce-Cottler2
1Department of Chemical Engineering, University of Virginia, Charlottesville, Virginia, United States of America.
PLoS computational biology
|April 26, 2024
概括
一个新的计算框架,细胞系统中的新陈代谢多尺度模型 (MiMICS),集成了多omics数据,揭示了微生物生物膜如何在不同尺度上调节新陈代谢. 这种工具准确地预测了对氧化等环境因素的代谢异质性的反应.
科学领域:
- 微生物学 微生物学
- 计算生物学 计算生物学
- 系统生物学 系统生物学
背景情况:
- 空间解析的转录学为微生物生物膜代谢提供了洞察力.
- 需要计算工具来整合多学科数据,以了解生物膜异质性.
研究的目的:
- 介绍一个新的计算框架,细胞系统中的新陈代谢多尺度模型 (MiMICS).
- 将基因组规模的代谢网络重建 (GENREs) 与基于代理和反应扩散模型结合起来.
- 研究控制异质微生物生物膜代谢的多层次机制.
主要方法:
- 通过将GENREs与混合自动机库 (HAL) 集成,开发了MiMICS.
- 整合了多个-omics引导的代谢模型来表示独特的代谢状态.
- 模拟Pseudomonas aeruginosa在低氧和氧化 (NO) 生物膜微环境中的代谢,使用空间转录基因数据.
主要成果:
- 米米克斯预测了四个P. aeruginosaPA14代谢模型状态的明显的氧气,酸盐和NO交换流.
- 模拟显示,由于局部NO变异性,在脱和氧化应激中出现了微观代谢异质性.
- MiMICS准确地将异构的微生物代谢状态映射到生物膜微环境中,预测空间关系.
结论:
- MiMICS是一个有价值的计算工具,用于将多omics数据机械地映射到生物膜代谢.
- 该框架阐明了微生物细胞如何根据微环境线索动态调节新陈代谢.
- MiMICS促进了对管理异质生物膜代谢的多层次机制的理解.
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