METACONE:一种可扩展的框架,用于探索代谢网络的转换
Álvaro Altamirano1, Ignacio Tapia1, Vicente Acuña2
1Departamento de Ingeniería Química y Bioprocesos, Pontificia Universidad Católica de Chile, Av. Vicuña Mackenna 4860, Macul, Santiago de Chile, 7820436, Región Metropolitana, Chile.
Computational biology and chemistry
|August 12, 2025
概括
METACONE是一个新的算法,可以有效计算大型生物网络中代谢转化模式的代表性基础. 该工具有助于理解微生物代谢和复杂微生物群落内的相互作用.
科学领域:
- 系统生物学 系统生物学
- 代谢工程是代谢工程.
- 计算生物学 计算生物学
背景情况:
- 初级转换模式 (ECM) 提供了对代谢网络潜力的实用视图,但在基因组规模上计算起来具有挑战性.
- 现有的方法在基因组规模模型中难以处理大量的ECM,这限制了它们的应用.
- 可扩展性是分析复杂代谢相互作用的关键瓶.
研究的目的:
- 开发一个可扩展的算法,METACONE,用于计算代谢转化的代表性线性基础.
- 为探索微生物系统中的代谢能力和相互作用提供一个实用的工具.
- 为了克服在大型代谢网络中计算基本转换模式 (ECM) 的计算局限性.
主要方法:
- 开发了METACONE (METAbolic Conversion cOne for Network Exploration),这是一个用于计算转换圆的代表线性基础的新算法.
- 实现了METACONE的两个变体,使用基于解决一系列线性程序的不同启发式.
- 在不同尺寸的代谢模型上评估算法性能和可扩展性.
主要成果:
- 证明了METACONE在各种代谢模型上的可扩展性,证实了它对基因组规模网络的效率.
- 分析了计算的基础,以探索Escherichia coli在各种环境条件下的代谢能力,确定已知的代谢模式.
- 成功地将METACONE应用于一个微生物联盟 (*Phocaeicola dorei*和 *Lachnoclostridium symbiosum*),回顾了已知的交叉养,并表明了新的相互作用.
结论:
- METACONE为分析代谢转换模式提供了一个可扩展的解决方案,解决了详尽的ECM清单的局限性.
- 该算法有助于探索单个生物体和复杂微生物联盟中的代谢潜力和相互作用.
- 在系统生物学和合成生物学应用中,METACONE是促进对微生物新陈代谢的理解的宝贵工具.
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