代谢交叉养相互作用调节微生物燃料电池中的动态社区结构,在有机负载变化的废水下
Natchapon Srinak1, Porntip Chiewchankaset2, Saowalak Kalapanulak1,2
1Bioinformatics and Systems Biology Program, School of Bioresources and Technology, School of Information Technology, King Mongkut's University of Technology Thonburi (Bang Khun Thian), Bangkok, Thailand.
PLoS computational biology
|October 17, 2024
概括
废水处理中的微生物群落通过代谢交叉养来适应. 这项研究模拟了有机加载率的变化如何影响微生物燃料电池 (MFC) 中的微生物协会,影响性能.
科学领域:
- 环境微生物学 环境微生物学
- 生物技术是生物技术.
- 代谢工程是代谢工程.
背景情况:
- 微生物燃料电池 (MFC) 处理工业废水,但其效率取决于微生物群落易受操作变化的影响.
- 了解MFC中的微生物适应和社区结构对于稳定的表现至关重要.
研究的目的:
- 通过使用一种新型代谢模型,研究处理工业废水的MFC中的微生物群落适应.
- 阐明代谢交叉养在不同有机载荷率 (OLR) 下塑造微生物结构中的作用.
主要方法:
- 开发一个微生物-微生物相互作用的基因组规模代谢模型 (mmGEM).
- 模拟三个关键的微生物协会:硫酸盐降解细菌 (SRB),甲原体 (MET) 和硫化物氧化细菌 (SOB).
- 模拟微生物群落对低 (L-OLRs) 和高 (H-OLRs) 有机负载率的反应.
主要成果:
- 随着OLR的增加,MFC的表现下降,与从SOB占主导地位向MET占主导地位的社区的转变相关.
- 该mmGEM准确地预测了微生物的丰富性和适应模式.
- 在H-OLR下,SOB的增长受到减少的硫循环和酸盐交叉养的限制,而MET受益于SRB的交叉养代谢物增加.
结论:
- 代谢交叉养是微生物社区结构适应MFCs在波动的OLRs下的关键驱动因素.
- 对交叉养动态的洞察力可以指导优化工业废水处理中MFCs的战略.
- 该研究为基于微生物相互作用和环境条件的MFC性能预测提供了一个框架.
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