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通过合成生态学和分子系统共生学来破译微生物群落的稳健性。

Deciphering microbial community robustness through synthetic ecology and molecular systems synecology.

机构信息

Université catholique de Louvain, Earth & Life Institute, Bioengineering Laboratory, Place Croix du Sud 2, bte. L07.05.19, B-1348 Louvain-la-Neuve, Belgium.

Université catholique de Louvain, Earth & Life Institute, Bioengineering Laboratory, Place Croix du Sud 2, bte. L07.05.19, B-1348 Louvain-la-Neuve, Belgium.

出版信息

Curr Opin Biotechnol. 2015 Jun;33:305-17. doi: 10.1016/j.copbio.2015.03.012. Epub 2015 Apr 14.

DOI:10.1016/j.copbio.2015.03.012
PMID:25880923
Abstract

Microbial ecosystems exhibit specific robustness attributes arising from the assembly and interaction networks of diverse, heterogeneous communities challenged by fluctuating environmental conditions. Synthetic ecology provides new insights into key biodiversity-stability relationships and robustness determinants of host-associated or environmental microbiomes. Driven by the advances of meta-omics technologies and bioinformatics, community-centered approaches (defined as molecular systems synecology) combined with the development of dynamic and mechanistic mathematical models make it possible to decipher and predict the outcomes of microbial ecosystems under disturbances. Beyond discriminating the normal operating range and natural, intrinsic dynamics of microbial processes from systems-level responses to environmental forcing, predictive modeling is poised to be integrated within prescriptive analytical frameworks and thus provide guidance in decision-making and proactive microbial resource management.

摘要

微生物生态系统表现出特定的稳健属性,这些属性源于多样化、异质群落的组装和相互作用网络,这些群落受到环境条件波动的挑战。合成生态学为关键的生物多样性-稳定性关系以及与宿主相关或环境微生物组的稳健性决定因素提供了新的见解。元组学技术和生物信息学的进步推动了以群落为中心的方法(定义为分子系统协同生态学)的发展,同时也结合了动态和机械数学模型的发展,使得破译和预测微生物生态系统在干扰下的结果成为可能。除了区分微生物过程的正常运行范围和自然内在动态与系统对环境胁迫的响应之外,预测建模有望整合到规定性分析框架中,从而为决策和主动的微生物资源管理提供指导。

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