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[1]邓婷,关晓彤,吴波,等.[综 述] 数学模型在合成微生物群落构建中的应用[J].应用与环境生物学报,2020,26(04):809-819.
 DENG Ting,GUAN Xiaotong,WU Bo? & HE Zhili?.Applying mathematical models in the construction of synthetic microbial communities[J].Chinese Journal of Applied & Environmental Biology,2020,26(04):809-819.
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[综 述] 数学模型在合成微生物群落构建中的应用()
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《应用与环境生物学报》[ISSN:1006-687X/CN:51-1482/Q]

卷:
26卷
期数:
2020年04期
页码:
809-819
栏目:
工业与环境微生物功能研究专栏
出版日期:
2020-08-25

文章信息/Info

Title:
Applying mathematical models in the construction of synthetic microbial communities
作者:
邓婷关晓彤吴波贺志理
中山大学环境科学与工程学院环境微生物组学研究中心,南方海洋科学与工程广东省实验室(珠海) 广州 510006
Author(s):
DENG Ting GUAN Xiaotong WU Bo? & HE Zhili?
Environmental Microbiomics Research Center, School of Environmental Science and Engineering and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Sun Yat-sen University, Guangzhou 510006, China
关键词:
合成微生物生态学合成微生物群落数学模型工业技术环境修复人类健康
Keywords:
synthetic microbial ecology synthetic microbial community mathematic model industrial technology environmental bioremediation human health
摘要:
微生物在自然环境中分布广泛、多样性高,作为群落成员发挥着重要的生态系统功能. 然而,自然微生物群落的组成和相互作用极其复杂,简单可控的合成微生物群落更易于研究微生物群落多样性与生态系统功能的关系及其相互作用机制等关键微生物生态学问题. 将数学模型应用于合成微生物群落是目前合成微生物生态学研究的重要手段,有助于理解微生物群落的动态演替和生态学原理. 本文综述构建合成微生物群落的数学模型,分别描述微生物个体、种群和基因组水平构建模型的基本原理和优缺点及其在合成微生物群落构建中的应用最新进展,并讨论集成微生物个体、种群与基因组水平的建模方法,指出通过“设计—构建—分析—学习”的循环能更好地实现数学模型在合成微生物群落构建中的应用,推动合成微生物生态学的研究. 同时,介绍合成微生物群落在工业技术、环境修复、人类健康等方面的应用,展望数学模型在合成微生物群落构建中应用的发展方向与应用前景. 未来应从完善实验数据和模型算法以及两者更好地结合等方面入手,提高数学模型在微生物群落构建中的预测性、适用性与通用性,并将这些模型应用于合成微生物生态学和微生物组工程,为相关生物技术提供理论指导,促进生物经济的发展. (图1 表1 参95)
Abstract:
Microorganisms are widely distributed in the natural environment, where they interact and play important roles in the biogeochemical cycles as well as within industries, agricultural systems, and bodily health. However, understanding natural microbial communities can be challenging because of their exceptionally high microbial diversity, multifaceted composition, and complicated interactions. The synthetic microbial communities can provide simple and controllable models for the mechanistic understanding of the relationships in microbial communities in terms of diversity-function as well as provide theoretical guidance for biotechnological applications. Applying predictive mathematical models to synthetic microbial communities can assist synthetic microbial ecology and help construct synthetic microbial communities. In this review, we described the different mathematical models for this construction based on the microbial interactions between microorganisms and their environments. We also discussed the fundamental principles, advantages, limitations, and recent advances in modeling microbial communities at the individual, population, and genome levels. Moreover, we emphasized the mathematical methods that integrated these levels using a “design-build-test-learn” cycle, which may advance mathematical model applications in this field and promote synthetic microbial ecology developments. We also mentioned potential applications of synthetic microbial communities in different sectors, such as the biotechnological industry as well as in the environmental and human health fields. Hence, this review aimed to provide recommendations for the development of more powerful mathematical models for synthetic microbial community construction, while encouraging the adoption of these models in microbiome-based biotechnologies. These could ultimately improve industrial productions, environmental bioremediation, maintaining human health, and promoting bioeconomies.

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更新日期/Last Update: 2020-08-25