通量平衡分析
生化工程
微生物种群生物学
代谢网络
微生物群
计算机科学
生态学
生物
计算生物学
生物信息学
工程类
遗传学
细菌
作者
Kok Siong Ang,Meiyappan Lakshmanan,Na‐Rae Lee,Dong‐Yup Lee
出处
期刊:Current Genomics
[Bentham Science]
日期:2018-09-12
卷期号:19 (8): 712-722
被引量:38
标识
DOI:10.2174/1389202919666180911144055
摘要
In nature, microbes do not exist in isolation but co-exist in a variety of ecological and biological environments and on various host organisms. Due to their close proximity, these microbes interact among themselves, and also with the hosts in both positive and negative manners. Moreover, these interactions may modulate dynamically upon external stimulus as well as internal community changes. This demands systematic techniques such as mathematical modeling to understand the intrinsic community behavior. Here, we reviewed various approaches for metabolic modeling of microbial communities. If detailed species-specific information is available, segregated models of individual organisms can be constructed and connected via metabolite exchanges; otherwise, the community may be represented as a lumped network of metabolic reactions. The constructed models can then be simulated to help fill knowledge gaps, and generate testable hypotheses for designing new experiments. More importantly, such community models have been developed to study microbial interactions in various niches such as host microbiome, biogeochemical and bioremediation, waste water treatment and synthetic consortia. As such, the metabolic modeling efforts have allowed us to gain new insights into the natural and synthetic microbial communities, and design interventions to achieve specific goals. Finally, potential directions for future development in metabolic modeling of microbial communities were also discussed.
科研通智能强力驱动
Strongly Powered by AbleSci AI