Kambam P K R, Henson M A, Sun L
Department of Chemical Engineering, University of Massachusetts Amherst, Amherst, MA 01003, USA.
IET Syst Biol. 2008 Jan;2(1):33-8. doi: 10.1049/iet-syb:20070011.
Artificial microbial ecosystems have been increasingly used to understand principles of ecology. These systems offer unique capabilities to mimic a variety of ecological interactions that otherwise would be difficult to study experimentally in a reasonable period of time. However, the elucidation of the genetic bases for these interactions remains a daunting challenge. To address this issue, we have designed and analysed a synthetic symbiotic ecosystem in which the genetic nature of the microbial interactions is defined explicitly. A mathematical model of the gene regulatory network in each species and their interaction through quorum sensing mediated intercellular signalling was derived to investigate the effect of system components on cooperative behaviour. Dynamic simulation and bifurcation analysis showed that the designed system admits a stable coexistence steady state for sufficiently large initial cell concentrations of the two species. The steady-state fraction of each species could be altered by varying model parameters associated with gene transcription and signalling molecule synthesis rates. The design also admitted a stable steady state corresponding to extinction of the two species for low initial cell concentrations and stable periodic solutions over certain domains of parameter space. The mathematical analysis was shown to provide insights into natural microbial ecosystems and to allow identification of molecular targets for engineering system behaviour.
人工微生物生态系统已越来越多地用于理解生态学原理。这些系统具有独特的能力,能够模拟各种生态相互作用,否则在合理的时间段内通过实验研究这些相互作用将非常困难。然而,阐明这些相互作用的遗传基础仍然是一项艰巨的挑战。为了解决这个问题,我们设计并分析了一个合成共生生态系统,其中微生物相互作用的遗传本质被明确界定。我们推导了每个物种中基因调控网络及其通过群体感应介导的细胞间信号传导进行相互作用的数学模型,以研究系统组件对合作行为的影响。动态模拟和分岔分析表明,对于两种物种足够大的初始细胞浓度,设计的系统允许存在一个稳定的共存稳态。通过改变与基因转录和信号分子合成速率相关的模型参数,可以改变每个物种的稳态分数。对于低初始细胞浓度,该设计还允许对应于两种物种灭绝的稳定稳态以及在参数空间的某些区域内的稳定周期解。结果表明,数学分析为自然微生物生态系统提供了见解,并有助于识别用于工程系统行为的分子靶点。