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Modeling population dynamics in a microbial consortium under control of a synthetic pheromone-mediated communication system

机译:在合成信息素介导的通信系统控制下,在微生物联盟中建模人口动态

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Microbial consortia can be used to catalyze complex biotransformations. Tools to control the behavior of these consortia in a technical environment are currently lacking. In the present study, a synthetic biology approach was used to build a model consortium of two Saccharomyces cerevisiae strains where growth and expression of the fluorescent marker protein EGFP by the receiver strain is controlled by the concentration of alpha-factor pheromone, which is produced by the emitter strain. We have developed a quantitative experimental and theoretical framework to describe population dynamics in the model consortium. We measured biomass growth and metabolite production in controlled bioreactor experiments, and used flow cytometry to monitor changes of the subpopulations and protein expression under different cultivation conditions. This dataset was used to parameterize a segregated mathematical model, which took into account fundamental growth processes, pheromone-induced growth arrest and EGFP production, as well as pheromone desensitization after extended exposure. The model was able to predict the growth dynamics of single-strain cultures and the consortium quantitatively and provides a basis for using this approach in actual biotransformations.
机译:微生物组成可用于催化复杂的生物转化。目前缺乏控制技术环境中这些联盟行为的工具。在本研究中,使用合成生物学方法来构建两个酿酒酵母菌株的模型联盟,其中通过接收器菌株的荧光标记蛋白EGFP的生长和表达由α因子信息素的浓度控制,该浓度由发射极应变。我们开发了一种定量的实验和理论框架,以描述模型联盟中的人口动态。我们测量了受控生物反应器实验中的生物质生长和代谢物生产,并使用流式细胞术,以监测不同培养条件下群体和蛋白质表达的变化。该数据集用于参数化分散的数学模型,该模型考虑了基本生长过程,信息素诱导的生长逮捕和EGFP生产,以及延长暴露后的信息酮脱敏。该模型能够定量地预测单应变培养和联盟的生长动态,并为在实际生物转发中使用这种方法提供基础。

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