自然环境中普遍存在污染物的菌群协同代谢而非单菌株的降解。针对不同类型污染物和土壤环境精准设计污染物高效降解菌群可以显著提高微生物修复效率。前期我们以单个降解菌株为核心的菌群设计研究首次证实代谢模型构建技术可以实现对污染物降解菌群的有效设计。然而以降解菌群为核心的菌群设计和构建未见报道。本项目拟以辛酰溴苯腈为靶标污染物，选择具有协同（菌株X-1和7D-2）和竞争（菌株7D-2和H8）关系的降解菌群为核心菌群，通过高通量测序筛选来自不同土壤的辅助菌株，构建核心菌群和辅助菌株组成的多菌株代谢模型。基于模型模拟菌群降解污染物的动态过程以及菌群成员间的相互作用，阐明不同辅助菌株对菌群降解能力和稳定性的影响，揭示菌群高效代谢辛酰溴苯腈的机制，预测最佳菌群组合及相应的环境因子，并进行实验室检验和田间应用。本项目不仅为污染物降解菌群的设计和操控提供理论依据及方法，而且为污染物的微生物修复提供新策略和技术。

Microbial degradation of organic pollutants is usually carried out by the metabolic cooperation within a bacterial consortium rather than a single strain. The application of educated microbial consortia directing towards predefined functions such as high effective degradation of target pollutant is of potential to induce significant improvement in degradation efficiency. Based on a key pollutant-degrading strain, we constructed a bacterial community with other assist strains without degrading ability, which showed microbial community metabolic models are useful to design optimized microbial consortia. However, little study involves in the community designing based on key consortium consisted of synergistic degrading strains. Here, bromoxynil octanoate will be selected as target pollutants and two communities consisted of strains with synergic (strain X-1 and 7D-2) or competitive (strain 7D-2 and H8) relationship respectively will be selected as key consortia for investigation. We will use high-throughput sequencing approaches for describing the structure of soil communities exposed to treatments of the two key consortia and/or the target pollutants. Then assist species involved in degradation processes of target pollutants will be chose and metabolic models of community consisted of the key consortia and assist strains will be constructed. Using these community models we will simulate the dynamic performances of alternative community combinations and the relationships among each strain in the community during the degrading process. The effect of assist strains on degradation abilities and stabilities of a community will also be analyzed. Based on simulations, we will predict variations in pollutant degradation efficiencies and structure of community with highest degrading rate. The predicted optimized consortia will be experimentally tested. By project, optimized consortia will be designed for application in bio-augmentation of bromoxynil octanoate contaminated environment and the mechanisms of enhanced degradation efficiency by optimized consortia will be illuminated. More importantly, the strategy of designing optimized consortia used in this project will not only help to learn the theory about manipulating structures and functions of an microbial community, but also will provide novel solutions for bio-augmentation of other pollutants.