Laboratory of Synthetic Microbiology, School of Chemical Engineering and Technology, Tianjin University , Tianjin , China ; Key Laboratory of Systems Bioengineering, Ministry of Education of China , Tianjin , China ; SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering , Tianjin , China.
Front Bioeng Biotechnol. 2014 Nov 3;2:48. doi: 10.3389/fbioe.2014.00048. eCollection 2014.
Although recognized as a promising microbial cell factory for producing biofuels, current productivity in cyanobacterial systems is low. To make the processes economically feasible, one of the hurdles, which need to be overcome is the low tolerance of hosts to toxic biofuels. Meanwhile, little information is available regarding the cellular responses to biofuels stress in cyanobacteria, which makes it challenging for tolerance engineering. Using large proteomic datasets of Synechocystis under various biofuels stress and environmental perturbation, a protein co-expression network was first constructed and then combined with the experimentally determined protein-protein interaction network. Proteins with statistically higher topological overlap in the integrated network were identified as common responsive proteins to both biofuels stress and environmental perturbations. In addition, a weighted gene co-expression network analysis was performed to distinguish unique responses to biofuels from those to environmental perturbations and to uncover metabolic modules and proteins uniquely associated with biofuels stress. The results showed that biofuel-specific proteins and modules were enriched in several functional categories, including photosynthesis, carbon fixation, and amino acid metabolism, which may represent potential key signatures for biofuels stress responses in Synechocystis. Network-based analysis allowed determination of the responses specifically related to biofuels stress, and the results constituted an important knowledge foundation for tolerance engineering against biofuels in Synechocystis.
尽管被认为是生产生物燃料的有前途的微生物细胞工厂，但蓝藻系统的当前生产力仍然很低。为了使这些工艺在经济上可行，需要克服的一个障碍是宿主对有毒生物燃料的低耐受性。同时，关于蓝藻细胞对生物燃料应激的反应的信息很少，这使得耐受工程具有挑战性。利用各种生物燃料应激和环境扰动下的 Synechocystis 大型蛋白质组数据集，首先构建了蛋白质共表达网络，然后将其与实验确定的蛋白质-蛋白质相互作用网络相结合。在综合网络中具有统计学上更高拓扑重叠的蛋白质被鉴定为对生物燃料应激和环境扰动都有反应的共同响应蛋白。此外，还进行了加权基因共表达网络分析，以区分生物燃料特有的响应与环境扰动的响应，并揭示与生物燃料应激相关的代谢模块和蛋白质。结果表明，生物燃料特异性蛋白和模块在几个功能类别中富集，包括光合作用、碳固定和氨基酸代谢，这可能代表 Synechocystis 中生物燃料应激反应的潜在关键特征。基于网络的分析可以确定与生物燃料应激特异性相关的响应，结果为 Synechocystis 中的生物燃料耐受工程提供了重要的知识基础。
