Vavitsas Konstantinos, Rue Emil Østergaard, Stefánsdóttir Lára Kristín, Gnanasekaran Thiyagarajan, Blennow Andreas, Crocoll Christoph, Gudmundsson Steinn, Jensen Poul Erik
Copenhagen Plant Science Centre, Department of Plant and Environmental Sciences, University of Copenhagen, Thorvaldsensvej 40, 1871, Frederiksberg C, Denmark.
Center for Systems Biology, University of Iceland, Sturlugata 8, 101, Reykjavik, Iceland.
Microb Cell Fact. 2017 Aug 15;16(1):140. doi: 10.1186/s12934-017-0757-y.
There are an increasing number of studies regarding genetic manipulation of cyanobacteria to produce commercially interesting compounds. The majority of these works study the expression and optimization of a selected heterologous pathway, largely ignoring the wholeness and complexity of cellular metabolism. Regulation and response mechanisms are largely unknown, and even the metabolic pathways themselves are not fully elucidated. This poses a clear limitation in exploiting the rich biosynthetic potential of cyanobacteria.
In this work, we focused on the production of two different compounds, the cyanogenic glucoside dhurrin and the diterpenoid 13R-manoyl oxide in Synechocystis PCC 6803. We used genome-scale metabolic modelling to study fluxes in individual reactions and pathways, and we determined the concentrations of key metabolites, such as amino acids, carotenoids, and chlorophylls. This allowed us to identify metabolic crosstalk between the native and the introduced metabolic pathways. Most results and simulations highlight the metabolic robustness of cyanobacteria, suggesting that the host organism tends to keep metabolic fluxes and metabolite concentrations steady, counteracting the effects of the heterologous pathway. However, the amino acid concentrations of the dhurrin-producing strain show an unexpected profile, where the perturbation levels were high in seemingly unrelated metabolites.
There is a wealth of information that can be derived by combining targeted metabolite identification and computer modelling as a frame of understanding. Here we present an example of how strain engineering approaches can be coupled to 'traditional' metabolic engineering with systems biology, resulting in novel and more efficient manipulation strategies.
关于对蓝藻进行基因操作以生产具有商业价值化合物的研究越来越多。这些研究大多聚焦于所选异源途径的表达和优化，很大程度上忽略了细胞代谢的整体性和复杂性。调控和响应机制在很大程度上尚不清楚，甚至代谢途径本身也未完全阐明。这在开发蓝藻丰富的生物合成潜力方面构成了明显限制。
在这项工作中，我们专注于在聚球藻PCC 6803中生产两种不同的化合物，生氰糖苷蜀黍氰苷和二萜类化合物13R-氧化曼诺醇。我们使用基因组规模的代谢模型来研究各个反应和途径中的通量，并测定了关键代谢物的浓度，如氨基酸、类胡萝卜素和叶绿素。这使我们能够识别天然代谢途径与引入的代谢途径之间的代谢相互作用。大多数结果和模拟突出了蓝藻的代谢稳健性，表明宿主生物体倾向于保持代谢通量和代谢物浓度稳定，抵消异源途径的影响。然而，生产蜀黍氰苷的菌株的氨基酸浓度呈现出意想不到的分布，在看似不相关的代谢物中干扰水平较高。
通过将靶向代谢物鉴定与计算机建模相结合作为一种理解框架，可以获得大量信息。在此，我们展示了一个菌株工程方法如何与系统生物学的“传统”代谢工程相结合的例子，从而产生新颖且更有效的操纵策略。
