Sweetlove Lee J, Nielsen Jens, Fernie Alisdair R
Department of Plant Sciences, University of Oxford, South Parks Road, Oxford, OX1 3RB, UK.
Department of Biology and Biological Engineering, Chalmers University of Technology, SE41128, Gothenburg, Sweden.
Plant J. 2017 May;90(4):749-763. doi: 10.1111/tpj.13464. Epub 2017 Mar 11.
The goal of increasing crop productivity and nutrient-use efficiency is being addressed by a number of ambitious research projects seeking to re-engineer photosynthetic biochemistry. Many of these projects will require the engineering of substantial changes in fluxes of central metabolism. However, as has been amply demonstrated in simpler systems such as microbes, central metabolism is extremely difficult to rationally engineer. This is because of multiple layers of regulation that operate to maintain metabolic steady state and because of the highly connected nature of central metabolism. In this review we discuss new approaches for metabolic engineering that have the potential to address these problems and dramatically improve the success with which we can rationally engineer central metabolism in plants. In particular, we advocate the adoption of an iterative 'design-build-test-learn' cycle using fast-to-transform model plants as test beds. This approach can be realised by coupling new molecular tools to incorporate multiple transgenes in nuclear and plastid genomes with computational modelling to design the engineering strategy and to understand the metabolic phenotype of the engineered organism. We also envisage that mutagenesis could be used to fine-tune the balance between the endogenous metabolic network and the introduced enzymes. Finally, we emphasise the importance of considering the plant as a whole system and not isolated organs: the greatest increase in crop productivity will be achieved if both source and sink metabolism are engineered.
许多雄心勃勃的研究项目致力于重新设计光合生物化学，以此来实现提高作物产量和养分利用效率的目标。这些项目中有许多都需要对中心代谢通量进行大幅改造。然而，正如在微生物等较为简单的系统中已充分证明的那样，中心代谢极难通过理性设计来改造。这是因为存在多层调控机制来维持代谢稳态，也因为中心代谢具有高度的关联性。在本综述中，我们讨论了代谢工程的新方法，这些方法有可能解决这些问题，并显著提高我们对植物中心代谢进行理性设计的成功率。特别是，我们提倡采用迭代的“设计—构建—测试—学习”循环，以快速转化的模式植物作为试验平台。通过将新的分子工具与计算建模相结合，在核基因组和质体基因组中整合多个转基因，从而设计工程策略并了解工程生物体的代谢表型，就可以实现这种方法。我们还设想，诱变可用于微调内源代谢网络与导入酶之间的平衡。最后，我们强调将植物视为一个整体系统而非孤立器官的重要性：如果对源代谢和库代谢都进行改造，将实现作物产量的最大增幅。
