Simultaneous manipulation of source and sink metabolism for improved crop yield

不同植物组织的代谢网络的能力是决定作物产量的关键因素。尤其重要的是吸收环境碳(CO2)和氮(NO3)的能力，将产生的糖和氨基酸输送到汇组织(如块茎、水果和种子)的能力，以及汇组织将输入的糖和氨基酸转化为储存化合物的能力。通过基因工程提高这些代谢和运输过程的能力或效率引起了人们的极大兴趣。目前在这一领域工作的许多研究联合体都集中在源组织中负责碳和氮同化的初始过程。然而，无论是从理论上还是从实验证据上都清楚地表明，整个植物的碳和氮通量受到源组织和库组织代谢能力的共同限制。如果来源能力增加，情况尤其如此：控制权将不可避免地转移到库区组织，因此库区组织的新陈代谢将严重限制转基因作物的产量潜力。在这个项目中，我们将在植物中实施前所未有的代谢工程战略。我们不仅将设计源组织和汇组织，而且我们将针对每个组织中的多个代谢和运输过程，试图消除整个代谢网络的流量瓶颈。该项目将利用生物组合共转化的新技术，该技术允许将无限数量的转基因稳定地整合到任何适合核基因组生物转化的植物中的单个基因位点。基于先验知识，我们已经确定了18个将被引入番茄植株的转基因靶标。我们将产生一个多达200个转基因品系的大型文库，并对这些品系进行果实产量筛选，期望与引入少量仅改变源或库的转基因相比，实现产量的阶梯变化。此外，该项目将进行广泛的研究，以确定更多的代谢瓶颈(通过比较代谢网络通量和酶活性)，确定参与果实氮素分配的转运体，并确定与收获指数和果实氮含量有关的强大遗传等位基因(基于对番茄导入种群的分析)。这项研究将提供更多的目标，这些目标将被超级转化为表现最好的转基因品系，以评估进一步增产的范围。

The capacity of the metabolic networks of different plant tissues is a key determinant of the yield of crop plants. Of particular importance is the capacity to assimilate environmental carbon (CO2) and nitrogen (NO3), the capacity to transport the resultant sugars and amino acids to the sink tissues (such as tubers, fruits and seeds) and the capacity of the sink tissues to convert the incoming sugars and amino acids into storage compounds. There is a great deal of interest in increasing the capacity or efficiency of these metabolic and transport processes by genetic engineering. Many of the current research consortia working in this area are focussing on the initial processes responsible for carbon and nitrogen assimilation in the source tissues. However, it is clear both on theoretical grounds and from experimental evidence that whole plant fluxes of carbon and nitrogen are co-limited by the metabolic capacities of both source and sink tissues. This is especially true if the source capacity is increased: control will inevitably shift to the sink tissues, the metabolism of which will therefore severely limit the yield potential of an engineered crop.In this project, we will implement a metabolic engineering strategy of unprecedented scale in plants. Not only will we engineer both source and sink tissues, but we will target multiple metabolic and transport processes in each in an attempt to remove flux bottlenecks from across the metabolic network. The project will exploit the new technique of biolistic combinatorial co-transformation which allows the stable integration of an unlimited number of transgenes into a single locus in any plant amenable to biolistic transformation of the nuclear genome. Based on prior knowledge, we have identified 18 transgene targets which will be introduced into tomato plants. We will generate a large library of up to 200 transgenic lines and these will be screened for fruit yield, with the expectation of achieving a step-change in yield in comparison to the introduction of small numbers of transgenes modifying just source or sink. In addition, the project will undertake extensive research to identify additional metabolic bottlenecks (by comparison of metabolic network fluxes and enzyme activities), to identify transporters involved in fruit nitrogen allocationand to identify strong genetic alleles for harvest index and fruit nitrogen content (based on analysis of tomato introgression populations). This research will provide additional targets which will be super-transformed into the best performing transgenic line to assess the scope for even further yield increases.