Activation of Non-Photosynthetic Leaf Cells for Improved Productivity

这项提议旨在回答生物学中的一个基本问题，该问题将使提高光合作用能力的工程得以实现，从而提高广泛植物物种的生产力。具体地说，人们建议阐明决定叶片细胞是否光合作用的遗传机制，并利用这些机制来激活叶片内不活跃的细胞的光合作用。这种利用传统上不活跃的叶片细胞进行光合作用的方法可能会导致农业生产力的阶段性变化。大多数植物所使用的光合作用形式被称为C3光合作用，因为固定二氧化碳的初始产物包含三个碳。虽然C3种植物的叶肉细胞对光的反应是绿色的，但叶片中的其他细胞，如束鞘，则不会。这项提议旨在阐明这种区别的遗传基础。为了了解调控不同光合作用能力的因素，将以水稻作为模式系统。水稻是最适合使用的系统，因为它的基因组相对较小，比任何其他谷物基因组都有更好的注释。这些功能使得基因表达谱的全基因组分析和其他计算分析变得简单。此外，水稻叶片的发育轨迹非常适合正在研究的生物问题。具体地说，光合作用沿着水稻叶片被激活，叶片底部有不活跃的细胞，叶尖有完全活跃的细胞。这种梯度可以用来分析光合作用被激活的动力学和机制。此外，由于光合作用活跃细胞和非光合作用细胞在同一梯度上并排发育，这是比较光合作用和非光合作用细胞类型发展的理想系统。研究计划将被分成六个工作包(WP)。WP1将计算光合作用的基因调控网络(GRN-Ps)。这将确定光合作用激活梯度中可能涉及的调节成分。WP2将使用GRN-Ps来识别C3叶肉中光合作用发育的新调控因子，并阐明这些调控成分之间的时空相互作用。然后，水稻的功能分析将测试这些调节因子可以被修饰和招募到在束鞘中发挥作用的程度。WP3将检验光合作用限制在C3束鞘中的假设，因为正常光诱导的光合作用基因的表达在这种细胞类型中受到抑制，而WP4将发现抑制机制的组成部分。然后，WP5将生成一个工具包，其中包括光合作用激活(或去抑制)的候选顺式和反式调节器，这些工具包将在快速瞬变测试系统中成对组合进行测试。最后，WP6将建立最小的合成回路来激活和维持水稻叶片非光合作用细胞的光合作用。总而言之，这项研究的结果将为未来提高光合作用效率的综合方法提供设计参数。

This proposal aims to answer a fundamental question in biology that will enable increased photosynthetic capacity to be engineered and therefore productivity to be improved in a wide range of plant species. Specifically, it is proposed to elucidate the genetic mechanisms that determine whether a cell in a leaf becomes photosynthetic or not and exploit these mechanisms to activate photosynthesis in inactive cells within the leaf. This utilization of conventionally inactive leaf cells for photosynthesis could lead to a step-change in agricultural productivity. The form of photosynthesis used by the majority of plants is referred to as C3 photosynthesis because the initial product of CO2 fixation contains three carbons. Whilst mesophyll cells of C3 species green up in response to light, other cells in the leaf such as the bundle sheath do not. This proposal aims to elucidate the genetic basis of this distinction. To understand factors regulating differential photosynthetic competence, rice will be used as a model system. Rice is the most appropriate system to use because it has a relatively small genome that is better annotated than any other cereal genome. These features make genome-wide analysis of gene expression profiles and other computational analyses straightforward. In addition, the rice leaf has a developmental trajectory that is perfectly suited to the biological question being addressed. Specifically, photosynthesis is activated along the rice leaf, with inactive cells at the base of the leaf and fully active cells at the tip. This gradient can be used to dissect the dynamics and mechanisms by which photosynthesis is activated. Moreover as photosynthetically active and inactive cells develop side-by-side in the same gradient it is an ideal system in which to compare the development of photosynthetic versus non-photosynthetic cell-types.The research programme will be split into six work packages (WP). WP1 will compute a Gene Regulatory Network for Photosynthesis (GRN-Ps). This will identify the likely regulatory components involved in the photosynthesis activation gradient. WP2 will use the GRN-Ps to identify novel regulators of photosynthetic development in the C3 mesophyll and elucidate the spatial and temporal interactions between these regulatory components. Functional analyses in rice will then test the extent to which these regulators can be modified and recruited to function in the bundle sheath. WP3 will test the hypothesis that photosynthesis is limited in the C3 bundle sheath because normal light-induced expression of photosynthesis genes is repressed in this cell type, and WP4 will discover the components of the repression mechanism. WP5 will then generate a toolkit of candidate cis and trans regulators of photosynthetic activation (or derepression) that will be tested in pairwise combinations in a rapid transient assay system. Finally, WP6 will build minimal synthetic circuits to activate and maintain photosynthesis in non-photosynthetic cells of rice leaves. Together the outputs of this research will provide design parameters for a synthetic approach to improving photosynthetic efficiency for the future.