Advancing our understanding of autonomous leaf-specific iron deficiency responses.

铁是所有生物和植物的必需营养素，是人类和牲畜铁的主要膳食来源。缺铁或贫血影响着世界上近30%的人口（约20亿人）。因此，了解植物用于调节铁在可食用组织（如叶片和种子）中的吸收和积累的机制，将有助于开发提高营养价值的生物强化作物。铁也是极具活性的，因此植物需要感知其内部水平来确定对铁的需求并调整吸收以防止潜在的有毒铁超载情况。在过去的十年中，在调控根水平铁摄取的分子机制方面取得了重大进展。然而，铁感应仍然是一个活跃的研究领域，有几个假设需要实验验证。该项目将测试最近提出的一个模型，其中叶片整合整个植物的铁状态，并将这些信息传达给根系，以适当调节植物内的铁吸收和分配。培训方面侧重于植物科学生物信息学（BIPS）项目，该项目由首席研究员开发，将计算机科学与工程专业的本科生与植物生物学专业的学生配对，进行双方感兴趣的跨学科研究项目。最近的时空基因表达分析表明，叶片对缺铁的反应比根系快。此外，在某些条件下，叶片和根显示相反的铁相关转录程序，表明叶片具有自主感知铁的机制。该项目将整合叶片特异性时间序列基因表达分析以及靶向高通量dna -蛋白质和蛋白质-蛋白质相互作用筛选，以确定调节叶片中铁稳态所需的转录复合物。此外，组织特异性基因编辑方法将用于评估叶绿体与细胞核之间的通信是否对叶片中适当的铁感知至关重要，特别是在成熟的光合叶片中。实验将辅以建模方法，探索基于约束的模拟的预测能力，当蛋白质- dna和蛋白质-蛋白质相互作用的稳定性，实验确定，依次纳入动力学模型。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Iron is an essential nutrient for all organisms and plants serve as the main dietary source of iron for humans and livestock. Iron deficiency, or anemia, affects nearly 30% of the world’s population (~2 billion people). Thus, understanding the mechanisms that plants use to regulate Fe uptake and accumulation in edible tissues, such as leaves and seeds, will support the development of biofortified crops for improved nutritional value. Iron is also extremely reactive and therefore plants need to sense their internal levels to determine the demand for iron and adjust uptake to prevent a potentially toxic iron overload situation. Over the last decade, there have been significant advances in the molecular mechanisms that regulate iron uptake at the root level. Iron sensing, however, remains an active area of research with several hypotheses that need to be tested experimentally. This project will test a recently proposed model where leaves integrate the iron status of the entire plant and communicate such information to roots to properly regulate iron uptake and allocation within the plant. Training aspects focus on the Bioinformatics in Plant Sciences (BIPS) program developed by the principal investigator that pairs undergraduate students in computer science and engineering with plant biology students to undertake interdisciplinary research projects of interest to both.Recent spatiotemporal gene expression analyses revealed that leaves respond faster to iron deficiency than roots. Moreover, under certain conditions, leaves and roots display opposite iron-related transcriptional programs suggesting that leaves have autonomous mechanisms to sense iron. This project will integrate leaf-specific time-series gene expression analyses together with targeted high-throughput DNA-protein and protein-protein interaction screens to identify transcriptional complexes necessary to regulate iron homoeostasis in leaves. In addition, tissue-specific gene editing approaches will be used to assess whether chloroplast-to-nucleus communication is essential for proper iron sensing in leaves, particularly in mature photosynthetic leaves. Experiments will be complemented with modeling approaches to explore the predictive power of constraint-based simulations when the stability of protein-DNA and protein-protein interactions, determined experimentally, are sequentially incorporated into kinetic models.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.