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

增进我们对自主叶片特异性缺铁反应的理解。

基本信息

批准号：
2224839
负责人：
David Mendoza-Cozatl
金额：
$ 125.57万
依托单位：
University of Missouri-Columbia
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2022
资助国家：
美国
起止时间：
2022-08-01 至 2025-07-31
项目状态：
未结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2224839&HistoricalAwards=false
关键词：
Advancing our understanding autonomous leaf

项目摘要

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.

铁是所有生物体的基本营养素，植物是人类和牲畜铁的主要饮食来源。缺铁或贫血影响着世界近30%的人口(约20亿人)。因此，了解植物用来调节可食用组织(如叶片和种子)铁吸收和积累的机制，将有助于开发生物强化作物以提高营养价值。铁也是非常活跃的，因此植物需要感知它们的内部水平，以确定对铁的需求，并调整吸收，以防止潜在的有毒铁超载的情况。在过去的十年里，在调控根水平铁吸收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，有几个假说需要进行实验验证。该项目将测试最近提出的一种模型，在该模型中，树叶整合整个植物的铁状态，并将这些信息传达给根，以适当地调节植物内铁的吸收和分配。培训方面的重点是由首席研究员开发的植物科学生物信息学(BIPS)项目，该项目将计算机科学和工程专业的本科生与植物生物学专业的学生配对，进行双方都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更快。此外，在某些条件下，叶和根表现出与铁相关的相反的转录程序，这表明叶具有感知铁的自主机制。该项目将结合叶片特定的时间序列基因表达分析，以及有针对性的高通量DNA-蛋白质和蛋白质-蛋白质相互作用筛选，以确定调节叶片铁稳态所需的转录复合体。此外，还将使用组织特异性基因编辑方法来评估叶绿体到细胞核的通讯是否对叶片，特别是成熟的光合作用叶片的铁感应是必不可少的。实验将与建模方法相辅相成，以探索基于约束的模拟的预测能力，当通过实验确定的蛋白质-DNA和蛋白质-蛋白质相互作用的稳定性被顺序纳入动力学模型时。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。