Bilateral NSF/BIO-BBSRC - Linking Cell Growth with Proliferation in the Plant Root Meristem

双边 NSF/BIO-BBSRC - 将细胞生长与植物根分生组织的增殖联系起来

• 批准号: 1546402
• 负责人: Albrecht von Arnim
• 金额: $ 70.63万
• 依托单位: University of Tennessee Knoxville
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-08-01 至 2020-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1546402&HistoricalAwards=false
• 关键词: Bilateral; NSF; BIO; BBSRC; Linking

The goal of this collaborative US/UK project that engages researchers at the University of Tennessee and the University of London is to better understand how plants coordinate the biosynthesis (production) of proteins with cell division as they grow. This is important because plants must carefully integrate information about available nutrients and their energy supply before deciding whether or not to invest limited resources into growth and the irreversible production of new cells. The work will lead to insights into the physiological and molecular processes that underpin the agricultural productivity of crop plants and will help to optimize plant function and crop productivity by genetic improvement. The project will develop the scientific workforce by training postdoctoral scientists, PhD students, as well as affiliated junior investigators with advanced multi-disciplinary skills at the interface of experimental and computational systems biology, skills that are highly portable in the academic and industrial sectors of the life sciences. Outreach to the general public will also be performed, in collaboration with an artist that uses plant life-related themes in her installations.Protein synthesis (translation) is a major sink for the carbon and nitrogen compounds that, once assimilated through photosynthesis, drive cell growth and proliferation. The project seeks to decipher how protein synthesis-driven cell growth is connected to cell proliferation in meristematic plant cells, using the root tip of the plant reference species Arabidopsis as an experimental system. An underlying hypothesis that shall be tested is that growth regulatory signaling pathways coordinate both the cell cycle and protein synthesis in response to growth stimulating signals. To this end, cell biological markers of cell proliferation will be imaged over time in strains harboring genetic lesions in key signaling pathways. Data on translational efficiency will be collected using genome-wide techniques in order to identify the targets of translational regulation in actively growing tissues. Translation data will be fitted to an emergent computational model of mRNA translation in order to derive biochemical parameters of translation such as the initiation rate. Finally, a network model will integrate new and published data to predict cell cycle transitions in response to the signals that drive cell proliferation and translation. The project is a collaboration between two experimental labs, who have complementary expertise in the regulatory processes that underpin cell division and protein translation. The two teams are joined by two computational investigators, who likewise contribute complementary expertise in machine learning, statistical modeling, pattern recognition and dynamic modeling using deterministic and probabilistic algorithms. This collaborative US/UK project is supported by the US National Science Foundation and the UK Biotechnology and Biological Sciences Research Council.

这个美国/英国合作项目的目标是让田纳西大学和伦敦大学的研究人员更好地了解植物如何在生长过程中协调蛋白质的生物合成（生产）与细胞分裂。这一点很重要，因为植物在决定是否将有限的资源投入到生长和新细胞的不可逆转的生产中之前，必须仔细整合有关可用养分及其能量供应的信息。这项工作将有助于深入了解支撑作物农业生产力的生理和分子过程，并有助于通过遗传改良优化植物功能和作物生产力。该项目将通过培训博士后科学家，博士生以及附属的初级研究人员来发展科学劳动力，这些研究人员在实验和计算系统生物学的界面上具有先进的多学科技能，这些技能在生命科学的学术和工业部门非常便携。此外，还将与一位艺术家合作，在她的装置中使用与植物生命相关的主题，向公众进行宣传。蛋白质合成（翻译）是碳和氮化合物的主要汇，一旦通过光合作用被吸收，就会驱动细胞生长和增殖。该项目旨在破译蛋白质合成驱动的细胞生长如何与分生植物细胞中的细胞增殖相联系，使用植物参考物种拟南芥的根尖作为实验系统。应检验的基本假设是生长调节信号传导途径响应于生长刺激信号而协调细胞周期和蛋白质合成。为此，细胞增殖的细胞生物标志物将随着时间的推移在关键信号传导途径中具有遗传病变的菌株中成像。将使用全基因组技术收集有关翻译效率的数据，以确定活跃生长组织中的翻译调控靶点。翻译数据将拟合到mRNA翻译的紧急计算模型，以获得翻译的生化参数，如起始速率。最后，网络模型将整合新的和已发表的数据，以预测细胞周期转换，以响应驱动细胞增殖和翻译的信号。该项目是两个实验室之间的合作，他们在支持细胞分裂和蛋白质翻译的调控过程中具有互补的专业知识。这两个团队由两名计算研究人员组成，他们同样在机器学习、统计建模、模式识别和使用确定性和概率算法的动态建模方面提供互补的专业知识。这个美国/英国合作项目得到了美国国家科学基金会和英国生物技术和生物科学研究理事会的支持。