INSPIRE: Unraveling Factors that Determine Fast Growth of a Photoautotroph

INSPIRE：揭示决定光合自养生物快速生长的因素

• 批准号: 1546840
• 负责人: Himadri Pakrasi
• 金额: $ 100万
• 依托单位: Washington University
• 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: 2015-09-01 至 2020-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1546840&HistoricalAwards=false
• 关键词: INSPIRE; Unraveling; Factors; Determine; Fast

This INSPIRE award is partially funded by the Systems and Synthetic Biology program in the Division of Molecular and Cellular Biosciences in the Directorate for Biological Sciences; the Biotechnology and Biochemical Engineering program and the Environmental Engineering program in the Division of Chemical, Bioengineering, Environmental, and Transport Systems in the Directorate for Engineering; the Office of Integrated Activities, and the Office of International Science & Engineering. This award is aimed at generating systems level insights into the processes and dynamics that influence growth in model photosynthetic organisms. As such, this project has important implications for fundamental understanding of a complex and essential biological process, and has significant implications for biotechnology applications. Photosynthesis is the engine of life on our planet, and organisms that live off of photosynthesis, such as cyanobacteria, algae, and plants, are primarily responsible for carbon sequestration in the biosphere. On the planet today, such oxygen-producing photosynthetic organisms assimilate 100 petagrams (100 gigatons) of carbon per year. In contrast, organisms that need chemical nutrients as sources of energy assimilate only 0.3 petagrams (0.3 gigatons) per year. This INSPIRE project is aimed at unraveling the most important factors that control growth rates of cyanobacteria, a model photosynthetic organism. It brings together two different fields, cyanobacteria physiology and mathematical modeling, to abstract fundamental rules of growth parameters and dynamics. It will help design tool kits for engineering cyanobacteria and other photosynthetic microorganisms to enable increased biomass production, an essential requirement for biotechnology applications for sunlight driven carbon-neutral production of food, feed and fuel. The project will also provide training for international undergraduates and engage students under the iGEM training program. The team of researchers identified recently a unicellular cyanobacterium, Synechococcus elongatus strain, UTEX 2973, with the fastest growth rate among all cyanobacterial strains studied to date. Surprisingly, this strain is a close relative of Synechococcus elongatus PCC 7942, a well-studied model cyanobacterial strain. The two share greater than 99% genome sequence identity. However, the growth potential of Synechococcus 2973 is nearly three-fold better than Synechococcus 7942. The investigators will determine the key factors that are responsible for fast growth of cyanobacteria by applying experimental molecular approaches to compare Synechococcus 7942 with Synechococcus 2973, using adaptive evolution, and developing metabolic and expression (ME) models. They will compare the transcriptome of the two strains under different light intensities, CO2 levels and growth phases. The integrating of ME models for Synechococcus 2973 and Synechococcus 7942 with the transcriptomic data generated are expected to uncover metabolic and expression differences that contribute to the increased biomass production of Synechococcus 2973. The photosynthetic and carbon fixation efficiencies will also be measured to better elucidate mechanistic differences between these strains. In addition, a subset of mutations identified by genome comparison will be analyzed in an effort to recapitulate the fast-growth phenotype.

该INSPIRE奖部分由生物科学理事会分子和细胞生物科学部门的系统和合成生物学计划资助;生物技术和生物化学工程计划以及工程理事会化学，生物工程，环境和运输系统部门的环境工程计划;综合活动办公室和国际科学工程办公室。 该奖项旨在对影响光合生物模型生长的过程和动态产生系统水平的见解。因此，该项目对于从根本上理解复杂和基本的生物过程具有重要意义，并对生物技术应用具有重大意义。光合作用是我们星球上生命的引擎，以光合作用为生的生物，如蓝藻，藻类和植物，主要负责生物圈中的碳封存。在今天的地球上，这种产生氧气的光合生物每年吸收100千兆吨的碳。相比之下，需要化学营养素作为能量来源的生物每年只吸收0.3千兆克（0.3千兆吨）。这个INSPIRE项目的目的是解开控制蓝细菌生长速度的最重要因素，蓝细菌是一种光合生物模型。它汇集了两个不同的领域，蓝藻生理学和数学建模，抽象的生长参数和动力学的基本规则。它将帮助设计用于工程化蓝细菌和其他光合微生物的工具包，以增加生物量生产，这是生物技术应用于阳光驱动的碳中性食品，饲料和燃料生产的基本要求。该项目还将为国际本科生提供培训，并让学生参与iGEM培训计划。研究小组最近发现了一种单细胞蓝藻，细长聚球藻菌株UTEX 2973，在迄今为止研究的所有蓝藻菌株中生长速度最快。令人惊讶的是，该菌株是细长聚球藻PCC 7942的近亲，细长聚球藻PCC 7942是一种经过充分研究的模式蓝藻菌株。两者的基因组序列相同性超过99%。然而，Synechococcus 2973的生长潜力比Synechococcus 7942好近三倍。研究人员将通过应用实验分子方法比较Synechococcus 7942与Synechococcus 2973，使用适应性进化以及开发代谢和表达（ME）模型来确定负责蓝藻快速生长的关键因素。他们将比较两种菌株在不同光照强度、CO2水平和生长阶段下的转录组。聚球藻2973和聚球藻7942的ME模型与所产生的转录组数据的整合预计将揭示有助于聚球藻2973的生物质产量增加的代谢和表达差异。还将测量光合和碳固定效率，以更好地阐明这些菌株之间的机制差异。此外，将分析通过基因组比较鉴定的突变子集，以概括快速生长表型。