Genomic design principles of carbon exchange between algae and bacteria

藻类和细菌之间碳交换的基因组设计原理

基本信息

批准号：
2117477
负责人：
Seppe Kuehn
金额：
$ 55.15万
依托单位：
University of Chicago
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2021
资助国家：
美国
起止时间：
2021-07-01 至 2024-06-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2117477&HistoricalAwards=false
关键词：
Genomic design principles carbon exchange

项目摘要

The research will discover the rules for building ecosystems that cycle carbon. Life on Earth is sustained by a global carbon cycle. Understanding how and why this cycling is maintained is a critically important question given the growing impact of human activity on carbon dioxide levels in the atmosphere. Carbon cycling happens through two processes: photosynthesis which creates sugars and biomass from carbon dioxide, and respiration which converts sugars and biomass back to carbon dioxide. Remarkably, roughly half of all of the photosynthesis on the planet is performed by microbes such as algae. Algae provide carbon in the form of sugars and other compounds to bacteria. The resulting growth of bacteria is not only essential for the health and function of nearly all ecosystems on the planet but key to the global carbon cycle. Despite the critical nature of this interaction, the principles the govern how carbon flows from algae to bacteria and back are not known. The project will uncover these principles using closed microbial biospheres: hermetically sealed microbial communities that sustain a carbon cycle between algae and bacteria when provided with only light. Uncovering these rules will open the door to predicting, designing, and controlling carbon flow through microbial communities with applications from modeling global carbon cycling to biofuels. The research is accompanied by a new curriculum that is directed at bringing cutting-edge experimental and data science methods to students of Ecology and Evolution as well as accessible demonstrations of scientific ideas to middle school age students.The research objective of this proposal is to discover the design principles governing carbon exchange between algae and bacteria and to apply these principles to build synthetic communities with predefined carbon cycling capabilities. A key roadblock to unlocking the power of microbial communities is that we do not know how genomic structure determines metabolic function. The project combines carbon-cycling closed microbial communities, high-throughput measurements, and machine-learning to discover the key genomic features (pathways and taxa) that enable carbon exchange between algae and bacteria. The outcomes of the project will be: (1) Combine machine learning and high-throughput measurements of carbon cycling to predict carbon exchange between algae and bacteria using taxonomic and metagenomic information and to test these predictions in synthetic consortia. (2) Dissect the interactions that sustain carbon exchange in algae-bacteria communities by exploiting a massively parallel droplet microfluidic platform to measure thousands of interactions. Leverage these insights to construct a consumer-resource model of carbon exchange and predict the impact of algal mutations on carbon recycling.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.

该研究将发现建立循环碳生态系统的规则。地球上的生命是由全球碳循环维持的。鉴于人类活动对大气中二氧化碳水平的影响不断增长，了解这种循环的方式以及为什么保持这种循环是一个至关重要的问题。碳循环通过两个过程进行：光合作用，从二氧化碳产生糖和生物量，以及将糖和生物量转化回二氧化碳的呼吸。值得注意的是，地球上所有光合作用的大约一半是由藻类等微生物进行的。藻类以糖和其他化合物形式提供碳。导致细菌的生长不仅对地球上几乎所有生态系统的健康和功能至关重要，而且对全球碳循环的关键至关重要。尽管这种相互作用的性质至关重要，但原理仍不知道碳流向从藻类到细菌和背部的碳流动方式。该项目将使用封闭的微生物生物圈来揭示这些原理：密封的密封的微生物群落，仅在光线下提供藻类和细菌之间维持碳循环。揭示这些规则将为通过微生物群落进行预测，设计和控制碳流动，从建模全球碳循环到生物燃料的应用。这项研究伴随着一项新的课程，该课程旨在将尖端的实验和数据科学方法带到生态学和进化的学生，以及向中学时代的学生提供科学思想的可访问的演示。该建议的研究目标旨在发现与细菌之间的碳交换的设计原理，并将这些原理在这些原理之间构建carbon Carbon CARBON CARBON CARBON CARBON CARBON CARBON CARBON CARBON CARBON CARBONCY CAINCY CYCLINES CARBONCY CAINCY CAINCY CYCLINES CARBON CAINCY CYCLINES CARBON CAINCY CAIN。解锁微生物群落力量的关键障碍是，我们不知道基因组结构如何决定代谢功能。该项目结合了碳循环封闭的微生物群落，高通量测量值和机器学习，以发现能够在藻类和细菌之间进行碳交换的关键基因组特征（途径和分类单元）。该项目的结果将是：（1）使用分类学和元基因组信息结合机器学习和对碳循环的高通量测量，以预测藻类和细菌之间的碳交换，并在合成联盟中测试这些预测。（2）通过利用大量平行的液滴微流体平台来测量数千种相互作用，剖析藻类 - 细菌群落中维持碳交换的相互作用。利用这些见解来构建一种碳交换的消费者资源模型，并预测藻类突变对碳回收的影响。该奖项反映了NSF的法定任务，并被认为是通过基金会的智力优点和更广泛影响的审查标准来评估值得通过评估来支持的。