Genomic design principles of carbon exchange between algae and bacteria

这项研究将发现建立循环碳的生态系统的规则。地球上的生命由全球碳循环维持。鉴于人类活动对大气中二氧化碳水平的影响越来越大，了解这种循环是如何以及为什么保持的是一个至关重要的问题。碳循环通过两个过程发生：光合作用，从二氧化碳中产生糖和生物质，呼吸作用将糖和生物质转化为二氧化碳。值得注意的是，地球上大约一半的光合作用是由藻类等微生物进行的。藻类以糖和其他化合物的形式为细菌提供碳。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，而且对全球碳循环至关重要。尽管这种相互作用具有关键性，但碳如何从藻类流向细菌并返回的原理尚不清楚。该项目将使用封闭的微生物生物圈来揭示这些原理：密封的微生物群落，在只有光的情况下维持藻类和细菌之间的碳循环。揭示这些规则将为预测、设计和控制通过微生物群落的碳流打开大门，其应用范围从模拟全球碳循环到生物燃料。这项研究是伴随着一个新的课程，旨在使削减-本项目的研究目标是发现藻类和细菌之间碳交换的设计原理，并将这些原理应用于构建具有预定碳的合成群落。循环能力。解开微生物群落力量的一个关键障碍是，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微生物群落，高通量测量和机器学习，以发现能够实现藻类和细菌之间碳交换的关键基因组特征（途径和分类群）。该项目的成果将是：（1）将联合收割机与碳循环的高通量测量相结合，利用分类学和宏基因组信息预测藻类和细菌之间的碳交换，并在合成财团中测试这些预测。(2)通过利用大规模并行液滴微流控平台来测量数千种相互作用，剖析维持藻类-细菌群落中碳交换的相互作用。利用这些见解来构建碳交换的消费者-资源模型，并预测藻类突变对碳循环的影响。该奖项反映了NSF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。

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.