EAGER: LINKING MICROBIAL COMMUNITY STRUCTURE AND FUNCTION FOR IMPROVED UNDERSTANDING OF ECOSYSTEM PROCESSES

微生物生态学的一个基本挑战是发现微生物群落和跨生物群系的生态系统过程之间的统一联系。这个EAGER项目将制定一个程序来分析由国家生态观测站网络（NEON）收集的土壤微生物数据，该网络的优势是通过在非洲大陆各地的实地地点进行标准化和质量控制的收集和处理方法，产生高质量的可比数据。这个项目的高风险、高回报方面将涉及开发和测试一种“DNA条形码”技术，用于田间土壤微生物组的表征。提高对微生物群落结构和生态系统过程之间联系的理解将使科学家能够更好地预测环境变化如何影响生物地球化学循环和自然资源的管理。这个项目将包括本科生和研究生的培训机会。这个EAGER项目将土壤微生物学与生态系统生态学相结合，以提高对生态系统过程的理解，并将使用基于MinION基因组学平台的新方法来绘制新的领域，以表征土壤微生物。具体的研究目标是：(1)建立NEON土壤微生物群数据的数据分析管道；(2)通过分析公开的NEON数据产品，确定微生物结构（物种丰富度、丰度、多样性、组成）与生态系统过程（土壤呼吸和氮矿化）之间的统一联系；(3)在科罗拉多州博尔德附近的NEON结构域（D10 - CPER, D10 - RMNP, D10 - STER, D13 - NIWO）使用基于MinION的DNA条形码技术收集和分析土壤微生物数据，通过与NEON科学家协调采样，开发和基准[使用下一代测序和磷脂脂肪酸（PLFA）分析]土壤分析方法。结果将揭示微生物群落结构和生态系统过程的一致性。为这些研究开发的方法和管道将有助于改进生态系统模型，这些模型对于减少碳通量和储量、硝化/反硝化、碳分解和整体土地管理预测中的不确定性至关重要。这些研究将包括对研究生的培训，开发使用大数据集的课程，以及使用教程让本科生使用和分析NEON数据。NEON站点收集的数据将通过GitHub和DRYAD &amp； PANGAEA等存储库共享。这项工作的结果将通过科学会议上的演讲和研讨会、“R”图书馆和同行评议的出版物与科学界分享。该奖项反映了美国国家科学基金会的法定使命，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。

A fundamental challenge of microbial ecology is to discover unifying links between microbial communities and ecosystem processes that hold across biomes. This EAGER project will develop a procedure to analyze soil microbial data collected by the National Ecological Observatory Network (NEON), which has the advantage of generating high-quality, comparable data through standardized and quality-controlled collection and processing methods at field sites across the continent. The high-risk, high-payoff aspect of this project will involve development and testing of a 'DNA barcoding' technique for characterizing soil microbiomes in the field. Improved understanding of the links between microbial community structure and ecosystem processes will enable scientists to better predict how environmental changes impact biogeochemical cycles and stewardship of natural resources. This project will include training opportunities at the undergraduate and graduate levels. This EAGER project integrates soil microbiology with ecosystem ecology to improve understanding of ecosystem processes, and will chart new ground using a new method, based on a MinION genomics platform, for characterizing soil microbes in the field. Specific research objectives are to (1) develop a data analysis pipeline for the NEON soil microbiota data; (2) identify unifying links between microbial structure (species richness, abundance, diversity, composition) and ecosystem processes (soil respiration and nitrogen mineralization) through analyses of publicly available NEON data products; and (3) collect and analyze soil microbial data in the field using MinION based DNA barcoding technique at NEON domain sites (D10 – CPER, D10 – RMNP, D10 – STER, D13 – NIWO) near Boulder, CO to develop and benchmark [using next generation sequencing and Phospholipid Fatty Acid (PLFA) profiling] soil analysis methods by coordinating sampling with NEON scientists. The results will reveal consistencies across biomes in microbial community structure and ecosystem processes. The methods and pipeline developed for these studies will facilitate improvements in ecosystem models that are key to reducing uncertainty in predictions of carbon fluxes and stocks, nitrification/denitrification, carbon decomposition, and overall land management. The studies will include training of graduate students, development of a course on using large data sets, and use of tutorials to engage undergraduates in using and analyzing NEON data.. The data collected at the NEON sites will be shared through GitHub and repositories like DRYAD & PANGAEA. Results from this work will be shared with scientific community via presentations and workshops at scientific meetings, an "R" library, and peer-reviewed publications.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.