INSPIRE Track 1: Microbial systems biology in freshwater lakes: a new framework for scaling from genes to ecosystems

INSPIRE 轨道 1：淡水湖中的微生物系统生物学：从基因扩展到生态系统的新框架

• 批准号: 1344254
• 负责人: Katherine McMahon
• 金额: $ 78.37万
• 依托单位: University of Wisconsin-Madison
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-01-01 至 2017-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1344254&HistoricalAwards=false
• 关键词: INSPIRE; Track; Microbial; systems; biology

This INSPIRE award is partially funded by the Ecosystem Studies Program in the Division of Environmental Biology in the Directorate for Biological Sciences and the Environmental Engineering Program in the Division of Chemical, Bioengineering, Environmental, and Transport Systems in the Directorate for Engineering.Microbes are critical, but often ignored, players in all ecosystems. They have tremendous influence on ecosystem resilience, with implications for predicting the response and feedback to drivers ranging from climate change to land-use change and management. However, it has been challenging to incorporate microbes and their vast diversity into predictive environmental models. Specifically, key advances are needed to address the knowledge gaps that prevent integration of microbial genomic information into ecosystem-scale science. Solutions will be highly interdisciplinary, with contributions from microbiologists, ecologists, computational biologists, and engineers. This project aims to use genomic data to determine how microbes in freshwater lakes control carbon cycling and water quality, and to convert this new understanding into predictive computational models that forecast how lakes will behave. Environmental engineers have a long history of working quantitatively with water quality models, but they do not incorporate microbes into them. Ecosystem scientists study the flux of matter and energy through ecosystems but they rarely consider microbes and often do not construct models based on first principles. This work will bring together three disciplines that are rarely integrated: microbiology, ecosystem science, and environmental engineering.This work will have broad impacts on science as well as education and outreach efforts. Microbial biologists and ecologists are hungry for new ways to transform complex datasets and fundamental concepts into understanding and prediction. Students and post-docs in fields of microbiology, ecology, and engineering need cross-training in computational biology, genomics, and modeling. They will need to push their science to be less descriptive and more predictive, which requires computational and integrative thinking that transcends the structure of current graduate programs in these disciplines. The project will leverage relevant network science initiatives such as the Global Lake Ecological Observatory Network (GLEON) and the nascent Genomic Observatories (GOs) network. Finally, our ability to make microbial ecosystem science relevant to the broader public depends on illustrating how tiny entities can have large impact on high-value ecosystems services. Freshwater lakes are excellent systems for this purpose since water quality is so tightly linked to microbes, with major feedbacks to local economic activity, ecosystem management decisions, and public perception of ecosystem health.

该INSPIRE奖是由生态系统研究计划在环境生物学系的生态系统研究计划中部分资助的，而在工程局中，化学，生物工程，环境和运输系统的化学，生物工程，环境和运输系统的环境工程计划是至关重要的，但通常忽略了所有生态系统的参与者。它们对生态系统的弹性有巨大的影响，这对预测从气候变化到土地利用变化和管理的驾驶员的反应和反馈意义。但是，将微生物及其大量多样性纳入预测性环境模型一直是一项挑战。具体而言，需要关键的进步来解决阻止微生物基因组信息与生态系统规模科学集成的知识差距。解决方案将是高度跨学科的，并提供微生物学家，生态学家，计算生物学家和工程师的贡献。该项目旨在使用基因组数据来确定淡水湖泊中的微生物如何控制碳循环和水质，并将这种新的理解转换为预测的计算模型，以预测湖泊的行为方式。环境工程师有悠久的与水质模型进行定量工作的历史，但他们不将微生物纳入其中。生态系统科学家研究了通过生态系统的物质和能量的通量，但他们很少考虑微生物，并且通常不会基于第一原理构建模型。这项工作将汇集三个很少融合的学科：微生物学，生态系统科学和环境工程。这项工作将对科学以及教育和推广工作产生广泛的影响。微生物生物学家和生态学家渴望将复杂的数据集和基本概念转变为理解和预测的新方法。微生物学，生态学和工程领域的学生和邮政在计算生物学，基因组学和建模中需要交叉培训。他们将需要推动科学的描述性较低，更具预测性，这需要计算和综合思维，以超越这些学科中当前研究生课程的结构。该项目将利用相关的网络科学计划，例如全球湖泊生态观测网络（GLEON）和新生的基因组观测站（GOS）网络。最后，我们使微生物生态系统科学与更广泛的公众相关的能力取决于说明微小实体如何对高价值生态系统服务产生重大影响。淡水湖是为此目的的绝佳系统，因为水质与微生物密切相关，对当地经济活动，生态系统管理决策和公众对生态系统健康的看法有重大反馈。

项目成果

Diversity, distribution, and expression of opsin genes in freshwater lakes

• DOI: 10.1111/mec.16891
• 发表时间: 2023-03-07
• 期刊: MOLECULAR ECOLOGY
• 影响因子: 4.9
• 作者: He, Shaomei;Linz, Alexandra M.;McMahon, Katherine D.
• 通讯作者: McMahon, Katherine D.