Collaborative Research: BoCP-Design: A multidomain microbial consortium to interrogate organic matter decomposition in a changing ocean

合作研究：BoCP-Design：一个多域微生物联盟，用于研究不断变化的海洋中的有机物分解

• 批准号: 2409874
• 负责人: Rene Boiteau
• 金额: $ 6万
• 依托单位: University of Minnesota-Twin Cities
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-10-01 至 2025-10-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2409874&HistoricalAwards=false
• 关键词: Collaborative; Research; BoCP; Design; multidomain

Despite low standing biomass, extensive carbon processing occurs in the oceans, largely by diverse microbial consumers. Until recently, bacteria were considered the main degraders of organic matter, while non-bacterial consumers’ role in carbon cycling was largely been ignored. However, eukaryotes such as fungi exhibit distinct metabolic capacities and responses to environmental variables, suggesting global change may alter the balance of microbial activities in the oceans and potentially alter the fate of marine carbon. Here, researchers integrate field data with modeling and laboratory experiments with representative cultures to identify microbes’ functional roles in marine organic matter degradation and to determine their response to changing environmental conditions. This project will open new windows into the diversity of microbial metabolisms and how these dynamics will shift with global change driven increases in temperature and other environmental factors. Additionally, this projects builds a new scientific research team and expands scientific training at levels ranging from K-5 teachers, to undergraduate and PhD students. This project will leverage a decade-long, coastal microbial time series, the Piver’s Island Coastal Observatory (PICO), to examine how diverse heterotrophic microbial communities (bacteria, phytoplankton, fungi and Labyrinthulomycetes protists) metabolize carbon compounds under different thermal regimes. This project will develop a model microbial consortium that has the potential to transform perception of carbon cycling in coastal systems by integrating functional, organismal-interaction and environment-dependent responses into a modeling framework. Empirical Dynamic Modeling will identify drivers of the observed dynamics, differentiate causation from correlation, infer effects of possibly unobserved variables (e.g. predation), and quantify interactions between organisms. This data will further be used to develop a culturable model consortium whose members metabolize distinct components of phytoplankton-derived organic matter. To test both model predictions and how well the consortium represents complex microbiomes, both the model consortium and a “wild” coastal seawater microbiome will be assayed for changes in function (phytoplankton DOM degradation) as temperatures increase (+4 °C). These experiments will compare outcomes for individual isolates, the consortium, and a wild coastal microbiome in composition/abundance, gene expression and degradation of specific compounds. Finally, experimental results will be used to parameterize and refine an Ensemble Sparse Identification of Nonlinear Dynamics model that can predict the fate and transformation of carbon in marine systems under varying climate scenarios. While this research leverages existing expertise in marine microbiomes, this model consortium approach can be applied to diverse systems to answer questions about environmental filtering, organismal interactions and functional diversity critical to predicting ecosystem-level responses to environmental change.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.

尽管存在生物量较低，但在海洋中，大量碳加工大部分发生在很大程度上是由潜水员微生物消费者进行的。直到最近，细菌仍被认为是有机物的主要降解者，而非细菌消费者在碳循环中的作用在很大程度上被忽略了。但是，真核生物（例如真菌）表现出明显的代谢能力和对环境变量的反应，这表明全球变化可能会改变海洋中微生物活性的平衡，并可能改变海洋碳的命运。在这里，研究人员将现场数据与建模和实验室实验与代表性培养物相结合，以确定微生物在海洋有机物定义中的功能作用，并确定它们对不断变化的环境条件的反应。该项目将为微生物代谢的多样性开放新窗口，以及这些动态如何随温度和其他环境因素的增加而变化。此外，该项目建立了一个新的科学研究团队，并扩大了从K-5教师到本科和博士生的水平的科学培训。该项目将利用十年的沿海微生物时间序列，即Piver's Island沿海天文台（PICO），以研究如何在不同的热体管制下分类碳代谢化合物。该项目将开发一个模型微生物联盟，该联盟有可能通过将功能性，有机体相互作用和环境依赖性响应整合到建模框架中来转化沿海系统中碳循环的感知。经验动态建模将确定观察到的动态的驱动因素，将原因与相关性区分开，推断可能未观察到的变量（例如捕食）的影响以及量化组织之间的相互作用。该数据将进一步用于开发一个文化模型财团，其成员代谢了浮游植物衍生的有机物的不同组成部分。为了测试模型预测以及财团代表复杂的微生物组，模型联盟和“野生”海水微生物组的功能变化（浮游植物DOM降解）随着温度的增加（+4°C）。这些实验将比较单个分离株，财团和野生沿海微生物组的结局，基因表达和特定化合物的降解。最后，实验结果将用于参数化和完善非线性动力学模型的整体稀疏识别，该模型可以预测在不同气候场景下碳系统中碳的命运和转化。 While this research leverages existing expertise in marine microbiomes, this model consortium approach can be applied to Diverse systems to answer questions about environmental filtering, organic interactions and functional diversity critical to predicting ecosystem-level responses to environmental change.This award reflects NSF's statutory mission and has been deemed precious of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.