OCE-PRF Predicting OMZ and seasonal microbial activity from community structure using machine learning and novel measurements of ATP turnover

OCE-PRF 使用机器学习和 ATP 周转的新颖测量方法根据群落结构预测 OMZ 和季节性微生物活动

基本信息

批准号：
2126668
负责人：
Kaycie Lanpher
金额：
$ 29.8万
依托单位：
University of California-San Diego Scripps Inst of Oceanography
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：
2021-09-01 至 2024-08-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2126668&HistoricalAwards=false
关键词：
OCE PRF Predicting OMZ seasonal

项目摘要

This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2).Marine microbes, including single-celled bacteria, archaea, and eukarya, are the main drivers of carbon and energy transformations in the ocean. The efficiency of the microbial loop at transforming dissolved nutrients into biomass and up the food web is defined by the individual activities of the microbial community. Unfortunately, current methods for characterizing microbial activities in the marine environment are biased, with most direct measurements focusing on heterotrophic microbes that respire carbon dioxide in oxygenated waters. These measurements exclude a large diversity of microbes that play major roles in ocean nutrient cycles, including photosynthesizes and chemotrophs as well as microbes in low oxygen, anoxic waters. This project will measure the activity of microbial organisms through novel applications of the adenylate energy system, which is used by all organisms and in almost all metabolic pathways. This work will focus on sites in the California Current Ecosystem with a wide range of oceanographic conditions and variable microbial communities. These locations include low oxygen canyons representative of oxygen minimum zones (OMZs), upwelling locations reflecting eastern boundary currents, and temporally dynamic coastal sites. Within the planned sampling, support will be allocated for undergraduate students to join shipboard efforts to help with seawater sampling and gain experience conducting oceanographic research. The datasets produced from these sampling efforts will be used to develop predictive models of microbial metabolism (activity) that can be applied to other oceanographic regions, based on community structure, abundance, and geochemical parameters across time and environmental concentrations.The highly productive California Current Ecosystem is subjected to seasonal successions of phytoplankton communities, with diatom and dinoflagellate dominance coinciding with upwelling. The ability of these phytoplankton groups to convert nutrients into biomass have impacts on primary productivity, biogeochemical cycles, and the microbial loop. Hypoxic environments shift the microbial community towards anaerobes and chemotrophs, which have unique metabolisms and differential efficiencies converting acquired carbon sources into biomass and energy. Therefore, the microbial loop efficiency in OMZs is likely to be directly impacted by microbial community structure, but precisely defining these differences in microbial activity has been hampered by biased sampling techniques. This project will address the hypotheses that microbial activity, in terms of energy storage, metabolic rates, and growth rates will be directly liked to and predicted by phytoplankton community structure and abundances in seasonal upwelling systems. Additionally, microbial activities in OMZs are linked directly to the implementation of anaerobic metabolic strategies and can thus be predicted by changes in community structure. Microbial activity will be characterized using high throughput applications of novel measures of the energy charge and adenosine triphosphate (ATP) turnover rates while the microbial community structure will be defined with 16S and 18S rRNA gene amplicon sequencing. Two dedicated, single day cruises to the La Jolla and Scripps Canyons located within the California Bight, and containing known OMZs will be conducted. Additionally, microbial activity measurements will be incorporated into an on-going time-series that is sampled for microbial community structure twice-a-week at the Scripps Institute of Oceanography pier in La Jolla, CA. Measurements from the cruises and time-series will be used to develop predictive models of microbial metabolism based on community structure, abundance, and geochemical parameters across time and within known OMZs using self-organizing maps (SOMs) and random forest regression. Therefore, this project will produce predictive models that can be generalized to broader ocean regions in addition to datasets with unprecedented resolution of natural microbial activity across time and environmental conditions.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.

该奖项的全部或部分资金来源于《2021 年美国救援计划法案》（公法 117-2）。海洋微生物，包括单细胞细菌、古细菌和真核生物，是海洋中碳和能源转化的主要驱动力。海洋。微生物循环将溶解的营养物质转化为生物质并进入食物网的效率由微生物群落的个体活动决定。不幸的是，目前表征海洋环境中微生物活动的方法存在偏差，大多数直接测量集中于在含氧水中呼吸二氧化碳的异养微生物。这些测量结果排除了在海洋营养循环中发挥重要作用的多种微生物，包括光合作用和化能微生物以及低氧、缺氧水域中的微生物。该项目将通过腺苷酸能量系统的新颖应用来测量微生物的活性，腺苷酸能量系统被所有生物体和几乎所有代谢途径所使用。这项工作将重点关注加州海流生态系统中具有广泛海洋条件和可变微生物群落的地点。这些位置包括代表最低氧区 (OMZ) 的低氧峡谷、反映东部边界流的上升流位置以及随时间变化的沿海地点。在计划的采样范围内，将为本科生提供支持，让他们加入船上工作，帮助进行海水采样并获得进行海洋学研究的经验。这些采样工作产生的数据集将用于开发微生物代谢（活动）的预测模型，该模型可根据不同时间和环境浓度的群落结构、丰度和地球化学参数应用于其他海洋区域。高产的加州海流生态系统受到浮游植物群落季节性演替的影响，硅藻和甲藻占主导地位，与上升流同时发生。这些浮游植物群将营养物质转化为生物量的能力对初级生产力、生物地球化学循环和微生物循环产生影响。缺氧环境使微生物群落转向厌氧菌和趋化微生物，它们具有独特的新陈代谢和将获得的碳源转化为生物质和能量的不同效率。因此，OMZ 中的微生物循环效率可能直接受到微生物群落结构的影响，但精确定义微生物活性的这些差异受到了有偏差的采样技术的阻碍。该项目将提出这样的假设：在能量储存、代谢率和生长率方面的微生物活动将直接受到浮游植物群落结构和季节性上升流系统丰度的影响和预测。此外，OMZ 中的微生物活动与厌氧代谢策略的实施直接相关，因此可以通过群落结构的变化来预测。将使用能量电荷和三磷酸腺苷 (ATP) 周转率的新测量方法的高通量应用来表征微生物活动，同时将通过 16S 和 18S rRNA 基因扩增子测序来定义微生物群落结构。将进行两次专门的单日巡游，前往位于加利福尼亚湾内的拉霍亚峡谷和斯克里普斯峡谷，并包含已知的 OMZ。此外，微生物活动测量结果将被纳入持续的时间序列中，每周两次在加利福尼亚州拉霍亚的斯克里普斯海洋学研究所码头进行微生物群落结构采样。巡航和时间序列的测量结果将用于开发微生物代谢的预测模型，该模型基于不同时间和已知 OMZ 内的群落结构、丰度和地球化学参数，使用自组织图 (SOM) 和随机森林回归。因此，除了在不同时间和环境条件下具有前所未有的自然微生物活动分辨率的数据集之外，该项目还将产生可推广到更广泛海洋区域的预测模型。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准。