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Application of thermodynamic theory for predicting microbial biogeochemistry

热力学理论在预测微生物生物地球化学中的应用

基本信息

批准号：
1451356
负责人：
Joseph Vallino
金额：
$ 20.37万
依托单位：
Marine Biological Laboratory
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2015
资助国家：
美国
起止时间：
2015-04-15 至 2016-03-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1451356&HistoricalAwards=false
关键词：
Application thermodynamic theory predicting microbial

项目摘要

Most of the elements critical for life on Earth, such as nitrogen, carbon, phosphorous, sulfur and many trace metals, are cycled between land, water and the atmosphere by the actions of microscopic bacteria and archaea that both extract and recycle these elements on a continuous basis. Understanding how microbes control these so called biogeochemical cycles is critical for understanding how the environment will change in the face of natural and anthropogenic alterations. To predict how ecosystems will respond to increases in nutrient inputs, changes in temperatures, increases in atmospheric carbon dioxide and similar drivers, computer models are constructed based on how bacteria grow and interact. However, because a single gram of soil or liter of water contains billions of bacteria consisting of thousands of difference species, it can be challenging to accurately predict their collective geochemistry by modeling all of their growth characteristics and interactions. An alternative approach assumes that complex systems, whether composed of living organisms or not, naturally organize to maximize the extraction and use of available energy. Known as the maximum entropy production (MEP) principle, this theory can be used to describe the collective actions of a community of microorganisms without needing to know exactly which microbes are present and exactly how they interact. If true, the MEP-based approach should produce models with better predictive capabilities than models based on conventional approaches. This project seeks to demonstrate the usefulness of MEP by comparing model predictions to biogeochemical observations collected in an aquatic environment. The investigators will disseminate the modeling approach and research results via journal publications and presentations. The research project will support one postdoctoral scholar in a multidisciplinary research area, independent undergraduate research projects via Marine Biological Laboratory's Semester in Environmental Science Program, and summer internships as part of the Woods Hole Partnership Education Program, which is a consortium of institutions committed to increasing diversity in Woods Hole.A mathematical framework to predict microbial biogeochemistry based on the maximum entropy production (MEP) principle applied to a distributed metabolic network has been developed. The model accurately predicts microbial dynamics and associated chemistry in experimental methanotrophic microcosms and is also adept in predicting metabolic switching between the known nitrate reduction pathways (denitrification, dissimilatory nitrate reduction to ammonium, and anammox) in well-mixed systems as a function of environmental conditions. The MEP approach describes both geochemistry and biogeochemistry, where the latter differs from the former in that living organisms maximizing energy dispersal over time and space as opposed to instantaneously. The objectives of this project are to: 1) advance the MEP biogeochemistry modeling approach by incorporating metabolic reactions for aerobic and anaerobic-based phototrophy; 2) extend the approach from 0D to 1D to examine hypotheses for integrating MEP over space; 3) collect diel biogeochemical measurements over vertical profiles in a meromictic pond (Siders Pond on Cape Cod, MA) for model development and testing; 4) measure allocation of molecular machinery associated with key biogeochemical pathways over depth in Siders Pond using metagenomics and metatranscriptomics and compare these observations to model predictions.

大多数对地球上的生命至关重要的元素，如氮、碳、磷、硫和许多微量金属，在陆地、水和大气之间循环，通过微观细菌和古细菌的作用，它们不断地提取和循环这些元素。了解微生物如何控制这些所谓的生物地球化学循环，对于了解环境在面对自然和人为变化时将如何变化至关重要。为了预测生态系统将如何对养分输入的增加、温度的变化、大气二氧化碳的增加和类似的驱动因素做出反应，基于细菌的生长和相互作用建立了计算机模型。然而，因为一克土壤或一升水含有数十亿细菌，由数千种不同的物种组成，通过模拟它们所有的生长特征和相互作用来准确预测它们的集体地球化学是具有挑战性的。另一种方法认为，复杂的系统，无论是否由生物体组成，都会自然地组织起来，以最大限度地提取和利用可用能源。这一理论被称为最大熵产生（MEP）原理，可以用来描述微生物群落的集体行为，而不需要确切地知道哪些微生物存在以及它们是如何相互作用的。如果这是真的，基于mep的方法产生的模型应该比基于传统方法的模型具有更好的预测能力。该项目旨在通过将模型预测与在水生环境中收集的生物地球化学观测结果进行比较，来证明MEP的实用性。研究人员将通过期刊出版物和报告传播建模方法和研究结果。该研究项目将支持一名多学科研究领域的博士后学者，通过海洋生物实验室的环境科学学期计划进行独立的本科生研究项目，以及作为伍兹霍尔合作伙伴教育计划一部分的暑期实习，该计划是一个致力于增加伍兹霍尔多样性的机构联盟。提出了一种基于最大熵产原理的微生物生物地球化学预测数学框架，并将其应用于分布式代谢网络。该模型准确地预测了实验甲烷营养微生物群落中的微生物动力学和相关化学，也擅长预测混合良好的系统中已知硝酸盐还原途径（反硝化、异化硝酸盐还原为铵和厌氧氨氧化）之间的代谢转换，作为环境条件的函数。MEP方法同时描述了地球化学和生物地球化学，后者与前者的不同之处在于生物体随着时间和空间最大化能量分散，而不是瞬间。本项目的目标是：1)通过纳入好氧和厌氧光养代谢反应，推进MEP生物地球化学建模方法；2)将方法从0D扩展到1D，以检验空间上MEP积分的假设；3)在一个分生池塘（马萨诸塞州科德角的Siders池塘）的垂直剖面上收集生物地球化学测量数据，用于模型开发和测试；4)利用宏基因组学和亚转录组学测量Siders Pond深度上与关键生物地球化学途径相关的分子机制分配，并将这些观察结果与模型预测进行比较。