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Metabolic Versatility and Interactio...
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The University of Wisconsin - Madison.
Metabolic Versatility and Interactions of Nitrogen Cycling Microbiomes.
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Metabolic Versatility and Interactions of Nitrogen Cycling Microbiomes./
作者:
Lawson, Christopher Evan.
出版者:
Ann Arbor : ProQuest Dissertations & Theses, : 2019,
面頁冊數:
273 p.
附註:
Source: Dissertations Abstracts International, Volume: 81-07, Section: B.
Contained By:
Dissertations Abstracts International81-07B.
標題:
Environmental engineering. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=27669836
ISBN:
9781392774328
Metabolic Versatility and Interactions of Nitrogen Cycling Microbiomes.
Lawson, Christopher Evan.
Metabolic Versatility and Interactions of Nitrogen Cycling Microbiomes.
- Ann Arbor : ProQuest Dissertations & Theses, 2019 - 273 p.
Source: Dissertations Abstracts International, Volume: 81-07, Section: B.
Thesis (Ph.D.)--The University of Wisconsin - Madison, 2019.
This item must not be sold to any third party vendors.
The catalytic capabilities of microbial communities (“microbiomes”) seem limitless, controlling Earth’s biogeochemical cycles and occupying every environmental niche. Engineers have tapped into these capabilities for centuries by harnessing microbiomes to perform important services for society. One important service is the removal of nitrogen from wastewater via engineered biological processes, such as partial nitritation-anammox (PNA). In these systems, a diverse group of nitrogen cycling bacteria remove ammonium from wastewater as dinitrogen gas through their combine metabolic activities that requires precise balancing. However, the metabolic networks and interactions of nitrogen cycling microbiomes remain poorly characterized, limiting the opportunity to improve nitrogen removal biotechnologies using a systems biology approach. This thesis aimed to understanding the metabolic versatility and interactions occurring in nitrogen cycling microbiomes and to develop new computational models that enable their prediction in natural and engineered ecosystems.In Chapter 1, we provide an overview of the microbial nitrogen cycling network, highlighting key functional guilds, their ecophysiology and interactions, and their application for wastewater treatment. We also outline the systems biology methodology that was used throughout this thesis work. In Chapter 2, we reconstructed the metabolism and interactions of poorly characterized heterotrophic organisms in anammox bioreactors based on metagenomic and metatranscriptomic analysis. This revealed that most heterotrophs were denitrifying bacteria that exchange carbon and nitrogen substrates with anammox bacteria, possibly allowing for improved nitrogen removal efficiency. In Chapters 3 and 4, we applied cutting-edge metabolomic tools, 13C fluxomics, and metabolic modeling to elucidate the autotrophic and mixotrophic metabolic networks operating in two key nitrogen cycling bacteria: the anammox bacterium Candidatus ‘Kuenenia stuttgartiensis’ and the nitrite-oxidizing bacterium Nitrospira moscoviensis. This provided detailed insights on the metabolic networks underlying their versatility and represented the first measurements of metabolic flux in nitrogen cycling microorganism. In Chapter 5, we extended insights from these metabolic networks to build genome-scale models for the anammox bacterium Brocadia sinica and the comammox bacterium Nitrospira nitrosa to predict their interactions under different environmental conditions. Our simulations predicted novel mechanisms driving the cooperation and competition between comammox and anammox bacteria, which could inform strategies to improve the success of mainstream PNA processes. In Chapter 6, we synthesize common principles and best practices for harnessing microbiomes into a design-build-test-learn (DBTL) cycle that can be used to advance microbiome engineering across disciplines. The cycle outlines top-down and bottom-up design processes, synthetic and self-assembled construction methods, and emerging tools to analyze microbiome function that can be used to improving human and animal health, agriculture and enable the bioeconomy.The knowledge and tools generated in these studies improves our ability to understand the functions and interactions occurring in nitrogen cycling microbiomes. Moreover, our findings represent the first steps in creating a systems biology approach for the bottom-up prediction of ecosystem function. From our results, we suggest future research needed to extend this systems biology approach for complete prediction and control of nitrogen cycling microbiomes.
ISBN: 9781392774328Subjects--Topical Terms:
557376
Environmental engineering.
Subjects--Index Terms:
Genome-scale modeling
Metabolic Versatility and Interactions of Nitrogen Cycling Microbiomes.
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The catalytic capabilities of microbial communities (“microbiomes”) seem limitless, controlling Earth’s biogeochemical cycles and occupying every environmental niche. Engineers have tapped into these capabilities for centuries by harnessing microbiomes to perform important services for society. One important service is the removal of nitrogen from wastewater via engineered biological processes, such as partial nitritation-anammox (PNA). In these systems, a diverse group of nitrogen cycling bacteria remove ammonium from wastewater as dinitrogen gas through their combine metabolic activities that requires precise balancing. However, the metabolic networks and interactions of nitrogen cycling microbiomes remain poorly characterized, limiting the opportunity to improve nitrogen removal biotechnologies using a systems biology approach. This thesis aimed to understanding the metabolic versatility and interactions occurring in nitrogen cycling microbiomes and to develop new computational models that enable their prediction in natural and engineered ecosystems.In Chapter 1, we provide an overview of the microbial nitrogen cycling network, highlighting key functional guilds, their ecophysiology and interactions, and their application for wastewater treatment. We also outline the systems biology methodology that was used throughout this thesis work. In Chapter 2, we reconstructed the metabolism and interactions of poorly characterized heterotrophic organisms in anammox bioreactors based on metagenomic and metatranscriptomic analysis. This revealed that most heterotrophs were denitrifying bacteria that exchange carbon and nitrogen substrates with anammox bacteria, possibly allowing for improved nitrogen removal efficiency. In Chapters 3 and 4, we applied cutting-edge metabolomic tools, 13C fluxomics, and metabolic modeling to elucidate the autotrophic and mixotrophic metabolic networks operating in two key nitrogen cycling bacteria: the anammox bacterium Candidatus ‘Kuenenia stuttgartiensis’ and the nitrite-oxidizing bacterium Nitrospira moscoviensis. This provided detailed insights on the metabolic networks underlying their versatility and represented the first measurements of metabolic flux in nitrogen cycling microorganism. In Chapter 5, we extended insights from these metabolic networks to build genome-scale models for the anammox bacterium Brocadia sinica and the comammox bacterium Nitrospira nitrosa to predict their interactions under different environmental conditions. Our simulations predicted novel mechanisms driving the cooperation and competition between comammox and anammox bacteria, which could inform strategies to improve the success of mainstream PNA processes. In Chapter 6, we synthesize common principles and best practices for harnessing microbiomes into a design-build-test-learn (DBTL) cycle that can be used to advance microbiome engineering across disciplines. The cycle outlines top-down and bottom-up design processes, synthetic and self-assembled construction methods, and emerging tools to analyze microbiome function that can be used to improving human and animal health, agriculture and enable the bioeconomy.The knowledge and tools generated in these studies improves our ability to understand the functions and interactions occurring in nitrogen cycling microbiomes. Moreover, our findings represent the first steps in creating a systems biology approach for the bottom-up prediction of ecosystem function. From our results, we suggest future research needed to extend this systems biology approach for complete prediction and control of nitrogen cycling microbiomes.
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