Integrating genome-scale metabolic models into the prediction of microbial kinetics in natural environments

We propose a new method to predict microbial metabolic rates in natural environments using genome-scale metabolic models. This method is a hybrid of existing approaches, i.e., rate laws and flux balance analysis (FBA). It accounts for the availabilities of chemical energy and growth nutrients in the...

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Published inGeochimica et cosmochimica acta Vol. 242; pp. 102 - 122
Main Authors Shapiro, Benjamin, Hoehler, Tori M., Jin, Qusheng
Format Journal Article
LanguageEnglish
Published Elsevier Ltd 01.12.2018
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Abstract We propose a new method to predict microbial metabolic rates in natural environments using genome-scale metabolic models. This method is a hybrid of existing approaches, i.e., rate laws and flux balance analysis (FBA). It accounts for the availabilities of chemical energy and growth nutrients in the environment, and applies FBA independently to the respiration and biosynthesis pathways of genome-scale metabolic models. We illustrate the new method by modeling the metabolism of a representative methanogen – Methanosarcina barkeri – in laboratory reactors and in pristine and biostimulated aquifers. The laboratory application demonstrates that the hybrid method predicts the rates of individual biochemical reactions within overall cell metabolism and tracks, explicitly, cellular fluxes of carbon and energy. The aquifer applications reveal that the growth of methanogens in natural systems can be limited by multiple factors, including energy sources and growth nutrients, and that the limitations are subject to Liebig’s Law of the Minimum. These results highlight the improvements of the new method in biogeochemical reaction modeling, including its applicability to diverse environments, from eutrophic to oligotrophic.
AbstractList We propose a new method to predict microbial metabolic rates in natural environments using genome-scale metabolic models. This method is a hybrid of existing approaches, i.e., rate laws and flux balance analysis (FBA). It accounts for the availabilities of chemical energy and growth nutrients in the environment, and applies FBA independently to the respiration and biosynthesis pathways of genome-scale metabolic models. We illustrate the new method by modeling the metabolism of a representative methanogen – Methanosarcina barkeri – in laboratory reactors and in pristine and biostimulated aquifers. The laboratory application demonstrates that the hybrid method predicts the rates of individual biochemical reactions within overall cell metabolism and tracks, explicitly, cellular fluxes of carbon and energy. The aquifer applications reveal that the growth of methanogens in natural systems can be limited by multiple factors, including energy sources and growth nutrients, and that the limitations are subject to Liebig’s Law of the Minimum. These results highlight the improvements of the new method in biogeochemical reaction modeling, including its applicability to diverse environments, from eutrophic to oligotrophic.
Author Jin, Qusheng
Hoehler, Tori M.
Shapiro, Benjamin
Author_xml – sequence: 1
  givenname: Benjamin
  surname: Shapiro
  fullname: Shapiro, Benjamin
  organization: Department of Earth Sciences, University of Oregon, Eugene, OR 97403, USA
– sequence: 2
  givenname: Tori M.
  surname: Hoehler
  fullname: Hoehler, Tori M.
  organization: NASA Ames Research Center, Mail Stop 239-4, Moffett Field, CA 94035, USA
– sequence: 3
  givenname: Qusheng
  surname: Jin
  fullname: Jin, Qusheng
  email: qjin@uoregon.edu
  organization: Department of Earth Sciences, University of Oregon, Eugene, OR 97403, USA
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Keywords Biogeochemical reaction modeling
Flux balance analysis
Genome-scale metabolic model
Nutrient limitation
Microbial kinetics
Methanogenesis
Language English
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SSID ssj0007550
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Snippet We propose a new method to predict microbial metabolic rates in natural environments using genome-scale metabolic models. This method is a hybrid of existing...
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elsevier
SourceType Enrichment Source
Index Database
Publisher
StartPage 102
SubjectTerms Biogeochemical reaction modeling
Flux balance analysis
Genome-scale metabolic model
Methanogenesis
Microbial kinetics
Nutrient limitation
Title Integrating genome-scale metabolic models into the prediction of microbial kinetics in natural environments
URI https://dx.doi.org/10.1016/j.gca.2018.08.047
Volume 242
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