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 in | Geochimica et cosmochimica acta Vol. 242; pp. 102 - 122 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
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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. |
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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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CitedBy_id | crossref_primary_10_1007_s11430_020_9793_5 crossref_primary_10_1111_1758_2229_13231 crossref_primary_10_3389_fevo_2021_653622 crossref_primary_10_3389_fmicb_2022_859063 crossref_primary_10_1128_spectrum_02259_21 crossref_primary_10_1016_j_apgeochem_2023_105782 crossref_primary_10_3390_fermentation9050406 |
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Keywords | Biogeochemical reaction modeling Flux balance analysis Genome-scale metabolic model Nutrient limitation Microbial kinetics Methanogenesis |
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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 |
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