A New Method of Genome-Scale Metabolic Model Validation for Biogeochemical Application
We propose a new method to integrate genome-scale metabolic models into biogeochemical reaction modeling. This method predicts rates of microbial metabolisms by combining flux balance analysis (FBA) with microbial rate laws. We applied this new hybrid method to methanogenesis by Methanosarcina barke...
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ndltd-uoregon.edu-oai-scholarsbank.uoregon.edu-1794-226792019-01-05T17:23:56Z A New Method of Genome-Scale Metabolic Model Validation for Biogeochemical Application Shapiro, Benjamin Jin, Qusheng Biogeochemical reaction modeling Flux balance analysis Genome-scale Geobacter Methanosarcina Shewanella We propose a new method to integrate genome-scale metabolic models into biogeochemical reaction modeling. This method predicts rates of microbial metabolisms by combining flux balance analysis (FBA) with microbial rate laws. We applied this new hybrid method to methanogenesis by Methanosarcina barkeri. Our results show that the new method predicts well the progress of acetoclastic, methanol, and diauxic metabolism by M. barkeri. The hybrid method represents an improvement over dynamic FBA. We validated genome-scale metabolic models of Methanosarcina barkeri, Methanosarcina acetivorans, Geobacter metallireducens, Shewanella oneidensis, Shewanella putrefaciens and Shewanella sp. MR4 for application to biogeochemical modeling. FBA was used to predict the response of cell metabolism, and ATP and biomass yield. Our analysis provides improvements to these models for the purpose of applications to natural environments. 2019-07-28 2017-09-06T21:45:55Z 2017-09-06 Electronic Thesis or Dissertation http://hdl.handle.net/1794/22679 en_US All Rights Reserved. University of Oregon |
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Biogeochemical reaction modeling Flux balance analysis Genome-scale Geobacter Methanosarcina Shewanella |
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Biogeochemical reaction modeling Flux balance analysis Genome-scale Geobacter Methanosarcina Shewanella Shapiro, Benjamin A New Method of Genome-Scale Metabolic Model Validation for Biogeochemical Application |
description |
We propose a new method to integrate genome-scale metabolic models into biogeochemical reaction modeling. This method predicts rates of microbial metabolisms by combining flux balance analysis (FBA) with microbial rate laws. We applied this new hybrid method to methanogenesis by Methanosarcina barkeri.
Our results show that the new method predicts well the progress of acetoclastic, methanol, and diauxic metabolism by M. barkeri. The hybrid method represents an improvement over dynamic FBA. We validated genome-scale metabolic models of Methanosarcina barkeri, Methanosarcina acetivorans, Geobacter metallireducens, Shewanella oneidensis, Shewanella putrefaciens and Shewanella sp. MR4 for application to biogeochemical modeling. FBA was used to predict the response of cell metabolism, and ATP and biomass yield. Our analysis provides improvements to these models for the purpose of applications to natural environments. === 2019-07-28 |
author2 |
Jin, Qusheng |
author_facet |
Jin, Qusheng Shapiro, Benjamin |
author |
Shapiro, Benjamin |
author_sort |
Shapiro, Benjamin |
title |
A New Method of Genome-Scale Metabolic Model Validation for Biogeochemical Application |
title_short |
A New Method of Genome-Scale Metabolic Model Validation for Biogeochemical Application |
title_full |
A New Method of Genome-Scale Metabolic Model Validation for Biogeochemical Application |
title_fullStr |
A New Method of Genome-Scale Metabolic Model Validation for Biogeochemical Application |
title_full_unstemmed |
A New Method of Genome-Scale Metabolic Model Validation for Biogeochemical Application |
title_sort |
new method of genome-scale metabolic model validation for biogeochemical application |
publisher |
University of Oregon |
publishDate |
2017 |
url |
http://hdl.handle.net/1794/22679 |
work_keys_str_mv |
AT shapirobenjamin anewmethodofgenomescalemetabolicmodelvalidationforbiogeochemicalapplication AT shapirobenjamin newmethodofgenomescalemetabolicmodelvalidationforbiogeochemicalapplication |
_version_ |
1718806584939773952 |