Metabolic modeling of synthesis gas fermentation in bubble column reactors
Background A promising route to renewable liquid fuels and chemicals is the fermentation of synthesis gas (syngas) streams to synthesize desired products such as ethanol and 2,3-butanediol. While commercial development of syngas fermentation technology is underway, an unmet need is the development...
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Format: | Article |
Language: | English |
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BioMed Central
2015
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Online Access: | http://hdl.handle.net/1721.1/97554 https://orcid.org/0000-0001-8964-8433 https://orcid.org/0000-0003-2895-9443 https://orcid.org/0000-0002-6106-7861 |
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author | Chen, Jin Henson, Michael A Gomez, Jose Alberto Hoeffner, Kai Barton, Paul I. |
author2 | Massachusetts Institute of Technology. Department of Aeronautics and Astronautics |
author_facet | Massachusetts Institute of Technology. Department of Aeronautics and Astronautics Chen, Jin Henson, Michael A Gomez, Jose Alberto Hoeffner, Kai Barton, Paul I. |
author_sort | Chen, Jin |
collection | MIT |
description | Background
A promising route to renewable liquid fuels and chemicals is the fermentation of synthesis gas (syngas) streams to synthesize desired products such as ethanol and 2,3-butanediol. While commercial development of syngas fermentation technology is underway, an unmet need is the development of integrated metabolic and transport models for industrially relevant syngas bubble column reactors.
Results
We developed and evaluated a spatiotemporal metabolic model for bubble column reactors with the syngas fermenting bacterium Clostridium ljungdahlii as the microbial catalyst. Our modeling approach involved combining a genome-scale reconstruction of C. ljungdahlii metabolism with multiphase transport equations that govern convective and dispersive processes within the spatially varying column. The reactor model was spatially discretized to yield a large set of ordinary differential equations (ODEs) in time with embedded linear programs (LPs) and solved using the MATLAB based code DFBAlab. Simulations were performed to analyze the effects of important process and cellular parameters on key measures of reactor performance including ethanol titer, ethanol-to-acetate ratio, and CO and H[subscript 2] conversions.
Conclusions
Our computational study demonstrated that mathematical modeling provides a complementary tool to experimentation for understanding, predicting, and optimizing syngas fermentation reactors. These model predictions could guide future cellular and process engineering efforts aimed at alleviating bottlenecks to biochemical production in syngas bubble column reactors. |
first_indexed | 2024-09-23T15:54:04Z |
format | Article |
id | mit-1721.1/97554 |
institution | Massachusetts Institute of Technology |
language | English |
last_indexed | 2024-09-23T15:54:04Z |
publishDate | 2015 |
publisher | BioMed Central |
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spelling | mit-1721.1/975542022-10-02T04:55:32Z Metabolic modeling of synthesis gas fermentation in bubble column reactors Chen, Jin Henson, Michael A Gomez, Jose Alberto Hoeffner, Kai Barton, Paul I. Massachusetts Institute of Technology. Department of Aeronautics and Astronautics Massachusetts Institute of Technology. Department of Chemical Engineering Gomez, Jose Alberto Hoeffner, Kai Barton, Paul I. Background A promising route to renewable liquid fuels and chemicals is the fermentation of synthesis gas (syngas) streams to synthesize desired products such as ethanol and 2,3-butanediol. While commercial development of syngas fermentation technology is underway, an unmet need is the development of integrated metabolic and transport models for industrially relevant syngas bubble column reactors. Results We developed and evaluated a spatiotemporal metabolic model for bubble column reactors with the syngas fermenting bacterium Clostridium ljungdahlii as the microbial catalyst. Our modeling approach involved combining a genome-scale reconstruction of C. ljungdahlii metabolism with multiphase transport equations that govern convective and dispersive processes within the spatially varying column. The reactor model was spatially discretized to yield a large set of ordinary differential equations (ODEs) in time with embedded linear programs (LPs) and solved using the MATLAB based code DFBAlab. Simulations were performed to analyze the effects of important process and cellular parameters on key measures of reactor performance including ethanol titer, ethanol-to-acetate ratio, and CO and H[subscript 2] conversions. Conclusions Our computational study demonstrated that mathematical modeling provides a complementary tool to experimentation for understanding, predicting, and optimizing syngas fermentation reactors. These model predictions could guide future cellular and process engineering efforts aimed at alleviating bottlenecks to biochemical production in syngas bubble column reactors. 2015-06-29T16:11:10Z 2015-06-29T16:11:10Z 2015-06 2015-03 2015-06-29T08:37:29Z Article http://purl.org/eprint/type/JournalArticle 1754-6834 http://hdl.handle.net/1721.1/97554 Chen, Jin, Jose A. Gomez, Kai Hoffner, Paul I. Barton, and Michael A. Henson. “Metabolic Modeling of Synthesis Gas Fermentation in Bubble Column Reactors.” Biotechnology for Biofuels 8, no. 1 (December 2015). https://orcid.org/0000-0001-8964-8433 https://orcid.org/0000-0003-2895-9443 https://orcid.org/0000-0002-6106-7861 en http://dx.doi.org/10.1186/s13068-015-0272-5 Biotechnology for Biofuels Chen et al. application/pdf BioMed Central |
spellingShingle | Chen, Jin Henson, Michael A Gomez, Jose Alberto Hoeffner, Kai Barton, Paul I. Metabolic modeling of synthesis gas fermentation in bubble column reactors |
title | Metabolic modeling of synthesis gas fermentation in bubble column reactors |
title_full | Metabolic modeling of synthesis gas fermentation in bubble column reactors |
title_fullStr | Metabolic modeling of synthesis gas fermentation in bubble column reactors |
title_full_unstemmed | Metabolic modeling of synthesis gas fermentation in bubble column reactors |
title_short | Metabolic modeling of synthesis gas fermentation in bubble column reactors |
title_sort | metabolic modeling of synthesis gas fermentation in bubble column reactors |
url | http://hdl.handle.net/1721.1/97554 https://orcid.org/0000-0001-8964-8433 https://orcid.org/0000-0003-2895-9443 https://orcid.org/0000-0002-6106-7861 |
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