Development of a core Clostridium thermocellum kinetic metabolic model consistent with multiple genetic perturbations

Dash, Satyakam; Khodayari, Ali; Zhou, Jilai; Holwerda, Evert K.; Olson, Daniel G.; Lynd, Lee R.; Maranas, Costas D.

doi:10.1186/s13068-017-0792-2

Title: Development of a core Clostridium thermocellum kinetic metabolic model consistent with multiple genetic perturbations

Abstract

Background. Clostridium thermocellum is a Gram-positive anaerobe with the ability to hydrolyze and metabolize cellulose into biofuels such as ethanol, making it an attractive candidate for consolidated bioprocessing (CBP). At present, metabolic engineering in C. thermocellum is hindered due to the incomplete description of its metabolic repertoire and regulation within a predictive metabolic model. Genome-scale metabolic (GSM) models augmented with kinetic models of metabolism have been shown to be effective at recapitulating perturbed metabolic phenotypes. Results. In this effort, we first update a second-generation genome-scale metabolic model (iCth446) for C. thermocellum by correcting cofactor dependencies, restoring elemental and charge balances, and updating GAM and NGAM values to improve phenotype predictions. The iCth446 model is next used as a scaffold to develop a core kinetic model (k-ctherm118) of the C. thermocellum central metabolism using the Ensemble Modeling (EM) paradigm. Model parameterization is carried out by simultaneously imposing fermentation yield data in lactate, malate, acetate, and hydrogen production pathways for 19 measured metabolites spanning a library of 19 distinct single and multiple gene knockout mutants along with 18 intracellular metabolite concentration data for a Δgldh mutant and ten experimentally measured Michaelis–Menten kinetic parameters. Conclusions. The k-ctherm118 model captures significant metabolic changes causedmore »« less

Authors:: Dash, Satyakam; Khodayari, Ali; Zhou, Jilai; Holwerda, Evert K.; Olson, Daniel G.; Lynd, Lee R.; Maranas, Costas D.

Publication Date:: Tue May 02 00:00:00 EDT 2017

Research Org.:: Pennsylvania State Univ., University Park, PA (United States)

Sponsoring Org.:: USDOE

OSTI Identifier:: 1618677

Alternate Identifier(s):: OSTI ID: 1393548

Grant/Contract Number:: SC0012377

Resource Type:: Published Article

Journal Name:: Biotechnology for Biofuels

Additional Journal Information:: Journal Name: Biotechnology for Biofuels Journal Volume: 10 Journal Issue: 1; Journal ID: ISSN 1754-6834

Publisher:: Springer Science + Business Media

Country of Publication:: Netherlands

Language:: English

Subject:: 09 BIOMASS FUELS; Clostridium thermocellum; Genome-scale metabolic model; Kinetic model; Ensemble modeling; Nitrogen limitation; Ethanol stress

Citation Formats


                    Dash, Satyakam, Khodayari, Ali, Zhou, Jilai, Holwerda, Evert K., Olson, Daniel G., Lynd, Lee R., and Maranas, Costas D. Development of a core Clostridium thermocellum kinetic metabolic model consistent with multiple genetic perturbations.  Netherlands: N. p., 2017. 
Web.  doi:10.1186/s13068-017-0792-2.

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                    Dash, Satyakam, Khodayari, Ali, Zhou, Jilai, Holwerda, Evert K., Olson, Daniel G., Lynd, Lee R., & Maranas, Costas D. Development of a core Clostridium thermocellum kinetic metabolic model consistent with multiple genetic perturbations.  Netherlands.  https://doi.org/10.1186/s13068-017-0792-2

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                    Dash, Satyakam, Khodayari, Ali, Zhou, Jilai, Holwerda, Evert K., Olson, Daniel G., Lynd, Lee R., and Maranas, Costas D. Tue .  
"Development of a core Clostridium thermocellum kinetic metabolic model consistent with multiple genetic perturbations".  Netherlands.  https://doi.org/10.1186/s13068-017-0792-2.

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@article{osti_1618677,

  title        = {Development of a core Clostridium thermocellum kinetic metabolic model consistent with multiple genetic perturbations},

  author       = {Dash, Satyakam and Khodayari, Ali and Zhou, Jilai and Holwerda, Evert K. and Olson, Daniel G. and Lynd, Lee R. and Maranas, Costas D.},

  abstractNote = {Background. Clostridium thermocellum is a Gram-positive anaerobe with the ability to hydrolyze and metabolize cellulose into biofuels such as ethanol, making it an attractive candidate for consolidated bioprocessing (CBP). At present, metabolic engineering in C. thermocellum is hindered due to the incomplete description of its metabolic repertoire and regulation within a predictive metabolic model. Genome-scale metabolic (GSM) models augmented with kinetic models of metabolism have been shown to be effective at recapitulating perturbed metabolic phenotypes. Results. In this effort, we first update a second-generation genome-scale metabolic model (iCth446) for C. thermocellum by correcting cofactor dependencies, restoring elemental and charge balances, and updating GAM and NGAM values to improve phenotype predictions. The iCth446 model is next used as a scaffold to develop a core kinetic model (k-ctherm118) of the C. thermocellum central metabolism using the Ensemble Modeling (EM) paradigm. Model parameterization is carried out by simultaneously imposing fermentation yield data in lactate, malate, acetate, and hydrogen production pathways for 19 measured metabolites spanning a library of 19 distinct single and multiple gene knockout mutants along with 18 intracellular metabolite concentration data for a Δgldh mutant and ten experimentally measured Michaelis–Menten kinetic parameters. Conclusions. The k-ctherm118 model captures significant metabolic changes caused by (1) nitrogen limitation leading to increased yields for lactate, pyruvate, and amino acids, and (2) ethanol stress causing an increase in intracellular sugar phosphate concentrations (~1.5-fold) due to upregulation of cofactor pools. Robustness analysis of k-ctherm118 alludes to the presence of a secondary activity of ketol-acid reductoisomerase and possible regulation by valine and/or leucine pool levels. In addition, cross-validation and robustness analysis allude to missing elements in k-ctherm118 and suggest additional experiments to improve kinetic model prediction fidelity. Overall, the study quantitatively assesses the advantages of EM-based kinetic modeling towards improved prediction of C. thermocellum metabolism and develops a predictive kinetic model which can be used to design biofuel-overproducing strains.},

  doi          = {10.1186/s13068-017-0792-2},

  journal      = {Biotechnology for Biofuels},

  number       = 1,

  volume       = 10,

  place        = {Netherlands},

  year         = {Tue May 02 00:00:00 EDT 2017},

  month        = {Tue May 02 00:00:00 EDT 2017}

}

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