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Genome-Scale Metabolic Model Accurately Predicts Fermentation of Glucose by Chromochloris zofingiensis

Michelle Meagher, Alex Metcalf, S. Alex Ramsey, Walter Prentice, Nanette R. Boyle
doi: https://doi.org/10.1101/2021.06.22.449518
Michelle Meagher
Chemical and Biological Engineering Department, Colorado School of Mines, Golden, CO
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Alex Metcalf
Chemical and Biological Engineering Department, Colorado School of Mines, Golden, CO
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S. Alex Ramsey
Chemical and Biological Engineering Department, Colorado School of Mines, Golden, CO
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Walter Prentice
Chemical and Biological Engineering Department, Colorado School of Mines, Golden, CO
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Nanette R. Boyle
Chemical and Biological Engineering Department, Colorado School of Mines, Golden, CO
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  • For correspondence: nboyle@mines.edu
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Abstract

Algae have the potential to be sources of renewable fuels and chemicals. One particular strain, Chromochloris zofingiensis, is of interest due to the co-production of triacylglycerols (TAGs) and astaxanthin, a valuable nutraceutical. To aid in future engineering efforts, we have developed the first genome-scale metabolic model on C. zofingiensis, iChr1915. This model includes 1915 genes, 3413 metabolic reactions and 2652 metabolites. We performed detailed biomass composition analysis for three growth conditions: autotrophic, mixotrophic and heterotrophic and used this data to develop biomass formation equations for each growth condition. The completed model was then used to predict flux distributions for each growth condition; interestingly, for heterotrophic growth, the model predicts the excretion of fermentation products due to overflow metabolism. We confirmed this experimentally via metabolomics of spent medium and fermentation product assays. An in silico gene essentiality analysis was performed on this model, as well as a flux variability analysis to test the production capabilities of this organism. In this work, we present the first genome scale metabolic model of C. zofingiensis and demonstrate its use predicting metabolic activity in different growth conditions, setting up a foundation for future metabolic engineering studies in this organism.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • we quantified the production of lactate in the cell and revised the flux maps to match

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted November 22, 2021.
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Genome-Scale Metabolic Model Accurately Predicts Fermentation of Glucose by Chromochloris zofingiensis
Michelle Meagher, Alex Metcalf, S. Alex Ramsey, Walter Prentice, Nanette R. Boyle
bioRxiv 2021.06.22.449518; doi: https://doi.org/10.1101/2021.06.22.449518
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Genome-Scale Metabolic Model Accurately Predicts Fermentation of Glucose by Chromochloris zofingiensis
Michelle Meagher, Alex Metcalf, S. Alex Ramsey, Walter Prentice, Nanette R. Boyle
bioRxiv 2021.06.22.449518; doi: https://doi.org/10.1101/2021.06.22.449518

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