Reconstruction, verification and in-silico analysis of a genome-scale metabolic model of bacterial cellulose producing Komagataeibacter xylinus.

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ID: 90902
2020
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Abstract
In this study, a comprehensive genome-scale metabolic network of Komagataeibacter xylinus as the model microorganism was reconstructed based on genome annotation, for better understanding of metabolic growth and biosynthesis of bacterial cellulose (BC). The reconstructed network included 640 genes, 783 metabolic reactions and 865 metabolites. The model was completely successful to predict the lack of growth under anaerobic conditions. Model validation by the data for the growth of acetic acid bacteria with ethanol-limited chemostat cultures showed that there is a good agreement for the O and CO fluxes with actual growth conditions. Then the model was used to forecast the simultaneous production of BC and by-products. The obtained data showed that the rate of BC production is consistent with experimental data with an accuracy of 93.7%. Finally, the study of flux balance analysis (FBA) data showed that the pentose phosphate pathway and the TCA cycle play an important role in growth-promoting metabolism in K. xylinus and have a close relationship with BC biosynthesis. By integrating this model with various metabolic engineering and systems biology tools in the future, it is possible to overcome the common challenges in the large-scale BC production, such as low yield and productivity.
Reference Key
rezazadeh2020reconstructionbioprocess Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Rezazadeh, Mohammad;Babaeipour, Valiollah;Motamedian, Ehsan;
Journal Bioprocess and biosystems engineering
Year 2020
DOI
10.1007/s00449-020-02299-4
URL
Keywords
flux balance analysis bacterial cellulose komagataeibacter xylinus genome scale metabolic model

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