In silico strategies to couple production of bioethanol with growth in cyanobacteria

Cyanobacteria have been considered as promising candidates for sustainable bioproduction from inexpensive raw materials, as they grow on light, carbon dioxide, and minimal inorganic nutrients. In this study, we present a genome‐scale metabolic network model for Synechocystis sp. PCC 6803 and study t...

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Bibliographic Details
Published in:Biotechnology and bioengineering 2019-08, Vol.116 (8), p.2061-2073
Main Authors: Lasry Testa, Romina, Delpino, Claudio, Estrada, Vanina, Diaz, Soledad M.
Format: Article
Language:English
Subjects:
bilevel programming
bioethanol
Biofuels
Carbon dioxide
coupled mutant
Coupling
Cyanobacteria
Ethanol
Ethanol - metabolism
Gene Knockout Techniques
Genomes
genome‐scale metabolic model
Industrial Microbiology
Metabolic networks
Metabolic Networks and Pathways
Microorganisms, Genetically-Modified
Mixed integer
Models, Biological
Mutants
Nutrients
Raw materials
strain design
Synechocystis - genetics
Synechocystis - metabolism
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Summary:Cyanobacteria have been considered as promising candidates for sustainable bioproduction from inexpensive raw materials, as they grow on light, carbon dioxide, and minimal inorganic nutrients. In this study, we present a genome‐scale metabolic network model for Synechocystis sp. PCC 6803 and study the optimal design of the strain for ethanol production by using a mixed integer linear problem reformulation of a bilevel programming problem that identifies gene knockouts which lead to coupling between growth and product synthesis. Five mutants were found, where the in silico model predicts coupling between biomass growth and ethanol production in photoautotrophic conditions. The best mutant gives an in silico ethanol production of 1.054 mmol·gDW −1·h −1. Rational design of growth‐coupled ethanol producing strains of the cyanobacteria Synechocystis sp. PCC 6803 was performed in silico by applying bilevel optimization techniques to a genome‐ scale metabolic network model. Solutions that couple ethanol production to growth were identified and evaluated with MOMA and in a bioreactor model, with positive results that encourage the in vivo implementation of the coupled mutants for photoautotrophic production of fourth generation biofuels.
ISSN:0006-3592
1097-0290
DOI:10.1002/bit.26998