INVESTIGADORES
DIAZ Maria Soledad
congresos y reuniones científicas
Título:
An MILP approach to the optimization of cyanobacteria metabolic network for bioethanol production
Autor/es:
CECILIA I. PAULO; VANINA G. ESTRADA; JIMENA DI MAGGIO; MARIA SOLEDAD DIAZ
Lugar:
Salt Lake City
Reunión:
Congreso; American Institute of Chemical Engineers Annual Meeting; 2010
Resumen:
Different alternatives to fossil fuels are currently being studied to reduce the
dependence on non-renewable resources. Biofuels constitute relevant sustainable
complements and/or substitutes to petroleum fuels due to energy security reasons,
environmental concerns, foreign exchange savings, and socioeconomic issues related
to the rural sector. The most common renewable fuel is ethanol derived from corn
grain and sugar cane (sucrose). The use of lignocellulosic biomass is an attractive
alternative, as second generation pathways for bioethanol production. On the other
hand, third generation biofuels are obtained through algae. Cyanobacteria are an
abundant and diverse group of ancient autotrophic prokaryotes that perform oxygenic
photosynthesis; they played a crucial role in the change of reductive to oxidative
atmosphere in the Precambrian period. Cyanobacteria live in freshwater, marine and
terrestrial environments and show a wide diversity of morphologies, metabolisms and
cell structures, they have several features that make them attractive to obtain
commercial interest products in pharmaceutical, nutraceutical, biofuels, and other
industries. They reach high cellular densities in culture and have simple growth
requirements: light, carbon dioxide, and other inorganic nutrients to growth. Few
authors have studied ethanol production from cyanobacteria (Deng & Coleman, 1998;
Dexter & Fu, 2009). Ethanol production through cyanobacteria allows the coupling of
energy production with the capture of industrial carbon dioxide emissions to reduce
greenhouse gasses pollution, without competing with food production. However,
current reported ethanol yields still require improvement to make this technology
economically attractive. For cost-effective production of ethanol, the metabolic
pathways involved in its generation must be engineered and optimized. Advances in
metabolic engineering and synthetic biology based on gene sequence, biochemical
and physiological data availability in public databases with the constant improvement
of the mathematical tools can help to accelerate the development of desired
phenotypes for the production of economically viable biofuels (Lee et al. 2008;
Picataggio, 2009). In this work, we formulate a mixed-integer linear programming
model to represent gene deletions in a metabolic network for the recombinant
cyanobacteria Synechocystis sp. strain PCC6803 to maximize ethanol production,
while maximizing biomass growth. The model includes more than 800 reactions from
the glycolysis, the pentose phosphate pathway, citric acid cycle and Calvin cycle, and
gene insertions corresponding to pyruvate decarboxylase (pdc) and alcohol
dehydrogenase II (adhII) from obligately Zymomonas mobilis into Synechocystis sp.
strain PCC6803 (Dexter and Fu, 2009) to enable the ethanol producing pathway. The
model has been implemented in GAMS (Brooke et al., 1997) and solved with CPLEX.
Numerical results provide useful insights on understanding of cellular metabolism as
well as designing of metabolic engineering strategies for ethanol production using
carbon dioxide as carbon source.