Dynamic metabolic modeling of heterotrophic and mixotrophic microalgal growth on fermentative wastes
Résumé
Microalgae are promising microorganisms for the production of numerous molecules of
interest, such as pigments, proteins or triglycerides that can be turned into biofuels. Heterotrophic
or mixotrophic growth on fermentative wastes represents an interesting approach to
achieving higher biomass concentrations, while reducing cost and improving the environmental
footprint. Fermentative wastes generally consist of a blend of diverse molecules and
it is thus crucial to understand microalgal metabolism in such conditions, where switching
between substrates might occur. Metabolic modeling has proven to be an efficient tool for
understanding metabolism and guiding the optimization of biomass or target molecule production.
Here, we focused on the metabolism of Chlorella sorokiniana growing heterotrophically
and mixotrophically on acetate and butyrate. The metabolism was represented by 172
metabolic reactions. The DRUM modeling framework with a mildly relaxed quasi-steadystate
assumption was used to account for the switching between substrates and the presence
of light. Nine experiments were used to calibrate the model and nine experiments for
the validation. The model efficiently predicted the experimental data, including the transient
behavior during heterotrophic, autotrophic, mixotrophic and diauxic growth. It shows that an
accurate model of metabolism can now be constructed, even in dynamic conditions, with
the presence of several carbon substrates. It also opens new perspectives for the heterotrophic
and mixotrophic use of microalgae, especially for biofuel production from wastes.
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