Modeling

To model the growth and lipid production of Chlorella vulgaris we used the Constraint-Based Modelling, being our principal tool the kit the COBRApy library offers ¹. The metabolic reconstruction we used was that of Chlorella vulgaris UTEX 395, published on July of this year ². This reconstruction is based on Chlamydomonas reinhardii, with experimental and bioinformatic data on the literature.

It includes 843 out of 7,100 annotated genes (around 12%), delineating 1,770 metabolites and 2,294 reactions, being the amino acid and lipid metabolisms the most accurately reconstructed ². Importantly the authors of this model report that the uptake rates were experimentally verified experimentally.

First, we analyzed which light wavelength was the best for the overall growth of the algae according to the metabolic model. When comparing different type of lights in the metabolic model, we couldn't find a notorious difference between the different light sources, while in the literature it is reported that the best light for growing Chlorella on long periods is the blue one (wavelength of 475 nm)

With this, we can see that if you optimize the light conditions in a rank; you can obtain the same biomass production values, independently from your initial light source.

Solar Light

Solar Light (Optimized)

Growthroom light comparison wt-optimized

With Growth room light search optimal intensity

Then, we analyzed the resources and nutrients for the culture. We simulated more water and carbon sources in the medium. Also we tried the effect of oxygen, given that it is present in small quantities, because we were not able to get a sealed biorreactor. For the water and oxygen simulations, we used the photoautotroph model, while for the carbon source (acetate) we used the heterotroph one. The plots of these experiments are below.

Referencias:

1. Ebrahim, A., Lerman, J. A., Palsson, B. O., & Hyduke, D. R. (2013). COBRApy: constraints-based reconstruction and analysis for python. BMC systems biology, 7(1), 74.

2. Zuñiga, C., Li, C. T., Huelsman, T., Levering, J., Zielinski, D. C., McConnell, B. O., ... & Betenbaugh, M. J. (2016). Genome-scale metabolic model for the green alga Chlorella vulgaris UTEX 395 accurately predicts phenotypes under autotrophic, heterotrophic, and mixotrophic growth conditions. Plant Physiology, pp-00593.

3. Blair, M. F., Kokabian, B., & Gude, V. G. (2014). Light and growth medium effect on Chlorella vulgaris biomass production. Journal of environmental chemical engineering, 2(1), 665-674.