Abstract
In this study, a metabolic network describing the
primary metabolism of Chlamydomonas reinhardtii was
constructed. By performing chemostat experiments at different
growth rates, energy parameters for maintenance and biomass
formation were determined. The chemostats were run at
low irradiances resulting in a high biomass yield on light of
1.25 g mol-1. The ATP requirement for biomass formation
from biopolymers (Kx) was determined to be 109 mmol g-1
(18.9 mol mol-1) and the maintenance requirement (mATP)
was determined to be 2.85 mmol g-1 h-1. With these energy
requirements included in the metabolic network, the
network accurately describes the primary metabolism of C.
reinhardtii and can be used for modeling of C. reinhardtii
growth and metabolism. Simulations confirmed that
cultivating microalgae at low growth rates is unfavorable
because of the high maintenance requirements which
result in low biomass yields. At high light supply rates,
biomass yields will decrease due to light saturation
effects. Thus, to optimize biomass yield on light energy
in photobioreactors, an optimum between low and high
light supply rates should be found. These simulations
show that metabolic flux analysis can be used as a tool
to gain insight into the metabolism of algae and
ultimately can be used for the maximization of algal
biomass and product yield.
Original language | English |
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Pages (from-to) | 253-266 |
Journal | Journal of Applied Phycology |
Volume | 24 |
Issue number | 2 |
DOIs | |
Publication status | Published - 2012 |
Keywords
- genome-scale reconstruction
- escherichia-coli
- chlorophyll fluorescence
- chlorella-sorokiniana
- quantum requirement
- light
- photosynthesis
- microalgae
- network
- photobioreactor