Abstract
| Original language | English |
|---|---|
| Pages (from-to) | 253-266 |
| Journal | Journal of Applied Phycology |
| Volume | 24 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - 2012 |
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Keywords
- genome-scale reconstruction
- escherichia-coli
- chlorophyll fluorescence
- chlorella-sorokiniana
- quantum requirement
- light
- photosynthesis
- microalgae
- network
- photobioreactor
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Metabolic modeling of Chlamydomonas reinhardtii: energy requirements for photoautotrophic growth and maintenance. / Kliphuis, A.M.J.; Klok, A.J.; Martens, D.E.; Lamers, P.P.; Janssen, M.G.J.; Wijffels, R.H.
In: Journal of Applied Phycology, Vol. 24, No. 2, 2012, p. 253-266.Research output: Contribution to journal › Article › Academic › peer-review
TY - JOUR
T1 - Metabolic modeling of Chlamydomonas reinhardtii: energy requirements for photoautotrophic growth and maintenance
AU - Kliphuis, A.M.J.
AU - Klok, A.J.
AU - Martens, D.E.
AU - Lamers, P.P.
AU - Janssen, M.G.J.
AU - Wijffels, R.H.
PY - 2012
Y1 - 2012
N2 - 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.
AB - 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.
KW - genome-scale reconstruction
KW - escherichia-coli
KW - chlorophyll fluorescence
KW - chlorella-sorokiniana
KW - quantum requirement
KW - light
KW - photosynthesis
KW - microalgae
KW - network
KW - photobioreactor
U2 - 10.1007/s10811-011-9674-3
DO - 10.1007/s10811-011-9674-3
M3 - Article
VL - 24
SP - 253
EP - 266
JO - Journal of Applied Phycology
JF - Journal of Applied Phycology
SN - 0921-8971
IS - 2
ER -