01/01/2011
New Insights on Algal Metabolism
The Science
Photosynthetic algae are a potential bioenergy source; however, significant unknowns about their basic metabolic properties have hindered development of algae for biofuel production. DOE researchers now present a new metabolic network reconstruction and a genome-scale model of light-driven metabolism for the alga Chlamydomonas reinhardtii. This approach represents a significant advance over previous metabolic models for this organism since it incorporates greatly improved functional gene annotations, experimental validation of gene expression, and quantitative reaction measurements under different light conditions. This model allows enhanced understanding and prediction of photosynthetic growth properties (including lipid synthesis) under varying conditions and provides a broad knowledgebase of potential targets for directed metabolic engineering. This publication was featured in the Editor’s Choice section of the August 12th issue of Science.
Summary
Metabolic network reconstruction encompasses existing knowledge about an organism’s metabolism and genome annotation, providing a platform for omics data analysis and phenotype prediction. The model alga Chlamydomonas reinhardtii is employed to study diverse biological processes from photosynthesis to phototaxis. Recent heightened interest in this species results from an international movement to develop algal biofuels.
BER Program Manager
Dawn Adin
U.S. Department of Energy, Biological and Environmental Research (SC-33)
Biological Systems Science Division
[email protected]
References
Chang, R. L., L. Ghamsari, A. Manichaikul, E. F. Hom, S. Balaji, W. Fu, Y. Shen, T. Hao, B. Palsson, K. Salehi-Ashtiani, and J. A. Papin. 2011. “Metabolic Network Reconstruction of Chlamydomonas Offers Insight into Light-Driven Algal Metabolism,” Molecular Systems Biology 7:518. DOI:10.1038/msb.2011.52.