Aiding Algae Development

Researchers reconstruct the genome scale metabolic network for a model alga strain
By Erin Voegele | September 20, 2011

A project led by Roger Chang, a Ph.D. candidate in the bioinformatics and systems biology program at the University of California-San Diego, could lead to significant benefits for the algae biofuels industry. Chang and his colleagues have reconstructed the genome scale metabolic network for the model alga species Chlamydomonas reinhardtii. The results of the project where recently published in the scientific journal Molecular Systems Biology.

“We did this by integrating functional annotation of its genome as well as using sequence-based analysis and literature curation and large-scale transcript verification experiments,” Chang says. “While we were doing this, we gave special attention to precise representation of photon usage, and also chemical accuracy of representing lipid species.”

According Chang, prior research has well-established that these metabolic network reconstructions and computational methods have become instrumental in engineering efforts, both in terms of developing production strains and for developing bioreactors. “Using computer-aided approaches like this enables prediction of specific genetic manipulations that can be used to increase production of desirable chemical products and also productions of more cost-effective growth conditions for these strains and industrial applications,” he says. “Where our network fits in is that it’s the first such network to be developed for a eukaryotic algae. So, it sort of represents establishing these sorts of capabilities within the study of eukaryotic algae. It’s also the first to enable specifically the analysis of light source parameters that are used for growth.”

It is unlikely that Chlamydomonas reinhardtii will be used to generate production strains, Chang notes, because it is a laboratory model species. Other known strains of algae are known to be more productive. “As a model eukaryotic algae, the most knowledge exists for this system, which is why we chose it in the first place,” he adds. “Having enabled computer-aided analysis of metabolism in this alga, we expect it to serve as a development platform for the whole industry, and likely set sort of a new precedent for incorporating computational analysis into engineering designs for biofuels, whether it be for this species, or other alga, or other photosynthetic species.” 

—Erin Voegele