Format

Send to

Choose Destination
See comment in PubMed Commons below
Mol Syst Biol. 2011 Aug 2;7:518. doi: 10.1038/msb.2011.52.

Metabolic network reconstruction of Chlamydomonas offers insight into light-driven algal metabolism.

Author information

1
Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA.

Abstract

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. Integrating biological and optical data, we reconstructed a genome-scale metabolic network for this alga and devised a novel light-modeling approach that enables quantitative growth prediction for a given light source, resolving wavelength and photon flux. We experimentally verified transcripts accounted for in the network and physiologically validated model function through simulation and generation of new experimental growth data, providing high confidence in network contents and predictive applications. The network offers insight into algal metabolism and potential for genetic engineering and efficient light source design, a pioneering resource for studying light-driven metabolism and quantitative systems biology.

PMID:
21811229
PMCID:
PMC3202792
DOI:
10.1038/msb.2011.52
[Indexed for MEDLINE]
Free PMC Article
PubMed Commons home

PubMed Commons

0 comments
How to join PubMed Commons

    Supplemental Content

    Full text links

    Icon for HighWire Icon for PubMed Central
    Loading ...
    Support Center