A refined genome-scale reconstruction of Chlamydomonas metabolism provides a platform for systems-level analyses

Imam, Saheed; Schäuble, Sascha; Valenzuela, Jacob; Lopez Garcia de Lomana, Adrian; Carter, Warren; Price, Nathan D.; Baliga, Nitin S.

doi:10.1111/tpj.13059

Title: A refined genome-scale reconstruction of Chlamydomonas metabolism provides a platform for systems-level analyses

Journal Article · Tue Oct 20 00:00:00 EDT 2015 · The Plant Journal

DOI:https://doi.org/10.1111/tpj.13059· OSTI ID:1378660

Imam, Saheed ^[1]; Schäuble, Sascha ^[2]; Valenzuela, Jacob ^[1]; Lopez Garcia de Lomana, Adrian ^[1]; Carter, Warren ^[1]; Price, Nathan D. ^[3]; Baliga, Nitin S. ^[4]

Institute for Systems Biology, Seattle, WA (United States)
Institute for Systems Biology, Seattle, WA (United States); Friedrich-Schiller-Univ. Jena, Jena (Germany)
Institute for Systems Biology, Seattle, WA (United States); Univ. of Washington, Seattle, WA (United States)
Institute for Systems Biology, Seattle, WA (United States); Univ. of Washington, Seattle, WA (United States); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

Microalgae have reemerged as organisms of prime biotechnological interest due to their ability to synthesize a suite of valuable chemicals. To harness the capabilities of these organisms, we need a comprehensive systems-level understanding of their metabolism, which can be fundamentally achieved through large-scale mechanistic models of metabolism. In this study, we present a revised and significantly improved genome-scale metabolic model for the widely-studied microalga, Chlamydomonas reinhardtii. The model, iCre1355, represents a major advance over previous models, both in content and predictive power. iCre1355 encompasses a broad range of metabolic functions encoded across the nuclear, chloroplast and mitochondrial genomes accounting for 1355 genes (1460 transcripts), 2394 and 1133 metabolites. We found improved performance over the previous metabolic model based on comparisons of predictive accuracy across 306 phenotypes (from 81 mutants), lipid yield analysis and growth rates derived from chemostat-grown cells (under three conditions). Measurement of macronutrient uptake revealed carbon and phosphate to be good predictors of growth rate, while nitrogen consumption appeared to be in excess. We analyzed high-resolution time series transcriptomics data using iCre1355 to uncover dynamic pathway-level changes that occur in response to nitrogen starvation and changes in light intensity. This approach enabled accurate prediction of growth rates, the cessation of growth and accumulation of triacylglycerols during nitrogen starvation, and the temporal response of different growth-associated pathways to increased light intensity. Thus, iCre1355 represents an experimentally validated genome-scale reconstruction of C. reinhardtii metabolism that should serve as a useful resource for studying the metabolic processes of this and related microalgae.

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Research Organization:: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)

Sponsoring Organization:: USDOE Office of Science (SC)

Grant/Contract Number:: AC02-05CH11231

OSTI ID:: 1378660

Journal Information:: The Plant Journal, Vol. 84, Issue 6; ISSN 0960-7412

Publisher:: Society for Experimental BiologyCopyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 45 works

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59 BASIC BIOLOGICAL SCIENCES
60 APPLIED LIFE SCIENCES
metabolic modeling
Chlamydomonas reinhardtii
constraint-based analysis
flux balance analysis
data integration
systems biology
biomass
lipid accumulation
photosynthesis

Title: A refined genome-scale reconstruction of Chlamydomonas metabolism provides a platform for systems-level analyses

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