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Title: Predicting Dynamic Metabolic Demands in the Photosynthetic Eukaryote Chlorella vulgaris

Journal Article · · Plant Physiology (Bethesda)
DOI:https://doi.org/10.1104/pp.17.00605· OSTI ID:1395182

Phototrophic organisms exhibit a highly dynamic proteome, adapting their biomass composition in response to diurnal light/dark cycles and nutrient availability. Here, we used experimentally determined biomass compositions over the course of growth to determine and constrain the biomass objective function (BOF) in a genome-scale metabolic model of Chlorella vulgaris UTEX 395 over time. Changes in the BOF, which encompasses all metabolites necessary to produce biomass, influence the state of the metabolic network thus directly affecting predictions. Simulations using dynamic BOFs predicted distinct proteome demands during heterotrophic or photoautotrophic growth. Model-driven analysis of extracellular nitrogen concentrations and predicted nitrogen uptake rates revealed an intracellular nitrogen pool, which contains 38% of the total nitrogen provided in the medium for photoautotrophic and 13% for heterotrophic growth. Agreement between flux and gene expression trends was determined by statistical comparison. Accordance between predicted flux trends and gene expression trends was found for 65% of multisubunit enzymes and 75% of allosteric reactions. Reactions with the highest agreement between simulations and experimental data were associated with energy metabolism, terpenoid biosynthesis, fatty acids, nucleotides, and amino acid metabolism. Furthermore, predicted flux distributions at each time point were compared with gene expression data to gain new insights into intracellular compartmentalization, specifically for transporters. A total of 103 genes related to internal transport reactions were identified and added to the updated model of C. vulgaris, iCZ946, thus increasing our knowledgebase by 10% for this model green alga.

Research Organization:
National Renewable Energy Laboratory (NREL), Golden, CO (United States); Johns Hopkins Univ., Baltimore, MD (United States)
Sponsoring Organization:
USDOE Office of Science (SC), Biological and Environmental Research (BER); National Science Foundation (NSF); USDOE Office of Energy Efficiency and Renewable Energy (EERE)
Grant/Contract Number:
SC0012658; AC36-08GO28308; 1332344
OSTI ID:
1395182
Alternate ID(s):
OSTI ID: 1399847; OSTI ID: 1485589
Report Number(s):
NREL/JA-5100-70303; /plantphysiol/176/1/450.atom
Journal Information:
Plant Physiology (Bethesda), Journal Name: Plant Physiology (Bethesda) Vol. 176 Journal Issue: 1; ISSN 0032-0889
Publisher:
American Society of Plant BiologistsCopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 44 works
Citation information provided by
Web of Science

Figures / Tables (6)