Genome-Based Metabolic Mapping and 13C Flux Analysis Reveal Systematic Properties of an Oleaginous Microalga Chlorella protothecoides
Abstract
We report that integrated and genome-based flux balance analysis, metabolomics, and 13C-label profiling of phototrophic and heterotrophic metabolism in Chlorella protothecoides, an oleaginous green alga for biofuel. The green alga Chlorella protothecoides, capable of autotrophic and heterotrophic growth with rapid lipid synthesis, is a promising candidate for biofuel production. Based on the newly available genome knowledge of the alga, we reconstructed the compartmentalized metabolic network consisting of 272 metabolic reactions, 270 enzymes, and 461 encoding genes and simulated the growth in different cultivation conditions with flux balance analysis. Phenotype-phase plane analysis shows conditions achieving theoretical maximum of the biomass and corresponding fatty acid-producing rate for phototrophic cells (the ratio of photon uptake rate to CO2 uptake rate equals 8.4) and heterotrophic ones (the glucose uptake rate to O2 consumption rate reaches 2.4), respectively. Isotope-assisted liquid chromatography-mass spectrometry/mass spectrometry reveals higher metabolite concentrations in the glycolytic pathway and the tricarboxylic acid cycle in heterotrophic cells compared with autotrophic cells. We also observed enhanced levels of ATP, nicotinamide adenine dinucleotide (phosphate), reduced, acetyl-Coenzyme A, and malonyl-Coenzyme A in heterotrophic cells consistently, consistent with a strong activity of lipid synthesis. To profile the flux map in experimental conditions, we applied nonstationary 13C metabolicmore »
- Authors:
-
- Tsinghua Univ., Beijing (China). Ministry of Education Key Lab. of Bioinformatics; National Renewable Energy Lab. (NREL), Golden, CO (United States). Biosciences Center
- Publication Date:
- Research Org.:
- National Renewable Energy Laboratory (NREL), Golden, CO (United States)
- Sponsoring Org.:
- NREL Director's Postdoc Fellowship; National Natural Science Foundation of China (NSFC)
- OSTI Identifier:
- 1220638
- Report Number(s):
- NREL/JA-2700-63117
Journal ID: ISSN 0032-0889
- Grant/Contract Number:
- AC36-08GO28308; 31370282; 41030210; 2012Z08128
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Plant Physiology (Bethesda)
- Additional Journal Information:
- Journal Name: Plant Physiology (Bethesda); Journal Volume: 167; Journal Issue: 2; Journal ID: ISSN 0032-0889
- Publisher:
- American Society of Plant Biologists
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 09 BIOMASS FUELS; flux balance analysis; green algae; LC-MS mediated metabolomics; metabolic network reconstruction; non-stationary 13C flux analysis
Citation Formats
Wu, Chao, Xiong, Wei, Dai, Junbiao, and Wu, Qingyu. Genome-Based Metabolic Mapping and 13C Flux Analysis Reveal Systematic Properties of an Oleaginous Microalga Chlorella protothecoides. United States: N. p., 2014.
Web. doi:10.1104/pp.114.250688.
Wu, Chao, Xiong, Wei, Dai, Junbiao, & Wu, Qingyu. Genome-Based Metabolic Mapping and 13C Flux Analysis Reveal Systematic Properties of an Oleaginous Microalga Chlorella protothecoides. United States. https://doi.org/10.1104/pp.114.250688
Wu, Chao, Xiong, Wei, Dai, Junbiao, and Wu, Qingyu. Mon .
"Genome-Based Metabolic Mapping and 13C Flux Analysis Reveal Systematic Properties of an Oleaginous Microalga Chlorella protothecoides". United States. https://doi.org/10.1104/pp.114.250688. https://www.osti.gov/servlets/purl/1220638.
@article{osti_1220638,
title = {Genome-Based Metabolic Mapping and 13C Flux Analysis Reveal Systematic Properties of an Oleaginous Microalga Chlorella protothecoides},
author = {Wu, Chao and Xiong, Wei and Dai, Junbiao and Wu, Qingyu},
abstractNote = {We report that integrated and genome-based flux balance analysis, metabolomics, and 13C-label profiling of phototrophic and heterotrophic metabolism in Chlorella protothecoides, an oleaginous green alga for biofuel. The green alga Chlorella protothecoides, capable of autotrophic and heterotrophic growth with rapid lipid synthesis, is a promising candidate for biofuel production. Based on the newly available genome knowledge of the alga, we reconstructed the compartmentalized metabolic network consisting of 272 metabolic reactions, 270 enzymes, and 461 encoding genes and simulated the growth in different cultivation conditions with flux balance analysis. Phenotype-phase plane analysis shows conditions achieving theoretical maximum of the biomass and corresponding fatty acid-producing rate for phototrophic cells (the ratio of photon uptake rate to CO2 uptake rate equals 8.4) and heterotrophic ones (the glucose uptake rate to O2 consumption rate reaches 2.4), respectively. Isotope-assisted liquid chromatography-mass spectrometry/mass spectrometry reveals higher metabolite concentrations in the glycolytic pathway and the tricarboxylic acid cycle in heterotrophic cells compared with autotrophic cells. We also observed enhanced levels of ATP, nicotinamide adenine dinucleotide (phosphate), reduced, acetyl-Coenzyme A, and malonyl-Coenzyme A in heterotrophic cells consistently, consistent with a strong activity of lipid synthesis. To profile the flux map in experimental conditions, we applied nonstationary 13C metabolic flux analysis as a complementing strategy to flux balance analysis. We found that the result reveals negligible photorespiratory fluxes and a metabolically low active tricarboxylic acid cycle in phototrophic C. protothecoides. In comparison, high throughput of amphibolic reactions and the tricarboxylic acid cycle with no glyoxylate shunt activities were measured for heterotrophic cells. Lastly, taken together, the metabolic network modeling assisted by experimental metabolomics and 13C labeling better our understanding on global metabolism of oleaginous alga, paving the way to the systematic engineering of the microalga for biofuel production.},
doi = {10.1104/pp.114.250688},
journal = {Plant Physiology (Bethesda)},
number = 2,
volume = 167,
place = {United States},
year = {Mon Dec 15 00:00:00 EST 2014},
month = {Mon Dec 15 00:00:00 EST 2014}
}
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