Genome-Based Metabolic Mapping and 13C Flux Analysis Reveal Systematic Properties of an Oleaginous Microalga Chlorella protothecoides
Abstract
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. 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. 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.
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Wu et al. (2014) found key metabolite concentrations, including ATP and acetyl-CoA, elevated under heterotrophic conditions.
“Optimal conditions for biomass and fatty acid production were identified, with key metabolite concentrations, including ATP and acetyl-CoA, elevated under heterotrophic conditions.”
From Harnessing Artificial Intelligence to Revolutionize Microalgae Biotechnology: Unlocking Sustainable Solutions for High-Value Compounds and Carbon Neutrality (2025) · cites this paper as [51]
Nonstationary 13C flux analysis revealed low photorespiration in phototrophic cells and high TCA cycle activity in heterotrophic cells.
“Nonstationary 13C flux analysis revealed low photorespiration in phototrophic cells and high TCA cycle activity in heterotrophic cells.”
From Harnessing Artificial Intelligence to Revolutionize Microalgae Biotechnology: Unlocking Sustainable Solutions for High-Value Compounds and Carbon Neutrality (2025) · cites this paper as [51]
Wu et al. (2014) reconstructed metabolic network of C. protothecoides included 272 reactions, enabling simulations of phototrophic and heterotrophic growth.
“The reconstructed metabolic network included 272 reactions, enabling simulations of phototrophic and heterotrophic growth.”
From Harnessing Artificial Intelligence to Revolutionize Microalgae Biotechnology: Unlocking Sustainable Solutions for High-Value Compounds and Carbon Neutrality (2025) · cites this paper as [51]
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“Interestingly, inhibition of photosynthesis by elevated CO2 was reported in other eukaryotic algae, such as C. reinhardtii (Yang and Gao, 2003) and Chlorococcum littorale (Satoh et al., 2001).”
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Jagadevan, S., Banerjee, A., Banerjee, C., Guria, C., Tiwari, R., Baweja, M., & Shukla, P. (2018) · Biotechnology for Biofuels · doi:10.1186/s13068-018-1181-1 · Cited by 275 · see citing works
Genetic engineering of microalgae for enhanced biorefinery capabilities
Fayyaz, M., Chew, K. W., Show, P. L., Ling, T. C., Ng, I.-S., & Chang, J.-S. (2020) · Biotechnology Advances · doi:10.1016/j.biotechadv.2020.107554 · Cited by 225 · see citing works
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Tibocha-Bonilla, J. D., Zuñiga, C., Godoy-Silva, R. D., & Zengler, K. (2018) · Biotechnology for Biofuels · doi:10.1186/s13068-018-1244-3 · Cited by 84 · see citing works
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- Authors
- Wu, C., Xiong, W., Dai, J., & Wu, Q.
- Affiliations
- Ministry of Education Key Laboratory of Bioinformatics, School of Life Sciences, Tsinghua University, Beijing 100084, China (C.W., W.X., J. D., Q.W.); and
- Venue
- Plant Physiology
- Publisher
- Oxford University Press (OUP)
- Published
- 2014-12-15
- Volume
- 167
- Issue
- 2
- Pages
- 586-599
- ISSN
- 1532-2548
- Cited by
- 99
- References
- 4
- Language
- en
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