Advances in metabolic modeling of oleaginous microalgae
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Production of biofuels and bioenergy precursors by phototrophic microorganisms, such as microalgae and cyanobacteria, is a promising alternative to conventional fuels obtained from non-renewable resources. Several species of microalgae have been investigated as potential candidates for the production of biofuels, for the most part due to their exceptional metabolic capability to accumulate large quantities of lipids. Constraint-based modeling, a systems biology approach that accurately predicts the metabolic phenotype of phototrophs, has been deployed to identify suitable culture conditions as well as to explore genetic enhancement strategies for bioproduction. Core metabolic models were employed to gain insight into the central carbon metabolism in photosynthetic microorganisms. More recently, comprehensive genome-scale models, including organelle-specific information at high resolution, have been developed to gain new insight into the metabolism of phototrophic cell factories. Here, we review the current state of the art of constraint-based modeling and computational method development and discuss how advanced models led to increased prediction accuracy and thus improved lipid production in microalgae.
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Mathematical models for optimising the cultivation processes of microalgae, such as dynamic flux balance analysis (DFBA), allow the prediction of the effects of changes in illumination and other conditions on the composition of metabolites.
“Mathematical models for optimising the cultivation processes of microalgae, such as dynamic flux balance analysis (DFBA), allow the prediction of the effects of changes in illumination and other conditions on the composition of metabolites [106].”
From Multi-Sensing Monitoring of the Microalgae Biomass Cultivation Systems for Biofuels and Added Value Products Synthesis—Challenges and Opportunities (2025) · cites this paper as [106]
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Microalgae with Artificial Intelligence: A Digitalized Perspective on Genetics, Systems and Products
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Lipids from Microalgae for Cosmetic Applications
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“Genera of microalgae used for biofuel production are Chlamydomonas, Chlorella, Nannochloropsis, Synechocystis, Tetraselmis, Monoraphidium, Ostreococcus, Tisochrysis, and Phaeodactylum [32].”
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- Authors
- Tibocha-Bonilla, J. D., Zuñiga, C., Godoy-Silva, R. D., & Zengler, K.
- Affiliations
- University of California San Diego (US)
- Corresponding author
- Zengler, Karsten
- ORCID
- Zengler, Karsten
- Venue
- Biotechnology for Biofuels
- Published
- 2018-09-05
- Volume
- 11
- Issue
- 1
- Pages
- 241-241
- ISSN
- 1754-6834 (ISSN-L)
- PMC
- PMC6124020
- OpenAlex
- W2892125910
- Cited by
- 84
- References
- 102
- Citations by year
- 2026: 5 · 2025: 19 · 2024: 8 · 2023: 9 · 2022: 10 · 2021: 16 · 2020: 10 · 2019: 7
- FWCI
- 0.81
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Biotechnology for Biofuels (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Greater South Information System
- Funders
- National Science Foundation (1332344, 1804187)
- U.S. Department of Energy (DOE), Office of Science, Office of Biological & Environmental Research (DE-SC0012658, DE-SC0018344)
- Gordon and Betty Moore Foundation (GBMF7000)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Microbial Metabolic Engineering and Bioproduction
- Physical Sciences › Energy › Renewable Energy, Sustainability and the Environment › Algal biology and biofuel production
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Biochemistry › Lipid metabolism and biosynthesis
- Keywords
- oleaginous microalgae, metabolic modeling, constraint-based modeling, genome-scale metabolic models, lipid production, biofuel production, central carbon metabolism, phototrophic microorganisms, culture condition optimization
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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