DRUM: A new framework for metabolic modeling under non-balanced growth. Application to the carbon metabolism of unicellular microalgae
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Metabolic modeling is a powerful tool to understand, predict and optimize bioprocesses, particularly when they imply intracellular molecules of interest. Unfortunately, the use of metabolic models for time varying metabolic fluxes is hampered by the lack of experimental data required to define and calibrate the kinetic reaction rates of the metabolic pathways. For this reason, metabolic models are often used under the balanced growth hypothesis. However, for some processes such as the photoautotrophic metabolism of microalgae, the balanced-growth assumption appears to be unreasonable because of the synchronization of their circadian cycle on the daily light. Yet, understanding microalgae metabolism is necessary to optimize the production yield of bioprocesses based on this microorganism, as for example production of third-generation biofuels. In this paper, we propose DRUM, a new dynamic metabolic modeling framework that handles the non-balanced growth condition and hence accumulation of intracellular metabolites. The first stage of the approach consists in splitting the metabolic network into sub-networks describing reactions which are spatially close, and which are assumed to satisfy balanced growth condition. The left metabolites interconnecting the sub-networks behave dynamically. Then, thanks to Elementary Flux Mode analysis, each sub-network is reduced to macroscopic reactions, for which simple kinetics are assumed. Finally, an Ordinary Differential Equation system is obtained to describe substrate consumption, biomass production, products excretion and accumulation of some internal metabolites. DRUM was applied to the accumulation of lipids and carbohydrates of the microalgae Tisochrysis lutea under day/night cycles. The resulting model describes accurately experimental data obtained in day/night conditions. It efficiently predicts the accumulation and consumption of lipids and carbohydrates.
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Since COBRA approaches mainly operate at steady-state, dynamic frameworks will need to be adapted to account for dynamic fluctuations within the rumen environment.
“Moreover, since COBRA approaches mainly operates at steady-state, dynamic frameworks (Mahadevan et al., 2002; Baroukh et al., 2014) will need to be adapted to account for the dynamic fluctuations within the rumen environment.”
From Addressing global ruminant agricultural challenges through understanding the rumen microbiome: past, present, and future (2018) · cites this paper as Baroukh et al., 2014
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- Authors
- Baroukh, C., Muñoz-Tamayo, R., Steyer, J.-P., & Bernard, O.
- Affiliations
- Institut national de recherche en sciences et technologies du numérique (FR)
- Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement (FR)
- Corresponding author
- Baroukh, Caroline
- Venue
- PLoS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2014-08-08
- Volume
- 9
- Issue
- 8
- Pages
- e104499
- ISSN
- 1932-6203 (ISSN-L)
- PMC
- PMC4126706
- OpenAlex
- W2042444504
- Cited by
- 80
- References
- 80
- Citations by year
- 2026: 2 · 2025: 4 · 2024: 6 · 2023: 7 · 2022: 5 · 2021: 8 · 2020: 8 · 2019: 7 · 2018: 9 · 2017: 5 · 2016: 14 · 2015: 3 · 2014: 1
- FWCI
- 3.15
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- PLoS ONE (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- HAL (submittedVersion, other-oa)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Figshare (submittedVersion, cc-by)
- Funders
- Institut national de recherche en informatique et en automatique (INRIA)
- Agence Nationale de la Recherche (ANR-12-BIME-0004, ANR-13-BIME-0004)
- Institut National de la Recherche Agronomique
- 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 › Molecular Biology › Gene Regulatory Network Analysis
- Keywords
- dynamic metabolic modeling, elementary flux modes, Tisochrysis lutea, diurnal cycle, circadian rhythm, lipid accumulation, carbohydrate accumulation, ordinary differential equations, third-generation biofuels
- MeSH terms
- Algorithms, Computer Simulation, Models, Biological, Biomass, Metabolic Networks and Pathways, Microalgae
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