Network reduction in metabolic pathway analysis: Elucidation of the key pathways involved in the photoautotrophic growth of the green alga Chlamydomonas reinhardtii

Rügen, Marco; Bockmayr, Alexander; Legrand, Jack; Cogne, Guillaume

doi:10.1016/j.ymben.2012.01.009

Cited by 19 publications

(11 citation statements)

References 34 publications

(52 reference statements)

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“…Microalgae models exist for more than 60 years and can be divided into two main categories: dynamical macroscopic models (see [15] for a full review) and static metabolic models [17], [22], [24], [26], [52].…”

Section: Discussionmentioning

confidence: 99%

“…For metabolic models, only static flux predictions under constant light were made, where lipids and carbohydrates were at a constant ratio in biomass [17], [22], [24], [26], [52]. Even if, sometimes, the influence of light intensity on metabolic fluxes and biomass composition was studied [24], [52], only the recent model of Knoop et al [17] tried to simulate, thanks to dynamic flux balance analysis, the evolution of metabolic fluxes during a day/night cycle.…”

Section: Discussionmentioning

confidence: 99%

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DRUM: A New Framework for Metabolic Modeling under Non-Balanced Growth. Application to the Carbon Metabolism of Unicellular Microalgae

et al. 2014

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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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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

DRUM: A New Framework for Metabolic Modeling under Non-Balanced Growth. Application to the Carbon Metabolism of Unicellular Microalgae

et al. 2014

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“…Since light directly impacts microalgae growth and behavior, efforts have been made to define the quality and quantity of light constraints in metabolic models [29, 37]. Models can be significantly improved by considering a more realistic light uptake mechanism, since correctly defined constraints regarding light-driven reactions allow for the assessment of light influence on carbon allocation.…”

Section: Lessons Learned From Metabolic Modeling Of Oleaginous Phototmentioning

confidence: 99%

Advances in metabolic modeling of oleaginous microalgae

Tibocha‐Bonilla

Zuñiga

Godoy-Silva

et al. 2018

Biotechnol Biofuels

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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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“…For [38][39][40], the parameters to estimate were inherited by the use of Shastri et al [8] biomass equation, which includes a maintenance term. For [29], the parameters to estimate were inherited by the use of the model of Cogne et al [13]. For [11 ], seven biomass compositions were necessary to perform DFBA.…”

Section: Lessons From the Static Regimementioning

confidence: 99%

“…However given the high number of Elementary Flux Modes (EFMs) obtained from their metabolic network (around 30,000) [29], a reduction using experimental data may not be sufficient to use MBM [24]. HCM or LHCM also seems to present difficulties in obtaining a simple model with identifiable parameters.…”

Section: Towards a Dynamic Regimementioning

confidence: 99%

Mathematical modeling of unicellular microalgae and cyanobacteria metabolism for biofuel production

Baroukh

Muñoz-Tamayo

Bernard

et al. 2015

Current Opinion in Biotechnology

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Network reduction in metabolic pathway analysis: Elucidation of the key pathways involved in the photoautotrophic growth of the green alga Chlamydomonas reinhardtii

Cited by 19 publications

References 34 publications

DRUM: A New Framework for Metabolic Modeling under Non-Balanced Growth. Application to the Carbon Metabolism of Unicellular Microalgae

DRUM: A New Framework for Metabolic Modeling under Non-Balanced Growth. Application to the Carbon Metabolism of Unicellular Microalgae

Advances in metabolic modeling of oleaginous microalgae

Mathematical modeling of unicellular microalgae and cyanobacteria metabolism for biofuel production

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