ArticleScientific reports2015
Elucidating temporal resource allocation and diurnal dynamics in phototrophic metabolism using conditional FBA.
Article in Scientific reports, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed, 57 citations in OpenAlex.
- Charting the state of GEMs in microalgae: progress, challenges, and innovations.Frontiers in plant science · 2025Review
- Conditional flux balance analysis toolbox for python: application to research metabolism in cyclic environments.Bioinformatics advances · 2024Article
- Predicting Metabolic Adaptation Under Dynamic Substrate Conditions Using a Resource-Dependent Kinetic Model: A Case Study UsingFrontiers in molecular biosciences · 2022Article
- Time-Optimal Adaptation in Metabolic Network Models.Frontiers in molecular biosciences · 2022Article
- Protocol for hybrid flux balance, statistical, and machine learning analysis of multi-omic data from the cyanobacteriumSTAR protocols · 2021Article
- What is quantitative plant biology?Quantitative plant biology · 2021Review
- Dynamic Allocation of Carbon Storage and Nutrient-Dependent Exudation in a Revised Genome-Scale Model ofFrontiers in genetics · 2021Article
- Advances in flux balance analysis by integrating machine learning and mechanism-based models.Computational and structural biotechnology journal · 2021Review
- A Hybrid Flux Balance Analysis and Machine Learning Pipeline Elucidates Metabolic Adaptation in Cyanobacteria.iScience · 2020Article
- Alternative Crassulacean Acid Metabolism Modes Provide Environment-Specific Water-Saving Benefits in a Leaf Metabolic Model.The Plant cell · 2020Article
- Dynamic metabolic resource allocation based on the maximum entropy principle.Journal of mathematical biology · 2020Article
- Opportunities at the Interface of Network Science and Metabolic Modeling.Frontiers in bioengineering and biotechnology · 2020Review
- Modelling microbial communities using biochemical resource allocation analysis.Journal of the Royal Society, Interface · 2019Article
- Article
- DynamicME: dynamic simulation and refinement of integrated models of metabolism and protein expression.BMC systems biology · 2019Article
- A diurnal flux balance model of Synechocystis sp. PCC 6803 metabolism.PLoS computational biology · 2019Article
- Flux-dependent graphs for metabolic networks.NPJ systems biology and applications · 2018Article
- Engineering photosynthetic production of L-lysine.Metabolic engineering · 2017Article
- A Protocol for Generating and Exchanging (Genome-Scale) Metabolic Resource Allocation Models.Metabolites · 2017Article
- Cellular trade-offs and optimal resource allocation during cyanobacterial diurnal growth.Proceedings of the National Academy of Sciences of the United States of America · 2017Article
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The computational analysis of phototrophic growth using constraint-based optimization requires to go beyond current time-invariant implementations of flux-balance analysis (FBA). Phototrophic organisms, such as cyanobacteria, rely on harvesting the sun's energy for the conversion of atmospheric CO2 into organic carbon, hence their metabolism follows a strongly diurnal lifestyle. We describe the growth of cyanobacteria in a periodic environment using a new method called conditional FBA. Our approach enables us to incorporate the temporal organization and conditional dependencies into a constraint-based description of phototrophic metabolism. Specifically, we take into account that cellular processes require resources that are themselves products of metabolism. Phototrophic growth can therefore be formulated as a time-dependent linear optimization problem, such that optimal growth requires a differential allocation of resources during different times of the day. Conditional FBA then allows us to simulate phototrophic growth of an average cell in an environment with varying light intensity, resulting in dynamic time-courses for all involved reaction fluxes, as well as changes in biomass composition over a diurnal cycle. Our results are in good agreement with several known facts about the temporal organization of phototrophic growth and have implications for further analysis of resource allocation problems in phototrophic metabolism.
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