ArticleNature communications2018
Statistical mechanics for metabolic networks during steady state growth.
Article in Nature communications, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed.
- Flux sampling and context-specific genome-scale metabolic models for biotechnological applications.Trends in biotechnology · 2026Review
- Cross-feeding percolation phase transitions of intercellular metabolic networks.Science advances · 2025Article
- Predicting the Rate Structure of an Evolved Metabolic Network.Metabolites · 2025Article
- Metabolic Objectives and Trade-Offs: Inference and Applications.Metabolites · 2025Review
- Control Theory and Systems Biology: Potential Applications in Neurodegeneration and Search for Therapeutic Targets.International journal of molecular sciences · 2023Review
- COVRECON: automated integration of genome- and metabolome-scale network reconstruction and data-driven inverse modeling of metabolic interaction networks.Bioinformatics (Oxford, England) · 2023Article
- Article
- Probing Single-Cell Fermentation Fluxes and Exchange Networks via pH-Sensing Hybrid Nanofibers.ACS nano · 2023Article
- Inference of metabolic fluxes in nutrient-limited continuous cultures: A Maximum Entropy approach with the minimum information.iScience · 2022Article
- Relationship between fitness and heterogeneity in exponentially growing microbial populations.Biophysical journal · 2022Article
- Learning the distribution of single-cell chromosome conformations in bacteria reveals emergent order across genomic scales.Nature communications · 2021Article
- Addressing uncertainty in genome-scale metabolic model reconstruction and analysis.Genome biology · 2021Review
- Cooperative metabolic resource allocation in spatially-structured systems.Journal of mathematical biology · 2021Article
- Information Theory in Computational Biology: Where We Stand Today.Entropy (Basel, Switzerland) · 2020Article
- Dynamic metabolic resource allocation based on the maximum entropy principle.Journal of mathematical biology · 2020Article
- The common message of constraint-based optimization approaches: overflow metabolism is caused by two growth-limiting constraints.Cellular and molecular life sciences : CMLS · 2020Review
- Article
- Predicting the decision making chemicals used for bacterial growth.Scientific reports · 2019Article
- Maximum entropy and population heterogeneity in continuous cell cultures.PLoS computational biology · 2019Article
- An introduction to the maximum entropy approach and its application to inference problems in biology.Heliyon · 2018Review
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Which properties of metabolic networks can be derived solely from stoichiometry? Predictive results have been obtained by flux balance analysis (FBA), by postulating that cells set metabolic fluxes to maximize growth rate. Here we consider a generalization of FBA to single-cell level using maximum entropy modeling, which we extend and test experimentally. Specifically, we define for Escherichia coli metabolism a flux distribution that yields the experimental growth rate: the model, containing FBA as a limit, provides a better match to measured fluxes and it makes a wide range of predictions: on flux variability, regulation, and correlations; on the relative importance of stoichiometry vs. optimization; on scaling relations for growth rate distributions. We validate the latter here with single-cell data at different sub-inhibitory antibiotic concentrations. The model quantifies growth optimization as emerging from the interplay of competitive dynamics in the population and regulation of metabolism at the level of single cells.
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Registered trials
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