ArticleNature2017
A global resource allocation strategy governs growth transition kinetics of Escherichia coli.
Article in Nature, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 127 papers.
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Who cites it
127 citing papers in PubMed.
- Fluorescent proteins misreport ribosome abundance under translation inhibition.bioRxiv : the preprint server for biology · 2026Article
- Coarse-grained resource allocation modeling for decoding and rewiring microbial metabolism.Trends in microbiology · 2026Review
- Enzyme kinetics shapes the growth response of metabolic networks.PLoS computational biology · 2026Article
- A systems-level atlas of carbon-response transcriptional states inProceedings of the National Academy of Sciences of the United States of America · 2026Article
- Fitness advantage of sequential metabolic strategies emerges from community interactions in strongly fluctuating environments.PLoS computational biology · 2026Article
- Physiological architecture and evolutionary origins of cellular adaptability.bioRxiv : the preprint server for biology · 2026Article
- A proteome optimal allocation model for elucidating effects of temperature on bacterial growth.NPJ systems biology and applications · 2026Article
- Inferring bacterial cell size dynamics across media conditions.Scientific reports · 2026Article
- Probing the proteome.eLife · 2026Article
- Quantitative Coarse-Grained Modeling of Microbial Metabolism: Uncovering Growth Laws, Environmental Responses, and Host-Circuit Coupling.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Dynamic Constrained Allocation Flux Balance Analysis (dCAFBA).Methods in molecular biology (Clifton, N.J.) · 2026Article
- Maintenance of cytoplasmic and membrane densities shapes cellular geometry in Escherichia coli.Nature communications · 2025Article
- Stand Density Drives Soil Microbial Community Structure in Response to Nutrient Availability inPlants (Basel, Switzerland) · 2025Article
- Soil Nutrient Enrichment Induces Trade-Offs in Bacterial Life-History Strategies Promoting Plant Productivity.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Glyceraldehyde-3-phosphate dehydrogenase homologs as bifunctional gatekeepers of metabolic segregation inProceedings of the National Academy of Sciences of the United States of America · 2025Article
- Comparative transcriptomic analysis of perfluoroalkyl substances-induced responses of exponential and stationary phase Escherichia coli.BMC genomics · 2025Article
- GBA Solver: a user-friendly web server for growth balance analysis.Bioinformatics (Oxford, England) · 2025Article
- Gene expression cycles drive non-exponential bacterial growth.Physical review research · 2025Article
- Cell Geometry Limits Bacterial Metabolic Efficiency.bioRxiv : the preprint server for biology · 2025Article
- Minimization of proteome reallocation explains metabolic transition in hierarchical utilization of carbon sources.mSystems · 2025Article
67 more citing papers are in PubMed but not listed here.
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6 authors.
Funding
Abstract
A grand challenge of systems biology is to predict the kinetic responses of living systems to perturbations starting from the underlying molecular interactions. Changes in the nutrient environment have long been used to study regulation and adaptation phenomena in microorganisms and they remain a topic of active investigation. Although much is known about the molecular interactions that govern the regulation of key metabolic processes in response to applied perturbations, they are insufficiently quantified for predictive bottom-up modelling. Here we develop a top-down approach, expanding the recently established coarse-grained proteome allocation models from steady-state growth into the kinetic regime. Using only qualitative knowledge of the underlying regulatory processes and imposing the condition of flux balance, we derive a quantitative model of bacterial growth transitions that is independent of inaccessible kinetic parameters. The resulting flux-controlled regulation model accurately predicts the time course of gene expression and biomass accumulation in response to carbon upshifts and downshifts (for example, diauxic shifts) without adjustable parameters. As predicted by the model and validated by quantitative proteomics, cells exhibit suboptimal recovery kinetics in response to nutrient shifts owing to a rigid strategy of protein synthesis allocation, which is not directed towards alleviating specific metabolic bottlenecks. Our approach does not rely on kinetic parameters, and therefore points to a theoretical framework for describing a broad range of such kinetic processes without detailed knowledge of the underlying biochemical reactions.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.