ArticleScientific reports2016
Principles of proteome allocation are revealed using proteomic data and genome-scale models.
Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- Bacterial cell size modulation along the growth curve across nutrient conditions.bioRxiv : the preprint server for biology · 2024Article
- Proteome allocation is linked to transcriptional regulation through a modularized transcriptome.Nature communications · 2024Article
- StressME: Unified computing framework of Escherichia coli metabolism, gene expression, and stress responses.PLoS computational biology · 2024Article
- Design and thermodynamic analysis of a pathway enabling anaerobic production of poly-3-hydroxybutyrate inSynthetic and systems biotechnology · 2023Article
- Proteome allocation is linked to transcriptional regulation through a modularized transcriptome.bioRxiv : the preprint server for biology · 2023Article
- Reconstruction of a catalogue of genome-scale metabolic models with enzymatic constraints using GECKO 2.0.Nature communications · 2022Article
- Elementary vectors and autocatalytic sets for resource allocation in next-generation models of cellular growth.PLoS computational biology · 2022Article
- Global pleiotropic effects in adaptively evolvedOpen biology · 2022Article
- Proteome Regulation Patterns Determine Escherichia coli Wild-Type and Mutant Phenotypes.mSystems · 2021Article
- A quantitative method for proteome reallocation using minimal regulatory interventions.Nature chemical biology · 2020Article
- Review
- Metabolic Modelling as a Framework for Metabolomics Data Integration and Analysis.Metabolites · 2020Review
- Genome-scale model of metabolism and gene expression provides a multi-scale description of acid stress responses in Escherichia coli.PLoS computational biology · 2019Article
- Machine and deep learning meet genome-scale metabolic modeling.PLoS computational biology · 2019Review
- DynamicME: dynamic simulation and refinement of integrated models of metabolism and protein expression.BMC systems biology · 2019Article
- Modeling the multi-scale mechanisms of macromolecular resource allocation.Current opinion in microbiology · 2018Review
- 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
- Resource allocation in mammalian systems.Biotechnology advancesReview
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Integrating omics data to refine or make context-specific models is an active field of constraint-based modeling. Proteomics now cover over 95% of the Escherichia coli proteome by mass. Genome-scale models of Metabolism and macromolecular Expression (ME) compute proteome allocation linked to metabolism and fitness. Using proteomics data, we formulated allocation constraints for key proteome sectors in the ME model. The resulting calibrated model effectively computed the "generalist" (wild-type) E. coli proteome and phenotype across diverse growth environments. Across 15 growth conditions, prediction errors for growth rate and metabolic fluxes were 69% and 14% lower, respectively. The sector-constrained ME model thus represents a generalist ME model reflecting both growth rate maximization and "hedging" against uncertain environments and stresses, as indicated by significant enrichment of these sectors for the general stress response sigma factor σ
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