ArticlePLoS computational biology2024
StressME: Unified computing framework of Escherichia coli metabolism, gene expression, and stress responses.
Article in PLoS computational biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 16 citations in OpenAlex.
- Selection favors cost-ordered adaptive mutational paths in a stress-magnitude-dependent manner.EMBO reports · 2026Article
- A short peptide derived from late embryogenesis abundant proteins enhances acid tolerance in Escherichia coli via modulation of two-component regulatory systems.The FEBS journal · 2026Article
- QSProteome: a community-driven interactive platform for large-scale exploration and evaluation of predicted protein complex structures.Nucleic acids research · 2026Article
- Analysis of metabolic stability under environmental perturbations using a kinetic model.Biophysics and physicobiology · 2026Article
- The Dawn of High-Throughput and Genome-Scale Kinetic Modeling: Recent Advances and Future Directions.ACS synthetic biology · 2025Review
- Transcriptomic insights into slyA-mediated regulation of motility and secretion in Escherichia coli.Antonie van Leeuwenhoek · 2025Article
- Genome-scale metabolic model-guided systematic framework for designing customized live biotherapeutic products.NPJ systems biology and applications · 2025Review
- Model of metabolism and gene expression predicts proteome allocation in Pseudomonas putida.NPJ systems biology and applications · 2025Article
- Seasonal and environmental drivers of antibiotic resistance and virulence in Escherichia coli from aquaculture and their public health implications.Scientific reports · 2025Article
- Current State, Challenges, and Opportunities in Genome-Scale Resource Allocation Models: A Mathematical Perspective.Metabolites · 2024Review
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
Abstract
Generalist microbes have adapted to a multitude of environmental stresses through their integrated stress response system. Individual stress responses have been quantified by E. coli metabolism and expression (ME) models under thermal, oxidative and acid stress, respectively. However, the systematic quantification of cross-stress & cross-talk among these stress responses remains lacking. Here, we present StressME: the unified stress response model of E. coli combining thermal (FoldME), oxidative (OxidizeME) and acid (AcidifyME) stress responses. StressME is the most up to date ME model for E. coli and it reproduces all published single-stress ME models. Additionally, it includes refined rate constants to improve prediction accuracy for wild-type and stress-evolved strains. StressME revealed certain optimal proteome allocation strategies associated with cross-stress and cross-talk responses. These stress-optimal proteomes were shaped by trade-offs between protective vs. metabolic enzymes; cytoplasmic vs. periplasmic chaperones; and expression of stress-specific proteins. As StressME is tuned to compute metabolic and gene expression responses under mild acid, oxidative, and thermal stresses, it is useful for engineering and health applications. The modular design of our open-source package also facilitates model expansion (e.g., to new stress mechanisms) by the computational biology community.
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Registered trials
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.