ArticlePLoS computational biology2019
Genome-scale model of metabolism and gene expression provides a multi-scale description of acid stress responses in Escherichia coli.
Article in PLoS computational biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
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Who cites it
28 citing papers in PubMed, 62 citations in OpenAlex.
- A proteome optimal allocation model for elucidating effects of temperature on bacterial growth.NPJ systems biology and applications · 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
- Genome-scale metabolic model-guided systematic framework for designing customized live biotherapeutic products.NPJ systems biology and applications · 2025Review
- Toehold Switch-Based Approach for Engineering Acid-Tolerance Modules to Enhance Production Robustness of Industrial E. coli Strains at Low pH.Microbial biotechnology · 2025Article
- A Multi-Omics, Machine Learning-Aware, Genome-Wide Metabolic Model of Bacillus Subtilis Refines the Gene Expression and Cell Growth Prediction.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
- Driving towards digital biomanufacturing by CHO genome-scale models.Trends in biotechnology · 2024Review
- Characterization of Mild Acid Stress Response in an Engineered Acid-TolerantMicroorganisms · 2024Article
- Current State, Challenges, and Opportunities in Genome-Scale Resource Allocation Models: A Mathematical Perspective.Metabolites · 2024Review
- Strategies to increase the robustness of microbial cell factories.Advanced biotechnology · 2024Review
- StressME: Unified computing framework of Escherichia coli metabolism, gene expression, and stress responses.PLoS computational biology · 2024Article
- Ribosome profiling reveals the fine-tuned response ofmSystems · 2023Article
- Laboratory evolution, transcriptomics, and modeling reveal mechanisms of paraquat tolerance.Cell reports · 2023Article
- Acid-tolerant bacteria and prospects in industrial and environmental applications.Applied microbiology and biotechnology · 2023Review
- Model-driven experimental design workflow expands understanding of regulatory role of Nac inNAR genomics and bioinformatics · 2023Article
- Towards applications of genome-scale metabolic model-based approaches in designing synthetic microbial communities.Quantitative biology (Beijing, China) · 2023Review
- Characterizing the Interplay of Rubisco and Nitrogenase Enzymes in Anaerobic-Photoheterotrophically Grown Rhodopseudomonas palustris CGA009 through a Genome-Scale Metabolic and Expression Model.Microbiology spectrum · 2022Article
- Construction of Multiscale Genome-Scale Metabolic Models: Frameworks and Challenges.Biomolecules · 2022Review
- Strategies to increase tolerance and robustness of industrial microorganisms.Synthetic and systems biotechnology · 2022Article
- Review
- The challenges and prospects of Escherichia coli as an organic acid production host under acid stress.Applied microbiology and biotechnology · 2021Review
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 2 countries.
Funding
Abstract
Response to acid stress is critical for Escherichia coli to successfully complete its life-cycle by passing through the stomach to colonize the digestive tract. To develop a fundamental understanding of this response, we established a molecular mechanistic description of acid stress mitigation responses in E. coli and integrated them with a genome-scale model of its metabolism and macromolecular expression (ME-model). We considered three known mechanisms of acid stress mitigation: 1) change in membrane lipid fatty acid composition, 2) change in periplasmic protein stability over external pH and periplasmic chaperone protection mechanisms, and 3) change in the activities of membrane proteins. After integrating these mechanisms into an established ME-model, we could simulate their responses in the context of other cellular processes. We validated these simulations using RNA sequencing data obtained from five E. coli strains grown under external pH ranging from 5.5 to 7.0. We found: i) that for the differentially expressed genes accounted for in the ME-model, 80% of the upregulated genes were correctly predicted by the ME-model, and ii) that these genes are mainly involved in translation processes (45% of genes), membrane proteins and related processes (18% of genes), amino acid metabolism (12% of genes), and cofactor and prosthetic group biosynthesis (8% of genes). We also demonstrated several intervention strategies on acid tolerance that can be simulated by the ME-model. We thus established a quantitative framework that describes, on a genome-scale, the acid stress mitigation response of E. coli that has both scientific and practical uses.
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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.