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<p>This study employs a generalized logistic model to resolve the complete growth kinetics of <i>Escherichia coli</i> under varying temperatures (29–45&#xa0;°C) and glucose concentrations (0.1–2.0% w/v). The model quantifies critical growth parameters, including the characteristic time <i>t</i><sub><i>cL</i></sub>, symmetry factor <i>τ</i> (glucose-dependent), and peak growth rate (temperature-dominated). It identifies a lower thermal growth limit between 15&#xa0;°C and 20&#xa0;°C, which is consistent with membrane phase transition and impaired translation, undetectable by classical exponential approaches. Doubling times at maximum growth rate align with literature values, validating the framework’s predictive accuracy. Crucially, glucose modulates growth symmetry (reducing <i>τ</i> by 2.6-fold at saturating concentrations) and temperature governs maximum rates (yielding a 2.4-fold increase in <i>b</i>), enabling precise microbial community control. This parametric separation offers actionable strategies for enhancing beneficial strains (e.g., probiotics, bioremediation agents) and suppressing pathogens in wastewater treatment, fermentation, and biofilm biocontrol. By decoupling the thermodynamic drivers of growth—where temperature governs the rate factor b (linked to catalytic kinetics) and substrate availability governs the asymmetry parameter τ (reflecting population-level energy allocation)—our model provides a generalizable framework for predicting cellular responses in biomedical contexts, such as bacterial infection dynamics or cancer cell proliferation under metabolic stress.</p>

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A logistic model for glucose‑driven asymmetry in multi‑phase E. coli growth kinetics

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月27日

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  • María-Isabel González-Siso,
  • Manuel Becerra,
  • Daniel Torrecilla,
  • Ana-María Díaz-Díaz,
  • Jorge López-Beceiro,
  • Ramón Artiaga

摘要

This study employs a generalized logistic model to resolve the complete growth kinetics of Escherichia coli under varying temperatures (29–45 °C) and glucose concentrations (0.1–2.0% w/v). The model quantifies critical growth parameters, including the characteristic time tcL, symmetry factor τ (glucose-dependent), and peak growth rate (temperature-dominated). It identifies a lower thermal growth limit between 15 °C and 20 °C, which is consistent with membrane phase transition and impaired translation, undetectable by classical exponential approaches. Doubling times at maximum growth rate align with literature values, validating the framework’s predictive accuracy. Crucially, glucose modulates growth symmetry (reducing τ by 2.6-fold at saturating concentrations) and temperature governs maximum rates (yielding a 2.4-fold increase in b), enabling precise microbial community control. This parametric separation offers actionable strategies for enhancing beneficial strains (e.g., probiotics, bioremediation agents) and suppressing pathogens in wastewater treatment, fermentation, and biofilm biocontrol. By decoupling the thermodynamic drivers of growth—where temperature governs the rate factor b (linked to catalytic kinetics) and substrate availability governs the asymmetry parameter τ (reflecting population-level energy allocation)—our model provides a generalizable framework for predicting cellular responses in biomedical contexts, such as bacterial infection dynamics or cancer cell proliferation under metabolic stress.