Escherichia coli remains the premier microbial chassis in industrial biotechnology; yet, translating laboratory-scale metabolic successes into robust, hundred-ton-scale manufacturing presents persistent multidimensional bottlenecks. This review systematically elucidates a contemporary paradigm shift in E. coli fermentation regulation, transitioning from isolated, empirical process adjustments to cross-scale, deeply coupled intelligent cybernetic frameworks. We first deconstruct the precise cross-scale links between macroscopic physicochemical parameters and intracellular biological regulatory networks, detailing how fluctuations in temperature, pH, and dissolved oxygen fundamentally reshape intracellular molecular cascades alongside transmembrane proton motive forces. To mitigate spatial heterogeneity, substrate mixing delays, and carbon catabolite repression common in large-volume bioreactors, we comprehensively evaluate advanced mitigation strategies that integrate process-level model predictive control (MPC) with dynamic synthetic biology circuits, including quorum-sensing-based growth-production decoupling, metabolite-responsive feedback loops, and optogenetic switches. Critically, we highlight the convergence of multi-scale modeling and digital twins as a frontier simulation-driven tool, which dynamically couples computational fluid dynamics (CFD) with genome-scale metabolic models (GEMs) to render the industrial fermentation "black box" transparent. Finally, we outline the evolutionary trajectory of E. coli biomanufacturing toward a digitized, intelligent, and sustainable paradigm, leveraging low-carbon C1 feedstocks and paving the way for next-generation green biomanufacturing.
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